Sustainable supplier selection in the textile and apparel industry: an integrated fuzzy multi-criteria approach

Sustainable supplier selection in the textile and apparel industry is hindered by generic criteria and the difficulty of balancing expert cognitive efficiency with ranking robustness. This study develops a textile-specific indicator system with 23 indicators, screened from 42 candidates via the Content Validity Ratio (CVR) by 13 industry experts, and proposes an integrated fuzzy MCDM framework combining Fuzzy Best-Worst Method (Fuzzy-BWM) and Triangular Fuzzy Number-MULTIMOORA (TFN-MULTIMOORA). In a case study of a Chinese apparel trading enterprise and six core suppliers, the economic dimension received the highest weight (0.453), followed by the social (0.279) and environmental (0.267) dimensions, while product quality (0.068) and strategic decision-making and execution ability (0.058) were the most influential sub-indicators. Supplier S3 ranked first across the Ratio System, Reference Point and Full Multiplicative Form. Cross-method validation with four alternative fuzzy MCDM methods yielded a mean Spearman rank correlation of 0.903, and sensitivity analysis under 16 weight variation scenarios produced a mean Spearman correlation of 0.966. These results indicate that the proposed framework provides a textile-specific, cognitively efficient and robust alternative to existing sustainable supplier selection approaches.