Su Yang

As the global urbanization process continues to accelerate the implementation of the “dual carbon” strategy, urban underground pipelines, as important infrastructure and urban lifelines, have generated significant resource consumption and ecological environmental impacts throughout their entire life cycle. This paper is based on lifecycle assessment (LCA) theoretical framework and systematically defines the scope of lifecycle assessment for underground pipeline projects, covering the stages of raw material production and processing, raw material transportation, construction, operation and maintenance, and disposal. Then, a comprehensive lifecycle inventory database has been established through inventory analysis. A lifecycle environmental impact assessment model for underground pipeline projects has been developed utilizing categorization, characterization, standardization, and weight determination, enabling quantitative evaluation of environmental impacts at each stage. At last, an urban underground pipeline project was selected as a case and the emission inventory data were integrated with the environmental impact assessment model to conduct a systematic analysis across all the lifecycle stages. The results indicate that the photochemical ozone creation potential (POCP), atmospheric particulate matters potential (APMP), and solid waste potential (SWP) have the most significant environmental impacts, and the total environmental impact values are 70, 104 and 83.9 capita equivalent, respectively. Moreover, the raw material production and processing, operation and maintenance, and construction stages are identified as the primary contributors to these environmental impacts, and the values are 17.5, 10.6 and 1.8 capita equivalent, respectively. Based on these findings, targeted improvement measures have been proposed for each stage, providing valuable references for optimizing engineering practices.

The construction industry has long been recognized as one of the world’s most hazardous sectors, with safety issues remaining a persistent challenge. To enhance sustainable safety management in this field, this study employs Self-Determination Theory (SDT) to explore the psychological mechanisms underlying construction workers’ safety behaviors. Through structural equation modeling using SPSS 27 and AMOS 28 software on 334 questionnaires, the research reveals that safety awareness and work pressure not only directly influence safety behaviors but also mediate through psychological factors. Notably, social identity significantly moderates the cognitive–behavioral pathway, while autonomous and control motivations moderate the psychological–behavioral relationship. This study breaks through the limitations of traditional safety management that focuses solely on external factors, constructing a multi-level theoretical model that encompasses cognitive, stress, psychological, motivational, and social factors. The research provides a theoretical foundation and practical pathway for construction enterprises to implement people-oriented safety management, contributing to the Sustainable Development Goals centered on the health and safety of employees.

In the face of evolving digital technologies, all industries have undergone radical changes. Similarly, the construction industry needs to apply digital technology to improve the existing Supply Chain (SC), which has problems such as the inefficient collaboration among various links, the poor ability to cope with risks, the higher costs, the waste of resources and pollution, etc., and to adapt to the development of the digital era. Prefabricated Construction (PC), with their advantages of having a high efficiency and being energy-saving, can help improve the above problems and promote the sustainable development of the construction industry. Therefore, this review uses a combination of scientific bibliometrics and a qualitative analysis to search a total of 129 works of literature on the application of digital technologies in Prefabricated Construction Supply Chain Management (PCSCM) for the period of 2015–2024 included in the Web of Science, Scopus, and PubMed databases. After visualization and analysis in Citespace v6.3.1.0 and VOSviewer v1.6.20.0, it was found that most of the literature focuses on the economic benefits of cost reduction and efficiency, while there are fewer studies on the topic of sustainable development. Therefore, this study summarizes the current status of the application of digital technologies in PCSCM, addressing the lack of attention to environmental benefits in the existing studies and the limitations of the current research. Creatively, it proposes recommendations that will help PCSCM achieve sustainable development in the future, and points out that the construction industry must break through the limitation of focusing only on its own economic interests to realize the vision of a harmonious coexistence between human beings and nature.

The construction industry’s poor safety is a global issue, with construction workers’ unsafe behaviors (CWUBs) identified as a major cause of accidents. Based on social cognitive theory (SCT) and using multiple regression analysis, this study categorizes accident experience (AE) into direct and indirect types, examining how each affects CWUBs and the roles of risk perception (RP), safety attitude (SA), and safety competence (SC) in these relationships. Utilizing a structured questionnaire completed by 334 valid respondents and analyzed through structural equation modeling (SEM), the study found that indirect experience (IE) significantly reduced CWUBs, with a standardized path coefficient of −0.364, while direct experience (DE) has a smaller impact, with a standardized path coefficient of −0.154, but a significant p. Furthermore, IE positively influenced RP, SA, and SC, explaining 66.8% of its total effect. This study offers a new framework for understanding how AE influences CWUBs, providing actionable insights for managers to implement effective strategies that reduce CWUBs on construction sites.

