the analytic hierarchy process and analytic network process
TRANSCRIPT
The analytic hierarchy processand analytic network process: an
overview of applicationsSeyhan Sipahi and Mehpare Timor
School of Business, Istanbul University, Istanbul, Turkey
AbstractPurpose – The purpose of this paper is to present a detailed literature review of the recentapplications of the analytic hierarchy process (AHP) and analytic network process (ANP) groupdecision-making methodologies.
Design/methodology/approach – Among more than 600 related papers published in the period2005-2009, a total of 232 application articles published in highly reputed international academicjournals were selected and referenced in this paper. Papers were categorized according to applicationareas, subject titles, publication date, country of origin, academic journals, and integratedmethodologies, and are summarized herein by various tables and charts.
Findings – The findings show that during the years 2005-2009, use of the AHP technique hascontinued to increase exponentially. Moreover, it is expected that ANP will gain more popularity in thefuture, as the benefits of ANP become better understood. Applications of AHP have been dominant inmanufacturing, followed by the environmental management and agriculture field, power and energyindustry, transportation industry, construction industry, and healthcare. Other remarkable applicationfields include education, logistics, e-business, IT, R&D, telecommunication industry, finance andbanking, urban management, defense industry and military, government, marketing, tourism andleisure, archaeology, auditing, and the mining industry.
Research limitations/implications – The study does not consider theoretical based AHP or ANParticles. Also the search excluded conference proceedings, masters’ theses, and doctoral dissertations.
Practical implications – It is hoped that this study will guide practitioners in future work towardsadvancement of these techniques and will help the managers to select better decisions by making useof these methodologies.
Originality/value – The paper presents a comprehensive literature review of recent applications ofAHP, and also ANP decision tools over the period 2005-2009. Furthermore, the paper covers fuzzyAHP and fuzzy ANP extensions that are becoming popular methods in some application areas oftraditional AHP and ANP.
Keywords Analytical hierarchy process, Decision making
Paper type Literature review
1. IntroductionIn the 1970s, Thomas L. Saaty developed the analytic hierarchy process (AHP)technique, which constructs a decision-making problem in various hierarchies as goal,criteria, sub-criteria, and decision alternatives. The theoretical background andmathematical concept of the AHP methodology have been expressed in several booksand articles (Vargas, 1990; Saaty, 1990, 2001b; Saaty and Vargas, 2001).
The AHP technique performs pairwise comparisons to measure the relativeimportance of elements at each level of the hierarchy and evaluates alternatives at thelowest level of the hierarchy in order to make the best decision among multiplealternatives. AHP provides decision makers with a way to transform subjective
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AHP and ANP:an overview of
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Management DecisionVol. 48 No. 5, 2010
pp. 775-808q Emerald Group Publishing Limited
0025-1747DOI 10.1108/00251741011043920
judgments into objective measures. Due to its mathematical simplicity and flexibility,AHP has been a favorite decision tool for research in many fields, such as engineering,food, business, ecology, health, and government.
In addition to AHP, the analytic network process (ANP) technique, also developedby Thomas L. Saaty, is a generic form of AHP that allows for more complex,interdependent, relationships, and feedback among elements in the hierarchy (Saaty,2001a). ANP has been used in several decision-making applications in the last decade,especially in the study of risk and uncertainty.
The purpose of this study is to present a detailed literature review of the recentapplications of AHP and ANP. Out of more than 600 related articles published in theperiod from 2005 to 2009, a total of 232 application-based articles published in Englishlanguage and highly reputable academic journals were selected and referred in thispaper. Articles were categorized according to methodology, journal name, publicationdate, country of origin, application areas, subject titles, and integrated methodologies,and are summarized herein by various tables and charts.
2. Previous AHP literature studiesIn the last 20 years, few studies were published in the area of AHP literature searches.In 1993, Apostolou and Hassell (1993) summarized current use of AHP in accountingresearch. The literature was presented chronologically by year of publication todocument the evolution of AHP use in accounting. Omkarprasad and Sushil (2006)extensively analyzed the applicability of AHP, and reviewed 150 articles that had beenpublished in highly reputed journals since 2003. Articles were categorized by“selection”, “evaluation”, “benefit-cost analysis”, “allocations”, “planning anddevelopment”, “priority and ranking”, “decision making”, “forecasting”, and “healthand related fields” application categories. In another literature search study, Ho (2008)reviewed integrated AHP articles that were published from 1997 to 2006.“Mathematical programming”, “quality function deployment (QFD)”,“meta-heuristics”, “SWOT analysis”, and “data envelopment analysis (DEA)”,decision tools that were commonly combined with AHP, were emphasized in Ho’sarticle. Furthermore, the most popular application areas for integrated AHP weresummarized. Liberatore and Nydick (2008) studied 50 AHP articles in medical andhealthcare published since 1997. These articles were classified by “publication year”,“journal”, “healthcare category”, “method of analyzing alternatives”, “participants”,and “application type”.
This article aimed to present a rather comprehensive literature review of recentapplications of the AHP as well as the ANP over the period from 2005 to 2009.Furthermore, our study covers fuzzy AHP and fuzzy ANP extensions that arebecoming popular methods in some application areas of traditional AHP and ANP. Theliterature review was undertaken by conducting an expansive search on such academicdatabases as ISI Web of Science, Science Direct, Proquest ABI/Inform, and Ebscohost(business) using the AHP keywords “AHP”, “Analytic Hierarchy Process”, “ANP”,“Analytic Network Process”, “Fuzzy AHP”, “Fuzzy Analytic Hierarchy Process”,“Fuzzy ANP”, “Fuzzy Analytic Network Process”, and “pairwise comparisons”. Oursearch excluded conference proceedings, master’s theses, and doctoral dissertations.We inspected each article by publication year, methodology, country of origin,integrated techniques, application areas, and by subject.
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3. Classifications and observationsTable I classifies articles by country of origin and by publication year. Taiwan had thelargest number of published articles (52) followed by Turkey (36), The USA (19), China(10), and Korea (10). Table II indicates the use of AHP, ANP, Fuzzy AHP, or FuzzyANP methodologies in these countries. Numbers in parentheses represent referencenumbers. As observed in Table II, the articles published in USA, China, and Koreawere predominantly based on the AHP method. However, in Taiwan and Turkey,articles focused on fuzzy AHP as well. Table III categorizes all 232 articles by AHPmethodology and publication year. Numbers in brackets represent reference numbers.
Of 232 articles, 169 utilized the AHP method. Also, a significant use of fuzzy AHP isobserved. Although the use of fuzziness has been increasing, fuzziness in AHP hasbeen criticized in that the fuzzy approach does not yield better results than the simplerand more direct approach of the AHP and does not yield more-valid priorities (Saaty,2006). Additionally, 2009 was the year in which the highest number of applicationarticles was published.
Table IV indicates the top ten journals that published the largest number of articlesduring the period from 2005 to 2009. In total 40 articles appeared in Expert Systemswith Applications, followed by the European Journal of Operational Research (14),International Journal of Production Economics (12), and International Journal ofProduction Research (11). Numbers in brackets represent reference numbers.
In this study, articles have also been classified according to additional methods usedwith AHP, fuzzy AHP, ANP, or fuzzy ANP. Integrated methods were used in 141 (61per cent) of the articles (see Figure 1). Among the integrated methodologies, simulationwas the most popular technique followed by TOPSIS and GIS. Other tools that werecommonly combined with AHP were goal programming, DEA, Delphi method,balanced scorecard, factor analysis, fuzzy logic model, genetic algorithm, and SWOTanalysis (see Figure 2). The association of the integrated methodologies to AHP andANP and the reference numbers of the articles related to them are tabulated in Table V.
