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New generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave differently when dealing with knowledge-related activities due to divergent characteristics caused by generational discrepancy. To provide a theoretical foundation for construction companies and safety managers to improve safety management, this research explores the factors and paths impacting the NGCWs' ability to share their safety knowledge.

Based on literature review, main factors that influence the safety knowledge sharing of the NGCWs were identified. Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling were applied to identify the hierarchical and contextual relations among the factors influencing the safety knowledge sharing of the NGCWs.

The results showed that sharing atmosphere ranked first in centrality and had a high degree of influence and being influenced, indicating itself an extremely important influencing factor of safety knowledge sharing of NGCWs. Six root influencing factors were identified, including individual characteristics, work pressure, sharing platform, incentive mechanism, leadership support and safety management system.

The number of influencing factors of safety knowledge sharing of the NGCWs identified in this study is limited, and the data obtained by the expert scoring method is subjective. In future studies, the model should be further developed and validated by incorporating experts from different fields to improve its integrity and applicability.

The influencing factors identified in this paper can provide a basis for construction companies and safety managers to improve productivity and safety management by taking relevant measures to promote safety knowledge sharing. The research contributes to the understanding knowledge management in the context of the emerging market. It helps to answer the question of how the market can maintain the economic growth success through effective knowledge management.

This paper investigates the influencing factors of NGCWs' safety knowledge sharing from the perspective of intergenerational differences, and the 13 influencing factor index system established expands the scope of research on factors influencing safety knowledge sharing among construction workers and fills the gap in safety knowledge sharing research on young construction workers. Furthermore, this paper establishes a multi-layer recursive structure model to clarify the influence path of the influencing factors and contributes to the understanding of safety knowledge sharing mechanism.

The purpose of this paper is to explore the correction mechanism of resilient safety culture on new generation of construction workers (NGCWs)' unsafe behavior and test the multiple mediation effects of job crafting and perceived work meaningfulness based on the context of Chinese construction industry in order to find a new way to effectively correct the NGCWs' unsafe behavior.

A theoretical model of correction mechanism was established based on literature research and theoretical deduction. An empirical study was employed based on confirmatory factor analysis and regression analysis with a sample of 404 NGCWs in China.

The results indicated that resilient safety culture can effectively correct NGCWs' unsafe behavior through job crafting and perceived work meaningfulness. Job crafting and perceived work meaningfulness can play independent and serial mediating roles between resilient safety culture and unsafe behavior.

Research results only represent a short-term law about the correction mechanism of NGCWs' unsafe behavior based on a questionnaire study from China's construction industry. It is necessary to continue to implement a longitudinal study to test it in a relatively long period in future research. The findings also need to be verified based on the young construction workers in other countries.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to correct NGCWs' unsafe behavior from the perspective of resilient safety culture. Furthermore, the construction of resilient safety culture in construction enterprises can help NGCWs better carry out job crafting and perceive the meaning of work.

This paper clarifies the correction mechanism of resilient safety culture on unsafe behavior of NGCWs, and further tests the independent mediating roles and a serial mediating role of job crafting and perceived work meaningfulness between resilient safety culture and unsafe behavior, which fills the research gap about the influence mechanism of resilient safety culture on young construction workers' unsafe behavior and enriches the theoretical system of unsafe behavior correction of construction workers.

The purpose of this paper is to explore the influence mechanism of job satisfaction and positive affect on knowledge sharing among project members in Chinese construction industry, and test the moderating role of organizational commitment between them in order to find a new approach from the perspective of psychology to improve the knowledge sharing performance within project management organizations in China constantly.

An empirical study was used based on confirmatory factor analysis and hierarchical regression analysis with a sample of 540 project members from 80 project management organizations in China.

Research results showed that job satisfaction and positive affect of project members both have a significant positive impact on knowledge sharing; organizational commitment could moderate the influence of job satisfaction and positive affect on knowledge sharing among project members partially within the Chinese context.

A questionnaire study from China only represents the relationship and regular pattern within a shorter time interval in the Chinese context. It is necessary to continue to implement a longitudinal study in a relatively long period in future research.

Knowledge sharing among project members can be enhanced through improving job satisfaction and positive affect, and strengthening project members’ organizational commitment can amplify the influence effect of job satisfaction and positive affect on knowledge sharing.

This paper clarifies the direct influence mechanism of project members’ job satisfaction and positive affect on explicit knowledge sharing (EKS) and tacit knowledge sharing (TKS), and further tests the partial moderating effect of organizational commitment on the influence relationship of job satisfaction and positive affect on EKS and TKS.

