1. Institute Of Leather Engineering & Technology, University Of Dhaka, Bangladesh.

* Correspondence: trtanni306@gmail.com

Keywords: Green Supply Chain Management (GSCM), Bangladesh, barriers, leather goods industry

1. INTRODUCTION

In early environmental management frameworks, operating managers were involved only at arm’s length. Separate organizational units had responsibility for ensuring environmental excellence in product development, process design, operations, logistics, marketing, regulatory compliance and waste management. Today, this has changed. As in the quality revolution of the 1980s and supply chain revolution of the 1990s, it has become clear that the best practices call for integration of environmental management with ongoing operations. Green supply chain management (GSCM) is gaining increasing interest among researchers and practitioners of operations and supply chain management. The growing importance of GSCM is driven mainly by the escalating deterioration of environment, e.g. diminishing raw material resources, overflowing waste sites and increasing level of pollution. However, it is not just about being environment friendly; it is about good business sense and higher profit. There is a number of  serious environmental, economic and social issues that are highly interlinked and have been faced as major challenges during the past one or two decades [1]. This is mainly due to unsustainable patterns of consumption and production in business, resulting in scarcity of natural resources and large amount of waste generation by polluting the environment. Environmental management is an important topic in supply chain management (SCM). Due to Government legislation and increased consciousness among stakeholders to preserve the environment, organizations are coerced into executing environmental practices to improve their green image and survive in in the global market [2]. The issue of an environmentally conscious supply chain or Green Supply Chain Management (GSCM) has grown into the recent years and both academia and industry are interested in this [3], [4]. GSCM has appeared as an organizational philosophy which assists firms to enhance their financial affairs and market share by reducing environmental negative impact and improving ecological efficiency [5]. Beamon (1999) has defined green supply chain as “ The expansion of traditional supply chain to include activities to reduce waste of resources and negative environmental effects of a product throughout its entire life cycle, from extraction of raw materials to final utilization and disposal [6]. GSCM is an integration of natural environmental worries into supply chain management by implementing various green practices like life cycle analysis (LCA), green design, green purchasing, 3Rs (recycling, reuse and remanufacturing), environmental technologies, green logistics, and collaborative practices with suppliers, distributors and customers [7], [8]. It is necessary to analyze the interrelationship between green practices and performances to reach GSCM efficiency and gain a sustainable competitive advantage. Anyway, many industries hesitate to take a more proactive approach to include GSCM practices due to a lack of verification as to whether GSCM performances and benefits surpass the costs of implementing such practices and initiatives [9]. Moreover, as studies which consider links and interrelationships between GSCM practices and performances are limited, it emphasizes the need for future study which examines the relationship of GSCM practices, and economic and environmental performances. There is a growing need for integrating environmentally sound choices into supply-chain management study and practice. Perusal of the literature shows that a broad frame of reference for green supply-chain management (GSCM) is not adequately developed. Regulatory bodies that formulate regulations to meet societal and ecological concerns to facilitate growth of business and economy also suffer from its absence. A succinct classification to help academicians, researchers and practitioners in understanding integrated GSCM from a wider perspective is needed. Further, sufficient literature is available to warrant such classification. This paper takes an integrated and fresh look into the area of GSCM and its barriers in implementing it in Bangladesh. Using the rich body of available literature, including earlier reviews that had relatively limited perspectives, the literature on GSCM is classified on the basis of the problem context in supply chain’s major influential areas. It is also classified on the basis of methodology and approach adopted. Various mathematical tools/techniques used in literature vis-à-vis the contexts of GSCM are mapped. Finally, the findings and interpretations are summarized, and the main study issues and opportunities are highlighted. Applying green procurement preferences to promote environmental initiatives is encouraged by governments in many countries [10]. While GSCM issues are currently highly relevant for export industries, this issue is expected to influence the whole industries of Bangladesh in a significant way. Industries should consider green issues as green/eco-products can provide them with great marketing advantages and a good corporate image [11]. By promoting eco-products, industries can make their own contribution to economic benefits and environmental protection for society at large [12]. Hence, Bangladeshi industry should adopt a proactive approach to address issues of green supply chain/ green purchasing for future competitiveness. The adoption of Green Supply Chain Management (GSCM) in the Bangladeshi leather goods industry is a significant concern due to increasing pollution, limited resource availability, and growing environmental consciousness. However, GSCM implementations are complicated by various barriers, which can be identified and categorized based on their meaning and similarities. This study aims to understand these barriers from a Bangladeshi perspective, focusing on the Bangladeshi Leather Goods Industry. The project consists of three objectives: identifying barriers to adopting green supply chain management, evaluating barriers in adopting green practices and performance, and implementing the Analytical Hierarchy Process (AHP) method to determine the relative importance of these barriers. The first objective is to identify the barriers to GSCM adoption in Bangladesh, as different organizations may have different views on these barriers. The second objective is to evaluate the GSCM barriers using an AHP approach to determine the relative importance of these barriers. The study methodology includes a step-wise procedure, solution methodology, and an overview of the AHP method. The application of the AHP tool in the leather goods industry is demonstrated through the development of questionnaires, data collection, and AHP calculation and method. Results and discussions include the categories and ranking description of barriers. The conclusion of the study provides managerial implications and limitations, as well as recommendations for the proposed project work. By understanding the barriers to GSCM implementation from a Bangladeshi perspective, businesses can better manage their green supply chain management strategies and contribute to a sustainable and competitive economy.