YearCountry 2005 2006 2007 2008 2009 Total
Taiwan 5 3 14 10 20 52Turkey 4 5 10 5 12 36The USA 2 6 6 4 1 19China 1 2 2 4 1 10Korea 1 1 4 1 3 10Hong Kong 2 1 1 5 – 9Greece 1 – 1 3 2 7India 1 1 2 1 2 7The UK 1 2 2 – 2 7Other countriesa 6 8 5 13 9 41Cooperative works 3 8 8 9 6 34Total 27 37 55 55 58 232
Notes: aArgentina, Austria, Belgium, Brazil, Chile, Colombia, Denmark, Finland, France, Germany,Hungary, Indonesia, Iran, Italy, Japan, Malaysia, Mexico, Netherlands, New Zealand, Poland, Qatar,Rwanda, Saudi Arabia, Serbia, Singapore, Slovenia, South Africa, Spain, Sri Lanka, Switzerland,Thailand, UAE (Dubai)
Table I.Classification of articles
by country andpublication year
AHP and ANP:an overview of
applications
777
AHP AHP and ANP ANP Fuzzy AHP
FuzzyAHP andfuzzy ANP Fuzzy ANP
Grandtotal
Taiwan Chang et al. (2007a); Chang et al.(2007); Chao and Chen (2009);Che et al. (2007); Chen and Liu(2007); Cheng et al. (2005);Chiueh et al. (2008); Chou andCheng (2006); Hsieh et al. (2006);Hsu et al. (2008a); Hsu et al.(2008b); Hsu and Pan (2009);Huang (2009); Huang et al.(2009); Kuo et al. (2008); Kuoand Chen (2006); Lin and Hsu(2007); Liou and Tzeng (2007);Liu and Hai, 2005); Liu andChen (2007); Tsai and Su (2005);Shee and Wang (2008); Su andChou (2008); Tsai (2005); Tsaiand Hung (2009); Wang andChang (2007); Wei et al. (2005);Wu et al. (2007); Yu and Tsai(2008
Chang et al.(2007b); Yanget al. (2009)
Chang et al. (2009); Liaoand Chang (2009); Linand Juan (2009)
Chang et al. (2009); Chiang et al.(2008); Hsu et al. (2009); Hu et al.(2009); Huang et al. (2008); Kangand Lee (2007); Kreng and Wu(2007); Lai and Tsai (2009); Lee(2009); Lee et al. (2008); Lee et al.(2009a); Lee et al. (2009b); Linet al. (2009); Lin (2009); Ma et al.(2007); Sun et al. (2009); Tsenget al. (2009); Wu et al. (2009)
52
Turkey Ayag (2005); Ayag (2007);Baykasoglu et al. (2009);Caliskan (2006); Celik (2009);Dagdeviren et al. (2009);Dikmen and Birgonul (2006);Erol et al. (2009); Gol and Catay(2007); Isiklar and Buyukozkan(2007); Kahraman et al. (2007);Kandakoglu et al. (2009);Korkmaz et al. (2008); Ozgenet al. (2008); Sevkli et al. (2007);Sun et al. (2008); Yurdakul andIc (2005)
Ismayilova et al.(2007);
Demirtas and Ustun(2009); Yuksel andDagdeviren (2007)
Bozbura et al. (2007);Buyukozkan et al. (2008); Cebeci(2009); Celik et al. (2009);Dagdeviren and Yuksel (2008);Erensal et al. (2006); Ertugruland Karakasoglu (2009); Golecand Taskin (2007); Kayakutluand Buyukozkan (2008); Kulakand Kahraman (2005); Secmeet al. (2009); Tiryaki andAhlatcioglu (2009); Tolga et al.(2005)
Kahramanet al. (2006)
Ayag and Ozdemir(2007) and Ayag andOzdemir (2009)
36
(continued )
Table
II.Classifi
cationof
thetop
five
countries’articlesby
methodology
MD
48,5
778
AHP AHP and ANP ANP Fuzzy AHP
FuzzyAHP andfuzzy ANP Fuzzy ANP
Grandtotal
USA Cooper and Qiu (2006); Gabrielet al. (2006); Gibney and Shang(2007); Huang and Bian (2009);Khorramshahgol andDjavanshir (2008); Kull andTalluri (2008); Lee and Kozar(2006); Levary (2007); Levary(2008); Li et al. (2008); Ma et al.(2005); Okudan (2006); Park andRothrock (2007); Rabelo et al.(2007); Sale and Sale (2005);Strager and Rosenberger (2006);Sun et al. (2007);
Partovi (2006);Peniwati andBrenner (2008)
Bertolini andBevilacqua (2006)
China Cheng et al. (2008); Hu et al.(2008); Ngai and Chan (2005);Wan et al. (2009); Wang andYang (2007); Wang et al.(2008a); Wang et al. (2008b);Ying et al. (2007); Zhang et al.(2006); Zhao et al. (2006);
10
Korea Ahn and Choi (2008); An et al.(2007); Chung and Lee (2009);Kim et al. (2005); Lee et al.(2007); Niaraki and Kim (2009);Shin et al. (2007); Shin et al.(2009); Yang et al. (2007); Yooand Choi (2006);
10
Grand total 83 5 5 31 1 2 127
Table
II.
AHPand
ANP:
anoverview
ofapplications
779
Year
Method 2005 2006 2007 2008 2009Total no.of articles
AHP Ayag (2005); Carnero (2005);Chan et al. (2005); Chan andChung (2005); Cheng et al.(2005); Chougule and Ravi(2005); Hummel et al. (2005);Kim et al. (2005); Krajnc andGlavic (2005); Kwak et al.(2005); Lam and Chin (2005);Liu and Hai (2005); Tsai(2005); Ma et al. (2005); Ngaiand Chan (2005); Paralikasand Lygeros (2005); Richmanet al. (2005); Sale and Sale(2005); Scholl et al. (2005);Tsai (2005); Wang et al.(2005); Wattage and Mardle(2005); Wei et al. (2005);Yurdakul and Ic (2005)
Abildtrup et al. (2006);Alkahtani et al. (2006); Arslanand Khisty (2006); Bertoliniand Bevilacqua (2006);Caliskan (2006); Chan et al.(2006); Chan (2006); Chou andCheng (2006); Cieslik et al.(2006); Cooper and Qiu (2006);Dey (2006); Dikmen andBirgonul (2006); Ertay et al.(2006); Gabriel et al. (2006);Hsieh et al. (2006); Karami(2006); Korhonen et al. (2006);Korhonen and Voutilainen(2006); Kuo and Chen (2006);Lee and Kozar (2006); Lianget al. (2006); Masozera et al.(2006); Nagesha andBalachandra (2006); Okudan(2006); Strager andRosenberger (2006); Sun et al.(2008); Teo and Ling (2006);Tudela et al. (2006);Vashishtha andRamachandran (2006); Yooand Choi (2006); Yuniarto andLabib (2006); Zhang et al.(2006); Zhao et al. (2006)
An et al. (2007); Arshinderand Deshmukh (2007); Ayag(2007); Banuelas and Antony(2007); Carlucci and Schiuma(2007); Chang et al. (2007a);Chang et al. (2007);Chatzimouratidis andPilavachi (2007); Che et al.(2007); Chen and Liu (2007);Diamantopoulos (2007);Gerdsri and Kocaoglu (2007);Gibney and Shang (2007); Goland Catay (2007); Hafeez et al.(2007); Hsu et al. (2008b);Isiklar and Buyukozkan(2007); Islam (2007);Kahraman et al. (2007);Korpela et al. (2007); Lee et al.(2007); Levary (2007); Lin andHsu (2007); Liou and Tzeng(2007); Liu et al. (2007);Oddershede et al. (2007); Parkand Rothrock (2007); Petersand Zelewski (2007); Rabeloet al. (2007); Saaty (2001b);Sevkli et al. (2007); Shin et al.(2007); Srdjevic (2007); Sunet al. (2007); Wang and Yang(2007); Wang and Chang(2007); Wu et al. (2007); Yanget al. (2007); Ying et al. (2007);Zeng et al. (2007)
Ahn and Choi (2008); Anandaand Herath (2008); Angelouand Economides (2008);Carrion et al. (2008);Chatzimouratidis andPilavachi (2008); Cheng et al.(2008); Chin et al. (2008);Chiueh et al. (2008); Ciconeet al. (2008); Dey andRamcharan (2008);Firouzabadi et al. (2008);Garcia et al. (2008); Giokasand Pentzaropoulos (2008);Hsu et al. (2008a); Hu et al.(2008); Huang et al. (2009);Kengpol (2008);Khorramshahgol andDjavanshir (2008); Kinra andKotzab (2008); Korkmaz et al.(2008); Kull and Talluri(2008); Kuo et al. (2008); Leeand Chan (2008); Lee et al.(2008); Levary (2008); Li et al.(2008); Martinez-Olvera(2008); Ozgen et al. (2008);Parra-Lopez et al. (2008);Partovi (2007); Quintero et al.(2008); Shee D (2008); Su andChou (2008); Valente andVettorazzi (2008); Wang et al.(2008a); Wang et al. (2008b);Wang et al. (2008c); Wanget al. (2008d); Wong and Li(2008); Yu J (2008)
Aguilar-Lasserre et al. (2009);Bahinipati et al. (2009);Baykasoglu et al. (2009);Berrittella et al. (2009); Celik(2009); Chao and Chen (2009);Chatzimouratidis andPilavachi (2009a);Chatzimouratidis andPilavachi (2009b); Chung andLee (2009); Dagdeviren et al.(2009); Erol et al. (2009);Garcia-Cascales and Lamata(2009); Ho and Emrouznejad(2009); Hsu and Pan (2009);Huang (2009); Huang andBian (2009); Hughes (2009);Kandakoglu et al. (2009);Karger and Hennings (2009);Li and Li (2009); Mansar et al.(2009); Michnik and Lo (2009);Naesens et al. (2009); Nekhayet al. (2009); Niaraki and Kim(2009); Oconnor and Kuyler(2009); Park et al. (2009);Sharma and Agrawal (2009);Shin et al. (2009); Sueyoshiet al. (2009); Tsai and Hung(2009); Wan et al. (2009)
169
(continued )
Table
III.Categorized
referencesat
aglance
MD
48,5
780
Year
Method 2005 2006 2007 2008 2009Total no.of articles
Fuzzy AHP Kulak and Kahraman (2005);Tolga et al. (2005)
Erensal et al. (2006) Bozbura et al. (2007); Chanet al. (2005); Chen et al. (2007);Golec and Taskin (2007);Hwang et al. (2007); Kang andLee (2007); Kreng and Wu(2007); Ma et al. (2007); Raviand Mukherjee (2007)
Buyukozkan et al. (2008);Cakir and Canbolat (2008);Chan et al. (2008); Chiang et al.(2008); Dagdeviren andYuksel (2008); Huang et al.(2008); Kayakutlu andBuyukozkan (2008); Lee et al.(2008); Sasmal andRamanjaneyulu (2008); Wangand Chin (2008); Zaerpouret al. (2008)
Cebeci (2009); Celik et al.(2009); Chang et al. (2009);Chang et al. (2009); Ertugruland Karakasoglu (2009); Hsuet al. (2009); Hu et al. (2009);Lai and Tsai (2009); Lee(2009); Lee et al. (2009a); Leeet al. (2009b); Lin et al. (2009);Lin (2009); Naghadehi et al.(2009); Secme et al. (2009);Sun et al. (2009); Tiryaki andAhlatcioglu (2009); Tsenget al. (2009); Wu et al. (2009)
42
ANP Cheng and Li (2007); Yukseland Dagdeviren (2007)
Wong et al. (2008a); Yan et al.(2008); Zoffer et al. (2008)
Chang et al. (2009); Demirtasand Ustun (2009); Liao andChang (2009); Lin and Juan(2009)
9
AHP andANP
Wolfslehner et al. (2005) Leung et al. (2006); Peniwatiand Brenner (2008)
Chang et al. (2007b);Ismayilova et al. (2007);Partovi (2006)
Wong et al. (2008b) Cortes-Aldana et al. (2009);Yang et al. (2009)
9
Fuzzy ANP Ayag and Ozdemir (2007) Ayag and Ozdemir (2009) 2Fuzzy AHPand FuzzyANP
Kahraman et al. (2006) 1
Total no. ofarticles
27 37 55 55 58 232
Table
III.
