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The cumulative length of subways and tunnels in China has reached nearly 25 000 kilometers, bringing huge demand for underground construction. The monitoring for construction safety has become more significant, due to complicated environment and rapid-onset natural disasters, which raises the frequency of accidents in underground construction. The informatization engineering of monitoring and early-warning on natural disasters is built to achieve construction safety, through promoting integrated monitoring on multi-hazard and disaster chains, and practicing intelligent algorithms on comprehensive quick accurate perception and early-warning of construction hazards. The integrated network architecture for intelligent safety monitoring with edge-computing ability is established, realizing the visualization of monitoring data analysis through researches on AD hoc transmission based on directional antenna network bridge, development of IoT edge computing software and researches on accessing to IoT platform for multiple types of sensors, and development of the front-end and back-end of the monitoring system. The introduction of IoT and cloud computing sustains accessing to platform for huge amount of sensors and full exploiting of big-data mining, improving intelligent safety hazard identification, and reducing safety risks in construction. Based on the instant response of edge devices and interval data acquisition of sensors, and the capability for more than 100 000 sensors to access the system simultaneously, the complete monitoring system for underground constructions with second-level warning is established. [ABSTRACT FROM AUTHOR]

Construction safety is of significance since construction accidents can result in loss of property and large numbers of casualties. This research aims to identify the critical causes of construction accidents by introducing a hybrid approach. The hybrid approach is developed to identify the critical causes of construction accidents by combining the human factors analysis and classification system (HFACS) model with complex network (CN) theory. A total of 863 construction accident cases were collected, and 46 causal factors were identified. Subsequently, the accident causal network was established, and six critical causal factors were extracted. The hybrid analysis approach is demonstrated with a real construction accident case, and the results demonstrate that the hybrid approach could better identify the critical causal factors. Consequently, this research enables the enhancement of understanding the HFACS framework and CN theory, as well as a contribution to safety management in the construction industry at different levels. [ABSTRACT FROM AUTHOR]

The complexity of the wharf components and the harshness of the offshore construction environment increase the safety risk of hazards, which has highlighted the importance and urgency of safety risk management in high-pile wharf constructions. This paper established a visualized digital construction safety risk model for high-pile wharf based on a so-called FAHP method (the combination of fuzzy comprehensive evaluation (FCE) and analytic hierarchy process (AHP) methods). The construction safety risk indicators were constructed as the target layer, the principle layer and the scheme layer, and then the corresponding safety risk assessment algorithm was established. The physical, functional and safety risk assessment parameters of the component in the BIM model were employed to the safety risk assessment algorithm, and the risk assessment level of each sub-process was subsequently classified. The case study indicated that the high-pile wharf construction project included five elements in principle layer and 15 risk indicators in the scheme layer. Moreover, it was demonstrated that the sub-processes with the highest construction risk level were steel pipe pile sinking in wharf construction and steel pipe pile, steel sheath-immersed pile sinking and embedded rock pile construction in approaches to bridge construction with a risk level of III. In this way, the quantitative visualization of the construction safety risk was effectively realized, which facilitates the safety risk management of construction sites and timely warning and response to unexpected safety accidents. [ABSTRACT FROM AUTHOR]

Purpose: Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety. Design/methodology/approach: A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China. Findings: The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations. Originality/value: This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management. [ABSTRACT FROM AUTHOR]

