Research Progress in Construction Workers’ Risk-Taking Behavior and Hotspot Analysis Based on CiteSpace Analysis

Abstract

With the continuous development of the global construction industry and urbanization, the accident rate in the construction industry has also been increasing year by year, with construction workers’ risk-taking behavior being an important factor. Therefore, effectively reducing the occurrence of construction workers’ risk-taking behavior and improving safety in the construction industry are of great significance to both academia and industry management. Based on the relevant literature on construction workers’ risk-taking behaviors published between 1 January 2012 and 28 August 2024, this study uses CiteSpace software to visualize and analyze the countries, institutions, authors, cited works, and keywords of 272 selected articles. It aims to analyze the development and current status of construction workers’ risk-taking behavior from multiple perspectives, reveal the research hotspots, and predict future development trends. The results of this study show that, firstly, the emergence of risk-taking behavior among construction workers is closely related to a variety of factors, such as work pressure, environmental factors, safety atmosphere, organizational culture, etc. Therefore, future research needs to further explore how to consider these factors comprehensively to understand the causes of risk-taking behaviors more comprehensively. Second, the research methods of risk-taking behaviors of construction workers are becoming increasingly diversified, and the means of research have shifted from a single empirical analysis to a comprehensive analysis, incorporating advanced equipment. Third, the focus of the research object has been gradually shifted from the traditional behavioral patterns of adolescents to the occupational groups, especially construction workers, which strengthens the safety management field. Fourth, the management mode is also gradually standardized, and the scope of future research can be extended to all stages of the occurrence of the behavior, and the methodology is more focused on precision and effectiveness. This study not only helps scholars to have a comprehensive understanding of the current state of research and the future direction of development in this field. It also provides valuable references for managers to improve safety management strategies in practice.

1. Introduction

The issue of safety in the construction industry has always been of great concern. Despite the government’s continuous introduction of industry standards and construction codes to guide construction operations, the incidence of accidents and the death rate in the construction industry remain high due to the improper assessment and handling of various risks by construction workers [1]. Statistically, the root cause of 90% of construction accidents is unsafe behavior [2,3], and risk-taking behavior is the main unsafe behavior [4]. Therefore, effectively reducing the occurrence of risk-taking behavior has become a common academic concern.

There are a variety of academic views and understandings of the concept of risk-taking behavior. Ma S S et al. (2021) [5] consider risk-taking as an unsafe behavior that can lead to accidents and injuries. Hasanzadeh et al. (2020) [6] argued that risk-taking behavior is bolder or riskier behavior when there is a perceived decrease in risk. Many other scholars have presented their views on this issue, and these scholars have developed a diverse conceptualization of risk-taking behavior, which further enriches the research perspectives.

In terms of research methodology, from the initial questionnaire survey to behavioral experiments to the application of virtual reality technology, researchers have begun to use more refined situational simulations to explore construction workers’ behavior [7]. These experiments are usually combined with a variety of advanced equipment that makes the research more rational and rigorous, thus reducing the influence of subjective factors. These include using wearable EEG and virtual reality to classify perceptions related to building hazards [8,9], comparing the effectiveness of safety training for novice and veteran construction workers using immersive virtual reality technology [10], evaluating the risky behaviors leading to construction workers’ falls using reinforced learning methods using virtual reality [11], and similar methods. Behavioral devices commonly used for experiments nowadays are electroencephalograms (EEG) [12,13,14], eye trackers [15,16,17,18], functional near-infrared spectroscopy (fNIRS) [19], virtual reality (VR) [11,20], and other devices. The research theme has also been increasingly refined, from purely exploring risk attitudes to a comprehensive examination of workers’ psychosocial factors, team dynamics, and work environments [21]. The theoretical framework has also been constantly updated, gradually developing from an early single behavioral model to a more diversified perspective. In terms of research objects, studies now focus not only on individual behavior but also on the interaction between individual and group behavior.

The present study was designed to summarize this area and aims to provide an overview of risk-taking behavior from multiple perspectives. This new approach is necessary because previous studies have not been able to adequately reveal the process of change in the content of the literature over the years, nor have they been able to provide more accurate predictions of these changes. For this reason, this paper uses CiteSpace literature data visualization software to collect a large number of publications. This approach reveals the evolution and distribution of publications in the study of risk-taking behavior, the knowledge base that has been developed, and topical issues. This paper uses this approach to summarize the current status and possible future trends. A theoretical reference is provided for future researchers and relevant policymakers. On this basis, future research directions are proposed.

