Fuzzy Cognitive Map-Enabled Approach for Investigating the Relationship between Influencing Factors and Prefabricated Building Cost Considering Dynamic Interactions

Prefabricated buildings have the advantages of efficiency, green, and sustainability. However, high cost seriously restricts the development and application of prefabricated buildings. The existing literature mainly focuses on a comparison of the incremental cost of prefabricated buildings and conventional buildings, and because most of the studies on the influencing factors of prefabricated cost are static analyses, the guiding role of prefabricated building cost control is inadequately explored. This study presents a fuzzy cognitive map (FCM)-enabled approach to investigate the relationship between influencing factors and prefabricated building cost, considering dynamic interactions. Content analysis and the Delphi method are combined to identify influencing factors, and the degree of influence was determined with the help of domain experts; thus, a cause-effect model consisting of nine concepts is established for analyzing the influencing factors of prefabricated building cost based on FCM. Results indicate that (1) the factors that have the greatest impact on CT (prefabricated building cost) include C1 (scale effect), C6 (PC PE), C4 (standardization degree), and C8 (construction management level); (2) C1 is the possible root cause that affects the cost of prefabricated buildings, because it displays the strongest negative correlation with CT, and the work in the early decision-making and design stage is of great significance; and (3) when the factors that are difficult to control for construction enterprises are not considered, the cost is most sensitive to changes in C6 and C4. The novelty of the proposed approach is that it can model the dynamic interactions between influencing factors and prefabricated building cost, and perform many kinds of what-if scenario analyses, including predictive, diagnostic, and sensitivity analyses. The proposed approach can be used to identify influencing factors for enhancing the probability of success in cost control of prefabricated buildings.