research article an evaluative study on the choice of...

Hindawi Publishing CorporationMathematical Problems in EngineeringVolume 2013 Article ID 430945 9 pageshttpdxdoiorg1011552013430945

Research ArticleAn Evaluative Study on the Choice ofRegional Strategic Emerging Industry Based on DEMATELHeilongjiang Province as an Example

Xiuying Guo12 Xiaofeng Hui1 and Junxiang Wang2

1 School of Management Harbin Institute of Technology Harbin Heilongjiang 150001 China2 College of Mathematics Heilongjiang Institute of Technology Harbin Heilongjiang 150050 China

Correspondence should be addressed to Xiuying Guo guoxiuying6163com

Received 29 March 2013 Accepted 22 May 2013

Academic Editor Tingwen Huang

Copyright copy 2013 Xiuying Guo 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

Currently the convergence of choosing regional strategic emerging industry is very serious in our country And affected by itsdevelopmental stage at present the research of themethodology for choosing and evaluating regional strategic emerging industry isnot verymature and lacks systematic and dynamic study By expanding the DEMATELmethod to the field of the complex weightednetwork comparing the regional industry to a dynamic system and establishing the DEMATEL improvedmodel based on industryinput-output table it is possible to realize the systematicness and dynamic nature of choosing regional strategy emerging industry

1 Introduction

Throughout the history the economic crisis will promotethe development of emerging industries every time and invarious countries around the world the emerging industriesare of strategic importance to deal with the financial crisisconstruct the new economical growth point and preemptthe development opportunities of the future In September2009 Premier Jiabao Wen presided over three forums aboutstrategic emerging industry development and ldquothe conceptof strategic emerging industryrdquo was proposed for the firsttime In October 2010 the State Council determined sevenindustries as strategic emerging industries in China energyconservation and environment protection new generation ofinformation technology biotechnology high-end equipmentmanufacturing new energy new materials and alternativefuel vehicles In March 2012 Premier Jiabao Wen empha-sized in the ldquogovernment work reportrdquo to further promotethe healthy development of strategic emerging industriespromoting the optimization and upgrading of industrialstructure [1]

At present strategic emerging industry has entered astage of deepening development which means as the core ofall levels of local government establishing regional strategic

emerging industries and overall promoting the upgrading ofregional industrial structure and then promoting the sustain-able development of social economy Due to the economicdevelopment level of various regions in China and resourceendowments have differences regional industrial structurehas its own characteristics and its industrial gradual progresshas obvious regional characteristics [2] Therefore regionalpractice must first be selected scientifically before regionalstrategic emerging industry will be developed At presentled by the planning of country strategic emerging industryproceeding from the separate condition advantage andcharacteristic the provinces (cities regions) of our countrypropose the strategic emerging industry planning during theperiod of ldquo12th Five-Year Planrdquo However after sorting outthe strategic emerging industry planning in thirty provinces(cities regions) of our country the author found that duringthe period of ldquo12th Five-Year Planrdquo the convergence in thechoice of the regional strategic emerging industries is veryserious as shown in Figure 1

The number of region selecting new material is twenty-nine the region selecting new energy is twenty-six thenumber of selecting biological is twenty-five these threeones are ranked as the top three The convergence in the

2 Mathematical Problems in Engineering

Nuc

lear

pow

er

IOT

indu

stry

Elec

troni

c inf

orm

atio

nin

dustr

y

Biop

harm

acy

indu

stry

Mar

ine e

cono

my

indu

stry

Aero

spac

e ind

ustr

y

New

-ene

rgy

auto

mob

ilein

dustr

y

New

mat

eria

l ind

ustr

y

New

ener

gy in

dustr

y

Hig

h-en

d eq

uipm

ent

man

ufac

turin

g

Bioi

ndus

try

Info

rmat

ion

indu

stry

Ener

gy-s

avin

g in

dustr

y

The m

oder

n fo

od in

dustr

y

30

25

20

15

10

5

0

The number of districts

Figure 1 Selected case charts of the strategic emerging industry inthirty provinces (cities) of our country

choice of the regional strategic emerging industries caneasily result in vicious competition redundant constructionwaste of resources and other issues of excess productioncapacity Regional strategic emerging industry is never asimple regional of the country strategic emerging industriesthe difference between the two is not only in amount butalso in quality Therefore how to accurately and scientificallyselect and evaluate the regional strategic emerging industrywill have important theoretical and practical meanings

At present many scholars are carrying on the theoreticaland empirical research of the strategic emerging industriesfirst Qiao and Yang [3] and Xiong and Zeng [4] establishedan evaluation system from the perspective of coupling theemerging industries and traditional industries Second He[5] Li [6] and Luo [7] and Hu et al [8] constructedthe choice model based on the Analytic Hierarchy Process(AHP) fuzzy comprehensive and the combination of ldquoAHP-IEmdashPCArdquo empowerment evaluation method Third Liu andCheng [9] and Liu [10] used comparative analysis to proposethe suggestion of choosing mechanism Forth Ao and Liu[11] come up with the choosing principle basic principle andseveral kinds of typical selective methods of the strategicemerging industry from the theoretical level

It is not difficult to see that scholars for regional strategicemerging industry choice mainly focused on the importanceof strategic emerging industry connotation and character-istic mechanism of formation and development selectionprinciple and cultivation measures discussion of theoryempirical research is mainly to have a set of strategic emerg-ing industries evaluation of each area method is selectionthe method of simple transplantation for leading industry

lacking regional strategic emerging industry choice and thechoice of system science method and evaluation system Asregional industrial system is a complicated dynamic systemand strategic emerging industry has strong correlation effectand characteristics of sustainable development this paperwill be based on the complicated network and input-outputtheory with the aid of DEMATEL improved model as anexample to Heilongjiang province regional strategic emerg-ing industry selection research andwill do dynamic gatheredqualitative research for selection result

