Measuring the Construction Project Resilience from the Perspective of Employee Behaviors

Rational resistance amidst gentle breeze and mild rain: Examining online collective behavior among the Chinese public using the elaborated social identity model

This research examines internet collective behavior in mainland China during the COVID-19 pandemic, focusing on the factors and characteristics that drive such behavior. The Chinese government initially implemented a conservative and biased policy to contain the spread of the virus, but the sudden lifting of lockdown measures in late 2022 resulted in a surge in infections and scarcity of medical resources. This policy shift led many Chinese internet users to perceive the government's actions as hasty and harsh, prompting them to engage in collective online behavior. The study employed a survey-based approach, collecting 1,626 valid questionnaires, which underwent reliability testing, descriptive statistical analysis, and a difference-in-differences test. A structural equation model (SEM) was then constructed and applied to comprehensively analyze the mediating and moderating effects of latent variables. Ethical considerations were prioritized, with informed consent obtained from all participants, who were provided with detailed information about the study and given sufficient time to review and ask questions. The research yielded three primary conclusions: the Chinese public demonstrated a perception of fairness and exhibited obedience, respect, and cooperation with the government during the epidemic; the observed online collective behavior can be characterized as a moderate and rational form of resistance, explained by the elaborated social identity model (ESIM); and the middle class consistently adopted a self-vulnerability strategy, positioning themselves as beneficiaries of protection to maximize their own interests in epidemic prevention and control. This study shows notable insights into internet collective behavior in mainland China during the COVID-19 pandemic, highlighting perceptions, resistance, and strategies adopted by different segments of the population.

Scientometric Analysis and AHP for Hierarchizing Criteria Affecting Construction Equipment Operators’ Performance

The construction sector constitutes a significant indicator of a country’s economic growth. Construction equipment is an integral part of every construction project, and its contribution during construction determines any project’s completion. It also represents a significant capital investment for companies in this sector. A major strategic goal for such companies is the increase in the equipment’s productivity, which is affected mostly by its operators. The aim of this research is to recognize and prioritize the criteria affecting the performance of construction equipment operators. Scientometric analysis, using VOSViewer software, was implemented for the formation of different kinds of bibliometric networks, proposing a holistic approach to this research field. Those networks delineated the field with regard to construction equipment operators and revealed the correlations between the network’s items, which were formed because of previous research, and finally, conclusions were drawn. An extensive literature review in conjunction with structured interviews with experts and operators determined the factors affecting the operators’ performance, with a view to creating a hybrid decision model based on the Analytical Hierarchy Process (AHP), as implemented by the Transparent Choice tool. Many experts evaluated the criteria affecting the operators’ performance, leading to remarkable conclusions. Moreover, a few pointers for future research are provided.

Is Resilient Transportation Infrastructure Low-Carbon? Evidence from High-Speed Railway Projects in China

Establishing resilient transport infrastructure is an effective way for cities to deal with external disturbances and uncertainties during rapid urbanization. However, human society is presently facing a series of sustainable development obstacles, where the energy shortage and environmental pollution are catching significant concerns. Hence, it is imperative to investigate the carbon emission of the growing number of resilient transportation infrastructure (RTI) projects. Through extracting the carbon emission factor (CEF), this study built the carbon emission measurement model (CEMM) to evaluate the carbon emission of 26 resilient high-speed railway construction projects in China. The results indicated that the carbon emissions of the entire high-speed railway infrastructure projects in China show regional and social environmental differences. Meanwhile, there are potential correlations and positive relationships between the resilience of the high-speed railway infrastructure projects and their carbon emission. Suggestions and recommendations for governments and construction enterprises are put forward to further improve the resilient and low-carbon development of transportation infrastructure in China.