Industry 5.0 is expected to solve the issue of job insecurity and reluctance to adopt emerging technologies in Industry 4.0 through increased workforce participation. To achieve that, proactive training should be afforded to enable the workforce to co-work with new technologies. Drones are an emerging technology increasingly adopted in construction, which has enormous data collection and safety implications when operational skills are inadequate. Yet, current drone training programs appear to be generic, and their ability to equip operators for flying tasks is questioned. This study aims to answer this question by assessing the adequacy of existing drone training programs and proposing training needs and strategies for drone operators in the construction industry. Data collected using semi-structured interviews from 22 purposively selected respondents in Hong Kong and desk research of websites were subjected to inductive content and thematic analysis using MAXQDA Analytics Pro 2022 software and narrative review. It was deduced that drone training courses in Hong Kong were mostly generic (UAS Pilot Training—Level 1, FPV operation). Interviewees considered existing drone training/training courses as inadequate for four reasons, including “lack of context-fitting considerations”, “incompetence of drone operators”, and “lack of demand/interest”. Regarding the need for specialized drone training courses, two barriers and two training ecosystem themes emerged, with the high cost of specialized courses being a potential barrier to adoption since they could hamper enrolment. The training ecosystem themes were consistent with the “the training is inadequate” theme. This study proposes two drone operation training strategies: “competence-based training” and a “train-the-trainer” model. Drone training courses or programs under each training strategy should include (i) training content such as “safety training” and off-GPS training and (ii) knowledge and skill maintenance measures such as mandatory continuous professional development and retraining techniques. The proposed training strategies will equip operators to work efficiently and safely with drones. The study offers valuable references for training organizations and government authorities.

The financing function of land in China has been extensively documented, but little research has explored the role of land finance in the real estate market affecting local government debt. In light of the recent simultaneous increase in China’s real estate market risk and local government debt risk over the past two years, a pressing need to reevaluate the significance of land finance has arisen. Thus, this study explores the role of land finance in the relationship between the real estate market and local debt risk. The data were collected from 224 Chinese cities from 2010 to 2019. The study found that real estate market prosperity significantly promotes the expansion of local government debt. Land finance acts as a mediator and a moderator in this relationship. The study also found that during periods of real estate market booms, local governments tend to sell more land, which reinforces their debt-raising behavior and exacerbates the impact of the real estate market on local government debt; during periods of real estate market downturns, local governments tend to decrease debt, but the government debt repayment risk increases significantly. Furthermore, the amplifying effect of land finance is more pronounced in economically developed regions and cities with higher public budget revenues.

This paper aims to clarify the intricate relationships between technological innovation, transportation industry development, and CO₂ emissions to facilitate a positive synergy among technology, the economy, and climate, advancing the fulfillment of the ‘double carbon’ goal. Utilizing panel data from 30 provinces in China from 2005 to 2020, we employ the panel vector autoregressive model using a generalized method of moments to empirically examine the dynamic interactive effects between these participants. The findings reveal that the transportation industry significantly promoted the inhibitory impact of technological innovation on CO₂ emissions. However, such reductions cannot counterbalance the rise in emissions from the transportation industry. Moreover, its effects varied significantly across regions. Specifically, transportation industry development within eastern China contributed to a shift in the local carbon emission effects from positive to negative under the positive influence of technological innovation. In the northeast, the transportation industry enhanced the inhibitory effect of technological innovation on CO₂ emissions. In contrast, across the western region, industrial development in transportation intensified the role of technological innovation in promoting CO₂ emissions. Furthermore, this work found that CO₂ emissions notably diminished the CO₂ reduction performance of technological innovation in the eastern part and enhanced this performance in the northeastern region. These findings further revealed the complex interplay between technological innovation, the transportation industry, and CO₂ emissions. They offer insights for policymakers to tailor region-specific technologies to bolster the ‘dual carbon’ goal and sustainable transportation development strategies, thereby achieving CO₂ reduction.

Scaffolding safety is a significant concern in the construction industry. To address this, researchers have proposed various safety monitoring approaches. However, current intelligent monitoring systems fall short of fully integrating real-time data, and predictive capabilities, reducing their overall effectiveness in ensuring scaffolding safety. Therefore, this study aims to develop a conceptual framework to advance the intelligent scaffolding monitoring system based on cyber-physical systems (CPS) and digital twins (DT) integration. The framework focuses on developing a DT-enabled scaffolding risk assessment model (SRAM), a sensor-based real-time data collection system, and an intelligent cyber-physical scaffolding risk alert. This research provides essential insights for more accurate accident risk assessments, more efficient data collection system, and faster warning mechanisms for construction safety.

Policy measures are crucial for regulating collusive bidding and are integral to effective governance. However, current research lacks a comparative exploration of strategies to combat collusive bidding through policy. Therefore, this study aims to identify more effective countermeasures by examining policy variations between regions with low and high incidences of collusive bidding. Using Latent Dirichlet Allocation (LDA) topic modeling, the study extracts key themes from these policies, while qualitative analysis highlights differences in approaches. It underscores that integrating electronic and information technology into bidding systems significantly reduces collusive practices. While increasing penalties can deter collusive bidding, achieving desired impacts requires thorough investigation and vigilant oversight. Additionally, strengthening external supervision enhances control over such activities. This study identifies critical governance strategies for addressing collusive bidding and advocates further research into more effective methods within the construction sector.

Business communities in the construction market are becoming increasingly diverse, with a deepening impact on industrial development and enterprise competition. Despite many existing empirical studies on communities, they weaken competitive interactions and have limited applicability to the dynamic issues of community formation and evolution. To address the gaps identified in the literature on bidding competition dynamics, this study constructs a multi-agent system (MAS) model. This model is designed to simulate the formation of community-type rivalry in the construction market by incorporating key variables identified from empirical observations of bidding behavior. It also designs and runs two experiments focusing on the impact of overall market factors and enterprises’ own factors on the formation of an equilibrium state of community-type rivalry to explore the mechanism behind its formation. We find that the density of community networks and the process of community formation are significantly affected by the number of enterprises, the scope of competition among enterprises, and the lifespan of the link, while they are not significantly affected by the size of the market or the exit thresholds of enterprises. In addition, this study finds that, under the bidding competition rule, the number of times that an enterprise bids is closely related to its network location advantage. However, larger and more mature enterprises have difficulty in maintaining a central position in a competitive network. This study provides different perspectives for an understanding of corporate community formation and offers valuable insights into the governance of community phenomena in the construction market.