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Risk assessment of construction projects using Monte Carlo simulation
Abstract
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.
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Increasingly more academics and practitioners are reluctant to resort to risk matrices.
“Since then, increasingly more academics and practitioners are reluctant to resort to risk matrices (Qazi et al. 2021).”
From Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation (2024) · cites this paper as Qazi et al. 2021
Risk matrices are widely recognised tools by academics and practitioners in various sectors to assess and rank risks according to likelihood of occurrence and impact on project objectives.
“Risk matrices are widely recognised tools by academics and practitioners in various sectors to assess and rank risks according to their likelihood of occurrence and impact on project objectives.”
From Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation (2024) · cites this paper as Qazi and Simsekler, 2021
Risk matrices are widely recognised tools by academics and practitioners in various sectors to assess and rank risks according to likelihood of occurrence and impact on project objectives.
“Risk matrices are widely recognised tools by academics and practitioners in various sectors to assess and rank risks according to their likelihood of occurrence and impact on project objectives.”
From Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation (2024) · cites this paper as Qazi et al. 2021
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Cited by
Sorted by citations
Acebes, F., González-Varona, J. M., López-Paredes, A., & Pajares, J. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03180-5 · Cited by 74
Metadata
- Authors
- Qazi, A., & Simsekler, M. C. E.
- Affiliations
- American University of Sharjah (AE)
- Khalifa University of Science and Technology (AE)
- Venue
- International Journal of Managing Projects in Business
- Publisher
- Emerald
- Published
- 2021-02-12
- Volume
- 14
- Issue
- 5
- Pages
- 1202-1218
- ISSN
- 1753-8378 (ISSN-L)
- OpenAlex
- W3130298214
- Cited by
- 41
- References
- 0
- Citations by year
- 2026: 15 · 2025: 12 · 2024: 5 · 2023: 4 · 2022: 4 · 2021: 1
- FWCI
- 1.94
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Managing Projects in Business (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Construction Project Management and Performance
- Social Sciences › Economics, Econometrics and Finance › Finance › Capital Investment and Risk Analysis
- Social Sciences › Decision Sciences › Management Science and Operations Research › Multi-Criteria Decision Making
- Keywords
- construction risk, risk prioritization, Monte Carlo simulation, expected utility, risk preferences, risk matrix, risk exposure, risk probability and impact, risk correlation
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