An Extended CRITIC Algorithm Based on Spherical Fuzzy Sets to Determine the Objective Weights of Decision-Makers

Determining decision-maker weight coefficients is a crucial step in multi-criteria group decision-making models. However, much of the existing literature focuses on developing algorithms to select the best alternative based on exact criteria weights, often leading to relatively subjective outcomes. Therefore, this study proposes an algorithm that objectively calculates decision-maker weight coefficients by extending the CRiteria Importance Through Interpreters Correlation (CRITIC) method within Spherical Fuzzy Sets (SFSs). The algorithm modifies the normalization process of the spherical fuzzy number (SFN) elements in the initial decision-maker priority matrix and enhances the SFN aggregation in the normalized priority matrix. By applying a distance measure between SFN elements, the algorithm reduces discrepancies between normalized elements, providing a more objective representation of the relationships in the initial priority matrix and leading to more accurate decision-maker weights. We validate the proposed algorithm through three case studies, demonstrating its feasibility and effectiveness in calculating objective decision-maker weights. In addition, the results indicate that the algorithm can be integrated with other decision-making methods, paving the way for the future development of dynamic decision-support systems.