AHPand
ANP:
anoverview
ofapplications
781
Year of publicationJournal name 2005 2006 2007 2008 2009
Total no. ofarticles
Expert Systems withApplications
Cheng et al. (2005);Ngai and Chan (2005);Tsai (2005)
Bozbura et al. (2007);Carlucci and Schiuma(2007); Che et al. (2007);Chen et al. (2007); Kangand Lee (2007)
Cakir and Canbolat(2008); Chin et al.(2008); Lee et al. (2008);Sasmal andRamanjaneyulu (2008);Su and Chou (2008)
Cebeci (2009); Celiket al. (2009); Chang et al.(2009); Chang et al.(2009); Chao and Chen(2009); Dagdeviren et al.(2009); Ertugrul andKarakasoglu (2009); Hoand Emrouznejad(2009); Hsu et al. (2009);Hsu and Pan (2009); Huet al. (2009); Huang(2009); Huang and Bian(2009); Karami (2006);Lai and Tsai (2009);Lee et al. (2009a); Leeet al. (2009b); Li and Li(2009); Lin and Juan(2009); Mansar et al.(2009); Naghadehi et al.(2009); Niaraki andKim (2009); Secme et al.(2009); Sun et al. (2009);Wu et al. (2009); Yanget al. (2009)
40
European Journal ofOperational Research
Kwak et al. (2005);Scholl et al. (2005)
Arslan and Khisty(2006); Caliskan (2006);Kahraman et al. (2006);Korhonen et al. (2006);Korhonen andVoutilainen (2006)
Kreng and Wu (2007);Park and Rothrock(2007); Wang andChang (2007)
Partovi (2007) Cortes-Aldana et al.(2009); Michnik and Lo(2009); Sueyoshi et al.(2009)
14
(continued)
Table
IV.
Classifi
cationof
thetop
tenjournals’articles
byyears
MD
48,5
782
Year of publicationJournal name 2005 2006 2007 2008 2009
Total no. ofarticles
International Journalof ProductionEconomics
Liu and Hai (2005);Tolga et al. (2005); Weiet al. (2005)
Dey (2006) Korpela et al. (2007);Partovi (2006); Rabeloet al. (2007)
Buyukozkan et al.(2008); Kengpol (2008);Kinra and Kotzab(2008); Martinez-Olvera (2008)
Naesens et al. (2009) 12
International Journalof ProductionResearch
Ayag (2007); Chouguleand Ravi (2005);Yurdakul and Ic (2005)
Yuniarto and Labib(2006)
Ayag and Ozdemir(2009); Ayag (2005);Ravi and Mukherjee(2007); Sevkli et al.(2007)
Chan et al. (2008);Chiang et al. (2008); Liet al. (2008)
11
Computers &Industrial Engineering
Chang et al. (2007a) Firouzabadi et al.(2008); Garcia-Cascalesand Lamata (2009);Levary (2008); Wanget al. (2008d); Yu J(2008)
Ayag and Ozdemir(2009); Bahinipati et al.(2009); Demirtas andUstun (2009); Lin(2009)
10
Information Sciences Kulak and Kahraman(2005)
Erensal et al. (2006);Ertay et al. (2006)
Chang et al. (2007b);Golec and Taskin(2007); Yuksel andDagdeviren (2007)
Dagdeviren andYuksel (2008);Korkmaz et al. (2008);Ozgen et al. (2008)
Tiryaki andAhlatcioglu (2009)
10
Energy Policy Liang et al. (2006) Chatzimouratidis andPilavachi (2007); Leeet al. (2007)
Chatzimouratidis andPilavachi (2008);Cicone et al. (2008); Leeet al. (2008); Wang et al.(2008a)
Chatzimouratidis andPilavachi (2009a);Chatzimouratidis andPilavachi (2009b)
9
(continued)
Table
IV.
AHPand
ANP:
anoverview
ofapplications
783
Year of publicationJournal name 2005 2006 2007 2008 2009
Total no. ofarticles
Journal ofEnvironmentalManagement
Wattage and Mardle(2005)
Zhao et al. (2006) Zeng et al. (2007) Dey and Ramcharan(2008)
Celik (2009); Changet al. (2009); Chung andLee (2009); Oconnorand Kuyler (2009)
8
Omega Chan et al. (2005) Chou and Cheng (2006);Peniwati and Brenner(2008)
Chan and Kumar(2007)
Huang et al. (2008) Hughes (2009); Tsaiand Hung (2009);Tseng et al. (2009)
8
Building andEnvironment
Kim et al. (2005) Teo and Ling (2006) An et al. (2007); Changet al. (2007); Cheng andLi (2007); Wu et al.(2007)
Hsu et al. (2008a);Wong and Li (2008)
8
Others 102Total no. of articles 232
Table
IV.
MD
48,5
784
4. Analysis of applications by areasTable VI categorizes articles according to application areas. The manufacturing industrycomes in at the top with 76 articles, followed by environmental management andagriculture (26), general decision problems (19), power and energy industry (15),transportation industry (15), construction industry (11), and healthcare (10). AHP andFuzzy AHP were the most preferred techniques. Other remarkable application fieldsinclude education, logistics, e-business, IT, R&D, telecommunication industry, financeand banking, urban management, defense industry and military, government, marketing,tourism and leisure, archaeology, auditing, mining industry, sport, and politics.
4.1 AHP and ANP in manufacturingA great interest in the study of AHP and ANP is obvious in the area of manufacturing.Supplier selection, supply chain evaluation, location selection, system selection orevaluation, and strategy evaluation are the most common problems tackled in themanufacturing area.
Figure 1.Percentages of integrated
methods
Figure 2.Integrated methods used
AHP and ANP:an overview of
applications
785
AHP Fuzzy AHP ANPAHP andANP
Simulation Ahn and Choi (2008); Ayag (2005);Ayag (2007); Banuelas and Antony(2007); Berrittella et al. (2009); Chungand Lee (2009); Gabriel et al. (2006);Hsu and Pan (2009); Kuo et al. (2008);Li and Li (2009); Park and Rothrock(2007); Rabelo et al. (2007); Richmanet al. (2005); Sharma and Agrawal(2009)
Huang et al. (2008)
TOPSIS Cheng et al. (2008); Dagdeviren et al.(2009); Hsieh et al. (2006); Isiklar andBuyukozkan (2007); Kandakoglu et al.(2009); Kuo et al. (2008); Yurdakul andIc (2005)
Buyukozkan et al. (2008); Ertugruland Karakasoglu (2009); Secme et al.(2009); Tseng et al. (2009); Wu et al.(2009)
GIS Carrion et al. (2008); Chiueh et al.(2008); Cooper and Qiu (2006); Huangand Bian (2009); Ma et al. (2005);Nekhay et al. (2009); Strager andRosenberger (2006); Valente andVettorazzi (2008); Wang et al. (2008);Ying et al. (2007)
Chang et al. (2009)
Goal programming Bertolini and Bevilacqua (2006);Firouzabadi et al. (2008); Ho andEmrouznejad (2009); Kull and Talluri(2008); Peters and Zelewski (2007)
Lee et al. (2009b); Wang and Chin(2008)
Chang et al. (2009); Demirtas andUstun (2009)
(continued )
Table
V.
Integratedmethods
toAHP,F
uzzyAHP,A
NP
andAHP-ANP
MD
48,5
786
AHP Fuzzy AHP ANPAHP andANP
DEA Ertay et al. (2006); Giokas andPentzaropoulos (2008); Korpela et al.(2007); Liu and Hai (2005); Sevkli et al.(2007); Sueyoshi et al. (2009); Wanget al. (2008d)
Tseng et al. (2009)
Delphi method Hsieh et al. (2006); Hu et al. (2008);Tsai (2005); Shin et al. (2009)
Kayakutlu and Buyukozkan (2008);Lee et al. (2009a)
Lin and Juan (2009)
Balanced scorecard Chan (2006); Hafeez et al. (2007);Huang (2009); Sale and Sale (2005)
Lee et al. (2008) Leung et al.(2006)
Factor analysis Carnero (2005); Liou and Tzeng (2007);Teo and Ling (2006); Zhang et al.(2006)
Lin et al. (2009); Ma et al. (2007)
Fuzzy logic model Arshinder and Deshmukh (2007);Arslan and Khisty (2006); Bahinipatiet al. (2009); Paralikas and Lygeros(2005); Yuniarto and Labib (2006)
Genetic algorithm Aguilar-Lasserre et al. (2009); Chanet al. (2005); Chan et al. (2006); Chanand Chung (2005); Lin and Hsu (2007)
SWOT Kahraman et al. (2007); Kandakogluet al. (2009); Masozera et al. (2006)
Zaerpour et al. (2008) Yuksel and Dagdeviren (2007)
Table
V.
AHPand
ANP:
anoverview
ofapplications
787
Wei et al. (2005) proposed an ERP system selection method in which an objectivehierarchy was constructed and appropriate attributes were specified to provideguidance for ERP system valuation. The proposed methodology attempted to ensurethat the evaluation process was aligned with the competitive strategies and goals of theenterprise. The AHP method was applied for dealing with the ambiguities involved inassessment of ERP alternatives and relative importance weightings of attributes.
Liu and Hai (2005) proposed a six-step AHP procedure for the supplier selectionproblem. In order to decide the total ranking of suppliers, they compared the weightedsum of the selection number of rank votes after determining the weights in a selectedrank. This investigation presented a novel weighting procedure in place of the AHPpaired comparison. This provided a simpler method than AHP, called the votinganalytic hierarchy process, but it does not lose the systematic approach of derivingweights to be used and scoring of the performance of suppliers. Ertay et al. (2006)integrated DEA and AHP for facility layout design in manufacturing systems. In theirstudy, the criteria to be minimized were viewed as inputs, whereas the criteria to bemaximized were considered outputs. Then, AHP was applied to collect qualitative datarelated to quality and flexibility. The DEA methodology was used to solve the layoutdesign problem by simultaneously considering both the quantitative and qualitativedata. The integrated procedure was applied to a real data set in a case study. Anotherstudy on supplier selection, was done by Sevkli et al. (2007). In their study, the DEAapproach was embedded into AHP for weight derivation and aggregation. Chan et al.(2005) developed a hybrid genetic algorithm for production and distribution problemsin multi-factory supply chain models. In their work, the AHP method was utilized toassign weights and relate supply chain criteria such as operating cost, service level,resources utilization, etc. Then, genetic algorithms were utilized to determine joballocation into suitable production plants. In another study, Chan and Chung (2005)combined AHP and genetic algorithms again to determine the optimized schedule forcollaboration of each entity to fulfill demands. They focused on the demand due datefactor in a multi-echelon distribution network problem and the impact on productionscheduling in manufacturing plants.
