Citation

Li X, Liu T, Liu Y. Int. J. Environ. Res. Public Health 2019; 17(1): ePub.

Affiliation

Macro Strategy Research Office, Chinese Academy of Labour and Social Security, Beijing 100029, China.

Copyright

(Copyright © 2019, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/ijerph17010011

PMID

31861332

Abstract

Hazardous chemical accidents (HCAs) seriously endanger public life, property, and health. Human and organizational factors are important causes of many kinds of accidents. In order to systematically explore the influencing factors of unsafe behaviors in HCAs in China, the method of human factors analysis and classification system based on the Bayesian network (BN-HFACs) was introduced. According to the 39 investigation reports of HCAs in China, the origin Bayesian network (BN) was obtained and the failure sensitivity of every node in BN was calculated. The results have shown that hazardous material environment (1.63) and mechanical equipment (0.49) in the level of preconditions of unsafe behavior have the same direction failure effect with operation error, while there is no factor has the same direction failure effect with operation violate. Some factors in organization influence and unsafe supervision, such as organization climate (0.34), operation guidance (0.37), planned operation (0.22), and legal supervision (0.19), are also important reasons for operational errors, while resource management (0.12), hidden investigation (0.18) and legal supervision (0.13) have an impact on operation violates. Moreover, there are still close relationships between other hierarchical elements, such as the operation guidance effect on the hazardous material environment (6.60), and the organizational climate has the most obvious impact on other factors at the level of organizational factors. Based on the above research conclusions, suggestions for individual, enterprise, and government were put forward, respectively, and the limitations of this study were also clarified.

Language: en

Keywords

Bayesian network; hazardous chemical accidents; human factors analysis and classification system; operation error; operation violate