This paper aims to investigate the relationships between empowering leadership, basic psychological needs satisfaction, work-related well-being, and project citizenship behavior.

Drawing upon the self-determination theory (SDT), a conceptual model was developed and then empirically tested using a cross-sectional survey of 435 project members in Chinese construction projects.

The results fully support the research hypotheses proposed in the study, illustrating the positive impacts of empowering leadership on work-related well-being and project citizenship behavior, the mediating role of basic psychological needs satisfaction, and the positive association between work-related well-being and project citizenship behavior.

This research determines the utility of empowering leadership in the context of construction projects, especially in enhancing individual outcomes (i.e. work-related well-being and project citizenship behavior). Therefore, construction project managers can apply empowering leadership to meet the basic psychological needs of subordinates to increase project members' work-related well-being and project citizenship behavior.

To our knowledge, the present study first explores the micro-level impacts of empowering leadership in the construction context. Additionally, this study enriches the understanding of the mediating mechanism between empowering leadership and individual outcomes from a self-determination perspective.

The purpose of this paper is to figure out the paths about transformation of tacit knowledge into explicit knowledge, i.e. tacit knowledge explicating (TKE) in real estate companies, and determine the influencing factors of TKE in Chinese real estate companies to enable enterprises make better use of their knowledge resources.

The study adopted an exploratory design method using thematic analysis and grounded theory, and semi-structured interviews were conducted to collect data. The interviewees consisted of employees in different positions, who come from Chinese real estate companies with different ranking ranges and different knowledge management levels. Data collection was divided into two rounds for the identification of transformation paths and influencing factors.

This study has shown that 11 paths about TKE divided into solidified organization process and construction of organizational infrastructure go into effect within the real estate companies. Factors influencing TKE in real estate companies concern three main categories: organizational distal factors, contextual proximal factors and individual factors, including 21 subordinates in total. Furthermore, correlation between TKE paths and influencing factors is established.

Research results may lack generalizability due to the method adopted. Therefore, researchers are encouraged to verify the outcomes of this research.

This research provides a new idea and solutions for the tacit knowledge management in real estate companies.

To the best of the authors’ knowledge, this study is the first to systematically identify paths and the influencing factors of TKE in real estate companies, contribute to the incipient but growing understanding of achievement of “tacit to explicit” and enrich the corporate tacit knowledge management literature.

The purpose is to identify and evaluate the safety risk factors in the coal mine construction process.

The text mining technique was applied in the stage of safety risk factor identification. The association rules method was used to obtain associations with safety risk factors. Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretative Structural Modeling (ISM) were utilized to evaluate safety risk factors.

The results show that 18 safety risk factors are divided into 6 levels. There are 12 risk transmission paths in total. Meanwhile, unsafe behavior and equipment malfunction failure are the direct causes of accidents, and inadequate management system is the basic factor that determines the safety risk status.

Due to the limitation of the computational matrix workload, this article only categorizes numerous lexical items into 18 factors. Then, the workshop relied on a limited number of experts; thus, the findings may be potentially biased. Next, the accident report lacks a universal standard for compilation, and the use of text mining technique may be further optimized. Finally, since the data are all from China, subsequent cross-country studies should be considered.

The results can help China coal mine project managers to have a clear understanding of safety risks, efficiently carry out risk hazard identification work and take timely measures to cut off the path of transmission with risks identified in this study. This helps reduce the economic losses of coal mining enterprises, thus improving the safety standards of the entire coal mining industry and the national standards for coal mine safety policy formulation.

Coal mine construction projects are characterized by complexity and difficulties in construction. Current research on the identification and assessment of safety risk factors in coal mine construction is insufficient. This study combines objective and systematic research approaches. The findings contribute to the safety risk management of China coal mine construction projects by providing a basis for the development of safety measures.

The purpose of this study is to identify the causative factors of metro construction safety accidents, analyze the correlation between accidents and causative factors and assist in developing safety management strategies for improving safety performance in the context of the Chinese construction industry.

To achieve these objectives, 13 types and 48 causations were determined based on 274 construction safety accidents in China. Then, 204 cause-and-effect relationships among accidents and causations were identified based on data mining. Next, network theory was employed to develop and analyze the metro construction accident causation network (MCACN).

The topological characteristics of MCACN were obtained, it is both a small-world network and a scale-free network. Controlling critical causative factors can effectively control the occurrence of metro construction accidents. Degree centrality strategy is better than closeness centrality strategy and betweenness centrality strategy.

