SFLOAR technique: A novel fuzzy occupational risk assessment approach to prioritize hazard in public transport.

This article focuses on the development and application of a novel hybrid occupational health and safety (OHS) risk assessment model, termed SFLOAR-Fine-Kinney, designed to prioritize prevalent occupational hazards among public transport drivers. The model integrates spherical fuzzy sets (SFSs), the Fine-Kinney method, the Alternative Ranking Technique based on Adaptive Standardized Intervals (ARTASI), and the Logarithmic Decomposition of Criteria Importance (LODECI) to address uncertainty and expert judgment ambiguity in risk evaluation. Applied to eighteen identified hazards, the model ranks work stress as the most significant risk and income/salary policies as the least, with exposure identified as the most critical risk parameter. Sensitivity and comparative analyses demonstrate the model's robustness and consistency with existing multi-criteria decision-making methods. The study offers theoretical and managerial insights for policymakers, occupational health professionals, and public transport managers aiming to improve risk management and working conditions in the public transportation sector.