An integrated interval-valued spherical fuzzy Choquet integral based decision making model for prioritizing risk in Fine-Kinney

Abstract

The Fine-Kinney model has been expanded to serve as a tool for analyzing systemic risk in different industries, including occupational hazards. However, existing models for prioritizing risk in Fine-Kinney fail to account for the interconnectedness of experts’ cognitive information in interval-valued spherical fuzzy situations. This paper creates a new fuzzy compromise ranking of alternatives from distance to ideal solution (CRADIS) method to address the limitations of the Fine-Kinney model in occupational risk analysis. The interval-valued spherical fuzzy numbers are extended into the conventional risk scales in the Fine-Kinney model to generate a processing method for uncertain risk rating data. Then, the weighted averaging operator is developed based on the Choquet integral and interval-valued spherical fuzzy sets to construct the collective risk assessment matrix. This developed operator can capture inter-dependencies among risk data. Next, an enhanced CRADIS method with interval-valued spherical fuzzy sets and entropy measures is presented to address the risk ranking issue in the application of Fine-Kinney. To demonstrate the implementation of the synthesized occupational risk framework, a case study analyzing the occupational hazards in the metro construction process uses numerical methods. The proposed framework undergoes parameter sensitivity analysis to test its rationality. An evaluation compares the enhanced framework with the risk-prioritizing methods used in F–K to assess its advantages. The outcome suggests that the framework offers an appropriate and dependable approach to prioritizing occupational risks in a subjective and ambiguous scenario.