Carnero (2005) proposed a model that carries out the decision making in relation toselection of diagnostic techniques and instrumentation in predictive maintenanceprograms. The model combines AHP and factor analysis and has been tested in screw
Area AHP ANPAHP andANP
FuzzyAHP
FuzzyANP
Fuzzy AHP andfuzzy ANP Total
Manufacturing industry 45 2 4 23 1 1 76Environmental managementand agriculture
24 1 1 26
General decision problem 12 2 1 3 1 19Power and energy industry 14 1 15Transportation industry 12 1 2 15Construction industry 8 1 1 1 11Health 10 10Others 44 3 2 11 60Total 169 9 9 42 2 1 232
Table VI.Classification byapplication area andmethodology
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compressors with integration of lubricant and vibration analyses. Lam and Chin (2005)examined the critical success factors of conflict management in collaborative newproduct development. By using AHP, they prioritized the importance of four categoriesof success factors, namely relationship management, conflict handling system, newproduct development, process management, and communication. They found thatcommunication management, trust, and commitment to the collaboration are the mostimportant factors. Ayag (2005) used AHP to evaluate conceptual design alternatives ina new product design environment and used a simulation generator integrated withthis technique to perform economic analyses for AHP’s high-score alternatives. Finally,the results of both techniques, simulation and AHP, were used in a benefit/costanalysis to reach a final decision on the conceptual design alternatives. Isiklar andBuyukozkan (2007) proposed a model to evaluate mobile phone options with respect touser preference order. In their study, the most desirable features influencing the choiceof a mobile phone were identified. AHP was applied to determine the relative weightsof evaluation criteria and extension of the technique for order preference by similarityto ideal solution (TOPSIS) was applied to rank the mobile phone alternatives.
A few other research papers have utilized the ANP technique along with AHP tomeasure inter-factor dependencies in manufacturing. For instance, Partovi (2006) usedQFD, AHP, and ANP models for a facility location problem that incorporates bothexternal and internal criteria in the decision-making process. QFD matrices withinterconnected rows and columns relate market segments, competitive priorities,critical processes, location attributes, and various locations. In the model, AHPdetermines the intensity of the relationship between the row and column variables ofeach matrix, whereas ANP determines the intensity of synergistic effects amongcolumn variables. The model fine-tunes and adds precision to an otherwise qualitativestrategic decision process. Partovi (2007) also developed an analytical technique forprocess selection and evaluation for manufacturing systems, again using QFD, AHP,and ANP models. In another study, Yuksel and Dagdeviren (2007) explained theweaknesses of traditional SWOT analysis and performed a quantitative SWOTanalysis wherein the possible dependencies among SWOT factors were included. TheANP technique, which enables measurement of inter-factor dependencies, was utilizedin their work. They also used the AHP method with SWOT analysis to compare theeffects of the dependencies among the SWOT factors on prioritizing the alternativestrategies and on the SWOT sub-factor weights. Yang et al. (2009) proposed anintegrated process that allows manufacturing systems to construct a performancemeasurement model. Performance criteria from the literature and an expertquestionnaire were utilized prior to building the performance measurement model.AHP and ANP were utilized to determine the weight of each criterion when generatingthe performance model for manufacturing systems.
4.2 AHP and ANP in the construction industryAHP has been often used in the construction industry for technical assessment,construction safety, project evaluation, project risk analysis, and intelligent buildingdesign evaluation. For instance, Dikmen and Birgonul (2006) used the AHP method forassessment of the risk involved in international projects. International project, riskassessment, is a complicated task because of the sensitivity of project success related tocountry-specific risks as well as project risks. Teo and Ling (2006) proposed a model
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describing the development and testing of a model used to calculate the ConstructionSafety Index and an accompanying set of tools that can be used to audit theeffectiveness of a construction firm’s safety management system. A list of 590attributes useful in assessment of construction safety was identified, and the methodused to determine the first and second level weights using the AHP procedure wasdescribed. The five-point Likert scale was used to determine the importance weights oflower level attributes. Chen and Liu (2007) presented a new methodology based onAHP and the fuzzy Delphi method (FDM) for assessing rock mass rating. This researchtreats rock mass classification as a group decision problem, and applies the fuzzy logictheory as the criterion for calculating the weighting of factors.
Wong and Li (2008) applied AHP in multi-criteria for analysis of the selection ofintelligent building systems (IB). They designed two surveys, a general survey, and anAHP survey, to achieve the objectives. The first general survey aimed to collect generalviews from intelligent building experts and practitioners to identify the perceivedcritical selection criteria, while the AHP survey was conducted to prioritize and assignthe important weightings for the perceived criteria in the general survey. The studycontributes to the industry and IB research in at least two aspects. First, it widens theunderstanding of selection criteria as well as the degree of importance for the IBsystems. It also adopts multi-criteria AHP approach, which is a new method used toanalyze and select building systems in IB. Wong et al. (2008a, b) developed two othermodels to evaluate the system intelligence of intelligent building systems. AHP andANP were employed in those studies, to evaluate the system intelligence of the IB. AHPwas utilized, to determine the relative importance, of the intelligence attributes, andindicators in the model, while ANP was employed to examine the interdependencebetween the intelligent attributes, and operational benefits of the IB. Wang et al. (2008)studied bridge risk assessment, as a MCDM problem, which involves multipleassessment criteria, such as safety, functionality, and sustainability. Of the MCDMapproaches, the AHP method can only compare a very limited number of decisionalternatives. The pairwise comparison approach is obviously infeasible in thissituation. To overcome this difficulty, they combine the AHP with DEA and proposean integrated AHP-DEA methodology in their paper.
4.3 AHP in power and energy industriesDey (2006) used AHP to develop a decision support system (DSS) for project evaluationand selection. The model has been developed with the active involvement of projectparticipants. The article explains the entire methodology through a case study of thecross-India petroleum pipeline. Shin et al. (2007) applied the AHP process to evaluationof national nuclear research and development projects in Korea. Also in Korea, Lee et al.(2007) used the AHP method to develop a scientific and rational assessment model fordemand-side management investment programs (DSMIPs) in the areas of natural gasand district heating. Demand-side management (DSM) is the process of managing theconsumption of energy to optimize available and planned generation resources, andDSMIPs are the actions conducted by energy suppliers to promote investment.
Garcia et al. (2008) presented a model developed to evaluate the DynamicAdaptation of an Electric Energy Distribution System with respect to planning for agiven period of Tariff Control. The model is based on a two-stage strategy that dealswith the mid/short-term and long-term planning, respectively. The starting point for
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modeling is selected by the results from a multi-attribute method based on FuzzyDynamic Programming and AHP for a mid/short-term horizon. Lee et al. (2008) studiedthe potential for Korea to be competitive in development of hydrogen energytechnology using the AHP approach, in which they tabulated Korea’s competitiveposition compared with other countries.
Chatzimouratidis and Pilavachi (2007) evaluated the impact of non-radioactiveemissions in the most commonly used types of power plants using AHP to synthesizeobjective and subjective criteria. Sensitivity analysis was used in order to examine howa change of input data affects the final results. Finally, ten main types of power plantswere evaluated according to the level and type of emissions released. In another study,Chatzimouratidis and Pilavachi (2009a) studied types of power plants and presented asensitivity analysis comprised of four alternative scenarios. Before applying sensitivityanalysis, the reference scenario is presented and an overall ranking is carried outaccording to this scenario. The sensitivity analysis describes alterations of scores andrankings according to variations of criteria weights with regard to this scenario.Karger and Hennings (2009) investigated the advantages and disadvantages ofdecentralized electricity generation according to the overall concept of sustainabledevelopment on the basis of a hierarchically structured set of sustainability criteria. Byapplying an expanded AHP, a multi-criteria evaluation is conducted that identifiesdissent among the experts. The results demonstrate that decentralized electricitygeneration can contribute to climate protection. The extent to which it simultaneouslyguarantees security of supply is still a matter of controversy.
4.4 AHP and ANP in the transportation industryAmong all of the industries, transport is the sector with the fastest growth ofgreenhouse gases emissions, both in developed and in developing countries. AHP hasbeen utilized to conduct studies on improving ship registry, passenger security checksin airports, port security, and transportation investments.
Tsai and Su (2005) conducted a study of the political risk assessment process anddesigned a case study of business environment evaluations of five East Asian portsunder political influences, including Hong Kong, Singapore, Busan, Kaohsiung, andShangha. This system approach consists of political risk factor identification, riskmeasurement, and assessment processes using the three methods of Delphi, AHP, andWard’s clustering. A total of 15 high-ranking managers from five leading globalcarriers presented their viewpoints for analysis. It was concluded that the residualrisks resulting from port development and management policies were considered to bemore significant than the risks from the integrated political and economical conditions.
Tudela et al. (2006) compared the output of cost-benefit and multi-criteria analysesby considering an application to urban transport investments. A main conclusion fromthese results is that the decision-making process needs to formally incorporate otheraspects, apart from the economic ones. Furthermore, public opinion should be takeninto account, explicitly into the decision-making, particularly when informationregarding the projects that will affect them can be provided by the authority in anaccurately and timely fashion. In transportation investment studies, Caliskan (2006)applied decision-making methods such as the cognitive map and AHP. The cognitivemap is a process based on a chain of interviews held with transportation experts. Thedata obtained from the cognitive map were utilized to determine the fundamental and
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sub-criteria, and then an AHP model was established. Yoo and Choi (2006) used theAHP approach for identifying important factors to improve passenger security checksat airports. The researchers prepared a survey questionnaire to gather data fromexperienced screeners and supervisors working at screening points around the airport.The gathered data was analyzed by using the AHP methodology to formulate a model.
