Identification and Analysis of Barriers to Sustainable ... · 5.3 Co-relation Between Barriers 42...

Identification and Analysis of Barriers to Sustainable Supply Chain Management

Practices: A Case Study

Md. Abdul Moktadir

MASTER OF ENGINEERING IN ADVANCED ENGINEERING MANAGEMENT

Department of Industrial and Production Engineering

BANGLADESH UNIVERSITY OF ENGINEERING AND TECHNOLOGY

March 2017

i

Identification and Analysis of Barriers to Sustainable Supply Chain Management

Practices: A Case Study

by

Md. Abdul Moktadir

MASTER OF ENGINEERING IN ADVANCED ENGINEERING MANAGEMENT

Department of Industrial and Production Engineering

BANGLADESH UNIVERSITY OF ENGINEERING AND TECHNOLOGY

March 2017

ii

CERTIFICATE OF APPROVAL

iii

CANDIDATE’S DECLARATION

iv

This Work is Dedicated to My

Parents

v

Contents

Certificate of Approval ii

Candidate‘s Declaration iii

Contents v

List of Tables vii

List of Figures viii

Nomenclature ix

Acknowledgement x

Abstract xi

Chapter-1

Introduction

1.1 Introduction 1

1.2 Objectives of the Thesis 3

1.3 Scope of the Thesis 4

Chapter-2

Literature Review

2.1 Supply Chain Management 5

2.2 Sustainable Supply Chain Management 6

2.3 Overview of Leather Sector of Bangladesh 8

2.4 Barriers to Sustainable Supply Chain Management Implementation 11

Chapter-3

Methodology

3.1 Research Methodology 14

3.2 Solution Methodology 16

3.2.1 Grey Theory 16

3.2.2 DEMATEL Method 16

3.2.3 Application of Grey-DEMATEL Approach 17

vi

3.2.4 Procedure of Grey-DEMATEL Approach 18

Chapter-4

A Case Study

4.1 Application of the Proposed Research Framework 22

4.2 Data Collections 23

Chapter-5

Results and Discussions

5.1 Cause Group 39

5.2 Effect Group 41

5.3 Co-relation Between Barriers 42

5.4 Sensitivity Analysis 46

5.5 Managerial Implications 53

Chapter-6

Conclusions and Recommendations

6.1 Conclusions 55

6.2 Recommendations 56

References 57

Appendix A 70

vii

List of Tables Table 2.1 Estimated annual production capacity of raw materials 10

Table 2.2 Estimated annual production of finished products 10

Table 2.3 Estimated export capacity 10

Table 2.4 Bangladesh‘s export of leather and leather products (value in million US$) 11

Table 4.1 Profile of team members 24

Table 4.2 Identification of major barriers to adoption of sustainable supply chain

management

70

Table 4.3 Selection of common barriers with the help of experts and academia

feedback

24

Table 4.4 Linguistic assessment and related grey values 26

Table 4.5 Grey relation matrix for barriers of SSCM implementation computed by

Expert-1

27


Expert-2

28


Expert-3

29


Academic-1

30

Table 4.9 Average grey relation matrix for barriers of SSCM implementation 32

Table 4.10 Crisp relation matrix for barriers of SSCM implementation 33

Table 4.11 Normalized direct crisp relation matrix for barriers of SSCM implementation 34

Table 4.12 Total relation matrix for barriers of SSCM implementation 35

Table 4.13 Cause-effect parameter for barriers of SSCM implementation 36

Table 5.1 Final evaluation of barriers with ranking 44

Table 5.2 Weight assigned for sensitivity analysis to different evaluator 46

Table 5.3 Cause –effect parameters getting from sensitivity analysis 47

Table 5.4 Ranking of cause –effect relationship among common barriers obtained from

sensitivity analysis

48

viii

List of Figures

Fig. 3.1 Research flow chart 15

Fig. 4.1 Digraph shows the casual relationship among different barriers to

implementation of SSCM practices

38

Fig. 5.1 Barriers to sustainable supply chain management practices represented in

zones

45

Fig. 5.2 Digraph obtained on sensitivity analysis showing casual relation among

barriers of SSCM practices by giving highest weight to Expert-1

49



50



51


barriers of SSCM practices by giving highest weight to Academic-1

52

ix

Nomenclature

SCM : Supply Chain Management

TSCM : Traditional Supply Chain Management

SSCM

: Sustainable Supply Chain Management

DEMATEL : Decision Making Trail and Evaluation Laboratory

θ : Threshold Value

CFCS : Converting Fuzzy Values into Crisp Scores

MCDA : Multi Criteria Decision Attribute/Analysis

1yij : Grey relation number

ijy : Average grey number

.

ijy : Normalized lower limit value

.

ijy : Normalized upper limit value

ijZ : Normalized crisp value

*Z : Final crisp value

P : Normalized direct crisp relation matrix

T : Total relation matrix

I : Identity matrix

ri : Represents the sum of ith row elements in matrix T

cj : Represents the sum of jth column elements in matrix T

x

Acknowledgement

I acknowledge my profound indebtedness and express sincere gratitude to my supervisor and

mentor Dr. Syed Mithun Ali, Assistant Professor, Department of Industrial & Production

Engineering (IPE), BUET, Dhaka. He provided proper professional guidance, supervision

and valuable suggestions at all stages to carry out this thesis work. I have been privileged to

be a part of his research group, where I have enjoyed developing myself as an independent

researcher in the area of supply chain management. I am proud to have him as my supervisor

for Master‘s thesis.

I wish to express my heartiest gratitude to my respected teachers at the Department of

Industrial & Production Engineering (IPE), BUET and I offer my deepest appreciation to my

whole family - without all their support and encouragements throughout my studies I would

have never been able to reach what I have reached today. I would also like to thank my

dearest friends for comforting me and for helping me to discover myself.

Finally, I am grateful to Almighty Allah for giving me the strength, guidance, and

determination to achieve this success.

xi

Abstract

Currently, leather industries of Bangladesh are facing considerable amount of pressure to

adoption of sustainable supply chain management practices in traditional supply chain

network. The approach of incorporating sustainable supply chain management practices in

the traditional supply chain is becoming greatly important for the industry due to

environmental awareness, competitiveness, and government environmental policies. Hence,

SSCM implementation is a good practice of sustainable development in the competitive

world market due to its consideration for environmental, social and economic issues. There

are many barriers for adopting SSCM into leather processing industry of Bangladesh, but

these barriers do not ensure similar impact for all industrial sector and countries. To bridge

this gap, it is a crucial issue to identify most influential barriers to adopting SSCM practices.

In order to implement SSCM practices, a careful analysis of the most common barriers that

obstruct the whole process must be identified.

In this study, a numerous 35 barriers of SSCM implementation are identified through detailed

literature review and deeper survey on leather processing industry. Most common 20 barriers

are selected with the help of industrial and academic experts for the analysis of the cause-

effect and prominence relationship among them. The main contribution of this study is to

identify the key barriers and find out the cause-effect relationship among barriers to the

implementation of SSCM in the leather processing industry of Bangladesh by using a blended

grey based DEMATEL approach. The results of the thesis aim to support the leather

processing industry in a way that the industrial manager can identify most influential barriers

and this emerges as the crucial part of eradicating barriers. The results show that the ‗Lack of

awareness of local customers in green products‘ and ‗Lack of commitment from top

management‘ seem to be of greater priority in the casual group. Cause–effect relationship is

plotted to facilitate decision maker to identify casual barriers that need attention during

SSCM implementation in the traditional leather supply chain.

1

Chapter 1

Introduction

1.1 Introduction

Supply chain management (SCM) is the management of a supply chain network

of interconnected businesses involved in the final destination of product and service

packages required by end customers (Harland, 1996). It represents the coordination of key

business processes among industry partners to maximize value for the end customers

(Janvier-James, 2011). SCM plays a key role in the sustainable development of

manufacturing industry. It is an integrated process to maximize the profit of industry. The

rapid development of any industrial sector requires an increase of supply chain activities

(Holweg and Pil, 2008). Such increase of supply chain activities is an important issue in

the deterioration of natural resources, waste generation, water pollutions, harmful emission

of various gas and disruptions in the eco-system. To minimize the environmental

depletion, sustainable supply chain management practices help to integrate the

environmental management practices with supply chain management in order to prevent

the environmental degradation or to preserve so that further degradation is not allowed

(Diabat and Govindan, 2011). Therefore, sustainable supply chain management practices

have been a popular 21st-century trend among different industrial activities such as food

packaging (Smith, 2008), mining (Ting et al., 2014). Thus, today‘s business fields of

developed countries are facing competitive regulatory and social pressures for adopting

sustainable supply chain practices. Recent studies on sustainable supply chain management

practices show the pressures from government, stakeholder and customer to effectively

adopt sustainability issues into their supply chain network (Seuring and Müller, 2008).

2

Sustainable supply chain management helps to minimize or eliminate waste in all

forms including harmful gas emission, waste minimization, water pollutions, soil

pollutions, solid waste reductions. Majority of supply chain management innovations in

the 20th century aimed to the reduction of waste for economic purpose rather than

protection of the environment but the 21st century aims at reduction of waste for protection

of the environment (Pagell and Wu, 2009; Seuring and Müller, 2008; Walker and Jones,

2012; Zailani et al., 2012). Recent researches show that in the next couple of decades, most

of the Asian manufacturer will face environmental issues. In the context of Bangladesh for

leather processing factory, considering an environmental sustainable point of view,

traditional supply chain management needs to be modified sustainable supply chain

management. Various organizations of developed countries adopt manifold environmental

management strategies such as adoption of cleaner technology (Grutter and Egler, 2004),

ISO 14001 certifications (Nawrocka, 2008), and environmental management systems to

minimize the adverse environmental effect of their supply chain (Nawrocka et al., 2009).

During the adoption of sustainable supply chain management in traditional supply chain

management, some barriers can be an obstacle the whole system of the supply chain

(Sajjad et al., 2015). It is important to eradicate barriers to implementing sustainable

supply chain management practices in industrial fields. However, it is not possible to erase

all barriers simultaneously. Hereafter industries should identify and analysis those barriers

which have to be essentially removed during the adoption of sustainable supply chain

implementation.

The goal of this study is the identification and analysis of multiple barriers through

the grey based DEMATEL approach so that an industry might be minimizing the effect of

barriers to sustainable supply chain implementation. This study addresses two-phased

research which includes research methodology: an initial survey to identify major barriers

from existing literature review and deeper analysis of leather processing factory, and

solution methodology: identifications of common barriers and to find out most influential

barriers relevant to leather processing factory from the feedback of industry experts and

academic expert with the help of grey based DEMATEL approach. Barriers of the

sustainable supply chain are interlinked to other barriers. One barrier to adoption of

sustainable supply chain management practices has direct influence to the other barriers

3

(Xia et al., 2015). In order to effectively quantify the most common barriers to adoption of

SSCM practices, they should be ranked on basis of overall influence over other common

barriers. This study helps to find the cause-effect relation among other barriers to adopt

SSCM practices in the leather industry. Twenty barriers are identified to the adoption of

SSCM practices in the case of leather processing factory. After the study is conducted

casual relations of different barriers are plotted into digraph for prioritizing rank among

them.

Literature reveals that there is no work on analyzing and quantifying barriers to

sustainable supply chain management implementation in the context of leather industry of

Bangladesh. Even though, there are some studies on the sustainable development of other

fields (Ahmed et al., 2014; Azad et al., 2009; Biswas et al., 2004; Hossain et al., 2007;

Roy, 2013). Leather sector is a rising industrial sector of Bangladesh but till now no

research on it for sustainable development of Bangladesh. Thus, this study attempts to fill

this research gap in the sustainable supply chain literature with the help of grey-

DEMATEL approach. The major contribution of this study is identification and analyzing

of common barriers to adoption of sustainable supply chain management practices in the

leather field. During the implementation of sustainable supply chain management

practices, it is necessary to quantify the most influential barriers. A grey based DEMATEL

approach has been used in this thesis to effectively quantify the most influential barriers

among various common barriers. To realize this framework, a real life case study on

leather processing factory is also introduced.

1.2 Objectives of the Thesis

The overall aim of this thesis is to identify most influential barriers to sustainable

supply chain management practices in leather processing factory of Bangladesh. The

specific objectives of this thesis are as follows:

1. To identify major barriers to adoption of sustainable supply chain management

practices for a leather industry in Bangladesh.

4

2. To evaluate and analyze most influential barriers with the help of a grey-

DEMATEL approach.

1.3 Scope of the Thesis

The thesis is organized into six chapters including this one. The chapters are

structured in the following way: Chapter 1 represents the concept of supply chain, the

current condition of study, the research gap of the study and objectives of the study.

The rest of the thesis is organized as follows: Chapter 2 presents the literature

review of supply chain management, sustainable supply chain management, an overview

of leather sector of Bangladesh and barriers to sustainable supply chain management.

Research methodology, grey theory, DEMATEL method, application of grey-

DEMATEL approach and grey-DEMATEL solution methodology are presented in Chapter

3.

Chapter 4 describes a real case application of Bangladeshi leather processing

factory for modeling barriers to implementing sustainable supply chain management

practices.

Chapter 5 incorporates results and discussions on findings of this study and

sensitivity analysis is also given in Chapter 5.

Finally, conclusions and recommendations are presented in Chapter 6. References

and appendix are presented at the end of the thesis.

5

Chapter 2

Literature Review

2.1 Supply Chain Management

A supply chain is a dynamic activity and involves the constant flow of materials,

information, and funds. Therefore, supply chain management is the management of

materials, information, and funds as they move in a process from supplier to manufacturer

to wholesaler to retailer to consumer. Supply chain management involves coordinating and

integrating these flows among different companies (Chopra and Meindl, 2014). Supply

chain management helps to increase the profit of an organization as well as proper

utilization of resources. The main objective of supply chain management is to maximize

the profit of an industry. Hence supply chain success depends on the overall profitability of

a supply chain. Successful supply chain requires many decisions relating the decision of

flow of materials, information, and funds. Therefore, supply chain management helps to

manage such kinds of thing. Over the past decade, the traditional purchasing and logistics

functions have evolved into a broader strategic approach to materials and distribution

management known as supply chain management (Choon Tan, 2001). It is proved that

supply chain and supply chain management have played an important role in the business

efficiency and have attracted the attention of numerous academicians over the last few

years (Janvier-James, 2011). Supply chain management activity is the root of maximizing

profit of any kinds of industrial fields as well as service organizations. Therefore, it is

necessary to improve the supply chain management activities for the successful business.

6

2.2 Sustainable Supply Chain Management

Bangladesh is a developing country having a trend to increase economic growth

without considering the environment for increasing the production rates. The rapid

economic development and an over population destroy natural resources by polluting

water, air, and soil etc. (Hoque and Clarke, 2013). Hence, it is important to develop a

sustainable manufacturing framework in such a way that environmental depletion should

be minimized (Diabat and Govindan, 2011). Sustainable supply chain management is the

management of environmental, economic and social impacts and encouragement of good

manufacturing practices throughout the lifecycle of products. It helps to link development

and environmental issues and to force political and economic change locally, nationally,

and globally to overcome the problems (Zailani et al., 2012). SSCM is being achieved in

traditional supply chain management by considering the environmental, economic, and

social issue (Preuss, 2009). SSCM practices help to impart sustainable development of a

country which is the development that meets the needs of the present without

compromising the ability of future generations to meet their own needs (Paper, 2012). Eco-

friendly and cleaner technologies have played an important role in the leather industry for

sustainable development of the leather sector of Bangladesh. Hence, the implementation of

sustainable supply chain management practices in the leather industry of Bangladesh will

become one of the dominating factors for the survival of leather industry and its product

leather in near future. It is difficult to maintain a balance between human needs and

development without hampering resources. This study helps to develop a sustainable

supply chain framework by identifying and analyzing common barriers which are relevant

to leather processing factory of Bangladesh. Hence, these study will help to minimize

environmental degradation in such a way that the newly developed industry can consider

these barriers for starting their new business and also existing industry can convert their

traditional system to sustainable system.

