Interpretive structural modeling-analytic network process integrated framework for evaluating sustainable supply chain management alternatives

Abstract

Selection of appropriate practices (alternatives) is critical for making the best use of resources, time, and money to facilitate sustainable supply chain management. In this study, we propose an integrated framework based on interpretive structural modeling (ISM) and analytic network process to evaluate potential alternatives for sustainable supply chain management. The criteria used for evaluation are various enablers of sustainability, which are developed along economic, environmental, and social dimensions. ISM is employed to model the relationship among the various enablers. Sensitivity analysis is performed to determine the influences of dimensions, criteria, and alternatives scores on the stability of the ranking results. The results of our study demonstrate that governmental regulations, rewards and incentives, and listening to the views of the customers are the main enablers that can achieve sustainability in supply chains. From the perspective of alternatives, carbon taxing, management training for corporate sustainability, employee training programs on sustainability, and incentives for collaboration in sustainability have the top scores.