Sustainable recycling partner selection using fuzzy DEMATEL-AEW-FVIKOR: a case study in small-and-medium enterprises (SMEs)

Zhou, F., Wang, X., Lim, M.K. , He, Y. and Li, L. (2018) Sustainable recycling partner selection using fuzzy DEMATEL-AEW-FVIKOR: a case study in small-and-medium enterprises (SMEs). Journal of Cleaner Production, 196, pp. 489-504. (doi: 10.1016/j.jclepro.2018.05.247)

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Abstract

The requirement and policy of eco-economy motivate enterprises to achieve sustainability by implementing sustainable supply chain management (SSCM). In contrast to the large amount of literature focusing on green design and green production practices, this paper pays close attention to the sustainable management practice at the bottom of the supply chain by researching sustainable recycling partner evaluation from the economic, environmental and social perspectives. To develop a feasible analytical framework for recycling partner selection, the fuzzy-based technology is applied to cope with the vague, uncertain and qualitative information. A novel integrated MCDM “fuzzy DEMATEL-AEW-FVIKOR” approach is developed to choose a best recycling partner for small-and-medium enterprises (SMEs). The combined weighting technique integrating subjective weight based on fuzzy decision-making trial and evaluation laboratory (DEMATEDL) method with objective weight based on anti-entropy weighting (AEW) has been coupled with the fuzzy VlseKriterijuska Optimizacija I Komoromisno Resenje (FVIKOR) operations to choose the best candidate. To investigate the effectiveness and practicability of the proposed method, a case application has been conducted in a SME. Meanwhile, the sensitivity analysis of the method is also detected. The results argue that the best selected partner alternative keeps a high conformance with Shemshadi's and Chaghooshi's methods, and it demonstrates a strong robustness when v and φ parameters fluctuate. Besides, the proposed hybrid fuzzy DEMATEL-AEW-FVIKOR method shows its advantage in flexibility concerning the decision makers' preference.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Lim, Professor Ming
Authors: Zhou, F., Wang, X., Lim, M.K., He, Y., and Li, L.
College/School:College of Social Sciences > Adam Smith Business School > Management
Journal Name:Journal of Cleaner Production
Publisher:Elsevier
ISSN:0959-6526
Published Online:14 June 2018

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