Sustainable supply chain management practices are of top most concern for recent

world due to government regulation, customer expectation and the pressure imposed on the

buyer (Linton et al., 2007). SSCM, a cross-disciplinary field, has been growing popularity

both in industry and practitioners (Sarkis et al., 2011). Sustainable development is a

7

pattern of resource use that aims to human needs while protecting the natural resource so

that these needs cannot be met only for present but also for future (Kates et al., 2005). The

most adopted definition of sustainability is that of the Brundtland commission

―development that meets the needs of the present without compromising the ability of

future generation to meet their needs‖ (WCED, 1987, p.20 ; Paper 2012). The literature on

SSCM is still on the budding stage. Carter and Rogers (2008) mentioned sustainability is a

concept to gain long-term economic benefits by key integration of environmental, social,

and economic factors. Many researchers have indicated SSCM as an integrated approach

for minimizing ecological degradation (Esfahbodi et al., 2016; Harms, 2011).

Sustainability has become a popular global concern and hence motivated industrial

organizations are modifying their supply chain activities taking into consideration the

environmental, social and as well as economic impacts of their supply chains network

(Carter and Easton, 2011; Carter and Rogers, 2008). Sustainability is taken into

consideration by legislation, public awareness, and competitive opportunity. Sustainable

development is the better solution of reducing waste by proper utilization of the resource.

From this point of view, sustainable supply chain management is an activity that helps to

modify traditional supply chain. This modification turns to the sustainable development of

an organization. A truly sustainable organization can simultaneously achieve social,

environmental and economic benefits.

A wide range of issues like supply chain risk mitigation, greening in the supply

chain have to be incorporated in sustainable supply chain management. Along with this,

sustainable supply chain management approach includes product safety and performance,

protecting the environment, ensuring good governance thus making Bangladesh a good

place to work and live. The target of sustainable supply chain reduce is to reduce energy

consumption from operations, increase renewable energy use, reduce water consumption,

reduce hazardous waste generation, reduce environmental impacts from manufacturing etc

(Jayant and Azhar, 2014; Rauer and Kaufmann, 2015; Walker et al., 2008). As in

Bangladeshi leather industries, sustainability of supply chain is not maintained in

operational procedures due to the lack of proper law implementation or lack of proper law

existence. Also, scientific research and knowledge will definitely help private industries to

adopt the operational procedures to ensure SSCM and also to motivate government to

8

implement SSCM law to ensure sustainability. Operational implementation of SSCM in

industries should be a part of compliance maintenance as per International Standard

Organization. Along with supply chain, sustainability is also described as the potential to

reduce long term supply chain risks associated with resource depletion, population and

waste management (Govindan et al., 2014). During recent time, the micro-economic

application has been investigated in the field of engineering, operation, and supply chain

(Sarkis, 2012). In most of the case sustainability has described as ecological sustainability

with a little recognition of social and economic responsibilities (Maloni and Brown, 2006).

And almost all research conducted up to now has been done focusing on developed

countries (Zaabi et al., 2013). No research has been made in respect of Bangladeshi

context. Thinking about the adverse effect of the environment, top priority should be given

to maintaining and implementing sustainable supply chain to ensure a developed

infrastructure for the future generation of developing countries.

2.3 Overview of Leather Sector of Bangladesh

The government of Bangladesh has indicated leather sector as one of the most

growth and investment potential (ranked 5th) in the export earning sector (Paul et al.,

2013). Due to its high esteem expansion and less expensive work openings; the leather

sector has already been pronounced a thrust sector of the country. As of now Bangladesh

delivers and fares quality bovine and ovine, caprine (wild ox and bovine; sheep and goat)

leather that have a decent nearby and global notoriety for quality skins (Paul et al., 2013).

With export of quality leather, Bangladesh also export a huge amount of leather goods like

ladies bag, backpack, wallet, belts, travel bag etc. and leather footwear to developed

countries like Chaina, France, Italy, Germany, USA, UK, Japan, Spain, UAE ( Technical

Report, 2013). The entire leather sector of Bangladesh meets only 0.5% of the world‘s

leather demand which worth is USD 75 billion (Paul et al., 2013).

In Bangladesh, approximately 187 tanneries are located in the Hazaribagh area of

Dhaka that produces 180 million square feet of hides and skins per year (Technical Report,

2013). The supply-cycle of raw skins and hides 40-45% of the annual supply available

during the festival of Eid-ul-Azha, which is the major source of producing quality leather.

9

However, only about 40 tanneries are utilizing a major portion of their installed capacity

indicating ―sickness‖ existing in the sub-sector. This leather sector has a long established

tanning industry which produces around 1.13% of the world‘s leather from a local supply

of raw hides and skins ( Technical Report, 2013). Most of the tanneries of Bangladesh do

not have proper effluent treatment plants and every day those tanneries generate 20,000m3

of tannery effluent and 232 tones of solid waste. This effluent and solid waste are one of

critical issue for sustainable manufacturing practices in the leather industry. To minimize

this critical issue, specific cleaner technologies are required to adoption of sustainable

supply chain management practices in leather industries of Bangladesh ( Technical Report,

2013).

A newly established leather zone is expected to bring a clear conversion to the

leather industry with increasing green production, product diversification and new product

systems with increasing manufacturing sustainability of the sector. Sustainable

manufacturing practices and cleaner production will be a key issue for the development

nation destroying the environment. The leather sector of Bangladesh requires sustainable

manufacturing practices to achieve international standards in technical, environmental,

safety, and commercial aspects, and to attain competitiveness in the world market.

In addition to 2500 small footwear manufacturer, there are 30 modern shoe

manufacturers in Bangladesh, which produces quality footwear and export to developed

countries. The footwear sector is a top value added sector which earned revenues in an

amount of USD 483.81 million during 2014-15 fiscal years whereas leather sub-sector

earned revenues in excess of USD 397.54 million during 2014-15.

.

Leather goods sector is another rising sector as even, without large investment

could possibly to build industry. Besides, 3,500 MSMEs there are around 100 small-to-

medium leather goods manufacturers and a small number of larger manufacturers (

Technical Report, 2013). The leather goods manufacturing sector is ideal for young

people, women and micro entrepreneurs to start off in, based on the volume of start-up

costs and low capital investment. Leather goods manufacturing sector can also offer the

10

opportunity to achieve industrial experience and helps to transform to footwear or other

sub-sector. The leather goods sector earned revenue USD 249.16 million during the fiscal

year of 2014-15. The entire sector directly employs approximately 850,000 people. 53% of

the workforces are ladies in the leather and footwear ventures of Bangladesh.

Table 2.1: Estimated annual production capacity of raw materials

Item Capacity

Bovine hides and skins 9 million pieces

Sheep skins and lamb skins 16 million pieces

Light leather from sheep and goats 6.14 million pieces

Source: Bangladesh Livestock Research Institute & Bangladesh Tanners Association (BTA), 2015

Table 2.2: Estimated annual production of finished products

Item Amount Year

Leather Footwear 364.5 million pairs 2013

Leather Belts 1.7 billion units 2013

Leather Bag 80.22 million pieces 2012

Small Leather Goods 3.1 billion pieces 2013

Source: Baseline Supply Report on Leather Goods and Footwear Industries in Bangladesh, 2015

Table 2.3: Estimated export capacity

Item Capacity

Leather Footwear 12 million pairs

Espadrilles 2 million pieces

Leather Goods 1.8 million pieces

Source: LFMEAB, 2015

11

Table 2.4: Bangladesh‘s export of leather and leather products (value in million $)

Category 2011-12 2012-13 2013-14 2014-15

Leather 330.16 399.73 505.54 397.54

Leather

Products

99.36 161.62 240.09 249.16

Footwear 335.51 419.32 378.54 483.81

Total 765.03 980.67 1124.17 1130.51

Growth 17.51% 28.19% 32.12% .56%

Source: Bangladesh Export Promotion Bureau, 2015

2.4 Barriers to Sustainable Supply Chain Management

There are lots of barriers to adoption of sustainable supply chain management

practices in the traditional supply chain. In the context of Bangladesh, it is necessary to

identify barriers to implementing sustainable supply chain management practices,

especially for leather processing factory. In this section, this thesis shows the discussion on

most common barriers of sustainable manufacturing practices context of leather processing

factory of Bangladesh.

In the category of environment, plenty of barriers are present in Bangladesh. Strict

environmental regulations and reduction raw material resources have given importance to

SSCM implementation (Richey et al., 2005). Lack of Eco-Literacy amongst supply chain

partner is one of them. Lack of eco-literature in leather supply chain is the most important

barriers. Supply chain partner not have deeper knowledge about sustainable manufacturing

practice. Eco-literacy means the expertise understanding of the workforce resulting in

proactive responses when tackling environmental issues, rather than reactive responses. In

many of the research take this barrier for their research work. Lack of environmental

requirement, lack of practice on reverse logistics, lack of awareness of local customers in

the green product are the most common barriers in respect to environmental issues. In

Bangladesh, sustainable supply chain management is not practiced in structured ways in

12

any leather industry. Thus barriers are the major obstacle to adoption of sustainable supply

chain management practices in the leather processing factory.

In the category of technology, the barriers are the lack of technical expertise,

resistance to change and adopt innovation, lack of cleaner technology, outdated machinery

(Vachon and Klassen, 2007; Klassen and Whybark, 1999). All of those barriers hinder the

total sustainability of supply chain. In the context of leather processing factory, lack of

cleaner technology is one of the most important issues for adopting SSCM practices.

Therefore, the manager should give attention during the implementing stage. But the top

management of the industries of leather in Bangladesh has less interest in taking cleaner

technology as thinking the non-profit issue.

Another most common major category is knowledge & support. Under knowledge

and support, there are number of most common barriers present here that are information

gap, lack of commitment from top management, lack of training and education about

sustainability, limited access to market information (Guler et al., 2000; Muduli et al.,

2013). The lack of awareness and lack of knowledge of benefits of sustainability is a prime

and major barrier to the implementation of SSCM practices in leather processing factory.

The category of society also indicates the significant barriers to SSCM

implementation. Society pressure can be key success factor for an industry to the adoption

of SSCM practices in leather processing factory of Bangladesh. Hence, absent of society

pressure is a major barrier. There are four most common barriers are present here that are

the lack of government support & guideline to adopt sustainable supply chain practices,

the absence of society pressure, lack demand & pressure for the lower price, less of

business-friendly policy (Prakash and Barua, 2015). In Bangladesh, the companies also

don‘t show any interest as Govt. policy doesn‘t comply with directly or doesn‘t encourage

in green practices. Lack of support from the government towards the sustainable supply

chain management practice is a significant barrier.

The last and final major barrier category is the financial burden. In this category,

there are some most common barriers are present. Financial issues are the top priority

13

considerations in the implementation of SSCM practices in Bangladesh. The cost of

sustainability & economic condition, capacity constraints, lack of funds for sustainable

supply chain practices, green power shortage are the major barriers in this category

(Kulatunga et al., 2013; Presley et al., 2007). All of those barriers are the major issues

during SSCM implementing practices. Due to the lack of infrastructural facility, most of

the industries do not show the interest to take SSCM practices. Co-operative support from

all members of the supply chain is desired during the proper implementation of reverse

sustainable supply chain infrastructure in leather industries of Bangladesh.

14

Chapter 3

Methodology

3.1 Research Methodology

The aim of this thesis is to find out the most influential barriers to adoption of

SSCM practices in leather processing factory using grey based DEMATEL methodology.

To apply the research framework in a real life problem, we need to finalize the most

common SSCM implementing barriers. Based on the survey of literature on SSCM

implementing barriers, and discussion with the team of four members in which three

members are from case company and one from academic experts. In this thesis, 35 barriers

are identified from existing literature review and from field survey on leather processing

factory. From 35 existing SSCM implementing barriers, twenty barriers are taken into

account for analyzing and evaluation of most influential barriers.

The proposed research framework is shown in Fig. 3.1 which is used for this

study to find out the most influential barriers to adoption of sustainable supply chain

management practices in leather processing factory of Bangladesh.

15

No

Yes

Collection of major barriers of Sustainable Supply Chain Management Practices

Experts and academic opinion

Literature review

Identify the common barriers under different category

Financial

F1, F2, F3, F4

Social

S1, S2, S3, S4

Knowledge & Support

KS1, KS2, KS3, KS4

Technology

T1, T2, T3, T4

Environmental

E1, E2, E3, E4

Develop comparison matrix by experts /academic opinion

Develop average relation matrix

Develop the crisp relation matrix and normalized direct crisp relation matrix

Compute the total relation matrix

Compute the cause-effect relationship

Approval by experts and academic?

Assign weight to experts and academic for sensitivity analysis

Develop digraph using above data for justifying cause effect relationship

Results, discussions, conclusions, and recommendations

Fig. 1: Conceptual framework for this research

16

3.2 Solution Methodology

Grey theory, DEMATEL method, application of grey-DEMATEL approach and

procedure of grey-DEMATEL approach are presented in this section subsequently.

3.2.1 Grey Theory

Grey theory from grey set was first initiated by Deng in 1982 (Deng, 1982). Grey

systems methodology can manage many of the uncertainty decision which is created from

human decisions (Julong, 1989; Liu and Lin, 2011; Fu et al., 2001). Grey system theory

has successful applications in different fields such as manufacturing industries, agriculture,

economics, earthquakes, medicine etc. Any of the decision-making process can be

successfully done by grey system analysis, so as to improve the rightness of judgments (Li

et al., 2007). The grey number can be described as the number of uncertain data which can

generate required outcome with the small amount of data (Dong and Luo, 2006). Grey

numbers are easily convertible into crisp numbers using modified- CFCS (converting

fuzzy values into crisp scores) method by three step procedure (Fu et al., 2012). Grey

theory was introduced from a grey set by combining the concept of system theory, space

theory and control theory (Liu et al., 2011). The most import thing is grey theory can be

combined with any decision making methods to improve the quality of judgments (Arce et

al., 2015; Asad et al., 2016). One of the main advantages of grey system is that it can give

acceptable outcomes by using small amount of data. Therefore, grey theory is used to

solve various uncertainty problems with discrete data. As grey theory is very suitable to

combine itself to any multi-criteria decision-making method, we will use DEMATEL with

grey theory that means we will use grey DEMATEL method to get our desired result more

perfectly (Su et al., 2015).

3.2.2 DEMATEL Method

Decision-making trial and evaluation laboratory (DEMATEL) method is best

suited for analyzing a complex casual relationship among various factor or barriers (Hsu et

al., 2013; Wang et al., 2012; Jeng and Tzeng, 2012). DEMATEL is a structural modeling

17

approach which can show the interdependence among various factor and show the

influential cause-effect relationship in the form of a digraph (Büyüközkan and Ifi, 2012;

Chen and Chen, 2010; Shen et al., 2011). In DEMATEL method, all the factors or barriers

are divided into cause and effect group so that it helps to find the casual relationship

among multiple barriers. Basically, DEMATEL is a digraph theory which helps to realize

the cause and effect of the system by dividing into zone. Grey-DEMATEL approach can

be successfully applied to analyze the relationship between multiple factors (Shao et al.,

2016). In this study, grey theory has been combined with famous DEMATEL method to

get the more perfect result. Combining grey theory with other MCDM method, results in

more perfection in the result. DEMATEL is a powerful technique in the casual analysis

that helps researchers to divide the involving criteria into cause and effect group (Su et al.,

2015). This method can convert the relationship between cause and effect into a structural

system and also can reduce the number of criteria for evaluation. DEMATEL itself is a

very powerful technique and combining it with grey theory definitely gives it more

calculative power to solve the problem (Wu et al., 2011). It can be applied to the

managerial problem.

3.2.3 Application of Grey-DEMATEL Approach

The application of grey-DEMATEL appears in several fields including electronic

industry (Rajesh and Ravi, 2015), food packaging industry (Zhigang Wang et al., 2015a),

hospital service (Shieh et al., 2010), auto spare parts industry (Wu and Tsai, 2011). In

order to obtain the advantages of both grey theory and DEMATEL, we have chosen of

these two methodologies in this thesis to evaluate and analyze causal relationships among

common barriers of sustainable supply chain management practices in the leather industry

of Bangladesh.

