Download - Barriers to environmentally-friendly clothing production among Chinese apparel companies

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Original Article

Barriers to environmentally-friendly clothing

production among Chinese apparel companiesReceived 29 November 2010; revised 30 January 2011; accepted 15 March 2011

Qinghua Zhua,*, Joseph Sarkisb and Yong GengcaSchool of Business Management, Dalian University of Technology, Dalian, Liaoning Province

116024, China.

E-mail: [email protected] School of Management, Clark University, 950 Main Street, Worcester, MA 01610-1477,

USA.

E-mail: [email protected] of Applied Ecology, China Academy of Sciences, Shenyang, Liaoning Province 110016,

China.

E-mail: [email protected]

*Corresponding author.

Abstract Increasing environmental pressures have caused Chinese apparelcompanies to pay close attention to environmentally-friendly clothes production(EFCP) and its implementation, but barriers exist. This article uses a grey-basedDecision-Making Trial and Evaluation Laboratory (DEMATEL) approach tostructure and evaluate these barriers. Results show that for some apparelmanufacturing companies, lack of human resource capabilities and hard-to-enterenvironmentally friendly clothing (EFC) major markets act as barriers. Othercompanies have basic barriers of no top management support and immaturity inlarge-scale EFCP. We also introduce aggregate analysis for the set of apparelmanufacturing companies and suggest future research directions.Asian Business & Management (2011) 10, 425–452. doi:10.1057/abm.2011.15;published online 8 June 2011

Keywords: clothing; environmental; barriers; DEMATEL; grey analysis; China

Introduction

Apparel is an important export industry in China, which is the largest exporterof textiles and apparel in the world. However, the Chinese apparel industry hasexperienced increasing pressure to improve their environmental performance;Chinese apparel companies have to meet higher environmental standards when

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exporting to developed countries (Jørgensen et al, 2010) or become suppliersfor leading international retailers, such as Walmart (Arbar et al, 2009).

To meet these environmentally oriented challenges, Chinese apparelcompanies have started to consider environmentally-friendly clothes produc-tion (EFCP). However, both external and internal barriers for EFCP exist(Connell, 2010). Consumers’ preferences for environmentally friendly clothing(EFC), when compared with quality and cost, is uncertain (Devinney et al,2010). It is also difficult for Chinese apparel companies to enter high-profilemarkets such as Europe (Courville, 2006). Similar to other environmentalpractices, internal barriers for EFCP include insignificant benefits (van Hemeland Cramer, 2002) and lack of resources (Chan, 2008).

Studies on EFCP are limited (Connell, 2010), whereas studies on barriers toEFCP, especially in China, are nonexistent. This article investigates and eva-luates such barriers among Chinese apparel companies. The contributions of thisresearch are multifold. First, we review a comprehensive set of EFCP barriers.Second, we introduce our analysis of these barriers, using data from Chineseapparel companies, by applying an under-utilized methodology. Third, we applya unique methodology that may be further applied to barrier analysis across awide variety of issues facing operations and sustainability decisions or strategies.

We begin with a brief introduction of the Chinese apparel industry andenvironmental challenges they have met, moving on to the concept of andbarriers to EFCP in Part 2. In Part 3, we describe our questionnaire deve-lopment and data collection for EFCP barriers. A grey-based Decision-MakingTrial and Evaluation Laboratory (DEMATEL) approach is used to structurethe relationships amongst barriers for EFCP in China in Part 4. Results anddiscussions are presented in Part 5, followed by conclusions in Part 6.

The Chinese Apparel Industry and EFCP Barriers

The Chinese apparel industry and environmental challenges

China’s opening and reform policy in 1978 put the Chinese textile and apparelindustry on the global economic map, as it became a key export sector.Previously, this industry primarily served the domestic market with obsoleteequipment and technology. During the early 1980s, the Chinese governmentdecided that this industry would initiate the opening up of commerce to theworld market, as it was characterized by abundant materials and inexpensivelabor. The clothing industry, formed by many small- and medium-sizedtextile and apparel firms located primarily in the Yangtze River Delta and thePearl River Delta regions, required neither significant investment norsophisticated technology (Qiu and Qiu, 2009). In the 1990s and 2000s, industry

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advantages included economies of scale, cheap labor, preferable export policiesand unyielding upstream–downstream supply-chain collaboration. The rapiddevelopment of the early 2000s, however, gave way to stagnation in recentyears because of the worldwide financial crisis (Jin, 2010).

Recently, the Chinese apparel industry has experienced environmentalchallenges. Increasing global environmental quality concerns and green ‘tradebarriers’ have caused organizations to consider these challenges (Cui, 2009).Many Chinese apparel companies have so far failed to incorporate environ-mental management principles into their operations because of lack ofawareness and the need to pursue greater short-term economic profits (Fu,2006; Qiu and Qiu, 2009). The Chinese industry lacks advanced technologiesand equipment, resulting in poor energy and production efficiencies. Researchinvestment in the apparel industry is also limited, as most Chinese companiesrely on purchasing foreign equipment, materials and technologies.

In this article, we focus only on internal processes directly managed byclothes producers. This boundary may not uncover some major issues of EFCParising from the supply chain, but are realistically the major concerns faced bythis group. A full accounting of the myriad environmental issues facing ageneric textile and clothing supply chain can be found in van Berkel (1994).

The EFCP concept

The typical production processes for the apparel manufacturing stage of thetextile supply chain comprise: cutting, sewing, quality control, ironing, folding,finishing, packaging, storage and delivery. Reverse logistics are lacking. At eachstage of the process, energy and material is utilized as waste is generated. EFCPcan occur through process developments or product characteristics. Processissues may include conserving energy or material in the production process.Product characteristic changes for EFCP may include new ecodesigns, but for anapparel manufacturing company much of the emphasis would be on green pur-chasing activities. Specific examples of greening materials and products include:

1. Using cloth with no or low hazardous substance, through usingenvironmentally safe dyes and avoiding harmful additions during thecleaning process.