In practice, it is very difficult to quantitatively identify and determine the importance of different accidents and causative factors. The weights of nodes and edges are failed to be assigned when constructing MCACN.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to control construction risks and reduce safety accidents. More safety resources should be allocated to control critical risks. It is recommended that safety managers implement degree centrality strategy when making safety-related decisions.

This paper establishes the MCACN model based on data mining and network theory, identifies the properties and clarifies the mechanism of metro construction accidents and causations.

The COVID-19 pandemic has brought profound changes to all sectors of society including the construction sector. The main purpose of this study is to explore and provide insights into the impact and changes that have occurred in the construction sector due to COVID-19 and to present a mitigation framework to minimize the effects.

The scope of this study is limited to peer-reviewed articles in Scopus or Web of Science indexed journals. A systemized review was performed with bibliometric and content analyses of articles related to the impact of COVID-19 on the construction sector.

Through content analysis, the main topics discussed in the selected articles were grouped into 10 categories. Most of these studies were found to have focused on the challenges, impact, and health and safety at construction sites resulting from the pandemic. The study further identified 39 subtopics through detailed content analysis and organizes them into the categories of negative impacts, positive impacts and opportunities and barriers to COVID-19 safety guidelines in the construction sector. Moreover, the study developed a systematic mitigation strategy based on the recommendations of the literature review to reduce the impact of the current pandemic on the construction sector. The mitigation strategy presents separate set of measures regarding safety guidelines, process improvements, government intervention, psychological support and technology adoption.

The research insights provided in this study are useful for practitioners in guiding them to design effective strategies for addressing the challenges of the COVID-19 pandemic and future crises. Furthermore, a systematic presentation of the impacts, challenges and mitigation measures in this study will help researchers to identify existing gaps in the literature and explore other aspects of the impact of the pandemic on the construction sector.

The purpose of this paper is to present a novel five‐electrode electrochemical corrosion sensor. Health degradation by the corrosion of steel in civil engineering is a persistent problem. Structural health monitoring (SHM) techniques, including embedded sensors, can greatly improve the quantification of the steel corrosion information, which can lead to promote assessments of structural safety and serviceability. To integrate the corrosion monitoring system in future, the corrosion sensor and the monitoring methods have been explored here in advance. Also, the corrosion monitoring system has been applied preliminarily in the investigation of reinforcing concrete (RC) beams.

First, a novel five‐electrode electrochemical corrosion sensor has been developed as the hardware to provide the platform for corrosion monitoring methods. Second, half‐cell potential of the RC beams has been measured before and after corrosion. Third, galvanostatic step method has been used to excite the steel‐concrete system, and the transient response of the system has been obtained and analyzed. Finally, wavelet transform algorithm has been established to analyze the electrochemical noise (EN) data of the steel bars in RC beams.

The results show that the corrosion sensor can be used effectively as the hardware to support the electrochemical measuring techniques. Much valuable information which is extracted by analyzing the potential response to the galvanostatic pulse excitation can be applied to determine the general corrosion state of the reinforcing steel. For pitting corrosion, the energy distribution plot of EN can be adopted as a benchmark method to identify the presence of the corrosion pit.

The paper provides the key techniques for a SHM system to realize corrosion monitoring of large‐scale RC structures in the future.

The assembly simulation in tolerance analysis is one of the most important steps for the tolerance design of mechanical products. However, most assembly simulation methods are based on the rigid body assumption, and those assembly simulation methods considering deformation have a poor efficiency. This paper aims to propose a novel efficient and precise tolerance analysis method based on stable contact to improve the efficiency and reliability of assembly deformation simulation.

The proposed method comprehensively considers the initial rigid assembly state, the assembly deformation and the stability examination of assembly simulation to improve the reliability of tolerance analysis results. The assembly deformation of mating surfaces was first calculated based on the boundary element method with optimal initial assembly state, then the stability of assembly simulation results was assessed by the density-based spatial clustering of applications with noise algorithm to improve the reliability of tolerance analysis. Finally, combining the small displacement torsor theory, the tolerance scheme was statistically analyzed based on sufficient samples.

A case study of a guide rail model demonstrated the efficiency and effectiveness of the proposed method.

The present study only considered the form error when generating the skin model shape, and the waviness and the roughness of the matching surface were not considered.

To the best of the authors’ knowledge, the proposed method is original in the assembly simulation considering stable contact, which can effectively ensure the reliability of the assembly simulation while taking into account the computational efficiency.