A Fuzzy TOPSIS and Interval Type-2 Fuzzy TOPSIS Based Approach for Sustainable Smart Supplier Selection

Abstract

Increasing global competition and sustainability pressures have shifted supply chain management beyond a cost- and quality-oriented perspective. Today, firms are required to develop more holistic decision-making processes by incorporating environmental, social, and technological parameters. This study proposes an innovative supplier evaluation model that integrates sustainability principles with digital transformation dynamics. The model is structured around four main criterion groups: economic, environmental, technological, and operational. The criteria were determined through an extensive literature review and expert opinions from different sectors. In the analysis phase, two Multi-Criteria Decision-Making (MCDM) methods fuzzy TOPSIS and interval type-2 fuzzy TOPSIS were employed. The findings indicate that both methods identified the same supplier as the most suitable alternative. However, the interval type-2 fuzzy TOPSIS method provided a clearer differentiation among the alternatives, offering decision-makers a more reliable ranking under uncertainty. This demonstrates that type-2 fuzzy sets are more effective in environments characterized by high levels of uncertainty. As one of the few studies to apply both methods together, this research contributes to literature with a novel and comprehensive approach. Furthermore, the proposed model has the potential to guide decision-makers strategically, with applicability across diverse sectors and contexts.Increasing global competition and sustainability pressures have shifted supply chain management beyond a cost- and quality-oriented perspective. Today, firms are required to develop more holistic decision-making processes by incorporating environmental, social, and technological parameters. This study proposes an innovative supplier evaluation model that integrates sustainability principles with digital transformation dynamics. The model is structured around four main criterion groups: economic, environmental, technological, and operational. The criteria were determined through an extensive literature review and expert opinions from different sectors. In the analysis phase, two Multi-Criteria Decision-Making (MCDM) methods fuzzy TOPSIS and interval type-2 fuzzy TOPSIS were employed. The findings indicate that both methods identified the same supplier as the most suitable alternative. However, the interval type-2 fuzzy TOPSIS method provided a clearer differentiation among the alternatives, offering decision-makers a more reliable ranking under uncertainty. This demonstrates that type-2 fuzzy sets are more effective in environments characterized by high levels of uncertainty. As one of the few studies to apply both methods together, this research contributes to literature with a novel and comprehensive approach. Furthermore, the proposed model has the potential to guide decision-makers strategically, with applicability across diverse sectors and contexts.