To promote the EPC (engineering, procurement, construction) model in public projects has become a key task of China’s construction industry reform. However, the behavioral and strategic choices of stakeholders related to the EPC model will affect its stable development. We establish a tripartite evolutionary game model of government-owner-construction company, and analyze the behavioral strategies and influencing factors of these stakeholders in the development of the EPC model based on actual engineering case data. The results show that (ⅰ) there are six evolutionary stable strategies, formed from different combinations of conditions. Among them, the strategy of government incentive, owner choice, and company upgrading qualification is the most suitable for the development of the EPC model in China; (ⅱ) the relevant parameters have threshold effects, which may affect the behavioral strategies of various stakeholders. Therefore, the standards of government incentive policies must be scientific and reasonable. Graphical Abstract

The key to promoting the EPC (Engineering, Procurement, Construction) model in China’s public construction projects is to alter the path dependence of a project owner’s choice of project delivery model (PDM). This study uses evolutionary game theory to discuss the mechanism of government incentives as an external motivation to alter path dependence in the PDM. In addition, a cellular automata simulation to examine the influence of various government incentives on the project owner’s choice. The results show that the combination of subsidies and penalties can produce the best incentive. Subsidies are more effective at promoting PDM institutional change, whereas penalties are more effective at preventing PDM institutional change from anti-recession effects. Based on our results, we propose that the Chinese government should take active subsidy measures at the initial stage of EPC promotion, and adopt a dynamic incentive strategy of continuously reducing subsidies and increasing penalties according to the improvement of the development degree of EPC model.

The promotion of the EPC model in public construction projects is a priority for reform in the Chinese construction industry. This study integrates the push–pull–mooring (PPM) model with the stimulus-organism-response (SOR) framework to explore the influencing factors and action mechanisms of adopting the EPC model of the owners of public construction projects in China. An online questionnaire was sent to public construction project owners who have participated in EPC projects. Partial least squares-structural equation modeling (PLS-SEM) was employed to analyze the survey data. The results identified that the push factors for public construction project owners to the adoption of the EPC model include owners’ management ability, owner’s knowledge about EPC, and the matching degree between the owner’s management philosophy and EPC model; the pull factor is the performance pressure of the project; and the mooring factors include subjective norms, the maturity degree of the EPC, and the support environment. In addition, perceived usefulness, cognitive, and adoption attitude play a mediating role in the relationship between external stimuli and adoption behavior. Overall, this study enhances the understanding of Chinese public project owners’ behavior in adopting the EPC model and provides a theoretical basis for policy recommendations to promote the adoption of the EPC model by public construction project owners in China.

Prefabricated decoration serves as a critical pathway for building energy conservation and emission reduction. The study deconstructed prefabricated decoration projects into seven functional modules—integrated toilet, doors and windows, equipment piping, walls and partitions, roof, floor, and integrated kitchen—and compared the design, production, transportation, construction, maintenance, and demolition phases with traditional approaches. Subsequently, it analyzed the components of prefabricated decoration's incremental cost-effectiveness, quantified the incremental benefit-cost ratio through system dynamics modeling, and identified key influencing factors. Finally, a three-dimensional enhancement strategy of “technology optimization-supply chain synergy-policy incentives” was proposed to provide quantitative decision-making tools for industry adoption.

To clarify the overall vein, governance intention and focus point of the assembly building promotion policies, this paper adopts the content analysis method to conduct an in-depth study of the assembly building promotion policies in 32 regions of China from the dimensions of policy external structure, effectiveness level and policy tools. The study found that the number of policy releases is affected by regional economic development level, industrial foundation and other factors, showing significant regional differences. There is a structural imbalance in the distribution of policy instruments. In addition, there are structural deficiencies in the policy system, which is “macro-heavy and micro-heavy,” and there is a relative lack of specialized policies. Based on this, this paper proposes the implementation of differentiated policies based on the gradient of regional economic development, and the construction of a “1 + N” policy system, while establishing a dynamic evaluation mechanism. It provides theoretical support and path suggestions for the optimization of China’s assembly building promotion policy.

To address the dilemma of the low actual adoption rate of assembly and decoration technology, a comprehensive, scientific, and integrated evaluation system was constructed to provide a scientific basis for promoting and managing the technology. The study adopted a research method combining the Delphi method and the analytical hierarchy process. First, it organizes two rounds of expert consultation. These consultations cover 20 experts in the field of assembly and decoration. The study establishes a comprehensive evaluation system. This system contains five first-level indicators (quality, cost, schedule, safety, and environment). It also contains 24 s-level indicators. Then, it allocates the weights of the first-level indicators and the second-level indicators. The results of the study show that the weight distribution for each dimension is as follows: quality (17.31%), cost (11.96%), schedule (7.30%), safety (39.50%), and environment (23.93%). Among all secondary indicators, the indicator of “safety and security of construction personnel” (19.43%) has the highest weight proportion. The research results identify the key factors that influence the adoption of assembly and decoration technology in residential projects. This provides a scientific basis for making decisions and effectively promoting the technology in the future.