Risk assessment of construction projects using Monte Carlo simulation

Purpose: This paper aims to develop a process for prioritizing project risks that integrates the decision-maker's risk attitude, uncertainty about risks both in terms of the associated probability and impact ratings, and correlations across risk assessments. Design/methodology/approach: This paper adopts a Monte Carlo Simulation-based approach to capture the uncertainty associated with project risks. Risks are prioritized based on their relative expected utility values. The proposed process is operationalized through a real application in the construction industry. Findings: The proposed process helped in identifying low-probability, high-impact risks that were overlooked in the conventional risk matrix-based prioritization scheme. While considering the expected risk exposure of individual risks, none of the risks were located in the high-risk exposure zone; however, the proposed Monte Carlo Simulation-based approach revealed risks with a high probability of occurrence in the high-risk exposure zone. Using the expected utility-based approach alone in prioritizing risks may lead to ignoring few critical risks, which can only be captured through a rigorous simulation-based approach. Originality/value: Monte Carlo Simulation has been used to aggregate the risk matrix-based data and disaggregate and map the resulting risk profiles with underlying distributions. The proposed process supported risk prioritization based on the decision-maker's risk attitude and identified low-probability, high-impact risks and high-probability, high-impact risks.