2. MATERIAL AND METHODS

This project has, as its goal, the identification of such essential barriers so that they might be removed during GSCM implementation in leather goods industries through the Analytical Hierarchy Process (AHP). This study was undertaken in the leather goods industries of Bangladesh. The results might impact environmental adoption ensuring easier removal of essential barriers. It may be expanded to all industries in Bangladesh. First of all, we have to go through various literature review papers about green supply chain management barriers and go to an industry for survey and their expert’s opinion about our topic. Then we collect major barriers with sub-barriers in each main category from literature and survey with the help of experts from the industry. Then we sort out most common barriers into main criteria and sub-criteria from the opinion of the expert. After that we evaluate the barriers and rank the selected barriers using AHP method based on experts’ opinion. If it is then accepted by the experts, then we may go to the next step and if it is not accepted by the experts then we go back to the second step collecting the barriers again and organized them. After accepting the ranking by experts’ final evaluation of ranking of the selected barriers of green supply chain management is done. Then we discussed about the final results of each barrier in each category. Finally, we described about its managerial implication and future direction of this study. Based on literature reviews and discussions with the industrial experts, a detailed questionnaire was framed and circulated to various industries in Bangladesh. Later, the returned questionnaires were examined and the most common barriers accepted by various industries were identified. From these identified common barriers, the essential key barriers were picked using an AHP approach. An overview of AHP method is given below, in this work, Analytic Hierarchy Process (AHP) is used as the solution methodology. Analytic Hierarchy Process (AHP) is a multi-criteria decision making method that was initially proposed by Prof. Thomas L. Saaty. It is an MCDA approach which assists in analyzing, organizing and evaluating a complex multi criteria problem. It converts the problem attempted into a hierarchical structure comprising of different definite levels, like goal, criteria and sub-criteria [1], [76]–[79]. In short, it is a technique to get proportion scales from paired comparisons. The input of the process can be picked from real estimation, for example, length, intensity etc., or from subjective assessment such as satisfaction, review, interview and preference. AHP may hold some small inconsistency in judgment since human perceptions are not always consistent. The ratio scales and consistency index are derived consecutively from the principal Eigen vectors and the form the principal Eigen value. There are numerous additional methods, like ELECTRE and TOPSIS that have been presented to solve the multi criteria decision making problem. However, AHP is suggested as a better tool in comparison to others due to its wide applicability and ease in use [80]. Therefore, we implement an AHP method to evaluate green supply chain risks and drivers with respect to the scenario of Bangladesh. The summary of application of AHP method to green supply chain barriers assessment is tabulated in Table 01.

