Industrialization has been widely regarded as a sustainable construction method in terms of its environmental friendliness. However, existing studies mainly consider the single impact of greenhouse gas emissions or material consumption in the construction process of industrialized buildings, and pay less attention to ecological pollution and community interest, which leads to an insufficient understanding. There is an urgent need to systematically carry out accurate assessment of comprehensive construction environmental impact within industrialized building processes. Various methods, including face-to-face interviews, field research and building information modeling (BIM), were used for data collection. Four categories selected for the study included resource consumption, material loss, ecological pollution, and community interest. A life cycle assessment (LCA) model, namely input-process-output model (IPO), is proposed to analyze the construction environmental impact of the standard layer of industrialized buildings from four life cycle stages, namely, transportation, stacking, assembly and cast-in-place. The monetization approach of willingness to pay (WTP) was applied to make a quantitative comparison. Results reveal that the assembly stage has the largest impact on the environment at 66.13% among the four life cycle stages, followed by transportation at 16.39%, stacking at 10.29%, and cast-in-place at 7.19%. The key factors include power consumption, noise pollution, material loss, fuel consumption and component loss, which altogether account for more than 85% of the total impact. Relevant stakeholders can conduct their project using the same approach to determine the construction environmental performance and hence introduce appropriate measures to mitigate the environmental burden.

An enormous amount of investment has been spent towards informatization for the construction industrialization engineering, procurement, and construction (EPC) enterprises in China; however, the performance output remains uncertain. This paper aims to evaluate the informatization performance of the construction industrialization enterprises in China based on a proposed evaluation framework. The proposed framework entails a hierarchical input and output structure; the input metrics include 4 first‐level and 17 second‐level indicators, and the outputs include 6 first‐level and 27 second‐level indicators as the metrics, respectively. Survey and interview are utilized to collect data, with effective responses from thirty construction industrialization EPC enterprises. The informatization performance of these enterprises is evaluated using an improved D‐FCA method, which incorporates the analytic hierarchy process (AHP), data envelopment analysis (DEA), and fuzzy comprehensive evaluation analysis (FCA). The research results indicate that all the surveyed enterprises meet the performance requirement, and 60% of the thirty enterprises show excellent performance, reaching A level, AA level, and AAA level. Furthermore, for those enterprises with DEA scores less than 1, which indicates inefficient use of the resources during the informatization process, strategies are proposed to improve the performance of these enterprises. This study contributes a comprehensive framework to evaluate the informatization performance of construction industrialization enterprises in China. The enterprises studied currently mainly come from some developed areas, and the overall situation for construction industrialization needs to be further studied in future research.

The defect in quality caused by the noncompactness of sleeve grouting has become the main obstacle restricting the further implementation of the prefabricated building in China. Studies have been conducted to explore the influencing factors of inadequate grouting; however, few studies attempt to investigate the complex interrelationship and lack of systematic cognition among these factors. To fill this gap, this study conducted a comprehensive literature review to collect the influencing factors of sleeve grouting and verified the reliability of these factors using the combined methods of brainstorming and semistructured expert discussion. A total of 18 key factors were identified and determined. The structural interpretation model (SIM) and Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) approaches were then used to analyze, depict, and explain the internal relationships between the factors. The results indicate that all factors were classified into six levels, among which poor responsibility of supervisors and weather conditions are the most basic factors, while grouting speed and a loose‐sealing rubber plug are the most important factors. Finally, a three‐level control strategy was proposed to improve the compactness quality of sleeve grouting. The research findings provide valuable guidelines for managers to eliminate the grouting quality defect and to further the development of prefabricated buildings in China.

Prefabricated construction has been well recognized for its benefits, including accelerated construction cycle time and improved sustainability. However, low efficiency in the production of precast concrete components due to component and production complexity has not been sufficiently addressed in previous research. This paper explores the complexity of precast concrete components by establishing complexity indices and evaluating their influence on production efficiency. First, referring to research on product complexity in the machinery manufacturing industry, we define the complexity of precast concrete components in the construction industry. Then, based on a literature review, field studies, and expert interviews, we systematically construct the complexity indices of precast concrete components using the three‐stage coding method, Grounded Theory. The overall complexity index system for precast concrete components constructed comprises 16 constituent complexity indices in three dimensions (i.e., structural complexity of the component, production complexity, and management complexity). The relationship between complexity indices and production efficiency is then explored using structural equation model analysis based on the data collected through a questionnaire survey. The results reveal that complexity indices have a significant impact on the production efficiency for precast concrete components, where the number of embedded parts, waiting time in production, operating proficiency of workers, and degree of automation of the production line are found to be the most influential complexity indices. This study provides a foundation upon which production managers improve production efficiency for precast concrete components based on an analysis of their product complexity.