Scrutinizing the applicability of blockchain in the sustainability of supply chains using an intelligent fuzzy multi criteria decision making.

Blockchain technology is a decentralized method of securely storing information in blocks. Over the past few decades, sustainability has gained importance and been shown to be a crucial component in building robust supply chains. Manufacturers and suppliers are pressured to become more globally sustainable by customers who want their products verified for sustainability. Furthermore, problems with social sustainability are becoming more complex. Multi-criteria decision-making (MCDM) is the best tool for addressing this issue. In this article, we aimed to propose a combined compromise solution (CoCoSo) method for ranking blockchain platform selection using spherical fuzzy set (SFS) information. SFS is a well-known framework that provides greater freedom to decision-makers and better reliability than intuitionistic fuzzy sets, Pythagorean fuzzy sets, q-rung ortho-pair fuzzy sets, and picture fuzzy set-based frameworks. The CoCoSo approach under the SFS framework is a renowned tool for complicated decision-making problems. In this method, we consider both linear and non-linear correlations among criteria; the technique aims to give decision-makers a more comprehensive assessment of the alternatives. In the MCDM field, the idea of a power aggregation operator (PAO) is a valuable tool for investigating the weightage of alternatives. We also introduce Sugeno Weber tnorm (TN) and tconorm (TCN) operations under the SFS framework. MCDM Sciences utilizes The Sugeno-Weber operations because it provides a solution for managing ambiguous yet unclear information. The approach enables users to mix diverse inputs through a versatile mechanism that proves valuable for selecting from multiple factors. The cartel theme of this article is to construct a new family of aggregation operators (AOs) called spherical fuzzy (SF) Sugeno Weber power weighted averaging (SFSWPWA) and SF Sugeno Weber power weighted geometric (SFSWPWG) operators, including investigation of some fundamental axioms of AOs. The MCDM algorithm for the CoCoSo method will also be constructed, and the SFSWPWA and SFSWPWG operators will be established. We solve a real-life numerical problem for selecting the best blockchain platform using diagnosed approaches. In the numerical example, we rank blockchain platforms like Hyperledger Fabric, Ethereum, IBM Food Trust, and VeChain. Applying the proposed CoCoSo method, SFSWPWA and SFSWPWG operators "Ethereum" are the best options. The proposed methodologies also apply in real-life Sanrio's where decision-making is involved. To check the applicability of the developed technique, we made a comparison with existing approaches such as interval-valued intuitionistic fuzzy Heronian mean AOs, Pythagorean fuzzy Hamy mean AO, complex q-rung ortho-pair fuzzy Aczel Alsina AOs, and q-rung ortho-pair fuzzy Sugeno-Weber AOs. These discussed AOs are unable to handle SFS-based information. So, we concluded that the suggested framework is more reliable and superior to other discussed environments due to the presence of abstinence grade. Robust conclusions are given in the end.