Every country in the world, except for African nations, faces significant challenges due to the increasing older population, with China being particularly affected. This issue is more pronounced in rural areas compared to urban centers. To better understand consumer attitudes and willingness to pay (WTP) for age-friendly retrofitting and to identify industry development shortcomings, this study designed a retrofitting scenario and organized a questionnaire survey to collect WTP and its influencing factors from respondents in the Wuhu area of Anhui Province, China. This study determined the retrofit cost to be CNY 12,224.4 and found that over 80% of respondents intended to pursue age-friendly retrofitting. The analysis results indicated that respondents’ education level, perceived psychological benefits, and perceived social benefits were positively correlated with their WTP. Additionally, education level, monthly personal income, and choice of retirement area positively influenced retrofitting budgets, whereas age bracket, employment status, and perceived situational risk negatively influenced them. The study’s findings will assist consumers in making informed retrofitting decisions and support the government in formulating appropriate policies to enhance the quality of rural residential environments and improve the living standards of the elderly.

This research investigates how age expectation (AE) influences construction worker safety behavior (CWSB) by utilizing self-validation theory (SVT). Using structural equation modeling (SEM) and data from 391 Chinese construction workers, we found that components of AE, such as physical health expectation (PHE), mental health expectation (MHE), and cognitive function expectation (CFE), positively impact CWSB. Safety value (SV), including safety risk perception (SRP) and safety attitude (SA), mediates these effects. The study provides theoretical insights and practical guidance for enhancing CWSB through interventions on AE, supporting sustainable growth and workforce quality in the construction industry.

In pursuing low-carbon solutions in the construction sector, it is critically essential to unravel the intricate nexus between population aging and carbon emission efficiency (CEE). This research investigates this complex association utilizing provincial panel data from 2004 to 2020. Through the application of the super-efficient Slack-Based Measure and Malmquist–Luenberger (SBM-ML) model, the study quantifies the construction industry’s CEE, followed by using a fixed-effect model to assess population aging’s impact on CEE in the construction industry. Our study reveals a distinct “U”-shaped pattern, illustrating that population aging initially depresses but eventually amplifies CEE in the construction industry. We also observe marked regional disparities. For instance, the construction sectors in the eastern and northern regions show a rising trend, counteracting the initial decline in CEE due to aging. However, the central western and southern regions need more pronounced aging progression to experience comparable CEE improvement. These findings underscore the critical role of regional contexts and demographic transitions in shaping the CEE in the construction industry, providing valuable insights for crafting sustainable policies aiming at balanced population mobility and carbon neutrality.

With in‐depth development of industrialization and urbanization in China, improving the professional skills and quality of migrant workers in the construction industry has become an important measure to optimize the labor force structure and promote the industry upgrading. Numerous studies have been carried out on this topic, and construction industrial workers with high skills level and professional quality have replaced the professional identity of migrant workers. However, the psychological cognitive mechanism of migrant workers’ occupational role enhancement behavior has not been fully revealed. This study aims to construct a theoretical model of the intention to influence the industrialization of migrant workers in the construction industry based on the frameworks of the theory of planned behavior and risk perception theory, and to explore the key factors and cognitive mechanisms in their transformation into industrial workers in the construction industry. Empirical study using structural equation modeling through field collection of 383 questionnaires from migrant construction workers shows that perceived behavioral control, subjective norm, and behavioral attitude all have significant positive effects on behavioral intention, with decreasing direct effects in descending order of magnitude. Perceived behavioral control also predicts professionalization through the mediation of behavioral intentions, and the newly introduced risk perception factor in the model has a negative inhibitory effect on behavioral intentions and actual behavior. This study validates the important role of psychological intention on the industrialization of migrant workers in the construction industry, providing a new perspective to promote their transformation into industrial workers, and laying the foundation for the modern transformation and sustainable industry development.