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This paper studies the determinants for the desirability of the public-private partnership (PPP) mode in infrastructure development.

The author manually collects data on over 12,000 PPP projects in China, and regard the successful transition and abnormal termination as signals for the mode’s desirability and undesirability, respectively. Then, guided by relevant theories in the literature, the author investigates the impact of various project characteristics on the projects’ successful transition and abnormal termination.

First, execution-stage projects in industries where government support is indispensable, or where quality improvement is more important than cost reduction, face higher likelihood of abnormal termination. But such negative effects are mitigated if state-owned enterprises (SOEs) participate in the social party. Second, the structure of social party matters. The participation by private firms in the social party increases the termination likelihood, while the decentralization of the social party decreases it. Third, pre-execution projects with government payment or subsidies are more likely to enter into the execution stage.

Regulations on participation by SOEs in PPPs, such as policy [2023 No. 115] announced by State Council, should take industrial heterogeneity into consideration.

Using a large sample, the author empirically tests the seminal PPP-related theories in the literature. The author also uncovers some unique stylized facts about PPPs in China, especially the impact of SOE participation in the social party on PPP survival.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.