Kandakoglu et al. (2009) proposed a structured multi-methodological approachbased on the systematic application of SWOT analysis, AHP, and TOPSIS methods tosupport the critical decision process of shipping registry selection. Park et al. (2009)applied AHP to evaluate the competitiveness of air cargo express services. Theyexplored the relative importance of factors that influence the adoption of an air expressdelivery service, and evaluated the competitiveness of air cargo express carriers in theKorean market. They reported that AHP analysis shows that accuracy and promptnessare the two most influential factors for competitiveness, and that DHL is mostcompetitive in the Korean market, followed by FedEx, TNT, EMS, and UPS.
Chang et al. (2009) used ANP priorities with applied fuzzy delphi, and zero-one goalprogramming for revitalization strategies in a case study of the Alishan ForestRailway for the solution of real-world, multi-criteria revitalization strategies. Theproposed ANP model consists of a control hierarchy and a network of connectionsbetween clusters of alternatives, factors, and criteria.
4.5 AHP in healthIn medical and healthcare studies, AHP method was mostly used for cost/benefitanalysis, hospital location selection, nutrition, risk assessment, and rehabilitationproblems.
Hummel et al. (2005) applied the AHP to support evaluation by a rehabilitation teamof the performance of two treatment options designed to improve arm-hand function insubjects with sixth cervical vertebra (C6) level Motor Group 2: tetraplegia. AHP wasused by the rehabilitation team, and potential recipients, to quantitatively compare anew technology, Functional Electrical Stimulation (FES), with conventional surgery.Performance was measured by functional improvement, treatment load, risks,user-friendliness, and social outcomes. Functional improvement after FES wasconsidered better than that after conventional surgery. However, the rehabilitationteam’s overall rating for conventional surgery was slightly higher than that for FES (57per cent vs 44 per cent). As compared to the rehabilitation team, potential recipientsgave greater weight to burden of treatment and less weight to functional improvement.The study showed that evaluation of new technology must be more comprehensivethan evaluation of functional improvement alone, and that patient preferences maydiffer from those of the rehabilitation team. Cieslik et al. (2006) studied the process ofpolyphenol supplied to human organisms from fruit and vegetables. On this basis,plant raw materials that supply polyphenols to the organism to the greatest extent (andthus contribute to an improvement in health of people in Poland) were identified.
Wu et al. (2007) used AHP for a hospital location, selection problem. The subjectivefactor was measured using AHP. Throughout the analysis, the various criteria andsub-criteria were identified while considering optimal selection of location to ensure acompetitive advantage as a means of setting up hospitals. A detailed sensitivityanalysis was performed to identify the variation in behavior of the alternatives.
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Hsu et al. (2008b) used AHP to select medical disposal companies based on theresults of interviews with experts in the field, thus reducing overhead costs andenhancing medical waste management in order to efficiently dispose of large amountsof medical waste to ensure sanitation and personal hygiene; doing so efficientlyreduces potential environmental hazards and decreases operational expenses.However, hospitals lack objective criteria to select the most appropriate wastedisposal firm and evaluate performance, instead relying on their own subjectivejudgments and previous experiences. An appropriate weight criterion based on AHPwas derived to assess the effectiveness of a medical waste disposal firm’squalifications, a contractor’s service capability and equipment, and economic factors.
Baykasoglu et al. (2009) carried out a case study to evaluate cost and benefits ofgowns and drapes, used in considerable amounts at a hospital. The aim was to form abasis for making effective selection decisions between disposable and reusableproducts. The literature was reviewed, and interviews were conducted with doctors,finance personnel, and the administrators of the hospital to determine the factorsassociated with gown and drape use. AHP was used as the main instrument indeveloping the cost/benefit analysis model. They concluded that single-use productswere very strong in terms of benefits, but their costs were still expensive as areplacement for reusable products. If the cost of single-use products was reduced bysome technological advancement in production as well as in distribution, theseproducts would gain a very competitive position in the gown and drape market. Thiswould lead to better infection control in the hospitals.
5. ConclusionThis study aims to present a detailed literature review of the recent applications ofAHP and ANP during the years 2005-2009. Prior AHP related literature review studiescovered different time periods and not considered ANP methodology. In their study,Omkarprasad and Sushil (2006) predicted that the use of AHP as a decision supporttool would keep increasing worldwide. Our study supports the accuracy of thisprediction. During the years 2005-2009, the use of the AHP technique has continued toincrease exponentially. In this study, country and geographical-based classificationswere used to demonstrate the widespread use of the method. AHP has been used as amanagerial decision tool in many industries for strategy evaluation, performanceassessment, product and process design, risk evaluation, system selection, cost/benefitanalysis, quality evaluation, and measurement of objectives.
During the years 2005-2009, applications of AHP have been dominant inmanufacturing, followed by the environmental management and agriculture field,power and energy industry, transportation industry, construction industry, andhealthcare. Other remarkable application fields include education, logistics, e-business,IT, R&D, telecommunication industry, finance and banking, urban management,defense industry and military, politics, government, marketing, tourism and leisure,sport, archaeology, auditing, and the mining industry. Supplier selection, supply chainevaluation, location selection, system selection or evaluation, and strategy evaluationare the most common problems solved in manufacturing. AHP is used in theconstruction industry for technical assessment, construction safety, project evaluation,project risk analysis and intelligent building design evaluation. In the transportationindustry, AHP has been utilized to conduct studies in improving ship registry,
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passenger security checks in airports, port security, and transportation investments.Also AHP methodology has been becoming increasingly important tool in differentdecision-making situations in education. It has been used for measurement ofuniversity objectives, dean selection, electronic library performance evaluation,optimum selection of educational materials, university design, and web-basede-learning system evaluation. It is assumed that AHP will continue to be used as aneffective decision method in education sector.
With increasing governmental emphasis on preventive health initiatives in theworld, a wide use of decision-making techniques is expected in the public health area.Moreover, the internationally recognized urgency of the need for renewable energy andsmart grid initiatives is a sure bet to create a surge in the number of decision-makingarticles published in the coming years.
Even though the widespread use of the method demonstrates that AHP is still apowerful decision tool for assisting managers in many decision situations, AHP doesnot take into account dependencies and interrelations among factors. However, realworld problems usually consist of dependence or feedback between elements.Compared to AHP, the ANP methodology makes it possible to consider all kinds ofdependence and feedback in the decision problem. For this reason, the ANP method isbetter to provide a flexible model to solve real world situations as compared to the AHPmethod. It is thus expected that ANP will gain more popularity in the future, as thebenefits of ANP become better understood. Especially in developed countries, it isexpected that ANP will be used predominantly.
Furthermore, in Ho’s study (2008), it was estimated that the growth in the use ofintegrated AHP methodologies would continue in the coming years. Our studyexpressly reports the accuracy of this foresight. It was observed that besides the use ofAHP as a stand-alone method, researchers have been continuing to use a combinationof AHP with other decision-making techniques. During the years 2005-2009, simulationhas been the most frequently used integrated method, followed by TOPSIS and GIS.Other significant tools that are commonly combined with AHP have been goalprogramming, DEA, Delphi method, balanced scorecard, factor analysis, fuzzy logicmodel, genetic algorithm, and SWOT analysis. Simulation is an effective methodology,in that it examines the uncertainty in AHP and helps to reduce the uncertainty to someextent. Regarding the growing use of the AHP-Simulation models, it is expected thatthis trend will keep continuing in the coming years.
AHP and ANP have been applied in a wide variety of areas as a useful and practicalmulti-criteria decision-making tool. However, in this study, it was also observed asignificant number of studies related to Fuzzy AHP. Country-based classificationsreported that the use of the fuzzy AHP methodology has been rising especially inTaiwan and Turkey. Even though the use of the fuzzy AHP methodology is rising insome regions, the accuracy of the fuzzy approach in AHP or ANP has been stronglycriticized by authorities (Saaty, 2006). Therefore the authors presume that in thecontext of better decision-making, the implementation of the Fuzzy AHP, would beflawed by experts, in the future.
It is hoped that this study can be used by managers, and academics as a foundationfor further research, help practitioners to make better decisions by the use of thesetechniques, and guide scholars towards advancement of these methodologies.
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Chougule, R.G. and Ravi, B. (2005), “Variant process planning of castings using AHP-basednearest neighbour algorithm for case retrieval”, International Journal of ProductionResearch, Vol. 43 No. 6, pp. 1255-73.
Chung, E. and Lee, K.S. (2009), “Prioritization of water management for sustainability usinghydrologic simulation model and multi-criteria decision making techniques”, Journal ofEnvironmental Management, Vol. 90 No. 3, pp. 1502-11.
Cicone, D. et al., (2008), “Functionality of the approach of hierarchical analysis in the full costaccounting in the IRP of a metropolitan airport”, Energy Policy, Vol. 36 No. 3, pp. 991-8.
Cieslik, E. et al., (2006), “Contents of polyphenols in fruit and vegetables”, Food Chemistry, Vol. 94No. 1, pp. 135-42.
Cooper, J.R. and Qiu, F. (2006), “Expediting and standardizing stone artifact refitting using acomputerized suitability model”, Journal of Archaeological Science, Vol. 33 No. 7,pp. 987-98.
Cortes-Aldana, F.A. et al., (2009), “University objectives and socioeconomic results: amulti-criteria measuring of alignment”, European Journal of Operational Research,Vol. 199 No. 3, pp. 811-22.
Dagdeviren, M. et al., (2009), “Weapon selection using the AHP and TOPSIS methods underfuzzy environment”, Expert Systems with Applications, Vol. 36 No. 4, pp. 8143-51.
Dagdeviren, M. and Yuksel, I. (2008), “Developing a fuzzy analytic hierarchy process (AHP)model for behavior-based safety management”, Information Sciences, Vol. 178 No. 6,pp. 1717-33.
Demirtas, E.A. and Ustun, O. (2009), “Analytic network process and multi-period goalprogramming integration in purchasing decisions”, Computers & Industrial Engineering,Vol. 56 No. 2, pp. 677-90.
Dey, P.K. (2006), “Integrated project evaluation and selection using multiple-attributedecision-making technique”, International Journal of Production Economics, Vol. 103No. 1, pp. 90-103.