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3.2.4 Procedure of Grey-DEMATEL Methodology

Step 1: Compute the initial relation matrices

Let the number of identified common barriers to sustainable supply chain

management practices be ‗n’ and the respondents chosen to be l. Each respondent k is given

the task of evaluating the direct influence of barrier i over barrier j on an integer scale

ranging from 0, 1, 2, 3, 4, 5, indicating “no influence”, “very low influence”, “low

influence”, medium influence”, “high influence” and “very high influence” subsequently

among n barrier. Thus, set up l initial comparison relation matrices based on ratings obtain

from respondents.

Step 2: Compute the grey relation matrices

An upper value and lower value of grey scales need to be identified from the integer

rating scale (Deng, 1982; Deng, 1989). i.e.,

, . (3.1)k k ky y yij ij ij

Where, 1 ;1 ;1 .k l i n j n

The initial relation matrices are converted into grey relation matrices based on the

obtained grey values,

i. e. 1 2 3, , ,......., .ly y y yij ij ij ij

Step 3: Calculate the average grey relation matrix

The average grey relation matrix [⊗ yij ] is computed (Lin et al., 2004; Kose et

al., 2013) from l grey relation matrices, ;kyij

k= 1 – l as,

, . (3.2)

k ky yij ijk kyij l l

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Step 4: Calculate the crisp relation matrix from the average grey relation matrix

The grey values are modified into crisp values by modified- CFCS method (Arikan

et al. 2013; Dou et al., 2014), following a three-step procedure which is described as

follows;

(i) Normalization of the grey value

. min max/ (3.3)miny y yjij ij ij

Where .

ijy indicates the normalized lower limit value of the grey number ijy .

. min max/ (3.4)miny y yjij ij ij

Where .

ijy indicates the normalized upper limit value of the grey number ijy .

max minmax . (3.5)min y yj ij j ij

(ii) Calculating total normalized crisp value

. . . .

. .

1. (3.6)

1

ij ij ij ij

ij

ij ij

y y y yZ

y y

(iii) Computing the final crisp values

min max* , (3.7)miny ZZ ijj ij

And *ijZ Z . (3.8)

Step 5: Calculate the normalized direct crisp relation matrix

In this step, the normalized direct crisp relation matrix, P is obtained by computing

Q and multiplying Q with the average relation matrix Z. i. e.,

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1

1 ,max *1 j

nQ

Z iji n

(3.9)

And, P=Z×Q. (3.10)

Each element in matrix P falls between zero and one.

Step 6: Compute the total relation matrix

In this step, the total relation matrix, T is calculated by the following equation,

1 (3.11)T P I P

Where, I is the identity matrix.

Step 7: Obtain the cause and effect parameters by summing rows and columns

Assume ijt denotes the elements in the total relation matrix, T. Let r and c be

defined as n×1 and 1×n vectors representing the sum of row elements and sum of column

elements for the total relation matrix T, respectively. If ri represents the sum of ith row

elements in matrix T, then ri summarizes both direct and indirect effects given by barrier i

towards the other barrier. If cj represents the sum of jth column elements in matrix T, then

cj summarizes both direct and indirect effects received by barrier j from other barriers, i.e.,

1nr t iji ij

(3.12)

1nc t jij ij

(3.13)

When j=i, the sum i jr c indicates the total effects given and received by barrier

i; i. e, i jr c represents the degree of importance that the barrier i plays in the entire

system. On the other hand i jr c outlines the net effect that the barrier i

contributes to the entire system. If i jr c is positive, barrier i is the net cause.

Barrier i indicates the net effect if i jr c comes out to be negative value.

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Step 8: Compute threshold value from total relation matrix and plot the digraph

Total relation matrix, T provides information on how one barrier affects another

barriers, a threshold value needs to calculate to avoid the complexity to plot the diagraph.

Calculated threshold value indicates that the greater value than threshold has higher

influence during SSCM implementing. Threshold value is usually computed by sum of the

mean value and standard deviation of elements in the total relation matrix T. In digraph,

causal relations is plotted from the dataset of , .i j i jr c r c i j

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Chapter 4

A Case Study

4.1 Application of the proposed research framework

This proposed research framework is applied in a leather processing factory in

Bangladesh. The case leather processing factory has shown as a representative case

selected for implementation of sustainable supply chain management practices. XYZ is a

global export oriented leather processing factory of Bangladesh which exports leather to

different developed countries like Germany, Italy, and China and also meets demand for

Footwear Company of their own brand. Supply chain network of XYZ is indirectly

globally distributed their products and it is important to consider sustainable supply chain

management practices in their traditional supply chain. To introduce the sustainable supply

chain management practices in their leather processing factory is a top most recent

concern.

Recently this leather processing factory is interested in implementing sustainable

supply chain management practices. They want to find out barriers to adoption of

sustainable supply chain management in their TSCM. This study helps to find out the most

common barriers to adoption of sustainable supply chain practices in leather processing

factory supply chain. In this study, 20 common barriers ware collected from the literature

reviews with the help of industry experts and academic expert.

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4.2 Data Collection

In the process of data collection, a team of four experts, three from the relevant

industry and one from academic expert, is constructed. Table 4.1 shows the team members'

profile. To improve the validity and reliability of thesis, triangular approach (Azevedo et

al., 2013) could be applied in this thesis. Triangulation approaches are of three types-data

triangulation (combining multiple data sources), methodological triangulation (using

multiple research methods to analyze the same problem, or investigator triangulation

(using multiple investigators to work on the same task. In this thesis, data and investigator

triangulation approach are utilized. The required data are collected from industry

professionals and academic expert. Here, data collection is performed in two phases, which

are illustrated below.

Phase-1: Finalizing the most common barriers for implementing sustainable

manufacturing practices

At first, identify 35 barriers to adopting sustainable manufacturing practices in

different industries through a survey of literature and investigate the relevant sector. These

barriers may be applicable to specific industry category for a specific country. To identify

suitable barriers in the social, economic, and technological context of Bangladesh, the

experts are asked to add or delete any barriers to undertaking sustainable manufacturing

practices in the leather industry. In this study, collect responses from the experts and then

arrange several discussion sessions to finalize the barriers. Thus, 20 barriers are identified

for this study. We proceed to the next step of this thesis by taking input from experts to

evaluate comparison among identified barriers for the purpose of developing a grey-

DEMATEL model. For the sake of confidentiality, the name of the companies is not

mentioned here.

Phase-2: Evaluation of comparison among identified barriers to sustainable manufacturing

practices

We communicate the objectives as well as the brief methodology of this thesis to

the expert panel and we ask them to fill a pair-wise comparison matrix necessary for

developing a grey-DEMATEL model. The barriers to adopt of sustainable supply chain

24

management practices have been considered in the study and their relevant literature is

given in Table 4.2 which is shown in Appendix A.

A summary of codes used for the most common barriers to adoption of SSCM practices for

the ease of reference is shown in Table 4.3.

Table 4.1: Profile of team members

Academics Research areas Affiliation Academic 1 Supply Chain Risk

Management Bangladesh University of Engineering and Technology, Bangladesh.

Professionals Company, Product Company size (Employees, Annual sales turnover)

General Manager XYZ, Finished Leather

Area: 2.5 hector, Employees-382, Annual Production-10 million Sq. feet leather.

Chief Executive officer

XYZ, Finished Leather


Officer XYZ, Finished Leather


Table 4.3: Selection of common barriers

Barrier Category Barriers Identification Code

A. Environment Lack of eco-literacy amongst supply chain partner

(E1)

Lack of environmental requirement (E2)

Lack of practice on reverse logistics (E3)

Lack of awareness of local customers in green product

(E4)

B. Technology

Lack of technical expertise (T1)

Resistance to change and adopt innovation (T2)

Lack of cleaner technology (T3)

Outdated machineries (T4)

25

Barrier Category Barriers Identification Code

C. Knowledge & Support

Information gap (KS1)

Lack of commitment from top management (KS2)

Lack of training and education about sustainability

(KS3)

Limited access to market information (KS4)

D. Society Lack of government support & guideline to adopt sustainable supply chain practices

(S1)

Absence of society pressure (S2)

Lack demand & pressure for lower price (S3)

Less of business friendly policy (S4)

E. Financial

Cost of sustainability & economic condition (F1)

Capacity constraints (F2)

Lack of funds for sustainable supply chain practices

(F3)

Green power shortage (F4)

The applications of proposed framework to the case of leather processing factory XYZ is

explained as follows:

Step 1: A group composing of 3 supply chain experts and 1 academic expert is formed to

evaluate the direct influential barriers among twenty common barriers to adoption of

SSCM practices for the case leather processing factory XYZ. The supply chain experts and

academic expert selected based on 10 years of working experience in the relevant field.

They evaluated the direct influence of one barrier to the other barriers on linguistic

provided grey scales varying from “no influence‖ to “very high influence‖. Four initial

comparison matrices (20×20) are formulated based on the integer grey scale ratings.

Linguistics ratings of grey scales are given in Table 4.4 for formulating comparison

relation matrices.

Table 4.3: Selection of common barriers (Continued)

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Table 4.4: Linguistic assessment and related grey values

Linguistic assessment Related grey values

No influence (0.0, 0.1)

Very low influence (0.1, 0.3)

Low influence (0.2, 0.5)

Medium influence (0.4, 0.7)

High influence (0.6, 0.9)

Very high influence (0.9, 1.0)

Step 2: In this step, four initial grey relationship matrices are formulated

1 2 3 4[ ],[ ],[ ],[ ]ij ij ij ijy y y y based on the influence ratings obtained from the three

supply chain experts and one academic experts using Equation (3.1). The matrices are

shown in Tables 4.5, 4.6, 4.7 and 4.8 respectively.

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Table 4.5: Grey relation matrix for barriers of SSCM implementation computed by Expert-1

E1 E2 E3 E4 T1 T2 T3 T4 KS1 KS2 KS3 KS4 S1 S2 S3 S4 F1 F2 F3 F4 E1 0 0.6 0.2 0.1 0.6 0.2 0.9 0.4 0.6 0.4 0.4 0.2 0.4 0.6 0.2 0.1 0.4 0.2 0.2 0.1 0.1 0.9 0.5 0.3 0.9 0.5 1 0.7 0.9 0.7 0.7 0.5 0.7 0.9 0.5 0.3 0.7 0.5 0.5 0.3 E2 0.4 0 0.6 0.1 0.1 0.4 0.2 0.2 0.2 0.2 0.1 0.2 0.4 0.2 0.1 0.1 0.2 0.6 0.1 0.1 0.7 0.1 0.9 0.3 0.3 0.7 0.5 0.5 0.5 0.5 0.3 0.5 0.7 0.5 0.3 0.3 0.5 0.9 0.3 0.3 E3 0.2 0.1 0 0.2 0.2 0.6 0.4 0.6 0.4 0.4 0.2 0.2 0.2 0.2 0.1 0.1 0.2 0.6 0.1 0.1 0.5 0.3 0.1 0.5 0.5 0.9 0.7 0.9 0.7 0.7 0.5 0.5 0.5 0.5 0.3 0.3 0.5 0.9 0.3 0.3 E4 0.6 0.4 0.4 0 0.6 0.4 0.4 0.4 0.6 0.9 0.1 0.4 0.4 0.6 0.2 0.2 0.6 0.4 0.2 0.2 0.9 0.7 0.7 0.1 0.9 0.7 0.7 0.7 0.9 1 0.3 0.7 0.7 0.9 0.5 0.5 0.9 0.7 0.5 0.5 T1 0.6 0.1 0.2 0.4 0 0.2 0.2 0.2 0.4 0.4 0.4 0.1 0.4 0.6 0.2 0.1 0.4 0.2 0.2 0.1 0.9 0.3 0.5 0.7 0.1 0.5 0.5 0.5 0.7 0.7 0.7 0.3 0.7 0.9 0.5 0.3 0.7 0.5 0.5 0.3 T2 0.2 0.1 0.6 0.2 0.2 0 0.2 0.6 0.4 0.2 0.2 0.4 0.2 0.4 0.1 0.1 0.2 0.4 0.1 0.1 0.5 0.3 0.9 0.5 0.5 0.1 0.5 0.9 0.7 0.5 0.5 0.7 0.5 0.7 0.3 0.3 0.5 0.7 0.3 0.3 T3 0.2 0.2 0.2 0.6 0.6 0.6 0 0.2 0.6 0.4 0.4 0.4 0.4 0.4 0.2 0.1 0.6 0.4 0.6 0.2 0.5 0.5 0.5 0.9 0.9 0.9 0.1 0.5 0.9 0.7 0.7 0.7 0.7 0.7 0.5 0.3 0.9 0.7 0.9 0.5 T4 0.4 0.2 0.2 0.2 0.2 0.2 0.6 0 0.4 0.4 0.2 0.6 0.2 0.4 0.6 0.1 0.2 0.6 0.1 0.1 0.7 0.5 0.5 0.5 0.5 0.5 0.9 0.1 0.7 0.7 0.5 0.9 0.5 0.7 0.9 0.3 0.5 0.9 0.3 0.3 KS1 0.4 0.4 0.4 0.4 0.6 0.4 0.4 0.4 0 0.6 0.1 0.4 0.6 0.6 0.4 0.2 0.6 0.4 0.6 0.6 0.7 0.7 0.7 0.7 0.9 0.7 0.7 0.7 0.1 0.9 0.3 0.7 0.9 0.9 0.7 0.5 0.9 0.7 0.9 0.9 KS2 0.6 0.4 0.6 0.6 0.4 0.4 0.6 0.6 0.6 0 0.1 0.6 0.6 0.9 0.2 0.6 0.6 0.4 0.2 0.4 0.9 0.7 0.9 0.9 0.7 0.7 0.9 0.9 0.9 0.1 0.3 0.9 0.7 1 0.5 0.9 0.9 0.7 0.5 0.7 KS3 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.4 0.4 0.2 0 0.2 0.2 0.4 0.1 0.4 0.2 0.1 0.6 0.2 0.3 0.5 0.3 0.3 0.3 0.3 0.5 0.7 0.7 0.5 0.1 0.5 0.5 0.7 0.3 0.7 0.5 0.3 0.9 0.5 KS4 0.6 0.2 0.2 0.4 0.6 0.2 0.6 0.6 0.6 0.4 0.1 0 0.4 0.6 0.6 0.1 0.6 0.2 0.2 0.1 0.9 0.5 0.5 0.7 0.9 0.5 0.9 0.9 0.9 0.7 0.3 0.1 0.7 0.9 0.9 0.3 0.9 0.5 0.5 0.3 S1 0.1 0.6 0.6 0.2 0.6 0.2 0.6 0.4 0.4 0.6 0.6 0.2 0 0.4 0.6 0.6 0.4 0.6 0.6 0.6 0.3 0.9 0.9 0.5 0.9 0.5 0.9 0.7 0.7 0.9 0.9 0.5 0.1 0.7 0.9 0.9 0.7 0.9 0.9 0.9 S2 0.4 0.4 0.4 0.4 0.4 0.2 0.6 0.4 0.9 0.6 0.2 0.4 0.6 0 0.2 0.6 0.6 0.4 0.2 0.1 0.7 0.7 0.7 0.7 0.7 0.5 0.9 0.7 1 0.9 0.5 0.7 0.9 0.1 0.5 0.9 0.9 0.7 0.5 0.3 S3 0.1 0.2 0.1 0.2 0.2 0.1 0.2 0.1 0.2 0.4 0.2 0.6 0.2 0.1 0 0.1 0.2 0.6 0.4 0.1 0.3 0.5 0.3 0.5 0.5 0.3 0.5 0.3 0.5 0.7 0.5 0.9 0.5 0.3 0.1 0.3 0.5 0.9 0.7 0.3 S4 0.1 0.2 0.2 0.2 0.1 0.2 0.2 0.4 0.1 0.2 0.2 0.4 0.2 0.2 0.1 0 0.2 0.1 0.2 0.2 0.3 0.5 0.5 0.5 0.3 0.5 0.5 0.7 0.3 0.5 0.5 0.7 0.5 0.5 0.3 0.1 0.5 0.3 0.5 0.7 F1 0.6 0.4 0.4 0.6 0.6 0.4 0.6 0.4 0.9 0.6 0.2 0.4 0.6 0.2 0.2 0.1 0 0.6 0.2 0.6 0.9 0.7 0.7 0.9 0.9 0.7 0.9 0.7 1 0.9 0.5 0.7 0.9 0.5 0.5 0.3 0.1 0.9 0.5 0.9 F2 0.2 0.4 0.6 0.4 0.2 0.2 0.2 0.6 0.4 0.4 0.2 0.1 0.6 0.4 0.2 0.2 0.4 0 0.1 0.1 0.5 0.7 0.9 0.7 0.5 0.5 0.5 0.9 0.7 0.7 0.5 0.3 0.9 0.7 0.5 0.5 0.7 0.1 0.3 0.3 F3 0.1 0.2 0.1 0.2 0.2 0.1 0.1 0.1 0.2 0.1 0.4 0.6 0.6 0.2 0.4 0.4 0.2 0.1 0 0.4 0.3 0.5 0.3 0.5 0.5 0.3 0.3 0.3 0.5 0.3 0.7 0.9 0.9 0.5 0.7 0.7 0.5 0.3 0.1 0.7 F4 0.1 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.1 0.4 0.6 0.4 0.2 0.1 0.4 0.2 0.1 0.4 0 0.3 0.3 0.3 0.5 0.3 0.3 0.3 0.3 0.5 0.3 0.7 0.9 0.7 0.5 0.3 0.7 0.5 0.3 0.7 0.1

*E1 indicates the identification code of ―Lack of eco-literacy amongst supply chain partner‖ which is shown in Table 4.3. Another barrier is also shown in Table 4.3 by identification code.

