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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.

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