2 The Choice of Regional StrategicEmerging Industry Based onthe Improved DEMATEL Model

21 Industrial Complex Network and the Introduction of theTheory of Input and Output Regional industrial systembeing the most complicated subsystem of national economicsystem construction must composite complex system theoryand macroeconomic quantity analysis to make overall plan-ning [12] Industrial system is mainly related to the input andoutput of the interindustry so with the help of the input andoutput theory we need the theory of input and output to studysome characteristics of the regional industrial system Input-output theory is founded by theHarvardUniversity professorWassily Leontief in 1936 and itmainly studies the quantitativeanalysis of the input-output interdependence relationshipof each part in the economic system This interindustryperplexing relationship of supply and demand generally issuccinctly explained by the input-output table

22 Based on DEMATEL Improved Model of the Input-OutputTable and Empirical Research DEMATEL is an analysismethod using graph theory and matrix tools for systemanalysis proposed by the American scholar Gabus andFontela By constructing the direct affect matrix betweensystem factors apply thematrix to calculate the center degreeand reason degree of each factor and then determine theimportance of various factors in the system This method ismore effective for dealing with complicated social economicproblems especially for the problem of unclear relationshipsof system factor [13] In recent years many scholars applyDEMATEL to study complex system Tzeng et al [14] useDEMATEL structure analysis method (AHP) and fuzzyintegral to construct a selection evaluation model of onlinelearning project Liang andMa [15] apply DEMATELmethodto analyze the foundation engineering construction risk Zhuand Yang [16] bring DEMATEL and entropy according to theautocorrelation of customersrsquo demand and the influence ofmarket competition evaluation to correct the basic importantfactor of the customersrsquo needs and integrate the processingresults of the two sides then we can get more objective finalimportant factor of the customersrsquo needs

On the basis of using DEMATEL method for referencethis paper extends the DEMATEL method to the weightedfield of complex network confirms network supportingmatrix using the improved DEMATEL method studies the

Mathematical Problems in Engineering 3

relations of every industrial department based on input-output matrix then determines the preselected strategicemerging industry whose centrality and reason degree arehigh The DEMATEL improved model based on complexnetwork is described as follows

Step 1 Generated standardized effect matrix119863

We regard every industrial department of the nationaleconomy as one point and regard input-output relationshipof each department as one border Take for example input-output table of 42 industry departments of Heilongjiangprovince in 2007 we regard each industry department as aninfluencing factor and regard the input and output valuesof every industrial departments as weighted interrelationbetween every factor 119886

119894119895 and get direct affect matrix 119860 =

(119886119894119895) (119894 119895 = 1 2 42) By setting up the table of 42

industrial departments corresponding to sequence numberas shown in Table 1 we represent the industry name withsequence number in the latter research

According to the direct affect matrix 119860 with the help of

119863 = 119904119860 (119904 gt 0) (1)

construct standardized affect matrix 119863 where 119889119894119895= 119904119886119894119895

(119894 119895 = 1 2 119873) and ldquo119878rdquo is called the scale factor 0 lt 119878 ltSup We usually make

Sup = max

1

max1le119894le119873

sum119873

119895=1

10038161003816100381610038161003816119886119894119895

10038161003816100381610038161003816

1

max1le119895le119873

sum119873

119894=1

10038161003816100381610038161003816119886119894119895

10038161003816100381610038161003816

(2)

According to (1) and (2) calculation methods we useMATLAB 71 to calculate the ratio factor of Heilongjiangprovince standardization impact matrix 119863 119904 = 765036819 +119864 minus 9 and get the standardized affect matrix119863

Step 2 Construct total impact matrix 119879

The sum of rows of matrix 119863 is called the outgoingdegree of 119894 industry which expresses the direct impact totalintensity of the industry 119894 as 119889out

119894= sum119873

119895=1119889119894119895 The sum of

columns of matrix 119863 column is called incoming degree ofindustry119895 which expresses the direct impact total intensity ofthe industry119895 as 119889in

119895= sum119873

119895=1119889119894119895 However for the actual issue

we not only consider the direct effect between the industriesbut we also need to consider the indirect effects betweenthe industries and the chain effects brought by an industrychangeThe total effectmatrix119879 expresses the comprehensivesummation of the direct and indirect effects between factorsin order to determine the final effect of each factor relative tothe highest level factor in the system That is

119879 = 119862 + 1198622+ sdot sdot sdot + 119862

119899= 119862119868 minus 119862119899minus1

119868 minus 119862 (3)

Since 0 le 119862119894119895le 1 so when 119899 rarr infin 119862119899minus1 rarr 0

119879 = 119862119868

119868 minus 119862= 119862(119868 minus 119862)

minus1 (4)

Table 1 The table of 42 industries of national economy in Hei-longjiang province corresponding to sequence number

Industrial sequencenumber Industry name

1 Agriculture forestry animal husbandryand fishery

2 Coal mining and coal washing industry3 Oil and natural gas industry4 Metal mines5 Nonselected industry

6 Food manufacturing and tobaccoprocessing

7 Textile crafts and others8 Textile leather and products industry

9 Wood processing and furnituremanufacturing industry

10 Paper printing and stationery and sportsgoods manufacturing industry

11 Petroleum processing coking andnuclear fuel processing

12 The chemical industry13 Nonmetallic mineral products industry

14 Metal smelting and rolling processingindustry

15 Metal products industry

16 General special equipmentmanufacturing industry

17 Transportation equipment manufacturing

18 Electrical machineryEquipment manufacturing industry in

19communications equipment computersand other electronic equipment metalmine and other mining manufacturing

