Abstract

This study was focused on the roles of human factors in construction accident and also dealt with the probabilities of fours levels of injury. We used an empirical Bayesian method and the human factors analysis and classification system framework to analyze the probability distributions of the severity of accidents of high risk operations in hydropower construction. Accident severity in four levels of injury was modeled: severe injury, one death, two deaths, and three deaths. The results show the behavior characteristics of workers and factors influencing their operation violations. The calculation of posterior distributions of the levels of injury enables us to rank the factors with respect to their risk of injury. The study revealed that lack of the ability to determine hazards is the direct reason in many accidents; resource management, inadequate supervision and supervisory violations also play important roles in the occurrence of accidents.

Key words: Empirical Bayesian analysis, human factors, work accidents, risk analysis and assessment.