Dey, P.K. and Ramcharan, E.K. (2008), “Analytic hierarchy process helps select site for limestonequarry expansion in Barbados”, Journal of Environmental Management, Vol. 88 No. 4,pp. 1384-95.
Diamantopoulos, N.K. (2007), “Managerial assessments of export performance: conceptualframework and empirical illustration”, Journal of International Marketing, Vol. 15 No. 3,pp. 1-31.
Dikmen, I. and Birgonul, M.T. (2006), “An analytic hierarchy process based model for risk andopportunity assessment of international construction projects”, Canadian Journal of CivilEngineering, Vol. 33 No. 1, pp. 58-68.
Erensal, Y.C. et al., (2006), “Determining key capabilities in technology management using fuzzyanalytic hierarchy process: a case study of Turkey”, Information Sciences, Vol. 176 No. 18,pp. 2755-70.
Erol, I. et al., (2009), “Sustainability in the Turkish retailing industry”, Sustainable Development,Vol. 17 No. 1, pp. 49-67.
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Ertay, T. et al., (2006), “Integrating data envelopment analysis and analytic hierarchy for thefacility layout design in manufacturing systems”, Information Sciences, Vol. 176 No. 3,pp. 237-62.
Ertugrul, I. and Karakasoglu, N. (2009), “Performance evaluation of Turkish cement firms withfuzzy analytic hierarchy process and TOPSIS methods”, Expert Systems with Applications,Vol. 36 No. 1, pp. 702-15.
Firouzabadi, A.K. et al., (2008), “A multiple stakeholders’ approach to strategic selectiondecisions”, Computers & Industrial Engineering, Vol. 54 No. 4, pp. 851-65.
Gabriel, S.A. et al., (2006), “A multiobjective optimization model for project selection withprobabilistic considerations”, Socio-Economic Planning Sciences, Vol. 40 No. 4, pp. 297-313.
Garcia, E. et al., (2008), “A new model to evaluate the dynamic adaptation of an electricdistribution system”, Energy Economics, Vol. 30 No. 4, pp. 1648-58.
Garcia-Cascales, M.S. and Lamata, M.T. (2009), “Selection of a cleaning system for enginemaintenance based on the analytic hierarchy process”, Computers & IndustrialEngineering, Vol. 56 No. 4, pp. 1442-51.
Gerdsri, N. and Kocaoglu, D.F. (2007), “Applying the analytic hierarchy process (AHP) to build astrategic framework for technology roadmapping”, Mathematical and ComputerModelling, Vol. 46 Nos 7-8, pp. 1071-80.
Gibney, R. and Shang, J. (2007), “Decision making in academia: a case of the dean selectionprocess”, Mathematical and Computer Modelling, Vol. 46 Nos 7/8, pp. 1030-40.
Giokas, D.I. and Pentzaropoulos, G.C. (2008), “Efficiency ranking of the OECD member states inthe area of telecommunications: a composite AHP/DEA study”, TelecommunicationsPolicy, Vol. 32 Nos 9-10, pp. 672-85.
Gol, H. and Catay, B. (2007), “Third-party logistics provider selection: insights from a Turkishautomotive company”, Supply Chain Management, Vol. 12 No. 6, pp. 379-84.
Golec, A. and Taskin, H. (2007), “Novel methodologies and a comparative study formanufacturing systems performance evaluations”, Information Sciences, Vol. 177 No. 23,pp. 5253-74.
Hafeez, K. et al., (2007), “Outsourcing non-core assets and competences of a firm using analytichierarchy process”, Computers & Operations Research, Vol. 34 No. 12, pp. 3592-608.
Ho, W. (2008), “Integrated analytic hierarchy process and its applications: a literature review”,European Journal of Operational Research, Vol. 186 No. 1, pp. 211-28.
Ho, W. and Emrouznejad, A. (2009), “Multi-criteria logistics distribution network design usingSAS/OR, part 2”, Expert Systems with Applications, Vol. 36 No. 3, pp. 7288-98.
Hsieh, L. et al., (2006), “Performance evaluation for university electronic libraries in Taiwan”, TheElectronic Library, Vol. 24 No. 2, pp. 212-24.
Hsu, P. et al., (2008a), “Optimizing resource-based allocation for senior citizen housing to ensure acompetitive advantage using the analytic hierarchy process”, Building and Environment,Vol. 43 No. 1, pp. 90-7.
Hsu, P. et al., (2008b), “Selection of infectious medical waste disposal firms by using the analytichierarchy process and sensitivity analysis”,Waste Management, Vol. 28 No. 8, pp. 1386-94.
Hsu, S.H. et al., (2009), “Design facial appearance for roles in video games, part 1”, Expert Systemswith Applications, Vol. 36 No. 3, pp. 4929-34.
Hsu, T. and Pan, F.F.C. (2009), “Application of Monte Carlo AHP in ranking dental qualityattributes, part 1”, Expert Systems with Applications, Vol. 36 No. 2, pp. 2310-6.
AHP and ANP:an overview of
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Hu, A.H. et al., (2009), “Risk evaluation of green components to hazardous substance usingFMEA and FAHP, part 2”, Expert Systems with Applications, Vol. 36 No. 3, pp. 7142-7.
Hu, H. et al., (2008), “Automated management and evaluation system for community healthservice”, Kybernetes, Vol. 37 Nos 9/10, pp. 1359-66.
Huang, C. et al., (2008), “A fuzzy AHP application in government-sponsored R&D projectselection”, Omega, Vol. 36 No. 6, pp. 1038-52.
Huang, H. (2009), “Designing a knowledge-based system for strategic planning: a balancedscorecard perspective”, Expert Systems with Applications, Vol. 36 No. 1, pp. 209-18.
Huang, L. et al., (2009), “What kind of marketing distribution mix can maximize revenues: thewholesaler travel agencies’ perspective?”, Tourism Management, Vol. 30 No. 5, pp. 733-9.
Huang, Y. and Bian, L. (2009), “A Bayesian network and analytic hierarchy process basedpersonalized recommendations for tourist attractions over the internet”, Expert Systemswith Applications, Vol. 36 No. 1, pp. 933-43.
Hughes, W.R. (2009), “A statistical framework for strategic decision making with AHP:probability assessment and Bayesian revision”, Omega, Vol. 37 No. 2, pp. 463-70.
Hummel, J.M.M. et al., (2005), “A multi-criteria decision analysis of augmentative treatment ofupper limbs in persons with tetraplegia”, Journal of Rehabilitation Research andDevelopment, Vol. 42 No. 5, pp. 635-44.
Hwang, H.S. et al., (2007), “Web-based multi-attribute analysis model for make-or-buy decisions”,Mathematical and Computer Modelling, Vol. 46 Nos 7-8, pp. 1081-90.
Isiklar, G. and Buyukozkan, G. (2007), “Using a multi-criteria decision making approach toevaluate mobile phone alternatives”, Computer Standards & Interfaces, Vol. 29 No. 2,pp. 265-74.
Islam, R. (2007), “MBNQA criteria in education: assigning weights from a Malaysian perspectiveand proposition for an alternative evaluation scheme”, International Transactions inOperational Research, Vol. 14 No. 5, pp. 373-94.
Ismayilova, N.A. et al., (2007), “A multi-objective faculty-course-time slot assignment problemwith preferences”, Mathematical and Computer Modeling, Vol. 46 Nos 7-8, pp. 1017-29.
Kahraman, C. et al., (2006), “A fuzzy optimization model for QFD planning process using analyticnetwork approach”, European Journal of Operational Research, Vol. 171 No. 2, pp. 390-411.
Kahraman, C. et al., (2007), “Prioritization of e-government strategies using a SWOT-AHPanalysis: the case of Turkey”, European Journal of Information Systems, Vol. 16 No. 3,pp. 284-98.
Kandakoglu, A. et al., (2009), “A multi-methodological approach for shipping registry selection inmaritime transportation industry”, Mathematical and Computer Modelling, Vol. 49 Nos3-4, pp. 586-97.
Kang, H. and Lee, A.H.I. (2007), “Priority mix planning for semiconductor fabrication by fuzzyAHP ranking”, Expert Systems with Applications, Vol. 32 No. 2, pp. 560-70.
Karami, E. (2006), “Appropriateness of farmers’ adoption of irrigation methods: the application ofthe AHP model”, Agricultural Systems, Vol. 87 No. 1, pp. 101-19.
Karger, C.R. and Hennings, W. (2009), “Sustainability evaluation of decentralized electricitygeneration”, Renewable and Sustainable Energy Reviews, Vol. 13 No. 3, pp. 583-93.
Kayakutlu, G. and Buyukozkan, G. (2008), “Assessing knowledge-based resources in a utilitycompany: identify and prioritise the balancing factors”, Energy, Vol. 33 No. 7, pp. 1027-37.
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Kengpol, A. (2008), “Design of a decision support system to evaluate logistics distributionnetwork in Greater Mekong sub-region countries”, International Journal of ProductionEconomics, Vol. 115 No. 2, pp. 388-99.
Khorramshahgol, R. and Djavanshir, G.R. (2008), “The application of analytic hierarchy processto determine proportionality constant of the taguchi quality loss function”, IEEETransactions on Engineering Management, Vol. 55 No. 2, pp. 340-8.
Kim, S. et al., (2005), “Development of a housing performance evaluation model for multi-familyresidential buildings in Korea”, Building and Environment, Vol. 40 No. 8, pp. 1103-16.
Kinra, A. and Kotzab, H. (2008), “A macro-institutional perspective on supply chainenvironmental complexity”, International Journal of Production Economics, Vol. 115No. 2, pp. 283-95.
Korhonen, P. et al., (2006), “A financial alliance compromise between executives and supervisoryauthorities”, European Journal of Operational Research, Vol. 175 No. 2, pp. 1300-10.
Korhonen, P. and Voutilainen, R. (2006), “Finding the most preferred alliance structure betweenbanks and insurance companies”, European Journal of Operational Research, Vol. 175No. 2, pp. 1285-99.
