Unraveling the evolutionary patterns of construction accidents: a risk assessment framework based on average mutual information theory - Jian Liu; Hanqiang Tang; Rui Feng (Scientific Reports)
Abstract Studies of the evolutionary law of construction accidents and the formulation of effective risk assessments are crucial for ensuring construction safety and reducing accidents. However, existing research often focuses exclusively on one of the four critical perspectives: human, facilities, environment, and management, with limited systematic theoretical analysis. Current risk assessments typically emphasized the impact of risks at specific points in time, neglecting the cumulative effects of risks over extended periods. This study has explored how hazardous and harmful factors affect the evolution of accidents, then has established a risk assessment model utilizing average mutual information theory. The findings indicate that “Command violations”, “Command errors”, and “Illegal operations” are the primary direct causes, while “Inadequate occupational safety and health management structure and staffing” and “Inadequate or unimplemented occupational health management system” are key management factors. In addition, it also provides practical guidance for construction enterprises to strengthen safety management from aspects such as safety production investment and safety management system integration. These contributions are expected to significantly improve the safety level of construction projects and reduce the occurrence of accidents.