Table 01: Summary of application of AHP method to green supply chain barriers evaluation

Sl. NO.	Author	Contribution
1	[81]	AHP approach for supply chain management evaluation
2	[82]	Application of Fuzzy AHP for Evaluation of Green Supply Chain Management Strategies
3	[83], [84]	A fuzzy AHP-TOPSIS framework for ranking the solutions of Knowledge Management adoption in Supply Chain to overcome its barriers
4	[85], [86]	Risk analysis in green supply chain using fuzzy AHP approach
5	[87], [88]	Managing risks in the supply chain using the AHP method
6	[89]	study on the Optimization of Green Suppliers Based on AHP

The AHP aims to evaluate barriers in green supply chain implementation by forming an aim and forming pairwise comparisons using data from a leather goods company and expert opinions, using a nine-point Saaty’s scale.

Table 02: Saaty’s Scale Values for Random Consistency Index

n	1	2	3	4	5	6	7	8	9	10
RI	0	0	0.58	0.9	1.12	1.24	1.32	1.41	1.45	1.49

First, a set of pairwise comparison matrices for each level of the hierarchy are formulated and then all the pairwise comparisons are calculated. The pairwise comparison matrix is A and element a_ij of the matrix is the relative importance of i^th barrier with respect to j^th barrier. The representation is done like the following:

A = [a_ij]

Where the entry in row i and column j of A (a_ij) indicates how much important barrieri is than barrier j. Each entry in matrix A is positive (a_ij> 0) and reciprocal ((a_ij= 1/a_ji) for all i, j= 1,2, 3,…n) [91]. “Importance” is measured on an integer-valued 1-9 scale reported in Table 03. It makes the transformation of qualitative judgments or intangible attributes into preference weights (level of importance) or numerical values.

Table 03: The AHP pair-wise comparison values or scale of preference between two elements [91]

Preference weights or level of importance (value of aij)	Definition of verbal scale	Explanation
aij=1	If the two criteria are equally Preferred	Two activities or criteria contribute equally to the objective or goal
aij=3	If criteria i is moderately preferred than criteria j	Experience and judgment slightly favor criteria over another
aij=5	If criteria i is strongly preferred than criteria j	Experience and judgment strongly favor one criteria over another
aij=7	If criteria i is very strongly preferred than criteria j	A criterion is strongly favored over another and its importance demonstrated in practice
aij=9	If criteria i is absolutely preferred than criteria j	The evidence favoring one criteria over another is of the highest degree possible of affirmation
2,4,6,8	Intermediate values	Use to compromise between two judgments

The pairwise comparisons are performed in terms of which element dominates or influences the order. AHP can aggregate many aspects of the decision situation into a single objective function. Its goal is to choose the best alternative that can optimize the objective function making pairwise comparisons of the criteria using Saaty’s nine-point scale. The nine-point scale seeks to know the dependence criteria, which one will impact on the common criteria more and if that, how much more. According to Saaty, a value of 1 between two criteria denotes that both criteria equally influence the focused point, where a value of 9 indicates that the effect of one criterion is extremely more important than the other. The framed pair-wise comparisons matrices were operated to determine the Eigen values and Eigen vectors, which are further analyzed to calculate the relative importance weights of the factors. The consistency ratio (CR) is computed to ensure the consistency of pair wise comparisons. The used mathematical expression for finding the CR is given as, CR = CI/RI, where the consistency index is denoted by

