Compared with the conventional cast-in-situ method, prefabricated construction (PC) is a sustainable construction method. In China, the sustainable performance qualities of PC—such as its improved quality, lower cost and shorter turnaround—have barely been achieved. This is likely attributable to the weak sustainable construction capability of construction enterprises in undertaking PC projects. This study observed that there is relatively scant research on critical influencing factors relating to this capability, after investigating the most recent literature about PC development obstacles. Without a clear understanding of this knowledge, construction enterprises are unlikely to formulate effective measures to enhance their sustainable construction capability to tackle efficiency, cost, risk, and broader performance issues in PC. Therefore, this study identified 27 factors from the literature and interviews, ranked these factors using the Entropy method and the fuzzy analytic hierarchy process (FAHP), examined the top five critical factors, and discussed the problem-solving measures. This study drew the conclusion that construction enterprises should focus on PC business scope expansion, project delivery quality improvement, and technology investment and innovation, as well as the return on investments in technology. It is also suggested that incentivised strategies be formulated by the Chinese government in order to improve industry practitioners’ capability of implementing sustainable PC projects. This will eventually expedite the industry’s transformation towards leaner, more efficient and sustainable practice.

Prefabricated construction (PC) is considered as a sustainable construction mode that can improve project performance such as quality and efficiency. Even though, Chinese governments at different levels have formulated many guidelines and incentives to help construction firms better implement PC, their implementing PC level is still low. To some extent, this is likely attributed to ineffective measures of improving PC projects’ performance for construction firms lacking adequate understanding of their PC development level and corresponding influencing factors. Furthermore, there are relatively scant research works exploring the issue. Thus, this study aims to formulate a PC maturity model that can be used to evaluate the PC development level of construction firms. It is also expected that this model can identify the key factors that influence the development maturity. The model is firstly established using a four-step methodology, namely, maturity dimension determination, maturity-associated criteria identification, criteria weights calculation based on Entropy and Fuzzy Analytical Hierarchy Process (FAHP), and maturity level evaluation based on fuzzy integral. Next, three construction firms are selected as study cases to test the model’s effect on mapping out PC maturity and key influencing factors. Key findings are eventually analysed to derive effective strategies for improving the maturity of construction firms, further expediting the sustainable transition of the construction sector into PC.

Prefabricated construction (PC) is increasingly promoted in the construction sector for its potential benefits, including reduced resource assumption and improved quality. Accordingly, Lean methods are popularly applied to PC projects for optimizing operational processes and enhancing their performance in line with strategic objectives. A key factor in effectively implementing Lean to improve strategic control is developing specific strategies and planning that consider their complex interactions. Thus, this paper aims to propose a quantitative network-based model by integrating Interpretive Structural Modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) under complex network theory to develop a Lean implementation framework for effective strategy formulation. Specifically, 17 Lean implementation strategies for PC in the context of the Chinese prefabrication industry were identified via an extensive literature review and expert interviews. Then, ISM-MICMAC quantitatively identifies the direct and indirect relationships among strategies, while subsequent analysis of Topological Structure Weight (TSW) and Structural Degree Weight (SDW), as complex network parameters, is used to evaluate the importance of each strategy. The findings show that the strategic planning for Lean implementation in PC consists of four levels, i.e., foundation, organizational, technical, and control. Selecting appropriate Lean tools and technologies is crucial for PC implementation, which must be built on a top-level management team and foster a Lean culture. Moreover, it involves building a standardized system of processes and activities, enhancing both internal and external collaboration, and continuously improving processes in response to changes. On one hand, this in-depth network-based analysis offers practical insights for PC stakeholders, particularly in China, on Lean implementation in line with PC performance and strategic control and objectives. On the other hand, the network-based model can be future-implemented globally. Additionally, this study expands the current body of knowledge on Lean in PC by exploring the interrelationships of Lean implementation strategies.

The BeiDou navigation satellite system (BDS) provides precise positioning, navigation, and timing (PNT) services in the Asia-Pacific Region, but the BDS-based structural health monitoring (SHM) approach (SHM) is rarely studied, especially in civil engineering. Moreover, how BDS can be applied to complete the tasks of SHM in a real project is also not fully investigated, especially working in conjunction with other techniques. This study aims to propose a BDS-based approach for SHM in civil engineering. The performance of the proposed approach is investigated through a case study—the Tianhan Grand Theater (TGT). A specific Tianhan system corresponding to BDS is proposed to complete the SHM tasks of TGT. Based on the collected data, the trusses with maximum displacement and stress are found by BDS to evaluate structural health in the construction stage. The results show that the maximum displacement and stress have certain safety reserves and meet the requirements of the specifications and regulations. Thus, BDS can satisfactorily complete the tasks of SHM for Long-span steel structures. This study gives a clear view to engineers and researchers that how to apply BDS in structural construction and provides a valuable real case for evaluating the performance of BDS in SHM.

Prefabrication is increasingly recognized as a sustainable construction practice, with the efficiency of prefabricated component (PC) production lines playing a critical role in its success. However, supplier selection for PC production lines has become more complex due to evolving industrial demands, uncertain supply chain conditions, and operational complexities. This study addresses this gap by developing a lean-based AHP–improved VIKOR decision-making framework to enhance the supplier selection for PC production lines. The framework integrates advanced lean principles with universal and specific evaluation criteria, identified through a comprehensive literature review and expert interviews. Its validity was tested via a real-world case study with Yizhong Construction Co., Ltd., Tianjin, China. The results show that the three suppliers are ranked as Zhongjian > Tianyi > Xindadi, where Zhongjian is the best supplier in this case study, with a VIKOR index of 0.156. The findings show that the developed framework can improve the supplier selection efficiency by aligning with lean principles and enhancing the performance of PC production lines. By addressing the challenges of PC supplier selection, this study provides a practical tool to advance the adoption of prefabrication in construction. Furthermore, it contributes to the development of the PC industry by offering a robust method for the selection of suitable suppliers, which can help to optimize the production efficiency and support sustainable practices in construction.

The integration of digital technologies is increasingly recognized as a critical enabler of lean practices in prefabricated construction projects. However, a systematic understanding of the underlying factors that drive this lean–digital transformation remains limited. To address the gap, this study identified 18 factors through an in-depth review of 30 papers and a follow-up questionnaire survey. The factors are divided into five dimensions, i.e., organizational, social, technological, economic and environmental, according to an extended framework of the Socio-Technical Systems (STS) and Technology–Organization–Environment (TOE). These 18 factors were then analyzed via a back propagation (BP) neural network model. The empirical data were collected from 148 practitioners across 11 regions in China where PC industrialization, digital technology adoption, and lean-related practices are relatively mature. These regions were selected because digitalization-driven lean practices are more observable in such contexts, allowing the BP model to capture the comprehensive contribution of key factors more effectively. The findings reveal that the effective implementation of the smart lean practices via digitalization is primarily driven by a systematic process, where greater attention should be directed toward simulation-based process optimization, robust information management, integrated design and construction, lean management systems, and the workers’ digital skills. Although the empirical evidence is derived from relatively mature PC and digital construction markets in China, the identified factors provide reference insights for broader PC projects including less mature regions to make effective measures to improve lean implementation. This study contributes to the existing knowledge body of lean in PC by extending the theories of STS and TOE to advance the understanding of digital drivers. Additionally, the results serve as a reference for stakeholders by informing strategic priorities such as resource allocation for workforce development, advancing the realization of smart lean prefabricated construction.