Green supply chain management with linguistic preferences and incomplete information

As firms move toward environmental sustainability, management must extend managements efforts to improve environmental practices across the supply chain. The selection of a suitable green supplier according to green supply chain management criteria (GSCM) is essential for the sustainable development of manufacturing firms. The objective of this study was to select an optimal alternative in the presence of incomplete information and linguistic preferences using multiple GSCM criteria. The goal of GSCM is to reduce a firm's pollution and other environmental impacts. In the proposed method, the weights of GSCM criteria and alternatives are described using linguistic preferences that can be resolved with fuzzy set theory. Subsequently, the rank of each alternative was calculated from incomplete information by applying a grey degree. Moreover, a case study was used to resolve the proposed method, and the results and managerial implications of the analysis are discussed in detail.

► The objective of this study was to select an optimal alternative in the presence of incomplete information and linguistic preferences using multiple GSCM criteria.
► The weights of GSCM criteria and alternatives are described using linguistic preferences that can be resolved with fuzzy set theory.
► The rank of each alternative was calculated from incomplete information by applying a grey possible degree.
► This study resulted a hierarchical model presented and provides a structured and logical method of synthesizing judgments that can be used for the evaluation of appropriate suppliers.