20 instrumentations and culturesOffice machinery manufacturing industry

21 Manufacturing and others22 Waste

23 Electricity heat production and supplyindustry

24 Gas production and supply industry25 Water production and supply industry26 Construction27 Transportation and warehousing industry28 Postal industry

29 Information transmission computerservice and software industry

30 Wholesale and retail trade industry31 Accommodation and catering industry32 Finance and insurance industry33 Real estate34 Leasing and business services35 Tourism

36 Research and experimental developmentindustry

37 Integrated technology services38 Other social services39 Education40 Health social security and social welfare

41 Culture sports and entertainmentindustry

42 Public management and socialorganization


Table 2The table of 42 industries impacted degree in Heilongjiangprovince in 2007

Industrial serial number Impact degree1 0950712 0305223 099774 00952455 0041656 0421617 00371948 00358449 008707510 01141211 07139212 07518613 01319114 06753115 01303616 05862817 01566918 02329519 007938720 009546921 001787222 002586323 06633724 001413625 004638626 005934827 06221628 004989829 01126530 05290431 01365532 01821833 009651434 01540435 000893236 003167637 001457738 01287839 002105140 002970941 002736542 0001848

According to the formula in (4) after calculation we canget the total effect matrix 119879of 42 industries of Heilongjiangprovince in 2007

Step 3 Calculate the impacted degree matrix 119879119903and the

affected degree matrix 119879119888

The row sum and column sum of sum-impact matrix 119879are known as the impact matrix 119879

119903and the affected matrix

119879119888 thereinto

119879119903 (119894) =

119899

sum

119895=1

119905119894119895

119879119888(119895) =

119899

sum

119894=1

119905119894119895

(5)

By the formula in (5) we calculated the impact degreeof 42 industries of Heilongjiang province in Table 2 affecteddegree of 42 industries of Heilongjiang province in Table 3

Step 4 Calculate centrality degree matrix 119872 and reasondegree matrix 119877

The impact matrix 119879119903plus the affected matrix 119879

119888is the

centrality degree matrix119872 namely

119872 = 119879119903+ 119879119888 (6)

119872119894is the centrality degree of 119894th industry representing

the importance of 119894th industry in regional industrial systemnamely

119872119894= 119879119903 (119894) + 119879119888 (119894) (7)

The impacted matrix 119879119903minus the affected matrix 119879

119888is

the reason degree matrix 119877 namely

119877 = (119879119903minus 119879119888) (8)

119877119894is the reason degree of 119894th industry which represents

causes or results of 119894th industry in input-output process of theindustrial system factors namely

119877119894= 119879119903 (119894) minus 119879119888 (119894) (9)

If the reason degree 119877119894gt 0 then it shows that the 119894th

industry is more influential than other industries and theindustry 119894 is reason industry if the reason degree 119877

119894lt 0

then it shows that the 119894th industry is more affected than otherindustries and the industry 119894 is called the outcome industryBy the formula in (6) and (8) we calculate the top 10 industrialcentrality degrees in Table 4 and the reason degree table of thecorresponding industry in Table 5

Step 5 Draw industry cause-result diagram

First establish Descartes coordinate system by the cen-trality degree to be the abscissa and the reason degree to bethe ordinate Second mark the position of the industry inthe coordinate system in Figure 2Third choose the strategicemerging industry according to the centrality degree andreason degree to analyze the various roles of the industriesin the regional industry system and give some suggestions tothe actual industrial system


Table 3 The table of 42 industries affected degree in Heilongjiangprovince in 2007

Industrial serial number Affected degree1 105232 019893 027314 00147145 00210516 111577 00486828 00697629 01104110 00879111 08148712 05853613 01103914 01989315 007622416 05003817 02416818 01286619 001856220 002592321 001042822 000471823 05930124 001637325 003794926 1281527 04081228 005632329 007668930 0250431 0220532 007642733 01050634 01000735 002019436 002584537 003351538 01506739 01227340 01784241 002533842 012669

23 The Analysis of DEMATEL Results and the Suggestionof Strategic Emerging Industry Selection As Table 2 shows0001848 le 119879

119903(119894) le 09977 the expected value is 0228915

and the standard deviation is 0281140 Among these data

N(1)

N(2)

N(3)

N(6)

N(11)

N(12)

N(14)

N(16)

N(17)

N(18)N(23)

N(26)

N(27)N(30)

N(31)N(32)

N(40)

0 1 2

0

1

Centrality degree

Reas

on d

egre

e

minus15

minus1

minus05

15

05

05 25

Figure 2The cause-result diagram of 42 industries in Heilongjiangprovince

the largest impacted degree is oil and natural gas exploitationindustry followed by agriculture hunting and chemicalindustry We can see that the industry influenced degree ofHeilongjiang province is less than 1 but the standard devi-ation is relatively large which means Heilongjiang Provinceindustrial agglomeration level is low and the distribution ofindustries is scattered Agriculture and energy industries arethe two major industries of Heilongjiang province

As Table 3 shows 0004718 le 119879119888(119895) le 12815 the

expected value is 0228916 and the standard deviation is0315526 We can see that the standard deviation of indus-trial impacted degree is larger than the industrial affecteddegree that is to say the affected degree varies greatlyFoodmanufacturing and tobacco processing industry animalhusbandry and fishery are rounding out the top threeindustries impacted degree and they aremainly concentratedin primary industry and secondary industry

As Table 4 shows 00283 le 119872119894le 200301 Heilongjiang

provincersquos industry centrality degree is low lacking the coreindustry in region system The centrality degree industriessuch as agriculture hunting petroleum processing cokingand nuclear fuel processing transportation and warehous-ing industries are more larger and can be taken as thedevelopment base of strategic emerging industry for theircomprehensive influence in Heilongjiang province

As Table 5 shows the reason degrees of 24 industriesare positive values 0002027 le 119877

