Because firms are considering the influence of their operations on the environment, the green supply chain has become a crucial indication of corporate performance. The issues here necessitate both competent management and a fresh, innovative strategy for cost reduction, productivity enhancement, and natural resource protection. We shall try to understand the Barriers of Green Supply Chain Management concept in this report. A total of 47 obstacles were discovered after a thorough review of the literature. Priority ranking stability is investigated via a sensitivity analysis. Using existing models have mostly focused on identifying these constraints.

1. Introduction

In recent years, ecological hardship and devastation have drawn attention to the negative repercussions of human activities. Green supply chain practices are gaining traction in today’s manufacturing environment. Natural resource depletion, rising consumer demands for quality and quantity, tight regulations, and cost reduction are all issues we face. On the other side, environmental protection by the government and the general population is a significant problem and hardship. As a result, the GSCM, or “Green Supply Chain Management,” addresses the environmental conundrum, which illustrates the absorption of environmental issues into traditional SCM, or “Supply Chain Management,” on many levels. GSCM is essential for decreasing a manufacturing facility’s total negative environmental impact. Green values can be included into everyday supply chain operations [1]. Nonetheless, the benefits of the GSCM in the sector, as well as the adoption of the Green ideology, will pose a slew of issues for businesses. The difficulties, referred to as problems encountered throughout GSCM’s employment, are classified into five categories: subcontracting, technology, information, financial, engaging, and supporting.

The following is how this paper is made: A literature overview of GSCM obstacles is presented in Section 2. part 3: a list of all the barriers that we were able to get from the studies Section 4 discusses the study’s solution method, which represents the two solutions that we will focus on: the ISM and the AHP. Finally, section 5 summarizes the study’s findings and makes recommendations for further research [2].

2. Literature review and background.

Despite the benefits and relevance of the GSCM for our company and future, businesses may face challenges in implementing the Green idea. Obstacles experienced during GSCM’s time on the job.

Many scholars conducted a literature review, according to which [3–5] . The hurdles to GSCM are divided into five categories:

1. Inadequate technology and facilities.
2. A lack of awareness and assistance.
3. Administration and activity policies that are not supportive.
4. Economic problems.
5. Outsourcing.

Table 1: Some existing works on green supply chain barriers analysis [2]

3. The list of the barriers in GSCM

Based on literature surveys and research conducted [14], 47 obstacles were discovered and categorised based on their context and similarities throughout this study. Table 2 lists the sources of source barriers.:

Table 2: List of barriers [14]

4. Solution methods

4.1. Interpretive structural modeling:

ISM (Interpretive Structural Modeling) is a tool for assessing the relationship between specific elements that define a problem or issue. It was first created in the 1970s. [15], [16]. ISM is interpretive since the choice of group for analysis determines if and how the variables are linked.[17] These ISM modeling phases are depicted in Figure 1.

Table 3: Top 12 barriers of green textile supply chain [13]

• Stage 1: Variables that impact the system: barriers (Table 2)
• Stage 2: With the most experienced supply chain managers and corporate executives, a group investigation is conducted to identify the most prominent barriers and establish a short list for the ISM study based on the hurdles highlighted in phase 1:

Example of case study of textile in South-east Asia [13]:

• Stage 3 : The formation of the structural self-interaction matrix is the first stage of the ISM (SSIM). Between either of the two obstacles I and j) and the related relationship path, contextual relationships were tested. Four symbols were utilized to represent the orientation of the relationship between two barriers (I and j) .:
• V: Barrier I has an impact on Barrier J.
• A: Barrier J has an impact on Barrier I .
• X: I and j are barriers that impact each other.
• O: The I and j barriers have nothing to do with each other.

• Stage 4: The SSIM has developed an accessibility matrix that has been tested for transitivity. ISM makes a key assertion about the transitivity of contextual interactions. Variable A must be associated with variable C if variable B is connected with variable C. SSIM was transformed to a binary matrix called the Initial Reachability Matrix by replacing V, A, X, and O with 1 or 0 and implementing the following principles. o If the SSIM entry I j) is V, the entries I j) and (j, I become 1 and 0, respectively.

o If the SSIM entry (I J) is A, the entries (I J) and (J, I) become 0 and 1, respectively.

o If the SSIM entry (I J) is X, then both (I J) and (J I) become 1.

o If the SSIM entry (I J) is O, then both (I J) and (J, I become 0.

Table 4: Reachability matrix [13]

• Stage 5 : The reachability matrix from Phase 4 was separated into many layers. The final reachability matrix’s reachability and history collection [15] For each factor, they are obtained. The intersection of the sets was then used to extract all variables. The top-level factor in the ISM hierarchy becomes the factor for which the accessibility and intersection sets are the same. [17]:

Table 5: Level partitions  [13]

• Step 6: Table 5’s level is utilized to generate a new digraph that contains transitivity ties that have been gained: A final digraph was constructed once the indirect connections were removed. The top level of the digraph was placed at the top. the second level at the second position. and so on until the bottom level was placed at the lowest position of the digraph.