2. Using natural materials such as cotton, hemp, silk, wool, or organic cotton,hemp and silk.

3. Using cloth with low or no dye.4. Using ‘waste’ as recovery cloth.

In this study, the EFCP concept includes both processes and products(materials).

Barriers to environmentally-friendly clothing production among Chinese apparel companies

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EFCP barriers

To implement environmental practice within organizations, both externaldrivers and internal resource/capabilities are needed; a lack of either can bebarriers to EFCP. Using stakeholder theory (Darnall et al, 2010), we identifythree kinds of external drivers related to marketing, suppliers and regulations.According to the resource-based view, both resources and capability areneeded for EFCP-like innovations. Thus, we develop a framework of questionson EFCP barriers, which include three external factors and two internal factors(Table 1).

MarketingMarket opportunities or customer demands are a key stimulus for environ-mental practices (van Hemel and Cramer, 2002; Jørgensen et al, 2010). Theavailability of EFC markets is relatively uncertain. For example, entering intorelationships with major suppliers like Walmart and Nike is not easy fordeveloping country producers of EFC (Arbar et al, 2009).

Part of the uncertainty and difficulty lies in determining consumerpreferences and premiums they are willing to pay for environmental productsin general and EFC in particular (Nimon and Beghin, 1999). The credibility ofthe message that a product is environmentally friendly is also a marketingconcern (Courville, 2006; Phau and Ong, 2007; Jørgensen et al, 2010).

Barriers from the consumer market also exist, including lack of knowledge,general attitudes, availability of environmentally preferable apparel, economicresources, retail environments and societal norms (Connell, 2010; Devinneyet al, 2010). Studies have consistently shown that aesthetic preference, qualityand price are primary factors, whereas environmental factors remain secondaryfor clothing and other products (Hartmann, et al, 2006; Phau and Ong, 2007).

Given this background, we arrive at two major barriers:

B1: Hard-to-enter EFC major markets, for example Europe, United States, Japan.

B2: Low preference/requirement for EFC when compared to price and quality ofclothes in current market.

Internal resourcesEven environmentally oriented projects require a ‘business case’ to be made(Sarkis et al, 2006). Often, benefits from environmental projects are neitherdirect cost savings, nor easily attributable to revenue generation (Presley et al,2007). These hard-to-define benefits are a key barrier for companies seeking to

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Table

1:Finalbarriers

andtheirdefinitionforenvironmentallyfriendly

clothes

production

Barriers

Definitions

Marketing

related

B1:Hard-to-enterEFC

major

markets,forexample

Europe,

United

States,Japan

Theinabilityto

enterEFC

marketsin

themajordeveloped

countries.Market

entry

difficultymayalsorelate

tolack

ofknowledgerelatedto

contractualobligations

associatedwithmaintainingEFC.

B2:Low

EFC

preference/requirem

ent

comparedto

price

andquality

in

currentmarket

EFC

clothes

mayhavealower

preference

bymost

marketsandconsumersbecause

of

perceived

oractualprice

orquality

ofEFC

clothes

when

comparedto

non-EFC

clothes.

Resources

related

B3:Difficult-to-quantify

EFCbenefits

Thebenefitsto

EFCare

difficultto

capture.Short-term

gainsrequirem

entsare

necessary

forthesematerialsto

beem

bracedbytextile

organizations,butenvironmental

materialsare

more

expensive.

B4:Notopmanagem

entsupport

for

EFCP

Topmanagem

entsupport

istypicallyrequired

foranymajorprogram

orproduct

success.Topmanagem

entsupportmayrangefrom

championingEFCto

dedicationof

actualfinancialresources.

B5:Lack

ofstrategic

planningfor

EFCP

TheinclusionofEFC

inlong-term

plansfortheorganizationwillenhance

EFC

manufacture.IncorporatingEFCPinto

theorganization‘sstrategic

planwillgain

the

necessary

long-term

support.

Capability

related

B6:Lack

ofknowledgeor

inform

ationonEFC

market

potential

Inform

ationconcerningEFC

especiallyrelatedto

consumer

needsisdifficultto

find

either

throughofficial(government/professionaldata)orunofficial(salespersons)

sources.

B7:Im

maturity

oflarge-scale

EFCP

Lack

ofeconomiesofscale

meansthathighefficiencies

are

difficultto

achieveandthat

manyofthedevelopments

tohelpbringabouttheseefficiencies

are

notavailable.

B8:Lack

oftechnologyforEFCP

Theproduct

andprocess

technologiesforEFC

are

veryexpensive,difficultto

use

ordo

notexist.Thus,easy

accessto

thistechnologyisseverelylimited,resultingin

poorer

quality,higher

costing,difficultyin

findingmaterialsforEFC

cloth.

B9:Lack

ofhumanresource

capabilitiesforEFCP

Havingthenecessary

laborto

plan,produce

anddeliver

EFCclothes

islimited.Workers

donothavethenecessary

skillsandcapabilitiesto

produce

EFC

clothing.

Suppliers-

related

B10:Highpurchasingcost

for

environmentallysoundmaterials

Thecostofinputmaterialsformanufacture

ofEFCishigher

thanmaterialsthatgointo

non-EFC

clothing.

Regulations-

related

B11:Lack

orlow

enforcem

entof

relatedregulatory

requirem

ents

Thereare

noorfewregulationsfortheorganizationto

adoptEFCoperations,materials

orpractices

forproductionofEFC.In

addition,even

ifregulationsexist,lack

of

enforcem

entmakes

iteasy

tooverlooktheadoptionofEFCPpractices

ormaterial.



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implement environmental practices or products (Sarkis et al, 1997; van Hemeland Cramer, 2002). Thus, the first barrier related to internal resources is:

B3: Difficult-to-quantify EFC benefits.

Lack of resources is a major barrier for any environmental practice (Chan,2008). If senior managers do not perceive environmental practices as a require-ment, barriers will exist for such environmental practices (van Hemel andCramer, 2002). Top management support for environmental (and most strategic)initiatives is critical for their success (Zhu et al, 2008; D’Amato and Roome,2009). Thus, another resource-oriented barrier is focused on management’s role:

B4:No top management support for EFCP.

