| Title |
A Dynamic Decision Support System for Sustainable Supplier Selection in Circular Economy |
| ID_Doc |
20131 |
| Authors |
Alavi, B; Tavana, M; Mina, H |
| Title |
A Dynamic Decision Support System for Sustainable Supplier Selection in Circular Economy |
| Year |
2021 |
| Published |
|
| 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. (C) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. |
| Author Keywords |
Sustainable circular supplier selection; decision support system; best-worst method; fuzzy inference system; machine learning |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000674195700004 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
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