An integrated model for occupational health and safety risk assessment based on probabilistic linguistic information and social network consensus analysis

Abstract

As a critical activity in occupational risk management, the occupational health and safety risk assessment (OHSRA) aims at assessing occupational hazards in the workplace and prioritizing them to ensure employees’ safety and reduce occupational risk to an acceptable level. In this paper, we develop a new integrated OHSRA model for the risk evaluation and prioritization of occupational hazards based on probabilistic linguistic information and social network consensus analysis. The probabilistic linguistic term sets are applied to handle the hesitant risk evaluations of occupational hazards provided by experts. A combinative distance-based assessment technique is introduced for determining the risk priority of the identified occupational hazards. Additionally, the social network consensus analysis with minimum adjustment distance is used to help individual experts reach consensus. Finally, a healthcare case study is implemented for illustrating the developed OHSRA model and its effectiveness is validated with a sensitivity analysis and a comparative analysis.

Keywords:

• Occupational health and safety
• risk assessment
• expert consensus
• probabilistic linguistic term set
• combinative distance-based assessment

Acknowledgements

The authors are very grateful to the respected editor and reviewers for their insightful and constructive comments and suggestions, which are very helpful in improving the quality of the paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was supported by the major project of National Social Science Fund of China (No. 21ZDA024) and the Fundamental Research Funds for the Central Universities (No. 22120230184).