To embed EFC into an organization, a long-term focus is required. Eventhough there may be opportunistic characteristics to such a decision, long-termsuccess can most effectively be achieved if there is strategic planning.Environmental strategic planning is even more difficult to integrate (Gibsonand Cassar, 2002). This situation brings us to a major barrier that may facethese organizations.

B5: Lack of strategic planning for EFCP.

Internal capabilityPotential market opportunities are a key driver for companies to implementenvironmental practices (van Hemel and Cramer, 2002). To strategically andoperationally respond to these opportunities, internal capabilities must exist(Gurau and Ranchhod, 2005; Sarkis et al, 2010). Gathering this information isnot necessarily a capability for many clothing companies, especially indeveloping countries. Thus, we propose the next barrier:

B6: Lack of knowledge or information on EFC market potential.

The price of EFC products, in large part determined by production costs,plays an important role in developing EFC markets (Hartmann et al, 2006;Phau and Ong, 2007). Thus, the ability to produce EFC at low unit cost isnecessary. Having the capacity to produce on a large scale will help lower unitcosts. Given that the experience and knowledge associated with EFCP in Chinais still relatively novel, we posit another major barrier:

B7: Immaturity of large-scale EFCP.

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Technical issues are major obstacles for sustainable product developmentand design (Simonsson, 2002). Having the necessary technological capabilitiescan reduce the amount of EFCP barriers. Technological capabilities mayinclude product and process technologies, or softer technological innovationssuch as organizational practices and procedures (Zhu et al, 2011). Technologicalinfeasibilities may exist because of either internal capabilities, or externalunavailability of technology. Either way, it can produce a significant barrier:

B8: Lack of technology for EFCP.

Lack of human resource knowledge and skill, as well as professional advice,can be key barriers to EFCP (Chan, 2008; del Brio et al, 2008; Sarkis et al,2010). Lack of human resource capabilities has been a major concern for Asianand developing countries for years (Visvanathan and Kumar, 1999). We nowintroduce the last major internal capability barrier.

B9: Lack of human resource capabilities for EFCP.

Key stakeholders: Suppliers and governmentBuyers of textiles have found that the price of green (recycled) materials istypically higher than standard virgin material (Larney and van Aardt, 2004).This economic barrier provides us with our next barrier:

B10: High purchasing cost for environmentally sound materials.

The lack of regulatory requirements may be a barrier for EFCP. A corollaryto this argument is that the ‘Porter Hypothesis’ states that innovations arelikely to come from regulatory pressures (Janicke and Lindemann, 2010). Thus,we develop the eleventh barrier:

B11: Lack or low enforcement of related regulatory requirements.

Questionnaire Development and Data Collection for EFCP Barriers

Interview EFCP experts

We focused on identifying and interviewing industrial experts to validate EFCPbarriers identified from the literature (see Section ‘Data collection’). Weinterviewed a vice-general manager who has worked in the clothes industrysince 1990, an official who had been in charge of the clothes industry



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government agency for 8 years, and a worker who had worked in two differentapparel companies for over 30 years. These three experts allowed us to acquirea more complete internal and external picture of the barriers.

On the basis of these three expert opinions, we realized that marketing-related barriers seem to play a very critical overall role. Internal resources andcapability dimensions were also viewed with importance. Some barriers relatedto suppliers and regulations do exist and were also included. These barriers,initially derived through literature review, were further supported by theexperts. Iteratively, with the experts, we refined each barrier and its definition.In the end, all three agreed with our definitions. A listing of the final barriersare shown and defined in Table 1.

Questionnaire development

Using the expert input, a questionnaire with four main sections was developed.The first section provided an EFC definition. The second was intended toacquire respondent and company information. The third identified barriersand their definitions. The fourth section, the core data acquisition portion forour methodology, was composed of a matrix that required completion forfurther DEMATEL analysis. Clear definitions of barriers were also developed,and are summarized in Table 1. Respondent and company backgroundsummaries are described in Section ‘Data collection’ (see Table 2). The resultsof paired comparisons of barriers are discussed in Part 4 (see Tables 4, 5, 6 and 7).

Data collection

The process of data collection required us to initially locate companies in theapparel production industry willing to provide some input into the evaluationof barriers. The goal was to locate companies that had diverse characteristics toallow for a comparative analysis. Considerations such as size and length ofexistence were two primary selection criteria. In identifying and locating com-panies, eight companies in Taicang,1 a city near Shanghai, were approached.Our sample includes two larger and two smaller companies. A summary ofbackground of the four respondents and their organizations are described inTable 2. Companies 1 and 2 are larger, whereas companies 3 and 4 are smaller.

All four companies completed the survey matrices by completing pairedcomparisons for all barriers (see results in Tables 4, 5, 6 and 7). These matricesare necessary for applying the grey-based DEMATEL method to completeour comparative analysis. The steps of this formal methodology are nowdetailed.

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Table

2:Respondentcompaniesandkey

respondents’backgrounds

Company

Establishment

year

Employee

number

(2008/current)

Market

distribution(%

)

(Europe/NorthAmerica/Japan/

Domestic)

Clothes

production

(%)Outwear/pants

orshirts

Respondents

(Role,Age/years

inindustry/years

incompany)

11991

700/360

2/0/90/8

70/30

Factory

manager,48/28/18

21990

600/400

15/5/73/7

75/25

Officedirector/ISO

system

manager,35/6/6

32002

100/100

0/0/100/0

100/0

Chairmanoftheboard,47/27/8

42005

180/170

0/0/90/10

70/30

Factory

manager,45/25/5



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A Grey-based DEMATEL Methodology

To analyze the acquired data, we apply the grey-based DEMATELmethodology. In the sections below, we briefly introduce the DEMATELapproach. Then steps for a grey-based DEMATEL method are introduced forour data analysis.

