TOPSIS Evaluation of Prefabricated Building Construction Based on Interval-Valued Picture Fuzzy Sets and Cumulative Prospect Theory

Prefabricated construction is increasingly adopted worldwide because of its advantages in sustainability and construction efficiency. Nevertheless, the construction phase still faces substantial and multifaceted risks. These risks are characterized by high uncertainty and strong dependence on the subjective judgments of decision-makers, which may limit the wider promotion and application of prefabricated construction. Existing risk assessment methods often struggle to represent neutral and refusal attitudes in expert evaluations with sufficient precision. They also do not fully account for the psychological and behavioral mechanisms of decision-makers under risk. To address these limitations, this study proposes an integrated evaluation framework that combines interval-valued picture fuzzy sets (IVPFSs), cumulative prospect theory (CPT), and TOPSIS. The decision objective is to rank alternative construction-stage risk-control schemes and identify the relatively important risk factors influencing the ranking results. IVPFSs are used to represent support, opposition, neutrality, and refusal degrees in expert evaluations. CPT is incorporated to capture decision-makers’ risk preferences, reference dependence, and loss-aversion behavior. A comprehensive risk indicator system is developed from five dimensions: personnel, management, technology, environment, and materials/equipment. Attribute weights are determined using a coordinated AHP–entropy weighting scheme to balance subjective expert judgment with objective information contained in the evaluation data. The proposed framework is applied to a prefabricated building project in Shanghai. The results indicate that personnel-related factors, especially the technical proficiency of construction workers, are relatively important risk sources in the examined case. The model also provides a structured ranking of alternative risk-control schemes. Overall, this study offers an exploratory case-based decision-support framework for construction-stage risk management in prefabricated building projects and demonstrates the potential value of incorporating behavioral preferences into fuzzy multi-criteria risk assessment.