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The use of proper risk analysis techniques and contingency determination procedures in construction projects improves project efficiency and effectiveness. However, the uncertainty inherent in risk and the lack of sufficient related historical data on risks make it difficult to precisely assess a project’s degree of risk exposure using classical deterministic or probabilistic risk analysis techniques. This paper provides an alternative to these techniques that uses fuzzy logic and expert judgment. It proposes a fuzzy contingency determination model (FCDM) that utilizes a novel and transparent fuzzy arithmetic procedure to determine construction project contingency using the α-cut method and the extension principle, based on t-norms. Linguistic scales, represented by fuzzy numbers, enable experts to use natural language to assess the probability and impact of risk and opportunity events instead of depending on historical data. The model expresses contingency either as confidence intervals at different levels of confidence, or as a single crisp value resulting from defuzzification. A software tool, the Fuzzy Contingency Determinator (FCD), has been developed to implement the FCDM’s fuzzy arithmetic procedure. The model is validated by comparing its results—work package and project contingencies—to those of a Monte Carlo simulation model, using actual project data. The main contributions of this paper are (1) providing a systematic, transparent, and flexible methodology to identify and assess risk and opportunity events and determine construction project contingency, using a novel and highly flexible fuzzy arithmetic procedure based on the α-cut method and the extension principle, the latter of which uses different t-norms—an approach that has not been previously applied in the construction domain to determine project contingency; (2) offering an alternative to traditional deterministic and probabilistic risk analysis approaches by using expert judgment, linguistic scales, and fuzzy numbers to overcome their limitations; (3) incorporating opportunity in its assessment procedure, which has been rarely applied in other risk assessment models; and (4) implementing the fuzzy arithmetic procedure of the FCDM using a simple, flexible, and user-friendly software tool: FCD. The ability to explore the effect of different fuzzy arithmetic procedures on contingency determination provides a generalizable approach that can be applied to different cases of risk analysis.
Elbarkouky et al. (Mon,) studied this question.