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Review Article DEMATEL Technique: A Systematic Review of the State-of-the-Art Literature on Methodologies and Applications Sheng-Li Si, 1 Xiao-Yue You, 1,2 Hu-Chen Liu , 3 and Ping Zhang 1,3 1 School of Economics and Management, Tongji University, Shanghai 200092, China 2 Institute for Manufacturing, University of Cambridge, Cambridge CB3 0FS, UK 3 School of Management, Shanghai University, Shanghai 200444, China Correspondence should be addressed to Hu-Chen Liu; [email protected] Received 8 October 2017; Accepted 14 December 2017; Published 14 January 2018 Academic Editor: Marco Pizzarelli Copyright © 2018 Sheng-Li Si et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Decision making trial and evaluation laboratory (DEMATEL) is considered as an effective method for the identification of cause- effect chain components of a complex system. It deals with evaluating interdependent relationships among factors and finding the critical ones through a visual structural model. Over the recent decade, a large number of studies have been done on the application of DEMATEL and many different variants have been put forward in the literature. e objective of this study is to review systematically the methodologies and applications of the DEMATEL technique. We reviewed a total of 346 papers published from 2006 to 2016 in the international journals. According to the approaches used, these publications are grouped into five categories: classical DEMATEL, fuzzy DEMATEL, grey DEMATEL, analytical network process- (ANP-) DEMATEL, and other DEMATEL. All papers with respect to each category are summarized and analyzed, pointing out their implementing procedures, real applications, and crucial findings. is systematic and comprehensive review holds valuable insights for researchers and practitioners into using the DEMATEL in terms of indicating current research trends and potential directions for further research. 1. Introduction Decision making trial and evaluation laboratory (DEMA- TEL) technique was first developed by the Geneva Research Centre of the Battelle Memorial Institute to visualize the structure of complicated causal relationships through matrixes or digraphs [1]. As a kind of structural modeling approach, it is especially useful in analyzing the cause and effect relationships among components of a system. e DEMATEL can confirm interdependence among factors and aid in the development of a map to reflect relative relation- ships within them and can be used for investigating and solving complicated and intertwined problems. is method not only converts the interdependency relationships into a cause and effect group via matrixes but also finds the critical factors of a complex structure system with the help of an impact relation diagram. Due to its advantages and capabilities, the approach of DEMATEL has received a great deal of attention in the past decade and many researchers have applied it for solving complicated system problems in various areas. In addition, the DEMATEL has been extended for better decision making under different environments since many real-world systems include imprecise and uncertain information. However, to the best of our knowledge, no systematic review has been performed for the DEMATEL technique and its applications. erefore, in this study, we present a comprehensive review of the state-of-the-art literature regarding the approaches to decision making based on the DEMATEL. As a result of search using the Scopus database and following a method- ological decision analysis, a total of 346 papers published in scientific journals from 2006 to 2016 were reviewed in detail. Based on the selected articles, the main objectives of this review are as follows: (1) to summarize the DEMATEL methods that have been used in the academic literature, (2) to reveal the different usage and application areas of these approaches, (3) to show the current research trends in this field of study, and (4) to find out the potential research directions in the future. Hindawi Mathematical Problems in Engineering Volume 2018, Article ID 3696457, 33 pages https://doi.org/10.1155/2018/3696457

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Page 1: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

Review ArticleDEMATEL Technique A Systematic Review of theState-of-the-Art Literature on Methodologies and Applications

Sheng-Li Si1 Xiao-Yue You12 Hu-Chen Liu 3 and Ping Zhang13

1School of Economics and Management Tongji University Shanghai 200092 China2Institute for Manufacturing University of Cambridge Cambridge CB3 0FS UK3School of Management Shanghai University Shanghai 200444 China

Correspondence should be addressed to Hu-Chen Liu huchenliushueducn

Received 8 October 2017 Accepted 14 December 2017 Published 14 January 2018

Academic Editor Marco Pizzarelli

Copyright copy 2018 Sheng-Li Si et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Decision making trial and evaluation laboratory (DEMATEL) is considered as an effective method for the identification of cause-effect chain components of a complex system It deals with evaluating interdependent relationships among factors and findingthe critical ones through a visual structural model Over the recent decade a large number of studies have been done on theapplication of DEMATEL andmany different variants have been put forward in the literatureThe objective of this study is to reviewsystematically the methodologies and applications of the DEMATEL technique We reviewed a total of 346 papers published from2006 to 2016 in the international journals According to the approaches used these publications are grouped into five categoriesclassical DEMATEL fuzzyDEMATEL greyDEMATEL analytical network process- (ANP-)DEMATEL and otherDEMATEL Allpapers with respect to each category are summarized and analyzed pointing out their implementing procedures real applicationsand crucial findingsThis systematic and comprehensive review holds valuable insights for researchers and practitioners into usingthe DEMATEL in terms of indicating current research trends and potential directions for further research

1 Introduction

Decision making trial and evaluation laboratory (DEMA-TEL) technique was first developed by the Geneva ResearchCentre of the Battelle Memorial Institute to visualizethe structure of complicated causal relationships throughmatrixes or digraphs [1] As a kind of structural modelingapproach it is especially useful in analyzing the cause andeffect relationships among components of a system TheDEMATEL can confirm interdependence among factors andaid in the development of a map to reflect relative relation-ships within them and can be used for investigating andsolving complicated and intertwined problems This methodnot only converts the interdependency relationships into acause and effect group via matrixes but also finds the criticalfactors of a complex structure system with the help of animpact relation diagram

Due to its advantages and capabilities the approach ofDEMATEL has received a great deal of attention in the pastdecade and many researchers have applied it for solving

complicated system problems in various areas In additionthe DEMATEL has been extended for better decisionmakingunder different environments since many real-world systemsinclude imprecise and uncertain information However tothe best of our knowledge no systematic review has beenperformed for the DEMATEL technique and its applicationsTherefore in this study we present a comprehensive reviewof the state-of-the-art literature regarding the approaches todecision making based on the DEMATEL As a result ofsearch using the Scopus database and following a method-ological decision analysis a total of 346 papers publishedin scientific journals from 2006 to 2016 were reviewed indetail Based on the selected articles the main objectives ofthis review are as follows (1) to summarize the DEMATELmethods that have been used in the academic literature (2)to reveal the different usage and application areas of theseapproaches (3) to show the current research trends in thisfield of study and (4) to find out the potential researchdirections in the future

HindawiMathematical Problems in EngineeringVolume 2018 Article ID 3696457 33 pageshttpsdoiorg10115520183696457

2 Mathematical Problems in Engineering

The remaining part of this paper is structured as followsIn Section 2 we introduce the research methodology used toidentify and refine the literature in this study In Section 3detailed reviews of each category of the DEMATEL studiesare presented Section 4 describes some general observationsand findings based on statistical analysis results of thereview Finally this paper concludes in Section 5 by sum-marizing the results and discussing opportunities for futureresearch

2 Research Methodology

For the purpose of this literature review we searched forarticles in the Scopus database published between 2006 and2016 The choice of this time period is based on the factthat the majority of papers on this topic were publishedduring this period and there are only five articles recordedin the Scopus prior to 2006 Inspired by the PreferredReporting Items for Systematic Reviews and Meta-Analyses(PRISRMA) method [2 3] the selection of articles in thisstudy is consisted of three stages that is literature searcharticles eligibility and data extraction and summarizingFirst the keyword ldquoDEMATELrdquo was used for searching inldquoabstract title and keywordsrdquo for journal papers and atotal of 509 document results were identified from ScopusNext we chose the articles which had used the DEMATELtechnique or its extensions to solve real-world problemsand 346 academic papers fell under the scope of this reviewafter title abstract and full-text screening Since this studyfocuses on both the DEMATEL and its applications thosestudies which only modify the DEMATEL technique withoutapplying to actual settings have been eliminated (for theinterested readers please refer eg to [4ndash6]) Finally theresulting papers were reviewed thoroughly to identify thefocus method application and combination with othermethods Also articles were summarized based on variouscriteria such as year of publication application areas andcitations

Based on the DEMATEL methods adopted the selectedpublications are roughly grouped into five categories the onesusing classical DEMATEL (105 articles) the ones using fuzzyDEMATEL (63 articles) the ones using grey DEMATEL(12 articles) the ones combining analytical network process(ANP) and DEMATEL (154 articles) and the ones basedon other DEMATEL methods (12 articles) The classificationscheme of the DEMATEL articles is shown in Figure 1Most of the papers on ANP and DEMATEL hybridizationare included in a review paper of DEMATEL approachesfor criteria interaction handling with ANP by Golcuk andBaykasoglu [7] Therefore in the following sections wewill not discuss the studies which apply the DEMATELin conjunction with ANP to deal with interactions amongcriteria

3 Reviews of DEMATEL Methods

31 The Classical DEMATEL As stated earlier the DEMA-TEL technique can convert the interrelations between factors

Classical DEMATEL303

Fuzzy DEMATEL 182

ANP and DEMATEL445

Grey DEMATEL35

Other DEMATEL 35

Figure 1 Classification scheme of the DEMATEL articles

into an intelligible structural model of the system and dividethem into a cause group and an effect group [8] Hence it isan applicable and useful tool to analyze the interdependentrelationships among factors in a complex system and rankthem for long-term strategic decision making and indicatingimprovement scopes The formulating steps of the classicalDEMATEL can be summarized as follows [8ndash10]

Step 1 (generate the group direct-influence matrix 119885) Toassess the relationships between 119899 factors 119865 = 1198651 1198652 119865119899in a system suppose that 119897 experts in a decision group 119864 =1198641 1198642 119864119897 are asked to indicate the direct influence thatfactor 119865119894 has on factor 119865119895 using an integer scale of ldquonoinfluence (0)rdquo ldquolow influence (1)rdquo ldquomedium influence (2)rdquoldquohigh influence (3)rdquo and ldquovery high influence (4)rdquo Then theindividual direct-influence matrix 119885119896 = [119911119896119894119895]119899times119899 provided bythe 119896th expert can be formed where all principal diagonalelements are equal to zero and 119911119896119894119895 represents the judgmentof decision maker 119864119896 on the degree to which factor 119865119894 affectsfactor 119865119895 By aggregating the 119897 expertsrsquo opinions the groupdirect-influence matrix 119885 = [119911119894119895]119899times119899 can be obtained by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 119894 119895 = 1 2 119899 (1)

Step 2 (establish the normalized direct-influence matrix 119883)When the group direct-influence matrix 119885 is acquired thenormalized direct-influence matrix 119883 = [119909119894119895]119899times119899 can beachieved by using

119883 = 119885119904 (2)

119904 = max(max1le119894le119899

119899sum119895=1

119911119894119895max1le119894le119899

119899sum119894=1

119911119894119895) (3)

Mathematical Problems in Engineering 3

All elements in the matrix 119883 are complying with 0 le 119909119894119895 lt1 0 le sum119899119895=1 119909119894119895 le 1 and at least one 119894 such that sum119899119895=1 119911119894119895 le 119904Step 3 (construct the total-influence matrix 119879) Using thenormalized direct-influence matrix 119883 the total-influencematrix 119879 = [119905119894119895]119899times119899 is then computed by summing the directeffects and all of the indirect effects by

119879 = 119883 + 1198832 + 1198833 + sdot sdot sdot + 119883ℎ = 119883 (119868 minus 119883)minus1 when ℎ 997888rarr infin (4)

in which 119868 is denoted as an identity matrix

Step 4 (produce the influential relation map (IRM)) At thisstep the vectors 119877 and 119862 representing the sum of the rowsand the sum of the columns from the total-influence matrix119879 are defined by the following formulas

119877 = [119903119894]119899times1 = [[119899sum119895=1

119905119894119895]]119899times1

119862 = [119888119895]1times119899 = [119899sum119894=1

119905119894119895]119879

1times119899

(5)

where 119903119894 is the 119894th row sum in the matrix 119879 and displays thesum of the direct and indirect effects dispatching from factor119865119894 to the other factors Similarly 119888119895 is the 119895th column sum inthematrix119879 and depicts the sum of direct and indirect effectsthat factor 119865119895 is receiving from the other factors

Let 119894 = 119895 and 119894 119895 isin 1 2 119899 the horizontal axisvector (119877 + 119862) named ldquoProminencerdquo illustrates the strengthof influences that are given and received of the factor Thatis (119877 + 119862) stands for the degree of central role that the factorplays in the systemAlike the vertical axis vector (119877minus119862) calledldquoRelationrdquo shows the net effect that the factor contributes tothe system If (119903119895 minus 119888119895) is positive then the factor 119865119895 has anet influence on the other factors and can be grouped intocause group if (119903119895 minus 119888119895) is negative then the factor 119865119895 is beinginfluenced by the other factors on the whole and should begrouped into effect group Finally an IRM can be created bymapping the dataset of (119877+119862119877minus119862) which provides valuableinsights for decision making

311 Observations and Findings Table 1 summarizes all theclassical DEMATEL studies based on the particular purposeof using DEMATEL the topic of decision making andother methods combined According to the distinct usageof the DEMATEL method the current classical DEMATELresearches can be classified into three types the first typeis merely clarifying the interrelationships between factors orcriteria the second type is identifying key factors based onthe causal relationships and the degrees of interrelationshipbetween them the third type is determining criteria weightsby analyzing the interrelationships and impact levels ofcriteria

In Table 1 we have provided an overview on the existingapplications of the classical DEMATEL for solving compli-cated and intertwined problems in many fields based onwhich we now point out some critical steps added to theoriginal approach

Step 4-1 (set a threshold value to draw the IRM) In the abovethe IRM is constructed based on the information from thematrix 119879 to explain the structure relations of factors But insome situations the IRM will be too complex to show thevaluable information for decision making if all the relationsare considered Therefore a threshold value 120579 is set in manystudies to filter out negligible effectsThat is only the elementof matrix 119879 whose influence level is greater than the value of120579 is selected and converted into an IRM

If the threshold value is too lowmany factors are includedand the IRMwill be too complex to comprehend In contrastsome important factors may be excluded if the thresholdvalue is too high In the literature the threshold value 120579 isusually determined by experts through discussions [10 11]the results of literature review the brainstorming technique[12] the maximum mean deentropy (MMDE) [13] theaverage of all elements in the matrix 119879 [14] or the maximumvalue of the diagonal elements of the matrix 119879 [15]

Step 4-2 (obtain the inner dependence matrix 1198791015840) When thetotal-influence matrix 119879 is produced in [16 17] an innerdependence matrix 1198791015840 is acquired by normalizing the matrix119879 so that each column sum is equal to 1 But in [18] the innerdependencematrix1198791015840 is derived based on the threshold value120579 and only the factors whose effects in the matrix 119879 are largerthan 120579 are shown in the matrix 1198791015840

To interpret the results easily and keep the complexity ofthe system manageable Tzeng [19] established a simplifiednormalized total-influence matrix 119904 using a normalizationmethod and the threshold value 120579 First the normalized total-influencematrix = [119894119895]119899times119899 is calculated by using (6) to forcethe values of the matrix 119879within the scope of a measurementscale

119894119895 = (119896 minus 0) (119905119894119895 minusmin 119905119894119895)max 119905119894119895 minusmin 119905119894119895 (6)

where 119896 is the highest score for measuring the degree ofrelative impact between factors and 119896 = 4 if the integralscale of 0 to 4 is used Then the simplified normalized total-influence matrix 119904 = [119904119894119895]119899times119899 is obtained by eliminatinginsignificant effects in the matrix based on the thresholdvalue 120579 That is

119904119894119895 = 119894119895 if 119894119895 gt 1205790 if 119894119895 le 120579 (7)

Step 4-21015840 (divide the IRM into four quadrants) Once an IRMis acquired eight of the classical DEMATEL studies classifiedthe factors in a complicated system into four quadrantsaccording to their locations in the diagram In [20ndash22] theIRM is divided into four quadrants I to IV as displayed in

4 Mathematical Problems in Engineering

Table1Va

rious

applications

ofthec

lassicalDEM

ATEL

Papers

Research

purposes

Com

binatio

nsRe

marks

Type

1interrelationships

BEfea

ndOFE

fe[42]

Specify

theinfl

uenced

egrees

ofthep

atient

perceivedvalues

whenapplying

lean

health-care

managem

entinan

emergencydepartment

Thresholdvalue-

average

Malekzadehetal[43]

Investigatethe

causea

ndeffectrelations

forthe

dimensio

nsandcompo

nentso

forganizational

intelligenceinIranianpu

blicun

iversities

Thresholdvalue

Ranjan

etal[44

]Ad

dressthe

interrelationships

betweendifferent

evaluatio

ncriteria

ofIndian

Railw

ayzones

VIKOR

Thresholdvalue-

average

Tzengetal[10]

Addressthe

depend

entrelations

ofevaluatio

ncriteria

andprop

osea

hybrid

MCD

Mmod

elfor

evaluatin

gintertwined

effectsin

e-learning

programs

FAA

HPfuzzy

integral

Threshold

value-experts

Huetal[45]

Establish

thec

ausalrelationshipandextent

ofmutualimpactam

ongqu

ality

features

andpu

tforth

adecision

analysismetho

dology

toremovep

otentia

lproblem

sfrom

thec

onventionalIPA

mod

elBP

NN

Huetal[46

]Analyze

thec

ause-effectrelationshipam

ongdifferent

quality

characteris

ticstomaker

evision

sto

thetraditio

nalIPA

mod

elandfin

dthec

orep

roblem

sinvolvedwith

winning

orders

GAM

RA

Chengetal[47]

Explorethe

conn

ectio

nbetweenserviceq

ualityattributes

andthes

ervice

quality

improvem

ent

priorityof

fine-dining

restaurantsa

nduseitasa

referencefor

serviceq

ualitystr

ategyplanning

andresource

reorganizing

IPGA

Hsie

handYeh[48]

Exam

inec

ause

andeffectrela

tions

offactorsinfl

uencingthe

serviceq

ualityinfastfood

restaurants

Thresholdvalue-

average

Chiu

etal[49]

Analyze

relatio

nships

ofcusto

mer

buying

decisio

nfactorsa

ndprovidea

marketin

gstr

ategy

planning

forfi

rmsintheL

CD-TVmarket

Hoetal[50]

Analyze

thec

ause-effectrelationbetweenqu

ality

characteris

ticsa

ndbu

ildam

etho

dology

ofsupp

lierq

ualityperfo

rmance

assessmenttoim

proves

upplierq

ualitythroug

hop

timizing

order-winnersandqu

alifiers

IPAM

RA

Tsaietal[51]

Determinethe

causalrelationships

ofandinteractiveinfl

uencea

mon

gcriteria

andprop

osea

mixed

mod

elto

evaluatejobsatisfactionin

high

-tech

indu

strie

sIPA

Najmiand

Makui

[52]

Und

ersta

ndther

elationshipbetweencomparis

onmetric

sand

prop

osea

conceptualmod

elfor

measurin

gsupp

lychainperfo

rmance

AHP

Shafiee

etal[53]

Determinethe

relationships

betweenfour

perspectives

ofBS

Candprop

osea

napproach

toevaluatethep

erform

ance

ofsupp

lychain

DEA

BSC

Thresholdvalue-

average

ShaikandAb

dul-K

ader

[16]

Und

ersta

ndtheinterdepend

ence

amon

gperfo

rmance

factorsa

nddevelopar

everse

logistics

enterpris

eperform

ance

measurementm

odel

BSC

Innerd

ependence

matrix

Mathematical Problems in Engineering 5

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

LinandTzeng[11]

Determinethe

relatio

nshipbetweenthee

valuationcriteria

contrib

utingindu

stryclu

stersand

establish

theirv

alue

structuresa

ndbu

ildav

alue-created

syste

mof

science(techno

logy)p

ark

Threshold

value-experts

LinandSun[18]

Exam

inethe

impactso

fand

determ

inethe

relationships

amon

gdifferent

drivingforces

forthe

grow

thof

indu

strialcluste

rs

Threshold

value-expertsinner

depend

ence

matrix

WangandHsueh

[54]

Recogn

izethe

causalrelationships

betweendesig

nattributes

andmarketin

grequ

irementsand

prop

osea

napproach

toincorporatec

ustomer

preference

andperceptio

ninto

prod

uct

developm

ent

AHPKa

nomod

el

WangandSh

ih[55]

Identifytheimpactso

ffun

ctionalattributes

oncusto

mer

requ

irementsandpresenta

fram

ework

toincorporatec

ustomer

preferencesintoprod

uctd

evelo

pment

CA1QFD

TO

PSIS

Koetal[56]

Analyze

directandindirectim

pactsa

mon

gvario

ustechno

logy

areasa

ndpresenta

combined

approach

toconstructtechn

olog

yim

pactnetworks

forR

ampDplanning

usingpatents

SNA

Yoon

etal[57]

Assesstechno

logicalimpactsa

nddegree

ofcauseo

reffectam

ongtechno

logy

areasw

ithin

the

Korean

techno

logy

syste

mandob

servetheirdynamictre

nds

PCCA

Shen

andTzeng[58]

Explorethe

cause-effectrelationships

amon

gthea

ttributes

inthes

trong

decisio

nrulesa

ndprop

osea

mod

elfortacklingthev

alue

stock

selectionprob

lem

DRS

AFCA

Altu

ntas

andDereli

[59]

Establish

causalrelationships

amon

gtechno

logies

andprop

osea

napproach

forp

rioritizing

investmentp

rojectsfrom

theg

overnm

entrsquos

perspective

PCA

Thresholdvalue-

average

Shen

andTzeng[60]

Explorethe

complex

relationshipam

ongfin

ancialindicatorsandim

provefuturefi

nancial

perfo

rmance

oftheITindu

stry

VC-D

RSAFIS

Leea

ndLin[13]

Find

theinterrelationshipof

financialratio

sidentified

bymanagerso

fshipp

ingcompanies

and

financialexpertsa

ndcompare

theirc

ognitio

nmapsb

ycoun

tryandexpertgrou

pTh

resholdvalue-

MMDE

W-K

Tan

andY-J

Tan[61]

Analyze

howdifferent

factorsinteractand

collectively

contrib

utetothes

uccessfultransform

ation

anddiffu

sionof

thes

mart-c

ard-basede-micropaym

entm

ultip

urpo

sescheme

Azadehetal[12]

Evaluatetheimpactdegree

ofleannessfactorsa

ndpresentsac

omprehensiv

eapp

roachfor

evaluatin

gandop

timizingtheleann

essd

egreeo

forganizations

(lean

prod

uctio

n)

DEA

fuzzy

DEA

FCM

AHP

Thresholdvalue-

average

Sara

etal[14]

Assessrelativeimpo

rtance

andmutualinfl

uenceo

fbarrie

rsforc

arbo

ncapturea

ndsto

rage

deployment

AHP

Thresholdvalue-

average

Liaw

etal[62]

Analyze

theind

irectrelations

betweensubsystemsa

ndcompo

nentsa

ndprop

osea

reliability

allocatio

nmetho

dto

solvethe

fund

amentalproblem

sofcon

ventionalreliabilityappo

rtionm

ent

metho

dsME-OWA

Type

2interrelationships

andkeyfactors

AlaeiandAlro

aia[

63]

Identifyandprioritizethe

factorsa

ffectingandaffectedby

thep

erform

ance

ofsm

alland

medium

enterpris

es

Bacudioetal[64

]Analyze

cause-effectrelationships

ofbarriersto

implem

entin

gindu

stria

lsym

biosisnetworks

inan

indu

strialp

ark

Thresholdvalue-

averageinner

depend

ence

matrix

Balkovskayaa

ndFilneva[

65]

Identifycausalrelationships

betweenthek

eyevaluatio

nindicatorsof

bank

ingperfo

rmance

aswell

asdefin

ingthem

oststrategicallyim

portantind

icators

BSC

Threshold

value-second

quartile

6 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Chen

[66]

Estim

atethe

impo

rtance

ofthes

ervice

factorso

fanacadem

iclib

rary

andidentifythec

ausal

factors

Threshold

value-experts

GovindanandCh

audh

uri[67]

Analyze

ther

isksfaced

bythird

-partylogisticsservice

providersinrelationto

oneo

fitscusto

mers

andextractthe

causalrelationships

amon

gthem

Govindanetal[68]

Investigatethe

influ

entia

lstre

ngth

offactorso

nadop

tionof

greensupp

lychainmanagem

ent

practic

esin

theInd

ianminingindu

stry

AHP

Thresholdvalue-

average

Gandh

ietal[69]

Evaluatesuccessfactorsin

implem

entatio

nof

greensupp

lychainmanagem

entinIndian

manufacturin

gindu

strie

s

Hwangetal[70]

Explorethe

causalrelatio

nships

amon

gdecisio

nfactorsrelatingto

greensupp

lychains

inthe

semicon

ductor

indu

stry

Hwangetal[71]

Identifydeterm

inantsandtheirc

ausalrela

tionships

affectin

gthea

doptionof

cloud

compu

tingin

sciencea

ndtechno

logy

institutio

nsTh

reshold

value-120583+

32120590Hwangetal[20]

Assessthed

ynam

icris

kinterdependenciesfor

distinctprojectp

hasesa

ndidentifycriticalrisk

factors

Threshold

value-experts

Rahimniaa

ndKa

rgozar

[72]

Disc

over

causalrelationships

betweenob

jectives

inun

iversitystr

ategymap

andprioritizethem

forresou

rcea

llocatio

nBS

CTh

resholdvalue-third

quartile

Sekh

aretal[73]

Prioritizea

ndmap

thec

ausalrelationstr

ucturesindimensio

nsandsubd

imensio

nsof

HR-flexibilityandfirm

perfo

rmance

from

ITindu

stry

perspective

Seleem

etal[74]

Selectandmanagethe

suita

blep

erform

ance

improvem

entinitia

tives

toenhancethe

internal

processeso

fmanufacturin

gcompanies

BSC

TOC

Rank

basedon119877an

d119862

Sharmae

tal[75]

Assessthec

ausalrelationships

amon

glean

criteria

andidentifycriticalonesfor

thes

uccessful

implem

entatio

nof

lean

manufacturin

gTh

resholdvalue-

average

Shen

[76]

Identifythek

eybarriersandtheirinterrelationships

impeding

theu

niversity

techno

logy

transfe

rfro

mam

ultistakeho

lder

perspective

Thresholdvalue-third

quartile

Seyed-Hosseinietal[77]

Analyze

ther

elationbetweencompo

nentso

fasyste

mandprop

osea

metho

dology

for

reprioritizationof

failu

remod

esin

FMEA

Rank

basedon119877minus

119862Ch

ang[78]

Analyze

ther

elationshipbetweencompo

nentso

fasyste

mandou

tline

ageneralalgorithm

for

prioritizationof

failu

remod

esin

FMEA

OWGA

Rank

basedon119877minus

119862Ch

angetal[79]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

GRA

Rank

basedon119877minus

119862Ch

angetal[80]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

TOPS

ISRa

nkbasedon119877minus

119862

Mathematical Problems in Engineering 7

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Liuetal[81]

Con

structthe

influ

entia

lrelations

amon

gfailu

remod

esandcauses

offailu

resa

nddevelopa

fram

eworkforp

rioritizationof

failu

remod

esAHPVIKOR

Mentese

tal[82]

Con

sider

thed

irect-in

directrelationships

betweenfactorsa

ndprop

osea

nintegrated

metho

dology

forrisk

assessmento

fcargo

shipsa

tcoasts

andop

enseas

OWGA

Huang

etal[8]

Identifymajor

indu

stry

inno

vatio

nrequ

irementsandpresentrecon

figured

inno

vatio

npo

licy

portfolio

stodevelopTaiwanrsquosSIPMallind

ustry

GRA

CA1

Threshold

value-experts

LiandTzeng[9]

Disc

over

andillustratethe

keyservices

needed

toattractSIP

usersa

ndSIPproviderstoan

SIP

Mall

Threshold

value-experts

Horng

etal[83]

Identifyther

elationships

andinteractions

amon

gdimensio

nsof

restaurant

spaced

esignfro

mthe

expertrsquosp

erspectiv

eTh

resholdvalue-

average

Chen

etal[84]

Determinec

riticalcore

factorsa

ffectingconsum

erintentionto

dine

atgreenrestaurantsa

nddevelopspecificimprovem

entstrategies

SEMQ

FD

Chengetal[85]

Develo

pathree-tiered

serviceq

ualityim

provem

entm

odelto

identifycritical

educational-service-qualitydeficienciesinho

spita

litytourism

and

leisu

reun

dergradu

ate

programs

IPGAQ

FD

Shiehetal[86]

Evaluatetheimpo

rtance

andconstructthe

causalrelatio

nsof

criteria

from

patientsrsquoview

points

andidentifykeysuccessfactorsforimprovingtheh

ospitalservice

quality

SERV

QUA

Lmod

elTh

resholdvalue-

average

Ranjan

etal[87]

Analyze

andexplaintheinteractio

nrelationships

andim

pactlevelsbetweenevaluatio

ncriteria

anddevelopaframew

orkforp

erform

ance

evaluatio

nof

engineeringdepartmentsin

auniversity

VIKOR

entro

pymetho

dTh

resholdvalue-

average

TanandKu

o[15]

Prioritizefacilitatio

nstrategies

ofruralp

arkandrecreatio

nagencies

from

thep

erspectiv

eof

leisu

reconstraints

Threshold

value-maxim

umvalue

Wuetal[88]

Describethe

contextualrelationships

evaluatedam

ongcriteria

andevaluatetheimpo

rtance

ofthe

criteria

used

inem

ploymentservice

outre

achprogram

person

nel

Thresholdvalue-

average

Sun[89]

Handlethe

innerd

ependencea

ndidentifycore

competences

ofnewlyqu

alified

nurses

Threshold

value-experts

WuandTsai[90]

Describethe

contextualrelatio

nships

amon

gthec

riteriaandevaluatetheimpo

rtance

ofdimensio

nscriteriain

auto

sparep

artsindu

stry

Thresholdvalue-

average

8 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Sun[91]

Identifyandanalyzec

riticalsuccessfactorsin

thee

lectronicd

esignautomationindu

stry

Threshold

value-experts

WuandTsai[92]

Depictthe

causalrelatio

nsandevaluatetheimpo

rtance

ofcriteria

inauto

sparep

artsindu

stry

AHP

Thresholdvalue-

average

Weietal[93]

Reprioritizethe

amendedmod

esin

theS

EMmod

elandestablish

acausalrelationshipmod

elfor

Web-advertisingeffects

Wuetal[24]

Explorethe

factorsh

inderin

gthea

cceptanceo

fusin

ginternalclo

udservices

inau

niversity

TAM

Four

quadrants

Hsu

[94]

Find

thed

eterminantfactorsinflu

encing

blog

desig

nandsim

plify

andvisualizethe

interrelationships

betweencriteria

fore

achfactor

FATh

reshold

value-experts

Hsu

andLee[95]

Explorethe

criticalfactorsinflu

encing

theq

ualityof

blog

interfa

cesa

ndthec

ausalrela

tionships

betweenthesefactors

Leee

tal[96]

Establish

thec

ausalrela

tionshipandthed

egreeo

finterrelationshipof

DTP

Bvaria

bles

(university

library

website)

Wuetal[23]

Explored

ecisive

factorsa

ffectingan

organizatio

nrsquosSoftw

area

saService(SaaS)a

doption

Four

quadrants

Pathariand

Sonar[97]

Analyze

asetof

securitysta

tementsin

inform

ationsecuritypo

licyproceduresand

controlsto

establish

anim

plicithierarchyandrelativ

eimpo

rtance

amon

gthem

Jafarnejad

etal[98]

Classifythec

riteriain

ERPselectioninto

thetwogrou

psof

ldquocauserdquoa

ndldquoeffectrdquoa

ndprop

osea

combinedMCD

Mapproach

toselectthep

roperE

RPsyste

m

Entro

pymetho

dfuzzy

AHP

TsaiandCh

eng[99]

Analyze

KPIsforE

-com

merce

andInternetmarketin

gof

elderly

prod

ucts

BSC

Wangetal[25]

Capturethe

causalrelationships

amon

gdivisio

nsandidentifythosed

ivision

swith

inam

atrix

organizatio

nthatmay

berespon

sibleforthe

poor

perfo

rmance

ofah

igh-tech

facilitydesig

nproject

SIA

Netinflu

ence

matrix

Linetal[100]

Explorethe

core

competences

andinvestigatetheircausea

ndeffectrela

tionships

oftheICdesig

nservicec

ompany

Threshold

value-experts

Chuang

etal[21]

Investigatethe

complex

multid

imensio

naland

dynamicnature

ofmem

bere

ngagem

entb

ehavior

inenvironm

entalprotectionvirtualcom

mun

ities

ISM

Threshold

value-expertsfour

quadrants

Rahm

anandSubram

anian[101]

Identifycriticalfactorsforimplem

entin

gEO

Lcompu

terrecyclin

gop

erations

inreverses

upply

chainandinvestigatethec

ausalrelationshipam

ongthefactors

Thresholdvalue-

average

Hsu

etal[102]

Recogn

izethe

influ

entia

lcriteriaof

carbon

managem

entingreensupp

lychainto

improvethe

overallp

erform

ance

ofsupp

liers

Thresholdvalue

Falatoon

itoosietal[103]

Exam

inec

omplex

causalrelationshipbetweenfactorsingreensupp

lychainmanagem

entand

providea

nevaluatio

nfram

eworkto

selectthem

osteligiblegreensupp

liers

Renetal[104]

Identifykeydrivingfactorsa

ndmap

theirc

ause-effectrelationships

fore

nhancing

the

susta

inabilityof

hydrogen

supp

lychain

Threshold

value-experts

Mud

uliand

Barve[105]

Extractthe

causalrelationships

amon

ggreensupp

lychainmanagem

entb

arrie

rsandestablish

asustainabled

evelop

mentframew

orkin

scaleInd

ianminingindu

strie

s

Mathematical Problems in Engineering 9

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

WuandCh

ang[106]

Identifythec

riticaldimensio

nsandfactorstoim

plem

entg

reen

supp

lychainmanagem

entinthe

electricalandele

ctronicind

ustries

Thresholdvalue-

average

Behera

andMuk

herje

e[107]

Capturer

elationships

andanalyzek

eyinflu

encing

factorsrele

vant

toselectionof

supp

lychain

coordinatio

nschemes

Thresholdvalue-

MMDE

Ahm

edetal[108]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

fore

valuatingsustainableE

OLvehicle

managem

entalternatives

FuzzyAHP

Ahm

edetal[109]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

andprop

osea

nintegrated

mod

elfor

sustainableE

OLvehicle

managem

entalternatives

election

AHPfuzzyA

HP

Miaoetal[110

]Ev

aluatetheimpo

rtance

andun

veiltheimplicitinterrela

tionships

amon

gdifferent

scales

ofCP

Vandconstructa

multiscalemod

elforthe

measuremento

fCPV

ofEV

sHoQ

Threshold

value-expertsrank

basedon119877+

119862Lin[111]

Analyze

interactions

amon

gindu

stria

ldevelo

pmentfactorsandexploreh

owto

establish

the

competitivenesso

fsolar

photovoltaicindu

stry

Porterrsquos

Diamon

dmod

el

AzarnivandandCh

itsaz

[112]

Quantify

theinterlin

kagesa

mon

gfund

amentalanthrop

ogenicindicatorsandprop

osea

syste

maticapproach

forw

ater

shortage

mitigatio

nin

thea

ridregion

seD

PSIRA

HP

COPR

AS-G

Chen

etal[113]

Quantify

theinfl

uenceo

nPM

25by

otherfactorsin

thew

eather

syste

mandidentifythem

ost

impo

rtantfactorsforP

M25

RMFo

urqu

adrants

dosM

uchangos

etal[114

]As

sesstheb

arrie

rsto

mun

icipalsolid

wastemanagem

entp

olicyplanning

andidentifythem

ost

onerou

sbarrie

rsto

thee

ffectiveimplem

entatio

nof

thep

olicy

ISM

Netinflu

ence

matrix

Guo

etal[115]

EvaluateandinvestigategreencorporateC

SRindicatorsof

manufacturin

gcorporations

from

agreenindu

strylawperspective

Four

quadrants

Chen

andCh

i[116

]Ex

plorek

eyfactorso

fChinarsquosCS

Rfro

mthep

erspectiv

eofaccou

ntingexperts

Changetal[117

]Identifykeystr

ategicfactorsintheimplem

entatio

nof

CSRin

airline

indu

stry

Leee

tal[118]

Calculatethe

causalrelationshipandinteractionlevelbetweenTA

Mvaria

bles

andfin

dthec

ore

varia

bles

form

anagem

ento

rimprovem

entw

hileintro

ducing

anew

etchingplasmatechn

olog

yFo

urqu

adrants

Wu[119]

Determinethe

causalrelationships

betweentheK

PIso

fthe

BSCandlin

kthem

into

astrategy

map

forb

anking

institutio

nsBS

C

Chienetal[22]

Identifyrelatio

nships

betweenris

kfactorsa

ndassesscriticalrisk

factorsfor

BIM

projects

Four

quadrants

10 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Wangetal[26]

Evaluatethep

erform

ance

ofdesig

ndelay

factorsa

ndidentifykeyfactorsthatd

rived

esigndelay

sof

afacilityconstructio

nproject

ISA

Netinflu

ence

matrix

Tzeng[19

]Investigatethe

relationshipbetweenfactorsa

ffectingparolebo

ardsrsquodecision

makingin

Taiwan

Simplified

norm

alized

total-relation

matrix

threshold

value

Gazibey

etal[120]

Analyze

thec

ause

andeffectrelations

amon

gthec

riteriaaffectin

gmainbattletankselection

Thresholdvalue-

average

Type

3interrelationships

andcriteria

weights

Khalili-D

amgh

anietal[121]

Determinethe

relativ

eimpo

rtance

weightsof

compensatoryob

jectivefun

ctions

andprop

osea

hybrid

multip

leob

jectivem

etaheuris

ticalgorithm

tosolveland-uses

uitabilityanalysisand

planning

prob

lem

AHP

Khazaietal[29]

Analyze

directandindirectdepend

encies

with

insocialandindu

stria

lvulnerabilityindicatorsand

developaframew

orkforspatia

lassessm

ento

find

ustrialand

socialvulnerabilityto

indirect

disaste

rlosses

Threshold

valuedepend

ency

weights

Tseng[122]

Resolvec

riteriainterdependencyrelationships

weightsandprop

osea

hybrid

metho

dto

evaluate

serviceq

ualityexpectationin

hotspringho

telrsquosrank

ingprob

lem

FuzzyTO

PSIS

Innerd

ependence

matrix

Quadere

tal[123]

Determinethe

causea

ndeffectrelationships

amon

gcriteria

andevaluatethec

riticalcriteria

for

CO2capturea

ndsto

rage

intheironandste

elindu

stry

Criteria

weights-

vector

leng

thth

reshold

value

Quadera

ndAhm

ed[124]

Identifycriticalfactorsfore

valuatingalternativeiron-makingtechno

logies

with

carbon

capture

andsto

rage

syste

ms

FuzzyAHP

Criteria

weights-

vector

leng

thth

reshold

value

Seyedh

osseinietal[17]

Identifythec

ause

andeffectrela

tionships

amon

glean

objectives

andprop

osed

asystematicamp

logicalm

etho

dfora

utopartmanufacturersto

determ

inethe

companyrsquoslean

strategymap

BSC

Innerd

ependence

matrix

weights-119877+

119862Cebi[27]

Determineimpo

rtance

degreeso

fwebsited

esignparametersb

ased

oninteractions

andtypeso

fwebsites

Thresholdvalue-

averagedeterm

ining

weightsusing119877+

119862Yazdani-C

hamzini

etal[28]

Analyze

interdependencea

nddepend

encies

andcompu

tetheg

lobalw

eightsfore

valuation

indicatorsandprop

osea

newhybrid

mod

elto

selectthes

trategyof

investingin

apriv

ates

ector

AHPfuzzy

TOPS

IS

Thresholdvalue-

expertsweights-119877+

119862No

teB

ackpropagatio

nneuralnetworkBP

NNbalancedscorecardBS

Cbu

ildinginformationmod

elingBIMcluste

ranalysisC

A1conjoint

analysis

CA2corporatesocialrespo

nsibilityC

SRcustomerperceived

valueCP

Vdata

envelopm

enta

nalysis

DEA

decom

posedtheory

ofplannedbehaviorD

TPB

dominance-based

roug

hseta

pproach

DRS

Aelectric

vehicle

EV

enhanced

drivingforce-pressure-state-im

pact-

respon

seeDPS

IRenterprise

resource

planning

ERP

end

-of-lifeE

OLfactor

analysis

FAfailure

mod

eand

effectanalysisFMEA

fuzzy

cogn

itive

mapFCM

fuzzy

inferences

ystemFISformalconceptanalysis

FC

Agap

analysis

GAgreyc

omplex

prop

ortio

nalassessm

entCO

PRAS-Ggreyr

elationalanalysisG

RAhou

seso

fqualityHoQ

impo

rtance-perform

ance

analysis

IPAimpo

rtance-perform

ance

andgapanalysis

IPGAimpo

rtance-satisfactio

nanalysis

ISAinformationtechno

logyITinterpretiv

estructuralm

odeling

ISM

integratedcircuitICkey

perfo

rmance

indicatorKP

Imaxim

alentro

pyorderedweightedaveraging

ME-OWAm

ultip

leregressio

nanalysis

MRA

ordered

weightedgeom

etric

averagingOWGApatentcitatio

nanalysis

PCApatentcoclassificatio

nanalysis

PCCA

relationmapR

Msatisfi

edim

portance

analysis

SIAsiliconintellectualp

ropertyor

Semicon

ductor-Intellectual-P

ropertySIP

socialnetworkanalysis

SNAstructuralequ

ationmod

elingSE

Mtechn

olog

yacceptance

mod

elTA

Mtheoryof

constraintsTO

Cvaria

blec

onsis

tencyDRS

AV

C-DRS

A

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Page 2: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