and the value of the random consistency  index  (RI) depends upon value of (n).The value of CR should be less than 0.10  to have better level of consistency [78].  The PICARD Bangladesh Ltd. Company was established in 1997, a Germany joint venture company, was created to become the largest leather goods manufacturer unit in Southeast Asia. Today, it is renowned worldwide for its outstanding product quality and service. Their premium leather supplier Austan Ltd is a 100% export oriented finished leather manufacturer for hand-bags and shoes by using high quality Bangladeshi raw materials for the very competitive markets in North America, Europe, China, Hong-Kong, Australia, Japan and Korea. They are one of the 1st companies among the tanneries in Bangladesh who are using their own environmentally compliant Effluent Treatment Plant to reduce the health and environmental threats. They are Bangladesh’s first Environment Compliant ISO 14001:2004 certified company. They produce currently leather bags and small leather goods. 32000 bags monthly and 40000 leather goods monthly. This leather goods and bags are exported to 15 different countries in the world and they have 20 clients around the world. To examine the case company, a decision team of ten professionals is formed. There are four senior supply chain managers, three environmental scientists, two project managers and one state pollution control board member. The professionals selected are highly skilled in their domains and are proficient in decision- making. Including, all of the experts have an experience of more than seven years. According to the study of [92], the professionals at this stage are knowledgeable and may help incremental acceptance of environmental management concept. These experts were interviewed personally for collecting the necessary qualitative and quantitative data needed for present study. The case company has a desire to reduce its environmental impact and wants to contribute to build a green and sustainable culture. It also wishes to limit the leather consumptions in order to guarantee sustainability from the point of view of business, society, people, nation etc. But the company managers were facing some difficulties in managing green and sustainable practices in greening the supply chain throughout the network. Consequently, there is decrease in GSCM performances, and may result into degradation of environment, climate problems, pollution and hazardous gas emissions etc. Despite the fact that many businesses find out the significance of GSCM because of governmental law and have shown their commitment to implement GSCM practices, it is still a relatively fresh concept in Bangladesh. The government has encouraged environmental partnership by supporting companies to start and improve their GSCM. Further, this company plans to execute green practices at all levels of production process as a proactive approach to attain profit and market share goals by reducing environmental impact and improving ecological efficiency. Hence, Picard was selected as a case company to consider and develop GSCM practices and performance. Questionnaires were designed to facilitate data collection. Our data collection’s two phases are discussed in the following, Section 5.2.1, Phase 1: Initial survey to identify common barriers Section 5.2.2, Phase 2: Identification of essential barriers. This study targeted managers in the middle or higher management levels from various in Bangladesh. Before starting this work, the objective of the survey, together with the GSCM concepts, were introduced to target respondents by proper documents to ensure that they fully understood various items in the survey questionnaire, its overall goals and objectives of the study and how the data would be used. From the 21 recommended barriers, the respondents were asked to identify the important barriers (given the choice of ‘Yes’ or ‘No’ for each barrier) for GSCM implementation in their industry.  Questionnaires were mailed to some of our leather goods industries and pursued periodically to ensure a quick and proper response. The duration of this initial survey was 15days. Hence, the valid overall response rate was 25.64%. Malhotra and Grover (1998) suggested that a response rate of 20% was enough for a positive assessment of the survey. From this initial survey, we observed that Bangladeshi Leather Goods industries are less aware of the environmental impact on their business but are still at the very initial stages of GSCM implementation.

Table 04: Experts Interview

Main Category of Barriers	Sub-Barriers	If relevant to leather products industry please write YES otherwise write NO
A.    Management related barriers (B1)	Lack of support from top management (B11)
	Lack of active plans to apply green supply chain management (B12)
	Lack of willingness to produce green product (B13)
B.     Technology related barriers (B2)	Lack of latest technology, materials and processes (B21)
	Lack of experienced technical expertise (B22)
	Difficulty in reducing the consumption of energy (B23)
C.    Governance and supply chain process related barriers (B3)	Difficulties with supply chain members (B31)
	Limited forecasting and planning (B32)
	Lack of house facilities and difficulty in operations (B33)
D.    Outsourcing related barriers (B4)	Lack of government support to adopt environmental friendly policies (B41)
	Lack of friendly and environmental partnership with suppliers (B42)
	Problem in maintaining and raising environmental suppliers (B43)
E.     Financial barriers (B5)	High investment and low profit (B51)
	Risk in hazardous material inventory and high cost of these materials disposal (B52)
	Non-availability of bank loans to encourage green products (B53)
F.     Knowledge related barriers (B6)	Lack of environmental knowledge among workers, manufacturers and suppliers (B61)
	Lack of awareness of customers (B62)
	Lack of facility of training on green system exposure to professionals (B63

