The unique nature of construction projects and uncertainties during project execution make construction a highly risk-prone industry. The system dynamics (SD) approach, which focuses on the cause-effect relationship of model variables, is a viable option to model and analyze construction risks, which are considered to be highly dynamic, and has the ability to capture the interrelationships and interactions among different risks. However, conventional SD has a limited ability to handle risk imprecision and uncertainty; these elements can be best dealt with using fuzzy logic. Research endeavors to integrate SD and fuzzy logic so as to address the shortcomings of SD in construction risk modeling and analysis are very few. In this paper, a methodology for developing a fuzzy system dynamics (FSD) framework is proposed that combines the strengths of SD with those of fuzzy logic to improve construction risk modeling and develop risk mitigation strategies. The main contributions of this paper are: (1) identifying research gaps in FSD modeling; (2) providing a systematic and detailed methodology for developing the FSD framework; and (3) examining existing approaches for representing fuzzy variables and fuzzy rules, and the impact of different fuzzy arithmetic operators and defuzzification methods in FSD models.
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