2 Mathematical Problems in Engineering

The remaining part of this paper is structured as followsIn Section 2 we introduce the research methodology used toidentify and refine the literature in this study In Section 3detailed reviews of each category of the DEMATEL studiesare presented Section 4 describes some general observationsand findings based on statistical analysis results of thereview Finally this paper concludes in Section 5 by sum-marizing the results and discussing opportunities for futureresearch

2 Research Methodology

For the purpose of this literature review we searched forarticles in the Scopus database published between 2006 and2016 The choice of this time period is based on the factthat the majority of papers on this topic were publishedduring this period and there are only five articles recordedin the Scopus prior to 2006 Inspired by the PreferredReporting Items for Systematic Reviews and Meta-Analyses(PRISRMA) method [2 3] the selection of articles in thisstudy is consisted of three stages that is literature searcharticles eligibility and data extraction and summarizingFirst the keyword ldquoDEMATELrdquo was used for searching inldquoabstract title and keywordsrdquo for journal papers and atotal of 509 document results were identified from ScopusNext we chose the articles which had used the DEMATELtechnique or its extensions to solve real-world problemsand 346 academic papers fell under the scope of this reviewafter title abstract and full-text screening Since this studyfocuses on both the DEMATEL and its applications thosestudies which only modify the DEMATEL technique withoutapplying to actual settings have been eliminated (for theinterested readers please refer eg to [4ndash6]) Finally theresulting papers were reviewed thoroughly to identify thefocus method application and combination with othermethods Also articles were summarized based on variouscriteria such as year of publication application areas andcitations

Based on the DEMATEL methods adopted the selectedpublications are roughly grouped into five categories the onesusing classical DEMATEL (105 articles) the ones using fuzzyDEMATEL (63 articles) the ones using grey DEMATEL(12 articles) the ones combining analytical network process(ANP) and DEMATEL (154 articles) and the ones basedon other DEMATEL methods (12 articles) The classificationscheme of the DEMATEL articles is shown in Figure 1Most of the papers on ANP and DEMATEL hybridizationare included in a review paper of DEMATEL approachesfor criteria interaction handling with ANP by Golcuk andBaykasoglu [7] Therefore in the following sections wewill not discuss the studies which apply the DEMATELin conjunction with ANP to deal with interactions amongcriteria

3 Reviews of DEMATEL Methods

31 The Classical DEMATEL As stated earlier the DEMA-TEL technique can convert the interrelations between factors

Classical DEMATEL303

Fuzzy DEMATEL 182

ANP and DEMATEL445

Grey DEMATEL35

Other DEMATEL 35

Figure 1 Classification scheme of the DEMATEL articles

into an intelligible structural model of the system and dividethem into a cause group and an effect group [8] Hence it isan applicable and useful tool to analyze the interdependentrelationships among factors in a complex system and rankthem for long-term strategic decision making and indicatingimprovement scopes The formulating steps of the classicalDEMATEL can be summarized as follows [8ndash10]

Step 1 (generate the group direct-influence matrix 119885) Toassess the relationships between 119899 factors 119865 = 1198651 1198652 119865119899in a system suppose that 119897 experts in a decision group 119864 =1198641 1198642 119864119897 are asked to indicate the direct influence thatfactor 119865119894 has on factor 119865119895 using an integer scale of ldquonoinfluence (0)rdquo ldquolow influence (1)rdquo ldquomedium influence (2)rdquoldquohigh influence (3)rdquo and ldquovery high influence (4)rdquo Then theindividual direct-influence matrix 119885119896 = [119911119896119894119895]119899times119899 provided bythe 119896th expert can be formed where all principal diagonalelements are equal to zero and 119911119896119894119895 represents the judgmentof decision maker 119864119896 on the degree to which factor 119865119894 affectsfactor 119865119895 By aggregating the 119897 expertsrsquo opinions the groupdirect-influence matrix 119885 = [119911119894119895]119899times119899 can be obtained by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 119894 119895 = 1 2 119899 (1)

Step 2 (establish the normalized direct-influence matrix 119883)When the group direct-influence matrix 119885 is acquired thenormalized direct-influence matrix 119883 = [119909119894119895]119899times119899 can beachieved by using

119883 = 119885119904 (2)

119904 = max(max1le119894le119899

119899sum119895=1

119911119894119895max1le119894le119899

119899sum119894=1

119911119894119895) (3)

Mathematical Problems in Engineering 3

All elements in the matrix 119883 are complying with 0 le 119909119894119895 lt1 0 le sum119899119895=1 119909119894119895 le 1 and at least one 119894 such that sum119899119895=1 119911119894119895 le 119904Step 3 (construct the total-influence matrix 119879) Using thenormalized direct-influence matrix 119883 the total-influencematrix 119879 = [119905119894119895]119899times119899 is then computed by summing the directeffects and all of the indirect effects by

119879 = 119883 + 1198832 + 1198833 + sdot sdot sdot + 119883ℎ = 119883 (119868 minus 119883)minus1 when ℎ 997888rarr infin (4)

in which 119868 is denoted as an identity matrix

Step 4 (produce the influential relation map (IRM)) At thisstep the vectors 119877 and 119862 representing the sum of the rowsand the sum of the columns from the total-influence matrix119879 are defined by the following formulas

119877 = [119903119894]119899times1 = [[119899sum119895=1

119905119894119895]]119899times1

119862 = [119888119895]1times119899 = [119899sum119894=1

119905119894119895]119879

1times119899

(5)

where 119903119894 is the 119894th row sum in the matrix 119879 and displays thesum of the direct and indirect effects dispatching from factor119865119894 to the other factors Similarly 119888119895 is the 119895th column sum inthematrix119879 and depicts the sum of direct and indirect effectsthat factor 119865119895 is receiving from the other factors

Let 119894 = 119895 and 119894 119895 isin 1 2 119899 the horizontal axisvector (119877 + 119862) named ldquoProminencerdquo illustrates the strengthof influences that are given and received of the factor Thatis (119877 + 119862) stands for the degree of central role that the factorplays in the systemAlike the vertical axis vector (119877minus119862) calledldquoRelationrdquo shows the net effect that the factor contributes tothe system If (119903119895 minus 119888119895) is positive then the factor 119865119895 has anet influence on the other factors and can be grouped intocause group if (119903119895 minus 119888119895) is negative then the factor 119865119895 is beinginfluenced by the other factors on the whole and should begrouped into effect group Finally an IRM can be created bymapping the dataset of (119877+119862119877minus119862) which provides valuableinsights for decision making

311 Observations and Findings Table 1 summarizes all theclassical DEMATEL studies based on the particular purposeof using DEMATEL the topic of decision making andother methods combined According to the distinct usageof the DEMATEL method the current classical DEMATELresearches can be classified into three types the first typeis merely clarifying the interrelationships between factors orcriteria the second type is identifying key factors based onthe causal relationships and the degrees of interrelationshipbetween them the third type is determining criteria weightsby analyzing the interrelationships and impact levels ofcriteria

In Table 1 we have provided an overview on the existingapplications of the classical DEMATEL for solving compli-cated and intertwined problems in many fields based onwhich we now point out some critical steps added to theoriginal approach

Step 4-1 (set a threshold value to draw the IRM) In the abovethe IRM is constructed based on the information from thematrix 119879 to explain the structure relations of factors But insome situations the IRM will be too complex to show thevaluable information for decision making if all the relationsare considered Therefore a threshold value 120579 is set in manystudies to filter out negligible effectsThat is only the elementof matrix 119879 whose influence level is greater than the value of120579 is selected and converted into an IRM

If the threshold value is too lowmany factors are includedand the IRMwill be too complex to comprehend In contrastsome important factors may be excluded if the thresholdvalue is too high In the literature the threshold value 120579 isusually determined by experts through discussions [10 11]the results of literature review the brainstorming technique[12] the maximum mean deentropy (MMDE) [13] theaverage of all elements in the matrix 119879 [14] or the maximumvalue of the diagonal elements of the matrix 119879 [15]

Step 4-2 (obtain the inner dependence matrix 1198791015840) When thetotal-influence matrix 119879 is produced in [16 17] an innerdependence matrix 1198791015840 is acquired by normalizing the matrix119879 so that each column sum is equal to 1 But in [18] the innerdependencematrix1198791015840 is derived based on the threshold value120579 and only the factors whose effects in the matrix 119879 are largerthan 120579 are shown in the matrix 1198791015840

To interpret the results easily and keep the complexity ofthe system manageable Tzeng [19] established a simplifiednormalized total-influence matrix 119904 using a normalizationmethod and the threshold value 120579 First the normalized total-influencematrix = [119894119895]119899times119899 is calculated by using (6) to forcethe values of the matrix 119879within the scope of a measurementscale

119894119895 = (119896 minus 0) (119905119894119895 minusmin 119905119894119895)max 119905119894119895 minusmin 119905119894119895 (6)

where 119896 is the highest score for measuring the degree ofrelative impact between factors and 119896 = 4 if the integralscale of 0 to 4 is used Then the simplified normalized total-influence matrix 119904 = [119904119894119895]119899times119899 is obtained by eliminatinginsignificant effects in the matrix based on the thresholdvalue 120579 That is

119904119894119895 = 119894119895 if 119894119895 gt 1205790 if 119894119895 le 120579 (7)

Step 4-21015840 (divide the IRM into four quadrants) Once an IRMis acquired eight of the classical DEMATEL studies classifiedthe factors in a complicated system into four quadrantsaccording to their locations in the diagram In [20ndash22] theIRM is divided into four quadrants I to IV as displayed in

4 Mathematical Problems in Engineering

Table1Va

rious

applications

ofthec

lassicalDEM

ATEL

Papers

Research

purposes

Com

binatio

nsRe

marks

Type

1interrelationships

BEfea

ndOFE

fe[42]

Specify

theinfl

uenced

egrees

ofthep

atient

perceivedvalues

whenapplying

lean

health-care

managem

entinan

emergencydepartment

Thresholdvalue-

average

Malekzadehetal[43]

Investigatethe

causea

ndeffectrelations

forthe

dimensio

nsandcompo

nentso

forganizational

intelligenceinIranianpu

blicun

iversities

Thresholdvalue

Ranjan

etal[44

]Ad

dressthe

interrelationships

betweendifferent

evaluatio

ncriteria

ofIndian

Railw

ayzones

VIKOR

Thresholdvalue-

average

Tzengetal[10]

Addressthe

depend

entrelations

ofevaluatio

ncriteria

andprop

osea

hybrid

MCD

Mmod

elfor

evaluatin

gintertwined

effectsin

e-learning

programs

FAA

HPfuzzy

integral

Threshold

value-experts

Huetal[45]

Establish

thec

ausalrelationshipandextent

ofmutualimpactam

ongqu

ality

features

andpu

tforth

adecision

analysismetho

dology

toremovep

otentia

lproblem

sfrom

thec

onventionalIPA

mod

elBP

NN

Huetal[46

]Analyze

thec

ause-effectrelationshipam

ongdifferent

quality

characteris

ticstomaker

evision

sto

thetraditio

nalIPA

mod

elandfin

dthec

orep

roblem

sinvolvedwith

winning

orders

GAM

RA

Chengetal[47]

Explorethe

conn

ectio

nbetweenserviceq

ualityattributes

andthes

ervice

quality

improvem

ent

priorityof

fine-dining

restaurantsa

nduseitasa

referencefor

serviceq

ualitystr

ategyplanning

andresource

reorganizing

IPGA

Hsie

handYeh[48]

Exam

inec

ause

andeffectrela

tions

offactorsinfl

uencingthe

serviceq

ualityinfastfood

restaurants

Thresholdvalue-

average

Chiu

etal[49]

Analyze

relatio

nships

ofcusto

mer

buying

decisio

nfactorsa

ndprovidea

marketin

gstr

ategy

planning

forfi

rmsintheL

CD-TVmarket

Hoetal[50]

Analyze

thec

ause-effectrelationbetweenqu

ality

characteris

ticsa

ndbu

ildam

etho

dology

ofsupp

lierq

ualityperfo

rmance

assessmenttoim

proves

upplierq

ualitythroug

hop

timizing

order-winnersandqu

alifiers

IPAM

RA

Tsaietal[51]

Determinethe

causalrelationships

ofandinteractiveinfl

uencea

mon

gcriteria

andprop

osea

mixed

mod

elto

evaluatejobsatisfactionin

high

-tech

indu

strie

sIPA

Najmiand

Makui

[52]

Und

ersta

ndther

elationshipbetweencomparis

onmetric

sand

prop

osea

conceptualmod

elfor

measurin

gsupp

lychainperfo

rmance

AHP

Shafiee

etal[53]

Determinethe

relationships

betweenfour

perspectives

ofBS

Candprop

osea

napproach

toevaluatethep

erform

ance

ofsupp

lychain

DEA

BSC

Thresholdvalue-

average

ShaikandAb

dul-K

ader

[16]

Und

ersta

ndtheinterdepend

ence

amon

gperfo

rmance

factorsa

nddevelopar

everse

logistics

enterpris

eperform

ance

measurementm

odel

BSC

Innerd

ependence

matrix

Mathematical Problems in Engineering 5

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

LinandTzeng[11]

Determinethe

relatio

nshipbetweenthee

valuationcriteria

contrib

utingindu

stryclu

stersand

establish

theirv

alue

structuresa

ndbu

ildav

alue-created

syste

mof

science(techno

logy)p

ark

Threshold

value-experts

LinandSun[18]

Exam

inethe

impactso

fand

determ

inethe

relationships

amon

gdifferent

drivingforces

forthe

grow

thof

indu

strialcluste

rs

Threshold

value-expertsinner

depend

ence

matrix

WangandHsueh

[54]

Recogn

izethe

causalrelationships

betweendesig

nattributes

andmarketin

grequ

irementsand

prop

osea

napproach

toincorporatec

ustomer

preference

andperceptio

ninto

prod

uct

developm

ent

AHPKa

nomod

el

WangandSh

ih[55]

Identifytheimpactso

ffun

ctionalattributes

oncusto

mer

requ

irementsandpresenta

fram

ework

toincorporatec

ustomer

preferencesintoprod

uctd

evelo

pment

CA1QFD

TO

PSIS

Koetal[56]

Analyze

directandindirectim

pactsa

mon

gvario

ustechno

logy

areasa

ndpresenta

combined

approach

toconstructtechn

olog

yim

pactnetworks

forR

ampDplanning

usingpatents

SNA

Yoon

etal[57]

Assesstechno

logicalimpactsa

nddegree

ofcauseo

reffectam

ongtechno

logy

areasw

ithin

the

Korean

techno

logy

syste

mandob

servetheirdynamictre

nds

PCCA

Shen

andTzeng[58]

Explorethe

cause-effectrelationships

amon

gthea

ttributes

inthes

trong

decisio

nrulesa

ndprop

osea

mod

elfortacklingthev

alue

stock

selectionprob

lem

DRS

AFCA

Altu

ntas

andDereli

[59]

Establish

causalrelationships

amon

gtechno

logies

andprop

osea

napproach

forp

rioritizing

investmentp

rojectsfrom

theg

overnm

entrsquos

perspective

PCA

Thresholdvalue-

average

Shen

andTzeng[60]

Explorethe

complex

relationshipam

ongfin

ancialindicatorsandim

provefuturefi

nancial

perfo

rmance

oftheITindu

stry

VC-D

RSAFIS

Leea

ndLin[13]

Find

theinterrelationshipof

financialratio

sidentified

bymanagerso

fshipp

ingcompanies

and

financialexpertsa

ndcompare

theirc

ognitio

nmapsb

ycoun

tryandexpertgrou

pTh

resholdvalue-

MMDE

W-K

Tan

andY-J

Tan[61]

Analyze

howdifferent

factorsinteractand

collectively

contrib

utetothes

uccessfultransform

ation

anddiffu

sionof

thes

mart-c

ard-basede-micropaym

entm

ultip

urpo

sescheme

Azadehetal[12]

Evaluatetheimpactdegree

ofleannessfactorsa

ndpresentsac

omprehensiv

eapp

roachfor

evaluatin

gandop

timizingtheleann

essd

egreeo

forganizations

(lean

prod

uctio

n)

DEA

fuzzy

DEA

FCM

AHP

Thresholdvalue-

average

Sara

etal[14]

Assessrelativeimpo

rtance

andmutualinfl

uenceo

fbarrie

rsforc

arbo

ncapturea

ndsto

rage

deployment

AHP

Thresholdvalue-

average

Liaw

etal[62]

Analyze

theind

irectrelations

betweensubsystemsa

ndcompo

nentsa

ndprop

osea

reliability

allocatio

nmetho

dto

solvethe

fund

amentalproblem

sofcon

ventionalreliabilityappo

rtionm

ent

metho

dsME-OWA

Type

2interrelationships

andkeyfactors

AlaeiandAlro

aia[

63]

Identifyandprioritizethe

factorsa

ffectingandaffectedby

thep

erform

ance

ofsm

alland

medium

enterpris

es

Bacudioetal[64

]Analyze

cause-effectrelationships

ofbarriersto

implem

entin

gindu

stria

lsym

biosisnetworks

inan

indu

strialp

ark

Thresholdvalue-

averageinner

depend

ence

matrix

Balkovskayaa

ndFilneva[

65]

Identifycausalrelationships

betweenthek

eyevaluatio

nindicatorsof

bank

ingperfo

rmance

aswell

asdefin

ingthem

oststrategicallyim

portantind

icators

BSC

Threshold

value-second

quartile

6 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Chen

[66]

Estim

atethe

impo

rtance

ofthes

ervice

factorso

fanacadem

iclib

rary

andidentifythec

ausal

factors

Threshold

value-experts

GovindanandCh

audh

uri[67]

Analyze

ther

isksfaced

bythird

-partylogisticsservice

providersinrelationto

oneo

fitscusto

mers

andextractthe

causalrelationships

amon

gthem

Govindanetal[68]

Investigatethe

influ

entia

lstre

ngth

offactorso

nadop

tionof

greensupp

lychainmanagem

ent

practic

esin

theInd

ianminingindu

stry

AHP

Thresholdvalue-

average

Gandh

ietal[69]

Evaluatesuccessfactorsin

implem

entatio

nof

greensupp

lychainmanagem

entinIndian

manufacturin

gindu

strie

s

Hwangetal[70]

Explorethe

causalrelatio

nships

amon

gdecisio

nfactorsrelatingto

greensupp

lychains

inthe

semicon

ductor

indu

stry

Hwangetal[71]

Identifydeterm

inantsandtheirc

ausalrela

tionships

affectin

gthea

doptionof

cloud

compu

tingin

sciencea

ndtechno

logy

institutio

nsTh

reshold

value-120583+

32120590Hwangetal[20]

Assessthed

ynam

icris

kinterdependenciesfor

distinctprojectp

hasesa

ndidentifycriticalrisk

factors

Threshold

value-experts

Rahimniaa

ndKa

rgozar

[72]

Disc

over

causalrelationships

betweenob

jectives

inun

iversitystr

ategymap

andprioritizethem

forresou

rcea

llocatio

nBS

CTh

resholdvalue-third

quartile

Sekh

aretal[73]

Prioritizea

ndmap

thec

ausalrelationstr

ucturesindimensio

nsandsubd

imensio

nsof

HR-flexibilityandfirm

perfo

rmance

from

ITindu

stry

perspective

Seleem

etal[74]

Selectandmanagethe

suita

blep

erform

ance

improvem

entinitia

tives

toenhancethe

internal

processeso

fmanufacturin

gcompanies

BSC

TOC

Rank

basedon119877an

d119862

Sharmae

tal[75]

Assessthec

ausalrelationships

amon

glean

criteria

andidentifycriticalonesfor

thes

uccessful

implem

entatio

nof

lean

manufacturin

gTh

resholdvalue-

average

Shen

[76]

Identifythek

eybarriersandtheirinterrelationships

impeding

theu

niversity

techno

logy

transfe

rfro

mam

ultistakeho

lder

perspective

Thresholdvalue-third

quartile

Seyed-Hosseinietal[77]

Analyze

ther

elationbetweencompo

nentso

fasyste

mandprop

osea

metho

dology

for

reprioritizationof

failu

remod

esin

FMEA

Rank

basedon119877minus

119862Ch

ang[78]

Analyze

ther

elationshipbetweencompo

nentso

fasyste

mandou

tline

ageneralalgorithm

for

prioritizationof

failu

remod

esin

FMEA

OWGA

Rank

basedon119877minus

119862Ch

angetal[79]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

GRA

Rank

basedon119877minus

119862Ch

angetal[80]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

TOPS

ISRa

nkbasedon119877minus

119862

Mathematical Problems in Engineering 7

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Liuetal[81]

Con

structthe

influ

entia

lrelations

amon

gfailu

remod

esandcauses

offailu

resa

nddevelopa

fram

eworkforp

rioritizationof

failu

remod

esAHPVIKOR

Mentese

tal[82]

Con

sider

thed

irect-in

directrelationships

betweenfactorsa

ndprop

osea

nintegrated

metho

dology

forrisk

assessmento

fcargo

shipsa

tcoasts

andop

enseas

OWGA

Huang

etal[8]

Identifymajor

indu

stry

inno

vatio

nrequ

irementsandpresentrecon

figured

inno

vatio

npo

licy

portfolio

stodevelopTaiwanrsquosSIPMallind

ustry

GRA

CA1

Threshold

value-experts

LiandTzeng[9]

Disc

over

andillustratethe

keyservices

needed

toattractSIP

usersa

ndSIPproviderstoan

SIP

Mall

Threshold

value-experts

Horng

etal[83]

Identifyther

elationships

andinteractions

amon

gdimensio

nsof

restaurant

spaced

esignfro

mthe

expertrsquosp

erspectiv

eTh

resholdvalue-

average

Chen

etal[84]

Determinec

riticalcore

factorsa

ffectingconsum

erintentionto

dine

atgreenrestaurantsa

nddevelopspecificimprovem

entstrategies

SEMQ

FD

Chengetal[85]

Develo

pathree-tiered

serviceq

ualityim

provem

entm

odelto

identifycritical

educational-service-qualitydeficienciesinho

spita

litytourism

and

leisu

reun

dergradu

ate

programs

IPGAQ

FD

Shiehetal[86]

Evaluatetheimpo

rtance

andconstructthe

causalrelatio

nsof

criteria

from

patientsrsquoview

points

andidentifykeysuccessfactorsforimprovingtheh

ospitalservice

quality

SERV

QUA

Lmod

elTh

resholdvalue-

average

Ranjan

etal[87]

Analyze

andexplaintheinteractio

nrelationships

andim

pactlevelsbetweenevaluatio

ncriteria

anddevelopaframew

orkforp

erform

ance

evaluatio

nof

engineeringdepartmentsin

auniversity

VIKOR

entro

pymetho

dTh

resholdvalue-

average

TanandKu

o[15]

Prioritizefacilitatio

nstrategies

ofruralp

arkandrecreatio

nagencies

from

thep

erspectiv

eof

leisu

reconstraints

Threshold

value-maxim

umvalue

Wuetal[88]

Describethe

contextualrelationships

evaluatedam

ongcriteria

andevaluatetheimpo

rtance

ofthe

criteria

used

inem

ploymentservice

outre

achprogram

person

nel

Thresholdvalue-

average

Sun[89]

Handlethe

innerd

ependencea

ndidentifycore

competences

ofnewlyqu

alified

nurses

Threshold

value-experts

WuandTsai[90]

Describethe

contextualrelatio

nships

amon

gthec

riteriaandevaluatetheimpo

rtance

ofdimensio

nscriteriain

auto

sparep

artsindu

stry

Thresholdvalue-

average

8 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Sun[91]

Identifyandanalyzec

riticalsuccessfactorsin

thee

lectronicd

esignautomationindu

stry

Threshold

value-experts

WuandTsai[92]

Depictthe

causalrelatio

nsandevaluatetheimpo

rtance

ofcriteria

inauto

sparep

artsindu

stry

AHP

Thresholdvalue-

average

Weietal[93]

Reprioritizethe

amendedmod

esin

theS

EMmod

elandestablish

acausalrelationshipmod

elfor

Web-advertisingeffects

Wuetal[24]

Explorethe

factorsh

inderin

gthea

cceptanceo

fusin

ginternalclo

udservices

inau

niversity

TAM

Four

quadrants

Hsu

[94]

Find

thed

eterminantfactorsinflu

encing

blog

desig

nandsim

plify

andvisualizethe

interrelationships

betweencriteria

fore

achfactor

FATh

reshold

value-experts

Hsu

andLee[95]

Explorethe

criticalfactorsinflu

encing

theq

ualityof

blog

interfa

cesa

ndthec

ausalrela

tionships

betweenthesefactors

Leee

tal[96]

Establish

thec

ausalrela

tionshipandthed

egreeo

finterrelationshipof

DTP

Bvaria

bles

(university

library

website)

Wuetal[23]

Explored

ecisive

factorsa

ffectingan

organizatio

nrsquosSoftw

area

saService(SaaS)a

doption

Four

quadrants

Pathariand

Sonar[97]

Analyze

asetof

securitysta

tementsin

inform

ationsecuritypo

licyproceduresand

controlsto

establish

anim

plicithierarchyandrelativ

eimpo

rtance

amon

gthem

Jafarnejad

etal[98]

Classifythec

riteriain

ERPselectioninto

thetwogrou

psof

ldquocauserdquoa

ndldquoeffectrdquoa

ndprop

osea

combinedMCD

Mapproach

toselectthep

roperE

RPsyste

m

Entro

pymetho

dfuzzy

AHP

TsaiandCh

eng[99]

Analyze

KPIsforE

-com

merce

andInternetmarketin

gof

elderly

prod

ucts

BSC

Wangetal[25]

Capturethe

causalrelationships

amon

gdivisio

nsandidentifythosed

ivision

swith

inam

atrix

organizatio

nthatmay

berespon

sibleforthe

poor

perfo

rmance

ofah

igh-tech

facilitydesig

nproject

SIA

Netinflu

ence

matrix

Linetal[100]

Explorethe

core

competences

andinvestigatetheircausea

ndeffectrela

tionships

oftheICdesig

nservicec

ompany

Threshold

value-experts

Chuang

etal[21]

Investigatethe

complex

multid

imensio

naland

dynamicnature

ofmem

bere

ngagem

entb

ehavior

inenvironm

entalprotectionvirtualcom

mun

ities

ISM

Threshold

value-expertsfour

quadrants

Rahm

anandSubram

anian[101]

Identifycriticalfactorsforimplem

entin

gEO

Lcompu

terrecyclin

gop

erations

inreverses

upply

chainandinvestigatethec

ausalrelationshipam

ongthefactors

Thresholdvalue-

average

Hsu

etal[102]

Recogn

izethe

influ

entia

lcriteriaof

carbon

managem

entingreensupp

lychainto

improvethe

overallp

erform

ance

ofsupp

liers

Thresholdvalue

Falatoon

itoosietal[103]

Exam

inec

omplex

causalrelationshipbetweenfactorsingreensupp

lychainmanagem

entand

providea

nevaluatio

nfram

eworkto

selectthem

osteligiblegreensupp

liers

Renetal[104]

Identifykeydrivingfactorsa

ndmap

theirc

ause-effectrelationships

fore

nhancing

the

susta

inabilityof

hydrogen

supp

lychain

Threshold

value-experts

Mud

uliand

Barve[105]

Extractthe

causalrelationships

amon

ggreensupp

lychainmanagem

entb

arrie

rsandestablish

asustainabled

evelop

mentframew

orkin

scaleInd

ianminingindu

strie

s

Mathematical Problems in Engineering 9

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

WuandCh

ang[106]

Identifythec

riticaldimensio

nsandfactorstoim

plem

entg

reen

supp

lychainmanagem

entinthe

electricalandele

ctronicind

ustries

Thresholdvalue-

average

Behera

andMuk

herje

e[107]

Capturer

elationships

andanalyzek

eyinflu

encing

factorsrele

vant

toselectionof

supp

lychain

coordinatio

nschemes

Thresholdvalue-

MMDE

Ahm

edetal[108]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

fore

valuatingsustainableE

OLvehicle

managem

entalternatives

FuzzyAHP

Ahm

edetal[109]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

andprop

osea

nintegrated

mod

elfor

sustainableE

OLvehicle

managem

entalternatives

election

AHPfuzzyA

HP

Miaoetal[110

]Ev

aluatetheimpo

rtance

andun

veiltheimplicitinterrela

tionships

amon

gdifferent

scales

ofCP

Vandconstructa

multiscalemod

elforthe

measuremento

fCPV

ofEV

sHoQ

Threshold

value-expertsrank

basedon119877+

119862Lin[111]

Analyze

interactions

amon

gindu

stria

ldevelo

pmentfactorsandexploreh

owto

establish

the

competitivenesso

fsolar

photovoltaicindu

stry

Porterrsquos

Diamon

dmod

el

AzarnivandandCh

itsaz

[112]

Quantify

theinterlin

kagesa

mon

gfund

amentalanthrop

ogenicindicatorsandprop

osea

syste

maticapproach

forw

ater

shortage

mitigatio

nin

thea

ridregion

seD

PSIRA

HP

COPR

AS-G

Chen

etal[113]

Quantify

theinfl

uenceo

nPM

25by

otherfactorsin

thew

eather

syste

mandidentifythem

ost

impo

rtantfactorsforP

M25

RMFo

urqu

adrants

dosM

uchangos

etal[114

]As

sesstheb

arrie

rsto

mun

icipalsolid

wastemanagem

entp

olicyplanning

andidentifythem

ost

onerou

sbarrie

rsto

thee

ffectiveimplem

entatio

nof

thep

olicy

ISM

Netinflu

ence

matrix

Guo

etal[115]

EvaluateandinvestigategreencorporateC

SRindicatorsof

manufacturin

gcorporations

from

agreenindu

strylawperspective

Four

quadrants

Chen

andCh

i[116

]Ex

plorek

eyfactorso

fChinarsquosCS

Rfro

mthep

erspectiv

eofaccou

ntingexperts

Changetal[117

]Identifykeystr

ategicfactorsintheimplem

entatio

nof

CSRin

airline

indu

stry

Leee

tal[118]

Calculatethe

causalrelationshipandinteractionlevelbetweenTA

Mvaria

bles

andfin

dthec

ore

varia

bles

form

anagem

ento

rimprovem

entw

hileintro

ducing

anew

etchingplasmatechn

olog

yFo

urqu

adrants

Wu[119]

Determinethe

causalrelationships

betweentheK

PIso

fthe

BSCandlin

kthem

into

astrategy

map

forb

anking

institutio

nsBS

C

Chienetal[22]

Identifyrelatio

nships

betweenris

kfactorsa

ndassesscriticalrisk

factorsfor

BIM

projects

Four

quadrants

10 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Wangetal[26]

Evaluatethep

erform

ance

ofdesig

ndelay

factorsa

ndidentifykeyfactorsthatd

rived

esigndelay

sof

afacilityconstructio

nproject

ISA

Netinflu

ence

matrix

Tzeng[19

]Investigatethe

relationshipbetweenfactorsa

ffectingparolebo

ardsrsquodecision

makingin

Taiwan

Simplified

norm

alized

total-relation

matrix

threshold

value

Gazibey

etal[120]

Analyze

thec

ause

andeffectrelations

amon

gthec

riteriaaffectin

gmainbattletankselection

Thresholdvalue-

average

Type

3interrelationships

andcriteria

weights

Khalili-D

amgh

anietal[121]

Determinethe

relativ

eimpo

rtance

weightsof

compensatoryob

jectivefun

ctions

andprop

osea

hybrid

multip

leob

jectivem

etaheuris

ticalgorithm

tosolveland-uses

uitabilityanalysisand

planning

prob

lem

AHP

Khazaietal[29]

Analyze

directandindirectdepend

encies

with

insocialandindu

stria

lvulnerabilityindicatorsand

developaframew

orkforspatia

lassessm

ento

find

ustrialand

socialvulnerabilityto

indirect

disaste

rlosses

Threshold

valuedepend

ency

weights

Tseng[122]

Resolvec

riteriainterdependencyrelationships

weightsandprop

osea

hybrid

metho

dto

evaluate

serviceq

ualityexpectationin

hotspringho

telrsquosrank

ingprob

lem

FuzzyTO

PSIS

Innerd

ependence

matrix

Quadere

tal[123]

Determinethe

causea

ndeffectrelationships

amon

gcriteria

andevaluatethec

riticalcriteria

for

CO2capturea

ndsto

rage

intheironandste

elindu

stry

Criteria

weights-

vector

leng

thth

reshold

value

Quadera

ndAhm

ed[124]

Identifycriticalfactorsfore

valuatingalternativeiron-makingtechno

logies

with

carbon

capture

andsto

rage

syste

ms

FuzzyAHP

Criteria

weights-

vector

leng

thth

reshold

value

Seyedh

osseinietal[17]

Identifythec

ause

andeffectrela

tionships

amon

glean

objectives

andprop

osed

asystematicamp

logicalm

etho

dfora

utopartmanufacturersto

determ

inethe

companyrsquoslean

strategymap

BSC

Innerd

ependence

matrix

weights-119877+

119862Cebi[27]

Determineimpo

rtance

degreeso

fwebsited

esignparametersb

ased

oninteractions

andtypeso

fwebsites

Thresholdvalue-

averagedeterm

ining

weightsusing119877+

119862Yazdani-C

hamzini

etal[28]

Analyze

interdependencea

nddepend

encies

andcompu

tetheg

lobalw

eightsfore

valuation

indicatorsandprop

osea

newhybrid

mod

elto

selectthes

trategyof

investingin

apriv

ates

ector

AHPfuzzy

TOPS

IS

Thresholdvalue-

expertsweights-119877+

119862No

teB

ackpropagatio

nneuralnetworkBP

NNbalancedscorecardBS

Cbu

ildinginformationmod

elingBIMcluste

ranalysisC

A1conjoint

analysis

CA2corporatesocialrespo

nsibilityC

SRcustomerperceived

valueCP

Vdata

envelopm

enta

nalysis

DEA

decom

posedtheory

ofplannedbehaviorD

TPB

dominance-based

roug

hseta

pproach

DRS

Aelectric

vehicle

EV

enhanced

drivingforce-pressure-state-im

pact-

respon

seeDPS

IRenterprise

resource

planning

ERP

end

-of-lifeE

OLfactor

analysis

FAfailure

mod

eand

effectanalysisFMEA

fuzzy

cogn

itive

mapFCM

fuzzy

inferences

ystemFISformalconceptanalysis

FC

Agap

analysis

GAgreyc

omplex

prop

ortio

nalassessm

entCO

PRAS-Ggreyr

elationalanalysisG

RAhou

seso

fqualityHoQ

impo

rtance-perform

ance

analysis

IPAimpo

rtance-perform

ance

andgapanalysis

IPGAimpo

rtance-satisfactio

nanalysis

ISAinformationtechno

logyITinterpretiv

estructuralm

odeling

ISM

integratedcircuitICkey

perfo

rmance

indicatorKP

Imaxim

alentro

pyorderedweightedaveraging

ME-OWAm

ultip

leregressio

nanalysis

MRA

ordered

weightedgeom

etric

averagingOWGApatentcitatio

nanalysis

PCApatentcoclassificatio

nanalysis

PCCA

relationmapR

Msatisfi

edim

portance

analysis

SIAsiliconintellectualp

ropertyor

Semicon

ductor-Intellectual-P

ropertySIP

socialnetworkanalysis

SNAstructuralequ

ationmod

elingSE

Mtechn

olog

yacceptance

mod

elTA

Mtheoryof

constraintsTO

Cvaria

blec

onsis

tencyDRS

AV

C-DRS

A

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Page 3: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

Mathematical Problems in Engineering 3

All elements in the matrix 119883 are complying with 0 le 119909119894119895 lt1 0 le sum119899119895=1 119909119894119895 le 1 and at least one 119894 such that sum119899119895=1 119911119894119895 le 119904Step 3 (construct the total-influence matrix 119879) Using thenormalized direct-influence matrix 119883 the total-influencematrix 119879 = [119905119894119895]119899times119899 is then computed by summing the directeffects and all of the indirect effects by

119879 = 119883 + 1198832 + 1198833 + sdot sdot sdot + 119883ℎ = 119883 (119868 minus 119883)minus1 when ℎ 997888rarr infin (4)

in which 119868 is denoted as an identity matrix

Step 4 (produce the influential relation map (IRM)) At thisstep the vectors 119877 and 119862 representing the sum of the rowsand the sum of the columns from the total-influence matrix119879 are defined by the following formulas

119877 = [119903119894]119899times1 = [[119899sum119895=1

119905119894119895]]119899times1

119862 = [119888119895]1times119899 = [119899sum119894=1

119905119894119895]119879

1times119899

(5)

where 119903119894 is the 119894th row sum in the matrix 119879 and displays thesum of the direct and indirect effects dispatching from factor119865119894 to the other factors Similarly 119888119895 is the 119895th column sum inthematrix119879 and depicts the sum of direct and indirect effectsthat factor 119865119895 is receiving from the other factors

Let 119894 = 119895 and 119894 119895 isin 1 2 119899 the horizontal axisvector (119877 + 119862) named ldquoProminencerdquo illustrates the strengthof influences that are given and received of the factor Thatis (119877 + 119862) stands for the degree of central role that the factorplays in the systemAlike the vertical axis vector (119877minus119862) calledldquoRelationrdquo shows the net effect that the factor contributes tothe system If (119903119895 minus 119888119895) is positive then the factor 119865119895 has anet influence on the other factors and can be grouped intocause group if (119903119895 minus 119888119895) is negative then the factor 119865119895 is beinginfluenced by the other factors on the whole and should begrouped into effect group Finally an IRM can be created bymapping the dataset of (119877+119862119877minus119862) which provides valuableinsights for decision making

311 Observations and Findings Table 1 summarizes all theclassical DEMATEL studies based on the particular purposeof using DEMATEL the topic of decision making andother methods combined According to the distinct usageof the DEMATEL method the current classical DEMATELresearches can be classified into three types the first typeis merely clarifying the interrelationships between factors orcriteria the second type is identifying key factors based onthe causal relationships and the degrees of interrelationshipbetween them the third type is determining criteria weightsby analyzing the interrelationships and impact levels ofcriteria

In Table 1 we have provided an overview on the existingapplications of the classical DEMATEL for solving compli-cated and intertwined problems in many fields based onwhich we now point out some critical steps added to theoriginal approach

Step 4-1 (set a threshold value to draw the IRM) In the abovethe IRM is constructed based on the information from thematrix 119879 to explain the structure relations of factors But insome situations the IRM will be too complex to show thevaluable information for decision making if all the relationsare considered Therefore a threshold value 120579 is set in manystudies to filter out negligible effectsThat is only the elementof matrix 119879 whose influence level is greater than the value of120579 is selected and converted into an IRM

If the threshold value is too lowmany factors are includedand the IRMwill be too complex to comprehend In contrastsome important factors may be excluded if the thresholdvalue is too high In the literature the threshold value 120579 isusually determined by experts through discussions [10 11]the results of literature review the brainstorming technique[12] the maximum mean deentropy (MMDE) [13] theaverage of all elements in the matrix 119879 [14] or the maximumvalue of the diagonal elements of the matrix 119879 [15]

Step 4-2 (obtain the inner dependence matrix 1198791015840) When thetotal-influence matrix 119879 is produced in [16 17] an innerdependence matrix 1198791015840 is acquired by normalizing the matrix119879 so that each column sum is equal to 1 But in [18] the innerdependencematrix1198791015840 is derived based on the threshold value120579 and only the factors whose effects in the matrix 119879 are largerthan 120579 are shown in the matrix 1198791015840

To interpret the results easily and keep the complexity ofthe system manageable Tzeng [19] established a simplifiednormalized total-influence matrix 119904 using a normalizationmethod and the threshold value 120579 First the normalized total-influencematrix = [119894119895]119899times119899 is calculated by using (6) to forcethe values of the matrix 119879within the scope of a measurementscale

119894119895 = (119896 minus 0) (119905119894119895 minusmin 119905119894119895)max 119905119894119895 minusmin 119905119894119895 (6)

where 119896 is the highest score for measuring the degree ofrelative impact between factors and 119896 = 4 if the integralscale of 0 to 4 is used Then the simplified normalized total-influence matrix 119904 = [119904119894119895]119899times119899 is obtained by eliminatinginsignificant effects in the matrix based on the thresholdvalue 120579 That is

119904119894119895 = 119894119895 if 119894119895 gt 1205790 if 119894119895 le 120579 (7)

Step 4-21015840 (divide the IRM into four quadrants) Once an IRMis acquired eight of the classical DEMATEL studies classifiedthe factors in a complicated system into four quadrantsaccording to their locations in the diagram In [20ndash22] theIRM is divided into four quadrants I to IV as displayed in

4 Mathematical Problems in Engineering

Table1Va

rious

applications

ofthec

lassicalDEM

ATEL

Papers

Research

purposes

Com

binatio

nsRe

marks

Type

1interrelationships

BEfea

ndOFE

fe[42]

