Title

A Dynamic Decision Support System for Sustainable Supplier Selection in Circular Economy

Document Type

Article

Publication Date

7-1-2021

DOI

10.1016/j.spc.2021.02.015

Abstract

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier selection engagement. We present a case study at a petrochemical holding company with a controlling interest over several subsidiary companies to demonstrate the applicability of the proposed approach.

Language

English

Comments

Alavi, B., Tavana, M. and Mina, H. (2021) ‘A Dynamic Decision Support System for Sustainable Supplier Selection in Circular Economy,’ Sustainable Production and Consumption, Vol. 27, pp. 905-920.

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