A Fuzzy TOPSIS and Interval Type-2 Fuzzy TOPSIS Based Approach for Sustainable Smart Supplier Selection
Küçük Resim Yok
Tarih
2025
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Abdulkadir KESKİN
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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.
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.
Açıklama
Anahtar Kelimeler
Multiple Criteria Decision Making, Çok Ölçütlü Karar Verme
Kaynak
Journal of Statistics and Applied Sciences
İstatistik ve Uygulamalı Bilimler Dergisi
İstatistik ve Uygulamalı Bilimler Dergisi
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
12