In this section, the identification of essential barriers for GSCM implementation was done using the AHP approach. After the initial survey 18 common barriers were identified and raised to a level of concern. This phase is categorized into four hierarchy decision process levels. The four levels are described below:

Level-1: The objective/overall goals

Level-2: This level represents the barrier category

Level-3: This level of the hierarchy contains specific barriers

Figure 01: AHP framework for identifying essential barriers of GSCM implementation 

Table 05: Selected barriers with identification code

Main Category of Barriers	Sub-Barriers	Identification Code
A.    Management related barriers (B1)	Lack of support from top management	B11
	Lack of active plans to apply green supply chain management	B12
	Lack of willingness to produce green product	B13
B.     Knowledge related barriers (B2)	Lack of environmental knowledge among workers, manufacturers and suppliers	B21
	Lack of awareness of customers	B22
	Lack of facility of training on green system exposure to professionals	B23
C.    Outsourcing related barriers (B3)	Lack of government support to adopt environmental friendly policies	B31
	Lack of friendly and environmental partnership with suppliers	B32
	Problem in maintaining and raising environmental suppliers	B33
D.    Governance and supply chain process related barriers (B4)	Difficulties with supply chain members	B41
	Limited forecasting and planning	B42
	Lack of house facilities and difficulty in operations	B43
E.     Financial barriers (B5)	High investment and low profit	B51
	Risk in hazardous material inventory and high cost of these materials disposal	B52
	Non-availability of bank loans to encourage green products	B53
F.     Technology related barriers (B6)	Lack of latest technology, materials and processes	B61
	Lack of experienced technical expertise	B62
	Difficulty in reducing the consumption of energy	B63

 

Table 06: The AHP pair-wise comparison values or scale of preference between two elements [91]

Preference weights or level of importance (value of aij)	Definition of verbal scale	Explanation
aij=1	If the two criteria are equally Preferred	Two activities or criteria contribute equally to the objective or goal
aij=3	If criteria i is moderately preferred than criteria j	Experience and judgment slightly favor criteria over another
aij=5	If criteria i is strongly preferred than criteria j	Experience and judgment strongly favor one criteria over another
aij=7	If criteria i is very strongly preferred than criteria j	A criteria is strongly favored over another and its importance demonstrated in practice
aij=9	If criteria i is absolutely preferred than criteria j	The evidence favoring one criteria over another is of the highest degree possible of affirmation
2,4,6,8	Intermediate values	Use to compromise between two judgments

First, Pair wise comparisons are derived for both the criteria and the sub-criteria of risks using expert’s inputs through a Saaty’s scale.  This way a pair wise comparison matrix for the main categories of risks is framed and their relative weights and ranks are found out.

Table 07: Pair wise assessment matrix for main categories of green supply chain barriers

Barriers	B1	B2	B3	B4	B5	B6	Relative Weight	Rank
B1	1	1	2	3	2	3	0.2718	1
B2	1	1	2	2	1/3	2	0.1761	3
B3	1/2	1/2	1	2	1/2	3	0.1426	4
B4	1/3	1/2	1/2	1	1/2	2	0.0988	5
B5	1/2	3	2	2	1	3	0.2421	2
B6	1/3	1/2	1/3	½	1/3	1	0.0685	6

 

Maximum Eigen Value =6.38556584; C.I. =0.07711317. Likewise, the pair-wise comparison matrices for sub-barriers under each category and their corresponding relative weights are shown in table.

Table 08: Pair-wise assessment matrix for Management related barriers in the green supply chain

	B11	B12	B13	Relative Weight	Rank
B11	1	2	3	0.5278	1
B12	0.5	1	3	0.3325	2
B13	0.3333333	0.33333	1	0.1396	3

Maximum Eigen Value =3.05362; C.I. =0.0268108

Table 09: Pair-wise assessment matrix for Knowledge related barriers in the green supply chain

	B21	B22	B23	Relative Weight	Rank
B21	1	0.33333	2	0.2493	2
B22	3	1	3	0.5936	1
B23	0.5	0.33333	1	0.1571	3

Maximum Eigen Value = 3.05362; C.I. = 0.0268108

Table 10: Pair-wise assessment matrix for Outsourcing related barriers in the green supply chain

