The implementation of prefabricated housing (PH) has become prevalent in China recently because of its advantages in improving production efficiency and saving energy. However, the benefits of adopting PH cannot always be accrued by the stakeholders because of the arising transaction costs (TCs) in the projects’ development process. This study investigates the strategies for developers to make rational choices for minimizing the TCs of the PH project considering their own attributes and external constraints. A Bayesian Belief Network model was applied as the analytical method, based on the surveys in China. The single sensitive analysis indicated that developers influence the TCs of PH through the three most impactful factors: Prefabrication rate, PH experience, and Contract payment method. Furthermore, combined strategies were recommended for developers in various situations based on the multiple sensitivity analysis. Developers facing high prefabrication rate challenges are suggested to reduce the risks by procuring high-qualified general contractors and adopting unit-price contracts type. For developers with limited PH experience, adopting the Engineering-Procurement-Construction procurement method is the most efficient in reducing their TCs in the context of China’s PH market. This study contributes to the current body of knowledge concerning the effect of traders’ attributes and choices on TCs, expanding the application of TCs theory and fulfilling the study on the determinants of TCs in construction management.

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.

Referring to the newspaper textual analysis method by Baker et al. (2016), this study constructs a monthly Chinese Real Estate Policy Uncertainty (REPU) index from 2001 to 2018. The index increases significantly near the promulgation of major policies. We also conduct evaluation of the index with the vector autoregression (VAR) model, which reveals that the rise of REPU indicates the decline in the growth rate of commodity housing development investment, sales area, and real estate industry added value. The REPU index is helpful to expand the understanding of policy uncertainty, and the accurate measurement of REPU is the basis for further research of its impact on China's real estate market.