This study presents a hybrid fuzzy Multi-Attribute Group Decision Making (MAGDM) model with application to commercial insurance selection. The proposed hybrid model uses Spherical Fuzzy (SF) sets using Yager t-norm and t-conorm operations. The Logarithmic Decomposition of Criteria Importance (LODECI) method is used for criterion weighting due to its efficacy in stabilizing scenarios that may challenge other weighting techniques. For alternative ranking, the study employs the Alternative Ranking Technique based on Adaptive Standardized Intervals (ARTASI), offering enhanced flexibility in handling uncertainties inherent in expert evaluations. The combination of these methods and the utilization of SF sets gives rise to the proposed SF-LODECI-ARTASI hybrid model. The paper systematically delineates the procedural steps involving SF sets, Yager t-norm and t-conorm operations, SF-LODECI, and SF-ARTASI methods. Subsequently, the developed hybrid model is applied to a case study of commercial insurance selection, supported by a numerical example. The research application results emphasize the consistency of these findings with other alternative methods. Additionally, sensitivity scenarios are constructed to scrutinize the robustness of the proposed hybrid model. The study concludes by elucidating implications and contributions to the existing literature. •Propose a hybrid model using Spherical Fuzzy (SF) sets, Logarithmic Decomposition of Criteria Importance (LODECI), and Alternative Ranking Technique based on Adaptive Standardized Intervals (ARTASI).•Use LODECI for criteria weighting due to its effectiveness in stabilizing unstable situations.•Use ARTASI for alternative ranking due to its effectiveness in expanding uncertainty levels in expert evaluations.•Observe consistency between the obtained results and those from other research in the field, validating robustness.•Conduct sensitivity analysis to test the robustness of the proposed hybrid model.