The basic DEMATEL method

DEMATEL was first developed in the mid-1970s (Gabus and Fontela, 1973;Fontela and Gabus, 1976). The method can structure complicated causal rela-tionships through matrices or digraphs. The matrices or digraphs portray rela-tionships between system components, with strengths of relationships amongstthese relationships quantitatively portrayed. Although other approaches, such asinterpretative structural modeling (ISM) or the Analytical Hierarchy Process(AHP), may be used, the DEMATEL digraphic structural evaluation techni-que has some advantages. It allows for a broader discrimination of measures(ISM only has 0–1 levels) and multiple directional relationships (AHP has aunidirectional relationship and multiple separate matrices requiring integration).

The DEMATEL method assumes a system contains a set of componentsC¼ {C1, C2, y, Cn}, with pairwise relations that can be evaluated. Thegrey-based DEMATEL method is now described.

A Grey-based DEMATEL Method

Using basic DEMATEL, as well as three steps for the grey system (seeAppendix), we develop an overall grey-based DEMATEL methodology toevaluate EFCP barriers amongst four companies. This grey-based DEMATELmethodology is composed of the following major stages and substages.

Stage 1: Develop a crisp direct-relation matrix for each company. The firststage in the process has three steps:

Table 3: The grey linguistic scale for the respondents’ assessments

Linguistic terms Grey numbers

No influence (N) [0,0]

Very low influence (VL) [0,0.25]

Low influence (L) [0.25,0.5]

High influence (H) [0.5,0.75]

Very high influence (VH) [0.75,1]

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Table

4:Thedirect-relationmatrix

forbarriers

ofenvironmentallyfriendly

clothes

productionbycompany1

Barriers

B1

B2

B3

B4

B5

B6

B7

B8

B9

B10

B11

B1:Hard-to-enterEFC

majormarket,forexample

Europe,

United

States,Japan

x4

41

43

42

13

4

B2:Low

EFC

preference/requirem

entcomparedto

price

andquality

incurrentmarket

4x

41

43

33

04

4


EFC

benefits

04

x1

33

23

14

2

B4:Notopmanagem

entsupport

forEFCP

03

4x

44

22

11

4

B5:Lack

ofstrategic

planningforEFCP

04

44

X4

22

13

4

B6:Lack

ofknowledgeorinform

ationonEFC

market

potential

04

44

4x

22

12

4

B7:Im

maturity

oflarge-scale

EFCP

24

44

44

x3

24

2

B8:Lack

oftechnologyforEFCP

04

43

34

4x

23

3

B9:Lack

ofhumanresourcecapabilitiesforEFCP

34

43

33

43

x3

1


forenvironmentallysoundmaterials

34

43

33

44

3x

3

B11:Lack

orlow

enforcem

entofrelatedregulatory

requirem

ents

04

44

33

22

21

x

Note:0=

noinfluence,1=

low

influence,2=

medium

influence,3=

highinfluence,4=

veryhighinfluence.



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Table


forbarriers


clothes


Barriers

B1

B2

B3

B4

B5

B6

B7

B8

B9

B10

B11

B1:Hard-to-enterEFC


Europe,

United

States,Japan

x2

21

24

24

34

4

B2:Low

EFC

preference/requirem

entcomparedto

price

andquality

incurrentmarket

3x

21

34

24

34

4


EFC

benefits

32

x1

34

43

23

3

B4:Notopmanagem

entsupport

forEFCP

22

3x

34

23

24

4

B5:Lack

ofstrategic

planningforEFCP

43

32

x4

22

23

3

B6:Lack

ofknowledgeorinform

ationonEFC

market

potential

43

21

3X

22

23

3

B7:Im

maturity

oflarge-scale

EFCP

43

21

34

x3

23

3

B8:Lack

oftechnologyforEFCP

13

21

34

1x

11

1

B9:Lack


12

21

34

33

x2

2



00

00

01

11

0x

1

B11:Lack

orlow

enforcem


requirem

ents

04

14

14

01

01

x

Note:0=

noinfluence,1=

low

influence,2=

medium

influence,3=

highinfluence,4=

veryhighinfluence.

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Table


forbarriers


clothes


Barriers

B1

B2

B3

B4

B5

B6

B7

B8

B9

B10

B11

B1:Hard-to-enterEFC


Europe,

United

States,Japan

x4

33

52

13

24

3

B2:Low

EFC

preference/requirem

entcomparedto

price

andquality

incurrentmarket

2x

23

23

23

24

3


EFC

benefits

43

x2

23

32

32

3

B4:Notopmanagem

entsupport

forEFCP

33

3x

23

22

24

3

B5:Lack

ofstrategic

planningforEFCP

25

32

x2

33

43

2

B6:Lack

ofknowledgeorinform

ationonEFC

market

potential

44

22

2x

32

24

2

B7:Im

maturity

oflarge-scale

EFCP

33

42

42

x4

32

4

B8:Lack

oftechnologyforEFCP

22

32

33

3x

24

3

B9:Lack


33

21

14

23

x1

4



32

23

42

41

2x

2

B11:Lack

orlow

enforcem


requirem

ents

43

22

23

24

21

x

Note:0=

noinfluence,1=

low

influence,2=

medium

influence,3=

highinfluence,4=

veryhighinfluence.



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Table


forbarriers


clothes


Barriers

B1

B2

B3

B4

B5

B6

B7

B8

B9

B10

B11

B1:Hard-to-enterEFC


Europe,

United

States,Japan

x4

10

40

40

02

0

B2:Low

EFC

preference/requirem

entcomparedto

price

andquality

incurrentmarket

0x

41

41

43

04

4


EFC

benefits

04

x1

43

23

14

2

B4:Notopmanagem

entsupport

forEFCP

03

4x

44

22

11

4

B5:Lack

ofstrategic

planningforEFCP

04

44

x4

22

13

4

B6:Lack

ofknowledgeorinform

ationonEFC

market

potential

04

14

4x

22

12

4

B7:Im

maturity

oflarge-scale

EFCP

04

44

44

x2

22

4

B8:Lack

oftechnologyforEFCP

04

43

34

4x

23

3

B9:Lack


04

43

33

43

x2

3



04

43

33

44

3x

3

B11:Lack

orlow

enforcem


requirem

ents

04

44

33

22

21

x

Note:0=

noinfluence,1=

low

influence,2=

medium

influence,3=

highinfluence,4=

veryhighinfluence.

