An approach to evaluating sustainable supply chain risk management based on BWM and linguistic value soft set theory

Abstract

Companies are attaching more and more importance to sustainable supply chain management (SSCM) as which makes the right strategy measures for companies. Due to the complexity of external environmental factors and internal structure, sustainable supply chain management is vulnerable to various risks. The purpose of this paper is to present a new two-stage approach for determining the best practitioner in Iran Pars Special Economic Energy Zone based on the sustainable supply chain risk management (SSCRM). The best and worst method (BWM) is used to determine the weight of risk factors. Then the method of linguistic value soft set is used to assess the impact of risk factors on each company’s sustainable supply chain which is a multiple attribute decision making problem with language preference in the second stage. Consequently, the ranking results of sustainable supply chain of each enterprise are obtained. This study contributes to finding the key risk factors of SSCRM. Evaluating these companies SSCRM with preference information, the best practitioner can obtain. The combination of BWM and linguistic value soft set approach provides a new nonparametric theoretical method and tool for this kind of decision-making problems with this background. At the same time, the conclusions of this study have guiding significance for the implementation of industrial supply chain. Limitations of the study along with future research directions are also presented.