Korkmaz, I. (2008), “An analytic hierarchy process and two-sided matching based decisionsupport system for military personnel assignment”, Information Sciences, Vol. 178 No. 14,pp. 2915-27.
Korpela, J. et al., (2007), “Warehouse operator selection by combining AHP and DEAmethodologies”, International Journal of Production Economics, Vol. 108 Nos 1/2,pp. 135-42.
Krajnc, D. and Glavic, P. (2005), “How to compare companies on relevant dimensions ofsustainability”, Ecological Economics, Vol. 55 No. 4, pp. 551-63.
Kreng, V.B. and Wu, C. (2007), “Evaluation of knowledge portal development tools using a fuzzyAHP approach: the case of Taiwanese stone industry”, European Journal of OperationalResearch, Vol. 176 No. 3, pp. 1795-810.
Kulak, O. and Kahraman, C. (2005), “Fuzzy multi-attribute selection among transportationcompanies using axiomatic design and analytic hierarchy process”, Information Sciences,Vol. 170 Nos 2/4, pp. 191-210.
Kull, T.J. and Talluri, S. (2008), “A supply risk reduction model using integrated multi-criteriadecision making”, IEEE Transactions on Engineering Management, Vol. 55 No. 3,pp. 409-19.
Kuo, Y. and Chen, P. (2006), “Selection of mobile value-added services for system operators usingfuzzy synthetic evaluation”, Expert Systems with Applications, Vol. 30 No. 4, pp. 612-20.
Kuo, Y. et al., (2008), “Using simulation and multi-criteria methods to provide robust solutions todispatching problems in a flow shop with multiple processors”, Mathematics andComputers in Simulation, Vol. 78 No. 1, pp. 40-56.
Kwak, N.K. et al., (2005), “An MCDM model for media selection in the dual consumer/industrialmarket”, European Journal of Operational Research, Vol. 166 No. 1, pp. 255-65.
Lai, W. and Tsai, C. (2009), “Fuzzy rule-based analysis of firm’s technology transfer in Taiwan’smachinery industry”, Expert Systems with Applications, Vol. 36 No. 10, pp. 12012-22.
Lam, P. and Chin, K. (2005), “Identifying and prioritizing critical success factors for conflictmanagement in collaborative new product development”, Industrial MarketingManagement, Vol. 34 No. 8, pp. 761-72.
AHP and ANP:an overview of
applications
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Lee, A.H.I. (2009), “A fuzzy supplier selection model with the consideration of benefits,opportunities, costs and risks, part 2”, Expert Systems with Applications, Vol. 36 No. 2,pp. 2879-93.
Lee, A.H.I. et al., (2008), “A fuzzy AHP and BSC approach for evaluating performance of ITdepartment in the manufacturing industry in Taiwan”, Expert Systems with Applications,Vol. 34 No. 1, pp. 96-107.
Lee, A.H.I. et al., (2009a), “A green supplier selection model for high-tech industry”, ExpertSystems with Applications, Vol. 36 No. 4, pp. 7917-27.
Lee, A.H.I. et al., (2009b), “Fuzzy multiple goal programming applied to TFT-LCD supplierselection by downstream manufacturers, part 2”, Expert Systems with Applications, Vol. 36No. 3, pp. 6318-25.
Lee, D.K. et al., (2007), “Development of assessment model for demand-side managementinvestment programs in Korea”, Energy Policy, Vol. 35 No. 11, pp. 5585-90.
Lee, G.K.L. and Chan, E.H.W. (2008), “The analytic hierarchy process (AHP) approach forassessment of urban renewal proposals”, Social Indicators Research, Vol. 89 No. 1,pp. 155-68.
Lee, S.K. et al., (2008), “The competitiveness of Korea as a developer of hydrogen energytechnology: the AHP approach”, Energy Policy, Vol. 36 No. 4, pp. 1284-91.
Lee, Y. and Kozar, K.A. (2006), “Investigating the effect of web site quality on e-business success:an analytic hierarchy process (AHP) approach”, Decision Support Systems, Vol. 42 No. 3,pp. 1383-401.
Leung, L.C. et al., (2006), “Implementing the balanced scorecard using the analytic hierarchyprocess and the analytic network process”, The Journal of the Operational ResearchSociety, Vol. 57 No. 6, pp. 682-91.
Levary, R.R. (2007), “Ranking foreign suppliers based on supply risk”, Supply ChainManagement, Vol. 12 No. 6, pp. 392-4.
Levary, R.R. (2008), “Using the analytic hierarchy process to rank foreign suppliers based onsupply risks”, Computers & Industrial Engineering, Vol. 55 No. 2, pp. 535-42.
Li, J. et al., (2008), “A multi-objective fuzzy graph approach for modular formulation consideringend-of-life issues”, International Journal of Production Research, Vol. 46 No. 14, pp. 4011-33.
Li, S. and Li, J.Z. (2009), “Hybridising human judgment, AHP, simulation and a fuzzy expertsystem for strategy formulation under uncertainty, part 1”, Expert Systems withApplications, Vol. 36 No. 3, pp. 5557-64.
Liang, Z. et al., (2006), “Decision support for choice optimal power generation projects: fuzzycomprehensive evaluation model based on the electricity market”, Energy Policy, Vol. 34No. 17, pp. 3359-64.
Liao, S. and Chang, K. (2009), “Select televised sportscasters for Olympic Games by analyticnetwork process”, Management Decision, Vol. 47 No. 1, pp. 14-23.
Liberatore, M.J. and Nydick, R.L. (2008), “The analytic hierarchy process in medical and healthcare decision making: a literature review”, European Journal of Operational Research,Vol. 189 No. 1, pp. 194-207.
Lin, C. and Hsu, M. (2007), “A GDSS for ranking a firm’s core capability strategies”, The Journalof Computer Information Systems, Vol. 47 No. 4, pp. 111-30.
Lin, C. and Juan, P. (2009), “Developing a hierarchy relation with an expert decision analysisprocess for selecting the optimal resort type for a Taiwanese international resort park, part1”, Expert Systems with Applications, Vol. 36 No. 2, pp. 1706-19.
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Lin, H. et al., (2009), “Evaluation of factors influencing knowledge sharing based on a fuzzy AHPapproach”, Journal of Information Science, Vol. 35 No. 1, pp. 25-44.
Lin, L.C. (2009), “An integrated framework for the development of radio frequency identificationtechnology in the logistics and supply chain management”, Computers & IndustrialEngineering, Vol. 57 No. 3, pp. 832-42.
Liou, J.J.H. and Tzeng, G. (2007), “A non-additive model for evaluating airline service quality”,Journal of Air Transport Management, Vol. 13 No. 3, pp. 131-8.
Liu, F.F. and Hai, H.L. (2005), “The voting analytic hierarchy process method for selectingsupplier”, International Journal of Production Economics, Vol. 97 No. 3, pp. 308-17.
Liu, Y. and Chen, C. (2007), “A new approach for application of rock mass classification on rockslope stability assessment”, Engineering Geology, Vol. 89 Nos 1-2, pp. 129-43.
Ma, J. (2005), “Siting analysis of farm-based centralized anaerobic digester systems fordistributed generation using GIS”, Biomass and Bioenergy, Vol. 28 No. 6, pp. 591-600.
Ma, M. (2007), “A design decision-making support model for customized product colorcombination”, Computers in Industry, Vol. 58 No. 6, pp. 504-18.
Mansar, S.L. et al., (2009), “Development of a decision-making strategy to improve the efficiencyof BPR, part 2”, Expert Systems with Applications, Vol. 36 No. 2, pp. 3248-62.
Martinez-Olvera, C. (2008), “Methodology for realignment of supply-chain structural elements”,International Journal of Production Economics, Vol. 114 No. 2, pp. 714-22.
Masozera, M.K. et al., (2006), “Assessing the suitability of community-based management for theNyungwe Forest Reserve, Rwanda”, Forest Policy and Economics, Vol. 8 No. 2, pp. 206-16.
Michnik, J. and Lo, M. (2009), “The assessment of the information quality with the aid of multiplecriteria analysis”, European Journal of Operational Research, Vol. 195 No. 3, pp. 850-6.
Naesens, K. et al., (2009), “A swift response framework for measuring the strategic fit for ahorizontal collaborative initiative”, International Journal of Production Economics, Vol. 121No. 2, pp. 550-61.
Nagesha, N. and Balachandra, P. (2006), “Barriers to energy efficiency in small industry clusters:multi-criteria-based prioritization using the analytic hierarchy process”, Energy, Vol. 31No. 12, pp. 1969-83.
Naghadehi, M.Z. et al., (2009), “The application of fuzzy analytic hierarchy process (FAHP)approach to selection of optimum underground mining method for Jajarm Bauxite Mine,Iran”, Expert Systems with Applications, Vol. 36 No. 4, pp. 8218-26.
Nekhay, O. et al., (2009), “Spatial analysis of the suitability of olive plantations for wildlifehabitat restoration”, Computers and Electronics in Agriculture, Vol. 65 No. 1, pp. 49-64.
Ngai, E.W.T. and Chan, E.W.C. (2005), “Evaluation of knowledge management tools using AHP”,Expert Systems with Applications, Vol. 29 No. 4, pp. 889-99.
Niaraki, A.S. and Kim, K. (2009), “Ontology based personalized route planning system using amulti-criteria decision making approach, part 1”, Expert Systems with Applications, Vol. 36No. 2, pp. 2250-9.
Oconnor, T. and Kuyler, P. (2009), “Impact of land use on the biodiversity integrity of the moistsub-biome of the grassland biome, South Africa”, Journal of Environmental Management,Vol. 90 No. 1, pp. 384-95.
Oddershede, A. et al., (2007), “Rural development decision support using the analytic hierarchyprocess”, Mathematical and Computer Modelling, Vol. 46 Nos 7/8, pp. 1107-14.
AHP and ANP:an overview of
applications
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Okudan, G. (2006), “A multi-criteria decision-making methodology for optimum selection of asolid modeller for design teaching and practice”, Journal of Engineering Design, Vol. 17No. 2, pp. 159-75.