27

28


E1 E2 E3 E4 T1 T2 T3 T4 KS1 KS2 KS3 KS4 S1 S2 S3 S4 F1 F2 F3 F4 E1 0 0.6 0.2 0.1 0.6 0.2 0.9 0.4 0.6 0.4 0.4 0.2 0.4 0.6 0.2 0.1 0.4 0.2 0.2 0.1 0.1 0.9 0.5 0.3 0.9 0.5 1 0.7 0.9 0.7 0.7 0.5 0.7 0.9 0.5 0.3 0.7 0.5 0.5 0.3 E2 0.4 0 0.6 0.1 0.1 0.4 0.2 0.2 0.2 0.2 0.1 0.2 0.4 0.2 0.1 0.1 0.2 0.6 0.1 0.1 0.7 0.1 0.9 0.3 0.3 0.7 0.5 0.5 0.5 0.5 0.3 0.5 0.7 0.5 0.3 0.3 0.5 0.9 0.3 0.3 E3 0.2 0.1 0 0.2 0.2 0.1 0.4 0.6 0.4 0.4 0.2 0.2 0.2 0.2 0.1 0.1 0.2 0.6 0.1 0.1 0.5 0.3 0.1 0.5 0.5 0.3 0.7 0.9 0.7 0.7 0.5 0.5 0.5 0.5 0.3 0.3 0.5 0.9 0.3 0.3 E4 0.6 0.4 0.6 0 0.6 0.4 0.6 0.4 0.6 0.6 0.1 0.4 0.6 0.6 0.2 0.2 0.6 0.4 0.2 0.2 0.9 0.7 0.9 0.1 0.9 0.7 0.9 0.7 0.9 0.9 0.3 0.7 0.9 0.9 0.5 0.5 0.9 0.7 0.5 0.5 T1 0.6 0.1 0.2 0.4 0 0.2 0.2 0.2 0.4 0.4 0.4 0.1 0.4 0.6 0.2 0.1 0.4 0.2 0.2 0.1 0.9 0.3 0.5 0.7 0.1 0.5 0.5 0.5 0.7 0.7 0.7 0.3 0.7 0.9 0.5 0.3 0.7 0.5 0.5 0.3 T2 0.2 0.1 0.4 0.2 0.2 0 0.2 0.6 0.4 0.2 0.2 0.4 0.2 0.4 0.1 0.1 0.2 0.4 0.1 0.1 0.5 0.3 0.7 0.5 0.5 0.1 0.5 0.9 0.7 0.5 0.5 0.7 0.5 0.7 0.3 0.3 0.5 0.7 0.3 0.3 T3 0.2 0.2 0.6 0.6 0.4 0.6 0 0.2 0.6 0.4 0.4 0.4 0.4 0.2 0.2 0.1 0.6 0.4 0.6 0.2 0.5 0.5 0.9 0.9 0.7 0.9 0.1 0.5 0.9 0.7 0.7 0.7 0.7 0.5 0.5 0.3 0.9 0.7 0.9 0.5 T4 0.4 0.2 0.2 0.2 0.2 0.2 0.6 0 0.4 0.4 0.2 0.6 0.2 0.4 0.6 0.1 0.2 0.6 0.1 0.1 0.7 0.5 0.5 0.5 0.5 0.5 0.9 0.1 0.7 0.7 0.5 0.9 0.5 0.7 0.9 0.3 0.5 0.9 0.3 0.3 KS1 0.4 0.4 0.4 0.4 0.6 0.4 0.4 0.4 0 0.6 0.1 0.4 0.6 0.6 0.4 0.2 0.6 0.4 0.6 0.6 0.7 0.7 0.7 0.7 0.9 0.7 0.7 0.7 0.1 0.9 0.3 0.7 0.9 0.9 0.7 0.5 0.9 0.7 0.9 0.9 KS2 0.6 0.4 0.6 0.6 0.4 0.2 0.6 0.6 0.6 0 0.1 0.6 0.6 0.9 0.2 0.6 0.6 0.4 0.4 0.4 0.9 0.7 0.9 0.9 0.7 0.5 0.9 0.9 0.9 0.1 0.3 0.9 0.7 1 0.5 0.9 0.9 0.7 0.7 0.7 KS3 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.4 0.4 0.2 0 0.2 0.2 0.4 0.1 0.4 0.2 0.1 0.6 0.2 0.3 0.5 0.3 0.3 0.3 0.3 0.5 0.7 0.7 0.5 0.1 0.5 0.5 0.7 0.3 0.7 0.5 0.3 0.9 0.5 KS4 0.6 0.2 0.2 0.4 0.6 0.2 0.6 0.6 0.6 0.4 0.1 0 0.4 0.6 0.6 0.1 0.6 0.2 0.2 0.1 0.9 0.5 0.5 0.7 0.9 0.5 0.9 0.9 0.9 0.7 0.3 0.1 0.7 0.9 0.9 0.3 0.9 0.5 0.5 0.3 S1 0.2 0.6 0.6 0.2 0.6 0.2 0.6 0.4 0.6 0.4 0.4 0.2 0 0.4 0.4 0.6 0.4 0.6 0.6 0.6 0.5 0.9 0.9 0.5 0.9 0.5 0.9 0.7 0.9 0.7 0.7 0.5 0.1 0.7 0.7 0.9 0.7 0.9 0.9 0.9 S2 0.4 0.4 0.4 0.4 0.4 0.2 0.6 0.4 0.9 0.6 0.2 0.4 0.6 0 0.2 0.6 0.6 0.4 0.2 0.1 0.7 0.7 0.7 0.7 0.7 0.5 0.9 0.7 1 0.9 0.5 0.7 0.9 0.1 0.5 0.9 0.9 0.7 0.5 0.3 S3 0.1 0.2 0.1 0.2 0.2 0.1 0.2 0.1 0.2 0.4 0.2 0.6 0.2 0.1 0 0.1 0.2 0.6 0.4 0.1 0.3 0.5 0.3 0.5 0.5 0.3 0.5 0.3 0.5 0.7 0.5 0.9 0.5 0.3 0.1 0.3 0.5 0.9 0.7 0.3 S4 0.1 0.2 0.2 0.2 0.1 0.2 0.2 0.4 0.1 0.2 0.2 0.4 0.2 0.2 0.1 0 0.2 0.1 0.2 0.2 0.3 0.5 0.5 0.5 0.3 0.5 0.5 0.7 0.3 0.5 0.5 0.7 0.5 0.5 0.3 0.1 0.5 0.3 0.5 0.7 F1 0.6 0.4 0.6 0.6 0.6 0.4 0.6 0.4 0.9 0.6 0.2 0.9 0.6 0.2 0.2 0.1 0 0.6 0.2 0.6 0.9 0.7 0.9 0.9 0.9 0.7 0.9 0.7 1 0.9 0.5 1 0.9 0.5 0.5 0.3 0.1 0.9 0.5 0.9 F2 0.2 0.4 0.6 0.4 0.2 0.2 0.2 0.6 0.4 0.4 0.2 0.1 0.6 0.4 0.2 0.2 0.4 0 0.1 0.1 0.5 0.7 0.9 0.7 0.5 0.5 0.5 0.9 0.7 0.7 0.5 0.3 0.9 0.7 0.5 0.5 0.7 0.1 0.3 0.3 F3 0.1 0.2 0.1 0.2 0.2 0.1 0.1 0.1 0.2 0.1 0.4 0.6 0.6 0.2 0.4 0.4 0.2 0.1 0 0.4 0.3 0.5 0.3 0.5 0.5 0.3 0.3 0.3 0.5 0.3 0.7 0.9 0.9 0.5 0.7 0.7 0.5 0.3 0.1 0.7 F4 0.1 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.1 0.4 0.6 0.4 0.2 0.1 0.4 0.2 0.1 0.4 0 0.3 0.3 0.3 0.5 0.3 0.3 0.3 0.3 0.5 0.3 0.7 0.9 0.7 0.5 0.3 0.7 0.5 0.3 0.7 0.1


28

29


E1 E2 E3 E4 T1 T2 T3 T4 KS1 KS2 KS3 KS4 S1 S2 S3 S4 F1 F2 F3 F4 E1 0 0.6 0.2 0.2 0.6 0.2 0.9 0.4 0.6 0.6 0.4 0.2 0.6 0.4 0.2 0.1 0.4 0.2 0.2 0.1 0.1 0.9 0.5 0.5 0.9 0.5 1 0.7 0.9 0.9 0.7 0.5 0.9 0.7 0.5 0.3 0.7 0.5 0.5 0.3 E2 0.4 0 0.6 0.1 0.1 0.4 0.2 0.2 0.2 0.2 0.2 0.2 0.4 0.2 0.1 0.1 0.2 0.6 0.1 0.1 0.7 0.1 0.9 0.3 0.3 0.7 0.5 0.5 0.5 0.5 0.5 0.5 0.7 0.5 0.3 0.3 0.5 0.9 0.3 0.3 E3 0.2 0.1 0 0.2 0.2 0.6 0.4 0.6 0.4 0.4 0.2 0.2 0.2 0.2 0.1 0.1 0.2 0.6 0.1 0.1 0.5 0.3 0.1 0.5 0.5 0.9 0.7 0.9 0.7 0.7 0.5 0.5 0.5 0.5 0.3 0.3 0.5 0.9 0.3 0.3 E4 0.6 0.4 0.4 0 0.6 0.4 0.4 0.4 0.6 0.9 0.2 0.4 0.4 0.6 0.2 0.2 0.6 0.4 0.2 0.2 0.9 0.7 0.7 0.1 0.9 0.7 0.7 0.7 0.9 1 0.5 0.7 0.7 0.9 0.5 0.5 0.9 0.7 0.5 0.5 T1 0.6 0.1 0.2 0.4 0 0.2 0.2 0.2 0.4 0.4 0.4 0.1 0.4 0.6 0.2 0.1 0.4 0.2 0.2 0.1 0.9 0.3 0.5 0.7 0.1 0.5 0.5 0.5 0.7 0.7 0.7 0.3 0.7 0.9 0.5 0.3 0.7 0.5 0.5 0.3 T2 0.2 0.1 0.6 0.2 0.2 0 0.2 0.6 0.4 0.2 0.2 0.4 0.2 0.4 0.1 0.1 0.2 0.4 0.1 0.1 0.5 0.3 0.9 0.5 0.5 0.1 0.5 0.9 0.7 0.5 0.5 0.7 0.5 0.7 0.3 0.3 0.5 0.7 0.3 0.3 T3 0.4 0.2 0.2 0.6 0.6 0.6 0 0.2 0.4 0.6 0.4 0.4 0.4 0.4 0.2 0.1 0.6 0.4 0.6 0.2 0.7 0.5 0.5 0.9 0.9 0.9 0.1 0.5 0.7 0.9 0.7 0.7 0.7 0.7 0.5 0.3 0.9 0.7 0.9 0.5 T4 0.4 0.2 0.2 0.2 0.2 0.2 0.6 0 0.4 0.4 0.2 0.6 0.2 0.4 0.6 0.1 0.2 0.6 0.1 0.1 0.7 0.5 0.5 0.5 0.5 0.5 0.9 0.1 0.7 0.7 0.5 0.9 0.5 0.7 0.9 0.3 0.5 0.9 0.3 0.3 KS1 0.4 0.4 0.2 0.4 0.6 0.2 0.4 0.4 0 0.6 0.2 0.4 0.6 0.4 0.4 0.2 0.6 0.4 0.6 0.6 0.7 0.7 0.5 0.7 0.9 0.5 0.7 0.7 0.1 0.9 0.5 0.7 0.9 0.7 0.7 0.5 0.9 0.7 0.9 0.9 KS2 0.6 0.4 0.4 0.6 0.4 0.4 0.6 0.6 0.6 0 0.2 0.6 0.4 0.6 0.2 0.4 0.6 0.4 0.2 0.4 0.9 0.7 0.7 0.9 0.7 0.7 0.9 0.9 0.9 0.1 0.5 0.9 0.7 0.9 0.5 0.7 0.9 0.7 0.5 0.7 KS3 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.4 0.4 0.2 0 0.2 0.2 0.4 0.1 0.4 0.2 0.1 0.6 0.2 0.3 0.5 0.3 0.3 0.3 0.3 0.5 0.7 0.7 0.5 0.1 0.5 0.5 0.7 0.3 0.7 0.5 0.3 0.9 0.5 KS4 0.6 0.2 0.2 0.4 0.6 0.2 0.6 0.6 0.6 0.4 0.1 0 0.4 0.6 0.6 0.1 0.6 0.2 0.2 0.1 0.9 0.5 0.5 0.7 0.9 0.5 0.9 0.9 0.9 0.7 0.3 0.1 0.7 0.9 0.9 0.3 0.9 0.5 0.5 0.3 S1 0.1 0.6 0.6 0.2 0.6 0.2 0.6 0.4 0.6 0.6 0.6 0.2 0 0.4 0.6 0.6 0.4 0.6 0.6 0.6 0.3 0.9 0.9 0.5 0.9 0.5 0.9 0.7 0.9 0.9 0.9 0.5 0.1 0.7 0.9 0.9 0.7 0.9 0.9 0.9 S2 0.4 0.4 0.2 0.4 0.4 0.2 0.6 0.4 0.6 0.6 0.4 0.4 0.6 0 0.2 0.4 0.6 0.4 0.2 0.1 0.7 0.7 0.5 0.7 0.7 0.5 0.9 0.7 0.9 0.9 0.7 0.7 0.9 0.1 0.5 0.7 0.9 0.7 0.5 0.3 S3 0.1 0.2 0.1 0.2 0.2 0.1 0.2 0.1 0.2 0.4 0.2 0.6 0.2 0.1 0 0.1 0.2 0.6 0.4 0.1 0.3 0.5 0.3 0.5 0.5 0.3 0.5 0.3 0.5 0.7 0.5 0.9 0.5 0.3 0.1 0.3 0.5 0.9 0.7 0.3 S4 0.1 0.2 0.2 0.2 0.1 0.2 0.2 0.4 0.1 0.2 0.2 0.4 0.2 0.2 0.1 0 0.2 0.1 0.2 0.2 0.3 0.5 0.5 0.5 0.3 0.5 0.5 0.7 0.3 0.5 0.5 0.7 0.5 0.5 0.3 0.1 0.5 0.3 0.5 0.7 F1 0.6 0.4 0.4 0.6 0.6 0.4 0.6 0.4 0.9 0.6 0.2 0.4 0.6 0.2 0.2 0.1 0 0.6 0.2 0.6 0.9 0.7 0.7 0.9 0.9 0.7 0.9 0.7 1 0.9 0.5 0.7 0.9 0.5 0.5 0.3 0.1 0.9 0.5 0.9 F2 0.2 0.4 0.6 0.4 0.2 0.2 0.2 0.6 0.4 0.4 0.2 0.1 0.6 0.4 0.2 0.2 0.4 0 0.1 0.1 0.5 0.7 0.9 0.7 0.5 0.5 0.5 0.9 0.7 0.7 0.5 0.3 0.9 0.7 0.5 0.5 0.7 0.1 0.3 0.3 F3 0.1 0.2 0.1 0.2 0.2 0.1 0.1 0.1 0.2 0.1 0.4 0.6 0.6 0.2 0.4 0.4 0.2 0.1 0 0.4 0.3 0.5 0.3 0.5 0.5 0.3 0.3 0.3 0.5 0.3 0.7 0.9 0.9 0.5 0.7 0.7 0.5 0.3 0.1 0.7 F4 0.1 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.1 0.4 0.6 0.4 0.2 0.1 0.4 0.2 0.1 0.4 0 0.3 0.3 0.3 0.5 0.3 0.3 0.3 0.3 0.5 0.3 0.7 0.9 0.7 0.5 0.3 0.7 0.5 0.3 0.7 0.1