Ensuring safety is crucial for promoting the sustainable growth of the construction industry. Assessing safety efficiency is of significant importance for optimizing safety management processes and improving the safety environment. However, the current mainstream methods for evaluating safety efficiency have limitations such as ignoring non-desired outputs and slack variables, the efficiency values being limited to the (0, 1) range, and a narrow perspective. To address these shortcomings, this study focuses on the characteristics of the construction industry and introduces the Super-SBM model and Malmquist index into the assessment of safety efficiency in the construction industry. The study analyzes the evolution characteristics of safety efficiency from both static and dynamic perspectives. Furthermore, using panel quantile regression models, the study identifies the factors influencing safety efficiency and analyzes their heterogeneity. Analyzing panel data from 30 provinces in China from 2015 to 2021, the results show that the overall safety efficiency of the construction industry in China is relatively low, with noticeable spatial clustering characteristics. Provinces in the eastern and central regions exhibit higher levels of construction safety efficiency. The Malmquist index demonstrates a declining trend, with technical efficiency being the primary factor limiting the improvement of safety efficiency in construction. Factors such as per capita GDP, urbanization rate, committed contract amounts, and the number of professionals engaged in survey and design, as well as engineering supervision, have an impact on construction safety efficiency, and the effects of these variables vary across different quantile levels of safety efficiency. This research can assist decision-makers in gaining a better understanding of the safety conditions in different regions of the construction industry. It can also assist in developing customized policies to enhance the health and safety environment, thereby promoting the stable development of the construction industry. [ABSTRACT FROM AUTHOR]

The current body of literature indicates that the utilization of emerging digital safety technologies has the potential to enhance the efficacy of safety management in construction significantly. Nevertheless, there has been limited uptake of digital safety technologies within the construction industry in developing countries. This study is focused on evaluating the adoption of digital safety technologies in construction specifically from the perspective of developing countries. Questionnaire data were gathered from project management professionals in China and subjected to analysis using mean ratings, factor analysis, and fuzzy composite evaluation. The developed model for assessing safety technology adoption comprises four primary criterion groups about factors influencing adoption, namely organizational, technological, individual, and external categories. The study results indicate that factors within the technology category exert the most significant influence on the adoption assessment model, followed by those in the external and organizational categories, and finally by individual category factors. These findings contribute to advancing the theory of digital technology adoption in construction safety management research within developing countries. Practitioners can utilize this information to effectively evaluate and compare success rates of safety technology adoption, thereby informing management decisions required for projects. The insights provided by this study will equip practitioners with scientific knowledge for more effective and sustainable program management, ultimately enhancing the success of safety technologies., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Clarifying the causes of subway construction accidents has an important impact on reducing the probability of accidents and protecting workers' lives and public property to a greater extent. A total of 138 investigation records of subway construction accidents from 2000 to 2020 were collected in this study. Based on a systemic analysis of 29 well-known accident causation models and the formative process of the subway construction accidents, we extracted the causative factors of subway construction accidents from the collected records. Furthermore, a causation analysis index system of subway accidents was proposed based on fault tree analysis (FTA), where we considered subway construction accidents as the top event and the five dimensions, i.e., human, equipment, environment, management, and safety culture, as first-level intermediate events. Moreover, 17 causative factors were considered to be related to the severity of subway construction accidents. It is found that human factors are prone to be critical to high-risk accidents. Finally, a Bayesian network (BN) was formed to explore the causative factors of high-risk subway construction accidents. Based on the combined application of FTA and BN, this study discusses the complex influence factors and their action routes to unsafe accidents in subway construction sites, and makes efforts to correspond safety decision basis for the management of China subway construction. [ABSTRACT FROM AUTHOR]

China has seen a rapid increase in its construction industry in recent years; however, safety conditions of their workers have not improved owing to low education levels and increasing age trend of construction personnel. This study analyzed construction occupations in China from 2010 to 2018 using descriptive analysis, ANOVA and factor analysis. The results showed May, July and August as the deadliest months during the peak of construction activities in the year. No particular day was established as having a higher risk than other days in the week. The most vulnerable times of the day are from 9 AM to 10 AM and 2 PM to 4 PM. A mathematic modeling based on factor analysis, which is the construction safety evaluation score equation, was developed to illustrate regional distribution, and Qinghai Province ranked the worst in construction safety in China. Problems such as poor labor and environment safety management procedures and false reporting or concealed reporting of construction accidents were revealed. Suggestions for improving China's construction safety were also generated. This study enriched statistical analysis results of construction accidents in China and evaluation modeling with an abundant database will serve as a reference for stakeholders and researchers to improve the construction safety situation in China. [ABSTRACT FROM AUTHOR]

