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The main purpose of this study is to identify the dimensions of hotel employees’ job risk perceptions and develop a measurement scale for this construct.

Four studies using a mixed-method design were conducted to develop and validate the scale of hotel employees’ perceived job risk (HEPJR). Study 1 identified the dimensions and initial items of HEPJR through a literature review and in-depth interviews. In Study 2, an explanatory factor analysis was perform to refine the preliminary items. Study 3 further refined the HEPJR scale through a confirmatory factor analysis. Study 4 confirmed that HEPJR is a 19-item scale through a cross-validation analysis.

A reliable and valid scale was developed to measure the following five dimensions of HEPJR: perceived human, equipment, internal environment, external environment and management risks. HEPJR and its dimensions significantly predict negative safety consequences and negative job satisfaction.

Employees in medium- and high-star-rated hotels in China were surveyed. Future research should test the HEPJR scale in other types of lodging formats (e.g. budget hotels, homestays and cruise ships) and different countries or regions.

Given the increasingly serious job risks faced by hotel employees, the HEPJR scale can become a benchmark for job risk identification, accident prevention and safety management.

This scale provides a clear conceptualization and an appropriate measurement tool of HEPJR from a risk-source perspective.

Despite the established significance of underlying accident causes to health and safety (H&S), and the persistent reporting of the underlying accident causal influence of construction project features (CPFs) which emanate from pre-construction decisions, no empirical research has focused on CPFs in terms of assessing their degree of potential to influence accident occurrence. The purpose of this paper is to, therefore, investigate this facet of the accident causal influence of CPFs.

A mixed method design was used involving semi-structured interviews, and a questionnaire survey of UK construction professionals.

CPFs generally have a moderate or a high potential to influence accident occurrence, implying a fair or severe potential to cause harm in terms of the H&S of workers. The degree of potential of CPFs to influence accident occurrence is influenced by: the extent to which certain proximate causes of accidents are common/prevalent within CPFs;and the degree of potential of those proximate causes to influence accident occurrence.

These findings provide insight into the H&S consequences of CPFs, awareness of which is essential if pre-construction project participants are to implement appropriate risk control measures especially in the early phases of projects to mitigate the accident causal influence of CPFs. The findings reinforce the contribution of clients and their design and project management teams to accident causation, the significance of the early planning of H&S in construction project delivery, and the importance of driving mechanisms such as the Construction (Design and Management) Regulations 2007.

The purpose of this paper was to map the safety management research of construction industry by scientometric analysis, which can predict important highlights and future research directions of safety management research in the construction industry. As an important issue in the construction industry, safety management issues have been researched from different perspectives. Although previous studies make knowledge contributions to the safety management research of construction industry, there are still huge obstacles to distinguish the comprehensive knowledge map of safety management research in the construction industry.

This study applies three scientometric analysis methods, collaboration network analysis, co-occurrence network analysis and cocitation network analysis, to the safety management research of construction industry. 5,406 articles were retrieved from the core collection database of the Web of Science. CiteSpace was used for constructing a comprehensive analysis framework to analyze and visualize the safety management research of construction industry. According to integrating the analysis results, a knowledge map for the safety management research of construction industry can be constructed.

The analysis results revealed the academic communities, key research topics and knowledge body of safety management research in the construction industry. The evolution paths of safety management research in the construction industry were divided into three development stages: “construction safety management”, “multi-objective safety management” and “comprehensive safety management”. Five research directions were predicted on the future safety management research of construction industry, including (1) comprehensive assessment indicators system; (2) intelligent safety management; (3) cross-organization collaboration of safety management; (4) multilevel safety behavior perception and (5) comparative analysis of safety climate.

The findings can reveal the overall status of safety management research in the construction industry and represent a high-quality knowledge body of safety management research in the construction industry that accurately reflects the comprehensive knowledge map on the safety management research of construction industry. The findings also predict important highlights and future research directions of safety management research in the construction industry, which will help researchers in the safety management research of construction industry for future collaboration and work.

Human error is among the leading causes of construction-based accidents. Previous studies on the factors affecting human error are rather vague from the perspective of complex and changeable working environments. The purpose of this paper is to develop a dynamic causal model of human errors to improve safety management in the construction industry. A theoretical model is developed and tested through a case study.

First, the authors defined the causal relationship between construction and human errors based on the cognitive reliability and error analysis method (CREAM). A dynamic Bayesian network (DBN) was then developed by connecting time-variant causal relationships of human errors. Next, prediction, sensitivity analysis and diagnostic analysis of DBN were applied to demonstrate the function of this model. Finally, a case study of elevator installation was presented to verify the feasibility and applicability of the proposed approach in a construction work environment.

The results of the proposed model were closer to those of practice than previous static models, and the features of the systematization and dynamics are more efficient in adapting toward increasingly complex and changeable environments.

This research integrated CREAM as the theoretical foundation for a novel time-variant causal model of human errors in construction. Practically, this model highlights the hazards that potentially trigger human error occurrences, facilitating the implementation of proactive safety strategy and safety measures in advance.