	B31	B32	B33	Relative Weight	Rank
B31	1	3	3	0.5936	1
B32	0.3333333	1	2	0.2493	2
B33	0.3333333	0.5	1	0.1571	3

Maximum Eigen Value = 3.05362; C.I. = 0.0268108

Table 11: Pair-wise assessment matrix for Governance and supply chain process related barriers in the green supply chain

	B41	B42	B43	Relative weight	Rank
B41	1	0.2	1	0.1562	3
B42	5	1	3	0.6586	1
B43	1	0.33333	1	0.1852	2

Maximum Eigen Value = 3.02906; C.I. = 0.0145319

Table 12: Pair-wise assessment matrix for financial barriers in the green supply chain

	B51	B52	B53	Relative Weight	Rank
B51	1	3	3	0.5936	1
B52	0.3333333	1	0.5	0.1571	3
B53	0.3333333	2	1	0.2493	2

Maximum Eigen Value = 3.05362; C.I. = 0.0268108

Table 13: Pair-wise assessment matrix for Technology related barriers in the green supply chain

	B61	B62	B63	Relative Weight	Rank
B61	1	3	2	0.53961	1
B62	0.3333333	1	0.5	0.16342	3
B63	0.5	2	1	0.29696	2

Maximum Eigen Value = 3.0092; C.I. = 0.004601

The pair wise comparison matrices are operated to determine the relative importance of weights are assigned corresponding to each category of barriers as given in Table.

Table 14: Global ranking of green supply chain barrier

Major Barriers	Relative Weights	Specific barriers	Relative Weights	Relative Rank	Global Weights	Global Rank
A.      Management related barriers (B1)	0.2718	B11	0.5278	1	0.1435	2
		B12	0.3325	2	0.0904	4
		B13	0.1396	3	0.0380	10
B. Knowledge related barriers (B2)	0.1761	B21	0.2493	2	0.0439	8
		B22	0.5936	1	0.1046	3
		B23	0.1571	3	0.0277	13
C. Outsourcing related barriers (B3)	0.1426	B31	0.5936	1	0.0846	5
		B32	0.2493	2	0.0355	12
		B33	0.1571	3	0.0224	14
D. Governance and supply chain process related barriers (B4)	0.0988	B41	0.1562	3	0.0154	17
		B42	0.6586	1	0.0651	6
		B43	0.1852	2	0.0183	16
E. Financial barriers (B5)	0.2421	B51	0.5936	1	0.1437	1
		B52	0.1571	3	0.0380	9
		B53	0.2493	2	0.0604	7
F. Technology related barriers (B6)	0.0685	B61	0.5396	1	0.0370	11
		B62	0.1634	3	0.0112	18
		B63	0.297	2	0.0204	15

3. RESULTS AND DISCUSSION

We infer from the table that the management related barrier is the first priority among the barriers categories. Unwillingness from the top management is a crucial barrier for GSCM implementation. The Financial barrier receives the next highest weight. Therefore, it shows that industries commonly need more finance to extend their environmental management systems. The knowledge barrier category ranks third, has found that there is a lack of knowledge in measuring environmental performance in supply chain management. The Outsourcing barrier category receives the fourth position. Green purchasing was explored to determine the key factors affecting the buying firm choice of suppliers, including major barriers and obstacles. Governance and supply chain related barriers and technology barriers is not so essential in comparison to other barrier categories.

Table 15: AHP weights for barrier category

Barrier category	Sorted weight value
Management	0.2718
Financial	0.2421
Knowledge	0.1761
Outsourcing	0.1426
Governance and Supply Chain Related	0.0988
Technology	0.0685

