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

BackgroundThe implementation of risk management for occupational health and safety is a fundamental requirement in all sectors. The occupational hazards and associated health consequences experienced by drivers in the public transport sector necessitate the implementation of proactive measures.ObjectiveThe objective of this paper is to propose a novel hybrid risk assessment model, based on spherical fuzzy sets, for the prioritization of prevalent occupational hazards among public transport drivers.MethodsThis study proposes the implementation of an integrated Fine-Kinney-based fuzzy occupational risk assessment model. This model incorporates the Alternative Ranking Technique based on Adaptive Standardized Intervals (ARTASI) approach and the Logarithmic Decomposition of Criteria Importance (LODECI) method. These are employed within the context of a spherical fuzzy environment. The integration of spherical fuzzy sets and the spherical fuzzy-Yager weighted arithmetic mean aggregation operator signifies a substantial advancement in the domain of occupational risk assessment. The amalgamation of these methodologies, in combination with the utilization of spherical fuzzy sets, culminates in the formulation of the proposed SFLOAR-Fine-Kinney hybrid model.ResultsThe results obtained from the proposed model indicates that the potential occupational hazard PTH12 (Work stress) is the most significant hazard, with the highest utility function value of 97.69061, and PTH15 (Income/salary policies) is the least serious hazard, with the lowest utility function value of 76.40069.ConclusionsThe present study offers theoretical and managerial implications for researchers, professionals and policymakers working in the public transport sector by harmoniously integrating quantitative and qualitative perspectives and employing robust assessment techniques.