scholarly journals Development of a risk analysis model. Appendix C. Risk analysis methodology. Final report

1979 ◽  
Author(s):  
◽  
2015 ◽  
Vol 22 (4) ◽  
pp. 403-423 ◽  
Author(s):  
Önder Ökmen ◽  
Ahmet Öztaş

Purpose – Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the uncertainty and correlation effects into account. In this regard, a simulation-based cost risk analysis model, the Correlated Cost Risk Analysis Model, previously has been proposed to evaluate the uncertainty effect on construction costs in case of correlated costs and correlated risk-factors. The purpose of this paper is to introduce the detailed evaluation of the Cost Risk Analysis Model through scenario and sensitivity analyses. Design/methodology/approach – The evaluation process consists of three scenarios with three sensitivity analyses in each and 28 simulations in total. During applications, the model’s important parameter called the mean proportion coefficient is modified and the user-dependent variables like the risk-factor influence degrees are changed to observe the response of the model to these modifications and to examine the indirect, two-sided and qualitative correlation capturing algorithm of the model. Monte Carlo Simulation is also applied on the same data to compare the results. Findings – The findings have shown that the Correlated Cost Risk Analysis Model is capable of capturing the correlation between the costs and between the risk-factors, and operates in accordance with the theoretical expectancies. Originality/value – Correlated Cost Risk Analysis Model can be preferred as a reliable and practical method by the professionals of the construction sector thanks to its detailed evaluation introduced in this paper.


Author(s):  
J. Robert Sims

Risk analysis has been used extensively to inform decisions throughout government and industry for many years. Many methodologies have been developed to perform these analyses, resulting in differences in terminology and approach that make it difficult to compare the results of an analysis in one field to that in another. In particular, many approaches result only in a risk ranking within a narrow area or field of interest, so the results cannot be compared to rankings in other areas or fields. However, dealing with terrorist threats requires prioritizing the allocation of homeland defense resources across a broad spectrum of possible targets. Therefore, a common approach is needed to allow comparison of risks. This presentation summarizes an approach that will allow the results of risk analyses based on using current methodologies to be expressed in a common format with common terminology to facilitate resource allocation decisions.


2021 ◽  
Vol 13 (4) ◽  
pp. 2034
Author(s):  
Chien-Liang Lin ◽  
Bey-Kun Chen

Risks inevitably exist in all stages of a project. In a construction project, which is highly dynamic and complex, risk factors affect the expected achievement rates of the three main performance goals, namely schedule, cost, and quality. A comprehensive risk management procedure requires three crucial steps: risk confirmation, analysis, and treatment. Risk analysis is the core of risk management. Through structural equation modeling, this study developed a risk analysis model that takes a different perspective and considered the occurrence probability of risk events and the extent to which these events affect a project. The contractor dimension was discovered to exert the strongest influence on an overall project, followed by the subcontractor and design dimensions. This paper proposes a novel construction project risk analysis model, which considers the entire project. The proposed model can be used as a reference for risk managers to make decisions about project risks, so as to achieve the ultimate goal of saving resources and the sustainable operation of the construction project.


2019 ◽  
Vol 183 ◽  
pp. 173-183 ◽  
Author(s):  
Huai-Wei Lo ◽  
James J.H. Liou ◽  
Chun-Nen Huang ◽  
Yen-Ching Chuang

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