Risk assessment of construction projects using Monte Carlo simulation

PurposeThis 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/approachThis paper a...

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Veröffentlicht in:International journal of managing projects in business Jg. 14; H. 5; S. 1202 - 1218
Hauptverfasser: Qazi, Abroon, Simsekler, Mecit Can Emre
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bingley Emerald Publishing Limited 06.07.2021
Emerald Group Publishing Limited
Schlagworte:
Attitudes
Construction industry
Expected utility
Fuzzy sets
Monte Carlo simulation
Product development
Project management
Risk assessment
Risk exposure
Risk matrix
Risk attitude
Risk assessment
Monte Carlo simulation
Project risks
ISSN:1753-8378, 1753-8386
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Zusammenfassung:PurposeThis 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/approachThis 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.FindingsThe 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/valueMonte 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.
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ISSN:1753-8378
1753-8386
DOI:10.1108/IJMPB-03-2020-0097