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Step 1a: Define a grey pairwise influence comparison scale for thecomponents. In this article, we use a 5-level scale with the following scaleitems: 0¼ no influence, 1¼ very low influence, 2¼ low influence, 3¼ highinfluence and 4¼ very high influence. The grey scales for these linguistic valuesare defined in Table 3.

Step 1b: Develop the grey direct-relation matrix X by having evaluatorsintroduce the grey pairwise influence relationships (#xij

k) between the barriersin an 11� 11 matrix. All the principal diagonal elements are initially set to acrisp value of 0 (0¼ no influence). Four pairwise influence matrices for each ofthe four apparel manufacturing companies are shown in Tables 4, 5, 6, and 7.

Step 1c: Make the grey direct-relation matrix into a crisp matrix Z usingthe modified-CFCS process as exemplified by expressions (A5)–(A9). Theprocess will need to be completed for each of the evaluators’ direct-relationmatrices. The overall crisp direct-relationship matrix for company 1 is shownin Table 8.

Stage 2: On the basis of the overall crisp direct-relation matrix Z, thenormalized direct-relation matrix N can be obtained through expressions (1)and (2). The N matrix for company 1 is shown in Table 9.

N ¼ sZ ð1Þ

s ¼ 1

max1pipn

Pnj¼1

zij

; i; j ¼ 1; 2; . . . ; n: ð2Þ

Stage 3: The total relation matrix (T ) is determined by expression (3), whereI represents an n� n identity matrix. The matrix for company 1 is shown inTable 10.

Table 8: The overall crisp direct-relationship matrix Z for company 1

Barriers B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11

B1 0.000 0.950 0.950 0.050 0.950 0.650 0.950 0.350 0.063 0.650 0.950

B2 0.950 0.000 0.950 0.050 0.950 0.650 0.650 0.650 0.000 0.950 0.950

B3 0.000 0.950 0.000 0.050 0.650 0.650 0.350 0.650 0.063 0.950 0.350

B4 0.000 0.650 0.950 0.000 0.950 0.950 0.350 0.350 0.063 0.050 0.950

B5 0.000 0.950 0.950 0.950 0.000 0.950 0.350 0.350 0.063 0.650 0.950

B6 0.000 0.950 0.950 0.950 0.950 0.000 0.350 0.350 0.063 0.350 0.950

B7 0.350 0.950 0.950 0.950 0.950 0.950 0.000 0.650 0.375 0.950 0.350

B8 0.000 0.950 0.950 0.650 0.650 0.950 0.950 0.000 0.375 0.650 0.650

B9 0.650 0.950 0.950 0.650 0.650 0.650 0.950 0.650 0.000 0.650 0.050

B10 0.650 0.950 0.950 0.650 0.650 0.650 0.950 0.950 0.688 0.000 0.650

B11 0.000 0.950 0.950 0.950 0.650 0.650 0.350 0.350 0.375 0.050 0.000



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T ¼ N þN2 þN3 þ � � �X1i¼1

Ni ¼ Nð1�NÞ�1 ð3Þ

Stage 4: Developing the causal influence and digraph diagram inDEMATEL requires two steps.

Step 4a: Determine row (Ri) and column (Dj) sums for each row i andcolumn j from the total relation matrix (T ). That is:

Ri ¼Xnj¼1

tij 8i ð4Þ

Dj ¼Xni¼1

tij 8j ð5Þ

Table 9: The normalized direct-relation matrix (N) for company 1


B1 0.000 0.123 0.123 0.006 0.123 0.084 0.123 0.045 0.008 0.084 0.123

B2 0.123 0.000 0.123 0.006 0.123 0.084 0.084 0.084 0.000 0.123 0.123

B3 0.000 0.123 0.000 0.006 0.084 0.084 0.045 0.084 0.008 0.123 0.045

B4 0.000 0.084 0.123 0.000 0.123 0.123 0.045 0.045 0.008 0.006 0.123

B5 0.000 0.123 0.123 0.123 0.000 0.123 0.045 0.045 0.008 0.084 0.123

B6 0.000 0.123 0.123 0.123 0.123 0.000 0.045 0.045 0.008 0.045 0.123

B7 0.045 0.123 0.123 0.123 0.123 0.123 0.000 0.084 0.048 0.123 0.045

B8 0.000 0.123 0.123 0.084 0.084 0.123 0.123 0.000 0.048 0.084 0.084

B9 0.084 0.123 0.123 0.084 0.084 0.084 0.123 0.084 0.000 0.084 0.006

B10 0.084 0.123 0.123 0.084 0.084 0.084 0.123 0.123 0.089 0.000 0.084

B11 0.000 0.123 0.123 0.123 0.084 0.084 0.045 0.045 0.048 0.006 0.000

Table 10: The total-relation matrix (T) for company 1


B1 0.128 0.555 0.566 0.305 0.502 0.455 0.388 0.312 0.114 0.384 0.464

B2 0.241 0.462 0.582 0.315 0.515 0.468 0.369 0.356 0.113 0.426 0.478

B3 0.103 0.445 0.343 0.232 0.371 0.362 0.256 0.284 0.091 0.342 0.311

B4 0.090 0.418 0.461 0.232 0.412 0.403 0.247 0.245 0.085 0.237 0.387

B5 0.114 0.513 0.526 0.381 0.358 0.455 0.290 0.287 0.103 0.345 0.437

B6 0.106 0.491 0.503 0.366 0.449 0.328 0.275 0.272 0.096 0.298 0.420

B7 0.185 0.608 0.623 0.442 0.552 0.538 0.313 0.380 0.162 0.450 0.444

B8 0.133 0.567 0.580 0.385 0.482 0.502 0.396 0.278 0.154 0.389 0.439

B9 0.217 0.579 0.592 0.383 0.493 0.479 0.411 0.364 0.109 0.404 0.381

B10 0.230 0.634 0.649 0.423 0.540 0.525 0.445 0.429 0.206 0.360 0.490

B11 0.098 0.455 0.467 0.340 0.385 0.375 0.255 0.251 0.122 0.244 0.278

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The row values Ri are the overall direct and indirect effect of barrier i onother barriers for EFCP. Similarly, the column values Dj represent the overalldirect and indirect effects of all barriers on barrier j. We separately determinedthese results for each of the four companies.