Omkarprasad, S.V. and Sushil, K. (2006), “Analytic hierarchy process: an overview ofapplications”, European Journal of Operational Research, Vol. 169 No. 1, pp. 1-29.
Ozgen, D. (2008), “A two-phase possibilistic linear programming methodology for multi-objectivesupplier evaluation and order allocation problems”, Information Sciences, Vol. 178 No. 2,pp. 485-500.
Paralikas, A.N. and Lygeros, A.I. (2005), “A multi-criteria and fuzzy logic based methodology forthe relative ranking of the fire hazard of chemical substances and installations”, ProcessSafety and Environmental Protection, Vol. 83 No. 2, pp. 122-34.
Park, S. and Rothrock, L. (2007), “Systematic analysis of framing bias in missile defense:implications toward visualization design”, European Journal of Operational Research,Vol. 182 No. 3, pp. 1383-98.
Park, Y. et al., (2009), “Evaluating competitiveness of air cargo express services”, TransportationResearch Part E: Logistics and Transportation Review, Vol. 45 No. 2, pp. 321-34.
Parra-Lopez, C. et al., (2008), “A systemic comparative assessment of the multifunctionalperformance of alternative olive systems in Spain within an AHP-extended framework”,Ecological Economics, Vol. 64 No. 4, pp. 820-34.
Partovi, F.Y. (2006), “An analytic model for location facilities strategically”,Omega, Vol. 34 No. 1,pp. 41-55.
Partovi, F.Y. (2007), “An analytical model of process choice in the chemical industry”,International Journal of Production Economics, Vol. 105 No. 1, pp. 213-27.
Peniwati, K. and Brenner, W. (2008), “Multi-decisions rating model: establishing rescue policiesfor regional drinking water companies (PDAMs) in Indonesia”, European Journal ofOperational Research, Vol. 186 No. 3, pp. 1127-36.
Peters, M.L. and Zelewski, S. (2007), “Assignment of employees to workplaces underconsideration of employee competences and preferences”, Management Research News,Vol. 30 No. 2, pp. 84-99.
Quintero, J. et al., (2008), “Fuel ethanol production from sugarcane and corn: comparativeanalysis for a Colombian case”, Energy, Vol. 33 No. 3, pp. 385-99.
Rabelo, L. et al., (2007), “Value chain analysis using hybrid simulation and AHP”, InternationalJournal of Production Economics, Vol. 105 No. 2, pp. 536-47.
Ravi, B. and Mukherjee, N.P. (2007), “Rapid tooling manufacturability evaluation usingfuzzy-AHP methodology”, International Journal of Production Research, Vol. 45 No. 5,pp. 1161-81.
Richman, M.B. (2005), “A novel computer based expert decision-making model for prostatecancer disease management”, The Journal of Urology, Vol. 174 No. 6, pp. 2310-8.
Saaty, T.L. (1990), “How to make a decision: the analytic hierarchy process”, European Journal ofOperational Research, Vol. 48 No. 1, pp. 9-26.
Saaty, T.L. (2001a), The Analytic Network Process, RWS Publications, Pittsburgh, PA.
Saaty, T.L. (2001b), Decision Making for Leaders, RWS Publications, Pittsburgh, PA.
Saaty, T.L. (2006), “There is no mathematical validity for using fuzzy number crunching in theanalytic hierarchy process”, Journal of Systems Science and Systems Engineering, Vol. 15No. 4, pp. 457-64.
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Saaty, T.L. and Vargas, L.G. (2001), Models, Methods, Concepts and Applications of the AnalyticHierarchy Process, Kluwer Academic Publishers, Boston, MA-Dordrecht-London.
Sale, R.S. and Sale, M.L. (2005), “Lending validity and consistency to performance measurement”,Managerial Auditing Journal, Vol. 20 Nos 8/9, pp. 915-27.
Sasmal, S. and Ramanjaneyulu, K. (2008), “Condition evaluation of existing reinforced concretebridges using fuzzy based analytic hierarchy approach”, Expert Systems with Applications,Vol. 35 No. 3, pp. 1430-43.
Scholl, A. et al., (2005), “Solving multiattribute design problems with analytic hierarchy processand conjoint analysis: an empirical comparison”, European Journal of OperationalResearch, Vol. 164 No. 3, pp. 760-77.
Secme, N.Y. et al., (2009), “Fuzzy performance evaluation in Turkish banking sector usinganalytic hierarchy process and TOPSIS”, Expert Systems with Applications, Vol. 36 No. 9,pp. 11699-709.
Sevkli, M. et al., (2007), “An application of data envelopment analytic hierarchy process forsupplier selection: a case study of BEKO in Turkey”, International Journal of ProductionResearch, Vol. 45 No. 9, pp. 1973-2003.
Sharma, S. and Agrawal, N. (2009), “Selection of a pull production control policy under differentdemand situations for a manufacturing system by AHP-algorithm”, Computers &Operations Research, Vol. 36 No. 5, pp. 1622-32.
Shee, D.Y. and Wang, Y. (2008), “Multi-criteria evaluation of the web-based e-learning system: amethodology based on learner satisfaction and its applications”, Computers & Education,Vol. 50 No. 3, pp. 894-905.
Shin, C. et al., (2007), “Applying the analytic hierarchy process to evaluation of the nationalnuclear R&D projects: the case of Korea”, Progress in Nuclear Energy, Vol. 49 No. 5,pp. 375-84.
Shin, T. et al., (2009), “The comparative evaluation of expanded national immunization policies inKorea using an analytic hierarchy process”, Vaccine, Vol. 27 No. 5, pp. 792-802.
Srdjevic, B. (2007), “Linking analytic hierarchy process and social choice methods to supportgroup decision-making in water management”, Decision Support Systems, Vol. 42 No. 4,pp. 2261-73.
Strager, M.P. and Rosenberger, R.S. (2006), “Incorporating stakeholder preferences for landconservation: weights and measures in spatial MCA”, Ecological Economics, Vol. 58 No. 1,pp. 79-92.
Su, C. and Chou, C. (2008), “A systematic methodology for the creation of Six Sigma projects: acase study of semiconductor foundry”, Expert Systems with Applications, Vol. 34 No. 4,pp. 2693-703.
Sueyoshi, T. et al., (2009), “A decision support framework for internal audit prioritization in arental car company: a combined use between DEA and AHP”, European Journal ofOperational Research, Vol. 199 No. 1, pp. 219-31.
Sun, C. et al., (2009), “The evaluation of cluster policy by fuzzy MCDM: empirical evidence fromHsinChu Science Park”, Expert Systems with Applications, Vol. 36 No. 9, pp. 11895-906.
Sun, Y. et al., (2007), “Syndicating web services: a QoS and user-driven approach”, DecisionSupport Systems, Vol. 43 No. 1, pp. 243-55.
Sun, Y. et al., (2008), “A group decision support approach to evaluate experts for R&D projectselection”, IEEE Transactions on Engineering Management, Vol. 55 No. 1, pp. 158-70.
AHP and ANP:an overview of
applications
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Teo, E.A.L. and Ling, F.Y.Y. (2006), “Developing a model to measure the effectiveness of safetymanagement systems of construction sites”, Building and Environment, Vol. 41 No. 11,pp. 1584-92.
Tiryaki, F. and Ahlatcioglu, B. (2009), “Fuzzy portfolio selection using fuzzy analytic hierarchyprocess”, Information Sciences, Vol. 179 Nos 1-2, pp. 53-69.
Tolga, E. (2005), “Operating system selection using fuzzy replacement analysis and analytichierarchy process”, International Journal of Production Economics, Vol. 97 No. 1,pp. 89-117.
Tsai, T. (2005), “Development of an integrated reflow soldering control system using incrementalhybrid process knowledge”, Expert Systems with Applications, Vol. 28 No. 4, pp. 681-92.
Tsai, W. and Hung, S. (2009), “Dynamic pricing and revenue management process in internetretailing under uncertainty: an integrated real options approach”, Omega, Vol. 37 No. 2,pp. 471-81.
Tsai, M. and Su, C.H. (2005), “Political risk assessment of five East Asian ports: the viewpoints ofglobal carriers”, Marine Policy, Vol. 29 No. 4, pp. 291-8.
Tseng, F. et al., (2009), “Measuring business performance in the high-tech manufacturingindustry: a case study of Taiwan’s large-sized TFT-LCD panel companies”,Omega, Vol. 37No. 3, pp. 686-97.
Tudela, A. et al., (2006), “Comparing the output of cost benefit and multi-criteria analysis: anapplication to urban transport investments”, Transportation Research Part A: Policy andPractice, Vol. 40 No. 5, pp. 414-23.
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Further reading
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About the authorsSeyhan Sipahi is an assistant professor of quantitative methods at School of Business, IstanbulUniversity. She earned her BS in Business Administration from the Istanbul University and herMA and PhD in quantitative methods from the Social Science Institute of the Istanbul University.Her PhD thesis was on “Ranking cities of Turkey by livability using analytic hierarchy process”.In 2007, she was visiting research scholar at Operations and Decision Technologies Departmentat Kelley School of Business, Indiana University. Her primary fields of research are spreadsheetmodeling, multi-attribute decision making in business, simulation optimization, andmanagement science applications in tourism and sport. She has several national andinternational articles published in reputed academic journals. She is associate editor of theJournal of the School of Business Administration, Istanbul University. She works for School ofBusiness Quantitative Methods Department since 1997.
Mehpare Timor is an associate professor of School of Business at Istanbul University. Sheearned her BS in Business Administration from the School of Business at Istanbul University, andher MS and PhD in Quantitative Methods Department, the Institute of Social Sciences at IstanbulUniversity. Her MS thesis was on “Computer aided assignment problem”, and PhD thesis was on“Lagrangean relaxation algorithm for optimal connection and flow costs on a computer networkmodel”. She has worked for the School of Business Quantitative Methods Department since 1987.Her primary fields of research are operations research algorithms, data envelopment analysis, datamining, multi-criteria decision-making and analytical hierarchy process. She has several nationaland international articles published in reputed academic journals, and she has written a book onOperations Research with Business Applications. Professor Timor is the area editor of EuropeanJournal of Pure and Applied Mathematics (EJPAM).
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