29

30

Table 4.8: Grey relation matrix for barriers of SSCM implementation computed by Academic-1

E1 E2 E3 E4 T1 T2 T3 T4 KS1 KS2 KS3 KS4 S1 S2 S3 S4 F1 F2 F3 F4 E1 0 0.6 0.2 0.2 0.6 0.2 0.9 0.4 0.9 0.6 0.4 0.2 0.6 0.6 0.2 0.1 0.4 0.2 0.2 0.1 0.1 0.9 0.5 0.5 0.9 0.5 1 0.7 1 0.9 0.7 0.5 0.9 0.9 0.5 0.3 0.7 0.5 0.5 0.3 E2 0.4 0 0.6 0.1 0.1 0.4 0.2 0.2 0.2 0.2 0.1 0.2 0.4 0.2 0.1 0.1 0.2 0.6 0.1 0.1 0.7 0.1 0.9 0.3 0.3 0.7 0.5 0.5 0.5 0.5 0.3 0.5 0.7 0.5 0.3 0.3 0.5 0.9 0.3 0.3 E3 0.2 0.1 0 0.2 0.2 0.6 0.4 0.6 0.4 0.4 0.2 0.2 0.2 0.2 0.1 0.1 0.2 0.6 0.1 0.1 0.5 0.3 0.1 0.5 0.5 0.9 0.7 0.9 0.7 0.7 0.5 0.5 0.5 0.5 0.3 0.3 0.5 0.9 0.3 0.3 E4 0.6 0.4 0.6 0 0.6 0.4 0.4 0.4 0.6 0.9 0.1 0.4 0.4 0.6 0.2 0.2 0.6 0.4 0.2 0.2 0.9 0.7 0.9 0.1 0.9 0.7 0.7 0.7 0.9 1 0.3 0.7 0.7 0.9 0.5 0.5 0.9 0.7 0.5 0.5 T1 0.6 0.1 0.2 0.4 0 0.2 0.2 0.2 0.4 0.4 0.4 0.1 0.4 0.6 0.2 0.1 0.4 0.2 0.2 0.1 0.9 0.3 0.5 0.7 0.1 0.5 0.5 0.5 0.7 0.7 0.7 0.3 0.7 0.9 0.5 0.3 0.7 0.5 0.5 0.3 T2 0.2 0.1 0.6 0.2 0.2 0 0.2 0.6 0.4 0.2 0.2 0.4 0.2 0.4 0.1 0.1 0.2 0.4 0.1 0.1 0.5 0.3 0.9 0.5 0.5 0.1 0.5 0.9 0.7 0.5 0.5 0.7 0.5 0.7 0.3 0.3 0.5 0.7 0.3 0.3 T3 0.2 0.2 0.2 0.6 0.6 0.6 0 0.4 0.6 0.4 0.4 0.4 0.4 0.4 0.2 0.1 0.6 0.4 0.6 0.2 0.5 0.5 0.5 0.9 0.9 0.9 0.1 0.7 0.9 0.7 0.7 0.7 0.7 0.7 0.5 0.3 0.9 0.7 0.9 0.5 T4 0.4 0.2 0.2 0.2 0.2 0.2 0.6 0 0.4 0.4 0.2 0.6 0.2 0.4 0.6 0.1 0.2 0.6 0.1 0.1 0.7 0.5 0.5 0.5 0.5 0.5 0.9 0.1 0.7 0.7 0.5 0.9 0.5 0.7 0.9 0.3 0.5 0.9 0.3 0.3 KS1 0.6 0.4 0.4 0.6 0.6 0.4 0.6 0.6 0 0.6 0.1 0.6 0.6 0.6 0.4 0.2 0.6 0.4 0.6 0.6 0.9 0.7 0.7 0.9 0.9 0.7 0.9 0.9 0.1 0.9 0.3 0.9 0.9 0.9 0.7 0.5 0.9 0.7 0.9 0.9 KS2 0.6 0.4 0.6 0.6 0.4 0.4 0.6 0.6 0.6 0 0.2 0.6 0.6 0.9 0.2 0.6 0.6 0.4 0.2 0.4 0.9 0.7 0.9 0.9 0.7 0.7 0.9 0.9 0.9 0.1 0.5 0.9 0.7 1 0.5 0.9 0.9 0.7 0.5 0.7 KS3 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.4 0.2 0.2 0 0.2 0.2 0.4 0 0.4 0.2 0.1 0.4 0.2 0.3 0.5 0.3 0.3 0.3 0.3 0.5 0.7 0.5 0.5 0.1 0.5 0.5 0.7 0.1 0.7 0.5 0.3 0.7 0.5 KS4 0.6 0.4 0.2 0.4 0.6 0.2 0.6 0.6 0.6 0.6 0.1 0 0.4 0.6 0.6 0.2 0.6 0.2 0.2 0.2 0.9 0.7 0.5 0.7 0.9 0.5 0.9 0.9 0.9 0.9 0.3 0.1 0.7 0.9 0.9 0.5 0.9 0.5 0.5 0.5 S1 0.2 0.6 0.6 0.2 0.6 0.2 0.6 0.4 0.6 0.6 0.4 0.2 0 0.4 0.6 0.6 0.6 0.4 0.6 0.6 0.5 0.9 0.9 0.5 0.9 0.5 0.9 0.7 0.9 0.9 0.7 0.5 0.1 0.7 0.9 0.9 0.9 0.7 0.9 0.9 S2 0.4 0.4 0.4 0.4 0.4 0.2 0.6 0.4 0.6 0.9 0.2 0.4 0.6 0 0.2 0.4 0.6 0.4 0.2 0.2 0.7 0.7 0.7 0.7 0.7 0.5 0.9 0.7 0.9 1 0.5 0.7 0.9 0.1 0.5 0.7 0.9 0.7 0.5 0.5 S3 0.1 0.2 0.2 0.2 0.2 0.1 0.2 0.2 0.2 0.4 0.2 0.6 0.2 0.1 0 0.1 0.2 0.6 0.4 0.1 0.3 0.5 0.5 0.5 0.5 0.3 0.5 0.5 0.5 0.7 0.5 0.9 0.5 0.3 0.1 0.3 0.5 0.9 0.7 0.3 S4 0.1 0.2 0.2 0.2 0.1 0.2 0.2 0.4 0.1 0.2 0.2 0.4 0.2 0.2 0.1 0 0.2 0.1 0.2 0.2 0.3 0.5 0.5 0.5 0.3 0.5 0.5 0.7 0.3 0.5 0.5 0.7 0.5 0.5 0.3 0.1 0.5 0.3 0.5 0.7 F1 0.4 0.4 0.4 0.6 0.6 0.4 0.6 0.6 0.9 0.6 0.1 0.6 0.6 0.4 0.2 0.1 0 0.6 0.2 0.6 0.7 0.7 0.7 0.9 0.9 0.7 0.9 0.9 1 0.9 0.3 0.9 0.9 0.7 0.5 0.3 0.1 0.9 0.5 0.9 F2 0.2 0.4 0.6 0.4 0.2 0.2 0.2 0.6 0.4 0.4 0.2 0.1 0.6 0.4 0.2 0.2 0.4 0 0.1 0.1 0.5 0.7 0.9 0.7 0.5 0.5 0.5 0.9 0.7 0.7 0.5 0.3 0.9 0.7 0.5 0.5 0.7 0.1 0.3 0.3 F3 0.1 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.2 0.1 0.4 0.6 0.6 0.2 0.4 0.4 0.2 0.1 0 0.4 0.3 0.5 0.5 0.5 0.5 0.3 0.3 0.3 0.5 0.3 0.7 0.9 0.9 0.5 0.7 0.7 0.5 0.3 0.1 0.7 F4 0.1 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.1 0.4 0.6 0.4 0.2 0.1 0.4 0.2 0.1 0.4 0 0.3 0.3 0.3 0.5 0.3 0.3 0.3 0.3 0.5 0.3 0.7 0.9 0.7 0.5 0.3 0.7 0.5 0.3 0.7 0.1


30

31

Step 3:

In order to have homogeneity of judgment, in this step, equal weightings are

assigned to all supply chain experts and academic experts and computed average grey

relation matrix [ ]ijy by using Equation (3.2). The average grey relation matrix is

shown in Table 4.9.

32

Table 4.9: Average grey relation matrix for barriers of SSCM implementation

E1 E2 E3 E4 T1 T2 T3 T4 KS1 KS2 KS3 KS4 S1 S2 S3 S4 F1 F2 F3 F4 E1 0 0.6 0.2 0.15 0.6 0.2 0.9 0.4 0.675 0.5 0.4 0.2 0.5 0.55 0.2 0.1 0.4 0.2 0.2 0.1 0.1 0.9 0.5 0.4 0.9 0.5 1 0.7 0.925 0.8 0.7 0.5 0.8 0.85 0.5 0.3 0.7 0.5 0.5 0.3 E2 0.4 0 0.6 0.1 0.1 0.4 0.2 0.2 0.2 0.2 0.125 0.2 0.4 0.2 0.1 0.1 0.2 0.6 0.1 0.1 0.7 0.1 0.9 0.3 0.3 0.7 0.5 0.5 0.5 0.5 0.35 0.5 0.7 0.5 0.3 0.3 0.5 0.9 0.3 0.3 E3 0.2 0.1 0 0.2 0.2 0.475 0.4 0.6 0.4 0.4 0.2 0.2 0.2 0.2 0.1 0.1 0.2 0.6 0.1 0.1 0.5 0.3 0.1 0.5 0.5 0.75 0.7 0.9 0.7 0.7 0.5 0.5 0.5 0.5 0.3 0.3 0.5 0.9 0.3 0.3 E4 0.6 0.4 0.5 0 0.6 0.4 0.45 0.4 0.6 0.825 0.125 0.4 0.45 0.6 0.2 0.2 0.6 0.4 0.2 0.2 0.9 0.7 0.8 0.1 0.9 0.7 0.75 0.7 0.9 0.975 0.35 0.7 0.75 0.9 0.5 0.5 0.9 0.7 0.5 0.5 T1 0.6 0.1 0.2 0.4 0 0.2 0.2 0.2 0.4 0.4 0.4 0.1 0.4 0.6 0.2 0.1 0.4 0.2 0.2 0.1 0.9 0.3 0.5 0.7 0.1 0.5 0.5 0.5 0.7 0.7 0.7 0.3 0.7 0.9 0.5 0.3 0.7 0.5 0.5 0.3 T2 0.2 0.1 0.55 0.2 0.2 0 0.2 0.6 0.4 0.2 0.2 0.4 0.2 0.4 0.1 0.1 0.2 0.4 0.1 0.1 0.5 0.3 0.85 0.5 0.5 0.1 0.5 0.9 0.7 0.5 0.5 0.7 0.5 0.7 0.3 0.3 0.5 0.7 0.3 0.3 T3 0.25 0.2 0.3 0.6 0.55 0.6 0 0.25 0.55 0.45 0.4 0.4 0.4 0.35 0.2 0.1 0.6 0.4 0.6 0.2 0.55 0.5 0.6 0.9 0.85 0.9 0.1 0.55 0.85 0.75 0.7 0.7 0.7 0.65 0.5 0.3 0.9 0.7 0.9 0.5 T4 0.4 0.2 0.2 0.2 0.2 0.2 0.6 0 0.4 0.4 0.2 0.6 0.2 0.4 0.6 0.1 0.2 0.6 0.1 0.1 0.7 0.5 0.5 0.5 0.5 0.5 0.9 0.1 0.7 0.7 0.5 0.9 0.5 0.7 0.9 0.3 0.5 0.9 0.3 0.3 KS1 0.45 0.4 0.35 0.45 0.6 0.35 0.45 0.45 0 0.6 0.125 0.45 0.6 0.55 0.4 0.2 0.6 0.4 0.6 0.6 0.75 0.7 0.65 0.75 0.9 0.65 0.75 0.75 0.1 0.9 0.35 0.75 0.9 0.85 0.7 0.5 0.9 0.7 0.9 0.9 KS2 0.6 0.4 0.55 0.6 0.4 0.35 0.6 0.6 0.6 0 0.15 0.6 0.55 0.825 0.2 0.55 0.6 0.4 0.25 0.4 0.9 0.7 0.85 0.9 0.7 0.65 0.9 0.9 0.9 0.1 0.4 0.9 0.7 0.975 0.5 0.85 0.9 0.7 0.55 0.7 KS3 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.4 0.35 0.2 0 0.2 0.2 0.4 0.075 0.4 0.2 0.1 0.55 0.2 0.3 0.5 0.3 0.3 0.3 0.3 0.5 0.7 0.65 0.5 0.1 0.5 0.5 0.7 0.25 0.7 0.5 0.3 0.85 0.5 KS4 0.6 0.25 0.2 0.4 0.6 0.2 0.6 0.6 0.6 0.45 0.1 0 0.4 0.6 0.6 0.125 0.6 0.2 0.2 0.125 0.9 0.55 0.5 0.7 0.9 0.5 0.9 0.9 0.9 0.75 0.3 0.1 0.7 0.9 0.9 0.35 0.9 0.5 0.5 0.35 S1 0.15 0.6 0.6 0.2 0.6 0.2 0.6 0.4 0.55 0.55 0.5 0.2 0 0.4 0.55 0.6 0.45 0.55 0.6 0.6 0.4 0.9 0.9 0.5 0.9 0.5 0.9 0.7 0.85 0.85 0.8 0.5 0.1 0.7 0.85 0.9 0.75 0.85 0.9 0.9 S2 0.4 0.4 0.35 0.4 0.4 0.2 0.6 0.4 0.75 0.675 0.25 0.4 0.6 0 0.2 0.5 0.6 0.4 0.2 0.125 0.7 0.7 0.65 0.7 0.7 0.5 0.9 0.7 0.95 0.925 0.55 0.7 0.9 0.1 0.5 0.8 0.9 0.7 0.5 0.35 S3 0.1 0.2 0.125 0.2 0.2 0.1 0.2 0.125 0.2 0.4 0.2 0.6 0.2 0.1 0 0.1 0.2 0.6 0.4 0.1 0.3 0.5 0.35 0.5 0.5 0.3 0.5 0.35 0.5 0.7 0.5 0.9 0.5 0.3 0.1 0.3 0.5 0.9 0.7 0.3 S4 0.1 0.2 0.2 0.2 0.1 0.2 0.2 0.4 0.1 0.2 0.2 0.4 0.2 0.2 0.1 0 0.2 0.1 0.2 0.2 0.3 0.5 0.5 0.5 0.3 0.5 0.5 0.7 0.3 0.5 0.5 0.7 0.5 0.5 0.3 0.1 0.5 0.3 0.5 0.7 F1 0.55 0.4 0.45 0.6 0.6 0.4 0.6 0.45 0.9 0.6 0.175 0.575 0.6 0.25 0.2 0.1 0 0.6 0.2 0.6 0.85 0.7 0.75 0.9 0.9 0.7 0.9 0.75 1 0.9 0.45 0.825 0.9 0.55 0.5 0.3 0.1 0.9 0.5 0.9 F2 0.2 0.4 0.6 0.4 0.2 0.2 0.2 0.6 0.4 0.4 0.2 0.1 0.6 0.4 0.2 0.2 0.4 0 0.1 0.1 0.5 0.7 0.9 0.7 0.5 0.5 0.5 0.9 0.7 0.7 0.5 0.3 0.9 0.7 0.5 0.5 0.7 0.1 0.3 0.3 F3 0.1 0.2 0.125 0.2 0.2 0.1 0.1 0.1 0.2 0.1 0.4 0.6 0.6 0.2 0.4 0.4 0.2 0.1 0 0.4 0.3 0.5 0.35 0.5 0.5 0.3 0.3 0.3 0.5 0.3 0.7 0.9 0.9 0.5 0.7 0.7 0.5 0.3 0.1 0.7 F4 0.1 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.2 0.1 0.4 0.6 0.4 0.2 0.1 0.4 0.2 0.1 0.4 0 0.3 0.3 0.3 0.5 0.3 0.3 0.3 0.3 0.5 0.3 0.7 0.9 0.7 0.5 0.3 0.7 0.5 0.3 0.7 0.1

*E1 indicates the identification code of ―Lack of Eco-Literacy amongst supply chain partner‖ which is shown in Table 4.3. Another barrier is also shown in Table 4.3 by identification code.