Specify

theinfl

uenced

egrees

ofthep

atient

perceivedvalues

whenapplying

lean

health-care

managem

entinan

emergencydepartment

Thresholdvalue-

average

Malekzadehetal[43]

Investigatethe

causea

ndeffectrelations

forthe

dimensio

nsandcompo

nentso

forganizational

intelligenceinIranianpu

blicun

iversities

Thresholdvalue

Ranjan

etal[44

]Ad

dressthe

interrelationships

betweendifferent

evaluatio

ncriteria

ofIndian

Railw

ayzones

VIKOR

Thresholdvalue-

average

Tzengetal[10]

Addressthe

depend

entrelations

ofevaluatio

ncriteria

andprop

osea

hybrid

MCD

Mmod

elfor

evaluatin

gintertwined

effectsin

e-learning

programs

FAA

HPfuzzy

integral

Threshold

value-experts

Huetal[45]

Establish

thec

ausalrelationshipandextent

ofmutualimpactam

ongqu

ality

features

andpu

tforth

adecision

analysismetho

dology

toremovep

otentia

lproblem

sfrom

thec

onventionalIPA

mod

elBP

NN

Huetal[46

]Analyze

thec

ause-effectrelationshipam

ongdifferent

quality

characteris

ticstomaker

evision

sto

thetraditio

nalIPA

mod

elandfin

dthec

orep

roblem

sinvolvedwith

winning

orders

GAM

RA

Chengetal[47]

Explorethe

conn

ectio

nbetweenserviceq

ualityattributes

andthes

ervice

quality

improvem

ent

priorityof

fine-dining

restaurantsa

nduseitasa

referencefor

serviceq

ualitystr

ategyplanning

andresource

reorganizing

IPGA

Hsie

handYeh[48]

Exam

inec

ause

andeffectrela

tions

offactorsinfl

uencingthe

serviceq

ualityinfastfood

restaurants

Thresholdvalue-

average

Chiu

etal[49]

Analyze

relatio

nships

ofcusto

mer

buying

decisio

nfactorsa

ndprovidea

marketin

gstr

ategy

planning

forfi

rmsintheL

CD-TVmarket

Hoetal[50]

Analyze

thec

ause-effectrelationbetweenqu

ality

characteris

ticsa

ndbu

ildam

etho

dology

ofsupp

lierq

ualityperfo

rmance

assessmenttoim

proves

upplierq

ualitythroug

hop

timizing

order-winnersandqu

alifiers

IPAM

RA

Tsaietal[51]

Determinethe

causalrelationships

ofandinteractiveinfl

uencea

mon

gcriteria

andprop

osea

mixed

mod

elto

evaluatejobsatisfactionin

high

-tech

indu

strie

sIPA

Najmiand

Makui

[52]

Und

ersta

ndther

elationshipbetweencomparis

onmetric

sand

prop

osea

conceptualmod

elfor

measurin

gsupp

lychainperfo

rmance

AHP

Shafiee

etal[53]

Determinethe

relationships

betweenfour

perspectives

ofBS

Candprop

osea

napproach

toevaluatethep

erform

ance

ofsupp

lychain

DEA

BSC

Thresholdvalue-

average

ShaikandAb

dul-K

ader

[16]

Und

ersta

ndtheinterdepend

ence

amon

gperfo

rmance

factorsa

nddevelopar

everse

logistics

enterpris

eperform

ance

measurementm

odel

BSC

Innerd

ependence

matrix

Mathematical Problems in Engineering 5

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

LinandTzeng[11]

Determinethe

relatio

nshipbetweenthee

valuationcriteria

contrib

utingindu

stryclu

stersand

establish

theirv

alue

structuresa

ndbu

ildav

alue-created

syste

mof

science(techno

logy)p

ark

Threshold

value-experts

LinandSun[18]

Exam

inethe

impactso

fand

determ

inethe

relationships

amon

gdifferent

drivingforces

forthe

grow

thof

indu

strialcluste

rs

Threshold

value-expertsinner

depend

ence

matrix

WangandHsueh

[54]

Recogn

izethe

causalrelationships

betweendesig

nattributes

andmarketin

grequ

irementsand

prop

osea

napproach

toincorporatec

ustomer

preference

andperceptio

ninto

prod

uct

developm

ent

AHPKa

nomod

el

WangandSh

ih[55]

Identifytheimpactso

ffun

ctionalattributes

oncusto

mer

requ

irementsandpresenta

fram

ework

toincorporatec

ustomer

preferencesintoprod

uctd

evelo

pment

CA1QFD

TO

PSIS

Koetal[56]

Analyze

directandindirectim

pactsa

mon

gvario

ustechno

logy

areasa

ndpresenta

combined

approach

toconstructtechn

olog

yim

pactnetworks

forR

ampDplanning

usingpatents

SNA

Yoon

etal[57]

Assesstechno

logicalimpactsa

nddegree

ofcauseo

reffectam

ongtechno

logy

areasw

ithin

the

Korean

techno

logy

syste

mandob

servetheirdynamictre

nds

PCCA

Shen

andTzeng[58]

Explorethe

cause-effectrelationships

amon

gthea

ttributes

inthes

trong

decisio

nrulesa

ndprop

osea

mod

elfortacklingthev

alue

stock

selectionprob

lem

DRS

AFCA

Altu

ntas

andDereli

[59]

Establish

causalrelationships

amon

gtechno

logies

andprop

osea

napproach

forp

rioritizing

investmentp

rojectsfrom

theg

overnm

entrsquos

perspective

PCA

Thresholdvalue-

average

Shen

andTzeng[60]

Explorethe

complex

relationshipam

ongfin

ancialindicatorsandim

provefuturefi

nancial

perfo

rmance

oftheITindu

stry

VC-D

RSAFIS

Leea

ndLin[13]

Find

theinterrelationshipof

financialratio

sidentified

bymanagerso

fshipp

ingcompanies

and

financialexpertsa

ndcompare

theirc

ognitio

nmapsb

ycoun

tryandexpertgrou

pTh

resholdvalue-

MMDE

W-K

Tan

andY-J

Tan[61]

Analyze

howdifferent

factorsinteractand

collectively

contrib

utetothes

uccessfultransform

ation

anddiffu

sionof

thes

mart-c

ard-basede-micropaym

entm

ultip

urpo

sescheme

Azadehetal[12]

Evaluatetheimpactdegree

ofleannessfactorsa

ndpresentsac

omprehensiv

eapp

roachfor

evaluatin

gandop

timizingtheleann

essd

egreeo

forganizations

(lean

prod

uctio

n)

DEA

fuzzy

DEA

FCM

AHP

Thresholdvalue-

average

Sara

etal[14]

Assessrelativeimpo

rtance

andmutualinfl

uenceo

fbarrie

rsforc

arbo

ncapturea

ndsto

rage

deployment

AHP

Thresholdvalue-

average

Liaw

etal[62]

Analyze

theind

irectrelations

betweensubsystemsa

ndcompo

nentsa

ndprop

osea

reliability

allocatio

nmetho

dto

solvethe

fund

amentalproblem

sofcon

ventionalreliabilityappo

rtionm

ent

metho

dsME-OWA

Type

2interrelationships

andkeyfactors

AlaeiandAlro

aia[

63]

Identifyandprioritizethe

factorsa

ffectingandaffectedby

thep

erform

ance

ofsm

alland

medium

enterpris

es

Bacudioetal[64

]Analyze

cause-effectrelationships

ofbarriersto

implem

entin

gindu

stria

lsym

biosisnetworks

inan

indu

strialp

ark

Thresholdvalue-

averageinner

depend

ence

matrix

Balkovskayaa

ndFilneva[

65]

Identifycausalrelationships

betweenthek

eyevaluatio

nindicatorsof

bank

ingperfo

rmance

aswell

asdefin

ingthem

oststrategicallyim

portantind

icators

BSC

Threshold

value-second

quartile

6 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Chen

[66]

Estim

atethe

impo

rtance

ofthes

ervice

factorso

fanacadem

iclib

rary

andidentifythec

ausal

factors

Threshold

value-experts

GovindanandCh

audh

uri[67]

Analyze

ther

isksfaced

bythird

-partylogisticsservice

providersinrelationto

oneo

fitscusto

mers

andextractthe

causalrelationships

amon

gthem

Govindanetal[68]

Investigatethe

influ

entia

lstre

ngth

offactorso

nadop

tionof

greensupp

lychainmanagem

ent

practic

esin

theInd

ianminingindu

stry

AHP

Thresholdvalue-

average

Gandh

ietal[69]

Evaluatesuccessfactorsin

implem

entatio

nof

greensupp

lychainmanagem

entinIndian

manufacturin

gindu

strie

s

Hwangetal[70]

Explorethe

causalrelatio

nships

amon

gdecisio

nfactorsrelatingto

greensupp

lychains

inthe

semicon

ductor

indu

stry

Hwangetal[71]

Identifydeterm

inantsandtheirc

ausalrela

tionships

affectin

gthea

doptionof

cloud

compu

tingin

sciencea

ndtechno

logy

institutio

nsTh

reshold

value-120583+

32120590Hwangetal[20]

Assessthed

ynam

icris

kinterdependenciesfor

distinctprojectp

hasesa

ndidentifycriticalrisk

factors

Threshold

value-experts

Rahimniaa

ndKa

rgozar

[72]

Disc

over

causalrelationships

betweenob

jectives

inun

iversitystr

ategymap

andprioritizethem

forresou

rcea

llocatio

nBS

CTh

resholdvalue-third

quartile

Sekh

aretal[73]

Prioritizea

ndmap

thec

ausalrelationstr

ucturesindimensio

nsandsubd

imensio

nsof

HR-flexibilityandfirm

perfo

rmance

from

ITindu

stry

perspective

Seleem

etal[74]

Selectandmanagethe

suita

blep

erform

ance

improvem

entinitia

tives

toenhancethe

internal

processeso

fmanufacturin

gcompanies

BSC

TOC

Rank

basedon119877an

d119862

Sharmae

tal[75]

Assessthec

ausalrelationships

amon

glean

criteria

andidentifycriticalonesfor

thes

uccessful

implem

entatio

nof

lean

manufacturin

gTh

resholdvalue-

average

Shen

[76]

Identifythek

eybarriersandtheirinterrelationships

impeding

theu

niversity

techno

logy

transfe

rfro

mam

ultistakeho

lder

perspective

Thresholdvalue-third

quartile

Seyed-Hosseinietal[77]

Analyze

ther

elationbetweencompo

nentso

fasyste

mandprop

osea

metho

dology

for

reprioritizationof

failu

remod

esin

FMEA

Rank

basedon119877minus

119862Ch

ang[78]

Analyze

ther

elationshipbetweencompo

nentso

fasyste

mandou

tline

ageneralalgorithm

for

prioritizationof

failu

remod

esin

FMEA

OWGA

Rank

basedon119877minus

119862Ch

angetal[79]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

GRA

Rank

basedon119877minus

119862Ch

angetal[80]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

TOPS

ISRa

nkbasedon119877minus

119862

Mathematical Problems in Engineering 7

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Liuetal[81]

Con

structthe

influ

entia

lrelations

amon

gfailu

remod

esandcauses

offailu

resa

nddevelopa

fram

eworkforp

rioritizationof

failu

remod

esAHPVIKOR

Mentese

tal[82]

Con

sider

thed

irect-in

directrelationships

betweenfactorsa

ndprop

osea

nintegrated

metho

dology

forrisk

assessmento

fcargo

shipsa

tcoasts

andop

enseas

OWGA

Huang

etal[8]

Identifymajor

indu

stry

inno

vatio

nrequ

irementsandpresentrecon

figured

inno

vatio

npo

licy

portfolio

stodevelopTaiwanrsquosSIPMallind

ustry

GRA

CA1

Threshold

value-experts

LiandTzeng[9]

Disc

over

andillustratethe

keyservices

needed

toattractSIP

usersa

ndSIPproviderstoan

SIP

Mall

Threshold

value-experts

Horng

etal[83]

Identifyther

elationships

andinteractions

amon

gdimensio

nsof

restaurant

spaced

esignfro

mthe

expertrsquosp

erspectiv

eTh

resholdvalue-

average

Chen

etal[84]

Determinec

riticalcore

factorsa

ffectingconsum

erintentionto

dine

atgreenrestaurantsa

nddevelopspecificimprovem

entstrategies

SEMQ

FD

Chengetal[85]

Develo

pathree-tiered

serviceq

ualityim

provem

entm

odelto

identifycritical

educational-service-qualitydeficienciesinho

spita

litytourism

and

leisu

reun

dergradu

ate

programs

IPGAQ

FD

Shiehetal[86]

Evaluatetheimpo

rtance

andconstructthe

causalrelatio

nsof

criteria

from

patientsrsquoview

points

andidentifykeysuccessfactorsforimprovingtheh

ospitalservice

quality

SERV

QUA

Lmod

elTh

resholdvalue-

average

Ranjan

etal[87]

Analyze

andexplaintheinteractio

nrelationships

andim

pactlevelsbetweenevaluatio

ncriteria

anddevelopaframew

orkforp

erform

ance

evaluatio

nof

engineeringdepartmentsin

auniversity

VIKOR

entro

pymetho

dTh

resholdvalue-

average

TanandKu

o[15]

Prioritizefacilitatio

nstrategies

ofruralp

arkandrecreatio

nagencies

from

thep

erspectiv

eof

leisu

reconstraints

Threshold

value-maxim

umvalue

Wuetal[88]

Describethe

contextualrelationships

evaluatedam

ongcriteria

andevaluatetheimpo

rtance

ofthe

criteria

used

inem

ploymentservice

outre

achprogram

person

nel

Thresholdvalue-

average

Sun[89]

Handlethe

innerd

ependencea

ndidentifycore

competences

ofnewlyqu

alified

nurses

Threshold

value-experts

WuandTsai[90]

Describethe

contextualrelatio

nships

amon

gthec

riteriaandevaluatetheimpo

rtance

ofdimensio

nscriteriain

auto

sparep

artsindu

stry

Thresholdvalue-

average

8 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Sun[91]

Identifyandanalyzec

riticalsuccessfactorsin

thee

lectronicd

esignautomationindu

stry

Threshold

value-experts

WuandTsai[92]

Depictthe

causalrelatio

nsandevaluatetheimpo

rtance

ofcriteria

inauto

sparep

artsindu

stry

AHP

Thresholdvalue-

average

Weietal[93]

Reprioritizethe

amendedmod

esin

theS

EMmod

elandestablish

acausalrelationshipmod

elfor

Web-advertisingeffects

Wuetal[24]

Explorethe

factorsh

inderin

gthea

cceptanceo

fusin

ginternalclo

udservices

inau

niversity

TAM

Four

quadrants

Hsu

[94]

Find

thed

eterminantfactorsinflu

encing

blog

desig

nandsim

plify

andvisualizethe

interrelationships

betweencriteria

fore

achfactor

FATh

reshold

value-experts

Hsu

andLee[95]

Explorethe

criticalfactorsinflu

encing

theq

ualityof

blog

interfa

cesa

ndthec

ausalrela

tionships

betweenthesefactors

Leee

tal[96]

Establish

thec

ausalrela

tionshipandthed

egreeo

finterrelationshipof

DTP

Bvaria

bles

(university

library

website)

Wuetal[23]

Explored

ecisive

factorsa

ffectingan

organizatio

nrsquosSoftw

area

saService(SaaS)a

doption

Four

quadrants

Pathariand

Sonar[97]

Analyze

asetof

securitysta

tementsin

inform

ationsecuritypo

licyproceduresand

controlsto

establish

anim

plicithierarchyandrelativ

eimpo

rtance

amon

gthem

Jafarnejad

etal[98]

Classifythec

riteriain

ERPselectioninto

thetwogrou

psof

ldquocauserdquoa

ndldquoeffectrdquoa

ndprop

osea

combinedMCD

Mapproach

toselectthep

roperE

RPsyste

m

Entro

pymetho

dfuzzy

AHP

TsaiandCh

eng[99]

Analyze

KPIsforE

-com

merce

andInternetmarketin

gof

elderly

prod

ucts

BSC

Wangetal[25]

Capturethe

causalrelationships

amon

gdivisio

nsandidentifythosed

ivision

swith

inam

atrix

organizatio

nthatmay

berespon

sibleforthe

poor

perfo

rmance

ofah

igh-tech

facilitydesig

nproject

SIA

Netinflu

ence

matrix

Linetal[100]

Explorethe

core

competences

andinvestigatetheircausea

ndeffectrela

tionships

oftheICdesig

nservicec

ompany

Threshold

value-experts

Chuang

etal[21]

Investigatethe

complex

multid

imensio

naland

dynamicnature

ofmem

bere

ngagem

entb

ehavior

inenvironm

entalprotectionvirtualcom

mun

ities

ISM

Threshold

value-expertsfour

quadrants

Rahm

anandSubram

anian[101]

Identifycriticalfactorsforimplem

entin

gEO

Lcompu

terrecyclin

gop

erations

inreverses

upply

chainandinvestigatethec

ausalrelationshipam

ongthefactors

Thresholdvalue-

average

Hsu

etal[102]

Recogn

izethe

influ

entia

lcriteriaof

carbon

managem

entingreensupp

lychainto

improvethe

overallp

erform

ance

ofsupp

liers

Thresholdvalue

Falatoon

itoosietal[103]

Exam

inec

omplex

causalrelationshipbetweenfactorsingreensupp

lychainmanagem

entand

providea

nevaluatio

nfram

eworkto

selectthem

osteligiblegreensupp

liers

Renetal[104]

Identifykeydrivingfactorsa

ndmap

theirc

ause-effectrelationships

fore

nhancing

the

susta

inabilityof

hydrogen

supp

lychain

Threshold

value-experts

Mud

uliand

Barve[105]

Extractthe

causalrelationships

amon

ggreensupp

lychainmanagem

entb

arrie

rsandestablish

asustainabled

evelop

mentframew

orkin

scaleInd

ianminingindu

strie

s

Mathematical Problems in Engineering 9

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

WuandCh

ang[106]

Identifythec

riticaldimensio

nsandfactorstoim

plem

entg

reen

supp

lychainmanagem

entinthe

electricalandele

ctronicind

ustries

Thresholdvalue-

average

Behera

andMuk

herje

e[107]

Capturer

elationships

andanalyzek

eyinflu

encing

factorsrele

vant

toselectionof

supp

lychain

coordinatio

nschemes

Thresholdvalue-

MMDE

Ahm

edetal[108]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

fore

valuatingsustainableE

OLvehicle

managem

entalternatives

FuzzyAHP

Ahm

edetal[109]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

andprop

osea

nintegrated

mod

elfor

sustainableE

OLvehicle

managem

entalternatives

election

AHPfuzzyA

HP

Miaoetal[110

]Ev

aluatetheimpo

rtance

andun

veiltheimplicitinterrela

tionships

amon

gdifferent

scales

ofCP

Vandconstructa

multiscalemod

elforthe

measuremento

fCPV

ofEV

sHoQ

Threshold

value-expertsrank

basedon119877+

119862Lin[111]

Analyze

interactions

amon

gindu

stria

ldevelo

pmentfactorsandexploreh

owto

establish

the

competitivenesso

fsolar

photovoltaicindu

stry

Porterrsquos

Diamon

dmod

el

AzarnivandandCh

itsaz

[112]

Quantify

theinterlin

kagesa

mon

gfund

amentalanthrop

ogenicindicatorsandprop

osea

syste

maticapproach

forw

ater

shortage

mitigatio

nin

thea

ridregion

seD

PSIRA

HP

COPR

AS-G

Chen

etal[113]

Quantify

theinfl

uenceo

nPM

25by

otherfactorsin

thew

eather

syste

mandidentifythem

ost

impo

rtantfactorsforP

M25

RMFo

urqu

adrants

dosM

uchangos

etal[114

]As

sesstheb

arrie

rsto

mun

icipalsolid

wastemanagem

entp

olicyplanning

andidentifythem

ost

onerou

sbarrie

rsto

thee

ffectiveimplem

entatio

nof

thep

olicy

ISM

Netinflu

ence

matrix

Guo

etal[115]

EvaluateandinvestigategreencorporateC

SRindicatorsof

manufacturin

gcorporations

from

agreenindu

strylawperspective

Four

quadrants

Chen

andCh

i[116

]Ex

plorek

eyfactorso

fChinarsquosCS

Rfro

mthep

erspectiv

eofaccou

ntingexperts

Changetal[117

]Identifykeystr

ategicfactorsintheimplem

entatio

nof

CSRin

airline

indu

stry

Leee

tal[118]

Calculatethe

causalrelationshipandinteractionlevelbetweenTA

Mvaria

bles

andfin

dthec

ore

varia

bles

form

anagem

ento

rimprovem

entw

hileintro

ducing

anew

etchingplasmatechn

olog

yFo

urqu

adrants

Wu[119]

Determinethe

causalrelationships

betweentheK

PIso

fthe

BSCandlin

kthem

into

astrategy

map

forb

anking

institutio

nsBS

C

Chienetal[22]

Identifyrelatio

nships

betweenris

kfactorsa

ndassesscriticalrisk

factorsfor

BIM

projects

Four

quadrants

10 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Wangetal[26]

Evaluatethep

erform

ance

ofdesig

ndelay

factorsa

ndidentifykeyfactorsthatd

rived

esigndelay

sof

afacilityconstructio

nproject

ISA

Netinflu

ence

matrix

Tzeng[19

]Investigatethe

relationshipbetweenfactorsa

ffectingparolebo

ardsrsquodecision

makingin

Taiwan

Simplified

norm

alized

total-relation

matrix

threshold

value

Gazibey

etal[120]

Analyze

thec

ause

andeffectrelations

amon

gthec

riteriaaffectin

gmainbattletankselection

Thresholdvalue-

average

Type

3interrelationships

andcriteria

weights

Khalili-D

amgh

anietal[121]

Determinethe

relativ

eimpo

rtance

weightsof

compensatoryob

jectivefun

ctions

andprop

osea

hybrid

multip

leob

jectivem

etaheuris

ticalgorithm

tosolveland-uses

uitabilityanalysisand

planning

prob

lem

AHP

Khazaietal[29]

Analyze

directandindirectdepend

encies

with

insocialandindu

stria

lvulnerabilityindicatorsand

developaframew

orkforspatia

lassessm

ento

find

ustrialand

socialvulnerabilityto

indirect

disaste

rlosses

Threshold

valuedepend

ency

weights

Tseng[122]

Resolvec

riteriainterdependencyrelationships

weightsandprop

osea

hybrid

metho

dto

evaluate

serviceq

ualityexpectationin

hotspringho

telrsquosrank

ingprob

lem

FuzzyTO

PSIS

Innerd

ependence

matrix

Quadere

tal[123]

Determinethe

causea

ndeffectrelationships

amon

gcriteria

andevaluatethec

riticalcriteria

for

CO2capturea

ndsto

rage

intheironandste

elindu

stry

Criteria

weights-

vector

leng

thth

reshold

value

Quadera

ndAhm

ed[124]

Identifycriticalfactorsfore

valuatingalternativeiron-makingtechno

logies

with

carbon

capture

andsto

rage

syste

ms

FuzzyAHP

Criteria

weights-

vector

leng

thth

reshold

value

Seyedh

osseinietal[17]

Identifythec

ause

andeffectrela

tionships

amon

glean

objectives

andprop

osed

asystematicamp

logicalm

etho

dfora

utopartmanufacturersto

determ

inethe

companyrsquoslean

strategymap

BSC

Innerd

ependence

matrix

weights-119877+

119862Cebi[27]

Determineimpo

rtance

degreeso

fwebsited

esignparametersb

ased

oninteractions

andtypeso

fwebsites

Thresholdvalue-

averagedeterm

ining

weightsusing119877+

119862Yazdani-C

hamzini

etal[28]

Analyze

interdependencea

nddepend

encies

andcompu

tetheg

lobalw

eightsfore

valuation

indicatorsandprop

osea

newhybrid

mod

elto

selectthes

trategyof

investingin

apriv

ates

ector

AHPfuzzy

TOPS

IS

Thresholdvalue-

expertsweights-119877+

119862No

teB

ackpropagatio

nneuralnetworkBP

NNbalancedscorecardBS

Cbu

ildinginformationmod

elingBIMcluste

ranalysisC

A1conjoint

analysis

CA2corporatesocialrespo

nsibilityC

SRcustomerperceived

valueCP

Vdata

envelopm

enta

nalysis

DEA

decom

posedtheory

ofplannedbehaviorD

TPB

dominance-based

roug

hseta

pproach

DRS

Aelectric

vehicle

EV

enhanced

drivingforce-pressure-state-im

pact-

respon

seeDPS

IRenterprise

resource

planning

ERP

end

-of-lifeE

OLfactor

analysis

FAfailure

mod

eand

effectanalysisFMEA

fuzzy

cogn

itive

mapFCM

fuzzy

inferences

ystemFISformalconceptanalysis

FC

Agap

analysis

GAgreyc

omplex

prop

ortio

nalassessm

entCO

PRAS-Ggreyr

elationalanalysisG

RAhou

seso

fqualityHoQ

impo

rtance-perform

ance

analysis

IPAimpo

rtance-perform

ance

andgapanalysis

IPGAimpo

rtance-satisfactio

nanalysis

ISAinformationtechno

logyITinterpretiv

estructuralm

odeling

ISM

integratedcircuitICkey

perfo

rmance

indicatorKP

Imaxim

alentro

pyorderedweightedaveraging

ME-OWAm

ultip

leregressio

nanalysis

MRA

ordered

weightedgeom

etric

averagingOWGApatentcitatio

nanalysis

PCApatentcoclassificatio

nanalysis

PCCA

relationmapR

Msatisfi

edim

portance

analysis

SIAsiliconintellectualp

ropertyor

Semicon

ductor-Intellectual-P

ropertySIP

socialnetworkanalysis

SNAstructuralequ

ationmod

elingSE

Mtechn

olog

yacceptance

mod

elTA

Mtheoryof

constraintsTO

Cvaria

blec

onsis

tencyDRS

AV

C-DRS

A

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

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2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

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websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

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forthe

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ystem

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penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

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prop

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fuzzymod

elforsup

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ction

Defuzzificationweights-

vector

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thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

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ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

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efor

collabo

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eprodu

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nQFD

LIP

Defuzzification-

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Interrelationships

Criteria

weights

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betweenmarketin

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ystems

QFD

fuzzy

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Defuzzification-CO

A(T)weights-|119877minus

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ykasoglu

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Interrelationships

Criteria

weights

Evaluatethew

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riteriaandprop

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mod

elforsolving

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lem

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ncompany

FuzzyTO

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Defuzzification-sig

ned

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dweights-

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leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

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metho

d(T)

Fetanatand

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rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

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ndprop

osea

hybrid

MCD

Mapproach

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ffsho

rewindfarm

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FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

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ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

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ndfeedback

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and

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ybrid

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Mmod

elto

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obile

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adop

tion

FuzzyDANPfuzzy

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Weights-

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DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

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leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

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Aenviro

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entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

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Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

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onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Mathematical Problems in Engineering

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Submit your manuscripts atwwwhindawicom

Page 4: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

4 Mathematical Problems in Engineering

Table1Va

rious

applications

ofthec

lassicalDEM

ATEL

Papers

Research

purposes

Com

binatio

nsRe

marks

Type

1interrelationships

BEfea

ndOFE

fe[42]

Specify

theinfl

uenced

egrees

ofthep

atient

perceivedvalues

whenapplying

lean

health-care

managem

entinan

emergencydepartment

Thresholdvalue-

average

Malekzadehetal[43]

Investigatethe

causea

ndeffectrelations

forthe

dimensio

nsandcompo

nentso

forganizational

intelligenceinIranianpu

blicun

iversities

Thresholdvalue

Ranjan

etal[44

]Ad

dressthe

interrelationships

betweendifferent

evaluatio

ncriteria

ofIndian

Railw

ayzones

VIKOR

Thresholdvalue-

average

Tzengetal[10]

Addressthe

depend

entrelations

ofevaluatio

ncriteria

andprop

osea

hybrid

MCD

Mmod

elfor

evaluatin

gintertwined

effectsin

e-learning

programs

FAA

HPfuzzy

integral

Threshold

value-experts

Huetal[45]

Establish

thec

ausalrelationshipandextent

ofmutualimpactam

ongqu

ality

features

andpu

tforth

adecision

analysismetho

dology

toremovep

otentia

lproblem

sfrom

thec

onventionalIPA

mod

elBP

NN

Huetal[46

]Analyze

thec

ause-effectrelationshipam

ongdifferent

quality

characteris

ticstomaker

evision

sto

thetraditio

nalIPA

mod

elandfin

dthec

orep

roblem

sinvolvedwith

winning

orders

GAM

RA

Chengetal[47]

Explorethe

conn

ectio

nbetweenserviceq

ualityattributes

andthes

ervice

quality

improvem

ent

priorityof

fine-dining

restaurantsa

nduseitasa

referencefor

serviceq

ualitystr

ategyplanning

andresource

reorganizing

IPGA

Hsie

handYeh[48]

Exam

inec

ause

andeffectrela

tions

offactorsinfl

uencingthe

serviceq

ualityinfastfood

restaurants

Thresholdvalue-

average

Chiu

etal[49]

Analyze

relatio

nships

ofcusto

mer

buying

decisio

nfactorsa

ndprovidea

marketin

gstr

ategy

planning

forfi

rmsintheL

CD-TVmarket

Hoetal[50]

Analyze

thec

ause-effectrelationbetweenqu

ality

characteris

ticsa

ndbu

ildam

etho

dology

ofsupp

lierq

ualityperfo

rmance

assessmenttoim

proves

upplierq

ualitythroug

hop

timizing

order-winnersandqu

alifiers

IPAM

RA

Tsaietal[51]

Determinethe

causalrelationships

ofandinteractiveinfl

uencea

mon

gcriteria

andprop

osea

mixed

mod

elto

evaluatejobsatisfactionin

high

-tech

indu

strie

sIPA

Najmiand

Makui

[52]

Und

ersta

ndther

elationshipbetweencomparis

onmetric

sand

prop

osea

conceptualmod

elfor

measurin

gsupp

lychainperfo

rmance

AHP

Shafiee

etal[53]

Determinethe

relationships

betweenfour

perspectives

ofBS

Candprop

osea

napproach

toevaluatethep

erform

ance

ofsupp

lychain

DEA

BSC

Thresholdvalue-

average

ShaikandAb

dul-K

ader

[16]

Und

ersta

ndtheinterdepend

ence

amon

gperfo

rmance

factorsa

nddevelopar

everse

logistics

enterpris

eperform

ance

measurementm

odel

BSC

Innerd

ependence

matrix

Mathematical Problems in Engineering 5

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

LinandTzeng[11]

Determinethe

relatio

nshipbetweenthee

valuationcriteria

contrib

utingindu

stryclu

stersand

establish

theirv

alue

structuresa

ndbu

ildav

alue-created

syste

mof

science(techno

logy)p

ark

Threshold

value-experts

LinandSun[18]

Exam

inethe

impactso

fand

determ

inethe

relationships

amon

gdifferent

drivingforces

forthe

grow

thof

indu

strialcluste

rs

Threshold

value-expertsinner

depend

ence

matrix

WangandHsueh

[54]

Recogn

izethe

causalrelationships

betweendesig

nattributes

andmarketin

grequ

irementsand

prop

osea

napproach

toincorporatec

ustomer

preference

andperceptio

ninto

prod

uct

developm

ent

AHPKa

nomod

el

WangandSh

ih[55]

Identifytheimpactso

ffun

ctionalattributes

oncusto

mer

requ

irementsandpresenta

fram

ework

toincorporatec

ustomer

preferencesintoprod

uctd

evelo

pment

CA1QFD

TO

PSIS

Koetal[56]

Analyze

directandindirectim

pactsa

mon

gvario

ustechno

logy

areasa

ndpresenta

combined

approach

toconstructtechn

olog

yim

pactnetworks

forR

ampDplanning

usingpatents

SNA

Yoon

etal[57]

Assesstechno

logicalimpactsa

nddegree

ofcauseo

reffectam

ongtechno

logy

areasw

ithin

the

Korean

techno

logy

syste

mandob

servetheirdynamictre

nds

PCCA

Shen

andTzeng[58]

Explorethe

cause-effectrelationships

amon

gthea

ttributes

inthes

trong

decisio

nrulesa

ndprop

osea

mod

elfortacklingthev

alue

stock

selectionprob

lem

DRS

AFCA

Altu

ntas

andDereli

[59]

Establish

causalrelationships

amon

gtechno

logies

andprop

osea

napproach

forp

rioritizing

investmentp

rojectsfrom

theg

overnm

entrsquos

perspective

PCA

Thresholdvalue-

average

Shen

andTzeng[60]

Explorethe

complex

relationshipam

ongfin

ancialindicatorsandim

provefuturefi

nancial

perfo

rmance

oftheITindu

stry

VC-D

RSAFIS

Leea

ndLin[13]

Find

theinterrelationshipof

financialratio

sidentified

bymanagerso

fshipp

ingcompanies

and

financialexpertsa

ndcompare

theirc

ognitio

nmapsb

ycoun

tryandexpertgrou

pTh

resholdvalue-

MMDE

W-K

Tan

andY-J

Tan[61]

Analyze

howdifferent

factorsinteractand

collectively

contrib

utetothes

uccessfultransform

ation

anddiffu

sionof

thes

mart-c

ard-basede-micropaym

entm

ultip

urpo

sescheme

Azadehetal[12]

Evaluatetheimpactdegree

ofleannessfactorsa

ndpresentsac

omprehensiv

eapp

roachfor

evaluatin

gandop

timizingtheleann

essd

egreeo

forganizations

(lean

prod

uctio

n)

DEA

fuzzy

DEA

FCM

AHP

Thresholdvalue-

average

Sara

etal[14]

Assessrelativeimpo

rtance

andmutualinfl

uenceo

fbarrie

rsforc

arbo

ncapturea

ndsto

rage

deployment

AHP

Thresholdvalue-

average

Liaw

etal[62]

Analyze

theind

irectrelations

betweensubsystemsa

ndcompo

nentsa

ndprop

osea

reliability

allocatio

nmetho

dto

solvethe

fund

amentalproblem

sofcon

ventionalreliabilityappo

rtionm

ent

metho

dsME-OWA

Type

2interrelationships

andkeyfactors

AlaeiandAlro

aia[

63]

Identifyandprioritizethe

factorsa

ffectingandaffectedby

thep

erform

ance

ofsm

alland

medium

enterpris

es

Bacudioetal[64

]Analyze

cause-effectrelationships

ofbarriersto

implem

entin

gindu

stria

lsym

biosisnetworks

inan

indu

strialp

ark

Thresholdvalue-

averageinner

depend

ence

matrix

Balkovskayaa

ndFilneva[

65]

Identifycausalrelationships

betweenthek

eyevaluatio

nindicatorsof

bank

ingperfo

rmance

aswell

asdefin

ingthem

oststrategicallyim

portantind

icators

BSC

Threshold

value-second

quartile

6 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Chen

[66]

Estim

atethe

impo

rtance

ofthes

ervice

factorso

fanacadem

iclib

rary

andidentifythec

ausal

factors

Threshold

value-experts

GovindanandCh

audh

uri[67]

Analyze

ther

isksfaced

bythird

-partylogisticsservice

providersinrelationto

oneo

fitscusto

mers

andextractthe

causalrelationships

amon

gthem

Govindanetal[68]

Investigatethe

influ

entia

lstre

ngth

offactorso

nadop

tionof

greensupp

lychainmanagem

ent

practic

esin

theInd

ianminingindu

stry

AHP

Thresholdvalue-

average

Gandh

ietal[69]

Evaluatesuccessfactorsin

implem

entatio

nof

greensupp

lychainmanagem

entinIndian

manufacturin

gindu

strie

s

Hwangetal[70]

Explorethe

causalrelatio

nships

amon

gdecisio

nfactorsrelatingto

greensupp

lychains

inthe

semicon

ductor

indu

stry

Hwangetal[71]

Identifydeterm

inantsandtheirc

ausalrela

tionships

affectin

gthea

doptionof

cloud

compu

tingin

sciencea

ndtechno

logy

institutio

nsTh

reshold

value-120583+

32120590Hwangetal[20]

Assessthed

ynam

icris

kinterdependenciesfor

distinctprojectp

hasesa

ndidentifycriticalrisk

factors

Threshold

value-experts

Rahimniaa

ndKa

rgozar

[72]

Disc

over

causalrelationships

betweenob

jectives

inun

iversitystr

ategymap

andprioritizethem

forresou

rcea

llocatio

nBS

CTh

resholdvalue-third

quartile

Sekh

aretal[73]

Prioritizea

ndmap

thec

ausalrelationstr

ucturesindimensio

nsandsubd

imensio

nsof

HR-flexibilityandfirm

perfo

rmance

from

ITindu

stry

perspective

Seleem

etal[74]

Selectandmanagethe

suita

blep

erform

ance

improvem

entinitia

tives

toenhancethe

internal

processeso

fmanufacturin

gcompanies

BSC

TOC

Rank

basedon119877an

d119862

Sharmae

tal[75]

Assessthec

ausalrelationships

amon

glean

criteria

andidentifycriticalonesfor

thes

uccessful

implem

entatio

nof

lean

manufacturin

gTh

resholdvalue-

average

Shen

[76]

Identifythek

eybarriersandtheirinterrelationships

impeding

theu

niversity

techno

logy

transfe

rfro

mam

ultistakeho

lder

perspective

Thresholdvalue-third

quartile

Seyed-Hosseinietal[77]

Analyze

ther

elationbetweencompo

nentso

fasyste

mandprop

osea

metho

dology

for

reprioritizationof

failu

remod

esin

FMEA

Rank

basedon119877minus

119862Ch

ang[78]

Analyze

ther

elationshipbetweencompo

nentso

fasyste

mandou

tline

ageneralalgorithm

for

prioritizationof

failu

remod

esin

FMEA

OWGA

Rank

basedon119877minus

119862Ch

angetal[79]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

GRA

Rank

basedon119877minus

119862Ch

angetal[80]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

TOPS

ISRa

nkbasedon119877minus

119862

Mathematical Problems in Engineering 7

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Liuetal[81]

Con

structthe

influ

entia

lrelations

amon

gfailu

remod

esandcauses

offailu

resa

nddevelopa

fram

eworkforp

rioritizationof

failu

remod

esAHPVIKOR

Mentese

tal[82]

Con

sider

thed

irect-in

directrelationships

betweenfactorsa

ndprop

osea

nintegrated

metho

dology

forrisk

assessmento

fcargo

shipsa

tcoasts

andop

enseas

OWGA

Huang

etal[8]

Identifymajor

indu

stry

inno

vatio

nrequ

irementsandpresentrecon

figured

inno

vatio

npo

licy

portfolio

stodevelopTaiwanrsquosSIPMallind

ustry

GRA

CA1

Threshold

value-experts

LiandTzeng[9]

Disc

over

andillustratethe

keyservices

needed

toattractSIP

usersa

ndSIPproviderstoan

SIP

Mall

Threshold

value-experts

Horng

etal[83]

Identifyther

elationships

andinteractions

amon

gdimensio

nsof

restaurant

spaced

esignfro

mthe

expertrsquosp

erspectiv

eTh

resholdvalue-

average

Chen

etal[84]

Determinec

riticalcore

factorsa

ffectingconsum

erintentionto

dine

atgreenrestaurantsa

nddevelopspecificimprovem

entstrategies

SEMQ

FD

Chengetal[85]

Develo

pathree-tiered

serviceq

ualityim

provem

entm

odelto

identifycritical

educational-service-qualitydeficienciesinho

spita

litytourism

and

leisu

reun

dergradu

ate

programs

IPGAQ

FD

Shiehetal[86]

Evaluatetheimpo

rtance

andconstructthe

causalrelatio

nsof

criteria

from

patientsrsquoview

points

andidentifykeysuccessfactorsforimprovingtheh

ospitalservice

quality

SERV

QUA

Lmod

elTh

resholdvalue-

average

Ranjan

etal[87]

Analyze

andexplaintheinteractio

nrelationships

andim

pactlevelsbetweenevaluatio

ncriteria

anddevelopaframew

orkforp

erform

ance

evaluatio

nof

engineeringdepartmentsin

auniversity

VIKOR

entro

pymetho

dTh

resholdvalue-

average

TanandKu

o[15]

Prioritizefacilitatio

nstrategies

ofruralp

arkandrecreatio

nagencies

from

thep

erspectiv

eof

leisu

reconstraints

Threshold

value-maxim

umvalue

Wuetal[88]

Describethe

contextualrelationships

evaluatedam

ongcriteria

andevaluatetheimpo

rtance

ofthe

criteria

used

inem

ploymentservice

outre

achprogram

person

nel

Thresholdvalue-

average

Sun[89]

Handlethe

innerd

ependencea

ndidentifycore

competences

ofnewlyqu

alified

nurses

Threshold

value-experts

WuandTsai[90]

Describethe

contextualrelatio

nships

amon

gthec

riteriaandevaluatetheimpo

rtance

ofdimensio

nscriteriain

auto

sparep

artsindu

stry

Thresholdvalue-

average

8 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Sun[91]

Identifyandanalyzec

riticalsuccessfactorsin

thee

lectronicd

esignautomationindu

stry

Threshold

value-experts

WuandTsai[92]

Depictthe

causalrelatio

nsandevaluatetheimpo

rtance

ofcriteria

inauto

sparep

artsindu

stry

AHP

Thresholdvalue-

average

Weietal[93]