119894le 07246 They

become the reason factors to influence the development ofother industries The top 2 of 24 industries impacted degreeincluding oil and natural gas industry andmetal smelting androlling processing industry which have more influence thanother industries are the cause of industry And the reasondegrees of 24 industries are negative values minus0124842119889 le119877119894le minus0002237 The last 2 of 18 industries impacted degree

including construction industry and food manufacturingand tobacco processing industry which are affected morelargely by other industries are the result industry This kindof industry departments should put more attention to thedevelopment and changes of their related industries andadjust their development strategies timely

In view of the above analysis the higher degree of influ-ence in Heilongjiang Province mainly comprises agriculture


Table 4 The table of top 10 industries centrality degree in Heilongjiang province in 2007

Industry number Industry name Centrality1 Agriculture forestry animal husbandry and fishery 20036 Food manufacturing and tobacco processing 1537311 Petroleum processing coking and nuclear fuel processing 1528826 Construction 1340812 The chemical industry 133723 Oil and natural gas industry 1270823 Electricity heat production and supply industry 1256416 General special equipment manufacturing industry 1086727 Transportation and warehousing industry 1030314 Metal smelting and rolling processing industry 087424

Table 5 The table of reason degree in Heilongjiang province in 2007 (the top 10 industries centrality degree)

Industry number Industry name Reason degree1 Agriculture forestry animal husbandry and fishery minus0101566 Food manufacturing and tobacco processing minus06941211 Petroleum processing coking and nuclear fuel processing minus01009526 Construction minus1222112 The chemical industry 016653 Oil and natural gas industry 07246123 Electricity heat production and supply industry 00703616 General special equipment manufacturing industry 008589727 Transportation and warehousing industry 02140414 Metal smelting and rolling processing industry 047637

forestry animal husbandry and fishery oil and equipmentmanufacturing Therefore for Heilongjiang province on thebasis of international and domestic scientific and techno-logical progress and industrial development objective trendsto be taken full advantage of the primary industry and theadvantages of the secondary industry should be given fullplay from the specific situation in Heilongjiang provincecombined with the major needs of the current economicand social development the strategic emerging industryselection should be determined Specific recommendationsare as follows(1) Relying on the centrality the agriculture forestry

animal husbandry and fisheries would be ranked first inHeilongjiang province bioindustry and farm machinery andequipment manufacturing industry can be an importantpart of the strategic emerging industries There are 200million mu of arable land in Heilongjiang province and isthe countryrsquos total arable land ninth and it is one of themost important grain production bases in China HoweverinHeilongjiang Province there is still raw grain economy andthe agricultural lack of scientific and technological contentand industrial innovationTherefore the resource advantagesof agriculture should be given full play in order to accel-erate the upgrading of industrial structure of agriculture tostrengthen the deepening agricultural production processingand development of upstream and downstream biologicalindustry chain and vigorously to develop green products the

formation of the ecological cycle of bioclusters At the sametime in Heilongjiang province the agricultural investmentin the equipment manufacturing industry should be furtherstrengthened to make their own province of farmmachineryand equipment manufacturing industry and to graduallyrealize the industrialization of agriculture ultimately theformation of the organic combination of TIAC(2)Relying on the degrees of the reasonsmining industry

on oil and natural gas as well as electric power the heatproduction and the supply industry ranked in first numberin Heilongjiang province the led ldquooil economyrdquo shouldbe changed gradually the formation of a new pattern ofwind energy hydropower biomass and other new types ofclean energy-based diversified energy development shouldbe formed Carry out the riding implementation strategiesand develop with the large-scale backbone enterprises Basedon the straight play of the leading role of large enterprisethe upgrading of the energy industry should be promotedaccelerately Actively participate in the restructuring andindustrial upgrading of the central enterprises do a good jobto build together and to form a complete set explore togetherwith the central enterprises to form the diversification of thenew energy industry base and industrial base so as to realizethe transformation of economy of the resource-based citiesespecially the resource-exhausted cities

(3) Rely on the common use in the higher central degreesand causes of them and also depend on the special equipment


manufacturing actively seize the chances of the policy inthe aircraft rail transportation and automobile industry InHeilongjiang Provincewe should focus on themanufacturingindustry of the construction of the transportation equipmentThere is a good base on transportation equipment manufac-ture in Heilongjiang province Dongan group has becomea major research and production base for aviation engineand helicopter transmission system there are 4G1 and 4G9two series engine manufacturing technology and products inthe automobile engine company of Dongrsquo an there are fourproduction bases in North car group with Qi Ha Mu andDa and there is the e-design manufacturing and export baseof railway freight and railway cran of China and the domesticmarket share is more than 20(4) In the mining province there are varieties of mineral

resources abundant in Heilongjiang province Now 134kinds of minerals of various kinds have been discoveredaccounting for 572 of the 234 kinds of various mineralsthat have been found in ChinaThere are 87 species that havebeen identified reserves of mineral and it has been identifiedthat there are 87 kinds of mineral reserves accountingfor 377 of the number of the resources of the mineralreserves Therefore the new material industry may be takenas strategic emerging industry in Heilongjiang provincewhich has important strategic significance for promotingthe upgrading of industrial structure and transformation ofeconomic development

In January 2011 ldquoHeilongjiang Province National Eco-nomic and Social Development 12th Five-Year Planrdquo isproposed by the Heilongjiang Provincial Party Committeethe synopsis to develop new materials industry biologicalindustry new energy equipment manufacture new farmmachinery and equipment manufacturing transportationequipment manufacturing industry and five strategic emerg-ing industries is pointed out clearly and it is consistent withthe strategic emerging industry in this paper

3 The Cluster Analysis of RegionalEmerging Industries

The cultivation of strategic emerging industry cluster is animportant way develop regional economic transformationand industrial upgrading so we should appraise the standardof strategic emerging industry accumulation dynamicallyafter we have chosen and determined the strategic emergingindustries

