| Title |
An integrated information fusion and grey multi-criteria decision-making framework for sustainable supplier selection |
| ID_Doc |
76406 |
| Authors |
Aslani, B; Rabiee, M; Tavana, M |
| Title |
An integrated information fusion and grey multi-criteria decision-making framework for sustainable supplier selection |
| Year |
2021 |
| Published |
International Journal Of Systems Science-Operations & Logistics, 8, 4 |
| DOI |
10.1080/23302674.2020.1776414 |
| Abstract |
The recent changes in global business markets have forced supply chains to include sustainability and considerable uncertainty in their decision-making processes. In this study, we propose an integrated information fusion and grey multi-criteria decision-making (MCDM) framework for solving sustainable supplier selection problems with imprecise information. We identify a series of criteria in the literature based on the economic, social, and environmental aspects of sustainability and obtain the relative importance of these criteria from experts' opinions. We then propose a best-worst method (BWM) integrated with grey theory to calculate the weights of criteria. These weights are used to evaluate a set of suppliers based on three sustainability aspects. A hybrid method composed of weighted aggregated sum product assessment (WASPAS), the technique for order of preference by similarity to ideal solution (TOPSIS), and grey theory are proposed for ranking the suppliers. We aggregate the grey MCDM results with the concept of information fusion to find an integrated score for each supplier. The final ranking is obtained by incorporating expert opinions with the integrated scores. We also present a case study to demonstrate the applicability of the proposed framework. A sensitivity analysis is performed to test the reliability and robustness of the results. |
| Author Keywords |
Sustainable supplier selection; grey theory; best-worst method; weighted aggregated sum product assessment (WASPAS); TOPSIS; information fusion |
| 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:000725292900001 |
| WoS Category |
Engineering, Industrial; Operations Research & Management Science |
| Research Area |
Engineering; Operations Research & Management Science |
| PDF |
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