Evaluating risk response strategies on construction projects using a fuzzy rule-based system

S. H. Fateminia, Nima Gerami Seresht, A. R. Fayek

Research output: Contribution to conferencePaperpeer-review

9 Citations (Scopus)

Abstract

The development and implementation of risk response strategies contributes to effective risk management processes in construction organizations. Risk response strategies need to be developed and implemented as follows: first, all possible risk responses for each given risk event of a project are identified; next, each risk response is evaluated to determine its effectiveness; then, for each risk event of the project, the optimal risk response is identified and implemented; and finally, the risk events and responses are consistently monitored. The existing literature confirms that there is a lack of research on evaluation criteria for risk responses, making it difficult to determine their effectiveness. This paper presents research that fills this gap by developing a way to evaluate the effectiveness of risk response strategies using a fuzzy rule-based system (FRBS) that consists of three inputs and one output. The inputs of the FRBS are the affordability and the achievability of risk responses and the controllability of risk events; the output is the effectiveness of the risk response. The application of fuzzy ranking methods instead of crisp ranking methods allows the model to mimic three human attitudes towards risk: risk averse, neutral, and risk taking. The proposed model lays the foundation for an automated evaluation of risk response strategies and provides a decision support tool for experts in the field.

Original languageEnglish
Pages282-288
Number of pages7
DOIs
Publication statusPublished - 1 Jan 2019
Event36th International Symposium on Automation and Robotics in Construction, ISARC 2019 - Banff, Canada
Duration: 21 May 201924 May 2019

Conference

Conference36th International Symposium on Automation and Robotics in Construction, ISARC 2019
Country/TerritoryCanada
CityBanff
Period21/05/1924/05/19

Keywords

  • FRBS
  • Fuzzy logic
  • Risk management
  • Risk response

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