Publication | Open Access
Multi-criteria decision support framework for sustainable implementation of effective green supply chain management practices
43
Citations
75
References
2016
Year
EngineeringIndustrial EngineeringGreen ManufacturingSustainable Supply Chain ManagementMultiple-criteria Decision AnalysisFuzzy Risk AnalysisEnvironmental PolicySustainable DesignFuzzy Multi-criteria Decision-makingManagementMulti-criteria Decision MakingLogisticsSupply ChainSystems EngineeringSustainable SourcingFuzzy OptimizationMulticriteria EvaluationGreen Decision-makingGreen Supply ChainFuzzy LogicSustainable ImplementationSupply Chain ManagementWeighted CriteriaEnvironmental EngineeringBusinessEnvironmental IssuesSustainabilitySustainable Supply ChainsSustainable ProductionFuzzy Topsis
At present, environmental issues become real critical barriers for many supply chain corporations concerning the sustainability of their businesses. In this context, several studies have been proposed from both academia and industry trying to develop new measurements related to green supply chain management (GSCM) practices to overcome these barriers, which will help create new environmental strategies, implementing those practices in their manufacturing processes. The objective of this study is to present the technical and analytical contribution that multi-criteria decision making analysis (MCDA) can bring to environmental decision making problems, and especially to GSCM field. For this reason, a multi-criteria decision-making methodology, combining fuzzy analytical hierarchy process and fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS), is proposed to contribute to a better understanding of new sustainable strategies through the identification and evaluation of the most appropriate GSCM practices to be adopted by industrial organizations. The fuzzy AHP process is used to construct hierarchies of the influential criteria, and then identify the importance weights of the selected criteria, while the fuzzy TOPSIS process employs these weighted criteria as inputs to evaluate and measure the performance of each alternative. To illustrate the effectiveness and performance of our MCDA approach, we have applied it to a chemical industry corporation located in Safi, Morocco.
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