Applying a Hybrid MCDM Model to Evaluate Green Supply Chain Management Practices

Jung-Fa Tsai, Shih-Ping Shen and Ming-Hua Lin ()
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Jung-Fa Tsai: Department of Business Management, National Taipei University of Technology, Taipei 106344, Taiwan
Shih-Ping Shen: Department of Business Management, National Taipei University of Technology, Taipei 106344, Taiwan
Ming-Hua Lin: Department of Urban Industrial Management and Marketing, University of Taipei, Taipei 111036, Taiwan

Sustainability, 2023, vol. 15, issue 3, 1-18

Abstract: The COVID-19 pandemic has prompted global supply chain managers to reassess their operations. Developing a green supply chain requires successfully integrating environmental responsibility principles and benchmarks into supply chain management practices. In the past, there have been few studies on the most effective strategies for reducing the environmental impact of supply chains and improving their sustainability. This study used the decision-making trial and evaluation laboratory (DEMATEL) method to construct a structural model evaluation system of the green supply chain management (GSCM) to evaluate the interdependent relationships among dimensions and criteria. A GSCM evaluation system was created after using the DEMATEL-based ANP (DANP) to convert the GSCM evaluation indicators and impact factors into degrees of importance. This study explores the obstacles and challenges that organizations face when implementing GSCM practices and how these challenges can be overcome. The results found that organizational changes had the most significant impact, given that they would also improve the other three dimensions. Among the 16 evaluation criteria, resource allocation and market expansion optimization were the most important. Based on these findings, the study proposed specific improvement strategies that corporations and other stakeholders could use to adopt GSCM practices.

Keywords: green supply chain management; DEMATEL; MCDM; DANP (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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