The innovation of this paper lies in the following points: firstly, through the analysis of CiteSpace, this paper dynamically traces the development of key hotspots in the field and clarifies the development of the field using a timeline, which can help researchers understand the historical background of the theoretical development and predict the future research trend; secondly, this paper systematically analyzes the basic literature on risk-taking behaviors of construction workers, providing clear theoretical support for further research and helping scholars identify and cite high-value references. Secondly, this paper systematically compiles the basic literature on construction workers’ risk-taking behavior, providing clear theoretical support for further research and helping scholars to identify and cite high-value references. Furthermore, this paper explores the impact of different regional policies and management systems on construction workers’ risk-taking behaviors, providing a reference for safety management from a global perspective.

The sections of this paper are partially organized as follows. Section 2 explains the data sources and analytical methods of this study. Section 3 describes the literature identified in the review of this paper and its characteristics, including the number of publications, the number of authors, and the collaborative networks among national institutions represented in the literature. Section 4 analyzes the knowledge base of risk-taking behavior. Section 5 describes the research themes and how they have evolved. Finally, the paper concludes in Section 6 with a summary of its findings and directions for future research. It is important to note that this paper does not compare the many findings in this field of study; rather, the goal of this paper is to provide a clear picture of the current state of the field, how it is changing, and important areas.

2. Data Sources and Methods of Analysis

2.1. Data Sources and Screening

The Web of Science Core Collection (WSCC), a comprehensive and influential citation database of scientific and technological knowledge graphs, is considered to be an effective source of data retrieval for scientometric analyses. To increase the representativeness and accessibility of the data, this paper focuses on the Web of Science Core Collection database, using data collected between 1 January 2012 and 28 August 2024. This article is based on TS = (“construction workers*” OR “construction laborers*” OR “building workers*” OR “building laborers*”) AND (TS = (“Adventure*” OR “Risk*” OR “Risk-taking*”)) AND (TS = (“behavior*” OR “behavior*”)) as a search statement to guide the literature search, selecting articles in Document Types. By using the refinement function of the Web of Science classification, this paper excluded the literature published in unrelated fields. This paper then manually reviewed the titles of the remaining literature and removed irrelevant literature. Finally, 272 studies were selected for this paper.

The selected literature must meet the following criteria: firstly, the literature should focus on the study of risk-taking behaviors, including its current status and the factors influencing it; secondly, the focus of the literature should focus on risk-taking behaviors among construction workers.

2.2. Methods of Analysis

The main difference between analysis using CiteSpace and analysis using other search engines or traditional literature research lies in the analysis methods and perspectives. Search engines such as CiteSpace rely on visual analysis such as co-citation of literature and co-occurrence of keywords to help researchers reveal the trend of disciplinary development, research hotspots, and literature networks at the macro level, which is suitable for large-scale literature data analysis. The difference is that traditional research relies more on qualitative analysis, focusing on details and theoretical frameworks through in-depth analysis of a single piece of literature or a specific field, emphasizing the depth of individual research. The two can complement each other, with search engines such as CiteSpace providing a systematic view of trends in the discipline, while traditional research focuses on exploring specific issues and theories.

Given the large number of articles to review, it would be very difficult to extract the information manually, so this paper uses visual research tools to help extract the important information from the articles. Commonly used data analysis and visualization software are divided into two categories based on whether they can handle textual data, namely bibliometric analysis tools (including TDA, CiteSpace, VOSviewer, etc.) and social network analysis tools (including Netdraw, Gephi, Pajek, etc.). After reviewing the information, we found that CiteSpace is a visualization tool focused on scientific literature analysis, especially good at handling tasks such as clustering, emergent analysis, and the evolution of trends in the literature. It has the following advantages: first, it can draw all kinds of knowledge maps based on the literature. It also provides three kinds of mapping layouts: clustering, time series, and time zone. Secondly, it can combine bibliometric data relationships with social network analysis methods for good visualization. Compared with other tools, such as VOSviewer and Gephi, CiteSpace excels in bibliometric analysis and visualization performance but is slightly less effective in customizability and cross-domain application. VOSviewer is suitable for network graph construction, Gephi is more suitable for complex network analysis, while CiteSpace is more focused on the bibliometric data, providing a simpler and more efficient analysis process. Therefore, the advantages of CiteSpace in literature analysis are irreplaceable. Therefore, CiteSpace software version 6.3.R1 was chosen as the main tool for this paper as it provides a comprehensive analysis of all the literature.