• Stage 7: The generated diagraph is transformed into an interpretative structural model by replacing variable nodes with sentences [17].

The driver’s power-dependence matrix reveals the relative importance of each aspect as well as their interdependence. Factors of Autonomy / Dependence / Driving / Linkage

4.2. Analytic Hierarchy Process

The Analytic Hierarchy Process (AHP). which rigorously delineates the complexity of the issue setting. is based on a set of assumptions. It is built on a well-defined mathematical structure of consistent matrices and the capacity to construct true or approximate right-hand weights. the eigenvector [18]. It’s a multi-criteria decision-making (MCDM) methodology that’s been successfully used to environmental challenges in recent years. This method is commonly used in the corporate world to make decisions [19].

Three criteria have been used to AHP to assure the grading of obstacles to GSCM deployment. and the findings have been reported.

4.2.1. Identifying roadblocks and constructing a hierarchical prioritizing model. as specified in Chapter III

The common impediments are identified and escalated to a priority level of concern after the first stage. In this level Figure 6. the four-hierarchy choice process is broken down into phases:

• Level-I: The goal/general purpose.
• Level-II: This is the level reflected in the barrier group.
• Level III: This level of the system presents unique obstacles.
• Level-IV: Priorities for critical barriers are defined at this level.

4.2.2.  Establish normalized weights for each barrier category and each individual barrier

We’ll need a numerical scale to do comparisons that demonstrates how much more significant or better one piece is than another in terms of the criteria or characteristic being compared against.

Table 6: Selection ratio among two components

4.2.3. Pair-Wise Comparison Matrix Consistency Check [20]

The consistency ratio may be computed using the procedures below:

• Calculate the eigenvector or relative weights for each n-dimensional matrix.
• Compute the consistency index for each matrix of order n by the formula: CI = (λmax−n) / (n−1)
• The consistency ratio is then calculated using the formula: CR=CI/RI (random Index)

Arrange the elements in a matrix and get comments from individuals who are arguing the relative relevance of the various factors in relation to the ultimate objective of home happiness [21]. Table 6 depicts the decision-making scale to be used. This scale has been proven to be effective in a variety of applications as well as theoretical comparisons with a variety of other scales.

Table 7: Pair-by-pair comparison matrix for the barrier group [14]

Table 8: Standardize matrix of barrier category

The weight is simply derived by dividing each value from Table 7 by the sum, yielding the standardised matrix,

To test if the measured value is right, multiply the value of the column of criterion value by the weight,

Table 9: Matrix of pair-wise comparisons multiplied by weight [14]

Table 10 :Weighted sum value ration with Critirea value [14]

So λ max = 5,39114602

CI = (λmax−n) / (n−1) = 0,0977865 è 0<CI<1

CR = CI/RI = 0,094732

The random index is abbreviated as RI, the random index table for up to 10 parameters was shown by the randomly produced pairwise matrix consistency index [14]:

We may assume that the matrix is sufficiently consistent since CR 0,1 and then utilize the result

Table 11 : AHP weights for barrier category [14],

5. Conclusion

To focus on environmental challenges, manufacturing firms have lately begun to implement the green idea in their supply chain management. However, owing to the identification of impediments, the process of applying green concepts in their supply chain management was found to be extremely challenging. The goal of this study is to identify and prioritize the hurdles to implementing Green supply chain management (GSCM) using both assess the ISM and AHP methods . From a thorough literature review and discussions with industry experts, 47 frequent hurdles were identified, and both studies were carried out using a questionnaire-based survey and work study group . this work utilizing a model used by well-known researchers in the field into foreign countries, An ISM-based model was constructed to investigate the interactions between the factors, The driver’s power-dependence matrix reveals the relative importance of each aspect as well as their interdependence, The ISM-based model provides a clear picture of the relationship between the variables, [22], The recommended solution, however, The AHP method was used to assign these barriers a rank (priorities) based on industrial experts judgments, which were then converted into a Pair-wise comparison matrix for barrier category, by dividing this matrix on the sum of each colomne we get a standardization matrix for barrier category, and finally a weight wich is the medium of the sum of each line, which gave us the barriers priorities ,This method is more accurate and give a clear idea on the impact of the main barriers and then we can focus on the solution , this method is used for almost all the issues that face the industrial world,

Our perspective for the the future is the application of AHP process on the moroccan industries with various activities in order to understand what block ou moroccan companies to apply the green supply chain management in their activities .

Acknowledgment

The authors thank the reviewers for their helpful comments to earlier drafts of this paper.

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