Abstract
The green supply chain management (GSCM) is an enterprise’s effort to protect the environment and a key way to achieve sustainable environmental development. On the contrary, globalization brings more risks to the supply chain. Resilience has become a critical definition in supply chain management to help enterprises review the disruption and return to normal state. Therefore, choosing a resilient-green supplier to build a supply chain environment with flexibility and greenness under interruption becomes necessary for research works. However, the existing studies tended to focus on only one of the factors with resilience and greenness, and no comprehensive criteria system and performance value is expressed by a crisp number. Therefore, this paper proposes a hybrid method which integrates the Best-Worst method (BWM), Weighted Aggregated Sum-Product Assessment (WASPAS), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to solve the critical problems. Firstly, BWM is used to weigh the criteria; secondly, intuitionistic fuzzy numbers are introduced into the ranking stage. Then, the integrated WASPAS and TOPSIS are used to rank the alternatives to select the optimal resilient-green supplier. Finally, an illustrative example proves the feasibility of this method.
Highlights
With the environment adverse changes, green supply chain management (GSCM) emerged as the times when enterprises and products needed to adapt to the characteristic of resource-efficient and environment-friendly
In order to prove the feasibility and practicability of the method proposed in this paper, we compare the alternative ranking obtained in the above illustrative example with the results of the classical multicriteria group decision-making (MCGDM) methods. rough literature review, we find that analytic hierarchy process (AHP) is one of the earliest methods to deal with MCGDM problems [108]
A supplier selection model integrating Weighted Aggregated SumProduct Assessment (WASPAS) and TOPSIS method based on intuitionistic fuzzy sets is provided
Summary
With the environment adverse changes, green supply chain management (GSCM) emerged as the times when enterprises and products needed to adapt to the characteristic of resource-efficient and environment-friendly. Us, a decision-making method was proposed for selecting suppliers that can take both environmental problems and disruption risks for further research studies into account. According to the green manufacturing process and resilience-related characteristics, the resiliencegreenness criteria system was constructed; secondly, the language terms used in many MCGDM problems were not in line with the expression habits of decision makers and reduced the accuracy of decision-making process; thirdly, the traditional weighting methods (such as AHP) of MCGDM had more steps to compare, so the calculation process was more complicated; lastly, the single MCGDM method made the alternatives’ ranking inaccurate and inconsistent. Erefore, in order to fill the research gap, a novel method, which integrated WASPAS, BWM, and TOPSIS based on intuitionistic fuzzy numbers, was proposed to select the resilient-green supplier under the supply chain environment.
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