This paper uses CiteSpace to explore the literature and collaborative networks on risk-taking behavior, the development of risk-taking behavior research, and the distribution and collaboration among countries, research institutions, and authors. This is achieved by setting the node type in the CiteSpace software to ‘co-author’, ‘institution’, and ‘country’. When the node type is set to ‘Cited Literature’, the paper can be analyzed for co-citations (in this paper, a co-citation is defined as a citation of article c in both article a and article b). Through co-citation analysis, this paper builds a knowledge base of research in the field and identifies the most important citations. Based on this, this paper conducts a series of dynamic analyses to observe the development of the topic. Using the clustering and co-occurrence of ‘keywords’, this paper identifies cutting-edge research and hotspots at different stages of development in the field. This paper generates an analysis graph by setting the node type ‘keyword’ and clustering the nodes in the keyword co-occurrence graph. In summary, this paper describes trends in risk-taking behavior and predicts future problems and breakthroughs that may require attention.

3. Analysis of the Current State of Research

3.1. Trends in the Number of Publications

This paper analyses 272 publications from 2012–2024 (Figure 1). The graph depicting the number of publications per year shows 3 distinct phases.

Articles published during the eight years from 2012 to 2019 account for 37.1% of the total. During this phase, no more than 20 papers were published per year. Although the research in this phase showed a slow growth trend and was not very productive each year, the definition of the risk-taking behavior of construction workers and the research methodology laid the theoretical foundations for subsequent research. Thus, these years represent what this paper calls the ‘preparatory’ phase of risk-taking behavior research.

From 2019 to 2022, the number of papers in the field of risk-taking behavior grows exponentially, reaching 10 times the number of papers published in 2012 by the end of this period, accounting for 51.1% of the papers published during the period covered by this paper, which is referred to in this paper as the ‘Rise’ of risk-taking behavior research.

From 2022 onwards, the study of risk-taking behavior enters what this paper calls a ‘decline’ phase. The number of articles in this phase accounted for about 37.8% of the total number of articles, which is similar to the first phase, but the number of articles in this phase showed a clear downward trend; for example, the number of articles reached 51 in 2022 but only 21 in 2024. It shows that the enthusiasm of scholars‘ research on construction workers’ risk-taking behavior began to slowly decrease after the booming development in the second stage. Nevertheless, risk-taking behavior became an active area of research for many scholars. In addition, a variety of research methods emerged during this period, and the research methodology slowly shifted from the previous empirical research to the method of researching with devices. Examples of such devices are EEG [22], eye trackers [23,24], functional near-infrared spectroscopy, virtual reality [25,26], and so on. For example, EEG was used to detect the attention and vigilance of construction workers [12], VR [27] was used to study the physiological state of construction workers under high altitudes [28], and so on. This method is more objective and rational compared to empirical studies, reducing subjective ideas.

3.2. Cooperation Network

By analyzing collaborative networks between countries and institutions, it is possible to identify international and institutional organizations that have published extensively and have had a significant impact on the field of risk-taking behavior of construction workers, and it is possible to detect collaborative relationships between them. After opening CiteSpace software, the researcher can select ‘Country’ and ‘Institution’, respectively, in the ‘Node Type’ option. Upon completion of the software run, CiteSpace will generate a network map of the country and institutional collaboration for the period 2012 to 2024. This paper found 251 organizations (number of nodes N = 251) from 49 countries (number of nodes N = 49) or territories participating in the study of risk-taking behavior (see Figure 2 and Figure 3). China (number of publication [Count] = 115) dominated the list, followed by USA (number of publication [Count] = 71), Australia (number of publication [Count] = 41), South Korea (number of publication [Count] = 13). There are the following research institutes that have studied the risk-taking behavior of construction workers more, including City University of Hongkong, Hongkong Polytechnic University, Chongqing University, Central South University, and so on. The degree of centrality is also important from the point of view of cooperative networks. Centrality denotes the strength of the number of connections a node has to other nodes throughout the network. High centrality denotes key nodes that have a strong influence on the relationships in the network. Australia has the highest degree of centrality (degree of centrality [Centr] = 0.77), followed by England (degree of centrality [Centr] = 0.51), and the USA (degree of centrality [Centr] = 0.49). In addition, these countries have close cooperation with other countries.