A fall-from-height accident is considered a major leading cause of construction fatalities. The analysis of accident characteristics could offer effective guidance to the construction industry to prevent falls from heights. By using accident statistical analysis and typical case investigation, this study indicates the basic pattern and reviews in detail the conditions of a fall-from-height incident in China. The result shows that more fatal fall-from-height accidents occur from 10 a.m. to 11 a.m. and 3 p.m. to 4 p.m. Accidents on weekdays are nearly as many as on weekends. The lowest incidence month is February. Accidents resulting in one death take most of the total. Furthermore, not fastening a safety belt is among the leading reasons workers die after falling from heights. Victims in fall-from-height accidents are mostly male workers. Fall heights are most often less than 15 meters. This study serves to alert construction safety policymakers to diagnose the current state of fallfrom-height accidents and provides a targeted direction for improving the safety record of work at height. [ABSTRACT FROM AUTHOR]

Performance evaluation in construction safety is of great importance to further improve upon safety management processes. This paper develops a data envelopment analysis (DEA) based framework to evaluate the construction safety performance at the macro level. The core of the method is to compare the output-input ratio of construction safety. Using the building practitioner, construction machinery and equipment, and construction area as the inputs, and value added of construction and death toll as the outputs, safety performance score is computed for the China's provincial construction industries from 2009 to 2017. The results show that the number of benchmark provinces every year is between five and seven. The gap between the best-performing and underperforming province was relatively small in 2012 and big in 2014. Beijing, Qinghai, Hainan, Fujian, Chongqing, and Tianjin can be utilized as role models for the provinces that need to improve their performance in construction safety. The eastern region has the highest score in construction safety performance, followed by the western and central region. This study provides an effective solution to solve performance issue in regional construction safety and improves the tradition performance evaluation system to a certain extent. [ABSTRACT FROM AUTHOR]

Purpose: Although research on prefabricated construction has gained increasing attention in recent years, limited efforts have been devoted to investigating safety issues in the off-site manufacture, especially workers' behavioral intentions to work safely. Thus, research is needed to identify the motivational factors determining off-site construction workers' safety behaviors. The purpose of this paper is to investigate workers' safety behavior by examining the determinants of behavioral intention in the off-site manufacturing plants in China. Design/methodology/approach: Theory of planned behavior (TPB) was modified and used in this study to explain how the elements in the hypothesized model interact. Data were collected using a questionnaire. Structural equation modeling technique with partial least-squares estimation was used to analyze the data collected. Findings: The findings of this study indicated that workers' tendency to engage in safety behavior is positively related to attitude toward the behavior, subjective norm, perceived behavioral control and behavioral habit, among which attitude toward the behavior and behavioral habit have most significant influences on safety behavior. This finding provides a better explanation on the pathways and the impacts of the crucial factors on the safety behaviors for the off-site manufacture. Originality/value: The possible innovation of this research lies in its attempt to understand the antecedents of workers' safety behavior in the off-site construction environment, which may make original contributions to construction safety research and practice. The findings of this study contribute to the body of knowledge in TPB. Corresponding countermeasures are put forward in order to improve workers' safety behavior in off-site construction. [ABSTRACT FROM AUTHOR]