Table 16: Final Result

Main Category of Barriers	Rank	Sub-Barriers	Rank
A.    Management related barriers (B1)	1	Lack of support from top management (B11)	2
		Lack of active plans to apply green supply chain management (B12)	4
		Lack of willingness to produce green product (B13)	10
B.     Knowledge related barriers (B2)	3	Lack of environmental knowledge among workers, manufacturers and suppliers (B21)	8
		Lack of awareness of customers (B22)	3
		Lack of facility of training on green system exposure to professionals (B23)	13
C.    Outsourcing related barriers (B3)	4	Lack of government support to adopt environmental friendly policies (B31)	5
		Lack of friendly and environmental partnership with suppliers (B32)	12
		Problem in maintaining and raising environmental suppliers (B33)	14
D.    Governance and supply chain process related barriers (B4)	5	Difficulties with supply chain members (B41)	17
		Limited forecasting and planning (B42)	6
		Lack of house facilities and difficulty in operations (B43)	16
E.     Financial barriers (B5)	2	High investment and low profit (B51)	1
		Risk in hazardous material inventory and high cost of these materials disposal (B52)	9
		Non-availability of bank loans to encourage green products (B53)	7
F.     Technology related barriers (B6)	6	Lack of latest technology, materials and processes (B61)	11
		Lack of experienced technical expertise (B62)	18
		Difficulty in reducing the consumption of energy (B63)	15

The ranking of specific barriers is shown in the table given below revealing that overall ranking is based on the global weight values of the AHP approach. Global weights are obtained by multiplying the relative weight of the barrier category values of with the relative weights of specific barrier. The result of each barrier, based on barrier categories, is discussed in the following sections. In implementing any system, involvement and support of management is important especially in issues such as GSCM adoption [11]. GSCM did not evolve alone. There are many corporate and industrial environmental philosophies and practices closely linked to and in support of green supply chain management [93]. This survey revealed that involvement and support management barrier category and specific barriers obtained the lowest weights. Under this category, Lack of support from top management (B11) barrier comes first. Corporate environmental awareness is most important to adopt GSCM. Lack of proactive plans to apply green supply chain management (B12) is next to B11. Proper planning about environmental seminars, training courses and mentorship programs is poor in our country from the top management of the industries. Lack of willingness to produce green product (B13) comes next. Industries are often unwilling to exchange information on green supply chain management, fearing exposure of an inherent weakness or giving other companies a competitive advantage [94]. Presently most industries are involved in adopting GSCM and are aware of GSCM benefits, but more commitment is certainly required for 100% progress. Green practices require radical changes in mindset and practice. Many authors have discussed the role of top management to determine a firm’s level of environmental commitment. In GSCM implementation, the lack of financial support is usually considered as the most important constraint to environmental actions [26]. In this barrier category, High investment and low profit (B51) is a dominant barrier. It reveals that industries in our country fear to invest for green supply chain management due to risk of loss or low profit. The non-availability of bank loans to encourage green products/processes (B53) acts is next to B51 barrier based on its weight. In Bangladesh compared to other developed countries, has a long sanctioning process, one that requires more time and extensive documents. Thus initiatives to start industries and to adopt environmental initiatives like green supply chain management may evolve a lengthier process. Risk in hazardous material inventory and high cost of these waste disposal (B52) ranks third in this category. It is also a significant financial barrier. From survey report, it is seen that industries will not risk profits, but they are ready to initiate environmental management systems if they can do so without violating profits. The knowledge barrier category is comprised of three barriers. Lack of awareness among customers (B22) barrier comes first. Customers are still unaware about green product and their usefulness and benefits of environment friendly products. Lack of environmental knowledge among workers, manufacturers and suppliers (B21) barrier comes next which shows that there is lack of preparedness owing to the low level of uptake of environmental management systems due to ignorance which in turn becomes a significant barrier. Lack of facility of training on green system exposure to professionals (B23) is considered next. The professionals in industries are less exposed to green system, moreover there is lack of facility of training programs on green systems and industries are reluctant to take responsibility to adopt and update environmental issues like green supply chain management. Lack of government support to adopt environmental friendly policies (B31) is the most essential barrier. Lack of government support and incentives is a significant barrier to acquire an environmental certificate. Lack of friendly and environmental partnership with suppliers (B32) barrier comes next. Industries generally do not have proper monitoring systems for their supplier’s environmental practices, so that there is lack of a friendly environment in their relationship. Problem in maintaining and raising environmental suppliers (B33) barrier comes last in this category. Outsourcing new knowledge through collaboration with suppliers is problematic in situations of technology privacy. This category demonstrates that industries have been forced to focus on new technology trends that help the environment. Limited forecasting and planning (B42) is the most important barrier in this category. There is a limitation in forecasting and planning in the leather goods industries in our country because many industries experience difficulties in forecasting and planning due to degree of diversity of goods and flows [95]. Lack of house facilities and difficulty in operations (B43) ranks as second barrier. It is hard for the industries to make a strategic decision on recovery options and to operate GSCM systems efficiently and effectively. A lack of house facilities claim that industries suffer from the combination of a lack of systems to monitor returns and a lack of house facilities like storage, equipment and vehicles as they are key barrier to their GSCM implementation. Difficulties with supply chain members (B41) comes next as third barrier of this category. Apparently poor coordination and support in the supply chain functions as an impediment for the implementation of GSCM.Lack of latest technology, materials and processes (B61) is identified as first barrier in this category. Underdevelopment of latest technologies, non-availability of appropriate technology/process within industry to adopt green supply chain and lack of eco-friendly materials causes this barrier as first one. Difficulty in reducing the consumption of energy (B63) is considered as second barrier. The industries face difficulties in designing a technology which can easily reduce usage of resource energy. Lack of experienced technical expertise (B62) barrier is considered as last one in this category. There is a lack of skilled technical experts and they failed to find an alternative to design a pollution free product to fulfill environmental requirements. This paper discusses identification of essential barriers from an organizational point of view. AHP is used to provide a simple approach and helps decision-makers to identify essential barriers. Using the AHP framework ensures that qualitative judgement is quantified to provide a highly precise comparison and to reduce or to eliminate any unbalanced scale of judgements, uncertainty, and imprecision among the pair-wise comparisons. Both the identification of barriers and the insights on GSCM provided contribute to the importance of this survey.