It is important to give the major construction to thestrategic emerging industries which have good aggregationand form regional leading and characteristic industry byexcavating their upstream and downstream industries Thisaction will drive the regional economic development Inaddition it is equally important to analyze the reasons of thestrategic emerging industries which have poor aggregationand realize the reasonable distribution

31 Analysis of the Industry Concentration Degree Index Inits narrow sense the degree of industrial concentration isused to express the largest proportion index of the largest

entrepreneur among the whole national economy or all theeconomic activities of enterprises It is a concept which isused to describe the characteristics of the market structureand the market power of large enterprises Usually it ismeant by the proportion of the total indexes of severalenterprises arranged in the front of one industry amongthe whole industry The bigger ratio the is the higher theindustry concentration is But in its broad sense the industryconcentration can be referred to some industry some certainowned enterprises and the proportion of some enterprises inthe whole economy The calculation formula is

119862119877119899=sum (119883119894)119899

sum(119883119894)119873

119873 gt 119899 (10)

119862119877119899is the industry concentration of the previous biggest

enterprises119883119894is the 119894th enterprise output production sales

sales volume employees number the total assets and so on119899 is the number of the previous biggest enterprises in theindustry119873 is the total number of enterprises in the industry

In this paper we choose 119899 = 4 and get the data ofindustrial concentration in accordance with the data of theldquostatistical yearbook of Heilongjiang provincerdquo in Table 6

32 Analysis of the Industrial Concentration Index The con-centration index of industry (EG index) is to solve thedistortion of spatial Gini index combined with Geffen Dahl(H) proposed by Elilsion and Glaeser [17] a new industrialconcentration index which measures the geographical spaceand reflects the difference of regional economic developmentThe assumption is as follows an economy (country orregion) in a certain industry with 119873 and119872 a geographicaldistribution in the economy area the calculation formula is

119903119894=

119866119894minus (1 minus sum

119872

119895=11199092

119895)119867119894

(1 minus sum119872

119895=11199092

119895) (1 minus 119867

119894)

(11)

where119867119894= sum119873

119895=11199112

119895 119866119894= sum119872

119895=1(119904119894119895minus 119909119895)2

119903119894=

sum119872

119895=1(119904119894119895minus 119909119895)2

minus (1 minus sum119872

119895=11199092

119895)sum119873

119895=11199112

119895

(1 minus sum119872

119895=11199092

119895) (1 minus sum

119873

119895=11199112

119895)

(12)

119878119894119895is the proportion of which the industry output of industry 119894

in reginal 119895 accounts for national output 119909119895is the proportion

of which all industries output in reginal 119895 accounts fortotal national output of all industries 119903

119894is the industrial

concentration degree of industry 119894 the greater the value of 119903119894

is (maximus is 1) the more concentrated the industry 119894 is 119866119894

represents a spatial Gini index of industry 119894 119867119894is on behalf

of the Herfindahl index of industry 119894 119911119895is enterprise 119895 in

the industrial share of total employment By the formula in(12) the Heilongjiang province strategic emerging industryindustrial agglomeration index is shown in Table 7

33 Analysis of Strategic Emerging Industry Agglomeration inHeilongjiang Province (1)The degree of industrial concen-tration of Heilongjiang province in five strategic emerging


Table 6 Strategic emerging industry of Heilongjiang industrial concentration

YearIndustry

New material Biology New energy equipmentmanufacturing industry

New farm machineryand equipment

manufacturing industry

Transportationequipment

manufacturing industry2008 0325716 0314621 0700157 0311452 07156212009 0412326 0378612 0709826 0368610 07789522010 0510165 0465365 0714054 0390874 0841048

Table 7 Strategic emerging industry of Heilongjiangrsquos industrial agglomeration index

YearIndustry






industries and its industry aggregation index are showing arising trend but the agglomeration level is not high the scopeof 119862119877

119899is 0314621ndash0841048 and the highest amplification

of industrial concentration is the advanced material annualamplification mean reaches which is closely related withthe lower economic development in Heilongjiang provincewhich is located in the frontier of the motherland theoverall level of economic development is not high As forthe advanced material one kind of emerging industry hasthe same starting point in different provinces ThereforeHeilongjiang province developed this area faster but theindustrial concentration is not very high reached 0510165 in2010 which required us to invest more in a high level andincrease its concentration ratio Among them the industryconcentration of transportation equipment manufacturingindustry concentration degree index was the highest reached0841048 in 2010 which fitted the rapid development of trans-portation equipment manufacturing industry trend in recentyears Therefore our province should concentrate more onstrength seize the opportunity depend on the relativelystrong foundation of equipment manufacturing industryand focus on supporting the potential of the transportationequipmentmanufacturing industry which results in the rapiddevelopment(2)Thedegree of industrial concentration ofHeilongjiang

province is normally low only reached 0031925ndash0293065and all less than 03 which declares that the Heilongjiangprovince which has advantage in agriculture states in aweaker area comparing to other provinces And its agri-culture machinery equipment manufacturersquos concentrationindex is only 0120672 which declares that its productivityof agriculture machinery equipment manufacture is verypoor which cannot fit the demand of modern agricultureproductivity However the greatest increasing trend is grat-ifying which separately reached 459 and 1043 of thetwo years It also means that the Heilongjiang province has

realized the importance and feasibility to develop the newkind of agriculture machinery equipment manufacture Theconcentration index of biological industry is low becausethe biological industry belongs to the resource intensiveindustries the phenomenon of all over the country repeatconstruction is pretty serious which is more difficult to formin a particular province of industrial agglomeration Newmaterial industry and new energy equipment manufactur-ingrsquos industry concentrations have increased steadily thanksto the advantage of abundant resources in Heilongjiangprovince

