4.6 Article

Identifying Critical Indicators in Performance Evaluation of Green Supply Chains Using Hybrid Multiple-Criteria Decision-Making

期刊

SUSTAINABILITY
卷 15, 期 7, 页码 -

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MDPI
DOI: 10.3390/su15076095

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green supply chain; performance evaluation; critical indicators; fuzzy DEMATEL-based ANP; MCDM

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This study identifies critical indicators in the performance evaluation of green supply chains (GSC) and provides suggestions for improvement. The research framework was determined using the Delphi method and the fuzzy DEMATEL-based ANP model. The critical indicators include the return rate of net assets, the growth rate of profit, the rate of service satisfaction, market share, production flexibility, and the green consensus.
Performance evaluation of green supply chains (GSC) is an important tool to improve their comprehensive management. Identifying critical indicators is crucial to evaluation. This study examines the critical indicators in performance evaluations of GPC and provides relevant suggestions for managers to improve GSCs' performances. Firstly, we summarized 24 evaluation indicators from five dimensions-financial value, customer service-level, business processes, innovation and development, and the so-called green level. Secondly, the Delphi method was used to determine the formal research framework. The fuzzy decision-making trial and evaluation laboratory based analytic network process (fuzzy DEMATEL-based ANP) model was applied. The weighted prominence of each indicator was calculated to identify those that were critical, and a causality diagram was constructed for them. Finally, corresponding countermeasures and implications regarding those were put forward. The research results show that the critical indicators include the return rate of net assets, the growth rate of profit, the rate of service satisfaction, market share, production flexibility, and the green consensus. Among them, the green consensus, the growth rate of profit and the rate of service satisfaction form a virtuous circle, leading to the improvement of the overall performance of GSC.

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