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Step 4: In this step, by a three step procedure involving modified- CFCS method, the crisp relation matrix Z is formulated from average

grey relation matrix. The crisp relation matrix is computed using Equations (3.3), (3.4), (3.5), (3.6), (3.7) and (3.8) is shown in Table 4.10.

Table 4.10: Crisp relation matrix for barriers of SSCM implementation

E1 E2 E3 E4 T1 T2 T3 T4 KS1 KS2 KS3 KS4 S1 S2 S3 S4 F1 F2 F3 F4

E1 0 0.745 0.273 0.193 0.745 0.273 0.9 0.509 0.783 0.619 0.52 0.273 0.627 0.678 0.273 0.12 0.509 0.273 0.273 0.12

E2 0.549 0 0.782 0.129 0.129 0.549 0.293 0.301 0.293 0.295 0.173 0.301 0.549 0.295 0.129 0.129 0.301 0.782 0.129 0.129

E3 0.273 0.12 0 0.273 0.273 0.581 0.5 0.745 0.5 0.502 0.28 0.273 0.273 0.268 0.12 0.12 0.273 0.745 0.12 0.12

E4 0.745 0.509 0.627 0 0.745 0.509 0.558 0.509 0.733 0.868 0.159 0.509 0.568 0.736 0.273 0.273 0.745 0.509 0.273 0.273

T1 0.745 0.12 0.273 0.509 0 0.273 0.267 0.273 0.5 0.502 0.52 0.12 0.509 0.736 0.273 0.12 0.509 0.273 0.273 0.12

T2 0.273 0.12 0.686 0.273 0.273 0 0.267 0.745 0.5 0.268 0.28 0.509 0.273 0.502 0.12 0.12 0.273 0.509 0.12 0.12

T3 0.332 0.273 0.391 0.745 0.686 0.745 0 0.332 0.675 0.561 0.52 0.509 0.509 0.444 0.273 0.12 0.745 0.509 0.745 0.273

T4 0.509 0.273 0.273 0.273 0.273 0.273 0.733 0 0.5 0.502 0.28 0.745 0.273 0.502 0.745 0.12 0.273 0.745 0.12 0.12

KS1 0.568 0.509 0.45 0.568 0.745 0.45 0.558 0.568 0 0.736 0.159 0.568 0.745 0.678 0.509 0.273 0.745 0.509 0.745 0.745

KS2 0.745 0.509 0.686 0.745 0.509 0.45 0.733 0.745 0.733 0 0.197 0.745 0.582 0.868 0.273 0.686 0.745 0.509 0.332 0.509

KS3 0.12 0.273 0.12 0.12 0.12 0.12 0.267 0.509 0.442 0.268 0 0.273 0.273 0.502 0.087 0.509 0.273 0.12 0.686 0.273

KS4 0.745 0.332 0.273 0.509 0.745 0.273 0.733 0.745 0.733 0.561 0.122 0 0.509 0.736 0.745 0.155 0.745 0.273 0.273 0.155

S1 0.193 0.745 0.745 0.273 0.745 0.273 0.733 0.509 0.675 0.678 0.64 0.273 0 0.502 0.686 0.745 0.568 0.686 0.745 0.745

S2 0.509 0.509 0.45 0.509 0.509 0.273 0.733 0.509 0.827 0.785 0.34 0.509 0.745 0 0.273 0.627 0.745 0.509 0.273 0.155

S3 0.12 0.273 0.155 0.273 0.273 0.12 0.267 0.155 0.267 0.502 0.28 0.745 0.273 0.119 0 0.12 0.273 0.745 0.509 0.12

S4 0.12 0.273 0.273 0.273 0.12 0.273 0.267 0.509 0.118 0.268 0.28 0.509 0.273 0.268 0.12 0 0.273 0.12 0.273 0.385

F1 0.686 0.509 0.568 0.745 0.745 0.509 0.733 0.568 0.9 0.736 0.238 0.679 0.745 0.327 0.273 0.12 0 0.745 0.273 0.745

F2 0.273 0.509 0.745 0.509 0.273 0.273 0.267 0.745 0.5 0.502 0.28 0.12 0.745 0.502 0.273 0.273 0.509 0 0.12 0.12

F3 0.12 0.273 0.155 0.273 0.273 0.12 0.118 0.12 0.267 0.119 0.52 0.745 0.745 0.268 0.509 0.509 0.273 0.12 0 0.509

F4 0.12 0.12 0.12 0.273 0.12 0.12 0.118 0.12 0.267 0.119 0.52 0.745 0.509 0.268 0.12 0.509 0.273 0.12 0.509 0


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Step 5: Normalized direct crisp relation matrix P is constructed from the crisp relation matrix by normalization process using

Equations (3.9) and (3.10).

Table 4.11: Normalized direct crisp relation matrix for barriers of SSCM implementation


E1 0.000 0.066 0.024 0.017 0.066 0.024 0.080 0.045 0.069 0.055 0.046 0.024 0.055 0.060 0.024 0.011 0.045 0.024 0.024 0.011

E2 0.049 0.000 0.069 0.011 0.011 0.049 0.026 0.027 0.026 0.026 0.015 0.027 0.049 0.026 0.011 0.011 0.027 0.069 0.011 0.011

E3 0.024 0.011 0.000 0.024 0.024 0.051 0.044 0.066 0.044 0.044 0.025 0.024 0.024 0.024 0.011 0.011 0.024 0.066 0.011 0.011

E4 0.066 0.045 0.055 0.000 0.066 0.045 0.049 0.045 0.065 0.077 0.014 0.045 0.050 0.065 0.024 0.024 0.066 0.045 0.024 0.024

T1 0.066 0.011 0.024 0.045 0.000 0.024 0.024 0.024 0.044 0.044 0.046 0.011 0.045 0.065 0.024 0.011 0.045 0.024 0.024 0.011

T2 0.024 0.011 0.061 0.024 0.024 0.000 0.024 0.066 0.044 0.024 0.025 0.045 0.024 0.044 0.011 0.011 0.024 0.045 0.011 0.011

T3 0.029 0.024 0.035 0.066 0.061 0.066 0.000 0.029 0.060 0.050 0.046 0.045 0.045 0.039 0.024 0.011 0.066 0.045 0.066 0.024

T4 0.045 0.024 0.024 0.024 0.024 0.024 0.065 0.000 0.044 0.044 0.025 0.066 0.024 0.044 0.066 0.011 0.024 0.066 0.011 0.011

KS1 0.050 0.045 0.040 0.050 0.066 0.040 0.049 0.050 0.000 0.065 0.014 0.050 0.066 0.060 0.045 0.024 0.066 0.045 0.066 0.066

KS2 0.066 0.045 0.061 0.066 0.045 0.040 0.065 0.066 0.065 0.000 0.017 0.066 0.051 0.077 0.024 0.061 0.066 0.045 0.029 0.045

KS3 0.011 0.024 0.011 0.011 0.011 0.011 0.024 0.045 0.039 0.024 0.000 0.024 0.024 0.044 0.008 0.045 0.024 0.011 0.061 0.024

KS4 0.066 0.029 0.024 0.045 0.066 0.024 0.065 0.066 0.065 0.050 0.011 0.000 0.045 0.065 0.066 0.014 0.066 0.024 0.024 0.014

S1 0.017 0.066 0.066 0.024 0.066 0.024 0.065 0.045 0.060 0.060 0.057 0.024 0.000 0.044 0.061 0.066 0.050 0.061 0.066 0.066

S2 0.045 0.045 0.040 0.045 0.045 0.024 0.065 0.045 0.073 0.069 0.030 0.045 0.066 0.000 0.024 0.055 0.066 0.045 0.024 0.014

S3 0.011 0.024 0.014 0.024 0.024 0.011 0.024 0.014 0.024 0.044 0.025 0.066 0.024 0.011 0.000 0.011 0.024 0.066 0.045 0.011

S4 0.011 0.024 0.024 0.024 0.011 0.024 0.024 0.045 0.010 0.024 0.025 0.045 0.024 0.024 0.011 0.000 0.024 0.011 0.024 0.034

F1 0.061 0.045 0.050 0.066 0.066 0.045 0.065 0.050 0.080 0.065 0.021 0.060 0.066 0.029 0.024 0.011 0.000 0.066 0.024 0.066

F2 0.024 0.045 0.066 0.045 0.024 0.024 0.024 0.066 0.044 0.044 0.025 0.011 0.066 0.044 0.024 0.024 0.045 0.000 0.011 0.011

F3 0.011 0.024 0.014 0.024 0.024 0.011 0.010 0.011 0.024 0.011 0.046 0.066 0.066 0.024 0.045 0.045 0.024 0.011 0.000 0.045

F4 0.011 0.011 0.011 0.024 0.011 0.011 0.010 0.011 0.024 0.011 0.046 0.066 0.045 0.024 0.011 0.045 0.024 0.011 0.045 0.000

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35

Step 6: The total relation matrix T is constructed using Equation (3.11) which is shown in Table 4.12.

Table 4.12: Total relation matrix for barriers of SSCM implementation


E1 0.110 0.160 0.135 0.123 0.180 0.114 0.202 0.166 0.206 0.182 0.128 0.142 0.185 0.183 0.109 0.087 0.169 0.145 0.117 0.091

E2 0.121 0.069 0.146 0.084 0.093 0.110 0.115 0.117 0.124 0.117 0.074 0.107 0.138 0.113 0.071 0.064 0.113 0.152 0.073 0.066

E3 0.103 0.081 0.082 0.101 0.108 0.115 0.135 0.156 0.145 0.137 0.084 0.110 0.119 0.116 0.074 0.065 0.115 0.152 0.076 0.068

E4 0.192 0.157 0.183 0.123 0.201 0.149 0.196 0.190 0.227 0.225 0.111 0.181 0.202 0.209 0.123 0.111 0.210 0.184 0.128 0.116

T1 0.151 0.092 0.113 0.128 0.097 0.095 0.128 0.125 0.158 0.150 0.112 0.107 0.150 0.165 0.092 0.074 0.146 0.120 0.099 0.076

T2 0.102 0.079 0.136 0.098 0.107 0.064 0.115 0.154 0.143 0.117 0.082 0.127 0.116 0.133 0.073 0.064 0.113 0.130 0.074 0.066

T3 0.144 0.126 0.151 0.174 0.182 0.157 0.132 0.161 0.206 0.185 0.132 0.170 0.183 0.172 0.114 0.092 0.195 0.169 0.159 0.109

T4 0.137 0.108 0.118 0.115 0.126 0.101 0.171 0.108 0.164 0.156 0.095 0.165 0.137 0.151 0.138 0.075 0.133 0.167 0.090 0.077

KS1 0.179 0.160 0.171 0.174 0.203 0.145 0.198 0.196 0.169 0.217 0.116 0.193 0.222 0.207 0.147 0.116 0.213 0.187 0.172 0.159

KS2 0.201 0.167 0.198 0.195 0.193 0.153 0.223 0.221 0.240 0.166 0.123 0.214 0.216 0.232 0.132 0.153 0.222 0.196 0.143 0.144

KS3 0.073 0.080 0.074 0.072 0.078 0.062 0.096 0.115 0.118 0.098 0.050 0.097 0.102 0.115 0.060 0.090 0.097 0.080 0.113 0.072

KS4 0.183 0.135 0.143 0.158 0.193 0.121 0.201 0.196 0.215 0.191 0.102 0.130 0.186 0.199 0.157 0.094 0.200 0.156 0.123 0.100

S1 0.141 0.174 0.190 0.146 0.195 0.128 0.204 0.187 0.217 0.205 0.153 0.165 0.154 0.187 0.156 0.153 0.192 0.198 0.171 0.157

S2 0.167 0.154 0.164 0.162 0.177 0.126 0.205 0.184 0.227 0.213 0.123 0.177 0.210 0.142 0.120 0.138 0.205 0.179 0.127 0.106

S3 0.080 0.086 0.084 0.091 0.098 0.067 0.102 0.094 0.112 0.124 0.076 0.138 0.108 0.092 0.056 0.060 0.104 0.138 0.101 0.061

S4 0.071 0.076 0.084 0.081 0.074 0.073 0.093 0.112 0.088 0.094 0.070 0.111 0.095 0.092 0.059 0.042 0.092 0.077 0.074 0.077

F1 0.192 0.162 0.185 0.191 0.208 0.154 0.216 0.201 0.248 0.221 0.124 0.202 0.224 0.184 0.129 0.104 0.155 0.210 0.136 0.160

F2 0.117 0.128 0.160 0.132 0.124 0.102 0.134 0.171 0.163 0.156 0.095 0.113 0.174 0.150 0.098 0.089 0.150 0.108 0.088 0.080

F3 0.079 0.087 0.083 0.090 0.099 0.066 0.092 0.091 0.113 0.094 0.100 0.142 0.147 0.104 0.101 0.095 0.104 0.087 0.063 0.097

F4 0.070 0.065 0.070 0.081 0.076 0.059 0.081 0.080 0.100 0.082 0.092 0.131 0.116 0.093 0.060 0.088 0.093 0.075 0.096 0.047 *E1 indicates the identification code of ―Lack of eco-literacy amongst supply chain partner‖ which is shown in Table 4.3.

Another barrier is also shown in Table 4.3 by identification code.

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36

Step 7: Let r and c defined to be 20×1 and 1×20 vectors representing sum of row

values and sum of column values for the total relation matrix T, respectively. Using

Equations (3.12) and (3.13) ir and jc values are computed. ir denotes sum of row i

and the values of ir indicates direct and indirect effect of barrier i over other

barriers for sustainable supply chain management practices. jc represents sum of

column j and the values of jc indicates overall direct and indirect effects of barriers j

to all other barriers. The cause and effect parameters i jr c and i jr c is

constructed from the total relation matrix, T for values i=j, which is presented in Table

4.13.