Reprioritizethe

amendedmod

esin

theS

EMmod

elandestablish

acausalrelationshipmod

elfor

Web-advertisingeffects

Wuetal[24]

Explorethe

factorsh

inderin

gthea

cceptanceo

fusin

ginternalclo

udservices

inau

niversity

TAM

Four

quadrants

Hsu

[94]

Find

thed

eterminantfactorsinflu

encing

blog

desig

nandsim

plify

andvisualizethe

interrelationships

betweencriteria

fore

achfactor

FATh

reshold

value-experts

Hsu

andLee[95]

Explorethe

criticalfactorsinflu

encing

theq

ualityof

blog

interfa

cesa

ndthec

ausalrela

tionships

betweenthesefactors

Leee

tal[96]

Establish

thec

ausalrela

tionshipandthed

egreeo

finterrelationshipof

DTP

Bvaria

bles

(university

library

website)

Wuetal[23]

Explored

ecisive

factorsa

ffectingan

organizatio

nrsquosSoftw

area

saService(SaaS)a

doption

Four

quadrants

Pathariand

Sonar[97]

Analyze

asetof

securitysta

tementsin

inform

ationsecuritypo

licyproceduresand

controlsto

establish

anim

plicithierarchyandrelativ

eimpo

rtance

amon

gthem

Jafarnejad

etal[98]

Classifythec

riteriain

ERPselectioninto

thetwogrou

psof

ldquocauserdquoa

ndldquoeffectrdquoa

ndprop

osea

combinedMCD

Mapproach

toselectthep

roperE

RPsyste

m

Entro

pymetho

dfuzzy

AHP

TsaiandCh

eng[99]

Analyze

KPIsforE

-com

merce

andInternetmarketin

gof

elderly

prod

ucts

BSC

Wangetal[25]

Capturethe

causalrelationships

amon

gdivisio

nsandidentifythosed

ivision

swith

inam

atrix

organizatio

nthatmay

berespon

sibleforthe

poor

perfo

rmance

ofah

igh-tech

facilitydesig

nproject

SIA

Netinflu

ence

matrix

Linetal[100]

Explorethe

core

competences

andinvestigatetheircausea

ndeffectrela

tionships

oftheICdesig

nservicec

ompany

Threshold

value-experts

Chuang

etal[21]

Investigatethe

complex

multid

imensio

naland

dynamicnature

ofmem

bere

ngagem

entb

ehavior

inenvironm

entalprotectionvirtualcom

mun

ities

ISM

Threshold

value-expertsfour

quadrants

Rahm

anandSubram

anian[101]

Identifycriticalfactorsforimplem

entin

gEO

Lcompu

terrecyclin

gop

erations

inreverses

upply

chainandinvestigatethec

ausalrelationshipam

ongthefactors

Thresholdvalue-

average

Hsu

etal[102]

Recogn

izethe

influ

entia

lcriteriaof

carbon

managem

entingreensupp

lychainto

improvethe

overallp

erform

ance

ofsupp

liers

Thresholdvalue

Falatoon

itoosietal[103]

Exam

inec

omplex

causalrelationshipbetweenfactorsingreensupp

lychainmanagem

entand

providea

nevaluatio

nfram

eworkto

selectthem

osteligiblegreensupp

liers

Renetal[104]

Identifykeydrivingfactorsa

ndmap

theirc

ause-effectrelationships

fore

nhancing

the

susta

inabilityof

hydrogen

supp

lychain

Threshold

value-experts

Mud

uliand

Barve[105]

Extractthe

causalrelationships

amon

ggreensupp

lychainmanagem

entb

arrie

rsandestablish

asustainabled

evelop

mentframew

orkin

scaleInd

ianminingindu

strie

s

Mathematical Problems in Engineering 9

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

WuandCh

ang[106]

Identifythec

riticaldimensio

nsandfactorstoim

plem

entg

reen

supp

lychainmanagem

entinthe

electricalandele

ctronicind

ustries

Thresholdvalue-

average

Behera

andMuk

herje

e[107]

Capturer

elationships

andanalyzek

eyinflu

encing

factorsrele

vant

toselectionof

supp

lychain

coordinatio

nschemes

Thresholdvalue-

MMDE

Ahm

edetal[108]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

fore

valuatingsustainableE

OLvehicle

managem

entalternatives

FuzzyAHP

Ahm

edetal[109]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

andprop

osea

nintegrated

mod

elfor

sustainableE

OLvehicle

managem

entalternatives

election

AHPfuzzyA

HP

Miaoetal[110

]Ev

aluatetheimpo

rtance

andun

veiltheimplicitinterrela

tionships

amon

gdifferent

scales

ofCP

Vandconstructa

multiscalemod

elforthe

measuremento

fCPV

ofEV

sHoQ

Threshold

value-expertsrank

basedon119877+

119862Lin[111]

Analyze

interactions

amon

gindu

stria

ldevelo

pmentfactorsandexploreh

owto

establish

the

competitivenesso

fsolar

photovoltaicindu

stry

Porterrsquos

Diamon

dmod

el

AzarnivandandCh

itsaz

[112]

Quantify

theinterlin

kagesa

mon

gfund

amentalanthrop

ogenicindicatorsandprop

osea

syste

maticapproach

forw

ater

shortage

mitigatio

nin

thea

ridregion

seD

PSIRA

HP

COPR

AS-G

Chen

etal[113]

Quantify

theinfl

uenceo

nPM

25by

otherfactorsin

thew

eather

syste

mandidentifythem

ost

impo

rtantfactorsforP

M25

RMFo

urqu

adrants

dosM

uchangos

etal[114

]As

sesstheb

arrie

rsto

mun

icipalsolid

wastemanagem

entp

olicyplanning

andidentifythem

ost

onerou

sbarrie

rsto

thee

ffectiveimplem

entatio

nof

thep

olicy

ISM

Netinflu

ence

matrix

Guo

etal[115]

EvaluateandinvestigategreencorporateC

SRindicatorsof

manufacturin

gcorporations

from

agreenindu

strylawperspective

Four

quadrants

Chen

andCh

i[116

]Ex

plorek

eyfactorso

fChinarsquosCS

Rfro

mthep

erspectiv

eofaccou

ntingexperts

Changetal[117

]Identifykeystr

ategicfactorsintheimplem

entatio

nof

CSRin

airline

indu

stry

Leee

tal[118]

Calculatethe

causalrelationshipandinteractionlevelbetweenTA

Mvaria

bles

andfin

dthec

ore

varia

bles

form

anagem

ento

rimprovem

entw

hileintro

ducing

anew

etchingplasmatechn

olog

yFo

urqu

adrants

Wu[119]

Determinethe

causalrelationships

betweentheK

PIso

fthe

BSCandlin

kthem

into

astrategy

map

forb

anking

institutio

nsBS

C

Chienetal[22]

Identifyrelatio

nships

betweenris

kfactorsa

ndassesscriticalrisk

factorsfor

BIM

projects

Four

quadrants

10 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Wangetal[26]

Evaluatethep

erform

ance

ofdesig

ndelay

factorsa

ndidentifykeyfactorsthatd

rived

esigndelay

sof

afacilityconstructio

nproject

ISA

Netinflu

ence

matrix

Tzeng[19

]Investigatethe

relationshipbetweenfactorsa

ffectingparolebo

ardsrsquodecision

makingin

Taiwan

Simplified

norm

alized

total-relation

matrix

threshold

value

Gazibey

etal[120]

Analyze

thec

ause

andeffectrelations

amon

gthec

riteriaaffectin

gmainbattletankselection

Thresholdvalue-

average

Type

3interrelationships

andcriteria

weights

Khalili-D

amgh

anietal[121]

Determinethe

relativ

eimpo

rtance

weightsof

compensatoryob

jectivefun

ctions

andprop

osea

hybrid

multip

leob

jectivem

etaheuris

ticalgorithm

tosolveland-uses

uitabilityanalysisand

planning

prob

lem

AHP

Khazaietal[29]

Analyze

directandindirectdepend

encies

with

insocialandindu

stria

lvulnerabilityindicatorsand

developaframew

orkforspatia

lassessm

ento

find

ustrialand

socialvulnerabilityto

indirect

disaste

rlosses

Threshold

valuedepend

ency

weights

Tseng[122]

Resolvec

riteriainterdependencyrelationships

weightsandprop

osea

hybrid

metho

dto

evaluate

serviceq

ualityexpectationin

hotspringho

telrsquosrank

ingprob

lem

FuzzyTO

PSIS

Innerd

ependence

matrix

Quadere

tal[123]

Determinethe

causea

ndeffectrelationships

amon

gcriteria

andevaluatethec

riticalcriteria

for

CO2capturea

ndsto

rage

intheironandste

elindu

stry

Criteria

weights-

vector

leng

thth

reshold

value

Quadera

ndAhm

ed[124]

Identifycriticalfactorsfore

valuatingalternativeiron-makingtechno

logies

with

carbon

capture

andsto

rage

syste

ms

FuzzyAHP

Criteria

weights-

vector

leng

thth

reshold

value

Seyedh

osseinietal[17]

Identifythec

ause

andeffectrela

tionships

amon

glean

objectives

andprop

osed

asystematicamp

logicalm

etho

dfora

utopartmanufacturersto

determ

inethe

companyrsquoslean

strategymap

BSC

Innerd

ependence

matrix

weights-119877+

119862Cebi[27]

Determineimpo

rtance

degreeso

fwebsited

esignparametersb

ased

oninteractions

andtypeso

fwebsites

Thresholdvalue-

averagedeterm

ining

weightsusing119877+

119862Yazdani-C

hamzini

etal[28]

Analyze

interdependencea

nddepend

encies

andcompu

tetheg

lobalw

eightsfore

valuation

indicatorsandprop

osea

newhybrid

mod

elto

selectthes

trategyof

investingin

apriv

ates

ector

AHPfuzzy

TOPS

IS

Thresholdvalue-

expertsweights-119877+

119862No

teB

ackpropagatio

nneuralnetworkBP

NNbalancedscorecardBS

Cbu

ildinginformationmod

elingBIMcluste

ranalysisC

A1conjoint

analysis

CA2corporatesocialrespo

nsibilityC

SRcustomerperceived

valueCP

Vdata

envelopm

enta

nalysis

DEA

decom

posedtheory

ofplannedbehaviorD

TPB

dominance-based

roug

hseta

pproach

DRS

Aelectric

vehicle

EV

enhanced

drivingforce-pressure-state-im

pact-

respon

seeDPS

IRenterprise

resource

planning

ERP

end

-of-lifeE

OLfactor

analysis

FAfailure

mod

eand

effectanalysisFMEA

fuzzy

cogn

itive

mapFCM

fuzzy

inferences

ystemFISformalconceptanalysis

FC

Agap

analysis

GAgreyc

omplex

prop

ortio

nalassessm

entCO

PRAS-Ggreyr

elationalanalysisG

RAhou

seso

fqualityHoQ

impo

rtance-perform

ance

analysis

IPAimpo

rtance-perform

ance

andgapanalysis

IPGAimpo

rtance-satisfactio

nanalysis

ISAinformationtechno

logyITinterpretiv

estructuralm

odeling

ISM

integratedcircuitICkey

perfo

rmance

indicatorKP

Imaxim

alentro

pyorderedweightedaveraging

ME-OWAm

ultip

leregressio

nanalysis

MRA

ordered

weightedgeom

etric

averagingOWGApatentcitatio

nanalysis

PCApatentcoclassificatio

nanalysis

PCCA

relationmapR

Msatisfi

edim

portance

analysis

SIAsiliconintellectualp

ropertyor

Semicon

ductor-Intellectual-P

ropertySIP

socialnetworkanalysis

SNAstructuralequ

ationmod

elingSE

Mtechn

olog

yacceptance

mod

elTA

Mtheoryof

constraintsTO

Cvaria

blec

onsis

tencyDRS

AV

C-DRS

A

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

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irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

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d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Page 5: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

Mathematical Problems in Engineering 5

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

LinandTzeng[11]

Determinethe

relatio

nshipbetweenthee

valuationcriteria

contrib

utingindu

stryclu

stersand

establish

theirv

alue

structuresa

ndbu

ildav

alue-created

syste

mof

science(techno

logy)p

ark

Threshold

value-experts

LinandSun[18]

Exam

inethe

impactso

fand

determ

inethe

relationships

amon

gdifferent

drivingforces

forthe

grow

thof

indu

strialcluste

rs

Threshold

value-expertsinner

depend

ence

matrix

WangandHsueh

[54]

Recogn

izethe

causalrelationships

betweendesig

nattributes

andmarketin

grequ

irementsand

prop

osea

napproach

toincorporatec

ustomer

preference

andperceptio

ninto

prod

uct

developm

ent

AHPKa

nomod

el

WangandSh

ih[55]

Identifytheimpactso

ffun

ctionalattributes

oncusto

mer

requ

irementsandpresenta

fram

ework

toincorporatec

ustomer

preferencesintoprod

uctd

evelo

pment

CA1QFD

TO

PSIS

Koetal[56]

Analyze

directandindirectim

pactsa

mon

gvario

ustechno

logy

areasa

ndpresenta

combined

approach

toconstructtechn

olog

yim

pactnetworks

forR

ampDplanning

usingpatents

SNA

Yoon

etal[57]

Assesstechno

logicalimpactsa

nddegree

ofcauseo

reffectam

ongtechno

logy

areasw

ithin

the

Korean

techno

logy

syste

mandob

servetheirdynamictre

nds

PCCA

Shen

andTzeng[58]

Explorethe

cause-effectrelationships

amon

gthea

ttributes

inthes

trong

decisio

nrulesa

ndprop

osea

mod

elfortacklingthev

alue

stock

selectionprob

lem

DRS

AFCA

Altu

ntas

andDereli

[59]

Establish

causalrelationships

amon

gtechno

logies

andprop

osea

napproach

forp

rioritizing

investmentp

rojectsfrom

theg

overnm

entrsquos

perspective

PCA

Thresholdvalue-

average

Shen

andTzeng[60]

Explorethe

complex

relationshipam

ongfin

ancialindicatorsandim

provefuturefi

nancial

perfo

rmance

oftheITindu

stry

VC-D

RSAFIS

Leea

ndLin[13]

Find

theinterrelationshipof

financialratio

sidentified

bymanagerso

fshipp

ingcompanies

and

financialexpertsa

ndcompare

theirc

ognitio

nmapsb

ycoun

tryandexpertgrou

pTh

resholdvalue-

MMDE

W-K

Tan

andY-J

Tan[61]

Analyze

howdifferent

factorsinteractand

collectively

contrib

utetothes

uccessfultransform

ation

anddiffu

sionof

thes

mart-c

ard-basede-micropaym

entm

ultip

urpo

sescheme

Azadehetal[12]

Evaluatetheimpactdegree

ofleannessfactorsa

ndpresentsac

omprehensiv

eapp

roachfor

evaluatin

gandop

timizingtheleann

essd

egreeo

forganizations

(lean

prod

uctio

n)

DEA

fuzzy

DEA

FCM

AHP

Thresholdvalue-

average

Sara

etal[14]

Assessrelativeimpo

rtance

andmutualinfl

uenceo

fbarrie

rsforc

arbo

ncapturea

ndsto

rage

deployment

AHP

Thresholdvalue-

average

Liaw

etal[62]

Analyze

theind

irectrelations

betweensubsystemsa

ndcompo

nentsa

ndprop

osea

reliability

allocatio

nmetho

dto

solvethe

fund

amentalproblem

sofcon

ventionalreliabilityappo

rtionm

ent

metho

dsME-OWA

Type

2interrelationships

andkeyfactors

AlaeiandAlro

aia[

63]

Identifyandprioritizethe

factorsa

ffectingandaffectedby

thep

erform

ance

ofsm

alland

medium

enterpris

es

Bacudioetal[64

]Analyze

cause-effectrelationships

ofbarriersto

implem

entin

gindu

stria

lsym

biosisnetworks

inan

indu

strialp

ark

Thresholdvalue-

averageinner

depend

ence

matrix

Balkovskayaa

ndFilneva[

65]

Identifycausalrelationships

betweenthek

eyevaluatio

nindicatorsof

bank

ingperfo

rmance

aswell

asdefin

ingthem

oststrategicallyim

portantind

icators

BSC

Threshold

value-second

quartile

6 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Chen

[66]

Estim

atethe

impo

rtance

ofthes

ervice

factorso

fanacadem

iclib

rary

andidentifythec

ausal

factors

Threshold

value-experts

GovindanandCh

audh

uri[67]

Analyze

ther

isksfaced

bythird

-partylogisticsservice

providersinrelationto

oneo

fitscusto

mers

andextractthe

causalrelationships

amon

gthem

Govindanetal[68]

Investigatethe

influ

entia

lstre

ngth

offactorso

nadop

tionof

greensupp

lychainmanagem

ent

practic

esin

theInd

ianminingindu

stry

AHP

Thresholdvalue-

average

Gandh

ietal[69]

Evaluatesuccessfactorsin

implem

entatio

nof

greensupp

lychainmanagem

entinIndian

manufacturin

gindu

strie

s

Hwangetal[70]

Explorethe

causalrelatio

nships

amon

gdecisio

nfactorsrelatingto

greensupp

lychains

inthe

semicon

ductor

indu

stry

Hwangetal[71]

Identifydeterm

inantsandtheirc

ausalrela

tionships

affectin

gthea

doptionof

cloud

compu

tingin

sciencea

ndtechno

logy

institutio

nsTh

reshold

value-120583+

32120590Hwangetal[20]

Assessthed

ynam

icris

kinterdependenciesfor

distinctprojectp

hasesa

ndidentifycriticalrisk

factors

Threshold

value-experts

Rahimniaa

ndKa

rgozar

[72]

Disc

over

causalrelationships

betweenob

jectives

inun

iversitystr

ategymap

andprioritizethem

forresou

rcea

llocatio

nBS

CTh

resholdvalue-third

quartile

Sekh

aretal[73]

Prioritizea

ndmap

thec

ausalrelationstr

ucturesindimensio

nsandsubd

imensio

nsof

HR-flexibilityandfirm

perfo

rmance

from

ITindu

stry

perspective

Seleem

etal[74]

Selectandmanagethe

suita

blep

erform

ance

improvem

entinitia

tives

toenhancethe

internal

processeso

fmanufacturin

gcompanies

BSC

TOC

Rank

basedon119877an

d119862

Sharmae

tal[75]

Assessthec

ausalrelationships

amon

glean

criteria

andidentifycriticalonesfor

thes

uccessful

implem

entatio

nof

lean

manufacturin

gTh

resholdvalue-

average

Shen

[76]

Identifythek

eybarriersandtheirinterrelationships

impeding

theu

niversity

techno

logy

transfe

rfro

mam

ultistakeho

lder

perspective

Thresholdvalue-third

quartile

Seyed-Hosseinietal[77]

Analyze

ther

elationbetweencompo

nentso

fasyste

mandprop

osea

metho

dology

for

reprioritizationof

failu

remod

esin

FMEA

Rank

basedon119877minus

119862Ch

ang[78]

Analyze

ther

elationshipbetweencompo

nentso

fasyste

mandou

tline

ageneralalgorithm

for

prioritizationof

failu

remod

esin

FMEA

OWGA

Rank

basedon119877minus

119862Ch

angetal[79]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

GRA

Rank

basedon119877minus

119862Ch

angetal[80]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

TOPS

ISRa

nkbasedon119877minus

119862

Mathematical Problems in Engineering 7

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Liuetal[81]

Con

structthe

influ

entia

lrelations

amon

gfailu

remod

esandcauses

offailu

resa

nddevelopa

fram

eworkforp

rioritizationof

failu

remod

esAHPVIKOR

Mentese

tal[82]

Con

sider

thed

irect-in

directrelationships

betweenfactorsa

ndprop

osea

nintegrated

metho

dology

forrisk

assessmento

fcargo

shipsa

tcoasts

andop

enseas

OWGA

Huang

etal[8]

Identifymajor

indu

stry

inno

vatio

nrequ

irementsandpresentrecon

figured

inno

vatio

npo

licy

portfolio

stodevelopTaiwanrsquosSIPMallind

ustry

GRA

CA1

Threshold

value-experts

LiandTzeng[9]

Disc

over

andillustratethe

keyservices

needed

toattractSIP

usersa

ndSIPproviderstoan

SIP

Mall

Threshold

value-experts

Horng

etal[83]

Identifyther

elationships

andinteractions

amon

gdimensio

nsof

restaurant

spaced

esignfro

mthe

expertrsquosp

erspectiv

eTh

resholdvalue-

average

Chen

etal[84]

Determinec

riticalcore

factorsa

ffectingconsum

erintentionto

dine

atgreenrestaurantsa

nddevelopspecificimprovem

entstrategies

SEMQ

FD

Chengetal[85]

Develo

pathree-tiered

serviceq

ualityim

provem

entm

odelto

identifycritical

educational-service-qualitydeficienciesinho

spita

litytourism

and

leisu

reun

dergradu

ate

programs

IPGAQ

FD

Shiehetal[86]

Evaluatetheimpo

rtance

andconstructthe

causalrelatio

nsof

criteria

from

patientsrsquoview

points

andidentifykeysuccessfactorsforimprovingtheh

ospitalservice

quality

SERV

QUA

Lmod

elTh

resholdvalue-

average

Ranjan

etal[87]

Analyze

andexplaintheinteractio

nrelationships

andim

pactlevelsbetweenevaluatio

ncriteria

anddevelopaframew

orkforp

erform

ance

evaluatio

nof

engineeringdepartmentsin

auniversity

VIKOR

entro

pymetho

dTh

resholdvalue-

average

TanandKu

o[15]

Prioritizefacilitatio

nstrategies

ofruralp

arkandrecreatio

nagencies

from

thep

erspectiv

eof

leisu

reconstraints

Threshold

value-maxim

umvalue

Wuetal[88]

Describethe

contextualrelationships

evaluatedam

ongcriteria

andevaluatetheimpo

rtance

ofthe

criteria

used

inem

ploymentservice

outre

achprogram

person

nel

Thresholdvalue-

average

Sun[89]

Handlethe

innerd

ependencea

ndidentifycore

competences

ofnewlyqu

alified

nurses

Threshold

value-experts

WuandTsai[90]

Describethe

contextualrelatio

nships

amon

gthec

riteriaandevaluatetheimpo

rtance

ofdimensio

nscriteriain

auto

sparep

artsindu

stry

Thresholdvalue-

average

8 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Sun[91]

Identifyandanalyzec

riticalsuccessfactorsin

thee

lectronicd

esignautomationindu

stry

Threshold

value-experts

WuandTsai[92]

Depictthe

causalrelatio

nsandevaluatetheimpo

rtance

ofcriteria

inauto

sparep

artsindu

stry

AHP

Thresholdvalue-

average

Weietal[93]

Reprioritizethe

amendedmod

esin

theS

EMmod

elandestablish

acausalrelationshipmod

elfor

Web-advertisingeffects

Wuetal[24]

Explorethe

factorsh

inderin

gthea

cceptanceo

fusin

ginternalclo

udservices

inau

niversity

TAM

Four

quadrants

Hsu

[94]

Find

thed

eterminantfactorsinflu

encing

blog

desig

nandsim

plify

andvisualizethe

interrelationships

betweencriteria

fore

achfactor

FATh

reshold

value-experts

Hsu

andLee[95]

Explorethe

criticalfactorsinflu

encing

theq

ualityof

blog

interfa

cesa

ndthec

ausalrela

tionships

betweenthesefactors

Leee

tal[96]

Establish

thec

ausalrela

tionshipandthed

egreeo

finterrelationshipof

DTP

Bvaria

bles

(university

library

website)

Wuetal[23]

Explored

ecisive

factorsa

ffectingan

organizatio

nrsquosSoftw

area

saService(SaaS)a

doption

Four

quadrants

Pathariand

Sonar[97]

Analyze

asetof

securitysta

tementsin

inform

ationsecuritypo

licyproceduresand

controlsto

establish

anim

plicithierarchyandrelativ

eimpo

rtance

amon

gthem

Jafarnejad

etal[98]

Classifythec

riteriain

ERPselectioninto

thetwogrou

psof

ldquocauserdquoa

ndldquoeffectrdquoa

ndprop

osea

combinedMCD

Mapproach

toselectthep

roperE

RPsyste

m

Entro

pymetho

dfuzzy

AHP

TsaiandCh

eng[99]

Analyze

KPIsforE

-com

merce

andInternetmarketin

gof

elderly

prod

ucts

BSC

Wangetal[25]

Capturethe

causalrelationships

amon

gdivisio

nsandidentifythosed

ivision

swith

inam

atrix

organizatio

nthatmay

berespon

sibleforthe

poor

perfo

rmance

ofah

igh-tech

facilitydesig

nproject

SIA

Netinflu

ence

matrix

Linetal[100]

Explorethe

core

competences

andinvestigatetheircausea

ndeffectrela

tionships

oftheICdesig

nservicec

ompany

Threshold

value-experts

Chuang

etal[21]

Investigatethe

complex

multid

imensio

naland

dynamicnature

ofmem

bere

ngagem

entb

ehavior

inenvironm

entalprotectionvirtualcom

mun

ities

ISM

Threshold

value-expertsfour

quadrants

Rahm

anandSubram

anian[101]

Identifycriticalfactorsforimplem

entin

gEO

Lcompu

terrecyclin

gop

erations

inreverses

upply

chainandinvestigatethec

ausalrelationshipam

ongthefactors

Thresholdvalue-

average

Hsu

etal[102]

Recogn

izethe

influ

entia

lcriteriaof

carbon

managem

entingreensupp

lychainto

improvethe

overallp

erform

ance

ofsupp

liers

Thresholdvalue

Falatoon

itoosietal[103]

Exam

inec

omplex

causalrelationshipbetweenfactorsingreensupp

lychainmanagem

entand

providea

nevaluatio

nfram

eworkto

selectthem

osteligiblegreensupp

liers

Renetal[104]

Identifykeydrivingfactorsa

ndmap

theirc

ause-effectrelationships

fore

nhancing

the

susta

inabilityof

hydrogen

supp

lychain

Threshold

value-experts

Mud

uliand

Barve[105]

Extractthe

causalrelationships

amon

ggreensupp

lychainmanagem

entb

arrie

rsandestablish

asustainabled

evelop

mentframew

orkin

scaleInd

ianminingindu

strie

s

Mathematical Problems in Engineering 9

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

WuandCh

ang[106]

Identifythec

riticaldimensio

nsandfactorstoim

plem

entg

reen

supp

lychainmanagem

entinthe

electricalandele

ctronicind

ustries

Thresholdvalue-

average

Behera

andMuk

herje

e[107]

Capturer

elationships

andanalyzek

eyinflu

encing

factorsrele

vant

toselectionof

supp

lychain

coordinatio

nschemes

Thresholdvalue-

MMDE

Ahm

edetal[108]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

fore

valuatingsustainableE

OLvehicle

managem

entalternatives

FuzzyAHP

Ahm

edetal[109]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

andprop

osea

nintegrated

mod

elfor

sustainableE

OLvehicle

managem

entalternatives

election

AHPfuzzyA

HP

Miaoetal[110

]Ev

aluatetheimpo

rtance

andun

veiltheimplicitinterrela

tionships

amon

gdifferent

scales

ofCP

Vandconstructa

multiscalemod

elforthe

measuremento

fCPV

ofEV

sHoQ

Threshold

value-expertsrank

basedon119877+

119862Lin[111]

Analyze

interactions

amon

gindu

stria

ldevelo

pmentfactorsandexploreh

owto

establish

the

competitivenesso

fsolar

photovoltaicindu

stry

Porterrsquos

Diamon

dmod

el

AzarnivandandCh

itsaz

[112]

Quantify

theinterlin

kagesa

mon

gfund

amentalanthrop

ogenicindicatorsandprop

osea

syste

maticapproach

forw

ater

shortage

mitigatio

nin

thea

ridregion

seD

PSIRA

HP

COPR

AS-G

Chen

etal[113]

Quantify

theinfl

uenceo

nPM

25by

otherfactorsin

thew

eather

syste

mandidentifythem

ost

impo

rtantfactorsforP

M25

RMFo

urqu

adrants

dosM

uchangos

etal[114

]As

sesstheb

arrie

rsto

mun

icipalsolid

wastemanagem

entp

olicyplanning

andidentifythem

ost

onerou

sbarrie

rsto

thee

ffectiveimplem

entatio

nof

thep

olicy

ISM

Netinflu

ence

matrix

Guo

etal[115]

EvaluateandinvestigategreencorporateC

SRindicatorsof

manufacturin

gcorporations

from

agreenindu

strylawperspective

Four

quadrants

Chen

andCh

i[116

]Ex

plorek

eyfactorso

fChinarsquosCS

Rfro

mthep

erspectiv

eofaccou

ntingexperts

Changetal[117

]Identifykeystr

ategicfactorsintheimplem

entatio

nof

CSRin

airline

indu

stry

Leee

tal[118]

Calculatethe

causalrelationshipandinteractionlevelbetweenTA

Mvaria

bles

andfin

dthec

ore

varia

bles

form

anagem

ento

rimprovem

entw

hileintro

ducing

anew

etchingplasmatechn

olog

yFo

urqu

adrants

Wu[119]

Determinethe

causalrelationships

betweentheK

PIso

fthe

BSCandlin

kthem

into

astrategy

map

forb

anking

institutio

nsBS

C

Chienetal[22]

Identifyrelatio

nships

betweenris

kfactorsa

ndassesscriticalrisk

factorsfor

BIM

projects

Four

quadrants

10 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Wangetal[26]

Evaluatethep

erform

ance

ofdesig

ndelay

factorsa

ndidentifykeyfactorsthatd

rived

esigndelay

sof

afacilityconstructio

nproject

ISA

Netinflu

ence

matrix

Tzeng[19

]Investigatethe

relationshipbetweenfactorsa

ffectingparolebo

ardsrsquodecision

makingin

Taiwan

Simplified

norm

alized

total-relation

matrix

threshold

value

Gazibey

etal[120]

Analyze

thec

ause

andeffectrelations

amon

gthec

riteriaaffectin

gmainbattletankselection

Thresholdvalue-

average

Type

3interrelationships

andcriteria

weights

Khalili-D

amgh

anietal[121]

Determinethe

relativ

eimpo

rtance

weightsof

compensatoryob

jectivefun

ctions

andprop

osea

hybrid

multip

leob

jectivem

etaheuris

ticalgorithm

tosolveland-uses

uitabilityanalysisand

planning

prob

lem

AHP

Khazaietal[29]

Analyze

directandindirectdepend

encies

with

insocialandindu

stria

lvulnerabilityindicatorsand

developaframew

orkforspatia

lassessm

ento

find

ustrialand

socialvulnerabilityto

indirect

disaste

rlosses

Threshold

valuedepend

ency

weights

Tseng[122]

Resolvec

riteriainterdependencyrelationships

weightsandprop

osea

hybrid

metho

dto

evaluate

serviceq

ualityexpectationin

hotspringho

telrsquosrank

ingprob

lem

FuzzyTO

PSIS

Innerd

ependence

matrix

Quadere

tal[123]

Determinethe

causea

ndeffectrelationships

amon

gcriteria

andevaluatethec

riticalcriteria

for

CO2capturea

ndsto

rage

intheironandste

elindu

stry

Criteria

weights-

vector

leng

thth

reshold

value

Quadera

ndAhm

ed[124]

Identifycriticalfactorsfore

valuatingalternativeiron-makingtechno

logies

with

carbon

capture

andsto

rage

syste

ms

FuzzyAHP

Criteria

weights-

vector

leng

thth

reshold

value

Seyedh

osseinietal[17]

Identifythec

ause

andeffectrela

tionships

amon

glean

objectives

andprop

osed

asystematicamp

logicalm

etho

dfora

utopartmanufacturersto

determ

inethe

companyrsquoslean

strategymap

BSC

Innerd

ependence

matrix

weights-119877+

119862Cebi[27]

Determineimpo

rtance

degreeso

fwebsited

esignparametersb

ased

oninteractions

andtypeso

fwebsites

Thresholdvalue-

averagedeterm

ining

weightsusing119877+

119862Yazdani-C

hamzini

etal[28]

Analyze

interdependencea

nddepend

encies

andcompu

tetheg

lobalw

eightsfore

valuation

indicatorsandprop

osea

newhybrid

mod

elto

selectthes

trategyof

investingin

apriv

ates

ector

AHPfuzzy

TOPS

IS

Thresholdvalue-

expertsweights-119877+

119862No

teB

ackpropagatio

nneuralnetworkBP

NNbalancedscorecardBS

Cbu

ildinginformationmod

elingBIMcluste

ranalysisC

A1conjoint

analysis

CA2corporatesocialrespo

nsibilityC

SRcustomerperceived

valueCP

Vdata

envelopm

enta

nalysis

DEA

decom

posedtheory

ofplannedbehaviorD

TPB

dominance-based

roug

hseta

pproach

DRS

Aelectric

vehicle

EV

enhanced

drivingforce-pressure-state-im

pact-

respon

seeDPS

IRenterprise

resource

planning

ERP

end

-of-lifeE

OLfactor

analysis

FAfailure

mod

eand

effectanalysisFMEA

fuzzy

cogn

itive

mapFCM

fuzzy

inferences

ystemFISformalconceptanalysis

FC

Agap

analysis

GAgreyc

omplex

prop

ortio

nalassessm

entCO

PRAS-Ggreyr

elationalanalysisG

RAhou

seso

fqualityHoQ

impo

rtance-perform

ance

analysis

IPAimpo

rtance-perform

ance

andgapanalysis

IPGAimpo

rtance-satisfactio

nanalysis

ISAinformationtechno

logyITinterpretiv

estructuralm

odeling

ISM

integratedcircuitICkey

perfo

rmance

indicatorKP

Imaxim

alentro

pyorderedweightedaveraging

ME-OWAm

ultip

leregressio

nanalysis

MRA

ordered

weightedgeom

etric

averagingOWGApatentcitatio

nanalysis

PCApatentcoclassificatio

nanalysis

PCCA

relationmapR

Msatisfi

edim

portance

analysis

SIAsiliconintellectualp

ropertyor

Semicon

ductor-Intellectual-P

ropertySIP

socialnetworkanalysis

SNAstructuralequ

ationmod

elingSE

Mtechn

olog

yacceptance

mod

elTA

Mtheoryof

constraintsTO

Cvaria

blec

onsis

tencyDRS

AV

C-DRS

A

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Hindawiwwwhindawicom Volume 2018

Mathematical Problems in Engineering

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Submit your manuscripts atwwwhindawicom

Page 6: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

6 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Chen

[66]

Estim

atethe

impo

rtance

ofthes

ervice

factorso

fanacadem

iclib

rary

andidentifythec

ausal

factors

Threshold

value-experts

GovindanandCh

audh

uri[67]

Analyze

ther

isksfaced

bythird

-partylogisticsservice

providersinrelationto

oneo

fitscusto

mers

andextractthe

causalrelationships

amon

gthem

Govindanetal[68]

Investigatethe

influ

entia

lstre

ngth

offactorso

nadop

tionof

greensupp

lychainmanagem

ent

practic

esin

theInd

ianminingindu

stry

AHP

Thresholdvalue-

average

Gandh

ietal[69]

Evaluatesuccessfactorsin

implem

entatio

nof

greensupp

lychainmanagem

entinIndian

manufacturin

gindu

strie

s

Hwangetal[70]

Explorethe

causalrelatio

nships

amon

gdecisio

nfactorsrelatingto

greensupp

lychains

inthe

semicon

ductor

indu

stry

Hwangetal[71]

Identifydeterm

inantsandtheirc

ausalrela

tionships

affectin

gthea

doptionof

cloud

compu

tingin

sciencea

ndtechno

logy

institutio

nsTh

reshold

value-120583+

32120590Hwangetal[20]

Assessthed

ynam

icris

kinterdependenciesfor

distinctprojectp

hasesa

ndidentifycriticalrisk

factors

Threshold

value-experts

Rahimniaa

ndKa

rgozar

[72]

Disc

over

causalrelationships

betweenob

jectives

inun

iversitystr

ategymap

andprioritizethem

forresou

rcea

llocatio

nBS

CTh

resholdvalue-third

quartile

Sekh

aretal[73]

Prioritizea

ndmap

thec

ausalrelationstr

ucturesindimensio

nsandsubd

imensio

nsof

HR-flexibilityandfirm

perfo

rmance

from

ITindu

stry

perspective

Seleem

etal[74]

Selectandmanagethe

suita

blep

erform

ance

improvem

entinitia

tives

toenhancethe

internal

processeso

fmanufacturin

gcompanies

BSC

TOC

Rank

basedon119877an

d119862

Sharmae

tal[75]

Assessthec

ausalrelationships

amon

glean

criteria

andidentifycriticalonesfor

thes

uccessful

implem

entatio

nof

lean

manufacturin

gTh

resholdvalue-

average

Shen

[76]

Identifythek

eybarriersandtheirinterrelationships

impeding

theu

niversity

techno

logy

transfe

rfro

mam

ultistakeho

lder

perspective

Thresholdvalue-third

quartile

Seyed-Hosseinietal[77]

Analyze

ther

elationbetweencompo

nentso

fasyste

mandprop

osea

metho

dology

for

reprioritizationof

failu

remod

esin

FMEA

Rank

basedon119877minus

119862Ch

ang[78]

Analyze

ther

elationshipbetweencompo

nentso

fasyste

mandou

tline

ageneralalgorithm

for

prioritizationof

failu

remod

esin

FMEA

OWGA

Rank

basedon119877minus

119862Ch

angetal[79]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

GRA

Rank

basedon119877minus

119862Ch

angetal[80]

Exam

inethe

directandindirectrelationships

betweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

TOPS

ISRa

nkbasedon119877minus

119862

Mathematical Problems in Engineering 7

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Liuetal[81]

Con

structthe

influ

entia

lrelations

amon

gfailu

remod

esandcauses

offailu

resa

nddevelopa

fram

eworkforp

rioritizationof

failu

remod

esAHPVIKOR

Mentese

tal[82]

Con

sider

thed

irect-in

directrelationships

betweenfactorsa

ndprop

osea

nintegrated

metho

dology

forrisk

assessmento

fcargo

shipsa

tcoasts

andop

enseas

OWGA

Huang

etal[8]

Identifymajor

indu

stry

inno

vatio

nrequ

irementsandpresentrecon

figured

inno

vatio

npo

licy

portfolio

stodevelopTaiwanrsquosSIPMallind

ustry

GRA

CA1

Threshold

value-experts

LiandTzeng[9]

Disc

over

andillustratethe

keyservices

needed

toattractSIP

usersa

ndSIPproviderstoan

SIP

Mall

Threshold

value-experts

Horng

etal[83]

Identifyther

elationships

andinteractions

amon

gdimensio

nsof

restaurant

spaced

esignfro

mthe

expertrsquosp

erspectiv

eTh

resholdvalue-

average

Chen

etal[84]

Determinec

riticalcore

factorsa

ffectingconsum

erintentionto

dine

atgreenrestaurantsa

nddevelopspecificimprovem

entstrategies

SEMQ

FD

Chengetal[85]

Develo

pathree-tiered

serviceq

ualityim

provem

entm

odelto

identifycritical

educational-service-qualitydeficienciesinho

spita

litytourism

and

leisu

reun

dergradu

ate

programs

IPGAQ

FD

Shiehetal[86]

Evaluatetheimpo

rtance

andconstructthe

causalrelatio

nsof

criteria

from

patientsrsquoview

points

andidentifykeysuccessfactorsforimprovingtheh

ospitalservice

quality

SERV

QUA

Lmod

elTh

resholdvalue-

average

Ranjan

etal[87]

Analyze

andexplaintheinteractio

nrelationships

andim

pactlevelsbetweenevaluatio

ncriteria

anddevelopaframew

orkforp

erform

ance

evaluatio

nof

engineeringdepartmentsin

auniversity

VIKOR

entro

pymetho

dTh

resholdvalue-

average

TanandKu

o[15]

Prioritizefacilitatio

nstrategies

ofruralp

arkandrecreatio

nagencies

from

thep

erspectiv

eof

leisu

reconstraints

Threshold

value-maxim

umvalue

Wuetal[88]

Describethe

contextualrelationships

evaluatedam

ongcriteria

andevaluatetheimpo

rtance

ofthe

criteria

used

inem

ploymentservice

outre

achprogram

person

nel

Thresholdvalue-

average

Sun[89]

Handlethe

innerd

ependencea

ndidentifycore

competences

ofnewlyqu

alified

nurses

Threshold

value-experts

WuandTsai[90]

Describethe

contextualrelatio

nships

amon

gthec

riteriaandevaluatetheimpo

rtance

ofdimensio

nscriteriain

auto

sparep

artsindu

stry

Thresholdvalue-

average

8 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Sun[91]

Identifyandanalyzec

riticalsuccessfactorsin

thee

lectronicd

esignautomationindu

stry

Threshold

value-experts

WuandTsai[92]

Depictthe

causalrelatio

nsandevaluatetheimpo

rtance

ofcriteria

inauto

sparep

artsindu

stry

AHP

Thresholdvalue-

average

Weietal[93]

Reprioritizethe

amendedmod

esin

theS

EMmod

elandestablish

acausalrelationshipmod

elfor

Web-advertisingeffects

Wuetal[24]