• The impact of technology heterogeneity on safety performance of the construction industry were analyzed. • Safety performance of China's provincial construction industry were calculated by a two-hierarchy frontier DEA approach. • The strategies to improve safety performance in China's provincial construction industry were developed. • This study expands the boundary of construction safety knowledge into a macro level. The technology heterogeneity in the construction industry causes difficulties for an unbiased evaluation of safety performance. The non-parametric and two-hierarchy frontier data envelopment analysis (DEA) model was constructed according to the inputs and outputs of China's provincial construction industry in 2017. Safety performance and its potential as well as undesirable output potential were analyzed from the aspect of technology gap and management efficiency. The results showed that the average safety performance in China's provincial construction industry was calculated to be 0.715, which was caused by technology gap and management efficiency. Northwest China has good performance in technology gap ratio and Central China performs well in management efficiency. Meanwhile, the strategies to improve safety performance in China's provincial construction industry were developed. In addition, potential of the safety technology gap and safety management efficiency took up 70.18% and 29.82% in terms of the undesirable output control. East, Central, South and Southwest China are the main areas needing to strengthen accident prevention practice. The findings can be used to help scholars understand the condition of safety performance in China's provincial construction industry, and provide guidelines to evaluate the performance in construction safety considering production technology heterogeneity. [ABSTRACT FROM AUTHOR]

Globalization facilitated the development of international construction. Construction safety issues have become a global problem. International construction projects lead to complexities and difficulties in safety management given the involvement of participants from different countries and regions. This study takes case of Chinese international contractors to explore and evaluate the difficulties of implementing safety practices in international construction projects. Mixed methods include qualitative (i.e., document analysis and structured interview) and quantitative methods (i.e., Delphi survey) were adopted. The most important difficulties of implementing safety practices in international construction projects identified in this study were labor-only subcontracting and complex labor structure, low safety awareness of local workers, high turnover rates of frontline workers, and the failure of Chinese workers who work far from home to adapt to a boring lifestyle in overseas projects. Eliminating these major difficulties can facilitate the implementation of safety practices in international construction projects and further improve safety performance. [ABSTRACT FROM AUTHOR]

Despite the fact that lean construction (LC) has been shown to improve construction safety, little research has been conducted to investigate how LC technologies could be applied to safety management. This study aimed to close the gap by developing a safety planning and control (SPC) process based on LC technologies and evaluating it using structural equation modeling. The process was based on the last planner system (LPS) research framework and consisted of four sub-systems (i.e., the analysis layer, the planning layer, the control layer, and the performance layer). Data was gathered from 300 Chinese construction projects. The findings will serve as a guide for construction stakeholders looking to improve the efficiency of safety management by incorporating some LC technologies into the SPC process. And the four sub-systems work together to create a positive circulation system that aids in the long-term improvement of construction safety management. [ABSTRACT FROM AUTHOR]

This paper presents a systematic approach that incorporates structural equation modeling (SEM) and exploratory factor analysis (EFA) to perceive and verify causal-relationships and interactions between enablers and goals of construction workers' safety behaviors (CWSB). A sample of 450 questionnaire surveys regarding CWSB was collected from construction workers in several Chinese construction companies. EFAwas used to extract eight common factors in order to identify the model structure among 28 questionnaire items. Then, SEM was employed to investigate the interrelationships among variables in the hypothesized safety behavior model. The built causal model was verified in terms of the hypothesis test and goodness-of-fit test. The impact of the path coefficient on CWSB was investigated and analyzed in detail. Results indicate that management-oriented supervision and system (F3) and leadership (F8) exert obvious positive impacts on CWSB in accordance with the path coefficients analysis, whereas psychological workers' condition (F5) and workplace conditions (F6) exert obvious negative influences. Individual differences among workers (F2) do not perform statistically significantly with workers' safety behaviors. The developed approach is capable of revealing causal-relationships, testing hypothesized models, and determining leading factors in complex project environments. This research provides insights into cause-effect relationships among the workers' perceived influential factors and goals, and the results can be used to understand the factors that the construction workers perceive as important factors in safety behaviors. This can further provide decision support on the improvement of construction safety performance in the context of the Chinese construction industry. [ABSTRACT FROM AUTHOR]

