4.7 Article

Performance evaluation of green suppliers using entropy-TOPSIS-F

期刊

JOURNAL OF CLEANER PRODUCTION
卷 207, 期 -, 页码 498-509

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.09.235

关键词

Green supply chain management; Environmental performance; Supplier selection; Fuzzy TOPSIS; Shannon entropy; Entropy-TOPSIS-F

资金

  1. CNPq (The Brazilian National Council for Scientific and Technological Development)
  2. (Brazilian National Council for Scientific and Technological Development)

向作者/读者索取更多资源

The main objective of this paper is to propose a method for the evaluation and selection of green suppliers for the Brazilian furniture industry. In order to achieve this goal, this study identifies environmental criteria for use in assessing and selecting green suppliers of the furniture industry; then, the study directs readers towards a successful implementation of GSCM practices. The proposed methodology uses a hybrid Entropy-TOPSIS-F framework to weight the criteria and select the supplier with the best environmental performance. The fuzzy approach is integrated with Shannon's Entropy and the TOPSIS method to deal with uncertainty in the decision-making process. To show the applicability and results of the proposed framework, we collected 32 experts' information from the furniture industry about the environmental criteria that are more suitable for evaluation and selection of suppliers in this sector. A real case involving the evaluation, based on the defined criteria, of three potential suppliers by three managers of a furniture industry was discussed. According to the findings, Management Commitment to GSCM, Ecodesign and Environmental management system are the first three criteria in the ranking of selection of sustainable suppliers. In addition, of the three potential suppliers of the case, supplier A(1) presented superior environmental performance. A sensitivity analysis is performed to test the stability of the Entropy-TOPSIS-F approach and to verify the robustness of the proposed framework. (C) 2018 Elsevier Ltd. All rights reserved.

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