4 Conclusion

Though the policy support is essential to strategic emergingindustry to achieve the objective of adaptation to localconditions upgrading of industrial structure and rapid andhealthy economic development it is very important to choosethe suitable industry according to the characteristics leveland realistic situation In this paper improved DEMATELmodel based on input-output and complex network theoryis adopted which can play a comprehensive evaluation effectby fully relying on the advantages of traditional industries andfully considering the coupling relationship between themTaking Heilongjiang province as an example to choose 2007input-output analysis of regional strategic emerging industrythe selection results are basically the same with the ldquo12thFive-Year Planrdquo in 2011 The results can show that the theselection and model analysis are in conformity with thedevelopment reality and reflect its science objectivity andreasonableness In addition a dynamic follow-up index teston industry concentration and aggregation is establishedwiththe industrial development data from 2008 to 2010 Con-sidering the sustainable development of strategic emergingindustry the ecoefficiency and dynamic industrial evaluationwill be continued in the future


Acknowledgments

This research was partially supported by the National NaturalScience Foundation of China (Grant nos 71173060 71102131)the Social Sciences Foundation of Heilongjiang Province(project no 10E078) the National Natural Science Founda-tion of Heilongjiang Province (Grant nos G201004) and theSocial Science research Foundation of Heilongjiang ProvinceEducation Department (project no 12512278)

References

[1] Premier Jiabao Wen ldquoGovernment Work Reportrdquo China Net-work 2012 httpwwwchinacomcn

[2] L Q Guo ldquoInternational Comparison and Enlightenment inthe adjustment of the declining industryrdquo Economic Review vol4 pp 14ndash16 2004

[3] F L Qiao and J Yang ldquoResearch on selection and evaluationof strategic emerging industry in Liaoning Provincerdquo Journal ofShenyang University of Technology vol 4 pp 268ndash273 2010

[4] Y Q Xiong and D Zeng ldquoThe cultivation and development ofstrategic emerging industries based on the perspective of thetraditional industriesrdquo Emerging Industry Research vol 4 pp49ndash54 2011

[5] Z C He ldquoStrategic emerging industry choice and evaluationand empirical analysisrdquo Public Understand Science vol 12 pp62ndash67 2010

[6] H M Li ldquoRegional strategic emerging industry selection eval-uationrdquo Journal of North China Water Conservancy and Hydro-power College (Social Sciences Edition) vol 4 pp 91ndash93 2011

[7] D S Luo ldquoThe establishment of evaluation index system ofindustrial characteristics and thinking basedrdquo Journal of CityEconomy vol 1 pp 7ndash9 2012

[8] Z H Hu C Q Li and X Y Qing ldquoBased on the AHP-IE-PCAlsquocombination weighting method of strategic emerging industryselection modelrsquordquo Public Understand Science vol 7 pp 104ndash1102011

[9] Z Y Liu and H S Cheng ldquoStrategic emerging industry clusterdevelopment and network characteristicsrdquo Reform vol 5 pp36ndash42 2010

[10] Y Liu ldquoExperience and Enlightenment of Japan in the devel-opment of strategic emerging industriesrdquo City DevelopmentStrategy vol 6 pp 2ndash25 2010

[11] Y C Ao and J X Liu ldquoTheoretical thoughts of the selection ofregional strategic new industriesrdquoThe Commercial Era vol 21pp 116ndash117 2012

[12] Z L Xing ldquoStudy on regional industrial structure networkmodel based on complex network theoryrdquo Industrial Technologyand Economy vol 2 pp 19ndash30 2012

[13] R Liu and Z F Zhou ldquoStudy on the evaluation index systemof credit risks of enterprise based on DEMATELrdquoManagementExperts Academic Edition vol 1 pp 22ndash30 2012

[14] G Tzeng C Chiang and C Li ldquoEvaluating intertwined effectsin e-learning programs a novel hybridMCDMmodel based onfactor analysis and DEMATELrdquo Expert Systems with Applica-tions vol 32 no 4 pp 1028ndash1044 2007

[15] Y K Liang and Z DMa ldquoConstruction risk analysis of founda-tion engineering based on DEMATEL methodrdquo Journal of En-gineering Management vol 2 pp 164ndash167 2010

[16] C Y Zhu andM S Yang ldquoModifying the importance ratings ofcustomersrsquo requirements correction based on DEMATEL and

Entropyrdquo Industrial Engineering andManagement vol 2 pp 97ndash101 2012

[17] G Ellison and E L Glaeser ldquoGeographic concentration in USmanufacturing industriesa dartboard approachrdquo Journal of Po-litical Economy vol 105 pp 889ndash927 1997

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of


Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of


Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of


Mathematical PhysicsAdvances in

Complex AnalysisJournal of


OptimizationJournal of


CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of


Operations ResearchAdvances in

Journal of


Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014


Algebra

Discrete Dynamics in Nature and Society



Decision SciencesAdvances in

Discrete MathematicsJournal of


Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of


Nuc

lear

pow

er

IOT

indu

stry

Elec

troni

c inf

orm

atio

nin

dustr

y

Biop

harm

acy

indu

stry

Mar

ine e

cono

my

indu

stry

Aero

spac

e ind

ustr

y

New

-ene

rgy

auto

mob

ilein

dustr

y

New

mat

eria

l ind

ustr

y

New

ener

gy in

dustr

y

Hig

h-en

d eq

uipm

ent

man

ufac

turin

g

Bioi

ndus

try

Info

rmat

ion

indu

stry

Ener

gy-s

avin

g in

dustr

y

The m

oder

n fo

od in

dustr

y

30

25

20

15

10

5

0

The number of districts

Figure 1 Selected case charts of the strategic emerging industry inthirty provinces (cities) of our country

choice of the regional strategic emerging industries caneasily result in vicious competition redundant constructionwaste of resources and other issues of excess productioncapacity Regional strategic emerging industry is never asimple regional of the country strategic emerging industriesthe difference between the two is not only in amount butalso in quality Therefore how to accurately and scientificallyselect and evaluate the regional strategic emerging industrywill have important theoretical and practical meanings