Table 4.13: Cause-effect parameter for barriers of SSCM implementation

Barriers Ri Cj Ri+Cj Ri-Cj

Horizontal Vertical E1 2.9344 2.6142 5.5486 0.3202 E2 2.0668 2.3437 4.4106 -0.2769 E3 2.1422 2.6699 4.8121 -0.5277 E4 3.4171 2.5175 5.9346 0.8996 T1 2.3769 2.8122 5.1892 -0.4353 T2 2.0938 2.1596 4.2534 -0.0657 T3 3.1116 3.0378 6.1494 0.0738 T4 2.5322 3.0257 5.5579 -0.4935

KS1 3.5438 3.3831 6.9270 0.1607 KS2 3.7315 3.1302 6.8617 0.6012 KS3 1.7430 2.0431 3.7861 -0.3001 KS4 3.1841 2.9222 6.1063 0.2618 S1 3.4718 3.1841 6.6559 0.2876 S2 3.3046 3.0390 6.3436 0.2656 S3 1.8730 2.0670 3.9400 -0.1941 S4 1.6322 1.8545 3.4866 -0.2223 F1 3.6071 3.0216 6.6287 0.5856 F2 2.5350 2.9101 5.4451 -0.3750 F3 1.9331 2.2249 4.1580 -0.2918 F4 1.6563 1.9300 3.5863 -0.2737

37

Step 8: Develop cause and effect digraph by using total relation matrix. A

threshold value (θ=0.178) is calculated by adding the standard deviation (σ) to the mean

(µ) of the elements in the total relation matrix T, to find out comparably negligible cause-

effects among different barriers. Fig. 4.1 indicates the obtained digraph showing cause-

effect relationship among the common barriers, plotted from the dataset of

(( ) ( )) , i j i jr c r c i j . The arrow represents the direction from cause barriers to effect

barriers to adoption of sustainable supply chain management practices. Two-way

significant relationships among barriers are represented in dotted lines whereas one-way

relationships among barriers indicated by solid lines in Fig. 4.1.

38

Fig. 4.1: Digraph shows the casual relationship among different barriers to implementation of SSCM practices

E1

E2

E3

E4

T1

T2

T3

T4

KS1

KS2

KS3

KS4 S1

S2

S3S4

F1

F2-F3

F4

-0.6000

-0.4000

-0.2000

0.0000

0.2000

0.4000

0.6000

0.8000

1.0000

0.0000 1.0000 2.0000 3.0000 4.0000 5.0000 6.0000 7.0000 8.0000

Series1

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Chapter 5

Results and Discussions

In this section, the final results are presented. Table 5.1 reveals the cause-effect

relationship among various SSCM implementation barriers in leather processing factory of

Bangladesh. A grey based DEMATEL approach is applied in this thesis to evaluate and

analyze most influential barriers to adoption of sustainable supply chain management

practices in case of the leather processing factory supply chain. A threshold value of

0.178 is considered in this thesis to reduce the complexity of digraph and to eliminate

some of the minor effect of barriers. Threshold value is computed from total relation

matrix T. The barriers are ranked on its importance the based on i jr c i j values as

follows; KS1>KS2>S1>F1>S2>T3>KS4>E4>T4>E1>F2>T1>E3>E2>T2>F3>S3>KS3>

F4>S4.

5.1 Cause Group

The casual barriers are ranked based on i jr c i j values in Fig. 4.1 as

follows, E4>KS2>F1>E1>S1>S2>KS4>KS1>T3. In this casual group, Lack of awareness

of local customer in green products (E4) and Lack of commitment from top management

(KS2) seem to be the crucial driving barriers, as those can effect of many other barriers to

SCCM implementation in leather processing company. We discuss the result with industry

experts and academic experts and they accepted those barriers as major barriers to

adoption of SSCM implementation. Lack of awareness of local customer and lack of

interest of top management are the major two hindrances of SSCM implementation. Lack

40

of awareness of local customer (E4) is on the category of environmental issues which

could obstacle the green supply chain implementation. When the customers are the lack of

awareness about green products the ultimate result is top management would not interest to

implement SSCM in their TSCM network.

Lack of commitment from top management (KS2) seems to be the major casual

issues during the SSCM implementation in respect to Bangladeshi leather processing

industry. In Bangladesh, top management is not interested to implementation of SSCM

because of sufficient funds not available and this implementation needs large investment.

Hence, this barrier is big issue during SSCM implementation. SSCM practices into TSSC

system needs large investment to modify the existing system and hence, top management

does not want to implement SSCM in their company especially in leather processing

industry. In leather processing industry, the top management is not aware about green

supply chain as well as SSCM.

The third position for barriers of SSCM implementation on importance goes to

cost of sustainability and economic condition (F1). This barrier takes place in casual

group. Therefore, cost of sustainability and poor economic condition is responsible to

hinder the implantation of SSCM in traditional system. In Bangladesh, SSCM

implementation is not an easy practice because of its cost to implement and need for

economic stability.

Lack of eco-literacy amongst supply chain partner (E1) is the forth casual barrier

that means in Bangladesh, the supply chain partners are not conscious about eco-products.

The lack of environmental knowledge is responsible to implement SSCM. The next casual

barrier is lack of support and guideline from regulatory authority (S1) and is one of the

most influential barriers that can directly influence other barriers during SSCM

implementation in leather processing industry. In Bangladesh, the regulatory authority do

not give support for SSCM practices and also not have any regulation for practicing SSCM

into manufacturing industry. This barrier is one of the major obstacles. Hence, it is

necessary to eradicate this barrier to influence other barriers during SSCM practices.

41

Absence of society pressure (S2) is an additional important casual issue during

SSCM practices. Bangladesh is an over populated country. The people are not conscious

about green products, sustainability, environmental issues. This turns to bad impact in

manufacturing industry. It‘s a great opportunity to drive other barriers by introducing

consciousness in society about green products and harmful effect of environment.

Lack of training and education about sustainability (KS4) is knowledge and

support related casual barrier. Introducing training and education can help to adopting

sustainable supply chain management practices in leather processing industry because in

leather processing industry not only employer but also owners of industry not have

sufficient knowledge about sustainability. By introducing training can help to modify

TSCM to SSCM in their supply chain network.

Information gap (KS1) is the eighth ranked casual barrier. An overall gap of

information on sustainability, green supply chain, reverse logistics, social sustainability,

and economic sustainability is one of the major barriers for adopting sustainable supply

chain management practices. Overcoming this barrier can help to implement SSCM

practices in leather processing industry.

The last one identified is the lack of cleaner technology (T3). Lack of cleaner

technology is largely responsible for destroying environment especially for leather

processing industry because of waste water directly imposed to river and polluting the air,

soil, and water. In Bangladesh, leather industry is directly responsible for environmental

degradation. The chemical use in tannery industry directly produces solid waste which can

pollute water as well as soil directly. Introducing cleaner technology for SSCM can largely

help to modify the current situation.

5.2 Effect Group

The effect group can be sorted on the basis of i jr c i j in Fig. 4.1 as

follows; T2>S3>S4>F4>E2>F3>KS3>F2>T1>T4>E3. The eleven barriers are directly

influenced by casual nine barriers which are hindrance to adopting SSCM practices in

42

leather processing factory in Bangladesh. Resistance to change and adopt innovation (T2)

is near to casual group and hence, has less influence by casual barriers. Resistance to

change and adopt innovation is the barriers of SSCM implantation which could influence

by other casual group and it is necessary to eradicate during introducing SSCM practices.

Other effect barriers are lack of demand and pressure for lower price (S3), less business-

friendly policy (S4), green power shortage (F4), lack of environmental requirement (E2),

lack of funds for sustainable supply chain practices (F3), limited access to market

information (KS3), capacity constraints (F2), lack of technical expertise (T1), outdated

machinery (T4), lack of practices on reverse logistics (E3). All of those barriers can easily

influence by casual barriers. During implantation of SSCM practices, it‘s necessary to

identify the cause and effect group to take action against barriers. This thesis could help to

the manager to identify this cause-effect relationship for introducing SSCM practices in

leather processing factory.

5.3 Correlation among the Barriers

The center of barriers can be ranked as follows on the basis of i jr c i j and

it is shown by following ways, KS1>KS2>S1>F1>S2>T3>KS4>E4>T4>E1>F2>T1>E3

E2>T2>F3>S3>KS3>F4>S4. Information gap (KS1) seems to be the highest correlation

with other barriers because overall information about sustainable supply chain can force

other barriers to adopt SSCM practices in existing supply chain and for the new

entrepreneur. In Bangladesh, the major obstacle is information gap. Insufficient knowledge

on the sustainable supply chain is the major issue for SSCM implementation. In

Bangladesh, every branch of supply chain network everybody is not conscious about green

products, reverse logistics, social issues, environmental requirement, and knowledge about

sustainability. Thus the ultimate result is pollution of water, soil, air etc. Bangladesh needs

to undertake the various training and educational facility of SSCM that ensure the

manufacturer, customer to conscious about environmentally friendly products.

43

In this study, one barrier is directly influenced by another barrier. In Fig. 5.1, the

barriers located above the x-axis have the most influence on the network and are indicated

as casual group barriers. The other barriers which are located under this line are indicated

as influenced group. The barriers are shown in Fig. 5.1 can be divided into four regions for

accurate analysis of their influences. In Fig. 5.1, zone 1 represents the barriers with the

least influential effect to other barriers and their importance is low. Resistance to change

and adopt innovation (T2), lack demand and pressure for lower price (S3), less of

business-friendly policy (S4), green power shortage (F4), lack of environmental

requirement (E2), lack of funds for sustainable supply chain practices (F3), limited access

to market information (KS3), lack of technical expertise (T1) and lack of practice on

reverse logistics (E3) barriers are under this zone. Zone two represents the casual relation

among different barriers which has less influence in SSCM implementation. In this zone,

there is no barrier.

Therefore, zone three represents the barriers which have the highest significance.

These barriers are located in the casual group and should consider for SSCM

implementation. These barriers are indicated as strong success factor to adopting SSCM

practices in leather processing supply chain. Therefore, these barriers help to the manager

to undertake proactive and reactive step to adopting SSCM practices in their supply chain

network. Lack of awareness of local customers in green products (E4), lack of

commitment from top management (KS2), cost of sustainability and economic condition

(F1), lack of eco-literacy amongst supply chain partner (E1), lack of support and guideline

from regulatory authority (S1), absence of society pressure (S2), lack of training and

education about sustainability (KS4), information gap (KS1), lack of cleaner technology

(T3) barriers come under this zone.

Zone four indicates the barriers which have high significance but is suited in the

under the x-axis that means it is suited in effect group. In these zone barriers capacity

constraints (F2) and outdated machinery (T4) take place into account which have high

influenced during SSCM practices by other casual barriers.

44

Table 5.1: Final evaluation of barriers with ranking Ranking Barriers Cause Group

1 Information gap (KS1) Lack of awareness of local customers in green product (E4) 2 Lack of commitment from top management (KS2) Lack of commitment from top management (KS2) 3 Lack of support and guideline from regulatory authority (S1) Cost of sustainability & economic condition (F1) 4 Cost of sustainability & economic condition (F1) Lack of eco-literacy amongst supply chain partner (E1) 5 Absence of society pressure (S2) Lack of support and guideline from regulatory authority (S1) 6 Lack of cleaner technology (T3) Absence of society pressure (S2) 7 Lack of training and education about sustainability (KS4) Lack of training and education about sustainability (KS4) 8 Lack of awareness of local customers in green product (E4) Information gap (KS1) 9 Outdated machineries(T4) Lack of cleaner technology (T3) 10

Lack of eco-literacy amongst supply chain partner (E1) Effect Group

Resistance to change and adopt innovation (T2) 11 Capacity constraints (F2) Lack demand & pressure for lower price (S3)

12 Lack of technical expertise (T1) Less of business friendly policy(S4)

13 Lack of practice on reverse logistics (E3) Green power shortage(F4)

14 Lack of environmental requirement (E2) Lack of environmental requirement (E2)

15 Resistance to change and adopt innovation (T2) Lack of funds for sustainable supply chain practices (F3)

16 Lack of funds for sustainable supply chain practices(F3) Limited access to market information (KS3)

17 Lack demand & pressure for lower price (S3) Capacity constraints (F2)

18 Limited access to market information (KS3) Lack of technical expertise (T1

19 Green power shortage(F4) Outdated machineries(T4) 20 Less of business friendly policy(S4) Lack of practice on reverse logistics (E3)

44

45

Fig. 5.1: Barriers to sustainable supply chain management practices represented in zones

E1

E2

E3

E4

T1

T2

T3

T4

KS1

KS2

KS3

KS4 S1

S2

S3S4

F1

F2F3F4

-0.6000

-0.4000

-0.2000

0.0000

0.2000

0.4000

0.6000

0.8000

1.0000

0.0000 1.0000 2.0000 3.0000 4.0000 5.0000 6.0000 7.0000 8.0000

Series1

X: (ri+cj) Y: (ri-cj) Z: zone

: xmean

5.21

Z2 Z4

Z3 Z1

45

46

5.4 Sensitivity Analysis

Sensitivity analysis is a process to test the robustness of the gained results. For the

purpose of testing robustness of obtained result different weighting has been assigned for

one expert while keeping equal weightings for the others experts. This can be done in a

number of ways, as for example, by changing the level of weightings given to an expert or

by changing the level of weightings to various barriers. In this study, we use archetypal

sensitivity analysis by assigning separate weightings to experts and academic. As for

example, first, the weight assigned for experts-1 is 0.4 while keeping the same weight for

other that is 0.2.

For sensitivity analysis, at first we made four separate total relationship matrix by

multiplying each assign weight in respond to Table 4.2, 4.3, 4.4 and 4.5. After that,

average relationship matrices have been computed and finally cause-effect relationships

among different barriers have been established. The weight assigned for different

evaluator, cause-effect relationships of different barriers and ranking of different barriers

during sensitivity analysis are shown in Table 5.2, 5.3 and 5.4.

Table 5.2: Weight assigned for sensitivity analysis to different evaluator

Expert-1 Expert-2 Expert-3 Academic-1

Scenario-1 0.4 0.2 0.2 0.2

Scenario-2 0.2 0.4 0.2 0.2

Scenario-3 0.2 0.2 0.4 0.2

Scenario-4 0.2 0.2 0.2 0.4

47

Table 5.3: Cause –effect parameters getting from sensitivity analysis

Identification

Code

Scenario-1 Scenario-2 Scenario-3 Scenario-4

i jr c i jr c i jr c i jr c i jr c i jr c i jr c i jr c

E1 5.451 0.302 5.461 0.293 5.701 0.329 5.558 0.355

E2 4.351 -0.272 4.347 -0.275 4.520 -0.275 4.386 -0.288

E3 4.761 -0.508 4.773 -0.589 4.882 -0.477 4.809 -0.540

E4 5.845 0.888 5.877 0.923 6.073 0.916 5.913 0.879

T1 5.132 -0.435 5.119 -0.416 5.320 -0.452 5.158 -0.435

T2 4.225 -0.077 4.155 -0.037 4.361 -0.061 4.245 -0.079

T3 6.071 0.071 6.081 0.055 6.309 0.089 6.134 0.068

T4 5.479 -0.476 5.478 -0.475 5.678 -0.491 5.563 -0.535

KS1 6.840 0.148 6.855 0.132 7.044 0.128 6.959 0.220

KS2 6.780 0.612 6.765 0.628 7.024 0.570 6.864 0.582

KS3 3.741 -0.276 3.742 -0.278 3.934 -0.344 3.721 -0.313

KS4 6.008 0.262 6.037 0.239 6.225 0.273 6.118 0.277

S1 6.567 0.290 6.568 0.264 6.831 0.308 6.628 0.299

S2 6.290 0.258 6.271 0.276 6.461 0.275 6.333 0.243

S3 3.895 -0.199 3.881 -0.182 4.037 -0.208 3.923 -0.179

S4 3.459 -0.230 3.457 -0.230 3.552 -0.206 3.465 -0.225

F1 6.532 0.569 6.573 0.611 6.770 0.589 6.606 0.582

F2 5.387 -0.376 5.386 -0.374 5.582 -0.386 5.394 -0.363

F3 4.108 -0.288 4.126 -0.304 4.260 -0.302 4.120 -0.266

F4 3.541 -0.264 3.543 -0.263 3.671 -0.276 3.576 -0.282

Therefore, diagraphs obtained from sensitivity analysis for expert-1, expert-2, expert-3 and

academic-1 are shown in Fig. 5.1, 5.2, 5.3, and 5.4 respectively.

