Low-Carbon Supplier Selection Using a Scenario-Based Integrated FCM-EDAS Approach: A Textile Company Case Study

Abstract In recent years, growing environmental concerns regarding carbon emissions have sparked increased interest in low-carbon supply chains. This necessitates a comprehensive examination of carbon emissions at every stage of the supply chain, with the potential for companies to diminish their carbon footprint by opting for low-carbon suppliers. Among the industries contributing significantly to environmental pollution, the textile industry stands out, presenting an opportunity for improvement through the selection of suppliers prioritizing eco-friendly materials and production methods. This study introduces a novel scenario-based integrated approach that utilizes the Fuzzy Cognitive Map (FCM) and Evaluation based on Distance from Average Solution (EDAS) methods for the selection of low-carbon suppliers. The FCM is employed to model both positive and negative relationships among identified low-carbon supplier selection criteria. Meanwhile, EDAS assesses potential suppliers based on these selected criteria. To underscore the reliability and applicability of the proposed approach, a case study is conducted within a textile company. Moreover, a scenario analysis is introduced to reveal how the choice of selection criteria impacts decisions regarding low-carbon suppliers across different circumstances. This study stands out for introducing a novel approach, combining FCM-EDAS, in the selection of low-carbon suppliers.