Strategic Supplier Selection with T-SF MEREC-AROMAN and T-SF MEREC-CoCoSo

Abstract

The chemical industry is a cornerstone of Turkey's industrial economy, supplying essential materials to a wide range of sectors, including pharmaceuticals, agriculture, and manufacturing. In such a dynamic and competitive environment, selecting the right suppliers is a strategic decision that can easily affect the cost and efficiency of operations and sustainability. Supplier evaluation is a complicated process that involves multiple, potentially conflicting criteria and uncertain expert judgments. Thus, in this study, two novel hybrid multi-criteria decision-making (MCDM) methods, T-spherical fuzzy MEREC (Method based on the Removal Effects of Criteria)-AROMAN (Alternative Ranking Order Method with Attainment of Normalization) (T-SF MEREC-AROMAN) and T-SF MEREC-CoCoSo (Combined Compromise Solution) are presented to aid in the decision-making process. The use of T-spherical fuzzy sets (T-SFS) in MEREC, AROMAN, and CoCoSo enhances the model's ability to capture hesitation and ambiguity in expert evaluations, offering a more realistic representation of real-world decision-making. A case study conducted in a chemical company in Turkey is presented to demonstrate the practical application of the proposed approach. For comparison, a well-known method, T-SF MEREC-TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) is utilized, which resulted in the same ranking as T-SF MEREC-AROMAN and T-SF MEREC-CoCoSo. A sensitivity analysis is performed, revealing that T-SF MEREC-AROMAN and T-SF MEREC-CoCoSo methods maintain strong robustness, constantly delivering the same ranking, against variations up to ±100%, in criterion weights, and some key parameter changes.