Appraisement of Green Suppliers by Fuzzy and Non-Fuzzy Based Holistic Approach to Sustain Industries: Case Empirical Research

Background: Green supply chain management has become a key strategy for manufacturing firms that want to stay competitive while reducing their environmental footprint. Objectives: This study proposes a decision support system for evaluating and selecting green suppliers in automobile parts, cement, and electronics production. The framework has two hierarchical multi-level modules. Module I uses triangular fuzzy sets for qualitative supplier data, which is subjective. Module II combines qualitative assessments with quantitative production cost and lead time statistics. Methods: Both modules are analysed using recursive multi-level aggregation and the Center of Area defuzzification rule. Results: In Case I, two-level qualitative hierarchy, supplier S3 ranks highest (3.09), followed by S2 (2.95) and S1 (2.70). In Case II, with a three-level mixed-data hierarchy, S3 again ranks first (4.427), but S1 (4.308) and S2 (4.306) differ by only 0.002, so the two suppliers are virtually tied. Conclusions: Both scenarios show that entirely qualitative and mixed qualitative–quantitative supplier data can be processed through a multi-level hierarchy in one visible mathematical framework. Two related procurement settings, three suppliers, and five experts provide limited empirical evidence, therefore claims of applicability to cement, electronics, or other sectors must be substantiated by multi-sector validation and robustness testing.