Understanding and Improving Input for Quantitative Risk Analysis in the Construction Industry

• Author / Creator

  Abou Rizk, Hala

• Risk analysis in the construction industry involves identifying risk events that could potentially affect a project and its delivery, quantifying those risks, and developing mitigation strategies to enhance project success. This thesis aims to improve the process of risk analysis through the enhancement of the quantification process (QRA) using Monte Carlo techniques. In particular, this study investigates qualitative verbal expressions utilized when gathering information from experts and the methods by which they are converted into quantitative data for analysis. The effects of the quantitative data used as inputs have been found to affect the resulting values and distributions. In order to enhance this process, a survey is created to better understand verbal expressions used in the risk analysis process. This has resulted in a table of corresponding quantitative values, in terms of deterministic values and beta distributions, which can be utilized for QRA and extended to other areas of academia.

• Subjects / Keywords

  • Range estimating
  • Monte Carlo Simulation
  • Risk analysis
  • Input parameters

• Graduation date

  Fall 2013

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R39C6SB73

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.