4. CONCLUSION

The study has identified essential barriers requiring elimination during GSCM implementation. The work has successfully given priorities (rank) to barrier categories and specific barriers based on experts’ judgments by AHP. It is not possible to remove all obstacles when starting GSCM implementation in industries. The paper has provided industries with extensive solutions for identification of essential barriers, and it provides a benchmark that may assist them during their GSCM implementation. The study revealed that leather goods industries in Bangladesh still struggle to prioritize environmental performance improvements over economic performance. Similarly, most industries struggle for financial support for new environmental adoptions. The leather goods industries also have low awareness on sharing of environmental knowledge and updating environmental technologies. However, they are interested in improving environmental performance. The results of this study reveal important implications for managers. Several managerial suggestions are from the results analysis. It is necessary to concentrate on the cause group criteria due to their influence on the effect group criteria. Managers are able to define which green practices within their organization require more attention and which green practices may be given less significance. This ranking assist managers allocate resource and financial investments in appropriately. Further, this method is effective by providing a general decision framework. Moreover, managers should invest on green purchasing which considers issues like waste reduction and hazardous material minimization. It is essential for mangers to give top attention to suppliers’ environmental performance and to ensure that the purchased materials are environment friendly. Further, it is worthwhile for managers to focus on reverse logistics and advance strategies of recovery and reuse of used products to improve environmental and financial performance. It is necessary for governmental managers to put provide motivation like financial support or tax incentives to guarantee more intense involvement of companies in GSCM practices. The motivations of companies to apply GSCM practices include proactive or reactive incentives like cost savings, gain in the competitive advantage, improvement in environmental performance, and legislation. Future researches may repeat this method using multiple experts to justify the validity of the study. It should be mentioned understanding the barriers and drivers of GSCM implementation help supply chain managers introduce environmentally effective practices. So future researches can develop GSCM barriers and motivations and their effects on GSCM practices. Moreover, this study has explored only one case study in a leather goods industry, hence conclusions may not suit various sectors. As different sectors might have different products, process characteristics or legislative requirements which affect supply chain management and environmental performance, future works should conduct study related to investigation of GSCM practices and performances in different industrial sectors.

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