Analysis of internal factors of green supply chain management: An interpretive structural modeling approach

Chakraborty, Arka; Amin, Md. Al

doi:10.1016/j.clscn.2023.100099

Cited by 11 publications

(7 citation statements)

References 48 publications

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“…This study used a focused group discussion technique to gather data. ISM recommends using a sample size of 10–30 survey participants to achieve reliable results [ 55 , 74 ]. Our study involved five academics and ten e-commerce businesspeople in performing the ISM analysis.…”

Section: Numerical Illustrationsmentioning

confidence: 99%

Enhancing resilience in transnational E-commerce supply chains: Critical factors, perspectives and strategic action plan

Nabil,

Al Amin,

Baldacci

2024

Heliyon

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Section: Numerical Illustrationsmentioning

confidence: 99%

Enhancing resilience in transnational E-commerce supply chains: Critical factors, perspectives and strategic action plan

Nabil,

Al Amin,

Baldacci

2024

Heliyon

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“…The findings also establish that internal factors have no impact on environmental performance through green supply chain management. Chakraborty et al (19) examined the internal factors related to the green supply chain using a structural interpretive modeling approach. In this study, eight factors have been identified that can be controlled within the organization.…”

Section: Literature Reviewmentioning

confidence: 99%

Development of Green Product Processes in Textile Industry Using Mathematical Modeling and NSGA-II Metaheuristic Algorithm: A Case Study in Oyaz Industrial Group Document Type : Original Article

Bahrami Kian,

Harsej,

Molani Aghdam

et al. 2024

IJE

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The development of green product processes is a strategic approach to minimize the impact of organizational supply chain on the environment while simultaneously expanding its economic performance. To achieve this task, it is crucial to emphasize aspects related to performance in optimizing resource utilization and implementing sustainability principles within an organizational domain. To this end, a multi-objective mixed-integer linear programming model is presented in this study with the objective of minimizing the production time of textiles, transportation costs, and inventory of the products, as well as minimizing the environmental effects of the processes of developing green products. In this model, the constraints and problem parameters are deterministic and solved using weighted sum methods, utilizing real data obtained from the "Oyaz" industrial group. By solving the model, an optimal combination for the values of the objective functions is obtained both collectively and separately. Furthermore, the capability of the proposed model is evaluated for solving large-scale instances using the NSGA-II algorithm. This metaheuristic method has demonstrated satisfactory capabilities compared to the mathematical model because of the slight difference in modeling errors while confirming the accuracy of the developed mathematical model, proving the accuracy and efficiency of the NSGA-II algorithm. Consequently, the sensitivity analysis examines the influence of changing key parameters, such as the maximum storage capacity of production centers, on the decisions of the proposed model. This parameter change is determined through consultation with experts in the textile field. Based on the results obtained, changing the maximum storage capacity has a considerable impact on fibers and cotton. Additionally, if the capacity is changed to the maximum possible value, it has the greatest impact on the purifiers.

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“…The authors utilized interpretative structural modeling (ISM) to incorporate industry experience into the evaluation process. Eight internally manageable factors were identified, with top management commitment being the most influential [32]. According to [33], to optimize the entire performance of a supply chain via green practices, the performance factors should be studied, and their interactions should be recognized and understood.…”

Section: Literature Reviewmentioning

confidence: 99%

Identification and Prioritization of Green Lean Supply Chain Management Factors Using Fuzzy DEMATEL

2023

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Green–lean supply chain management (GLSCM) refers to strategically adopting and coordinating environmentally sustainable practices and lean concepts in supply chain operations. A considerable set of factors needs to be identified to implement GLSCM successfully. This study examined the factors influencing green lean supply chain management implementation in the Readymade Garments Industries of Bangladesh through a literature review and discussions with field experts. The fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) approach is employed to analyze these factors to implement GLSCM effectively. This research identifies capacity utilization, green purchasing, and demand variation as the most influential factors in GLSCM, while quality improvement and the Kanban system are considered the least important factors. This study explored categorizing factors into the cause-and-effect group, the degree of interaction, and the interrelationship of the factors under consideration. The findings of this study may help managers develop an effective GLSCM system, hence increasing an organization’s total profitability.

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Analysis of internal factors of green supply chain management: An interpretive structural modeling approach

Cited by 11 publications

References 48 publications

Enhancing resilience in transnational E-commerce supply chains: Critical factors, perspectives and strategic action plan

Enhancing resilience in transnational E-commerce supply chains: Critical factors, perspectives and strategic action plan

Development of Green Product Processes in Textile Industry Using Mathematical Modeling and NSGA-II Metaheuristic Algorithm: A Case Study in Oyaz Industrial Group Document Type : Original Article

Identification and Prioritization of Green Lean Supply Chain Management Factors Using Fuzzy DEMATEL

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