Title
An integrated information fusion and grey multi-criteria decision-making framework for sustainable supplier selection
Document Type
Article
Publication Date
10-2-2021
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.
Language
English
Recommended Citation
Aslani, Babak; Rabiee, Meysam; and Tavana, Madjid, "An integrated information fusion and grey multi-criteria decision-making framework for sustainable supplier selection" (2021). Business Systems and Analytics Faculty Work. 40.
https://digitalcommons.lasalle.edu/bsa_faculty/40
Comments
Aslani, B., Rabiee, M. and Tavana, M. (2021) ‘An Integrated Information Fusion and Grey Multi-Criteria Decision-Making Framework for Sustainable Supplier Selection,’ International Journal of Systems Science: Operations and Logistics, Vol. 8, No. 4, 348-370.