During the 1970s a number of countries, notably Britain, the United States, Sweden and West Germany, passed important new legislation in the area of workplace health and safety. One consequence of such legislation has been a substantial upsurge of research interest, on the part of both economists and behavioural scientists, in the area of workplace health and safety in the various countries concerned. As this body of research accumulates we are beginning to see the emergence of a number of findings common to various countries. In the case of industrial accidents, for example, it is now reasonably well established that (i) the high (low) accident rate industries in one year are the high (low) accident rate industries in other years; (ii) the overall accident rate bears a positive relationship to movements in the business cycle; (iii) the unionised section of the workforce is disproportionately employed in the high accident rate industries; and (iv) employees in the high accident rate industries receive at least some measure of wage compensation for bearing this above average risk.

Few of the established risk identification methods refer to low-severity yet high-frequency safety risks data that may lead to several safety risks being ignored, thus reducing the potential of learning from a considerable number of cases. The purpose of this study is to explore a new valid method based on preaccident safety supervision data to identify these minor construction safety risks during routine construction operations.

A total of 329 official construction safety supervision reports containing 5,159 safety problem records from Shanghai between 2016 and 2018 served as raw material for in-depth analysis. Given the characteristics of the data collected, text mining integrated with natural language processing was applied to review the supervision reports and group safety risks automatically.

This study clarifies the way in which the supervision data should be employed to analyze high-frequency–low-severity safety risks. From these data, seven unsafe-act-related and nine unsafe-condition-related risks are identified. Regarding unsafe-act-related risks, inappropriate human behaviors could usually occur in personnel management, contract management, expense management, material management and acceptance work. For unsafe-condition-related risks, hoisting, scaffolding and reinforcement works are the main generators of onsite safety hazards during construction operations.

The study includes implications for project managers and supervisors to facilitate more effective proactive risk management by paying more attention to collecting and employing the supervision data established in each routine inspection.

Whereas previous research focused on analyzing severe accidents, this study seeks to identify the high-frequency–low-severity construction safety risks using the preaccident supervision data. The findings could provide a new thought and research direction for construction safety risk management.

The purpose is to introduce a safety planning and control (SPC) model that has been integrated into the production planning and control process. The paper is concerned with the impact of this model on human error control, since both workers' and managers' errors are major contributing factors in accident causation.

The analysis of this impact was based on two stages: the analysis of the main types of human errors detected in five sites in which the model has been implemented and a discussion on how the model contributes to the design of safe work systems from a cognitive engineering perspective.

The main conclusion is that six elements of the model (safety planning, near miss reporting, training, percentage of safe work packages indicator, participatory cycle, and planning and control diffusion) contribute to make both the boundaries of safe work visible and respected. Safety planning also helps to make the production system error‐tolerant to some extent. However, the analysis of causes of safety failures in the empirical studies pointed out a high incidence of violations of the boundaries (on average, 43.5 percent of the total safety failures), mostly by workers.

Although improvement in the existing mechanisms might make the model more behavior‐oriented, a broader set of measures is necessary to achieve excellence in dealing with human errors. Also, additional empirical data are necessary to clarify the nature and frequency of the human errors that have impact in construction safety.

The model may help in devising more effective tools to reduce errors in construction.

This paper presents tools and equipment aspects of the results from a three‐year United Kingdom Government funded research project investigating accident causality (ConCA). The project has used focus groups and studied in detail 100 construction accidents site audits, interviews with involved persons and follow‐up along the causal chain. This paper concentrates on the influence of construction tools and equipment which were found to be important contributory factors identified by the research. They have largely been overlooked by previous studies and are not typically acknowledged as accident contributors. This paper argues for further work to confirm these links and for the inclusion of tools and equipment in the list of categories in statutory reporting procedures. This would also require an increased acknowledgement by construction managers of their influence, leading to better design and management of their supply and care on site.

Safety climate plays an important role in the high-risk construction industry. Advances have been made in the understanding of construction safety climate in terms of four interrelated themes, specifically, its definition, measurement, antecedents and consequences. However, knowledge remains fragmented as the studies are scattered, and a systematic review covering these four themes is lacking. To address this research gap, this study aims to perform a systematic literature review of construction safety climate literature regarding the four themes.

Following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol guidelines, 178 eligible articles were obtained. This study provided thematic analysis of the 178 papers to identify what is known and what is not yet fully known regarding the four themes of construction safety climate. This study also conducted a descriptive analysis to identify the influential scholars, keywords, theories and research methods used by the literature, and finally presented an integrative framework directing future research.

The literature has not reached a consensus on the definition and measurement of construction safety climate. While it has identified the impact of safety climate on both behavioral and accident consequences, it has paid less attention to the antecedents and their underlying mechanisms regarding safety climate. Fang D. and Lingard H. are identified as the most influential authors in this field. “Questionnaire” and “safety behavior” are the keywords most closely related to safety climate. Unfortunately, the existing evidence for the causal relationships between safety climate and its antecedents and consequences is weak, as many studies lack clear theoretical substance, use a concurrent research design and focus only on individual-level climate perceptions. Finally, to support the development of construction safety climate around the four themes, potential research directions and research methods supporting them are illustrated.

This review makes contributions by integrating existing construction studies covering its definition, measurement, antecedents and consequences. This review also makes contributions to specific themes: no review exists on the antecedents of construction safety climate, and this review fills that gap; with regard to consequences, the existing reviews focus either on safety outcomes or safety behavior, but this review included both of them and further elaborated the different theories underpinning the relationships between safety climate and them. It is hoped that this systematic review will be helpful to the research community toward developing a nomologic network and promoting knowledge integration with respect to construction safety climate.