The flexible wooden boards are still being used on the scaffolds at some construction worksites in China. We examined if the board dimension, acclimation phase and construction work experience influence workers' walking strategies on these boards. Among the 40 construction workers recruited, half of them had more than 1 year of construction work experience. The participants' body sway and the gait adjustments were captured and analysed. Our analysis showed the width and thickness of the boards had significant effects on walking speed. There is a significant interaction between construction experience and board width on stride width, whereas the interaction between construction experience and acclimation phase affects step length and walking speed. The body sway at the C6/C7 and L5/S1 locations are significantly affected by most of the factors. We also found that once the participants acclimated to the board condition, the sway variability increased. Practitioner Summary:This study investigated gait and postural adjustments of workers with different construction experience while walking over wooden scaffold boards, which is one of the activities highly associated with falling accidents in China. [ABSTRACT FROM AUTHOR]

Abstract: The prevention of fall from height accidents has long been a popular topic in the field of construction safety. Previous research has indicated one of the potential hazards was induced by the use of steel bracket as scaffold support. While researchers are focusing to improve the existing scaffolding system, this research introduces a newly developed device to minimize fall accidents. The working platform, namely Rapid Demountable Platform (RDP) can be applied across window frames without fixing anchor bolts. Emphasizing on the rapid installation/dismantling, the RDP provides another safer option for working at height. The development of the RDP has incorporated modular concept and aesthetic factor into the design, achieving a more user-friendly platform. Although the RDP is not intended to totally replace the traditional bamboo truss-out scaffold, it is designed to act as an alternative or a supplement to the existing bamboo truss-out scaffold. The RDP is the first of this kind to minimize fall from height accidents especially in cities similar to Hong Kong where external working at height is frequently encountered. [Copyright &y& Elsevier]

Abstract: This study unveils causes of accidents in repair, maintenance, alteration and addition (RMAA) work. RMAA work is playing an increasingly important role in developed societies, including Hong Kong. Safety problems associated with RMAA work in Hong Kong has reached an alarming level. In view of rapid expansion of the RMAA sector and rising proportion of accidents in the construction industry, there is a pressing need to investigate causes of RMAA accidents. Structured interviews were conducted with RMAA contractors to explore causes of accidents in the RMAA sector. A two-round Delphi method with 13 safety experts was subsequently employed to verify the interview findings and rank the relative degree of importance for various causes of accidents. Accidents happen in RMAA work due to intersection of reasons. One of the root causes of accidents in RMAA works is low safety awareness of RMAA workers; however, wider organizational and industrial factors are not negligible. This study sheds light on why accidents happen in the RMAA sector. Only when the factors leading to accidents are identified can effective measures be made. [Copyright &y& Elsevier]

Abstract: The construction industry in China has relatively high fatality and injury rates, and traditional practices for construction safety are no longer sufficient to meet new challenges. Innovative strategies to reduce safety hazards and accidents are required to substantially improve current practices. An understanding of the influences of the construction safety climate and personal experience construction safety becomes critical before any effective measure can be established. By considering previous safety climate models, a Bayesian network (BN) based model is proposed, establishing a probabilistic relational network among causal factors, including safety climate factors and personal experience factors that have influences on human behavior pertinent to construction safety. It therefore provides a methodology to identify potential strategies for safety improvement. In this study, a survey involving more than 4700 employees at a large construction firm in China was applied to establish a BN. BN-based analysis demonstrated that the safety climate factors may have a more significant influence on an employee’s safety behavior than personal experience factors. A method to find a strategy by controlling one individual factor (or simple strategy) to improve safety behavior was then investigated. It was found that the simple strategy could be more effective when safety climate factors were properly controlled. In addition, a strategy via controlling multiple factors (or joint strategies) may even better improve the safety behavior. The analysis suggested that a joint control of both safety climate factors and personal experience factors worked most effectively. Finally, the prediction of human safety behavior under a specific climate was tested with the BN. [Copyright &y& Elsevier]