Step 4b: Determine the overall importance or prominence (Pi) of barrier iand net effect (Ei) of barrier i usingexpressions (6) and (7).

Pi ¼ fRi þDjji ¼ jg ð6Þ

Ei ¼ fRi �Djji ¼ jg ð7Þ

The larger the value of Pi, the greater the overall prominence (visibility/importance/influence) of barrier i in terms of overall relationships with otherbarriers. If Ei40 then barrier i is a net cause, or foundation, for other barriers.If Eio0, then barrier i is net effect of other barriers (Tzeng et al, 2007). Thesevalues may then be plotted onto a two-dimensional axis for each barrier.The results for four companies are shown in Table 11, and in Figures 1–4,respectively.

Stage 5: Develop the overall DEMATEL prominence-causal graphs for theaggregation of the four companies. This stage can be separated into twosubsteps.

Step 5a: Using the average of pair-comparison values from Tables 4, 5, 6 and 7,we develop a direct-relation matrix for barriers to EFCP for all four companiesin aggregation. We use the same four DEMATEL stages above. We determinethe aggregated overall structures (prominence and net cause) for the barriers.The aggregated results are shown in the final two columns of Table 11. Theoverall total-relation matrix T for the aggregation of the four companies isshown in Table 12. Figure 5 shows a graphic of the overall aggregated barriers’prominence and net-effect results.

Step 5b: To observe general patterns and relationships amongst all thebarriers simultaneously and in pairs, we further develop an overall prominence-causal relationship diagram (see Figure 6). The development of the digraphs(arrows) in Figure 6 shows the interrelationships amongst each of the indivi-dual barriers to EFCP. As the number of relationships can include all thepossibilities, we only mapped those relationships that are over a threshold y.Owing to the large number of barriers, we chose a high threshold value. Wecalculated this value by taking the mean and standard deviation of the values tijfrom the T matrix, and added one standard deviation to the mean. Thus,y¼ 0.442. All the relationships meeting or exceeding the threshold value areunderlined in the overall T matrix (Table 12). We then plot these dyadicrelationships. Two-way significant relationships are represented by solid lines,whereas one-way relationships are represented by dashed lines.



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Table

11:Thedegreeofprominence

andnet-cause/effectofbarriers

forcompaniesandaggregatedaveragevalue

Barrier

Company1

Company2

Company3

Company4

Aggregated

Prominence

Net

effect

Prominence

Net

effect

Prominence

Net

effect

Prominence

Net

effect

Prominence

Net

effect

B1

5.816

2.529

5.077

0.295

8.523

�0.874

2.768

2.552

6.103

1.353

B2

10.05

�1.402

5.599

0.447

8.213

�0.416

11.131

�2.267

9.055

�0.668

B3

9.032

�2.752

4.707

1.131

7.996

0.300

10.117

�2.085

6.928

�2.150

B4

7.019

�0.588

3.869

2.026

7.634

0.517

8.626

�0.698

7.094

�0.670

B5

8.868

�1.251

5.501

0.429

6.914

0.426

10.850

�1.544

8.387

�0.344

B6

8.493

�1.286

6.551

�1.534

8.149

0.074

9.023

�1.212

8.562

�0.874

B7

8.343

1.054

4.573

1.281

8.760

1.048

9.555

0.641

8.242

1.096

B8

7.763

0.846

4.188

�0.818

7.981

�0.136

9.022

1.424

7.379

0.334

B9

5.767

3.057

3.931

0.603

6.915

0.145

6.603

3.383

6.062

1.888

B10

8.811

1.053

2.954

�2.759

8.072

�1.018

9.443

1.589

7.407

�0.340

B11

7.797

�1.260

4.612

�1.101

8.436

�0.066

9.795

�1.783

7.816

�0.940

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Results and Discussion

We summarize the prominence of barrier and net-cause/effect values for fourindividual companies and overall values in Table 13. The results in Table 13show that we may categorize the four companies into two groups according tonet-effect values, as well as prominence for sets of barriers. Overall, because ofthe similarities we have Companies 1 and 4 as one company grouping, whereascompanies 2 and 3 are another grouping. These similarities are furtherdescribed in the following sections.

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

0.0

R-D

B1

B2

B3

B4B5B6

B7B8

B9

B10

B11

R+D

12.010.08.06.04.02.0

Figure 1: DEMATEL prominence-causal graphs for Company 1.

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

0.0

B1 B2

B3

B4

B5

B6

B7

B8

B9

B10

B11

R+D

R-D

8.06.04.02.0




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Results for group 1

Both apparel manufacturing companies 1 and 4 identify five key net-causebarriers with net-effect scores over 0. Two barriers for these companies, thatare highly valued causes, overlap. The barriers are lack of human resourcecapabilities for EFCP (B9) and hard-to-enter EFC major markets (B1). Theremaining three net-cause barriers are also similar for these two companies, butwith slightly different rankings. These similar net-cause barriers include:immaturity of large-scale EFCP (B7), lack of technology for EFCP (B8) andhigh purchasing cost for environmentally sound materials (B10).

-2.0

-1.0

0.0

1.0

2.0

0.0

B1

B2

B3

B4B5

B6

B7

B8

B9

B10

B11

R+D

R-D

10.08.06.04.02.0


-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

0.0

B1

B2B3

B4

B5B6

B7

B8

B9

B10

B11

R+D

R-D

12.010.08.06.04.02.0


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-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

0.0

B1

B2

B3

B4B5

B6

B7

B8

B9

B10

B11

R-D

R+D

10.08.06.04.02.0

Figure 5: Overall DEMATEL prominence-causal graphs for four companies.

