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A Framework for Aggregation of Heterogeneous Experts' Opinions in Construction Risk Assessment

  • Author / Creator
    Monzer, Natalie
  • Construction companies constantly seek to improve risk analysis techniques to determine projects' risk contingency. The construction risk assessment practice relies on heterogeneous experts' opinions in a group decision making (GDM) process to determine the risk probabilities and impacts on a project. In this research, the risk probabilities and impacts are expressed as linguistic terms represented by fuzzy sets, which better represents the uncertainty in experts' risk assessment. However, the current GDM process obtains the experts' collective risk assessment through the consensus reaching process (CRP), which has several limitations, such as being a time consuming procedure. This research improves construction risk assessment GDM by introducing a structured aggregation framework to combine heterogeneous experts' risk assessments. During the aggregation process, the industry common practice in order to represent the heterogeneous experts' different expertise level is to assign experts' importance weights. However, previous literature methods for assigning heterogeneous experts' importance weights are subjective and biased. Therefore, there is a lack of a structured approach for assessing experts' expertise level in construction risk assessment. The aggregation framework illustrated in this thesis presents a systematic and flexible multi-step methodology to assess heterogeneous experts' expertise level and assign experts' importance weights in the construction risk assessment GDM aggregation process. The methods used in the aggregation framework advance the practical application of evaluating heterogeneous experts in construction, while the combination of experts' risk assessments through aggregation advances construction industry GDM practice. A case study with actual project data demonstrates the steps involved in the aggregation framework, and analyzes the most suitable aggregation operator to be implemented in the context by comparing the project risk contingency results to Monte Carlo Simulation (MCS) results. The main contributions of this paper are: introducing a clear and consistent list of criteria, metrics and scales of measure to evaluate experts' risk assessment expertise; developing a method to weight experts' importance in risk assessment according to their expertise level; and improving construction risk assessment GDM by introducing a structured framework for construction risk assessment that combines heterogeneous experts' assessments through aggregation.

  • Subjects / Keywords
  • Graduation date
    Spring 2018
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R38G8FZ61
  • License
    Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.