Prefabricated buildings(PBs) have significant advantages in improving construction efficiency, saving resources, and reducing environmental pollution. They have become an important direction for transforming and upgrading the global construction industry. However, the high construction costs have severely restricted their large-scale adoption. To systematically explore the key influencing factors and the mechanism of the construction cost of PBs, this study uses the method of combining interpretative structural model (ISM) and structural equation model (SEM), identifies the main influencing factors by synthesizing literature and data analysis, analyze hierarchical relationships between these factors via ISM, and quantifies the influence intensity and mechanism of the construction cost by SEM method. The results show that the driving factors of the construction cost of PBs can be divided into several levels. The core factors, such as the assembly rate, the production scale of prefabricated components, the integration of design management, the technical level of designers, and the specialization of prefabricated components in the factory, play a crucial role in cost optimization. In conclusion, this study deeply reveals the impact mechanism of the construction cost of PBs, offers practical guidance for reducing construction costs and optimizing resource allocation, and provides a scientific basis for government policy-making and enterprise strategic decision-making.

This paper provides the first theory and evidence on the role of presale policies in the residential housing market. We start with constructing a novel dataset of unfinished projects, presale policies, and land auction outcomes across 270 major cities in China. We then identify 2,330 unfinished residential projects from 2010 to 2017 on a citizen complaint website run by the central government. We find that both presale criterion and postsale supervision of construction costs relate to a lower probability of unfinished projects. But only presale criterion relates negatively to the pace of new housing development, measured by developers' multitasking and land auction outcomes. A back-of-the-envelope calculation suggests that the average bundle of presale policies is inferior to the Pareto frontier in our sampled cities. Tightening the regulation on postsale supervision by 2 standard deviations may lead to a 58% reduction in the occurrence of unfinished projects, while keeping the pace of new housing development unchanged. Eliminating unfinished projects would entail a drastic increase in both presale criterion and postsale supervision, with slower housing development.