At present many scholars are carrying on the theoreticaland empirical research of the strategic emerging industriesfirst Qiao and Yang [3] and Xiong and Zeng [4] establishedan evaluation system from the perspective of coupling theemerging industries and traditional industries Second He[5] Li [6] and Luo [7] and Hu et al [8] constructedthe choice model based on the Analytic Hierarchy Process(AHP) fuzzy comprehensive and the combination of ldquoAHP-IEmdashPCArdquo empowerment evaluation method Third Liu andCheng [9] and Liu [10] used comparative analysis to proposethe suggestion of choosing mechanism Forth Ao and Liu[11] come up with the choosing principle basic principle andseveral kinds of typical selective methods of the strategicemerging industry from the theoretical level

It is not difficult to see that scholars for regional strategicemerging industry choice mainly focused on the importanceof strategic emerging industry connotation and character-istic mechanism of formation and development selectionprinciple and cultivation measures discussion of theoryempirical research is mainly to have a set of strategic emerg-ing industries evaluation of each area method is selectionthe method of simple transplantation for leading industry

lacking regional strategic emerging industry choice and thechoice of system science method and evaluation system Asregional industrial system is a complicated dynamic systemand strategic emerging industry has strong correlation effectand characteristics of sustainable development this paperwill be based on the complicated network and input-outputtheory with the aid of DEMATEL improved model as anexample to Heilongjiang province regional strategic emerg-ing industry selection research andwill do dynamic gatheredqualitative research for selection result

2 The Choice of Regional StrategicEmerging Industry Based onthe Improved DEMATEL Model

21 Industrial Complex Network and the Introduction of theTheory of Input and Output Regional industrial systembeing the most complicated subsystem of national economicsystem construction must composite complex system theoryand macroeconomic quantity analysis to make overall plan-ning [12] Industrial system is mainly related to the input andoutput of the interindustry so with the help of the input andoutput theory we need the theory of input and output to studysome characteristics of the regional industrial system Input-output theory is founded by theHarvardUniversity professorWassily Leontief in 1936 and itmainly studies the quantitativeanalysis of the input-output interdependence relationshipof each part in the economic system This interindustryperplexing relationship of supply and demand generally issuccinctly explained by the input-output table

22 Based on DEMATEL Improved Model of the Input-OutputTable and Empirical Research DEMATEL is an analysismethod using graph theory and matrix tools for systemanalysis proposed by the American scholar Gabus andFontela By constructing the direct affect matrix betweensystem factors apply thematrix to calculate the center degreeand reason degree of each factor and then determine theimportance of various factors in the system This method ismore effective for dealing with complicated social economicproblems especially for the problem of unclear relationshipsof system factor [13] In recent years many scholars applyDEMATEL to study complex system Tzeng et al [14] useDEMATEL structure analysis method (AHP) and fuzzyintegral to construct a selection evaluation model of onlinelearning project Liang andMa [15] apply DEMATELmethodto analyze the foundation engineering construction risk Zhuand Yang [16] bring DEMATEL and entropy according to theautocorrelation of customersrsquo demand and the influence ofmarket competition evaluation to correct the basic importantfactor of the customersrsquo needs and integrate the processingresults of the two sides then we can get more objective finalimportant factor of the customersrsquo needs

On the basis of using DEMATEL method for referencethis paper extends the DEMATEL method to the weightedfield of complex network confirms network supportingmatrix using the improved DEMATEL method studies the









119863 = 119904119860 (119904 gt 0) (1)



Sup = max

1

max1le119894le119873

sum119873

119895=1

10038161003816100381610038161003816119886119894119895

10038161003816100381610038161003816

1

max1le119895le119873

sum119873

119894=1

10038161003816100381610038161003816119886119894119895

10038161003816100381610038161003816

(2)




119894= sum119873

119895=1119889119894119895 The sum of


119895= sum119873



119879 = 119862 + 1198622+ sdot sdot sdot + 119862

119899= 119862119868 minus 119862119899minus1

119868 minus 119862 (3)


119879 = 119862119868

119868 minus 119862= 119862(119868 minus 119862)

minus1 (4)




































119879119903 (119894) =

119899

sum

119895=1

119905119894119895

119879119888(119895) =

119899

sum

119894=1

119905119894119895

(5)




119888is the


119872 = 119879119903+ 119879119888 (6)



119872119894= 119879119903 (119894) + 119879119888 (119894) (7)


119888is


119877 = (119879119903minus 119879119888) (8)



119877119894= 119879119903 (119894) minus 119879119888 (119894) (9)



119894lt 0










N(1)

N(2)

N(3)

N(6)

N(11)

N(12)

N(14)

N(16)

N(17)

N(18)N(23)

N(26)

N(27)N(30)

N(31)N(32)

N(40)

0 1 2

0

1

Centrality degree

Reas

on d

egre

e

minus15

minus1

minus05

15

05

05 25








119894le 07246 They























119862119877119899=sum (119883119894)119899

sum(119883119894)119873

119873 gt 119899 (10)






119903119894=


119872

119895=11199092

119895)119867119894

(1 minus sum119872

119895=11199092

119895) (1 minus 119867

119894)

(11)

where119867119894= sum119873

119895=11199112

119895 119866119894= sum119872

119895=1(119904119894119895minus 119909119895)2

119903119894=

sum119872

119895=1(119904119894119895minus 119909119895)2


119895=11199092

119895)sum119873

119895=11199112

119895

(1 minus sum119872

119895=11199092


119873

119895=11199112

119895)

