The Cost Burden of Safety Risk Incidents on Construction: A Probabilistic Quantification Method.

The construction sector is vulnerable to safety risk incidents due to its dynamic nature. Although numerous research efforts and technological advancements have focused on addressing workplace injuries, most of the studies perform empirical and deterministic postimpact evaluations on construction project performance. The effective modeling of the safety risk impacts on project performance provides decisionmakers with a valuable tool toward incidents prevention and proper safety risk management. Therefore, this study collected Australian incident records from the construction industry from 2016 onwards and conducted discrete event simulation to quantitatively measure the impact of safety risk incidents on project cost performance. Moreover, this study investigated the correlation between safety risk incidents and the age of injured workers. The findings show a strong correlation between the middle-aged workforce and the severity of incidents on project cost overruns. The ex-ante, nondeterministic analysis of safety risk impacts on project performance provides insightful results that will advance safety management theory in the direction of achieving zero harm workplace environments.

Quantitative Analysis of Safety Risks and Relationship with Delayed Project Completion Times.

Dynamic work environments in construction and civil infrastructure sectors remain susceptible to safety risks. Although previous research has resulted in improvements, there is currently a gap in measuring temporal impacts of safety risks quantitatively. Precise modeling of potential delays caused by safety incidents is vital for efficient management of risks and making informed decisions on project contingency. Toward this aim, the current research adopts a nondeterministic modeling method to simulate and quantify safety incidents and find correlations with project delays. Using a deductive approach, three research questions were formulated, and investigations conducted on Australian data collected from 2016 onwards. Quantitative impacts of safety risks on project completion times were numerically measured. Furthermore, safety risks were ranked based on their significance of temporal impacts on project performance. This paper contributes to the theory of safety management by developing a nondeterministic method to model impacts of safety risks at both industry and project levels. Practical contributions and outcomes can facilitate using machine learning methods to plan proportionate time buffers to address safety risks.