48

Table 5.4: Ranking of Cause –Effect relationship among common barriers obtained from

sensitivity analysis

Ranking

order

Scenario-1 Scenario-2 Scenario-3 Scenario-4

Barriers

code i jr c Barriers



code i jr c

1 E4 0.888 E4 0.923 E4 0.916 E4 0.879

2 KS2 0.612 KS2 0.628 F1 0.589 F1 0.582

3 F1 0.569 F1 0.611 KS2 0.570 KS2 0.582

4 E1 0.302 E1 0.293 E1 0.329 E1 0.355

5 S1 0.290 S2 0.276 S1 0.308 S1 0.299

6 KS4 0.262 S1 0.264 S2 0.275 KS4 0.277

7 S2 0.258 KS4 0.239 KS4 0.273 S2 0.243

8 KS1 0.148 KS1 0.132 KS1 0.128 KS1 0.220

9 T3 0.071 T3 0.055 T3 0.089 T3 0.068

10 T2 -0.077 T2 -0.037 T2 -0.061 T2 -0.079

11 S3 -0.199 S3 -0.182 S4 -0.206 S3 -0.179

12 S4 -0.230 S4 -0.230 S3 -0.208 S4 -0.225

13 F4 -0.264 F4 -0.263 E2 -0.275 F3 -0.266

14 E2 -0.272 E2 -0.275 F4 -0.276 F4 -0.282

15 KS3 -0.276 KS3 -0.278 F3 -0.302 E2 -0.288

16 F3 -0.288 F3 -0.304 KS3 -0.344 KS3 -0.313

17 F2 -0.376 F2 -0.374 F2 -0.386 F2 -0.363

18 T1 -0.435 T1 -0.416 T1 -0.452 T1 -0.435

19 T4 -0.476 T4 -0.475 E3 -0.477 T4 -0.535

20 E3 -0.508 E3 -0.589 T4 -0.491 E3 -0.540

49

Fig. 5.2: Digraph obtained on sensitivity analysis showing casual relation among barriers of SSCM practices by giving highest weight to Expert-1

E1

E2

E3

E4

T1

T2

T3

T4

KS1

KS2

KS3

KS4 S1

S2

S3S4

F1

F2F3

F4

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6 7 8

49

50


E1

E2

E3

E4

T1

T2

T3

T4

KS1

KS2

KS3

KS4S1S2

S3S4

F1

F2F3

F4

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6 7 8

50

51


E1

E2

E3

E4

T1

T2

T3

T4

KS1

KS2

KS3

KS4

S1S2

S3S4

F1

F2F3

F4

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6 7 8

51

52

Fig. 5.5: Digraph obtained on sensitivity analysis showing casual relation among barriers of SSCM practices by giving highest weight to Academic-1

E1

E2

E3

E4

T1

T2

T3

T4

KS1

KS2

KS3

KS4S1

S2

S3S4

F1

F2F3F4

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6 7 8

52

53

From the above plotted diagraph it is clear that there is no major change in

ranking among various barriers during sensitivity analysis. This results show the same

priority ranking order for cause-effect barriers for each experts and academic, accepting

minor order variation. Hence, there is no serious change in ranking during sensitivity

analysis. Therefore, sensitivity analysis ensures the robustness of obtained results.

5.5 Managerial Implications

The results of this study reveal important implications for decision makers during

sustainable supply chain management implementation. From the study results, several

managerial suggestions are formed. Therefore it is important to focus on the cause group

barriers due to their direct influence on the effect group barriers. It is evident from

obtained results that identification of most influential barriers in industries during SSCM

adoption is necessary to ensure sustainable manufacturing practices as well as for

sustainable development (Luthra et al., 2011; Muduli et al., 2013; Rauer and Kaufmann,

2015). Hence, this study helps decision maker to identify the most influential barriers to

give more attention during SSCM implementation. Managers are able to define which

barriers within their industries need greater attention and which barriers may be given less

importance. The ranking of cause group and effect group barriers assist manager to take

action during SSCM implementation. During the sustainable supply chain management

implementation, this thesis framework will be effective for analyzing and identification of

numerous barriers. This proposed framework will be helpful for the industrial manager to

systematically organize their decision by proper planning and by computing the relative

importance and influence of different SSCM implementation barriers by using grey-

DEMATEL approach and on the industries SSCM program.

This thesis gives direction to a better understanding of the cause-effect

relationship of SSCM barriers. The effect group can easily influence by the cause group

and therefore managers need to attention on cause group during implementing SSCM

practices in their traditional supply chain. The results of this thesis could encourage

managers and top management to the adoption of SSCM practices which are more

54

important for sustainable development of a country and have a great effect on the

traditional supply chain. The sensitivity analysis results help to evaluate the stability of

experts and academic practitioner‘s opinion. The manager can consider this framework for

a benchmarking to improve the traditional supply chain which leads to improving

environmental, social and economic sustainability (Chin et al., 2015). The results reveal

that lack of awareness of local customers in green products (E4), lack of commitment from

top management (KS2) and cost of sustainability and economic condition (F1) takes place

first three priority casual barriers. Therefore, decision maker and manager should take

attention to those casual barriers during SSCM implementation. It is necessary to provide

governmental support and regulation to motivate companies for SSCM practices.

Therefore managers should understand that results of this thesis could be changed due to

the case situation.

55

Chapter 6

Conclusions and Recommendations

6.1 Conclusions

Foreign buyer pressure, global market demand and environmental policies, the

organizations are pushing to implement sustainable supply chain management practices in

their traditional supply chain network for sustainable development (Mathiyazhagan et al.

2014). For this reason, environmental sustainability, green issues, social sustainability

have an increasing popularity among researchers and supply chain practicing managers

(Hutchins and Sutherland, 2008; Zhu et al., 2008; Giannakis and Papadopoulos, 2016; Xia

and Tang, 2011). Implementing SSCM practices in industries can ensure the long-term

environmental, social and economic benefits for both organizations and customers. Hence,

it is not easy task to implement SSCM in traditional supply chain network because of there

are numerous barriers present (Chkanikova and Mont, 2015; McCormick and Kåberger,

2007; A Sajjad et al., 2015). The goal of this thesis work was to identify and analyze

barriers that play a crucial role in hindering the implementation of sustainable supply chain

management practices in leather processing factory. Literature reveals that no study found

on sustainable supply chain management implementation in leather processing factory of

Bangladesh by using grey DEMATEL approach. This study has attempted to present

framework to analyze the barriers to adoption of SSCM practices in leather processing

factory with the help of a blended grey DEMATEL approach. The major contribution is to

identify and analyze the barriers from existing literature review and investigation of

relevant leather processing industry. 35 initial barriers are taken from existing literature

review and discussion with industrial experts. Twenty barriers are identified from 35

barriers through the initial survey. Therefore, it is not easy to eradicate all these barriers to

56

adoption of SSCM practices so industries must need to identify which barrier is major

obstacle for SSCM implementation. After discussion with experts and academic personnel,

a blended grey DEMATEL methodology is used which helps to identify cause-effect

relationships among different barriers, effectively ignoring imprecise judgments. In this

thesis, lack of awareness of local customers in green products and lack of commitment

from top management seem to be the most important barriers during SSSCM introducing

in traditional supply chain. Outdated machineries and lack of practices on reverse logistics

seem to be the most influential barriers that means other barriers can easily influenced to

those barriers and improvement of other barriers will directly influence those barriers.

Therefore our motivation is that this study helps to managers and planner to identify most

influential SSCM implementing barriers and eradicating those barriers by taking necessary

steps. Other industrial sector like textile, polymer, electronics, footwear, leather goods, and

mining of Bangladesh can also get idea from this thesis to find out the barriers for

sustainable manufacturing practices.

6.2 Recommendations

In this thesis, grey based multiple criteria decision-making tool DEMATEL is

proposed for analyzing and identifying of SSCM implementation barriers and a real life

industrial case study is introduced to show the way of testing proposed research model in

Bangladeshi context. The expectation is that this thesis will help to other industrial fields

of Bangladesh to evaluate barriers during SSCM implementations. This thesis could be

used for other industrial sector of Bangladesh like garments, footwear, leather goods,

polymer, food processing, mining, chemical, pharmaceutical etc. All of those industrial

sectors have harmful effect on environments and society. This thesis helps to industrial

manager to convert traditional supply chain to sustainable supply chain by considering

priority ranking of casual group barriers. This thesis cannot take all the barriers for

analysis. For this reason, other industrial sector can take relevant barriers for their analysis.

In future, other multi criteria decision making tools like Fuzzy-AHP, Fuzzy-VIKOR,

Fuzzy-DEMATEL, ANP, ISM, ELECTRE III, TOPSIS can be used for analysis barriers to

evaluate most influential barriers to adoption of SSCM practices (Bhatia and Chand, 2014;

Bhattacharya et al., 2014; Büyüközkan and Çifçi, 2012; Mangla et al., 2015; Wang et al.,

2012; Govindan et al., 2015; Sawadogo and Anciaux, 2009).

57

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Appendix A

Table 4.2: Identification of major barriers to adoption of sustainable supply chain management practices

Barriers Descriptions Relevant Literature

1. Information gap Lack of knowledge about sustainability and environmental relevant issues. Unwilling to implement green supply chain in manufacturing system.

Wu et al. (2012), Ghose (2003), Barve and Muduli (2013), Muduli et al. (2013),Shen and Tam (2002), Balasubramanian (2012), Mancini et al. (2012).

2. Costs of sustainability and poor economic conditions

Lack of interest to invest money for sustainability and also economic condition not well as like developed countries.

Nidumolu et at. (2009), Beske et at. (2008), Zhen Wang et al. (2015).

3. Absence of society pressure

Pressure from community, NGO and environmental authority is less.

Henriques and Sadorsky (1996), Guler et al. (2000), Zhigang Wang et al. (2015), Govindan et al. (2014), Giddings et al. (2002).

4. Lack of support and guidelines from regulatory authority/poor legislation

Absence of strong environmental legislation.

Hilson (2000), Wu et al. (2012), Le Bourhis et al. (2013), Nidumolu et al. (2009).

5. Non adaptation of cleaner technology

Unwilling to adopt pollution control & prevention technology.

Klassen and Whybark (1999), Vachon and Klassen (2007), Stephan Vachon (2007), Hu and Cheng (2013), Nowosielski (2007), Grutter and Egler (2004), Yusup et al. (2014).

6. Lack of eco-literacy amongst supply chain partner

Supply chain partner have not deeper knowledge about Sustainable manufacturing practice. Eco-literacy means the expertise conscious about environment during industrial activities.

Madsen and Ulhøi (2001), Li (2014), Theyel (2000), Tseng et al. (2013).

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Barriers Descriptions Relevant Literature

7. Less practice on reverse logistics

Absence of reverse logistics facility. Reverse logistics means reuse or recycle of the returned products for economic benefits.

Chan (2007), Jack et al. (2010), Pokharel and Mutha (2009), Sarkis et al. (2010), Verstrepen et al. (2007).

8. Capacity constraints Less facility of capacity for sustainable manufacturing practice.

Mudgal et al. (2010), Presley et al. (2007), Lee (2008), Muduli et al. (2013).

9. Lack of commitment from top management

Sustainable manufacturing practice in industry is ignored by top management.

Pun (2006), Seuring and Müller (2008), Fawcett et al. (2006), Hoejmose et al. (2012), Turker and Altuntas (2014).

10. In adequate supply chain strategic planning

In leather processing factory, strong supply chain strategic planning does not exist.

Pun (2006), Bansal and Roth (2000), Rugman and Verbeke (1998), Baumgartner and Korhonen (2010), MacDonald (2005).

11. Lack of market demand People do not conscious about green product. So that lack of demand of green product in market. Customers are price sensitive, interest in cheaper products; environment does not carry enough weight in the market.

Brécard et al. (2009), Lin et al. (2013), Wüstenhagen and Bilharz (2006), Chen et al. (2006), Graedel and Klee (2002).

12. Pressure for lower price Today‘s competitive market needs lower price with quality product. Green products need higher cost compare to other products.

Walker et al. (2008), Eltayeb and Zailani (2009), Khidir and Zailani (2009), Koho et al. (2011), Orsato (2006).

13. Lack of training and education about sustainability

Lack of knowledge about sustainable manufacturing practice. Insufficient program arranged by environmental authority.

Dubey and Gunasekaran (2015), Jabbour (2013); Ji et al. (2012), Johannessen and Olsen (2003), Wang and Wu (2013).

14. Lack of environmental requirements

Environmental management system incorporates operations and manages the entire environmental requirement.

Le Bourhis et al. (2013), Yuan et al. (2012), Arcury (1990), Brulle and Pellow (2006), National and Stewardship(2005).

15. Lack of sustainable communication technology

Inadequate application of E-ordering, Companywide ERP and intelligent network system.

Sandhu et al. (2012).

Table 4.2: Identification of major barriers to adoption of sustainable supply chain management practices (continued)

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Barriers Descriptions Relevant literature

16. Restrictive company policies towards product/process stewardship(RCPTPS)

Less control of minimizing environmental impact during role of designing, producing or selling of products over its entire life cycle.

Rakesh K Mudgal (2010), Beamon (2010), McKerlie et al. (2006), Madu et al. (2002).

17. Lack interest to share risk and award

Industries neither interest to share risk and give award for adopting environment friendly concepts.

Massoud et al. (2010), Young et al. (2010), Moldan et al. (2012), Parent et al. (2013), Blok et al. (2015).

18. Organizational boundaries

Lack of skilled staff, lack of experiences, less financial resources or capital access, green issues have low priority in leather industries of Bangladesh.

Jabbour and De Sousa Jabbour (2016), S. M. Lee et al. (2012), Santos and Eisenhardt (2005), Sarkis (2012), Sarkis et al. (2011), Stenberg (2007).

19. Poor supplier commitment

Lack of commitment between supplier and customer. Companies are often unwilling to exchange information.

Wycherley (1999), Stephan Vachon and Klassen (2006), Noci (1997), Hong et al. (2009).

20. Lack of awareness of local customers in green product(LALCGP)

Local customers are not aware about green products.

Bhanot et al. (2015a), Raci and Shankar (2005).

21. Unskilled human resources

Lack of quality worker and management personnel to implement sustainable manufacturing practice.

Parker et al. (2009), Hillary (2004).

22. Lack of technical expertise

Inadequate knowledge to find an alternative to design a pollution free product to implement sustainable manufacturing practice.

Revell and Rutherfoord (2003).

23. Lack of government support to adopt sustainable manufacturing practice.

Government regulations are not enough to adopt sustainable manufacturing practice.

Zhu and Geng (2013), Khidir and Zailani (2009), Prakash and Barua (2015), Govindan et al. (2013).

24. Misalignment of short term and long-term strategic goals

Lack of consciousness to align short term and long term strategy.

Rowe and Nejad (2009), Walker and Jones (2012).


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Barriers Descriptions Relevant Literature 25. Uncertain benefits

Insignificant economic advantage, slow returns on investment.

Mittal et al. (2013).

26. Resistance to change and adopt innovation

Less interest to adopt innovation.

Gaziulusoy et al. (2013), Whiteman et al. (2013), Lorek and Spangenberg (2014).

27. Power shortage Lack of facility of power supply during disturbances of electric power.

Bhanot et al. (2015a).

28. Lack of funds for sustainable manufacturing practice

Bank and other financial institute offer fewer funds for green projects.

Kulatunga et al. (2013).

29. Low availability of credit

Less facility to get funds from bank and financial institute with low interest rate.

Bhanot et al. (2015a), Jayal et al. (2010), Kulatunga et al. (2013), Wang et al. (2015).

30. Lack of training courses/consultancy/ institutions to train specific personnel.

Lack of facility to train people for sustainable development in leather sector.

Govindan et al. (2014).

31. Less of business friendly policy

Absence of business friendly policy.

Our contributed barrier.

32. Limited access to market information

The facility to access global market information is less.

(Technical Report, 2013).

33. Higher prices of imported processing chemicals for hides/skins

Price of Imported chemicals very high.


34. Outdated machineries in tannery

Backdated machineries present in tannery industry.

Our contributed barrier.

35. Absence of integrated policies

Policy maker does not consider integration of policies.



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