Explorethe

factorsh

inderin

gthea

cceptanceo

fusin

ginternalclo

udservices

inau

niversity

TAM

Four

quadrants

Hsu

[94]

Find

thed

eterminantfactorsinflu

encing

blog

desig

nandsim

plify

andvisualizethe

interrelationships

betweencriteria

fore

achfactor

FATh

reshold

value-experts

Hsu

andLee[95]

Explorethe

criticalfactorsinflu

encing

theq

ualityof

blog

interfa

cesa

ndthec

ausalrela

tionships

betweenthesefactors

Leee

tal[96]

Establish

thec

ausalrela

tionshipandthed

egreeo

finterrelationshipof

DTP

Bvaria

bles

(university

library

website)

Wuetal[23]

Explored

ecisive

factorsa

ffectingan

organizatio

nrsquosSoftw

area

saService(SaaS)a

doption

Four

quadrants

Pathariand

Sonar[97]

Analyze

asetof

securitysta

tementsin

inform

ationsecuritypo

licyproceduresand

controlsto

establish

anim

plicithierarchyandrelativ

eimpo

rtance

amon

gthem

Jafarnejad

etal[98]

Classifythec

riteriain

ERPselectioninto

thetwogrou

psof

ldquocauserdquoa

ndldquoeffectrdquoa

ndprop

osea

combinedMCD

Mapproach

toselectthep

roperE

RPsyste

m

Entro

pymetho

dfuzzy

AHP

TsaiandCh

eng[99]

Analyze

KPIsforE

-com

merce

andInternetmarketin

gof

elderly

prod

ucts

BSC

Wangetal[25]

Capturethe

causalrelationships

amon

gdivisio

nsandidentifythosed

ivision

swith

inam

atrix

organizatio

nthatmay

berespon

sibleforthe

poor

perfo

rmance

ofah

igh-tech

facilitydesig

nproject

SIA

Netinflu

ence

matrix

Linetal[100]

Explorethe

core

competences

andinvestigatetheircausea

ndeffectrela

tionships

oftheICdesig

nservicec

ompany

Threshold

value-experts

Chuang

etal[21]

Investigatethe

complex

multid

imensio

naland

dynamicnature

ofmem

bere

ngagem

entb

ehavior

inenvironm

entalprotectionvirtualcom

mun

ities

ISM

Threshold

value-expertsfour

quadrants

Rahm

anandSubram

anian[101]

Identifycriticalfactorsforimplem

entin

gEO

Lcompu

terrecyclin

gop

erations

inreverses

upply

chainandinvestigatethec

ausalrelationshipam

ongthefactors

Thresholdvalue-

average

Hsu

etal[102]

Recogn

izethe

influ

entia

lcriteriaof

carbon

managem

entingreensupp

lychainto

improvethe

overallp

erform

ance

ofsupp

liers

Thresholdvalue

Falatoon

itoosietal[103]

Exam

inec

omplex

causalrelationshipbetweenfactorsingreensupp

lychainmanagem

entand

providea

nevaluatio

nfram

eworkto

selectthem

osteligiblegreensupp

liers

Renetal[104]

Identifykeydrivingfactorsa

ndmap

theirc

ause-effectrelationships

fore

nhancing

the

susta

inabilityof

hydrogen

supp

lychain

Threshold

value-experts

Mud

uliand

Barve[105]

Extractthe

causalrelationships

amon

ggreensupp

lychainmanagem

entb

arrie

rsandestablish

asustainabled

evelop

mentframew

orkin

scaleInd

ianminingindu

strie

s

Mathematical Problems in Engineering 9

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

WuandCh

ang[106]

Identifythec

riticaldimensio

nsandfactorstoim

plem

entg

reen

supp

lychainmanagem

entinthe

electricalandele

ctronicind

ustries

Thresholdvalue-

average

Behera

andMuk

herje

e[107]

Capturer

elationships

andanalyzek

eyinflu

encing

factorsrele

vant

toselectionof

supp

lychain

coordinatio

nschemes

Thresholdvalue-

MMDE

Ahm

edetal[108]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

fore

valuatingsustainableE

OLvehicle

managem

entalternatives

FuzzyAHP

Ahm

edetal[109]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

andprop

osea

nintegrated

mod

elfor

sustainableE

OLvehicle

managem

entalternatives

election

AHPfuzzyA

HP

Miaoetal[110

]Ev

aluatetheimpo

rtance

andun

veiltheimplicitinterrela

tionships

amon

gdifferent

scales

ofCP

Vandconstructa

multiscalemod

elforthe

measuremento

fCPV

ofEV

sHoQ

Threshold

value-expertsrank

basedon119877+

119862Lin[111]

Analyze

interactions

amon

gindu

stria

ldevelo

pmentfactorsandexploreh

owto

establish

the

competitivenesso

fsolar

photovoltaicindu

stry

Porterrsquos

Diamon

dmod

el

AzarnivandandCh

itsaz

[112]

Quantify

theinterlin

kagesa

mon

gfund

amentalanthrop

ogenicindicatorsandprop

osea

syste

maticapproach

forw

ater

shortage

mitigatio

nin

thea

ridregion

seD

PSIRA

HP

COPR

AS-G

Chen

etal[113]

Quantify

theinfl

uenceo

nPM

25by

otherfactorsin

thew

eather

syste

mandidentifythem

ost

impo

rtantfactorsforP

M25

RMFo

urqu

adrants

dosM

uchangos

etal[114

]As

sesstheb

arrie

rsto

mun

icipalsolid

wastemanagem

entp

olicyplanning

andidentifythem

ost

onerou

sbarrie

rsto

thee

ffectiveimplem

entatio

nof

thep

olicy

ISM

Netinflu

ence

matrix

Guo

etal[115]

EvaluateandinvestigategreencorporateC

SRindicatorsof

manufacturin

gcorporations

from

agreenindu

strylawperspective

Four

quadrants

Chen

andCh

i[116

]Ex

plorek

eyfactorso

fChinarsquosCS

Rfro

mthep

erspectiv

eofaccou

ntingexperts

Changetal[117

]Identifykeystr

ategicfactorsintheimplem

entatio

nof

CSRin

airline

indu

stry

Leee

tal[118]

Calculatethe

causalrelationshipandinteractionlevelbetweenTA

Mvaria

bles

andfin

dthec

ore

varia

bles

form

anagem

ento

rimprovem

entw

hileintro

ducing

anew

etchingplasmatechn

olog

yFo

urqu

adrants

Wu[119]

Determinethe

causalrelationships

betweentheK

PIso

fthe

BSCandlin

kthem

into

astrategy

map

forb

anking

institutio

nsBS

C

Chienetal[22]

Identifyrelatio

nships

betweenris

kfactorsa

ndassesscriticalrisk

factorsfor

BIM

projects

Four

quadrants

10 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Wangetal[26]

Evaluatethep

erform

ance

ofdesig

ndelay

factorsa

ndidentifykeyfactorsthatd

rived

esigndelay

sof

afacilityconstructio

nproject

ISA

Netinflu

ence

matrix

Tzeng[19

]Investigatethe

relationshipbetweenfactorsa

ffectingparolebo

ardsrsquodecision

makingin

Taiwan

Simplified

norm

alized

total-relation

matrix

threshold

value

Gazibey

etal[120]

Analyze

thec

ause

andeffectrelations

amon

gthec

riteriaaffectin

gmainbattletankselection

Thresholdvalue-

average

Type

3interrelationships

andcriteria

weights

Khalili-D

amgh

anietal[121]

Determinethe

relativ

eimpo

rtance

weightsof

compensatoryob

jectivefun

ctions

andprop

osea

hybrid

multip

leob

jectivem

etaheuris

ticalgorithm

tosolveland-uses

uitabilityanalysisand

planning

prob

lem

AHP

Khazaietal[29]

Analyze

directandindirectdepend

encies

with

insocialandindu

stria

lvulnerabilityindicatorsand

developaframew

orkforspatia

lassessm

ento

find

ustrialand

socialvulnerabilityto

indirect

disaste

rlosses

Threshold

valuedepend

ency

weights

Tseng[122]

Resolvec

riteriainterdependencyrelationships

weightsandprop

osea

hybrid

metho

dto

evaluate

serviceq

ualityexpectationin

hotspringho

telrsquosrank

ingprob

lem

FuzzyTO

PSIS

Innerd

ependence

matrix

Quadere

tal[123]

Determinethe

causea

ndeffectrelationships

amon

gcriteria

andevaluatethec

riticalcriteria

for

CO2capturea

ndsto

rage

intheironandste

elindu

stry

Criteria

weights-

vector

leng

thth

reshold

value

Quadera

ndAhm

ed[124]

Identifycriticalfactorsfore

valuatingalternativeiron-makingtechno

logies

with

carbon

capture

andsto

rage

syste

ms

FuzzyAHP

Criteria

weights-

vector

leng

thth

reshold

value

Seyedh

osseinietal[17]

Identifythec

ause

andeffectrela

tionships

amon

glean

objectives

andprop

osed

asystematicamp

logicalm

etho

dfora

utopartmanufacturersto

determ

inethe

companyrsquoslean

strategymap

BSC

Innerd

ependence

matrix

weights-119877+

119862Cebi[27]

Determineimpo

rtance

degreeso

fwebsited

esignparametersb

ased

oninteractions

andtypeso

fwebsites

Thresholdvalue-

averagedeterm

ining

weightsusing119877+

119862Yazdani-C

hamzini

etal[28]

Analyze

interdependencea

nddepend

encies

andcompu

tetheg

lobalw

eightsfore

valuation

indicatorsandprop

osea

newhybrid

mod

elto

selectthes

trategyof

investingin

apriv

ates

ector

AHPfuzzy

TOPS

IS

Thresholdvalue-

expertsweights-119877+

119862No

teB

ackpropagatio

nneuralnetworkBP

NNbalancedscorecardBS

Cbu

ildinginformationmod

elingBIMcluste

ranalysisC

A1conjoint

analysis

CA2corporatesocialrespo

nsibilityC

SRcustomerperceived

valueCP

Vdata

envelopm

enta

nalysis

DEA

decom

posedtheory

ofplannedbehaviorD

TPB

dominance-based

roug

hseta

pproach

DRS

Aelectric

vehicle

EV

enhanced

drivingforce-pressure-state-im

pact-

respon

seeDPS

IRenterprise

resource

planning

ERP

end

-of-lifeE

OLfactor

analysis

FAfailure

mod

eand

effectanalysisFMEA

fuzzy

cogn

itive

mapFCM

fuzzy

inferences

ystemFISformalconceptanalysis

FC

Agap

analysis

GAgreyc

omplex

prop

ortio

nalassessm

entCO

PRAS-Ggreyr

elationalanalysisG

RAhou

seso

fqualityHoQ

impo

rtance-perform

ance

analysis

IPAimpo

rtance-perform

ance

andgapanalysis

IPGAimpo

rtance-satisfactio

nanalysis

ISAinformationtechno

logyITinterpretiv

estructuralm

odeling

ISM

integratedcircuitICkey

perfo

rmance

indicatorKP

Imaxim

alentro

pyorderedweightedaveraging

ME-OWAm

ultip

leregressio

nanalysis

MRA

ordered

weightedgeom

etric

averagingOWGApatentcitatio

nanalysis

PCApatentcoclassificatio

nanalysis

PCCA

relationmapR

Msatisfi

edim

portance

analysis

SIAsiliconintellectualp

ropertyor

Semicon

ductor-Intellectual-P

ropertySIP

socialnetworkanalysis

SNAstructuralequ

ationmod

elingSE

Mtechn

olog

yacceptance

mod

elTA

Mtheoryof

constraintsTO

Cvaria

blec

onsis

tencyDRS

AV

C-DRS

A

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

Hindawiwwwhindawicom Volume 2018

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Mathematical Problems in Engineering

Applied MathematicsJournal of

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Page 7: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

Mathematical Problems in Engineering 7

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Liuetal[81]

Con

structthe

influ

entia

lrelations

amon

gfailu

remod

esandcauses

offailu

resa

nddevelopa

fram

eworkforp

rioritizationof

failu

remod

esAHPVIKOR

Mentese

tal[82]

Con

sider

thed

irect-in

directrelationships

betweenfactorsa

ndprop

osea

nintegrated

metho

dology

forrisk

assessmento

fcargo

shipsa

tcoasts

andop

enseas

OWGA

Huang

etal[8]

Identifymajor

indu

stry

inno

vatio

nrequ

irementsandpresentrecon

figured

inno

vatio

npo

licy

portfolio

stodevelopTaiwanrsquosSIPMallind

ustry

GRA

CA1

Threshold

value-experts

LiandTzeng[9]

Disc

over

andillustratethe

keyservices

needed

toattractSIP

usersa

ndSIPproviderstoan

SIP

Mall

Threshold

value-experts

Horng

etal[83]

Identifyther

elationships

andinteractions

amon

gdimensio

nsof

restaurant

spaced

esignfro

mthe

expertrsquosp

erspectiv

eTh

resholdvalue-

average

Chen

etal[84]

Determinec

riticalcore

factorsa

ffectingconsum

erintentionto

dine

atgreenrestaurantsa

nddevelopspecificimprovem

entstrategies

SEMQ

FD

Chengetal[85]

Develo

pathree-tiered

serviceq

ualityim

provem

entm

odelto

identifycritical

educational-service-qualitydeficienciesinho

spita

litytourism

and

leisu

reun

dergradu

ate

programs

IPGAQ

FD

Shiehetal[86]

Evaluatetheimpo

rtance

andconstructthe

causalrelatio

nsof

criteria

from

patientsrsquoview

points

andidentifykeysuccessfactorsforimprovingtheh

ospitalservice

quality

SERV

QUA

Lmod

elTh

resholdvalue-

average

Ranjan

etal[87]

Analyze

andexplaintheinteractio

nrelationships

andim

pactlevelsbetweenevaluatio

ncriteria

anddevelopaframew

orkforp

erform

ance

evaluatio

nof

engineeringdepartmentsin

auniversity

VIKOR

entro

pymetho

dTh

resholdvalue-

average

TanandKu

o[15]

Prioritizefacilitatio

nstrategies

ofruralp

arkandrecreatio

nagencies

from

thep

erspectiv

eof

leisu

reconstraints

Threshold

value-maxim

umvalue

Wuetal[88]

Describethe

contextualrelationships

evaluatedam

ongcriteria

andevaluatetheimpo

rtance

ofthe

criteria

used

inem

ploymentservice

outre

achprogram

person

nel

Thresholdvalue-

average

Sun[89]

Handlethe

innerd

ependencea

ndidentifycore

competences

ofnewlyqu

alified

nurses

Threshold

value-experts

WuandTsai[90]

Describethe

contextualrelatio

nships

amon

gthec

riteriaandevaluatetheimpo

rtance

ofdimensio

nscriteriain

auto

sparep

artsindu

stry

Thresholdvalue-

average

8 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Sun[91]

Identifyandanalyzec

riticalsuccessfactorsin

thee

lectronicd

esignautomationindu

stry

Threshold

value-experts

WuandTsai[92]

Depictthe

causalrelatio

nsandevaluatetheimpo

rtance

ofcriteria

inauto

sparep

artsindu

stry

AHP

Thresholdvalue-

average

Weietal[93]

Reprioritizethe

amendedmod

esin

theS

EMmod

elandestablish

acausalrelationshipmod

elfor

Web-advertisingeffects

Wuetal[24]

Explorethe

factorsh

inderin

gthea

cceptanceo

fusin

ginternalclo

udservices

inau

niversity

TAM

Four

quadrants

Hsu

[94]

Find

thed

eterminantfactorsinflu

encing

blog

desig

nandsim

plify

andvisualizethe

interrelationships

betweencriteria

fore

achfactor

FATh

reshold

value-experts

Hsu

andLee[95]

Explorethe

criticalfactorsinflu

encing

theq

ualityof

blog

interfa

cesa

ndthec

ausalrela

tionships

betweenthesefactors

Leee

tal[96]

Establish

thec

ausalrela

tionshipandthed

egreeo

finterrelationshipof

DTP

Bvaria

bles

(university

library

website)

Wuetal[23]

Explored

ecisive

factorsa

ffectingan

organizatio

nrsquosSoftw

area

saService(SaaS)a

doption

Four

quadrants

Pathariand

Sonar[97]

Analyze

asetof

securitysta

tementsin

inform

ationsecuritypo

licyproceduresand

controlsto

establish

anim

plicithierarchyandrelativ

eimpo

rtance

amon

gthem

Jafarnejad

etal[98]

Classifythec

riteriain

ERPselectioninto

thetwogrou

psof

ldquocauserdquoa

ndldquoeffectrdquoa

ndprop

osea

combinedMCD

Mapproach

toselectthep

roperE

RPsyste

m

Entro

pymetho

dfuzzy

AHP

TsaiandCh

eng[99]

Analyze

KPIsforE

-com

merce

andInternetmarketin

gof

elderly

prod

ucts

BSC

Wangetal[25]

Capturethe

causalrelationships

amon

gdivisio

nsandidentifythosed

ivision

swith

inam

atrix

organizatio

nthatmay

berespon

sibleforthe

poor

perfo

rmance

ofah

igh-tech

facilitydesig

nproject

SIA

Netinflu

ence

matrix

Linetal[100]

Explorethe

core

competences

andinvestigatetheircausea

ndeffectrela

tionships

oftheICdesig

nservicec

ompany

Threshold

value-experts

Chuang

etal[21]

Investigatethe

complex

multid

imensio

naland

dynamicnature

ofmem

bere

ngagem

entb

ehavior

inenvironm

entalprotectionvirtualcom

mun

ities

ISM

Threshold

value-expertsfour

quadrants

Rahm

anandSubram

anian[101]

Identifycriticalfactorsforimplem

entin

gEO

Lcompu

terrecyclin

gop

erations

inreverses

upply

chainandinvestigatethec

ausalrelationshipam

ongthefactors

Thresholdvalue-

average

Hsu

etal[102]

Recogn

izethe

influ

entia

lcriteriaof

carbon

managem

entingreensupp

lychainto

improvethe

overallp

erform

ance

ofsupp

liers

Thresholdvalue

Falatoon

itoosietal[103]

Exam

inec

omplex

causalrelationshipbetweenfactorsingreensupp

lychainmanagem

entand

providea

nevaluatio

nfram

eworkto

selectthem

osteligiblegreensupp

liers

Renetal[104]

Identifykeydrivingfactorsa

ndmap

theirc

ause-effectrelationships

fore

nhancing

the

susta

inabilityof

hydrogen

supp

lychain

Threshold

value-experts

Mud

uliand

Barve[105]

Extractthe

causalrelationships

amon

ggreensupp

lychainmanagem

entb

arrie

rsandestablish

asustainabled

evelop

mentframew

orkin

scaleInd

ianminingindu

strie

s

Mathematical Problems in Engineering 9

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

WuandCh

ang[106]

Identifythec

riticaldimensio

nsandfactorstoim

plem

entg

reen

supp

lychainmanagem

entinthe

electricalandele

ctronicind

ustries

Thresholdvalue-

average

Behera

andMuk

herje

e[107]

Capturer

elationships

andanalyzek

eyinflu

encing

factorsrele

vant

toselectionof

supp

lychain

coordinatio

nschemes

Thresholdvalue-

MMDE

Ahm

edetal[108]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

fore

valuatingsustainableE

OLvehicle

managem

entalternatives

FuzzyAHP

Ahm

edetal[109]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

andprop

osea

nintegrated

mod

elfor

sustainableE

OLvehicle

managem

entalternatives

election

AHPfuzzyA

HP

Miaoetal[110

]Ev

aluatetheimpo

rtance

andun

veiltheimplicitinterrela

tionships

amon

gdifferent

scales

ofCP

Vandconstructa

multiscalemod

elforthe

measuremento

fCPV

ofEV

sHoQ

Threshold

value-expertsrank

basedon119877+

119862Lin[111]

Analyze

interactions

amon

gindu

stria

ldevelo

pmentfactorsandexploreh

owto

establish

the

competitivenesso

fsolar

photovoltaicindu

stry

Porterrsquos

Diamon

dmod

el

AzarnivandandCh

itsaz

[112]

Quantify

theinterlin

kagesa

mon

gfund

amentalanthrop

ogenicindicatorsandprop

osea

syste

maticapproach

forw

ater

shortage

mitigatio

nin

thea

ridregion

seD

PSIRA

HP

COPR

AS-G

Chen

etal[113]

Quantify

theinfl

uenceo

nPM

25by

otherfactorsin

thew

eather

syste

mandidentifythem

ost

impo

rtantfactorsforP

M25

RMFo

urqu

adrants

dosM

uchangos

etal[114

]As

sesstheb

arrie

rsto

mun

icipalsolid

wastemanagem

entp

olicyplanning

andidentifythem

ost

onerou

sbarrie

rsto

thee

ffectiveimplem

entatio

nof

thep

olicy

ISM

Netinflu

ence

matrix

Guo

etal[115]

EvaluateandinvestigategreencorporateC

SRindicatorsof

manufacturin

gcorporations

from

agreenindu

strylawperspective

Four

quadrants

Chen

andCh

i[116

]Ex

plorek

eyfactorso

fChinarsquosCS

Rfro

mthep

erspectiv

eofaccou

ntingexperts

Changetal[117

]Identifykeystr

ategicfactorsintheimplem

entatio

nof

CSRin

airline

indu

stry

Leee

tal[118]

Calculatethe

causalrelationshipandinteractionlevelbetweenTA

Mvaria

bles

andfin

dthec

ore

varia

bles

form

anagem

ento

rimprovem

entw

hileintro

ducing

anew

etchingplasmatechn

olog

yFo

urqu

adrants

Wu[119]

Determinethe

causalrelationships

betweentheK

PIso

fthe

BSCandlin

kthem

into

astrategy

map

forb

anking

institutio

nsBS

C

Chienetal[22]

Identifyrelatio

nships

betweenris

kfactorsa

ndassesscriticalrisk

factorsfor

BIM

projects

Four

quadrants

10 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Wangetal[26]

Evaluatethep

erform

ance

ofdesig

ndelay

factorsa

ndidentifykeyfactorsthatd

rived

esigndelay

sof

afacilityconstructio

nproject

ISA

Netinflu

ence

matrix

Tzeng[19

]Investigatethe

relationshipbetweenfactorsa

ffectingparolebo

ardsrsquodecision

makingin

Taiwan

Simplified

norm

alized

total-relation

matrix

threshold

value

Gazibey

etal[120]

Analyze

thec

ause

andeffectrelations

amon

gthec

riteriaaffectin

gmainbattletankselection

Thresholdvalue-

average

Type

3interrelationships

andcriteria

weights

Khalili-D

amgh

anietal[121]

Determinethe

relativ

eimpo

rtance

weightsof

compensatoryob

jectivefun

ctions

andprop

osea

hybrid

multip

leob

jectivem

etaheuris

ticalgorithm

tosolveland-uses

uitabilityanalysisand

planning

prob

lem

AHP

Khazaietal[29]

Analyze

directandindirectdepend

encies

with

insocialandindu

stria

lvulnerabilityindicatorsand

developaframew

orkforspatia

lassessm

ento

find

ustrialand

socialvulnerabilityto

indirect

disaste

rlosses

Threshold

valuedepend

ency

weights

Tseng[122]

Resolvec

riteriainterdependencyrelationships

weightsandprop

osea

hybrid

metho

dto

evaluate

serviceq

ualityexpectationin

hotspringho

telrsquosrank

ingprob

lem

FuzzyTO

PSIS

Innerd

ependence

matrix

Quadere

tal[123]

Determinethe

causea

ndeffectrelationships

amon

gcriteria

andevaluatethec

riticalcriteria

for

CO2capturea

ndsto

rage

intheironandste

elindu

stry

Criteria

weights-

vector

leng

thth

reshold

value

Quadera

ndAhm

ed[124]

Identifycriticalfactorsfore

valuatingalternativeiron-makingtechno

logies

with

carbon

capture

andsto

rage

syste

ms

FuzzyAHP

Criteria

weights-

vector

leng

thth

reshold

value

Seyedh

osseinietal[17]

Identifythec

ause

andeffectrela

tionships

amon

glean

objectives

andprop

osed

asystematicamp

logicalm

etho

dfora

utopartmanufacturersto

determ

inethe

companyrsquoslean

strategymap

BSC

Innerd

ependence

matrix

weights-119877+

119862Cebi[27]

Determineimpo

rtance

degreeso

fwebsited

esignparametersb

ased

oninteractions

andtypeso

fwebsites

Thresholdvalue-

averagedeterm

ining

weightsusing119877+

119862Yazdani-C

hamzini

etal[28]

Analyze

interdependencea

nddepend

encies

andcompu

tetheg

lobalw

eightsfore

valuation

indicatorsandprop

osea

newhybrid

mod

elto

selectthes

trategyof

investingin

apriv

ates

ector

AHPfuzzy

TOPS

IS

Thresholdvalue-

expertsweights-119877+

119862No

teB

ackpropagatio

nneuralnetworkBP

NNbalancedscorecardBS

Cbu

ildinginformationmod

elingBIMcluste

ranalysisC

A1conjoint

analysis

CA2corporatesocialrespo

nsibilityC

SRcustomerperceived

valueCP

Vdata

envelopm

enta

nalysis

DEA

decom

posedtheory

ofplannedbehaviorD

TPB

dominance-based

roug

hseta

pproach

DRS

Aelectric

vehicle

EV

enhanced

drivingforce-pressure-state-im

pact-

respon

seeDPS

IRenterprise

resource

planning

ERP

end

-of-lifeE

OLfactor

analysis

FAfailure

mod

eand

effectanalysisFMEA

fuzzy

cogn

itive

mapFCM

fuzzy

inferences

ystemFISformalconceptanalysis

FC

Agap

analysis

GAgreyc

omplex

prop

ortio

nalassessm

entCO

PRAS-Ggreyr

elationalanalysisG

RAhou

seso

fqualityHoQ

impo

rtance-perform

ance

analysis

IPAimpo

rtance-perform

ance

andgapanalysis

IPGAimpo

rtance-satisfactio

nanalysis

ISAinformationtechno

logyITinterpretiv

estructuralm

odeling

ISM

integratedcircuitICkey

perfo

rmance

indicatorKP

Imaxim

alentro

pyorderedweightedaveraging

ME-OWAm

ultip

leregressio

nanalysis

MRA

ordered

weightedgeom

etric

averagingOWGApatentcitatio

nanalysis

PCApatentcoclassificatio

nanalysis

PCCA

relationmapR

Msatisfi

edim

portance

analysis

SIAsiliconintellectualp

ropertyor

Semicon

ductor-Intellectual-P

ropertySIP

socialnetworkanalysis

SNAstructuralequ

ationmod

elingSE

Mtechn

olog

yacceptance

mod

elTA

Mtheoryof

constraintsTO

Cvaria

blec

onsis

tencyDRS

AV

C-DRS

A

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Page 8: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

8 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Sun[91]

Identifyandanalyzec

riticalsuccessfactorsin

thee

lectronicd

esignautomationindu

stry

Threshold

value-experts

WuandTsai[92]

Depictthe

causalrelatio

nsandevaluatetheimpo

rtance

ofcriteria

inauto

sparep

artsindu

stry

AHP

Thresholdvalue-

average

Weietal[93]

Reprioritizethe

amendedmod

esin

theS

EMmod

elandestablish

acausalrelationshipmod

elfor

Web-advertisingeffects

Wuetal[24]

Explorethe

factorsh

inderin

gthea

cceptanceo

fusin

ginternalclo

udservices

inau

niversity

TAM

Four

quadrants

Hsu

[94]

Find

thed

eterminantfactorsinflu

encing

blog

desig

nandsim

plify

andvisualizethe

interrelationships

betweencriteria

fore

achfactor

FATh

reshold

value-experts

Hsu

andLee[95]

Explorethe

criticalfactorsinflu

encing

theq

ualityof

blog

interfa

cesa

ndthec

ausalrela

tionships

betweenthesefactors

Leee

tal[96]

Establish

thec

ausalrela

tionshipandthed

egreeo

finterrelationshipof

DTP

Bvaria

bles

(university

library

website)

Wuetal[23]

Explored

ecisive

factorsa

ffectingan

organizatio

nrsquosSoftw

area

saService(SaaS)a

doption

Four

quadrants

Pathariand

Sonar[97]

Analyze

asetof

securitysta

tementsin

inform

ationsecuritypo

licyproceduresand

controlsto

establish

anim

plicithierarchyandrelativ

eimpo

rtance

amon

gthem

Jafarnejad

etal[98]

Classifythec

riteriain

ERPselectioninto

thetwogrou

psof

ldquocauserdquoa

ndldquoeffectrdquoa

ndprop

osea

combinedMCD

Mapproach

toselectthep

roperE

RPsyste

m

Entro

pymetho

dfuzzy

AHP

TsaiandCh

eng[99]

Analyze

KPIsforE

-com

merce

andInternetmarketin

gof

elderly

prod

ucts

BSC

Wangetal[25]

Capturethe

causalrelationships

amon

gdivisio

nsandidentifythosed

ivision

swith

inam

atrix

organizatio

nthatmay

berespon

sibleforthe

poor

perfo

rmance

ofah

igh-tech

facilitydesig

nproject

SIA

Netinflu

ence

matrix

Linetal[100]

Explorethe

core

competences

andinvestigatetheircausea

ndeffectrela

tionships

oftheICdesig

nservicec

ompany

Threshold

value-experts

Chuang

etal[21]

Investigatethe

complex

multid

imensio

naland

dynamicnature

ofmem

bere

ngagem

entb

ehavior

inenvironm

entalprotectionvirtualcom

mun

ities

ISM

Threshold

value-expertsfour

quadrants

Rahm

anandSubram

anian[101]

Identifycriticalfactorsforimplem

entin

gEO

Lcompu

terrecyclin

gop

erations

inreverses

upply

chainandinvestigatethec

ausalrelationshipam

ongthefactors

Thresholdvalue-

average

Hsu

etal[102]

Recogn

izethe

influ

entia

lcriteriaof

carbon

managem

entingreensupp

lychainto

improvethe

overallp

erform

ance

ofsupp

liers

Thresholdvalue

Falatoon

itoosietal[103]

Exam

inec

omplex

causalrelationshipbetweenfactorsingreensupp

lychainmanagem

entand

providea

nevaluatio

nfram

eworkto

selectthem

osteligiblegreensupp

liers

Renetal[104]

Identifykeydrivingfactorsa

ndmap

theirc

ause-effectrelationships

fore

nhancing

the

susta

inabilityof

hydrogen

supp

lychain

Threshold

value-experts

Mud

uliand

Barve[105]

Extractthe

causalrelationships

amon

ggreensupp

lychainmanagem

entb

arrie

rsandestablish

asustainabled

evelop

mentframew

orkin

scaleInd

ianminingindu

strie

s

Mathematical Problems in Engineering 9

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

WuandCh

ang[106]

Identifythec

riticaldimensio

nsandfactorstoim

plem

entg

reen

supp

lychainmanagem

entinthe

electricalandele

ctronicind

ustries

Thresholdvalue-

average

Behera

andMuk

herje

e[107]

Capturer

elationships

andanalyzek

eyinflu

encing

factorsrele

vant

toselectionof

supp

lychain

coordinatio

nschemes

Thresholdvalue-

MMDE

Ahm

edetal[108]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

fore

valuatingsustainableE

OLvehicle

managem

entalternatives

FuzzyAHP

Ahm

edetal[109]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

andprop

osea

nintegrated

mod

elfor

sustainableE

OLvehicle

managem

entalternatives

election

AHPfuzzyA

HP

Miaoetal[110

]Ev

aluatetheimpo

rtance

andun

veiltheimplicitinterrela

tionships

amon

gdifferent

scales

ofCP

Vandconstructa

multiscalemod

elforthe

measuremento

fCPV

ofEV

sHoQ

Threshold

value-expertsrank

basedon119877+

119862Lin[111]

Analyze

interactions

amon

gindu

stria

ldevelo

pmentfactorsandexploreh

owto

establish

the

competitivenesso

fsolar

photovoltaicindu

stry

Porterrsquos

Diamon

dmod

el

AzarnivandandCh

itsaz

[112]

Quantify

theinterlin

kagesa

mon

gfund

amentalanthrop

ogenicindicatorsandprop

osea

syste

maticapproach

forw

ater

shortage

mitigatio

nin

thea

ridregion

seD

PSIRA

HP

COPR

AS-G

Chen

etal[113]

Quantify

theinfl

uenceo

nPM

25by

otherfactorsin

thew

eather

syste

mandidentifythem

ost

impo

rtantfactorsforP

M25

RMFo

urqu

adrants

dosM

uchangos

etal[114

]As

sesstheb

arrie

rsto

mun

icipalsolid

wastemanagem

entp

olicyplanning

andidentifythem

ost

onerou

sbarrie

rsto

thee

ffectiveimplem

entatio

nof

thep

olicy

ISM

Netinflu

ence

matrix

Guo

etal[115]

EvaluateandinvestigategreencorporateC

SRindicatorsof

manufacturin

gcorporations

from

agreenindu

strylawperspective

Four

quadrants

Chen

andCh

i[116

]Ex

plorek

eyfactorso

fChinarsquosCS

Rfro

mthep

erspectiv

eofaccou

ntingexperts

Changetal[117

]Identifykeystr

ategicfactorsintheimplem

entatio

nof

CSRin

airline

indu

stry

Leee

tal[118]

Calculatethe

causalrelationshipandinteractionlevelbetweenTA

Mvaria

bles

andfin

dthec

ore

varia

bles

form

anagem

ento

rimprovem

entw

hileintro

ducing

anew

etchingplasmatechn

olog

yFo

urqu

adrants

Wu[119]

Determinethe

causalrelationships

betweentheK

PIso

fthe

BSCandlin

kthem

into

astrategy

map

forb

anking

institutio

nsBS

C

Chienetal[22]

Identifyrelatio

nships

betweenris

kfactorsa

ndassesscriticalrisk

factorsfor

BIM

projects

Four

quadrants

10 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Wangetal[26]

Evaluatethep

erform

ance

ofdesig

ndelay

factorsa

ndidentifykeyfactorsthatd

rived

esigndelay

sof

afacilityconstructio

nproject

ISA

Netinflu

ence

matrix

Tzeng[19

]Investigatethe

relationshipbetweenfactorsa

ffectingparolebo

ardsrsquodecision

makingin

Taiwan

Simplified

norm

alized

total-relation

matrix

threshold

value

Gazibey

etal[120]

Analyze

thec

ause

andeffectrelations

amon

gthec

riteriaaffectin

gmainbattletankselection

Thresholdvalue-

average

Type

3interrelationships

andcriteria

weights

Khalili-D

amgh

anietal[121]

Determinethe

relativ

eimpo

rtance

weightsof

compensatoryob

jectivefun

ctions

andprop

osea

hybrid

multip

leob

jectivem

etaheuris

ticalgorithm

tosolveland-uses

uitabilityanalysisand

planning

prob

lem

AHP

Khazaietal[29]

Analyze

directandindirectdepend

encies

with

insocialandindu

stria

lvulnerabilityindicatorsand

developaframew

orkforspatia

lassessm

ento

find

ustrialand

socialvulnerabilityto

indirect

disaste

rlosses

Threshold

valuedepend

ency

weights

Tseng[122]

Resolvec

riteriainterdependencyrelationships

weightsandprop

osea

hybrid

metho

dto

evaluate

serviceq

ualityexpectationin

hotspringho

telrsquosrank

ingprob

lem

FuzzyTO

PSIS

Innerd

ependence

matrix

Quadere

tal[123]

Determinethe

causea

ndeffectrelationships

amon

gcriteria

andevaluatethec

riticalcriteria

for

CO2capturea

ndsto

rage

intheironandste

elindu

stry

Criteria

weights-

vector

leng

thth

reshold

value

Quadera

ndAhm

ed[124]

Identifycriticalfactorsfore

valuatingalternativeiron-makingtechno

logies

with

carbon

capture

andsto

rage

syste

ms

FuzzyAHP

Criteria

weights-

vector

leng

thth

reshold

value

Seyedh

osseinietal[17]

Identifythec

ause

andeffectrela

tionships

amon

glean

objectives

andprop

osed

asystematicamp

logicalm

etho

dfora

utopartmanufacturersto

determ

inethe

companyrsquoslean

strategymap

BSC

Innerd

ependence

matrix

weights-119877+

119862Cebi[27]

Determineimpo

rtance

degreeso

fwebsited

esignparametersb

ased

oninteractions

andtypeso

fwebsites

Thresholdvalue-

averagedeterm

ining

weightsusing119877+

119862Yazdani-C

hamzini

etal[28]

Analyze

interdependencea

nddepend

encies

andcompu

tetheg

lobalw

eightsfore

valuation

indicatorsandprop

osea

newhybrid

mod

elto

selectthes

trategyof

investingin

apriv

ates

ector

AHPfuzzy

TOPS

IS

Thresholdvalue-

expertsweights-119877+

119862No

teB

ackpropagatio

nneuralnetworkBP

NNbalancedscorecardBS

Cbu

ildinginformationmod

elingBIMcluste

ranalysisC

A1conjoint

analysis

CA2corporatesocialrespo

nsibilityC

SRcustomerperceived

valueCP

Vdata

envelopm

enta

nalysis

DEA

decom

posedtheory

ofplannedbehaviorD

TPB

dominance-based

roug

hseta

pproach

DRS

Aelectric

vehicle

EV

enhanced

drivingforce-pressure-state-im

pact-

respon

seeDPS

IRenterprise

resource

planning

ERP

end

-of-lifeE

OLfactor

analysis

FAfailure

mod

eand

effectanalysisFMEA

fuzzy

cogn

itive

mapFCM

fuzzy

inferences

ystemFISformalconceptanalysis

FC

Agap

analysis

GAgreyc

omplex

prop

ortio

nalassessm

entCO

PRAS-Ggreyr

elationalanalysisG

RAhou

seso

fqualityHoQ

impo

rtance-perform

ance

analysis

IPAimpo

rtance-perform

ance

andgapanalysis

IPGAimpo

rtance-satisfactio

nanalysis

ISAinformationtechno

logyITinterpretiv

estructuralm

odeling

ISM

integratedcircuitICkey

perfo

rmance

indicatorKP

Imaxim

alentro

pyorderedweightedaveraging

ME-OWAm

ultip

leregressio

nanalysis

MRA

ordered

weightedgeom

etric

averagingOWGApatentcitatio

nanalysis

PCApatentcoclassificatio

nanalysis

PCCA

relationmapR

Msatisfi

edim

portance

analysis

SIAsiliconintellectualp

ropertyor

Semicon

ductor-Intellectual-P

ropertySIP

socialnetworkanalysis

SNAstructuralequ

ationmod

elingSE

Mtechn

olog

yacceptance

mod

elTA

Mtheoryof

constraintsTO

Cvaria

blec

onsis

tencyDRS

AV

C-DRS

A

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Page 9: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

Mathematical Problems in Engineering 9

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

WuandCh

ang[106]

Identifythec

riticaldimensio

nsandfactorstoim

plem

entg

reen

supp

lychainmanagem

entinthe

electricalandele

ctronicind

ustries

Thresholdvalue-

average

Behera

andMuk

herje

e[107]

Capturer

elationships

andanalyzek

eyinflu

encing

factorsrele

vant

toselectionof

supp

lychain

coordinatio

nschemes

Thresholdvalue-

MMDE

Ahm

edetal[108]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

fore

valuatingsustainableE

OLvehicle

managem

entalternatives

FuzzyAHP

Ahm

edetal[109]

Selectthem

ostimpo

rtantd

imensio

nsandcriteria

andprop

osea

nintegrated

mod

elfor

sustainableE

OLvehicle

managem

entalternatives

election

AHPfuzzyA

HP

Miaoetal[110

]Ev

aluatetheimpo

rtance

andun

veiltheimplicitinterrela

tionships

amon

gdifferent

scales

ofCP

Vandconstructa

multiscalemod

elforthe

measuremento

fCPV

ofEV

sHoQ

Threshold

value-expertsrank

basedon119877+

119862Lin[111]

Analyze

interactions

amon

gindu

stria

ldevelo

pmentfactorsandexploreh

owto

establish

the

competitivenesso

fsolar

photovoltaicindu

stry

Porterrsquos

Diamon

dmod

el

AzarnivandandCh

itsaz

[112]

Quantify

theinterlin

kagesa

mon

gfund

amentalanthrop

ogenicindicatorsandprop

osea

syste

maticapproach

forw

ater

shortage

mitigatio

nin

thea

ridregion

seD

PSIRA

HP

COPR

AS-G

Chen

etal[113]

Quantify

theinfl

uenceo

nPM

25by

otherfactorsin

thew

eather

syste

mandidentifythem

ost

impo

rtantfactorsforP

M25

RMFo

urqu

adrants

dosM

uchangos

etal[114

]As

sesstheb

arrie

rsto

mun

icipalsolid

wastemanagem

entp

olicyplanning

andidentifythem

ost

onerou

sbarrie

rsto

thee

ffectiveimplem

entatio

nof

thep

olicy

ISM

Netinflu

ence

matrix

Guo

etal[115]

EvaluateandinvestigategreencorporateC

SRindicatorsof

manufacturin

gcorporations

from

agreenindu

strylawperspective

Four

quadrants

Chen

andCh

i[116

]Ex

plorek

eyfactorso

fChinarsquosCS

Rfro

mthep

erspectiv

eofaccou

ntingexperts

Changetal[117

]Identifykeystr

ategicfactorsintheimplem

entatio

nof

CSRin

airline

indu

stry

Leee

tal[118]

