An Extended Spherical Fuzzy TAOV Model for Multi-Criteria Group Decisions under Heterogeneity and Correlated Criteria

Abstract This paper develops an extended spherical fuzzy multi-criteria group decision-making (MCGDM) framework that integrates hybrid weighting with the total area method based on orthogonal vectors (TAOV). The main motivation is to address key limitations in existing MCGDM approaches by simultaneously accounting for decision-maker heterogeneity and criteria correlation, aspects that are typically overlooked in prior studies. To this end, the proposed model combines subjective and objective weights through a game-theoretic formulation, enabling a balanced representation of expert judgment and data-driven information. Furthermore, orthogonality among criteria is ensured via principal component analysis (PCA), thereby mitigating redundancy and enhancing interpretability within a unified mathematical structure. By integrating spherical fuzzy modeling with hybrid weighting and orthogonalization, the framework improves both the accuracy and robustness of group decision processes. The effectiveness and robustness of the proposed framework are illustrated through a real-world case study on capital-raising strategies, demonstrating its advantages over conventional spherical fuzzy MCGDM models.