Risk Assessment Models in Engineering Project Management
Publish Year: 1400
Type: Journal paper
Language: English
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Document National Code:
JR_MSESJ-3-1_004
Index date: 19 February 2025
Risk Assessment Models in Engineering Project Management abstract
Risk assessment is a critical component of engineering project management, providing a structured approach to identifying, analyzing, and mitigating risks that could potentially impact project success. This narrative review examines the various risk assessment models applied in engineering project management, categorizing them into qualitative, quantitative, and hybrid models. The review highlights the strengths, limitations, and applicability of these models, offering a comparative analysis of their effectiveness, complexity, and flexibility. Quantitative models, such as Monte Carlo simulations, provide detailed risk assessments but are often constrained by data requirements and complexity. Qualitative models, while more accessible, may lack the rigor needed for comprehensive risk management. Hybrid models combine the strengths of both approaches, offering a balanced and adaptable solution for complex project environments. The review also identifies challenges and gaps in current models, particularly in addressing emerging project types and integrating human factors into risk assessment. The paper concludes by discussing future research opportunities, including the development of models tailored to new technologies and industries, and the exploration of long-term impacts of risk management decisions. Risk assessment is a critical component of engineering project management, providing a structured approach to identifying, analyzing, and mitigating risks that could potentially impact project success. This narrative review examines the various risk assessment models applied in engineering project management, categorizing them into qualitative, quantitative, and hybrid models. The review highlights the strengths, limitations, and applicability of these models, offering a comparative analysis of their effectiveness, complexity, and flexibility. Quantitative models, such as Monte Carlo simulations, provide detailed risk assessments but are often constrained by data requirements and complexity. Qualitative models, while more accessible, may lack the rigor needed for comprehensive risk management. Hybrid models combine the strengths of both approaches, offering a balanced and adaptable solution for complex project environments. The review also identifies challenges and gaps in current models, particularly in addressing emerging project types and integrating human factors into risk assessment. The paper concludes by discussing future research opportunities, including the development of models tailored to new technologies and industries, and the exploration of long-term impacts of risk management decisions.
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