Calculatethe

causalrelationshipandinteractionlevelbetweenTA

Mvaria

bles

andfin

dthec

ore

varia

bles

form

anagem

ento

rimprovem

entw

hileintro

ducing

anew

etchingplasmatechn

olog

yFo

urqu

adrants

Wu[119]

Determinethe

causalrelationships

betweentheK

PIso

fthe

BSCandlin

kthem

into

astrategy

map

forb

anking

institutio

nsBS

C

Chienetal[22]

Identifyrelatio

nships

betweenris

kfactorsa

ndassesscriticalrisk

factorsfor

BIM

projects

Four

quadrants

10 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Wangetal[26]

Evaluatethep

erform

ance

ofdesig

ndelay

factorsa

ndidentifykeyfactorsthatd

rived

esigndelay

sof

afacilityconstructio

nproject

ISA

Netinflu

ence

matrix

Tzeng[19

]Investigatethe

relationshipbetweenfactorsa

ffectingparolebo

ardsrsquodecision

makingin

Taiwan

Simplified

norm

alized

total-relation

matrix

threshold

value

Gazibey

etal[120]

Analyze

thec

ause

andeffectrelations

amon

gthec

riteriaaffectin

gmainbattletankselection

Thresholdvalue-

average

Type

3interrelationships

andcriteria

weights

Khalili-D

amgh

anietal[121]

Determinethe

relativ

eimpo

rtance

weightsof

compensatoryob

jectivefun

ctions

andprop

osea

hybrid

multip

leob

jectivem

etaheuris

ticalgorithm

tosolveland-uses

uitabilityanalysisand

planning

prob

lem

AHP

Khazaietal[29]

Analyze

directandindirectdepend

encies

with

insocialandindu

stria

lvulnerabilityindicatorsand

developaframew

orkforspatia

lassessm

ento

find

ustrialand

socialvulnerabilityto

indirect

disaste

rlosses

Threshold

valuedepend

ency

weights

Tseng[122]

Resolvec

riteriainterdependencyrelationships

weightsandprop

osea

hybrid

metho

dto

evaluate

serviceq

ualityexpectationin

hotspringho

telrsquosrank

ingprob

lem

FuzzyTO

PSIS

Innerd

ependence

matrix

Quadere

tal[123]

Determinethe

causea

ndeffectrelationships

amon

gcriteria

andevaluatethec

riticalcriteria

for

CO2capturea

ndsto

rage

intheironandste

elindu

stry

Criteria

weights-

vector

leng

thth

reshold

value

Quadera

ndAhm

ed[124]

Identifycriticalfactorsfore

valuatingalternativeiron-makingtechno

logies

with

carbon

capture

andsto

rage

syste

ms

FuzzyAHP

Criteria

weights-

vector

leng

thth

reshold

value

Seyedh

osseinietal[17]

Identifythec

ause

andeffectrela

tionships

amon

glean

objectives

andprop

osed

asystematicamp

logicalm

etho

dfora

utopartmanufacturersto

determ

inethe

companyrsquoslean

strategymap

BSC

Innerd

ependence

matrix

weights-119877+

119862Cebi[27]

Determineimpo

rtance

degreeso

fwebsited

esignparametersb

ased

oninteractions

andtypeso

fwebsites

Thresholdvalue-

averagedeterm

ining

weightsusing119877+

119862Yazdani-C

hamzini

etal[28]

Analyze

interdependencea

nddepend

encies

andcompu

tetheg

lobalw

eightsfore

valuation

indicatorsandprop

osea

newhybrid

mod

elto

selectthes

trategyof

investingin

apriv

ates

ector

AHPfuzzy

TOPS

IS

Thresholdvalue-

expertsweights-119877+

119862No

teB

ackpropagatio

nneuralnetworkBP

NNbalancedscorecardBS

Cbu

ildinginformationmod

elingBIMcluste

ranalysisC

A1conjoint

analysis

CA2corporatesocialrespo

nsibilityC

SRcustomerperceived

valueCP

Vdata

envelopm

enta

nalysis

DEA

decom

posedtheory

ofplannedbehaviorD

TPB

dominance-based

roug

hseta

pproach

DRS

Aelectric

vehicle

EV

enhanced

drivingforce-pressure-state-im

pact-

respon

seeDPS

IRenterprise

resource

planning

ERP

end

-of-lifeE

OLfactor

analysis

FAfailure

mod

eand

effectanalysisFMEA

fuzzy

cogn

itive

mapFCM

fuzzy

inferences

ystemFISformalconceptanalysis

FC

Agap

analysis

GAgreyc

omplex

prop

ortio

nalassessm

entCO

PRAS-Ggreyr

elationalanalysisG

RAhou

seso

fqualityHoQ

impo

rtance-perform

ance

analysis

IPAimpo

rtance-perform

ance

andgapanalysis

IPGAimpo

rtance-satisfactio

nanalysis

ISAinformationtechno

logyITinterpretiv

estructuralm

odeling

ISM

integratedcircuitICkey

perfo

rmance

indicatorKP

Imaxim

alentro

pyorderedweightedaveraging

ME-OWAm

ultip

leregressio

nanalysis

MRA

ordered

weightedgeom

etric

averagingOWGApatentcitatio

nanalysis

PCApatentcoclassificatio

nanalysis

PCCA

relationmapR

Msatisfi

edim

portance

analysis

SIAsiliconintellectualp

ropertyor

Semicon

ductor-Intellectual-P

ropertySIP

socialnetworkanalysis

SNAstructuralequ

ationmod

elingSE

Mtechn

olog

yacceptance

mod

elTA

Mtheoryof

constraintsTO

Cvaria

blec

onsis

tencyDRS

AV

C-DRS

A

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Page 10: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

10 Mathematical Problems in Engineering

Table1Con

tinued

Papers

Research

purposes

Com

binatio

nsRe

marks

Wangetal[26]

Evaluatethep

erform

ance

ofdesig

ndelay

factorsa

ndidentifykeyfactorsthatd

rived

esigndelay

sof

afacilityconstructio

nproject

ISA

Netinflu

ence

matrix

Tzeng[19

]Investigatethe

relationshipbetweenfactorsa

ffectingparolebo

ardsrsquodecision

makingin

Taiwan

Simplified

norm

alized

total-relation

matrix

threshold

value

Gazibey

etal[120]

Analyze

thec

ause

andeffectrelations

amon

gthec

riteriaaffectin

gmainbattletankselection

Thresholdvalue-

average

Type

3interrelationships

andcriteria

weights

Khalili-D

amgh

anietal[121]

Determinethe

relativ

eimpo

rtance

weightsof

compensatoryob

jectivefun

ctions

andprop

osea

hybrid

multip

leob

jectivem

etaheuris

ticalgorithm

tosolveland-uses

uitabilityanalysisand

planning

prob

lem

AHP

Khazaietal[29]

Analyze

directandindirectdepend

encies

with

insocialandindu

stria

lvulnerabilityindicatorsand

developaframew

orkforspatia

lassessm

ento

find

ustrialand

socialvulnerabilityto

indirect

disaste

rlosses

Threshold

valuedepend

ency

weights

Tseng[122]

Resolvec

riteriainterdependencyrelationships

weightsandprop

osea

hybrid

metho

dto

evaluate

serviceq

ualityexpectationin

hotspringho

telrsquosrank

ingprob

lem

FuzzyTO

PSIS

Innerd

ependence

matrix

Quadere

tal[123]

Determinethe

causea

ndeffectrelationships

amon

gcriteria

andevaluatethec

riticalcriteria

for

CO2capturea

ndsto

rage

intheironandste

elindu

stry

Criteria

weights-

vector

leng

thth

reshold

value

Quadera

ndAhm

ed[124]

Identifycriticalfactorsfore

valuatingalternativeiron-makingtechno

logies

with

carbon

capture

andsto

rage

syste

ms

FuzzyAHP

Criteria

weights-

vector

leng

thth

reshold

value

Seyedh

osseinietal[17]

Identifythec

ause

andeffectrela

tionships

amon

glean

objectives

andprop

osed

asystematicamp

logicalm

etho

dfora

utopartmanufacturersto

determ

inethe

companyrsquoslean

strategymap

BSC

Innerd

ependence

matrix

weights-119877+

119862Cebi[27]

Determineimpo

rtance

degreeso

fwebsited

esignparametersb

ased

oninteractions

andtypeso

fwebsites

Thresholdvalue-

averagedeterm

ining

weightsusing119877+

119862Yazdani-C

hamzini

etal[28]

Analyze

interdependencea

nddepend

encies

andcompu

tetheg

lobalw

eightsfore

valuation

indicatorsandprop

osea

newhybrid

mod

elto

selectthes

trategyof

investingin

apriv

ates

ector

AHPfuzzy

TOPS

IS

Thresholdvalue-

expertsweights-119877+

119862No

teB

ackpropagatio

nneuralnetworkBP

NNbalancedscorecardBS

Cbu

ildinginformationmod

elingBIMcluste

ranalysisC

A1conjoint

analysis

CA2corporatesocialrespo

nsibilityC

SRcustomerperceived

valueCP

Vdata

envelopm

enta

nalysis

DEA

decom

posedtheory

ofplannedbehaviorD

TPB

dominance-based

roug

hseta

pproach

DRS

Aelectric

vehicle

EV

enhanced

drivingforce-pressure-state-im

pact-

respon

seeDPS

IRenterprise

resource

planning

ERP

end

-of-lifeE

OLfactor

analysis

FAfailure

mod

eand

effectanalysisFMEA

fuzzy

cogn

itive

mapFCM

fuzzy

inferences

ystemFISformalconceptanalysis

FC

Agap

analysis

GAgreyc

omplex

prop

ortio

nalassessm

entCO

PRAS-Ggreyr

elationalanalysisG

RAhou

seso

fqualityHoQ

impo

rtance-perform

ance

analysis

IPAimpo

rtance-perform

ance

andgapanalysis

IPGAimpo

rtance-satisfactio

nanalysis

ISAinformationtechno

logyITinterpretiv

estructuralm

odeling

ISM

integratedcircuitICkey

perfo

rmance

indicatorKP

Imaxim

alentro

pyorderedweightedaveraging

ME-OWAm

ultip

leregressio

nanalysis

MRA

ordered

weightedgeom

etric

averagingOWGApatentcitatio

nanalysis

PCApatentcoclassificatio

nanalysis

PCCA

relationmapR

Msatisfi

edim

portance

analysis

SIAsiliconintellectualp

ropertyor

Semicon

ductor-Intellectual-P

ropertySIP

socialnetworkanalysis

SNAstructuralequ

ationmod

elingSE

Mtechn

olog

yacceptance

mod

elTA

Mtheoryof

constraintsTO

Cvaria

blec

onsis

tencyDRS

AV

C-DRS

A

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Page 11: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

Mathematical Problems in Engineering 11

I

0

II

IVIII

Prominence

Rela

tion

Mean

R minus C

R + C

Figure 2 Four-quadrant IRM

Figure 2 by calculating the mean of (119877 + 119862) The factors inquadrant I are identified as core factors or intertwined giverssince they have high prominence and relation the factors inquadrant II are identified as driving factors or autonomousgivers because they have low prominence but high relationThe factors in quadrant III have low prominence and relationand are relatively disconnected from the system (calledindependent factors or autonomous receivers) the factors inquadrant IV have high prominence but low relation (calledimpact factors or intertwined receivers) which are impactedby other factors and cannot be directly improved FromFigure 2 decision makers can visually detect the complexcausal relationships among factors and further spotlightvaluable insights for decision making

In addition Wu et al [23] developed a duo-themeDEMATEL to explore the decisive factors affecting the adop-tion Software as a Service (SaaS) in an organization Theytreated the perceived benefits (PB) and perceived risks (PR) ofadopting SaaS solutions as two distinct themes and developeda four-quadrant causal map called PB-PR matrix to facili-tate decision making (see Figure 3) The primary differencebetween the duo-theme and the traditional DEMATEL is thatthe duo-theme DEMATEL combine two IRMs into a singlePB-PRmatrix by transforming ldquopositiverdquo (119877+119862) value of eachfactor in PR into ldquonegativerdquo [24]

Step 5-1 (net influence matrix) After visualizing the complexcausal relationships among factors using the IRM Wang etal [25 26] further developed the net influence matrix 119873 =[Net119894119895]119899times119899 to evaluate the strength of influence of one factoron another in which

Net119894119895 = 119905119894119895 minus 119905119895119894 (8)

Step 6 (calculate the importance weights for criteria) Insome studies the classical DEMATEL technique was used tocompute theweights of criteria Normally the criteria weightsare determined based on the prominence (119877 + 119862) through anormalization procedure as follows [27 28]

119908119894 = 119903119894 + 119888119894sum119899119894=1 119903119894 + 119888119894 119894 = 1 2 119899 (9)

I

0

II

IVIII

Cause factors ofperceived benefits

Cause factors ofperceived risks

Effect factors ofperceived benefits

Effect factors ofperceived risks

R minus C

R + C

Figure 3 The PB-PR matrix

To correct for structural relations among criteria Khazaiet al [29] proposed using the degree of dispatching 119903119894 tocalculate the dependency weights of criteria

119908119889119894 = 1 minus 119903119894 minus 119903min119903max minus 119903min (10)

where 119903min = 119899(min119894119895119905119894119895) and 119903max = 119899(max119894119895119905119894119895)Then the overall weight of each criterion119908119894 is derived by

119908119894 = 119908119900119894sum119899119894=1 119908119900119894 119894 = 1 2 119899119908119900119894 = 119908im

119894 times 119908119889119894 (11)

where 119908im119894 is the importance weight of the 119894th criterion

assigned by a group of experts

312 Comparison with Other MCDM Methods In the liter-ature a lot of effective MCDM methods were developed fordealingwith group decisionmaking problems [30ndash32] In thispart the DEMATEL technique is compared with some otherMCDM methods to show its advantages and disadvantagesWe choose the most commonly used methods in MCDMthat is analytic hierarchical process (AHP) grey relationalanalysis (GRA) technique for order performance by simi-larity to ideal solution (TOPSIS) VIKOR (Vise Kriterijum-ska Optimizacija I Kompromisno Resenje) and ELECTRE(ELimination Et Choix Traduisant la REalite) to compare theprocedural basis of these MCDMmethods

In the AHP a hierarchy considers the distribution of agoal among the elements being compared and judges whichelement has a greater influence on that goal [33 34] TheGRA is an impact evaluation model that measures the degreeof similarity or difference between two sequences basedon relation grade [35] The VIKOR method introduces theranking index based on the particular measure of ldquoclosenessrdquoto the ideal solution by using linear normalization [36] Thebasic principle of the TOPSIS is that the chosen alternative

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Mathematical Problems in Engineering

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Page 12: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

12 Mathematical Problems in Engineering

should have the shortest distance from the ideal solution andthe farthest distance from the negative-ideal solution [37]The ELECTRE is a prominent outrankingMCDM techniquewhich selects the best action from a proposed set of onesbased on multiattribute utility theory [38] Compared withthese MCDM methods the DEMATEL technique has thefollowing advantages (1) It effectively analyzes the mutualinfluences (both direct and indirect effects) among differentfactors and understands the complicated cause and effectrelationships in the decision making problem (2) It is ableto visualize the interrelationships between factors via anIRM and enable the decision maker to clearly understandwhich factors have mutual influences on one another (3)TheDEMATEL can be used not only to determine the rankingof alternatives but also to find out critical evaluation criteriaand measure the weights of evaluation criteria Althoughthe AHP can be applied to rank alternatives and determinecriteria weights it assumes that the criteria are independentand fails to consider their interactions and dependenciesTheANP an advanced version of the AHP can deal with thedependence and feedback between criteria but as indicatedin [39ndash41] the assumption of equal weight for each cluster toobtain a weighted supermatrix in the ANP is not reasonablein practical situations

On the other hand in comparison to other MCDMmethods the possible disadvantages of the DEMATEL tech-nique may be the following (1) It determines the rankingof alternatives based on interdependent relationships amongthem but other criteria are not incorporated in the decisionmaking problem (2)The relative weights of experts are notconsidered in aggregating personal judgments of expertsinto group assessments (3) It cannot take into account theaspiration level of alternatives as in the GRA and VIKORmethods or obtain partial ranking orders of alternatives asin the ELECTRE approach Therefore the DEMATEL hasbeen integrated with otherMCDMmethods to combine theirdesired properties in the literature Next we will discussthe situations in which it is more appropriate to use theDEMATEL method before some other methods

313 Combination with Other Methods Analyzing the datacontained in Table 1 we can observe that the crispDEMATELhas been combined with a variety of other methods or toolsto solve the management decision problems effectively andthe methods most frequently integrated with the DEMA-TEL include AHP balanced scorecard (BSC) TOPSIS andquality function deployment (QFD) Generally the classicalDEMATEL are applied to the following circumstances incombination with other methods First it can be used toidentify the interdependency among dimensions or perspec-tives For example the DEMATEL was applied to determinethe interrelationships between four BSC perspectives [16]and to unveil the implicit interrelationships of customerrequirements [210] Second it can be used to calculate theweights of evaluation criteria For instance the DEMATELwas employed to resolve criteria interdependency relation-ship weights and then the TOPSIS is utilized to evaluate theservice quality of hot spring hotels [122]Third it can be usedto determine critical factors or criteria via analyzing their

dependent relations For example the DEMATEL methodwas applied first to select the most important sustainablecriteria and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108]

32 Fuzzy DEMATEL In the original DEMATEL the rela-tionships of decision factors are assessed by crisp values soas to establish a structural model However in many real-world applications human judgments are often unclear andexact numerical values are inadequate to estimate the vagueinterdependency relationships between criteria Hence theconcept of fuzzy sets [214] has been applied to the DEMATELmethod by many researchers The fuzzy DEMATEL papersidentified in this literature survey are summarized in Table 2for the convenience of reading and understandingThis tablealso gives the classification of such papers based on differentpurposes of using the fuzzy DEMATEL Generally two typesof fuzzy DEMATEL model have been put forward in theliterature that is fuzzy logic andDEMATEL and fuzzy-basedDEMATEL which will be outlined briefly in the following

321 Fuzzy Logic and DEMATEL In this model fuzzylogic and DEMATEL are combined in a decision model butimplemented independently This model first employs fuzzysets to handle the expertsrsquo vague judgments and assessmentson impact levels between factors and converts fuzzy numbersinto crisp values for the group direct-influence matrix 119885and then performs the classical DEMATEL procedure Basedon the basic definitions and operations of fuzzy sets thefollowing fuzzy logic and DEMATEL methodology wasdeveloped [130ndash132]

Step 1 Evaluate the mutual influences between factors usingfuzzy linguistic scale

In this step it is necessary to establish a fuzzy linguisticscale to assess the causal relationships among factors Inorder to tackle the vagueness and imprecision in humanassessments the linguistic terms ldquoNo Very Low Low HighVery Highrdquo expressed in triangular fuzzy numbers can beused for the linguistic variable ldquoinfluencerdquo As a result theindividual direct-influence fuzzy matrix 119885119896 = [119896119894119895]119899times119899 isacquired for each of the respondents 119864 = 1198641 1198642 119864119897where 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) is the fuzzy assessment of expert119864119896 regarding the influence degree between factors 119865119894 and 119865119895Step 2 Aggregate the assessments of experts and set up thegroup direct-influence fuzzy matrix 119885

After constructing the individual matrixes 119885119896 (119896 =1 2 119897) we can calculate the group direct-influence fuzzymatrix119885 = [119894119895]119899times119899 via aggregating all the expertsrsquo judgmentswhere 119894119894 can be viewed as a triangular fuzzy number (0 0 0)and 119894119895 is derived by

119894119895 = (1199111198941198951 1199111198941198952 1199111198941198953) = 1119897119897sum119896=1

119896119894119895= (1119897

119897sum119896=1

1199111198961198941198951 1119897119897sum119896=1

1199111198961198941198952 1119897119897sum119896=1

1199111198961198941198953) (12)

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

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owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Mathematical Problems in Engineering

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Page 13: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

Mathematical Problems in Engineering 13

Table2Va

rious

applications

offuzzyDEM

ATEL

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Fuzzylogica

ndDEM

ATEL

Kuo[125]

Interrelationships

Con

structa

suitablee

valuationstructureb

etweencriteria

andprop

osea

hybrid

metho

dforo

ptim

allocatio

nselectionfora

ninternational

distrib

utioncenter

AHPANPfuzzy

TOPS

ISfuzzy

measure

Defuzzification-

CFCS

threshold

value-average

Altu

ntas

etal[126]

Interrelationships

Find

thec

losenessratin

gsbetweenthefacilitie

sand

prop

osea

fuzzy

approach

forfacilitylayout

prob

lem

Defuzzification-CF

CS

Altu

ntas

andYilm

az[127]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectfactorsof

marketin

gresourcesa

ndprioritizethem

forsmall-andmedium-sized

enterpris

es

Defuzzification-

CFCS

threshold

value-average

Kabaketal[128]

Interrelationships

Keyfactorscriteria

Determinec

riticalsuccessfactorsshapingthec

ompetitivenesslevelof

theironandste

elindu

stryin

Turkey

Defuzzification-CF

CS

Luthra

etal[129]

Interrelationships

Keyfactorscriteria

Evaluatethee

nablersinsolarp

ower

developm

entsin

inIndiarsquos

current

scenario

Defuzzification-

bisectionof

area

WuandLee[130]

Interrelationships

Keyfactorscriteria

Prop

osea

metho

dto

segm

entrequiredcompetenciesfor

prom

otingthe

competencydevelopm

ento

fglobalm

anagers

Defuzzification-CF

CS

Liou

etal[131]

Interrelationships

Keyfactorscriteria

Map

outthe

structuralrelations

andidentifykeyfactorsa

nddevelopa

metho

dforb

uildingan

effectiv

esafetymanagem

entsystem

fora

irlines

Defuzzification-

COAth

reshold

value-experts

Tseng[132]

Interrelationships

Keyfactorscriteria

Integrateh

otelserviceq

ualityperceptio

nsinto

acause-effectmod

elfor

assessingcharacteris

ticsc

riteriaof

serviceq

ualitymeasurement

Defuzzification-

CFCS

innerd

ependence

matrix

TsengandLin[133]

Interrelationships

Keyfactorscriteria

Handler

elatio

nsbetweencausea

ndeffecto

fcriteriaanddevelopac

ause

andeffectm

odelof

mun

icipalsolid

wastemanagem

ent

Defuzzification-

CFCS

innerd

ependence

matrix

Changetal[134]

Interrelationships

Keyfactorscriteria

Evaluatesupp

lierp

erform

ance

tofin

dinflu

entia

lcriteriain

selecting

supp

liers

Defuzzification-CF

CS

ChangandCh

eng[135]

Interrelationships

Keyfactorscriteria

Analyze

ther

elationbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

napproach

torank

ther

iskof

failu

res

FuzzyOWA

Defuzzification-

maxim

umdegree

ofmem

bership

Zhou

etal[136]

Interrelationships

Keyfactorscriteria

Analyze

causalrelationships

andidentifykeysuccessfactorsfor

improvingtheo

verallem

ergencymanagem

ent

Defuzzification-CF

CS

Tsengetal[137]

Interrelationships

Keyfactorscriteria

Handlethe

intertwiningwith

inas

etof

criteria

andprovidea

nintegrated

serviceq

ualityexpectationmod

elforimprovingho

tspringmanagem

ent

Innerd

ependence

matrix

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Page 14: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

14 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Tseng[138]

Interrelationships

Keyfactorscriteria

Handlethe

innerd

ependencew

ithin

decisio

ncriteria

ofEK

MCand

developam

odelfore

valuatingthefi

rmEK

MCcapacity

Defuzzification-

CFCS

innerd

ependence

matrix

Wu[139]

Interrelationships

Keyfactorscriteria

Segm

entthe

criticalfactorsforsuccessfulkno

wledgem

anagem

ent

implem

entatio

nsDefuzzification-CF

CS

Lin[14

0]Interrelationships

Keyfactorscriteria

Exam

inethe

causea

ndeffectrelationships

amon

gcriteria

andform

astructuralmod

elto

evaluategreensupp

lychainmanagem

entp

ractices

Defuzzification-

CFCS

innerd

ependence

matrix

Patil

andKa

nt[14

1]Interrelationships

Keyfactorscriteria

Identifycriticalsuccessfactorso

fkno

wledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-graded

mean

Rouh

anietal[14

2]Interrelationships

Keyfactorscriteria

Evaluateandassessthec

riticalfactorsinER

Pprojectimplem

entatio

nFu

zzyAHP

Defuzzification-CF

CS

Wuetal[143]

Interrelationships

Keyfactorscriteria

Identifycriticalfactorsinflu

encing

theu

seof

additiv

esby

food

enterpris

esin

China

Defuzzification-

CFCS

threshold

value-qu

artile

Zhou

etal[144]

Interrelationships

Keyfactorscriteria

Measure

ther

elatio

nships

amon

gdifferent

factorsa

nddevelopar

oot

caused

egreep

rocedu

reform

easurin

gintersectio

nsafetyfactors

Defuzzification-CF

CS

Dou

etal[145]

Interrelationships

Keyfactorscriteria

Exam

inethe

cause-effectinterrelationships

amon

gES

DPs

andprop

oses

amod

elforfocalcompanies

toevaluateES

DPs

Fuzzyscoringmetho

dDefuzzification-CF

CS

Govindanetal[146]

Interrelationships

Keyfactorscriteria

Evaluatethed

riverso

fcorpo

ratesocialrespon

sibilityim

plem

entatio

nin

them

iningindu

stry

Defuzzification-centroid

metho

d

RoutroyandSunilK

umar

[147]

Interrelationships

Keyfactorscriteria

Identifyandestablish

relatio

nshipam

ongvario

ussupp

lierd

evelo

pment

program

enablersin

aspecific

manufacturin

genvironm

ent

Defuzzification-

CFCS

threshold

value-average

Tyagietal[14

8]Interrelationships

Keyfactorscriteria

Assesscriticalenablersfor

flexibles

upplychainperfo

rmance

measurementsystem

Defuzzification-

CFCS

threshold

value-average

Wuetal[149]

Interrelationships

Keyfactorscriteria

Identifyinteractions

amon

gthesec

riteriaandexplored

ecisive

factorsin

greensupp

lychainpractic

es

Defuzzification-

CFCS

innerd

ependence

matrix

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Mathematical Problems in Engineering

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Submit your manuscripts atwwwhindawicom

Page 15: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

Mathematical Problems in Engineering 15

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Sang

aiah

etal[150]

Interrelationships

Keyfactorscriteria

Criteria

weights

EvaluateGSD

projecto

utcomefactorsandfin

dthes

ignificance

ofcriteria

inorganizatio

nalbehaviorresearchph

enom

enon

TOPS

ISDefuzzification-

CFCS

weights-

vector

leng

th

Malviya

andKa

nt[151]

Interrelationships

Criteria

weights

Predictand

measure

thes

uccesspo

ssibilityof

greensupp

lychain

managem

entimplem

entatio

nDefuzzification-

CFCS

weights-119877+

119862Patil

andKa

nt[152]

Interrelationships

Criteria

weights

Evaluatewe

ightingof

criteria

andprop

osea

predictio

nfram

eworkfor

know

ledgem

anagem

entado

ptionin

supp

lychain

Defuzzification-

CFCS

weights-119877+

119862Sang

aiah

etal[153]

Interrelationships

Criteria

weights

Presentanintegrated

fram

eworkto

evaluatekn

owledgetransfer

effectiv

enessw

ithreferencetoGSD

projecto

utcome

TOPS

ISE

LECT

REDefuzzification-

CFCS

weights-119877+

119862Ba

keshlouetal[154]

Interrelationships

Criteria

weights

Und

ersta

ndtheinterrelatio

nam

ongcriteria

andprop

osea

hybrid

MODM

algorithm

forg

reen

supp

liersele

ction

FuzzyANPfuzzy

MOLP

Defuzzification-

CFCS

weights-

fuzzy

ANP

Fuzzy-basedDEM

ATEL

Jassbietal[155]

Interrelationships

Capturethe

causalrelatio

nships

betweenstr

ategicob

jectives

fora

strategymap

BSC

Defuzzification-CO

G

Leee

tal[156]

Interrelationships

Reanalyzea

ndexplainthec

ausalrela

tionshipandlevelofm

utualeffect

betweenvaria

bles

inTA

M

Defuzzification-

CFCS

(T)threshold

value

Valm

oham

madiand

Sofiyabadi[157]

Interrelationships

Analyze

thec

ausesa

ndeffectsrelatio

nsof

strategy

map

anddevelopa

strategymap

fora

nautomotiveind

ustry

BSC

Defuzzification-

CFCS

2no

rmalization

andaggregation

Youn

esiand

Rogh

anian[158]

Interrelationships

Assumethe

interdependenceo

fcustomer

attributes

andprop

osea

fram

eworkforsustainableprod

uctd

esign

QFD

fuzzy

ANP

Defuzzification-

centroid

metho

dthreshold

value-fuzzyMMDE

16 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

LinandWu[159]

Interrelationships

Keyfactorscriteria

Prop

osea

causalanalyticalmetho

dforg

roup

decisio

nmakingun

der

fuzzyenvironm

entand

applieditforR

ampDprojectsele

ction

Defuzzification-

CFCS

2no

rmalization

andaggregation

Fekrietal[160]

Interrelationships

Keyfactorscriteria

Identifythec

ause

andeffectg

roup

sofcriticalsuccessfactorsof

agile

newprod

uctd

evelo

pmentp

rocess

Explanatoryfactor

analysis

Defuzzification-

CFCS

2no

rmalization

andaggregation

Jeng

andTzeng[161]

Interrelationships

Keyfactorscriteria

Explorethe

causalrelatio

nshipbetweenUTA

UTvaria

bles

andexam

ine

socialinflu

ence

ontheu

seof

clinicald

ecision

supp

ortsystem

Defuzzification-CF

CS(T)threshold

value-experts

Chou

etal[162]

Interrelationships

Keyfactorscriteria

Establish

contextualrelationships

amon

gcriteria

andevaluatethe

criteria

forh

uman

resource

forscience

andtechno

logy

FuzzyAHP

Defuzzification-

CFCS

2no

rmalization

andaggregation

Afsharkazem

ietal[163]

Interrelationships

Keyfactorscriteria

Measure

directandindirectrelationships

betweenfactorsa

ndidentify

keyfactorsa

ffectingtheh

ospitalp

erform

ance

Defuzzification-

centroid

metho

dno

rmalization

andaggregation

RenandSovacool[164

]Interrelationships

Keyfactorscriteria

Identifycause-effectrelationships

amon

genergy

securitymetric

sto

determ

inethe

mostsalient

andmeaning

fuld

imensio

nsandenergy

securitystr

ategies

Defuzzification-CF

CS2

Akyuz

andCelik[165]

Interrelationships

Keyfactorscriteria

Evaluatecriticaloperatio

nalh

azards

durin

ggasfreeing

processincrud

eoiltankers

Defuzzification-CO

A

Tsao

andWu[166]

Interrelationships

Keyfactorscriteria

Evaluatethec

ause-effectrelatio

nshipof

complex

drillingprob

lemsfor

compo

undspecial-c

ored

rillin

gcompo

sitem

aterials

Defuzzification-

CFCS

2no

rmalization

andaggregation

Hoetal[167]

Interrelationships

Keyfactorscriteria

Analyze

thec

ause-effectrelationshipandthem

utualinfl

uenceo

finform

ationsecuritycontrolitemsa

ndidentifycore

controlitemsfor

inform

ationsecuritymanagem

entand

improvem

entstrategies

Defuzzification-

CFCS

2threshold

value

Jeng

[168]

Interrelationships

Keyfactorscriteria

Prob

ethe

relatio

nships

amon

gkeydimensio

nsin

supp

lychain

collabo

ratio

nto

enablebette

rstrategicdevelopm

ento

fmanufacturin

gfirms

Defuzzification-CF

CS(T)

Liuetal[169]

Interrelationships

Keyfactorscriteria

Analyze

ther

elatio

nsbetweenfailu

remod

esandcauses

offailu

reand

prop

osea

riskassessmentm

etho

dology

torank

ther

iskof

failu

res

FWA

Defuzzification-graded

mean

Panaihfare

tal[170]

Interrelationships

Keyfactorscriteria

Explorethe

keyfactorsinretailersele

ctionforc

ollabo

rativ

eplann

ing

forecastingandreplenish

mentand

ther

elatio

nships

betweenthese

factors

Defuzzification-

COAth

reshold

value-averageo

fpositive

119877minus119862

Hsu

etal[171]

Interrelationships

Criteria

weightsKe

yfactorscriteria

Find

t hek

eyfactorsinbu

ildingthes

tructure

relations

ofan

ideal

custo

merrsquoschoice

behavior

andprop

osea

fram

eworkform

arketin

gstrategicp

lann

ing

FuzzyANPfuzzy

AHP

Thresholdvalue-average

Mathematical Problems in Engineering 17

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

Cebi[172]

Interrelationships

Criteria

weights

Keyfactorscriteria

Determinec

riticaldesig

ncharacteris

ticso

fwebsites

basedon

interactions

amon

gthem

andpresentanintegrated

metho

dology

toevaluatethep

erceived

desig

nqu

ality

ofshop

ping

websites

Choq

uetintegral

Defuzzification-

centroid

metho

dweights-

119877+119862th

reshold

value

Gigovicetal[173]

Interrelationships

Criteria

weights

Evaluateland

suitabilityforthe

developm

ento

fecotourism

inther

egion

ofldquoD

unavskiK

ljucrdquo

Weights-

vector

leng

th

Jeon

getal[174]

Interrelationships

Criteria

weights

Identifyruralh

ousin

gsrsquosuitables

itesinreservoira

reas

under(mass)

tourism

Weights-

vector

leng

th

Rahimdeland

Bagh

erpo

ur[175]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

degree

ofcriteria

forthe

haulages

ystem

selectionforo

penpitm

ines

FuzzyTO

PSIS

Dalalah

etal[176]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uentialrelationshipbetweenthee

valuationcriteria

and

prop

osea

hybrid

fuzzymod

elforsup

pliersele

ction

Defuzzificationweights-

vector

leng

thnormalization

andaggregation

Hieteetal[177]

Interrelationships

Criteria

weights

Analyze

andcorrectfor

relations

betweenvaria

bles

inac

ompo

site

indicatorfor

disaste

rresilience

Dependency

weights

threshold

value-graphicalm

etho

d

WangandCh

en[178]

Interrelationships

Criteria

weights

Derivethe

prioritieso

ftechn

icalattributes

anddevelopafuzzy

MCD

MbasedQFD

toassis

tanenterpris

efor

collabo

rativ

eprodu

ctdesig

nQFD

LIP

Defuzzification-

centroid

metho

d(T)

Wang[179]

Interrelationships

Criteria

weights

Recogn

izethe

causalities

betweenmarketin

grequ

irementsandtechnical

attributes

andprop

osea

napproach

tocond

uctvendo

rassessm

entfor

busin

ess-intelligences

ystems

QFD

fuzzy

AHP

Defuzzification-CO

A(T)weights-|119877minus

119862|Ba

ykasoglu

etal[180]

Interrelationships

Criteria

weights

Evaluatethew

eightsof

thec

riteriaandprop

osea

mod

elforsolving

truckselectionprob

lem

ofalandtransportatio

ncompany

FuzzyTO

PSIS

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

18 Mathematical Problems in Engineering

Table2Con

tinued

Papers

Categorie

sRe

search

purposes

Com

binatio

nsRe

marks

WangandWu[181]

Interrelationships

Criteria

weights

Identifythed

ependencea

mon

gevaluatio

nfactorsa

ndprop

osea

fram

eworkto

evaluateprogrammablelogicc

ontro

llersup

pliers

FuzzyAHP

Defuzzification-

centroid

metho

d(T)

Fetanatand

Kho

rasaninejad[182]

Interrelationships

Criteria

weights

Dealw

iththeinfl

uences

ofcriteria

into

each

othera

ndprop

osea

hybrid

MCD

Mapproach

foro

ffsho

rewindfarm

sites

election

FuzzyANPfuzzy

ELEC

TRE

Defuzzification-Yager

rank

ingmetho

d(T)innerd

ependence

matrix

Huetal[183]

Interrelationships

Criteria

weights

Addressesthe

interdependencea

ndfeedback

effectsbetweencriteria

and

developah

ybrid

MCD

Mmod

elto

improvem

obile

commerce

adop

tion

FuzzyDANPfuzzy

VIKOR

Weights-

fuzzy

DANPfuzzyIRM

Keskin

[184]

Interrelationships

Criteria

weights

Analyze

theinteractio

nsbetweencriteria

anddeterm

inetheirweights

forsup

pliere

valuationandselection

Fuzzyc-means

algorithm

Defuzzification-sig

ned

distance

metho

dweights-

vector

leng

th

Pamucar

andCirovic[185]

Interrelationships

Criteria

weights

Obtainthew

eightcoefficientsof

criteria

andpresenta

mod

elforthe

selectionof

transportand

hand

lingresourcesinlogisticsc

enters

MABA

CDefuzzification-graded

mean(T)weights-

vector

leng

th

Taskin

etal[186]

Interrelationships

Criteria

weights

Determinethe

impo

rtance

weightsof

evaluatio

ncriteria

andprop

osea

fram

eworkfore

valuatingtheh

ospitalservice

quality

FuzzyANPVIKOR

Defuzzification-CF

CS(T)thresholdvalue-

expertsweights-

fuzzy

ANP

NoteD

EMAT

EL-based

analyticnetworkp

rocessD

ANPfuzzyw

eightedaverageFW

Aenviro

nmentalpracticesinkn

owledgem

anagem

entcapabilityEKM

Cenvironm

entalsup

plierd

evelo

pmentprogram

ESD

Pglob

alsoftw

ared

evelo

pmentGSD

linearinteger

programmingLIP

multiattributiveb

ordera

pproximationarea

comparis

onM

ABA

Cmultio

bjectiv

edecision

makingMODMunifiedtheory

ofacceptance

and

useo

ftechn

ologyUTA

UT

Mathematical Problems in Engineering 19

Step 3 Transform the group fuzzy assessments into crispvalues and form the group direct-influence matrix 119885

Using a defuzzification method the group direct-influence fuzzy matrix 119885 = [119894119895]119899times119899 can be defuzzified as agroup direct-influence matrix 119885 Or according to the CFCS(converting fuzzy data into crisp scores) method [215] thefuzzy assessments of experts 119885119896 (119896 = 1 2 119897) on thepairwise relations between factors can be defuzzified andaggregated into crisp scores to construct the group direct-influence matrix 119885 [126 130 132 134 136 137 139 142ndash144 147ndash149 152]

Step 4 Apply the classical DEMATEL approach to

(i) establish the normalized direct-influence matrix119883(ii) construct the total-influence matrix 119879(iii) produce the IRM

From the group direct-influence matrix 119885 the normal-ized direct-influence matrix119883 can be arrived at by (2) Thenthe total-influence matrix 119879 is obtained through (4) Finallyan IRM can be constructed by using (5) with the horizontalaxis (119877 + 119862) and the vertical axis (119877 minus 119862)322 Fuzzy-BasedDEMATEL In this extendedmodel fuzzylogic is first employed to deal with the vagueness andimprecision involved in the influence degree estimationthen the DEMATEL analysis is completed and finally theresulting fuzzy numbers are converted into numerical valuesfor making decisions The analytical procedure of fuzzy-based DEMATEL model is described as follows [159 171]

Step 1 Evaluate the relationships between factors using fuzzylinguistic scale

Step 2 Establish the group direct-influence fuzzy matrix119885 =[119894119895]119899times119899Step 3 Generate the normalized direct-influence fuzzymatrix119883 by

119883 = 119885119903 (13)

where

119883 =[[[[[[[

11990911 11990912 sdot sdot sdot 119909111989911990921 11990922 sdot sdot sdot 1199092119899 d

1199091198991 1199091198992 sdot sdot sdot 119909119899119899

]]]]]]] (14)

119903 = max1le119894le119899

( 119899sum119895=1

1199111198941198953) (15)

At least one 119894 is assumed such that sum119899119895=1 1199111198941198953 lt 119903 Note thatin some studies [157 159 160 162 166 176] the individual

direct-influence fuzzy matrixes 119885119896 (119896 = 1 2 119897) arenormalized first and then aggregated via arithmetic meanto get the normalized direct-influence fuzzy matrix 119883 Inaddition formula (16) was utilized to normalize the groupdirect-influence fuzzy matrix 119885 in [156 161 168 172 178 179181 183]

119903 = max119894119895

[[max1le119894le119899

( 119899sum119895=1

1199111198941198953) max1le119895le119899

( 119899sum119894=1

1199111198941198953)]] (16)

Step 4 Obtain the total-influence fuzzy matrix = [119894119895]119899times119899by

= limℎrarrinfin

(1198831 + 1198832 + sdot sdot sdot + 119883ℎ) = 119883 (1 minus 119883)minus1 when lim

ℎrarrinfin119883ℎ = 119874 (17)

Here 119894119895 = (1199051198941198951 1199051198941198952 1199051198941198953) and1198791 = [1199051198941198951]119899times119899 = 1198831 (119868 minus 1198831)minus1 1198792 = [1199051198941198952]119899times119899 = 1198832 (119868 minus 1198832)minus1 1198793 = [1199051198941198953]119899times119899 = 1198833 (119868 minus 1198833)minus1