(12)













YearIndustry







YearIndustry











4 Conclusion



Acknowledgments


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra

















119863 = 119904119860 (119904 gt 0) (1)



Sup = max

1

max1le119894le119873

sum119873

119895=1

10038161003816100381610038161003816119886119894119895

10038161003816100381610038161003816

1

max1le119895le119873

sum119873

119894=1

10038161003816100381610038161003816119886119894119895

10038161003816100381610038161003816

(2)




119894= sum119873

119895=1119889119894119895 The sum of


119895= sum119873



119879 = 119862 + 1198622+ sdot sdot sdot + 119862

119899= 119862119868 minus 119862119899minus1

119868 minus 119862 (3)


119879 = 119862119868

119868 minus 119862= 119862(119868 minus 119862)

minus1 (4)




































119879119903 (119894) =

119899

sum

119895=1

119905119894119895

119879119888(119895) =

119899

sum

119894=1

119905119894119895

(5)




119888is the


119872 = 119879119903+ 119879119888 (6)



119872119894= 119879119903 (119894) + 119879119888 (119894) (7)


119888is


119877 = (119879119903minus 119879119888) (8)



119877119894= 119879119903 (119894) minus 119879119888 (119894) (9)



119894lt 0










N(1)

N(2)

N(3)

N(6)

N(11)

N(12)

N(14)

N(16)

N(17)

N(18)N(23)

N(26)

N(27)N(30)

N(31)N(32)

N(40)

0 1 2

0

1

Centrality degree

Reas

on d

egre

e

minus15

minus1

minus05

15

05

05 25








119894le 07246 They























119862119877119899=sum (119883119894)119899

sum(119883119894)119873

119873 gt 119899 (10)






119903119894=


119872

119895=11199092

119895)119867119894

(1 minus sum119872

119895=11199092

119895) (1 minus 119867

119894)

(11)

where119867119894= sum119873

119895=11199112

119895 119866119894= sum119872

119895=1(119904119894119895minus 119909119895)2

119903119894=

sum119872

119895=1(119904119894119895minus 119909119895)2


119895=11199092

119895)sum119873

119895=11199112

119895

(1 minus sum119872

119895=11199092


119873

119895=11199112

119895)

(12)













YearIndustry







YearIndustry











4 Conclusion



Acknowledgments


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra


















119879119903 (119894) =

119899

sum

119895=1

119905119894119895

119879119888(119895) =

119899

sum

119894=1

119905119894119895

(5)




119888is the


119872 = 119879119903+ 119879119888 (6)



119872119894= 119879119903 (119894) + 119879119888 (119894) (7)


119888is


119877 = (119879119903minus 119879119888) (8)



119877119894= 119879119903 (119894) minus 119879119888 (119894) (9)



119894lt 0










N(1)

N(2)

N(3)

N(6)

N(11)

N(12)

N(14)

N(16)

N(17)

N(18)N(23)

N(26)

N(27)N(30)

N(31)N(32)

N(40)

0 1 2

0

1

Centrality degree

Reas

on d

egre

e

minus15

minus1

minus05

15

05

05 25








119894le 07246 They























119862119877119899=sum (119883119894)119899

sum(119883119894)119873

119873 gt 119899 (10)






119903119894=


119872

119895=11199092

119895)119867119894

(1 minus sum119872

119895=11199092

119895) (1 minus 119867

119894)

(11)

where119867119894= sum119873

119895=11199112

119895 119866119894= sum119872

119895=1(119904119894119895minus 119909119895)2

119903119894=

sum119872

119895=1(119904119894119895minus 119909119895)2


119895=11199092

119895)sum119873

119895=11199112

119895

(1 minus sum119872

119895=11199092


119873

119895=11199112

119895)

(12)













YearIndustry







YearIndustry











4 Conclusion



Acknowledgments


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra















N(1)

N(2)

N(3)

N(6)

N(11)

N(12)

N(14)

N(16)

N(17)

N(18)N(23)

N(26)

N(27)N(30)

N(31)N(32)

N(40)

0 1 2

0

1

Centrality degree

Reas

on d

egre

e

minus15

minus1

minus05

15

05

05 25








119894le 07246 They























119862119877119899=sum (119883119894)119899

sum(119883119894)119873

119873 gt 119899 (10)






119903119894=


119872

119895=11199092

119895)119867119894

(1 minus sum119872

119895=11199092

119895) (1 minus 119867

119894)

(11)

where119867119894= sum119873

119895=11199112

119895 119866119894= sum119872

119895=1(119904119894119895minus 119909119895)2

119903119894=

sum119872

119895=1(119904119894119895minus 119909119895)2


119895=11199092

119895)sum119873

119895=11199112

119895

(1 minus sum119872

119895=11199092


119873

119895=11199112

119895)

(12)













YearIndustry







YearIndustry











4 Conclusion



Acknowledgments


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra




























119862119877119899=sum (119883119894)119899

sum(119883119894)119873

119873 gt 119899 (10)






119903119894=


119872

119895=11199092

119895)119867119894

(1 minus sum119872

119895=11199092

119895) (1 minus 119867

119894)

(11)

where119867119894= sum119873

119895=11199112

119895 119866119894= sum119872

119895=1(119904119894119895minus 119909119895)2

119903119894=

sum119872

119895=1(119904119894119895minus 119909119895)2


119895=11199092

119895)sum119873

119895=11199112

119895

(1 minus sum119872

119895=11199092


119873

119895=11199112

119895)

(12)













YearIndustry







YearIndustry











4 Conclusion



Acknowledgments


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra











YearIndustry







YearIndustry











4 Conclusion



Acknowledgments


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra










Acknowledgments


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra
















Volume 2014




Journal of











Journal of


Function Spaces






Algebra









research article an evaluative study on the choice of...

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