Table 12: The overall total-relation matrix (T) for aggregation of four companies


B1 0.173 0.459 0.397 0.264 0.394 0.406 0.338 0.323 0.191 0.380 0.403

B2 0.260 0.396 0.457 0.297 0.452 0.460 0.370 0.383 0.208 0.440 0.470

B3 0.136 0.291 0.210 0.158 0.261 0.286 0.220 0.217 0.116 0.248 0.246

B4 0.214 0.443 0.448 0.246 0.425 0.470 0.314 0.320 0.186 0.357 0.446

B5 0.231 0.465 0.461 0.342 0.340 0.473 0.337 0.332 0.212 0.389 0.439

B6 0.248 0.479 0.399 0.322 0.425 0.351 0.325 0.312 0.187 0.369 0.428

B7 0.282 0.546 0.519 0.372 0.513 0.534 0.322 0.406 0.250 0.430 0.495

B8 0.196 0.460 0.438 0.302 0.418 0.469 0.355 0.263 0.197 0.370 0.388

B9 0.232 0.473 0.439 0.299 0.409 0.471 0.374 0.361 0.161 0.350 0.407

B10 0.209 0.409 0.390 0.290 0.377 0.384 0.334 0.311 0.203 0.266 0.360

B11 0.194 0.440 0.382 0.333 0.353 0.414 0.284 0.293 0.175 0.272 0.297

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

0.0B10

B1

B2

B3

B4

B5

B6

B7

B8

B9

B11

R-D

R+D

10.09.08.07.06.05.04.03.02.01.0

Figure 6: Overall DEMATEL prominence-causal relationship diagram.



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The barriers with high prominence for Companies 1 and 4 are similar. Thethree most prominent barriers are the same in both companies and include lowEFC preference/requirement compared to price and quality in current market(B2), difficult-to-quantify EFC benefits (B3) and lack of strategic planning forEFCP (B5). Interestingly, the most prominent barriers are also ones that have agreater net effect, with the greatest negative net-effect scores. This result meansthat other factors may need to be initially addressed in order to remove thesebarriers for these two companies.

Results for group 2

Company 2 shows seven barriers that can be identified as net-cause barriers,whereas Company 3 has five net-cause barriers. The four barriers with thehighest causation scores are similar for the two companies. These net-causebarriers are no top management support for EFCP (B4), immaturity oflarge-scale EFCP (B7), difficult-to-quantify EFC benefits (B3) and lack ofstrategic planning for EFCP (B5). The lack of planning and top managementsupport at these two companies shows that they are relative laggards (to theprevious group of Companies 1 and 4) in EFCP.

The prominence of barriers is different in Companies 2 and 3. Company 2considers lack of knowledge or information on EFC market potential as themost important barrier (B6), and low EFC preference/equipment compared toprice and quality in current market (B2) as the second most important barrier.Company 3 has a different perspective to the other three companies, andconsiders immaturity in large-scale EFCP (B7) as the most prominent barrier.

Overall results and discussions

Considering results for the four individual companies, as well as the overallresults, we can identify the most important barriers and the most importantreasons for barrier causation.

Table 13: Summary of degree of prominence and net-cause/effect values of barriers

Company Ranking Net Effects Ranking Prominence

1 B9, B1, B7, B10, B8 B2, B3, B5, B10, B6

2 B4, B7, B3, B5, B2, B9, B1 B6, B2, B5, B1, B3

3 B7, B4, B5, B3, B6 B7, B1, B11, B2, B6

4 B9, B1, B10, B8, B7 B2, B3, B5, B7, B10

Overall B9, B1, B7, B8 B2, B6, B5, B7

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The three most important barriers are low EFC preference/requirement,compared to price and quality in the current market (B2), lack of knowledgeor information on EFC market potential (B6) and lack of strategic planningfor EFCP (B5). The most important reasons affecting EFCP are primarilyinternal capability related. These items are lack of human resource capabilitiesfor EFCP (B9), immaturity of large-scale EFCP (B7) and lack of techno-logy for EFCP (B8). An external cause barrier is hard-to-enter EFC majormarkets (B1).

Figure 6 shows that two barriers are the results of other barriers, whereasthey are not significant causes for any other barriers. These barriers are B3(difficult-to-quantify EFC benefits) and B11 (lack or low enforcement ofrelated regulatory requirements). The significant causes of these two barriersare similar, including B2 (low EFC compared to price and quality in currentmarket), B4 (no top management support) and B7 (immaturity of large-scale EFCP). Such results indicate that B3 (difficult-to-quantify EFC bene-fits) and B11 (lack or low enforcement of related regulatory requirements)are generally not serious issues and can be overcome if causal barriers areaddressed.

A more in-depth check of Figure 6 shows that B2 (low EFC preference/requirement compared to price and quality in current market) is a key cause ofB3 (difficult-to-quantify EFC benefits). B2 results from a number of barriers,including B1, B4, B7, B8 and B9, whereas it also has two-way cause–effectrelationships with B5 and B6. Such results indicate that internal barriers resultin low consumer preference for EFC, which may be partly because of consumersuspicions concerning true EFC.

In Figure 6, barrier B7 is the greatest causation barrier. That is, thesecompanies consider the relative novelty of EFCP innovation as the majorbarrier, setting the foundation for other barriers. This situation is representa-tive of the lack of knowledge and capabilities that would come with larger-scaleproduction of EFC. Thus, it can be argued that as the industry matures andmore organizations adopt EFCP practices, a major barrier will be overcome,which would make it easier to address many of the other concerns.

Conclusions

We have introduced a number of issues facing apparel manufacturingorganizations in China. Initially, various barriers to the adoption of EFCP inthese organizations were identified. These barriers were then evaluated through astrategic evaluation methodology using grey-scale mathematics and DEMATEL.The technique was useful in integrating the perceptions and perspectives ofvarious apparel manufacturing companies and managers. A series of resultswere grouped into two sets of companies. The technique provided some strategic



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scenarios of barrier relationships for the specific companies. Aggregation pro-vided a slightly broader picture for all four companies. Clearly, additionaldata and information will allow for broader generalization of these exploratoryresults.