(18)

in which 1198831 = [1199091198941198951]119899times119899 1198832 = [1199091198941198952]119899times119899 1198833 = [1199091198941198953]119899times119899and 119868 is an identity matrix The elements of triangular fuzzynumbers in the matrix are divided into 1198791 1198792 and 1198793and 1198791 ≺ 1198792 ≺ 1198793 when 1199091198941198951 lt 1199091198941198952 lt 1199091198941198953 for any 119894 119895 isin1 2 119899Step 5 Produce the IRM

Once the total-influence fuzzy matrix is obtained then119894 +119862119894 and 119894 minus119862119894 can be calculated easily in which 119894 and119862119894are the sumof rows and the sumof columnswithin thematrix respectively Next the fuzzy numbers of 119894 +119862119894 and 119894 minus119862119894are converted into crisp numbers by using a defuzzificationmethod A causal diagram can be drawn like the classicalDEMATEL by mapping the ordered pairs of (119894 + 119862119894)def and(119894 minus 119862119894)def

In the above the fuzzy numbers are not transformed untilafter calculating the prominence degree 119894 + 119862119894 and the neteffect 119894 minus 119862119894 But a defuzzification step was implemented inStep 4 by some researchers [161 179 181 182] to defuzzify thetotal-influence fuzzy matrix into the total-influence matrix119879The rest of the steps are the same as the original DEMETALtechnique

Generally triangular fuzzy numbers were utilized inthe fuzzy DEMETAL studies except [129 177] In [177]the authors developed an extension of fuzzy DEMATEL totrapezoidal membership functions to analyze the complexcause-effect relationships between variables in a compos-ite indicator for disaster resilience In [129] the authorsemployed a fuzzy DEMATELmethodology using trapezoidalfuzzy numbers for evaluating the enablers in solar powerdevelopments in India

20 Mathematical Problems in Engineering

323 Observations and Findings

(1) Defuzzification Methods In the fuzzy DEMATEL lit-erature a variety of defuzzification methods have beenemployed for the factor interrelation analysis Consideringthat the defuzzification of fuzzy numbers is very vital fortheDEMATELmethodologies combinedwith fuzzy logic wehere conduct a survey on the defuzzification algorithms usedin the fuzzy DEMATEL studies

The CFCS method suggested by Opricovic and Tzeng[215] is the most prevalently adopted defuzzification algo-rithm in the fuzzy logic and DEMATEL models For thefuzzy influence assessment 119896119894119895 = (1199111198961198941198951 1199111198961198941198952 1199111198961198941198953) given byexpert 119864119896 the defuzzification procedure based on the CFCSis performed as follows [130 136 138 215 216]

Step 1 Normalization of the fuzzy numbers

1199111198961198941198951 = 1199111198961198941198951 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (19)

1199111198961198941198952 = 1199111198961198941198952 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (20)

1199111198961198941198953 = 1199111198961198941198953 minusmin 1199111198961198941198951max 1199111198961198941198953 minusmin 1199111198961198941198951 (21)

Step 2 Compute left and right normalized values

119897119911119896119894119895 = 11991111989611989411989521 + 1199111198961198941198952 minus 1199111198961198941198951 (22)

119903119911119896119894119895 = 11991111989611989411989531 + 1199111198961198941198953 minus 1199111198961198941198952 (23)

Step 3 Compute total normalized crisp value

119905119911119896119894119895 = 119897119911119896119894119895 (1 minus 119897119911119896119894119895) + 1199031199111198961198941198951199031199111198961198941198951 minus 119897119911119896119894119895 + 119903119911119896119894119895 (24)

Step 4 Compute crisp values

119911119896119894119895 = min 1199111198961198941198951 + 119905119911119896119894119895 (max 1199111198961198941198953 minusmin 1199111198961198941198951) (25)

Then the different judgments of 119897 experts are integrated toconstruct the group direct-influence matrix 119885 by

119911119894119895 = 1119897119897sum119896=1

119911119896119894119895 (26)

In the fuzzy-based DEMATEL methods the followingCFCS method was applied to calculate the prominence (119894 +119862119894)def and the relation (119894 minus 119862119894)def [159 162 164 167]

119910119894 = 119871 + Δ times (119898119894 minus 119871) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871)2 (Δ + 119898119894 minus 119897119894)2(Δ + 119898119894 minus 119897119894) (Δ + 119906119894 minus 119898119894)2 (119877 minus 119897119894) + (119906119894 minus 119871) (Δ + 119898119894 minus 119897119894)2 (Δ + 119906119894 minus 119898119894) (27)

where 119910119894 denotes the defuzzified value of the fuzzy number119910119894 = (119897119894 119898119894 119906119894) 119871 = min 119897119894 119877 = max 119906119894 and Δ = 119877 minus 119871The centroid method (center-of-gravity (COG) or center

of area (COA)) was used to determine the crisp values offuzzy numbers in [131 158 165 170 179] For the triangularfuzzy number 119910 = (119897 119898 119906) its crisp value can be found withthe following equivalent relations

119910 = 119897 + (119898 minus 119897) + (119906 minus 119897)3 or 119910 = 119897 + 119898 + 1199063

(28)

In [180 184] the signed distance of a fuzzy number (calledsigned distance method or Yager ranking method in [182])shown in (29) was used as its defuzzified value Patil andKant [141] defuzzified each fuzzy number into a crisp value byusing the graded mean integration representation method as(30) In [176] the defuzzification of fuzzy numbers is carriedout using (31) to compute the point that divides the area of afuzzy set into two equal parts

119910 = 119897 + 2119898 + 1199064 (29)

119910 = 119897 + 4119898 + 1199066 (30)

119910 =

119906 minus radic(119906 minus 119897) (119906 minus 119898)2 119906 minus 119898 gt 119898 minus 119897radic (119906 minus 119897) (119906 minus 119898)2 minus 119897 119906 minus 119898 lt 119898 minus 119897119898 otherwise

(31)

(2) Weighting Methods As shown in Table 2 many stud-ies have applied the fuzzy DEMETAL to determine theweights of criteria considering their hierarchies and a vari-ety of weighting methods have been suggested In addi-tion to those methods already mentioned in the classicalDEMETAL studies that is those based 119877 + 119862 and depen-dency weights some new weighting methods have beendeveloped

The vector length method has been used in [150 176 180184] which sets the importance of criteria with the followingformula

120596119894 = [(def119894 + 119862def

119894 )2 + (def119894 minus 119862def

119894 )2]12 (32)

Mathematical Problems in Engineering 21

Then theweight of any criterion can be normalized as follows

119908119894 = 120596119894sum119899119894=1 120596119894 119894 = 1 2 119899 (33)

Wang [179] evaluated the importance weights of criteriaby normalizing their absolute relation values

119908119894 = 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816sum119899119894=1 1003816100381610038161003816119903119894 minus 1198881198941003816100381610038161003816 119894 = 1 2 119899 (34)

Here |119903119894 minus 119888119894| represents a signed relation value for the 119895thcriterion

Besides based on the interactions among criteria fuzzyAHP was utilized by Wang and Wu [181] and Hsu et al[171] fuzzy ANP was used by Taskin et al [186] Fetanatand Khorasaninejad [182] and Bakeshlou et al [154] andfuzzy DEMATEL-based analytic network process (DANP)was employed by Hu et al [183] to calculate relative weightsof criteria

33 Grey DEMATEL Grey theory [35] is a mathematicaltheory proposed to cope with systems which lack infor-mation It is an effective methodology to resolve uncertainand indeterminate problems and is superior in theoreticalanalysis of systems with discrete data and incomplete infor-mation Hence grey theory has been incorporated with theDEMATEL by some researchers for the evaluation of factorintertwined relations in real-life systems To facilitate readingand comparison the reviewed twelve greyDEMATEL studiesare summarized in Table 3 All of them adopted grey DEMA-TEL methods for the identification of key factors throughanalyzing the interaffected relationships among them

Similar to the fuzzy DEMATEL there are mainly twotypes of grey DEMATEL methods that is the grey the-ory and DEMATEL and the grey-based DEMATEL Fu etal [187] first introduced the grey theory and DEMATELmethodology to investigate the importance of green supplierdevelopment programs at a telecommunications systemsprovider The proposed method involves assessing interde-pendency relationships among factors by a grey linguisticsscale transforming grey numbers into single real numbersusing a modified CFCS process and eventually executing theclassical DEMATEL steps to obtain an IRM with associatedanalysis Later the grey theory and DEMATEL method wasapplied by Dou and Sarkis [188] to evaluate the barriersof implementing China RoHS (the restriction of the use ofhazardous substances in electrical and electronic equipment)regulations from a multiple stakeholder perspective by Zhuet al [189] to identify the supply chain-based barriers fortruck-engine remanufacturing in China by Rajesh and Ravi[190] to ascertain the major enablers of supply chain riskmitigation in electronic supply chains by Shao et al [191] toanalyze the barriers between environmentally friendly prod-ucts and consumers on the European automobile industry byGovindan et al [192] to develop important criteria for third-party logistics provider selection and evaluation and by Xiaet al [193] to analyze the internal barriers for remanufacturersin the Chinese automotive sector

Bai and Sarkis [194] argued that the data conversionprocess of the grey andDEMATELmethodwill cause a loss oforiginal decision information thus leading to unreasonableor misleading results in the final decision Accordingly theyproposed a grey-based DEMATEL model to identify criticalsuccess factors (CFSs) in the successful implementation ofbusiness process management (BPM) In their integratedstructural model the authors evaluated various BPM imple-mentation CSFs directly through the grey-based DEMATELand did not ldquodegreyrdquo the grey numbers until after calculatingthe prominence and relation indexes Liang et al [195] alsoreported a grey-based DEMATEL for identifying the CFSsfor promoting sustainable development of biofuel industry inChina

Additionally Tseng [196] proposed a grey-fuzzy DEMA-TEL approach based on a grey possibility degree to dealwith real estate agent service quality expectation rankingwith uncertainty Su et al [197] developed a hierarchi-cal grey DEMATEL methodology for improving sustain-able supply chain management under hierarchical structureinterrelationships and incomplete information Ozcan andTuysuz [197] elaborated upon a grey-based multicriteriaperformance evaluation model for retail stores by integratingDEMATEL and GRA methods

It is worth noting that different from the threshold deter-mination methods mentioned in the traditional DEMATELpart the threshold value 120579 in the grey DEMATEL paperswas usually yielded based on the mean (120583) and standarddeviation (120590) of the values from the total-influence matrix119879 For example in [187 191 193 194] the threshold is set upby computing the sum of the mean and standard deviation(120583+120590) Rajesh andRavi [190] set the threshold value by adding15 times the standard deviation to the mean (120583 + 15120590) andZhu et al [189] added two standard deviations to the mean(120583 + 2120590) to calculate the value of 12057934 Other DEMATEL Methods In previous sections wehave overviewed the DEMATEL for decision making underdifferent contexts that is the original crisp DEMATEL thefuzzy DEMATEL and the grey DEMATEL Recently variousapproaches that combine other new uncertain theories withDEMATEL have been put forward to enhance its analysiscapability and practicality Table 4 shows those modificationsidentified in the literature and in the sequence a detailedliterature analysis is given

Jenab et al [199] proposed an interval DEMATEL(i-DEMATEL) method for evaluating and implementingcomputer integrated manufacturing technologies that takesinto account all decision parameters Abdullah and Zulkifli[200] reported an interval type 2 fuzzy DEMATEL (IT2-fuzzy DEMATEL) and combined it with fuzzy AHP forhuman resource management where interval type 2 trape-zoidal fuzzy numbers were used to resolve the relationshipsamong dimensions and criteria Nikjoo and Saeedpoor [201]presented an intuitionistic fuzzy DEMATEL approach todetermine the key components of strengths weaknessesopportunities and threats (SWOT) matrix and Govindan etal [202] used theDEMATELmethodwith intuitionistic fuzzysets (IFSs) to handle the important and causal relationships

22 Mathematical Problems in Engineering

Table3Ap

plications

ofgrey

DEM

ATEL

Papers

Research

purposes

Extensions

Remarks

Fuetal[187]

Evaluategreensupp

lierd

evelo

pmentp

rogram

sand

theirrelationships

toeach

other

andim

portance

forthe

organizatio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Dou

andSarkis[188]

Evaluatetheb

arrie

rsof

implem

entin

gCh

inaR

oHSregu

lations

from

amultip

lesta

keho

lder

perspective

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583di

stance

between

respon

dents

Zhuetal[189]

Exam

inethe

causal-effectrelatio

nships

amon

gtheimplem

entatio

nbarriersand

identifysupp

lychain-basedbarriersfortruck-eng

iner

emanufacturin

gin

China

Greytheory

andDEM

ATEL

CFCS

threshold

value-120583+

2120590distance

betweenrespon

dents

Rajesh

andRa

vi[19

0]Find

outcauseeffectrelationships

andascertainthem

ajor

enablersof

supp

lychain

riskmitigatio

nin

electro

nics

upplychains

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

15120590Shao

etal[191]

Visualizethe

prioritizationandinterrela

tionships

oftheb

arrie

rsbetween

environm

entally

friend

lyprod

uctsandtheirc

onsumerso

ntheE

urop

ean

automob

ileindu

stry

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Govindanetal[192]

Identifyim

portantcriteriaforthird-partylogisticsp

roviderselectio

nGreytheory

andDEM

ATEL

Mod

ified

CFCS

inner

depend

ence

matrix

Xiae

tal[19

3]Analyze

internalbarriersforrem

anufacturersin

thea

utom

otives

ectora

ndidentify

thec

ausalinternalbarrie

rsin

theC

hinese

automotives

ector

Greytheory

andDEM

ATEL

Mod

ified

CFCS

threshold

value-120583+

120590Ba

iand

Sarkis[19

4]Ev

aluatebu

sinessp

rocessmanagem

ent(BP

M)criticalsuccessfactorsto

aidproject

managersm

akep

roperB

PMinvestmentstrategies

GreyDEM

ATEL

Thresholdvalue-120583+

120590Liangetal[195]

Identifycriticalsuccessfactorsfor

sustainabled

evelo

pmento

fbiofuelindu

stry

inCh

ina

GreyDEM

ATEL

Tseng[19

6]Re

solveinterdepend

ency

relationships

amon

gcriteria

andpresenta

perceptio

napproach

todealwith

realestateagentservice

quality

expectationrank

ing

Grey-fuzzyDEM

ATEL

Innerd

ependencem

atrix

Suetal[197]

Identifyaspectso

fand

criteria

forsup

plierp

rioritizationandprop

osea

hierarchical

metho

dforimprovingsusta

inablesupp

lychainmanagem

ent

HierarchicalgreyDEM

ATEL

Ozcan

andTu

ysuz

[198]

Determinethe

impo

rtance

ofperfo

rmance

indicatorsandprop

osea

metho

dforthe

perfo

rmance

evaluatio

nof

retailsto

res

Grey-basedDEM

ATEL

Mod

ified

CFCS

Mathematical Problems in Engineering 23

Table4Ap

plications

ofotherD

EMAT

EL

Papers

Categorie

sRe

search

purposes

Extensions

Remarks

Jenabetal[199]

Interrelationships

Keyfactors

Prop

osea

syste

maticmetho

dfore

valuatingandselectingcompu

ter

integrated

manufacturin

g(C

IM)techn

ologiestakinginto

accoun

tmanagem

ento

bjectiv

esIntervalDEM

ATEL

Rank

basedon119877minus

119862Ab

dullahandZu

lkifli[200]

Interrelationships

Keyfactors

Capturethe

complex

relationships

amon

gdimensio

nsandcriteria

and

prop

osea

nintegrationmetho

dforh

uman

resourcesm

anagem

ent

IT2-fuzzyDEM

ATEL

fuzzyAHP

Defuzzification-

expected

value(T)

NikjooandSaeedp

oor[201]

Interrelationships

Keyfactors

Dealw

iththec

ausalrelationships

amon

gfactorsa

ndprop

osea

metho

dology

forp

rioritizingthec

ompo

nentso

fSWOTmatrix

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Govindanetal[202]

Interrelationships

Keyfactors

Handlethe

impo

rtantand

causalrelationships

betweengreensupp

lychain

managem

ent(GSC

M)p

ractices

andfin

dthem

ainpractices

toim

prove

environm

entaland

econ

omicperfo

rmances

IFS(ITF

N)a

ndDEM

ATEL

Defuzzification-

expected

valueinner

depend

ence

matrix

Fanetal[203]

Interrelationships

Keyfactors

Exam

inethe

interrelationships

amon

gther

iskfactorso

fITou

tsou

rcing

andidentifytheimpo

rtance

together

with

thec

lassificatio

nof

riskfactors

2-tuplea

ndDEM

ATEL

Liuetal[204]

Interrelationships

Criteria

weight

Obtainther

elativew

eightsof

criteria

andprop

osea

hybrid

MCD

Mfor

evaluatin

ghealth-carew

astetre

atmenttechn

ologies

2-tuplea

ndDEM

ATEL

fuzzyMULT

IMOORA

Criteria

weights-

vector

leng

th

Suoetal[205]

Interrelationships

Keyfactors

Dealw

ithcorrelated

factor

analysisprob

lemsu

singun

certainlin

guistic

term

sand

extend

thec

lassicalDEM

ATEL

metho

dto

anun

certain

linguisticenvironm

ent

Uncertain

linguistic

DEM

ATEL

Defuzzification-CO

G

Lietal[206]

Interrelationships

Keyfactors

Identifycriticalsuccessfactorsinem

ergencymanagem

ent

Evidentia

lDEM

ATEL

(D-S

theory

andIFS)

ChangandCh

eng[207]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

IFSandDEM

ATEL

Defuzzification-

centroid

metho

drank

basedon119877minus

119862Ch

ang[208]

Interrelationships

Keyfactors

Analyze

ther

elatio

nships

betweencompo

nentso

fasyste

mandou

tline

ageneralalgorith

mforp

rioritizationof

failu

remod

esin

FMEA

Softsetand

DEM

ATEL

Rank

basedon119877minus

119862GengandCh

u[209]

Interrelationships

Criteria

weights

Con

sider

them

utualinfl

uencer

elationships

amon

gattributes

andprop

ose

anew

impo

rtance-perform

ance

analysis(IPA

)app

roachforc

ustomer

satisfactionevaluatio

n

VagueD

EMAT

ELK

ano

mod

elDefuzzification-average

Wuetal[210]

Interrelationships

Criteria

weights

Analyze

theinterrelationships

amon

gcusto

mer

requ

irementsandprop

ose

anintegrated

analyticalmod

elforq

ualityfunctio

ndeployment(QFD

)Hesitant

fuzzy

DEM

ATEL

Criteria

weights-

vector

leng

th

24 Mathematical Problems in Engineering

between green practices and performances in green supplychain management Fan et al [203] developed an extendedDEMATEL method using 2-tuple fuzzy linguistic represen-tation model to identify risk factors of IT outsourcing andLiu et al [204] utilized a 2-tuple DEMATEL technique tocompute the importance weights of criteria and proposeda hybrid MCDM model for evaluating health-care wastetreatment technologies

Suo et al [205] presented an extension of DEMATELmethod in an uncertain linguistic environment which allowsthe judgments on the correlations between factors in theform of uncertain linguistic terms Li et al [206] proposedan evidential DEMATEL method for identifying CFSs inemergency management in which the evaluations of influ-encing factors expressed in intuitionistic fuzzy numbers(IFNs) were transformed into basic probability assignments(BPAs) andDempster-Shafer (D-S) theory was used to obtainthe group assessment BPA matrix Chang and Cheng [207]suggested an efficient algorithmwhich combines IFSs and theDEMATEL to evaluate the risk of failure modes and Chang[208] proposed a risk ranking model integrating soft settheory and the DEMATEL technique for the risk assessmentin failure mode and effect analysis (FMEA) Geng and Chu[209] dealt with the uncertainty and vagueness of expertevaluations by using vague sets and presented a revisedDEMATEL approach to capture the mutual influence rela-tionships among quality attributes Then a new importance-performance analysis (IPA)method for customer satisfactionevaluation was proposed based on Kano model and vagueDEMATELWu et al [210] presented an integrated analyticalmodel for QFD in which hesitant fuzzy DEMATEL wasadopted to analyze the interrelationships among customerrequirements and determine their weights

4 Bibliometric Analysis

Based on the collected papers on theDEMATEL a bibliomet-ric analysis is conducted in this section regarding quantity ofarticles published per year application areas of DEMATELand the highly cited papersThe intention of this bibliometricanalysis is to find out current research trends distribution ofthe articles in different categories and interactions with otherfields which provide valuable insights for researchers andpractitioners working in this field First from Figure 4 onecan observe that the number of publications on DEMATELhas increased considerably especially after the year 2009 Itcan be expected that the studies of utilizing the DEMATELand its variants will continue to grow at an increased pacein the coming decade Figure 4 also shows the trend in thenumber of publications in each category It can be found thatthe classical and the fuzzy DEMATEL methods are mostlyused for decision making in the earlier literature It was onlyafter the year 2010 when the focus shifted to employing thecombination of ANP and DEMATEL However the usage ofthe classical and the fuzzyDEMATELmethods has continuedto grow until more recently when some papers began to dealwith the grey and other DEMATEL applications Normallyif the relationships of systems are given by crisp values in

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Years

Fuzzy DEMATELGrey DEMATEL

Classical DEMATELANP and DEMATELOther DEMATEL

01020304050607080

Num

ber o

f art

icle

s

Figure 4 Distribution of articles according to the years

Table 5 The top ten papers based on citation measures

Papers Total citation Average citationTzeng et al [10] 334 4175Wu and Lee [130] 224 2800Lin and Wu [159] 166 2371Wu [211] 162 2314Huang et al [8] 131 1638Buyukozkan and Cifci [212] 128 4267Tsai and Chou [213] 128 2133Seyed-Hosseini et al [77] 128 1422Chiu et al [49] 128 1422Chang et al [134] 83 2075

establishing a structural model the classical DEMATEL canbe used for evaluating problems and decision making [217]For the cases that the human judgments about preferencesare unclear and hard to estimate by exact numerical valuesthe fuzzy DEMATEL is necessary for making better decisionsin fuzzy environments The grey DEMATEL can be appliedto the systems with limited data and incomplete informationwhich may exhibit random uncertainty

From Figure 5 we can see that the DEMATEL and itsvarious improvements have been widely used in a lot ofareas practically in computer science (406) engineering(357) business and managements (264) decision sci-ences (177) and social sciences (155)

In Table 5 the top ten papers are given by analyzing thetotal citation and average citation of each publication ldquoTotalcitationrdquo refers to the number of Scopus citations for a paperuntil 2016 and ldquoaverage citationrdquo or called ldquocitation per yearrdquois equal to the total citation divided by the number of yearsfrom publication It can be seen that the most influencedpapers in this filed are Tzeng et al [10] Wu and Lee [130] Linand Wu [159] Wu [211] Huang et al [8] and Buyukozkanand Cifci [212] Note that the ranking of articles based uponthe total citation does not necessarily match the averagecitation ranking Besides it can be observed that all the highlycited studies are at least five years old except Buyukozkan

Mathematical Problems in Engineering 25

Computer science406

Engineering 357

Business andmanagements 264

Decision sciences177

Social sciences155

Mathematics 128

Environmentalscience 106

Medicine 67

Economics andeconometrics 52

Energy 52

Other 172

Figure 5 Distribution of articles according to application areas

and Cifci [212] This is because sufficient time is usuallyneeded for an influential paper to establish citations

5 Conclusions and Suggestions forFuture Work

In recent decade the DEMATEL technique has attracted a lotof attention from both practitioners and researchers and hasbeen used in a wide range of areas due to its ability to handlecomplex relationships between components of a system Inthis paper a representative and comprehensive review on theDEMATEL methods and applications from 2006 to 2016 wasprovided According to the distinct forms of the DEMATELused in the selected publications five categories are identifiedand carefully investigated along with their main steps andcharacteristics This review uncovers the current state of theresearch on this area based on statistical analysis results of theDEMATEL literature It can be expected that the number ofapproaches and applications of the DEMATEL will continueto grow in the future due to its distinguished power and theincreasing complexity of decision making problems

Through the detailed review regarding the DEMATELmethodologies the following possible future research direc-tions for both theory and applications are suggested First

to represent uncertainty and vagueness within the decisionmaking process the original DEMATEL was mainly com-bined with fuzzy sets and grey theory and only a few studiesapplied other uncertain theories such as interval type 2 fuzzysets IFSs 2-tuples and uncertain linguistic terms to improvethe DEMATEL recently In the future investigating thecombination of DEMATEL with more advanced uncertaintheories such as hesitant fuzzy linguistic term sets and cloudmodel theory for better decisions in uncertainty would beinteresting Second the relative weights of decision makersare assumed to be equally important in computing the groupdirect-influence matrix 119885 However in practical situationsdecision makers usually come from different specialty fieldsand each expert has unique characteristics with regard toknowledge skills experience and personality which impliesthat different expert weights should be assigned to reflecttheir influences on final analysis results Moreover in theinterrelationship evaluation process some decision makersmay assign unduly high or unduly low preference values totheir ldquopreferredrdquo or ldquorepugnantrdquo factors Thus in the futureadvancedDEMATELmethods should be developed to relievethe influence of unfair arguments on the decision resultsThird proposing more objective and effective methods isrequired to set the crucial parameters in DEMATEL such as

26 Mathematical Problems in Engineering

threshold value 120579 and criteria weights in further research Forexample although different methods have been suggested todetermine the value of 120579 in current DEMATEL studies thesemethods are subjective and time-consuming [218]

From the perspective of applications our study also hasseveral implications for further research First the literaturereview shows that a series ofmodifiedDEMATEL approacheshave been developed but no or few studies have been doneto compare between the methods in the same or differentgroups So one recommendation for future research is theevaluation and comparison of the advantages and drawbacksof different DEMATEL methods in order to aid practitionersto select the suitable one for the problem to be solved Secondto analyze the complicated interrelations between factorsaccurately many computations are involved in the extendedDEMATEL models which limit their applications Thus asoftware tool should be developed in the future to facilitatethe implementation of the DEMATEL technique Finallyfuture research could apply the DEMATELmethodology andits variants to other situations and broader fields that are notconsidered in the previous studies

Conflicts of Interest

The authors declare no conflicts of interest

Acknowledgments

This work was supported by the National Natural ScienceFoundation of China (nos 61773250 and 71402090) theShanghai Pujiang Talents Program (no 15PJC050) and theProgram for Professor of Special Appointment (Young East-ern Scholar) at Shanghai Institutions of Higher Learning (noQD2015019)

References

[1] A Gabus and E Fontela World Problems An Invitation toFurther Thought within The Framework of DEMATEL BattelleGeneva Research Centre Geneva Switzerland 1972

[2] A Mardani E K Zavadskas Z Khalifah et al ldquoA reviewof multi-criteria decision-making applications to solve energymanagement problems two decades from 1995 to 2015rdquo Renew-able amp Sustainable Energy Reviews vol 71 pp 216ndash256 2017

[3] M Zare C Pahl H Rahnama et al ldquoMulti-criteria decisionmaking approach in E-learning a systematic review and clas-sificationrdquo Applied Soft Computing vol 45 pp 108ndash128 2016

[4] E Falatoonitoosi S Ahmed and S Sorooshian ldquoExpandedDEMATEL for determining cause and effect group in bidirec-tional relationsrdquo The Scientific World Journal vol 2014 ArticleID 103846 pp 1ndash7 2014

[5] H-S Lee G-H Tzeng W Yeih Y-J Wang and S-C YangldquoRevised DEMATEL resolving the infeasibility of DEMATELrdquoApplied Mathematical Modelling vol 37 no 10-11 pp 6746ndash6757 2013

[6] G-H Tzeng W-H Chen R Yu and M-L Shih ldquoFuzzydecision maps a generalization of the DEMATEL methodsrdquoSoft Computing vol 14 no 11 pp 1141ndash1150 2010

[7] I Golcuk and A Baykasoglu ldquoAn analysis of DEMATELapproaches for criteria interaction handling within ANPrdquoExpert Systems with Applications vol 46 pp 346ndash366 2016

[8] C-Y Huang J Z Shyu and G-H Tzeng ldquoReconfiguring theinnovation policy portfolios for Taiwan1015840s SIP mall industryrdquoTechnovation vol 27 no 12 pp 744ndash765 2007

[9] C-W Li and G-H Tzeng ldquoIdentification of interrelationshipof key customersrsquo needs based on structural model for ser-vicescapabilities provided by a Semiconductor-Intellectual-PropertyMallrdquoAppliedMathematics and Computation vol 215no 6 pp 2001ndash2010 2009

[10] G H Tzeng C H Chiang and C W Li ldquoEvaluating inter-twined effects in e-learning programs a novel hybrid MCDMmodel based on factor analysis and DEMATELrdquo Expert Systemswith Applications vol 32 no 4 pp 1028ndash1044 2007

[11] C Lin and G Tzeng ldquoA value-created system of science(technology) park by using DEMATELrdquo Expert Systems withApplications vol 36 no 6 pp 9683ndash9697 2009

[12] A Azadeh M Zarrin M Abdollahi S Noury and S Farah-mand ldquoLeanness assessment and optimization by fuzzy cog-nitive map and multivariate analysisrdquo Expert Systems withApplications vol 42 no 15-16 pp 6050ndash6064 2015

[13] P T-W Lee and C-W Lin ldquoThe cognition map of financialratios of shipping companies using DEMATEL and MMDErdquoMaritime Policy ampManagement vol 40 no 2 pp 133ndash145 2013

[14] J Sara R M Stikkelman and P M Herder ldquoAssessing rel-ative importance and mutual influence of barriers for CCSdeployment of the ROAD project using AHP and DEMATELmethodsrdquo International Journal of Greenhouse Gas Control vol41 pp 336ndash357 2015

[15] W-K Tan andC-Y Kuo ldquoPrioritization of facilitation strategiesof park and recreation agencies through DEMATEL analysisrdquoAsia Pacific Journal of Tourism Research vol 19 no 8 pp 859ndash875 2014

[16] M N Shaik and W Abdul-Kader ldquoComprehensive perfor-mance measurement and causal-effect decision making modelfor reverse logistics enterpriserdquo Computers amp Industrial Engi-neering vol 68 no 1 pp 87ndash103 2014

[17] S M Seyedhosseini A E Taleghani A Bakhsha and SPartovi ldquoExtracting leanness criteria by employing the conceptof balanced scorecardrdquoExpert SystemswithApplications vol 38no 8 pp 10454ndash10461 2011

[18] G T R Lin and C-C Sun ldquoDriving industrial clusters tobe nationally competitiverdquo Technology Analysis and StrategicManagement vol 22 no 1 pp 81ndash97 2010

[19] S Tzeng ldquoApplying DEMATEL to investigate the relationshipbetween factors affecting parole boardsrsquo decision-making inTaiwanrdquoThe Prison Journal vol 94 no 1 pp 118ndash136 2014

[20] WHwang B Hsiao H-G Chen andC-C Chern ldquoMultiphaseassessment of project risk interdependencies evidence from aUniversity ISD project in Taiwanrdquo Project Management Journalvol 47 no 1 pp 59ndash75 2016

[21] H-M Chuang C-K Lin D-R Chen and Y-S Chen ldquoEvolv-ing MCDM applications using hybrid expert-based ISM andDEMATELmodels an example of sustainable ecotourismrdquoTheScientific World Journal vol 2013 Article ID 751728 pp 1ndash182013

[22] K-F Chien Z-H Wu and S-C Huang ldquoIdentifying andassessing critical risk factors for BIM projects empirical studyrdquoAutomation in Construction vol 45 pp 1ndash15 2014

Mathematical Problems in Engineering 27

[23] W-W Wu L W Lan and Y-T Lee ldquoExploring decisivefactors affecting an organizationrsquos SaaS adoption a case studyrdquoInternational Journal of Information Management vol 31 no 6pp 556ndash563 2011

[24] W-W Wu L W Lan and Y-T Lee ldquoFactors hinderingacceptance of using cloud services in university a case studyrdquoElectronic Library vol 31 no 1 pp 84ndash98 2013

[25] W-C Wang Y-H Lin C-L Lin C-H Chung and M-TLee ldquoDEMATEL-basedmodel to improve the performance in amatrix organizationrdquo Expert Systems with Applications vol 39no 5 pp 4978ndash4986 2012

[26] W-C Wang C-L Lin S-H Wang J-J Liu and M-T LeeldquoApplication of importance-satisfaction analysis and influence-relations map to evaluate design delay factorsrdquo Journal of CivilEngineering and Management vol 20 no 4 pp 497ndash510 2014

[27] S Cebi ldquoDetermining importance degrees of website designparameters based on interactions and types of websitesrdquo Deci-sion Support Systems vol 54 no 2 pp 1030ndash1043 2013

[28] A Yazdani-Chamzini S Shariati S H Yakhchali and E KZavadskas ldquoProposing a new methodology for prioritising theinvestment strategies in the private sector of Iranrdquo EconomicResearch-Ekonomska Istrazivanja vol 27 no 1 pp 320ndash3452014

[29] B Khazai M Merz C Schulz and D Borst ldquoAn integratedindicator framework for spatial assessment of industrial andsocial vulnerability to indirect disaster lossesrdquoNatural Hazardsvol 67 no 2 pp 145ndash167 2013

[30] A Mardani A Jusoh and E K Zavadskas ldquoFuzzy multi-ple criteria decision-making techniques and applicationsmdashtwodecades review from 1994 to 2014rdquo Expert Systems with Appli-cations vol 42 no 8 pp 4126ndash4148 2015

[31] A Mardani A Jusoh K MDNor Z Khalifah N Zakwan andA Valipour ldquoMultiple criteria decision-making techniques andtheir applicationsmdasha review of the literature from 2000 to 2014rdquoEconomic Research-Ekonomska Istrazivanja vol 28 no 1 pp516ndash571 2015

[32] E K Zavadskas Z Turskis and S Kildiene ldquoState of art surveysof overviews on MCDMMADM methodsrdquo Technological andEconomic Development of Economy vol 20 no 1 pp 165ndash1792014

[33] G Kou D Ergu C Lin and Y Chen ldquoPairwise comparisonmatrix in multiple criteria decision makingrdquo Technological andEconomic Development of Economy vol 22 no 5 pp 738ndash7652016

[34] G Kou and C Lin ldquoA cosine maximization method for thepriority vector derivation in AHPrdquo European Journal of Oper-ational Research vol 235 no 1 pp 225ndash232 2014

[35] J L Deng ldquoIntroduction to grey system theoryrdquoThe Journal ofGrey System vol 1 no 1 pp 1ndash24 1989

[36] S Opricovic and G H Tzeng ldquoCompromise solution byMCDM methods a comparative analysis of VIKOR and TOP-SISrdquo European Journal of Operational Research vol 156 no 2pp 445ndash455 2004

[37] E K Zavadskas A Mardani Z Turskis A Jusoh and K MNor ldquoDevelopment of TOPSIS method to solve complicateddecision-making problems - an overview on developmentsfrom 2000 to 2015rdquo International Journal of Information Tech-nology amp Decision Making vol 15 no 3 pp 645ndash682 2016

[38] B Roy and P Vincke ldquoMulticriteria analysis survey and newdirectionsrdquo European Journal of Operational Research vol 8 no3 pp 207ndash218 1981

[39] H-C Liu J-X You L Zhen and X-J Fan ldquoA novel hybridmultiple criteria decision making model for material selectionwith target-based criteriardquoMaterials and Corrosion vol 60 pp380ndash390 2014

[40] Y P Ou Yang H M Shieh J D Leu and G H Tzeng ldquoA novelhybrid MCDM model combined with DEMATEL and ANPwith applicationsrdquo International Journal of Operations Researchvol 5 no 3 pp 160ndash168 2008

[41] G Kou D Ergu and J Shang ldquoEnhancing data consistency indecision matrix adapting Hadamard model to mitigate judg-ment contradictionrdquo European Journal of Operational Researchvol 236 no 1 pp 261ndash271 2014

[42] B Efe and O F Efe ldquoAn application of value analysis forlean healthcare management in an emergency departmentrdquoInternational Journal of Computational Intelligence Systems vol9 no 4 pp 689ndash697 2016

[43] G Malekzadeh M Kazemi M Lagzian and S MortazavildquoModeling organizational intelligence using DEMATELmethod in Iranian public universitiesrdquo Journal of Modelling inManagement vol 11 no 1 pp 134ndash153 2016

[44] R Ranjan P Chatterjee and S Chakraborty ldquoPerformanceevaluation of Indian Railway zones using DEMATEL andVIKORmethodsrdquo Benchmarking vol 23 no 1 pp 78ndash95 2016

[45] H-Y Hu Y-C Lee T-M Yen and C-H Tsai ldquoUsing BPNNand DEMATEL to modify importance-performance analysismodel - a study of the computer industryrdquo Expert Systems withApplications vol 36 no 6 pp 9969ndash9979 2009

[46] H-Y Hu S-I Chiu C-C Cheng and T-M Yen ldquoApplying theIPA and DEMATEL models to improve the order-winner crite-ria a case study of Taiwanrsquos network communication equipmentmanufacturing industryrdquo Expert Systems with Applications vol38 no 8 pp 9674ndash9683 2011

[47] C-C Cheng C-T Chen F-S Hsu and H-Y Hu ldquoEnhancingservice quality improvement strategies of fine-dining restau-rants new insights from integrating a two-phase decision-making model of IPGA and DEMATEL analysisrdquo InternationalJournal of Hospitality Management vol 31 no 4 pp 1155ndash11662012

[48] P-L Hsieh and T-M Yeh ldquoDeveloping a cause and effectmodelof factors influencing fast food restaurantsrsquo service quality usingDEMATELrdquo International Journal of Services and OperationsManagement vol 20 no 1 pp 21ndash42 2015

[49] Y J Chiu H C Chen G H Tzeng and J Z Shyu ldquoMarketingstrategy based on customer behaviour for the LCD-TVrdquo Inter-national Journal ofManagement and DecisionMaking vol 7 no2-3 pp 143ndash165 2006

[50] L-H Ho S-Y Feng Y-C Lee and T-M Yen ldquoUsing modifiedIPA to evaluate supplierrsquos performance multiple regressionanalysis and DEMATEL approachrdquo Expert Systems with Appli-cations vol 39 no 8 pp 7102ndash7109 2012

[51] S-B Tsai C-YHuang C-KWang et al ldquoUsing amixedmodelto evaluate job satisfaction in high-tech industriesrdquo PLoS ONEvol 11 no 5 Article ID e0154071 2016

[52] A Najmi and A Makui ldquoA conceptual model for measuringsupply chainrsquos performancerdquo Production Planning and Controlvol 23 no 9 pp 694ndash706 2012

[53] M Shafiee F Hosseinzadeh Lotfi and H Saleh ldquoSupply chainperformance evaluation with data envelopment analysis andbalanced scorecard approachrdquoAppliedMathematicalModellingvol 38 no 21-22 pp 5092ndash5112 2014

28 Mathematical Problems in Engineering

[54] C-HWang and O-Z Hsueh ldquoA novel approach to incorporatecustomer preference and perception into product configura-tion a case study on smart padsrdquo Computer Standards ampInterfaces vol 35 no 5 pp 549ndash556 2013

[55] C-H Wang and C-W Shih ldquoIntegrating conjoint analysiswith quality function deployment to carry out customer-drivenconcept development for ultrabooksrdquo Computer Standards ampInterfaces vol 36 no 1 pp 89ndash96 2013

[56] S-S Ko N Ko D Kim H Park and J Yoon ldquoAnalyzingtechnology impact networks for RampD planning using patentscombined application of network approachesrdquo Scientometricsvol 101 no 1 pp 917ndash936 2014

[57] J Yoon M Kim D Kim J Kim and H Park ldquoMonitoringthe change of technological impacts of technology sectors usingpatent information the case of Koreardquo Industrial Engineering ampManagement Systems vol 14 no 1 pp 58ndash72 2015

[58] K-Y Shen and G-H Tzeng ldquoCombined soft computing modelfor value stock selection based on fundamental analysisrdquoApplied Soft Computing vol 37 pp 142ndash155 2015

[59] S Altuntas and T Dereli ldquoA novel approach based on DEMA-TELmethod and patent citation analysis for prioritizing a port-folio of investment projectsrdquo Expert Systems with Applicationsvol 42 no 3 pp 1003ndash1012 2015

[60] K-Y Shen and G-H Tzeng ldquoA new approach and insightfulfinancial diagnoses for the IT industry based on a hybridMADMmodelrdquo Knowledge-Based Systems vol 85 pp 112ndash1302015

[61] W-K Tan and Y-J Tan ldquoTransformation of smart-card-basedsingle-purpose e-micropayment scheme to multi-purposescheme a case studyrdquo Expert Systems with Applications vol 39no 3 pp 2306ndash2313 2012

[62] C-S Liaw Y-C Chang K-H Chang and T-Y Chang ldquoME-OWA based DEMATEL reliability apportionment methodrdquoExpert Systems with Applications vol 38 no 8 pp 9713ndash97232011

[63] A A R Alaei and Y V Alroaia ldquoIdentifying and prioritizingthe factors affecting and affected by the performance of smalland medium enterprises by using DEMATEL technique (Thecase study of a province in Iran)rdquo Indian Journal of Science andTechnology vol 9 no 6 2016