To explore the relations between the number of accident deaths (NCD) and various factors in construction safety, a multiple linear regression model was established, based on the panel data of economy, construction labor, and the number of accident deaths in 31 provinces (regions) of China from 2009 to 2018. The results show that the average total profits and taxes (TPAT), and the death rate of ten thousand people (DR) are positively correlated with NCD, while the labor productivity (LP) is negatively correlated with it. Under the condition that other factors remain unchanged, NCD increases by 0.02 per a hundred million CNY. However, if DR increases by one ten thousand, NCD will increase by 8.66 on average. On the contrary, when LP increases by a hundred million CNY per ten thousand people, NCD decreases by 0.19. The model also predicts NCD in different provinces and cities from 2019 to 2020 with the method of quadratic exponential smoothing. As well, practice results show that the model is effective and practical., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

• Text mining can help identify safety risk factors from construction accident reports. • 37 safety risk factors were extracted from 221 metro construction accident reports. • Domain-specific lexicon was compiled for the construction accident analysis. • High-frequency terms were selected based on a tailored threshold. Workplace accidents in construction commonly cause fatal injury and fatality, resulting in economic loss and negative social impact. Analysing accident description reports helps identify typical construction safety risk factors, which then becomes part of the domain knowledge to guide safety management in the future. Currently, such practice relies on domain experts' judgment, which is subjective and time-consuming. This paper developed an improved approach to identify safety risk factors from a volume of construction accident reports using text mining (TM) technology. A TM framework was devised, and a workflow for building a tailored domain lexicon was established. An information entropy weighted term frequency (TF - H) was proposed for term-importance evaluation, and an accumulative TF - H was proposed for threshold division. A case study of metro construction projects in China was conducted. A list of 37 safety risk factors was extracted from 221 metro construction accident reports. The result shows that the proposed TF - H approach performs well to extract important factors from accident reports, solving the impact of different report lengths. Additionally, the obtained risk factors depict critical causes contributing most to metro construction accidents in China. Decision-makers and safety experts can use these factors and their importance degree while identifying safety factors for the project to be constructed. [ABSTRACT FROM AUTHOR]

There is a tendency for accidents and even fatalities to arise when people enter hazardous work areas during the construction of projects in urban areas. A limited amount of research has been devoted to developing vision-based proximity warning systems that can determine when people enter a hazardous area automatically. Such systems, however, are unable to identify specific hazards and the status of a piece of plant (e.g., excavator) in real-time. In this paper, we address this limitation and develop a real-time smart video surveillance system that can detect people and the status of plant (i.e. moving or stationary) in a hazardous area. The application of this approach is demonstrated during the construction of a mega-project, the Wuhan Rail Transit System in China. We reveal that our combination of computer vision and deep learning can accurately recognize people in a hazardous work area in real-time during the construction of transport projects. Our developed systems can provide instant feedback concerning unsafe behavior and thus enable appropriate actions to be put in place to prevent their re-occurrence. [ABSTRACT FROM AUTHOR]

Introduction . Navigated safety inspection based on task-specific checklists can increase the hazard detection rate, theoretically with interference from scene complexity. Visual clutter, a proxy of scene complexity, can theoretically impair visual search performance, but its impact on the effect of safety inspection performance remains to be explored for the optimization of navigated inspection. This research aims to explore whether the relationship between working memory and hazard detection rate is moderated by visual clutter. Methods . Based on a perceptive model of hazard detection, we: (a) developed a mathematical influence model for construction hazard detection; (b) designed an experiment to observe the performance of hazard detection rate with adjusted working memory under different levels of visual clutter, while using an eye-tracking device to observe participants' visual search processes; (c) utilized logistic regression to analyze the developed model under various visual clutter. Conclusion . The effect of a strengthened working memory on the detection rate through increased search efficiency is more apparent in high visual clutter. This study confirms the role of visual clutter in construction-navigated inspections, thus serving as a foundation for the optimization of inspection planning.