The major contributions of our study include: (1) clear identification of thelocus of barriers facing EFCP in China; (2) introduction of a strategicstructural planning tool for this problem; and (3) real-world data gathering toexplore some of the major relationships amongst these barriers.

Implications and future research

The study showed that EFCP barriers among these Chinese apparel companiesare mainly marketing related and capability barriers. Low EFC preference/requirement compared to price and quality in the current market is themost prominent barrier. Export is a key incentive for Chinese companies toproduce environmental products. Thus, governments, not only Chinese, butalso those in developed countries to which Chinese organizations haveexported clothes, should develop feasible measures to foster EFC marketdevelopment and clarity. How to develop reasonable policies still requiresfurther investigation. Lack of knowledge or information on EFC marketpotential is another important barrier. Information should be made publiclyavailable by governments or by organizations encouraged and monitored bygovernments.

The basic causation barriers are mainly internal capability related. Similar toother environmental practices or other industries, lack of human resourcecapabilities for EFCP is found to be the most basic barrier for Chinese apparelcompanies. Human resource recruiting and training should be a first step forChinese apparel companies to overcome barriers to implement EFCP.Immaturity of large-scale EFCP and lack of technology for EFCP are anothertwo critical capability-based barriers. Chinese government encouragement ofEFCP and development of related technology should be pursued. Govern-mental policies related to subsidies and preferable tax policies can also be usedto encourage organizations to adopt more EFC practices, furthering theirmovement down the learning curve.

Acknowledgements

This work was supported by a grant from National Science Fund fordistinguished young scholars (71025002), and the National Natural ScienceFoundation of China Project (71033004, 70772085) and One HundredOutstanding Scholars Project (CAS2008-318).

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About the Authors

Qinghua Zhu is a professor in the School of Business Management at DalianUniversity of Technology. She received her bachelor’s and master’s degrees inelectrical engineering from Southeast University, China and her PhD in systemsengineering from Dalian University of Technology. Her main research interestsare operations management and corporate environmental/social management.She has published numerous papers in both English and Chinese journals. Shereceived the Journal of Operations Management 2004 Best Paper Finalist Award,and the 2009 Academy of Management Best Paper Award for emerging markets.

Joseph Sarkis is a professor of Management within Clark University’sGraduate School of Management. He earned his PhD from the University ofBuffalo. His research interests are in operations and technology management,as well as business and the natural environment, on which topics he haspublished widely. He is currently editor-in-chief of Management ResearchReview and departmental editor for IEEE Transactions on EngineeringManagement. He has also been an ATT Industrial Ecology Fellow.

Yong Geng is currently the chaired professor on circular economy and industrialecology at the Institute of Applied Ecology of the Chinese Academy of Sciences.He is currently managing key national projects from the Natural ScienceFoundation of China (NSFC) and Ministry of Science and Technology (MOST),as well as Chinese Academy of Sciences (CAS). His research fields include indus-trial symbiosis, eco-industrial parks, low-carbon societies, green supply-chainmanagement and cleaner production. He has published over 30 papers in peer-reviewed international journals and three books in the above fields.

Note

1 The Yangtzi River Delta Region and the Pearl River Delta Region are two key bases of Chinese

apparel industry. The Shanghai area, in the Yangzi River Delta Region, is the most important

clothes production base, with the longest history, which mainly includes Shanghai city itself,

Suzhou city in Jiangsu Province and Hangzhou city in Zhejiang Province. Taicang is one of the

key clothes production bases in Suzhou.

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Appendix

A grey system theory

Grey system theory can be used to solve uncertainty problems in cases withdiscrete data and incomplete information (Deng, 1989). It can bringsatisfactory outcomes even with relatively limited and incomplete data orwith great variability in factors (Li et al, 1997).

We will now introduce some general notation and operations for greysystems. Let x denote a closed and bounded set of real numbers. A greynumber #x is defined as an interval with known upper and lower bounds butunknown distribution information for x (Deng, 1989). That is, �x ¼½�x; ��x� ¼ ½x0 2 xj�xpx0p ��x� where x and ��x are the lower and upperbounds of #x, respectively.



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Some basic grey number mathematical operations are represented by thefollowing relationships (expressions 1–4 (A1)–(A4)):

�x1 þ�x2 ¼ ½x1 þ x2; �x1 þ �x2� ðA1Þ

�x1 ��x2 ¼ ½x1 � �x2; �x1 � x2� ðA2Þ

�x1�� x2 ¼½minðx1x2; x1�x2; �x1x2; �x1�x2Þ;maxðx1x2; x1�x2; �x1x2; �x1�x2Þ� ðA3Þ

�x1 ��x2 ¼ ½x1; �x1��1

x2;1

�x2

� �ðA4Þ

To deal with problems of decision making in a grey environment, we convertfuzzy data into crisp scores (CFCS) through a defuzzication method. Thisapproach has been demonstrated to be more effective to alternative methods(Opricovic and Tzeng, 2003; Wu and Lee, 2007).

Let us define #xijp as the grey number for an evaluator p that will evaluate

the influence of barrier i on barrier j. In addition, �xpij and ��xpij are respectivelythe lower and upper grey values by an evaluator p for the relationshipevaluation between barrier i to barrier j.

That is: �xpij ¼ ½�xpij ; ��xpij� .

The modified-CFCS method involves a three-step procedure described asfollows:

(1) normalization

�expij ¼ ð�xpij �minj�xpijÞ=Dmax

min ðA5Þ

��expij ¼ ð ��xpij �minj

��xpijÞ=Dmaxmin ðA6Þ

where

Dmaxmin ¼ max

j��xpij �min

j�xpij ðA7Þ

(2) determination of a total normalized crisp value

Ypij ¼

�expijð1��expijÞ þ ð ��expij� ��expijÞ� �1��expij þ ��expij� � ðA8Þ

(3) computation of final crisp values

zpij ¼ min

j�xpij þ Y

pijD

maxmin ðA9Þ

Zhu et al