[64] L R Bacudio M F D Benjamin R C P Eusebio et al ldquoAna-lyzing barriers to implementing industrial symbiosis networksusing DEMATELrdquo Sustainable Production and Consumptionvol 7 pp 57ndash65 2016

[65] D Balkovskaya and L Filneva ldquoThe use of the balancedscorecard in bank strategic managementrdquo International Journalof Business Excellence vol 9 no 1 pp 48ndash67 2016

[66] Y-T Chen ldquoApplying the DEMATEL approach to identify thefocus of library service quality a case study of a Taiwaneseacademic libraryrdquo Electronic Library vol 34 no 2 pp 315ndash3312016

[67] K Govindan and A Chaudhuri ldquoInterrelationships of risksfaced by third party logistics service providers a DEMATELbased approachrdquo Transportation Research Part E Logistics andTransportation Review vol 90 pp 177ndash195 2016

[68] K Govindan K Muduli K Devika and A Barve ldquoInves-tigation of the influential strength of factors on adoption ofgreen supply chain management practices an Indian miningscenariordquo Resources Conservation amp Recycling vol 107 pp 185ndash194 2016

[69] S Gandhi S K Mangla P Kumar and D Kumar ldquoA combinedapproach using AHP and DEMATEL for evaluating success

factors in implementation of green supply chain managementin Indian manufacturing industriesrdquo International Journal ofLogistics Research and Applications vol 19 no 6 pp 537ndash5612016

[70] B-N Hwang C-Y Huang and C-H Wu ldquoA TOE approach toestablish a green supply chain adoption decision model in thesemiconductor industryrdquo Sustainability vol 8 no 2 article 1682016

[71] B-N Hwang C-Y Huang and C-L Yang ldquoDeterminantsand their causal relationships affecting the adoption of cloudcomputing in science and technology institutionsrdquo Innovationvol 18 no 2 pp 164ndash190 2016

[72] F Rahimnia and N Kargozar ldquoObjectives priority in universitystrategymap for resource allocationrdquo Benchmarking vol 23 no2 pp 371ndash387 2016

[73] C Sekhar M Patwardhan and V Vyas ldquoA study of HR flex-ibility and firm performance a perspective from IT industryrdquoGlobal Journal of Flexible SystemsManagement vol 17 no 1 pp57ndash75 2016

[74] S N Seleem E-A Attia and A El-Assal ldquoManaging perfor-mance improvement initiatives using DEMATEL method withapplication case studyrdquoProduction Planning andControl vol 27no 7-8 pp 637ndash649 2016

[75] V Sharma A R Dixit andM A Qadri ldquoEmpirical assessmentof the causal relationships among lean criteria usingDEMATELmethodrdquo Benchmarking vol 23 no 7 pp 1834ndash1859 2016

[76] Y-C Shen ldquoIdentifying the key barriers and their interrelation-ships impeding the university technology transfer in Taiwan amulti-stakeholder perspectiverdquo Quality amp Quantity vol 51 no6 pp 2865ndash2884 2017

[77] SM Seyed-HosseiniN Safaei andM J Asgharpour ldquoReprior-itization of failures in a system failure mode and effects analysisby decision making trial and evaluation laboratory techniquerdquoReliability Engineering amp System Safety vol 91 no 8 pp 872ndash881 2006

[78] K-H Chang ldquoEvaluate the orderings of risk for failure prob-lems using a more general RPNmethodologyrdquoMicroelectronicsReliability vol 49 no 12 pp 1586ndash1596 2009

[79] K Chang Y Chang and I Tsai ldquoEnhancing FMEA assessmentby integrating grey relational analysis and the decision makingtrial and evaluation laboratory approachrdquo Engineering FailureAnalysis vol 31 pp 211ndash224 2013

[80] K-H Chang Y-C Chang and Y-T Lee ldquoIntegrating TOPSISand DEMATEL methods to rank the risk of failure of FMEArdquoInternational Journal of Information Technology amp DecisionMaking vol 13 no 6 pp 1229ndash1257 2014

[81] H-C Liu J-X You X-F Ding and Q Su ldquoImproving riskevaluation in FMEA with a hybrid multiple criteria decisionmaking methodrdquo International Journal of Quality amp ReliabilityManagement vol 32 no 7 pp 763ndash782 2015

[82] A Mentes H Akyildiz M Yetkin and N Turkoglu ldquoA FSAbased fuzzy DEMATEL approach for risk assessment of cargoships at coasts and open seas of Turkeyrdquo Safety Science vol 79pp 1ndash10 2015

[83] J-SHorng C-H Liu S-F Chou andC-Y Tsai ldquoCreativity as acritical criterion for future restaurant space design developing anovelmodel withDEMATEL applicationrdquo International Journalof Hospitality Management vol 33 no 1 pp 96ndash105 2013

[84] C-T Chen W-H Lee Y-Y Chang and C-C Cheng ldquoThestrategy for enhancing consumer intention to dine at greenrestaurants three-phase decision-making modelrdquo Total Quality

Mathematical Problems in Engineering 29

ManagementampBusiness Excellence vol 28 no 5-6 pp 614ndash6322017

[85] C-C Cheng M-C Tsai and C-L Lin ldquoQuality educationservice put your feet in their shoesrdquo Current Issues in Tourismvol 19 no 11 pp 1120ndash1135 2016

[86] J I Shieh H H Wu and K K Huang ldquoA DEMATEL methodin identifying key success factors of hospital service qualityrdquoKnowledge-Based Systems vol 23 no 3 pp 277ndash282 2010

[87] R Ranjan P Chatterjee and S Chakraborty ldquoEvaluatingperformance of engineering departments in an Indian Uni-versity using DEMATEL and compromise ranking methodsrdquoOPSEARCH vol 52 no 2 pp 307ndash328 2015

[88] H-HWuH-KChen and J-I Shieh ldquoEvaluating performancecriteria of employment service outreach program personnel byDEMATEL methodrdquo Expert Systems with Applications vol 37no 7 pp 5219ndash5223 2010

[89] C C Sun ldquoAn exploration of core competences of newlyqualified nurses a case studyrdquo Quality amp Quantity vol 48 no2 pp 767ndash780 2014

[90] H-HWu and Y-N Tsai ldquoA DEMATELmethod to evaluate thecausal relations among the criteria in auto spare parts industryrdquoAppliedMathematics and Computation vol 218 no 5 pp 2334ndash2342 2011

[91] C-C Sun ldquoIdentifying critical success factors in EDA industryusing DEMATEL methodrdquo International Journal of Computa-tional Intelligence Systems vol 8 no 2 pp 208ndash218 2015

[92] H H Wu and Y N Tsai ldquoAn integrated approach of AHP andDEMATEL methods in evaluating the criteria of auto spareparts industryrdquo International Journal of Systems Science vol 43no 11 pp 2114ndash2124 2012

[93] P-L Wei J-H Huang G-H Tzeng and S-I Wu ldquoCausalmodeling of web-advertising effects by improving SEM basedon dematel techniquerdquo International Journal of InformationTechnology amp Decision Making vol 9 no 5 pp 799ndash829 2010

[94] C-C Hsu ldquoEvaluation criteria for blog design and analysisof causal relationships using factor analysis and DEMATELrdquoExpert Systems with Applications vol 39 no 1 pp 187ndash193 2012

[95] C-C Hsu and Y-S Lee ldquoExploring the critical factors influ-encing the quality of blog interfaces using the Decision-MakingTrial and Evaluation Laboratory (DEMATEL)methodrdquoBehaviour amp Information Technology vol 33 no 2 pp 183ndash1932014

[96] Y-C Lee Y-F Hsieh and Y-B Guo ldquoConstruct DTPB modelby using DEMATEL a study of a university library websiterdquoProgram vol 47 no 2 pp 155ndash169 2013

[97] V Pathari and R Sonar ldquoIdentifying linkages between state-ments in information security policy procedures and controlsrdquoInformation Management amp Computer Security vol 20 no 4pp 264ndash280 2012

[98] A Jafarnejad M Ansari H R Youshanlouei andMMMoodldquoA hybrid MCDM approach for solving the ERP system selec-tion problem with application to steel industryrdquo InternationalJournal of Enterprise Information Systems vol 8 no 3 pp 54ndash73 2012

[99] Y C Tsai and Y T Cheng ldquoAnalyzing key performance indica-tors (KPIs) for e-commerce and Internet marketing of elderlyproducts a reviewrdquo Archives of Gerontology and Geriatrics vol55 no 1 pp 126ndash132 2012

[100] Y-T Lin Y-H Yang J-S Kang and H-C Yu ldquoUsing DEMA-TEL method to explore the core competences and causal effectof the IC design service company an empirical case studyrdquo

Expert Systems with Applications vol 38 no 5 pp 6262ndash62682011

[101] S Rahman and N Subramanian ldquoFactors for implementingend-of-life computer recycling operations in reverse supplychainsrdquo International Journal of Production Economics vol 140no 1 pp 239ndash248 2012

[102] C-W Hsu T-C Kuo S-H Chen and A H Hu ldquoUsingDEMATEL to develop a carbonmanagement model of supplierselection in green supply chainmanagementrdquo Journal of CleanerProduction vol 56 pp 164ndash172 2013

[103] E Falatoonitoosi S Ahmed and S Sorooshian ldquoA multicri-teria framework to evaluate supplierrsquos greennessrdquo Abstract andApplied Analysis vol 2014 Article ID 396923 pp 1ndash12 2014

[104] J Ren A Manzardo S Toniolo and A Scipioni ldquoSustainabilityof hydrogen supply chain Part I identification of critical criteriaand cause-effect analysis for enhancing the sustainability usingDEMATELrdquo International Journal of Hydrogen Energy vol 38no 33 pp 14159ndash14171 2013

[105] K Muduli and A Barve ldquoEstablishment of a sustainabledevelopment framework in small scale mining supply chains inIndiardquo International Journal of Intelligent Enterprise vol 2 no1 pp 84ndash100 2013

[106] H-H Wu and S-Y Chang ldquoA case study of using DEMATELmethod to identify critical factors in green supply chain man-agementrdquo Applied Mathematics and Computation vol 256 pp394ndash403 2015

[107] P K Behera and K Mukherjee ldquoApplication of DEMATELand MMDE for analyzing key Influencing factors relevant toselection of supply chain coordination schemesrdquo InternationalJournal of Information Systems and Supply Chain Managementvol 8 no 2 pp 49ndash69 2015

[108] S Ahmed S Ahmed M R H Shumon M A Quader H MCho and M I Mahmud ldquoPrioritizing strategies for sustainableend-of-life vehicle management using combinatorial multi-criteria decisionmakingmethodrdquo International Journal of FuzzySystems vol 18 no 3 pp 448ndash462 2016

[109] S Ahmed S Ahmed M R H Shumon E Falatoonitoosiand M A Quader ldquoA comparative decision-making modelfor sustainable end-of-life vehicle management alternativeselection using AHP and extent analysis method on fuzzyAHPrdquo International Journal of SustainableDevelopmentampWorldEcology vol 23 no 1 pp 83ndash97 2016

[110] RMiao F Xu K Zhang andZ Jiang ldquoDevelopment of amulti-scale model for customer perceived value of electric vehiclesrdquoInternational Journal of Production Research vol 52 no 16 pp4820ndash4834 2014

[111] G Lin ldquoThe promotion and development of solar photovoltaicindustry discussion of its key factorsrdquo Distributed Generationand Alternative Energy Journal vol 26 no 4 pp 57ndash80 2011

[112] A Azarnivand and N Chitsaz ldquoAdaptive policy responses towater shortage mitigation in the arid regionsmdasha systematicapproach based on eDPSIR DEMATEL andMCDArdquo Environ-mental Modeling amp Assessment vol 187 article 23 2015

[113] Y Chen J Liu Y Li R Sadiq and Y Deng ldquoRM-DEMATELa new methodology to identify the key factors in P M 25rdquoEnvironmental Science and Pollution Research vol 22 no 8 pp6372ndash6380 2015

[114] L S dos Muchangos A Tokai and A Hanashima ldquoAnalyzingthe structure of barriers to municipal solid waste managementpolicy planning in Maputo city Mozambiquerdquo EnvironmentalDevelopment vol 16 pp 76ndash89 2015

30 Mathematical Problems in Engineering

[115] W-F Guo J Zhou C-L Yu et al ldquoEvaluating the greencorporate social responsibility of manufacturing corporationsfrom a green industry law perspectiverdquo International Journal ofProduction Research vol 53 no 2 pp 665ndash674 2015

[116] F H Chen and D-J Chi ldquoApplication of a new DEMATEL toexplore key factors of Chinarsquos corporate social responsibilityevidence from accounting expertsrdquoQuality amp Quantity vol 49no 1 pp 135ndash154 2013

[117] D-S Chang S-H Chen C-W Hsu and A H Hu ldquoIdentifyingstrategic factors of the implantation CSR in the airline industrythe case of Asia-Pacific airlinesrdquo Sustainability vol 7 no 6 pp7762ndash7783 2015

[118] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis ofadopting an integrated decision making trial and evaluationlaboratory on a technology acceptance modelrdquo Expert Systemswith Applications vol 37 no 2 pp 1745ndash1754 2010

[119] H YWu ldquoConstructing a strategymap for banking institutionswith key performance indicators of the balanced scorecardrdquoEvaluation and Program Planning vol 35 no 3 pp 303ndash3202012

[120] Y Gazibey O Kantemir and A Demirel ldquoInteraction amongthe criteria affectingmain battle tank selection An analysis withDEMATEL methodrdquo Defence Science Journal vol 65 no 5 pp345ndash355 2015

[121] K Khalili-Damghani B Aminzadeh-Goharrizi S Rastegarand B Aminzadeh-Goharrizi ldquoSolving land-use suitabilityanalysis and planning problem by a hybrid meta-heuristicalgorithmrdquo International Journal of Geographical InformationScience vol 28 no 12 pp 2390ndash2416 2014

[122] M-L Tseng ldquoUsing hybridMCDMto evaluate the service qual-ity expectation in linguistic preferencerdquoApplied SoftComputingvol 11 no 8 pp 4551ndash4562 2011

[123] M A Quader S Ahmed R A Raja Ghazilla S Ahmed andM Dahari ldquoEvaluation of criteria for CO2 capture and storagein the iron and steel industry using the 2-tuple DEMATELtechniquerdquo Journal of Cleaner Production vol 120 pp 207ndash2202016

[124] M A Quader and S Ahmed ldquoA hybrid fuzzyMCDM approachto identify critical factors and CO2 capture technology forsustainable iron and steel manufacturingrdquo Arabian Journal forScience and Engineering vol 41 no 11 pp 4411ndash4430 2016

[125] M Kuo ldquoOptimal location selection for an international distri-bution center by using a new hybrid methodrdquo Expert Systemswith Applications vol 38 no 6 pp 7208ndash7221 2011

[126] S Altuntas H Selim and T Dereli ldquoA fuzzy DEMATEL-basedsolution approach for facility layout problem a case studyrdquoTheInternational Journal of Advanced Manufacturing Technologyvol 73 no 5-8 pp 749ndash771 2014

[127] S Altuntas and M K Yilmaz ldquoFuzzy DEMATEL method toevaluate the dimensions of marketing resources an applicationin SMEsrdquo Journal of Business Economics and Management vol17 no 3 pp 347ndash364 2016

[128] O Kabak F Ulengin B Cekyay S Onsel and O OzaydınldquoCritical success factors for the iron and steel industry inTurkey A fuzzy DEMATEL approachrdquo International Journal ofFuzzy Systems vol 18 no 3 pp 523ndash536 2016

[129] S Luthra K Govindan R K Kharb and S K ManglaldquoEvaluating the enablers in solar power developments in thecurrent scenario using fuzzy DEMATEL an Indian perspec-tiverdquo Renewable amp Sustainable Energy Reviews vol 63 pp 379ndash397 2016

[130] W W Wu and Y T Lee ldquoDeveloping global managersrsquo com-petencies using the fuzzy DEMATEL methodrdquo Expert Systemswith Applications vol 32 no 2 pp 499ndash507 2007

[131] J J H Liou L Yen and G-H Tzeng ldquoBuilding an effectivesafety management system for airlinesrdquo Journal of Air TransportManagement vol 14 no 1 pp 20ndash26 2008

[132] M-L Tseng ldquoUsing the extension of DEMATEL to integratehotel service quality perceptions into a cause-effect model inuncertaintyrdquo Expert Systems with Applications vol 36 no 5 pp9015ndash9023 2009

[133] M-L Tseng and Y H Lin ldquoApplication of fuzzy DEMATELto develop a cause and effect model of municipal solid wastemanagement in Metro Manilardquo Environmental Modeling ampAssessment vol 158 no 1-4 pp 519ndash533 2009

[134] B Chang C Chang and C Wu ldquoFuzzy DEMATEL methodfor developing supplier selection criteriardquo Expert Systems withApplications vol 38 no 3 pp 1850ndash1858 2011

[135] K-H Chang and C-H Cheng ldquoEvaluating the risk of failureusing the fuzzy OWA and DEMATEL methodrdquo Journal ofIntelligent Manufacturing vol 22 no 2 pp 113ndash129 2011

[136] Q Zhou W Huang and Y Zhang ldquoIdentifying critical successfactors in emergency management using a fuzzy DEMATELmethodrdquo Safety Science vol 49 no 2 pp 243ndash252 2011

[137] M-L Tseng Y-H Chen and Y Geng ldquoIntegratedmodel of hotspring service quality perceptions under uncertaintyrdquo AppliedSoft Computing vol 12 no 8 pp 2352ndash2361 2012

[138] M-L Tseng ldquoAn assessment of cause and effect decision-making model for firm environmental knowledge managementcapacities in uncertaintyrdquo Environmental Modeling amp Assess-ment vol 161 no 1ndash4 pp 549ndash564 2010

[139] W-W Wu ldquoSegmenting critical factors for successful knowl-edge management implementation using the fuzzy DEMATELmethodrdquo Applied Soft Computing vol 12 no 1 pp 527ndash5352012

[140] R J Lin ldquoUsing fuzzy DEMATEL to evaluate the green supplychain management practicesrdquo Journal of Cleaner Productionvol 40 pp 32ndash39 2013

[141] S K Patil and R Kant ldquoA fuzzy DEMATEL method to identifycritical success factors of knowledge management adoption insupply chainrdquo Journal of Information and Knowledge Manage-ment vol 12 no 3 Article ID 1350019 2013

[142] S Rouhani A Ashrafi and S Afshari ldquoSegmenting criticalsuccess factors for ERP implementation using an integratedfuzzy AHP and fuzzy DEMATEL approachrdquo World AppliedSciences Journal vol 22 no 8 pp 1066ndash1079 2013

[143] L Wu Q Zhang L Shan and Z Chen ldquoIdentifying criticalfactors influencing the use of additives by food enterprises inChinardquo Food Control vol 31 no 2 pp 425ndash432 2013

[144] S Zhou J Sun K-P Li and X Yang ldquoDevelopment of aroot cause degree procedure for measuring intersection safetyfactorsrdquo Safety Science vol 51 no 1 pp 257ndash266 2013

[145] Y Dou Q Zhu and J Sarkis ldquoIntegrating strategic carbonmanagement into formal evaluation of environmental supplierdevelopment programsrdquo Business Strategy and the Environmentvol 24 no 8 pp 873ndash891 2015

[146] K Govindan D Kannan and K M Shankar ldquoEvaluating thedrivers of corporate social responsibility in the mining industrywith multi-criteria approach a multi-stakeholder perspectiverdquoJournal of Cleaner Production vol 84 no 1 pp 214ndash232 2014

[147] S Routroy and C V Sunil Kumar ldquoAnalyzing supplier devel-opment program enablers using fuzzy DEMATELrdquo MeasuringBusiness Excellence vol 18 no 4 pp 1ndash26 2014

Mathematical Problems in Engineering 31

[148] M Tyagi P Kumar and D Kumar ldquoAssessment of criticalenablers for flexible supply chain performance measurementsystem using fuzzy DEMATEL approachrdquo Global Journal ofFlexible Systems Management vol 16 no 2 pp 115ndash132 2015

[149] K-J Wu C-J Liao M-L Tseng and A S F Chiu ldquoExploringdecisive factors in green supply chain practices under uncer-taintyrdquo International Journal of Production Economics vol 159pp 147ndash157 2015

[150] A K Sangaiah P R Subramaniam and X Zheng ldquoA combinedfuzzy DEMATEL and fuzzy TOPSIS approach for evaluatingGSD project outcome factorsrdquo Neural Computing and Applica-tions vol 26 no 5 pp 1025ndash1040 2015

[151] R K Malviya and R Kant ldquoHybrid decision making approachto predict and measure the success possibility of green supplychainmanagement implementationrdquo Journal of Cleaner Produc-tion vol 135 pp 387ndash409 2016

[152] S K Patil and R Kant ldquoA hybrid approach based on fuzzyDEMATEL and FMCDM to predict success of knowledgeman-agement adoption in supply chainrdquoApplied Soft Computing vol18 pp 126ndash135 2014

[153] A K Sangaiah J Gopal A Basu and P R Subramaniam ldquoAnintegrated fuzzy DEMATEL TOPSIS and ELECTRE approachfor evaluating knowledge transfer effectiveness with referenceto GSD project outcomerdquo Neural Computing and Applicationsvol 28 no 1 pp 111ndash123 2017

[154] E A Bakeshlou A A Khamseh M A G Asl J Sadeghi andM Abbaszadeh ldquoEvaluating a green supplier selection problemusing a hybrid MODM algorithmrdquo Journal of Intelligent Manu-facturing vol 28 no 4 pp 913ndash927 2017

[155] J Jassbi F Mohamadnejad and H Nasrollahzadeh ldquoA fuzzyDEMATEL framework for modeling cause and effect relation-ships of strategy maprdquo Expert Systems with Applications vol 38no 5 pp 5967ndash5973 2011

[156] Y-C Lee M-L Li T-M Yen and T-H Huang ldquoAnalysis offuzzy decision making trial and evaluation laboratory on tech-nology acceptance modelrdquo Expert Systems with Applicationsvol 38 no 12 pp 14407ndash14416 2011

[157] CValmohammadi and J Sofiyabadi ldquoModeling cause and effectrelationships of strategymap using fuzzyDEMATEL and fourthgeneration of balanced scorecardrdquo Benchmarking vol 22 no 6pp 1175ndash1191 2015

[158] M Younesi and E Roghanian ldquoA framework for sustainableproduct design a hybrid fuzzy approach based on qualityfunction deployment for environmentrdquo Journal of CleanerProduction vol 108 pp 385ndash394 2015

[159] C J Lin and W W Wu ldquoA causal analytical method for groupdecision-making under fuzzy environmentrdquo Expert Systemswith Applications vol 34 no 1 pp 205ndash213 2008

[160] R Fekri A Aliahmadi and M Fathian ldquoIdentifying the causeand effect factors of agile NPD process with fuzzy DEMATELmethod The case of Iranian companiesrdquo Journal of IntelligentManufacturing vol 20 no 6 pp 637ndash648 2009

[161] D J-F Jeng and G-H Tzeng ldquoSocial influence on the use ofclinical decision support systems revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechniquerdquo Computers amp Industrial Engineering vol 62 no 3pp 819ndash828 2012

[162] Y-C Chou C-C Sun and H-Y Yen ldquoEvaluating the criteriafor human resource for science and technology (HRST) basedon an integrated fuzzy AHP and fuzzy DEMATEL approachrdquoApplied Soft Computing vol 12 no 1 pp 64ndash71 2012

[163] M-A Afsharkazemi J Manouchehri M Salarifar and A ANasiripour ldquoKey factors affecting the hospital performance aqualitative study using fuzzy logicrdquo Quality amp Quantity vol 47no 6 pp 3559ndash3573 2013

[164] J Ren and B K Sovacool ldquoQuantifying measuring andstrategizing energy security determining the most meaningfuldimensions and metricsrdquo Energy vol 76 pp 838ndash849 2014

[165] E Akyuz and E Celik ldquoA fuzzy DEMATEL method to evaluatecritical operational hazards during gas freeing process in crudeoil tankersrdquo Journal of Loss Prevention in the Process Industriesvol 38 pp 243ndash253 2015

[166] C-C Tsao and W-W Wu ldquoEvaluation of design conditions forcompound special-core drilling composite materials using thefuzzy DEMATEL methodrdquo International Journal of ComputerIntegrated Manufacturing vol 27 no 11 pp 979ndash985 2014

[167] L-H Ho M-T Hsu and T-M Yen ldquoIdentifying core controlitems of information security management and improvementstrategies by applying fuzzy DEMATELrdquo Information and Com-puter Security vol 23 no 2 pp 161ndash177 2015

[168] D J-F Jeng ldquoGenerating a causal model of supply chain col-laboration using the fuzzy DEMATEL techniquerdquoComputers ampIndustrial Engineering vol 87 pp 283ndash295 2015

[169] H-C Liu J-X You Q-L Lin and H Li ldquoRisk assessment insystem FMEA combining fuzzy weighted average with fuzzydecision-making trial and evaluation laboratoryrdquo InternationalJournal of Computer IntegratedManufacturing vol 28 no 7 pp701ndash714 2015

[170] F Panaihfar C Heavey and P J Byrne ldquoDeveloping retailerselection factors for collaborative planning forecasting andreplenishmentrdquo Industrial Management amp Data Systems vol115 no 7 pp 1292ndash1324 2015

[171] C-Y Hsu K-T Chen and G-H Tzeng ldquoFMCDM with fuzzyDEMATEL approach for customersrsquo choice behavior modelrdquoInternational Journal of Fuzzy Systems vol 9 no 4 pp 236ndash2462007

[172] S Cebi ldquoA quality evaluation model for the design quality ofonline shopping websitesrdquo Electronic Commerce Research andApplications vol 12 no 2 pp 124ndash135 2013

[173] L Gigovic D Pamucar D Lukic and S Markovic ldquoGIS-Fuzzy DEMATEL MCDA model for the evaluation of the sitesfor ecotourism development a case study of lsquoDunavski kljucrsquoregion Serbiardquo Land Use Policy vol 58 pp 348ndash365 2016

[174] J S Jeong L Garcıa-Moruno J Hernandez-Blanco and ASanchez-Rıos ldquoPlanning of rural housings in reservoir areasunder (mass) tourism based on a fuzzyDEMATEL-GISMCDAhybrid and participatory method for Alange Spainrdquo HabitatInternational vol 57 pp 143ndash153 2016

[175] M J Rahimdel and R Bagherpour ldquoHaulage system selectionfor open pit mines using fuzzy MCDM and the view on energysavingrdquo Neural Computing and Applications pp 1ndash13 2016

[176] D Dalalah M Hayajneh and F Batieha ldquoA fuzzy multi-criteriadecision making model for supplier selectionrdquo Expert Systemswith Applications vol 38 no 7 pp 8384ndash8391 2011

[177] M Hiete M Merz T Comes and F Schultmann ldquoTrape-zoidal fuzzy DEMATEL method to analyze and correct forrelations between variables in a composite indicator for disasterresiliencerdquo OR Spectrum vol 34 no 4 pp 971ndash995 2012

[178] C-H Wang and J-N Chen ldquoUsing quality function deploy-ment for collaborative product design and optimal selection ofmodule mixrdquo Computers amp Industrial Engineering vol 63 no4 pp 1030ndash1037 2012

32 Mathematical Problems in Engineering

[179] C-H Wang ldquoUsing quality function deployment to conductvendor assessment and supplier recommendation for business-intelligence systemsrdquo Computers amp Industrial Engineering vol84 pp 24ndash31 2015

[180] A Baykasoglu V Kaplanoglu Z D U Durmusoglu and CSahin ldquoIntegrating fuzzy DEMATEL and fuzzy hierarchicalTOPSIS methods for truck selectionrdquo Expert Systems withApplications vol 40 no 3 pp 899ndash907 2013

[181] C H Wang and H S Wu ldquoA novel framework to evaluateprogrammable logic controllers a fuzzy MCDM perspectiverdquoJournal of Intelligent Manufacturing vol 27 no 2 pp 315ndash3242016

[182] A Fetanat and E Khorasaninejad ldquoA novel hybrid MCDMapproach for offshore wind farm site selection a case study ofIranrdquo Ocean amp Coastal Management vol 109 pp 17ndash28 2015

[183] S-K Hu M-T Lu and G-H Tzeng ldquoImproving mobilecommerce adoption using a new hybrid fuzzy MADM modelrdquoInternational Journal of Fuzzy Systems vol 17 no 3 pp 399ndash4132015

[184] G A Keskin ldquoUsing integrated fuzzy DEMATEL and fuzzyC means algorithm for supplier evaluation and selectionrdquoInternational Journal of Production Research vol 53 no 12 pp3586ndash3602 2015

[185] D Pamucar and G Cirovic ldquoThe selection of transport andhandling resources in logistics centers using Multi-AttributiveBorder Approximation area Comparison (MABAC)rdquo ExpertSystems with Applications vol 42 no 6 pp 3016ndash3028 2015

[186] H Taskin U A Kahraman and C Kubat ldquoEvaluation ofthe hospital service in Turkey using fuzzy decision makingapproachrdquo Journal of Intelligent Manufacturing 2015

[187] X Fu Q Zhu and J Sarkis ldquoEvaluating green supplier devel-opment programs at a telecommunications systems providerrdquoInternational Journal of Production Economics vol 140 no 1pp 357ndash367 2012

[188] Y Dou and J Sarkis ldquoA multiple stakeholder perspective onbarriers to implementing China RoHS regulationsrdquo ResourcesConservation amp Recycling vol 81 pp 92ndash104 2013

[189] Q Zhu J Sarkis and K-H Lai ldquoSupply chain-based barriersfor truck-engine remanufacturing in Chinardquo TransportationResearch Part E Logistics and Transportation Review vol 68pp 103ndash117 2014

[190] R Rajesh and V Ravi ldquoModeling enablers of supply chainrisk mitigation in electronic supply chains a Grey-DEMATELapproachrdquo Computers amp Industrial Engineering vol 87 pp 126ndash139 2015

[191] J Shao M Taisch and M Ortega-Mier ldquoA grey-decision-making trial and evaluation laboratory (DEMATEL) analysison the barriers between environmentally friendly productsand consumers practitionersrsquo viewpoints on the Europeanautomobile industryrdquo Journal of Cleaner Production vol 112 pp3185ndash3194 2016

[192] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoA greyDEMATEL approach to develop third-party logistics providerselection criteriardquo Industrial Management amp Data Systems vol116 no 4 pp 690ndash722 2016

[193] X Xia K Govindan and Q Zhu ldquoAnalyzing internal barriersfor automotive parts remanufacturers in China using grey-DEMATEL approachrdquo Journal of Cleaner Production vol 87 no1 pp 811ndash825 2015

[194] C Bai and J Sarkis ldquoA grey-based DEMATEL model for eval-uating business process management critical success factorsrdquo

International Journal of Production Economics vol 146 no 1pp 281ndash292 2013

[195] H Liang J Ren Z Gao et al ldquoIdentification of critical successfactors for sustainable development of biofuel industry in Chinabased on grey decision-making trial and evaluation laboratory(DEMATEL)rdquo Journal of Cleaner Production vol 131 pp 500ndash508 2016

[196] M-L Tseng ldquoA causal and effect decision making modelof service quality expectation using grey-fuzzy DEMATELapproachrdquo Expert Systems with Applications vol 36 no 4 pp7738ndash7748 2009

[197] C-M Su D-J Horng M-L Tseng A S F Chiu K-J Wu andH-P Chen ldquoImproving sustainable supply chain managementusing a novel hierarchical grey-DEMATEL approachrdquo Journalof Cleaner Production vol 134 pp 469ndash481 2016

[198] T Ozcan and F Tuysuz ldquoModified grey relational analysisintegrated with grey dematel approach for the performanceevaluation of retail storesrdquo International Journal of InformationTechnology amp Decision Making vol 15 no 2 pp 353ndash386 2016

[199] K Jenab A Sarfaraz P DWeinsier AMoeini andAM A Al-Ahmari ldquoI-DEMATEL method for integrated manufacturingtechnology selectionrdquo Journal of Manufacturing TechnologyManagement vol 26 no 3 pp 349ndash363 2015

[200] L Abdullah and N Zulkifli ldquoIntegration of fuzzy AHP andinterval type-2 fuzzy DEMATEL an application to humanresource managementrdquo Expert Systems with Applications vol42 no 9 pp 4397ndash4409 2015

[201] A V Nikjoo andM Saeedpoor ldquoAn intuitionistic fuzzy DEMA-TEL methodology for prioritising the components of SWOTmatrix in the Iranian insurance industryrdquo International Journalof Operational Research vol 20 no 4 pp 439ndash452 2014

[202] K Govindan R Khodaverdi and A Vafadarnikjoo ldquoIntu-itionistic fuzzy based DEMATEL method for developing greenpractices and performances in a green supply chainrdquo ExpertSystems with Applications vol 42 no 20 pp 7207ndash7220 2015

[203] Z P Fan W Suo and B Feng ldquoIdentifying risk factors ofIT outsourcing using interdependent information an extendedDEMATEL methodrdquo Expert Systems with Applications vol 39no 3 pp 3832ndash3840 2012

[204] H Liu J X You Ch Lu andY Z Chen ldquoEvaluating health-carewaste treatment technologies using a hybridmulti-criteria deci-sion making modelrdquo Renewable amp Sustainable Energy Reviewsvol 41 pp 932ndash942 2015

[205] W-L Suo B Feng and Z-P Fan ldquoExtension of the DEMATELmethod in an uncertain linguistic environmentrdquo Soft Comput-ing vol 16 no 3 pp 471ndash483 2012

[206] Y Li Y Hu X Zhang Y Deng and S Mahadevan ldquoAnevidential DEMATELmethod to identify critical success factorsin emergencymanagementrdquoApplied SoftComputing vol 22 pp504ndash510 2014

[207] K-H Chang andC-H Cheng ldquoA risk assessmentmethodologyusing intuitionistic fuzzy set in FMEArdquo International Journal ofSystems Science vol 41 no 12 pp 1457ndash1471 2010

[208] K-H Chang ldquoA more general risk assessment methodologyusing a soft set-based ranking techniquerdquo Soft Computing vol18 no 1 pp 169ndash183 2014

[209] X Geng and X Chu ldquoA new importance-performance analysisapproach for customer satisfaction evaluation supporting PSSdesignrdquoExpert SystemswithApplications vol 39 no 1 pp 1492ndash1502 2012

Mathematical Problems in Engineering 33

[210] S-MWuH-C Liu and L-EWang ldquoHesitant fuzzy integratedMCDM approach for quality function deployment a case studyin electric vehiclerdquo International Journal of Production Researchvol 55 no 15 pp 4436ndash4449 2017

[211] W-W Wu ldquoChoosing knowledge management strategies byusing a combined ANP and DEMATEL approachrdquo ExpertSystems with Applications vol 35 no 3 pp 828ndash835 2008

[212] G Buyukozkan and G Cifci ldquoA novel hybrid MCDM approachbased on fuzzy DEMATEL fuzzy ANP and fuzzy TOPSIS toevaluate green suppliersrdquo Expert Systems with Applications vol39 no 3 pp 3000ndash3011 2012

[213] W-H Tsai and W-C Chou ldquoSelecting management systemsfor sustainable development in SMEs a novel hybrid modelbased on DEMATEL ANP and ZOGPrdquo Expert Systems withApplications vol 36 no 2 pp 1444ndash1458 2009

[214] L A Zadeh ldquoFuzzy setsrdquo Information and Control vol 8 no 3pp 338ndash353 1965

[215] S Opricovic and G-H Tzeng ldquoDefuzzification within a multi-criteria decision modelrdquo International Journal of UncertaintyFuzziness and Knowledge-Based Systems vol 11 no 5 pp 635ndash652 2003

[216] J Gopal A K Sangaiah A Basu and X Z Gao ldquoIntegrationof fuzzy DEMATEL and FMCDM approach for evaluatingknowledge transfer effectiveness with reference to GSD projectoutcomerdquo International Journal of Machine Learning and Cyber-netics pp 1ndash17 2015

[217] A K Sangaiah X Z Gao M Ramachandran and X ZhengldquoA fuzzy DEMATEL approach based on intuitionistic fuzzyinformation for evaluating knowledge transfer effectiveness inGSD projectsrdquo International Journal of Innovative Computingand Applications vol 6 no 3-4 pp 203ndash215 2015

[218] C-W Li and G-H Tzeng ldquoIdentification of a threshold valuefor the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by asemiconductor intellectual property mallrdquo Expert Systems withApplications vol 36 no 6 pp 9891ndash9898 2009

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Page 16: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 17: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 18: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 19: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 20: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 21: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 22: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 23: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 24: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 25: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 26: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 27: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 28: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 29: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 30: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 31: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 32: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 33: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage
Page 34: DEMATEL Technique: A Systematic Review of the State-of ...2017/10/08  · of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage

The Value Of A Distinct Brand

One Pass Distinct Sampling - Oracle Scratchpad | Just ... procedures in dbms_stats package ... One pass distinct sampling----- contains same number of distinct values.

Integrating Fuzzy Dematel and SMAA-2 for Maintenance Expenses6)2/G06026071.pdf · 2017. 2. 9. · DEMATEL method is to identify the dependence levels between criteria SMAA-2 method

COMBINING DELPHI, AHP, AND DEMATEL TO IMPROVE STUDENTS’ SATISFACTION ON NATIONAL ... · 2017-12-26 · 165 COMBINING DELPHI, AHP, AND DEMATEL TO IMPROVE STUDENTS’ SATISFACTION

Using DEMATEL to Analyze Key Factors on …chur.chu.edu.tw/bitstream/987654321/43172/1/102CHPI...Abstract DEMATEL was used to analyze the key factors on establishing a tea industry

Distinct chemical and mineralogical composition of

Characterization of Distinct Classes of Differential Gene

Distinct features of indian society

Natural killer cells induce distinct modes of cancer …...NK cells induce distinct modes of cancer cell death 1 Natural killer cells induce distinct modes of cancer cell death: Discrimination

CONTRIBUTIONS OF DISTINCT TRUNK SEGMENTS TO

DISTINCT SOURCES OF LAW AND DISTINCT DOCTRINES: FEDERAL

Using the DEMATEL method to identify key reasons for mathematics support … · 2019. 12. 12. · M. Dzator and J. Dzator, Using the DEMATEL Method to Identify Key Reasons for Mathematics

Distributions. Basic Model for Distributions of Distinct Objects The following problems are equivalent: Distributing n distinct objects into b distinct

KOMBINASI METODE DEMATEL (DECISION …eprints.umm.ac.id/25261/1/jiptummpp-gdl-firdanuris-38467...KOMBINASI METODE DEMATEL (DECISION MAKING TRIAL AND EVALUATION LABORATORY) DAN AHP

DEMATEL Yönteminin Yeşil Tedarik Zinicirinde Kullanılması

Characterization of Distinct Subpopulations of Hepatic

Journal of Advanced Management Science Vol. 3, No. 1 ... · PDF fileANP-DEMATEL, Delphi method-AHP-TOPSIS, Dependence-based interval-valued ER (DIER)-BSC, DEMATEL- ANP- VIKOR) had

Revised DEMATEL 2

Application of DEMATEL approach to identify the influential ...and Evaluation Laboratory (DEMATEL) methodology analyzes sustainable development indicators in the auto components sectors

DISTINCT FEATURE OF THE COLLEGE

Using DEMATEL Method to Analyze the Causal Relations on

DEMATEL ﮏﯿﻨﮑﺗ Decision Making Trial And EvaluationFarabar_BI-DEMATEL.pdf · 2016. 12. 3. · DEMATEL ﮏﯿﻨﮑﺗ Decision Making Trial And Evaluation 2هدﺎﻘﻧ

Distinct neural signatures of cognitive subtypes of

Using DEMATEL Analytic network process (ANP) hybrid

Occurrence of Western Distinct Population … of Western Distinct Population Segment Steller Sea ... north of Frederick Sound ... Occurrence of Western Distinct Population Segment

ments of matter has distinct properties and a distinct atomic … · 2019-08-20 · S 8.3 Each of the more than 100 ele ments of matter has distinct properties and a distinct atomic

T OWARDS A S YSTEM D YNAMICS M ODELING M E- THOD B ASED ON DEMATEL

Dematel Analytic Network Process Kepribadian Papi Kostick

DEMATEL Technique: A Systematic Review of the State-of-the ...downloads.hindawi.com/journals/mpe/2018/3696457.pdf · ReviewArticle DEMATEL Technique: A Systematic Review of the State-of-the-Art

University of Groningen Temporal separation of distinct

E-Government Challenges: Methods Supporting Qualitative ... · comprehensive understanding of e-government challenges. Keywords: E-government strategy planning, PESTELMO, DEMATEL,

THE DISTINCT EFFECTS OF INFORMATION …worldmanagementsurvey.org/wp-content/images/2010/07/The-Distinct...THE DISTINCT EFFECTS OF INFORMATION TECHNOLOGY AND ... The distinct effects

DEMATEL - بهین تصمیمbehin-tasmim.ir/files/dematel/DEMATEL.pdf · 2019. 12. 17. · DEMATEL Decision Making Trial and Evaluation Laboratory ﯽﻤﺸﺘﺤﻣ ﯽﻠﻋ ﺮﺘﮐد

Understanding DISTINCT COUNT - SQLBI Distinct Count in DAX Query Plans Analysis of different query plans for different formulations of the distinct count. ... about SSAS. Distinct

Further investigation of distinct components of Stroop