Purpose: Construction workers' reactions to safety-related issues during operation vary from person to person due to their different occupational levels, which can be attributed to various influencing factors and their correspondingly complicated interactions. This research aims to propose an integrated framework to combine the concepts of these factors and provide a holistic interpretation of the interrelationship among them. Methods: Based on items that were mainly extracted from competency theory, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to identify the critical factors from the data collected from 243 scaffolders on Wuhan Metro construction sites. The interactions among the identified factors were then analyzed, and the safety competency model was thus established with the use of structural equation modeling (SEM). Results: A total of 17 items were identified as critical to workers' safety competency, and these were further tested and attributed to four factors: (1) individual character and inclination; (2) self-adjustment and adaptability; (3) working attitudes; (4) safety-related operation qualification. Subsequent analysis showed that all the factors significantly contributed to one's safety competency, and individual character and inclination contributed most to the formation of one's ability, while the intermediating effects of self-adjustment and adaptability should not be neglected both in theoretical and practical terms. The resultant safety competency model consisting of these four factors was revealed to share a hierarchical structure with the classical competency model. Significance: This study provided an integrated theoretical framework and a set of modeling approaches to combine the related concepts and facilitate a greater understanding of construction safety in terms of workers' characteristics and behaviors. Practical implications: This study presented a tentative approach for assessing construction workers' safety competency, as well as emphasized to the managers and professionals the necessity of developing training systems to ensure workers are integrated into a crew in an appropriate and smooth manner. Limitations and Future Work: The volume and the scope of samples impeded the study from achieving a more generalized result and a more cost-efficient data collection approach is in need of development for a comprehensive and in-depth investigation.

This study aimed to reveal opinion leaders who could impact their coworkers' safety-related performance in Chinese construction teams. Questionnaires were distributed to 586 scaffolders in Wuhan to understand their opinions about influencing their coworkers, serving as the foundation for a social network analysis to identify the potential opinion leaders among workers. A further controlled trial with the identified workers was conducted to select real opinion leaders by comparing their influence on others' safety-related behavior, followed by an association analysis to profile these opinion leaders. Two main sources of opinion leaders were identified: foremen and seasoned workers. Implementing interventions through opinion leaders resulted in better safety-related behavior performance. Furthermore, compared with education level, the association analysis results indicated that one's practical skills and familiarity with respondents was more important in the formulation of opinion leaders. This research introduces the concept of opinion leaders into construction safety and proposes an approach to identify and validate opinion leaders within a crew, thus providing a tool to improve behavior promotion on sites, as well as a new perspective for viewing interactions among workers.

This paper presents a systematic Structural Equation Modeling (SEM) based approach for Prospective Safety Performance Evaluation (PSPE) on construction sites, with causal relationships and interactions between enablers and the goals of PSPE taken into account. According to a sample of 450 valid questionnaire surveys from 30 Chinese construction enterprises, a SEM model with 26 items included for PSPE in the context of Chinese construction industry is established and then verified through the goodness-of-fit test. Three typical types of construction enterprises, namely the state-owned enterprise, private enterprise and Sino-foreign joint venture, are selected as samples to measure the level of safety performance given the enterprise scale, ownership and business strategy are different. Results provide a full understanding of safety performance practice in the construction industry, and indicate that the level of overall safety performance situation on working sites is rated at least a level of III (Fair) or above. This phenomenon can be explained that the construction industry has gradually matured with the norms, and construction enterprises should improve the level of safety performance as not to be eliminated from the government-led construction industry. The differences existing in the safety performance practice regarding different construction enterprise categories are compared and analyzed according to evaluation results. This research provides insights into cause-effect relationships among safety performance factors and goals, which, in turn, can facilitate the improvement of high safety performance in the construction industry., (Copyright © 2015 Elsevier Ltd. All rights reserved.)