An analysis of the number of authors’ publications and collaborative networks in this paper shows that 201 authors are working on risk-taking behaviors (Figure 4), of whom 54 authors have published more than two papers and 15 authors have published more than three papers. Among these prolific scholars, Arcury, Thomas A., van der Beek, and Allard J were some of the first to start focusing on the field of risk-taking behavior of construction workers when he published his paper in 2012. The top two authors in terms of number of publications are Chan, Alan H S (Count = 5), Chan, and Alan Hoi Shou (Count = 5). There are also many scholars with Count = 4, namely Li Heng, Edwards, Peter, Chen Huihua, Govender, Rajen, Zhou Jianliang, Ahn, Changbum R, Duan, Pinsheng, Bowen, Paul, Goh, Yang Miang.

These scholars have made important contributions to the field of construction workers’ risk-taking behavior. The network of collaboration between academics appears more dispersed compared to the close network of collaboration between countries and institutions. Within these collaborative networks, several stable small-scale partnerships have emerged, signaling the gradual formation of collaborative networks. The establishment of these collaborative groups has promoted the diversification of research areas and resulted in both broad and in-depth academic discussions and cooperation.

4. Knowledge Base Analysis

4.1. Co-Citation Clustering

In this study, if two articles appear in one article at the same time, it means that these two articles have a co-citation relationship, and a higher frequency of co-citation, which in turn indicates that these two articles have a strong correlation. Co-citations can be used to identify core literature and research frontiers within a field, finding which papers are read and cited in risk-taking behavior. Based on the information CiteSpace extracted from the data, the 272 publications analyzed in this paper were cited in 6435 references. By clustering the cited publications to identify the top keyword clusters for each year (based on their frequency), this paper identifies 10 major clusters reflecting the knowledge base of research on risk-taking behavior (Figure 5).

The literature search showed that relevant papers were published as early as 2010. However, it was not until 2013 that there were enough publications to conduct a cluster analysis. The term “South Africa” first appeared in papers as early as 2010. The cited publications focus on the occurrence of risk-taking behaviors in different regions, and the keywords used in this cluster are fear of testing, human immunodeficiency, acquired immune deficiency syndrome, measurement scales, discrimination, etc. The finding that the very first studies of risk-taking behavior did not focus on construction workers gives us further insight into the frontiers of risk-taking behavior research. The keyword “safety behavior” formed the largest cluster and contained the most citations during the period 2012–2020, reflecting the importance of the research theme in the field. Keywords such as systems thinking, worker, situational safety violations, and system dynamics, are used in this cluster. The use of these keywords reflects a gradual shift towards the regulation and institutionalization of the management of safety behavior and a shift in thinking from a local and singular perspective to a more global and integrated analysis. At the same time, the way of thinking is increasingly considered in the context of the actual situation and not just at the theoretical level.

The “migrant worker” cluster has a long duration (2015–2024) and focuses on theoretical approaches such as training, computer vision, fuzzy inference, qualitative research, etc. The theoretical models of the commonly used methods are revealed to provide reference to the scholars behind them. The “group identification” cluster started in 2015 and will continue until 2023. To some extent, this reflects the focus on collective consciousness in current research on construction workers’ risk-taking behavior. The objects of research in this cluster include different perspectives of safety management norms, such as safety climate, safety citizenship behavior, project management, mediating role, and so on. This provides a knowledge base for the study of construction workers’ risk-taking behavior. Risk-taking behavior (2017–2022) also forms a cluster, and this keyword is the subject of the research presented in this article, under which organizational factors, personal factors, the technology acceptance model, and so, on become an important knowledge base, and different research perspectives provide important reference values.

4.2. Frequently Cited Literature

After opening CiteSpace software, the researcher can select ‘Cited Literature’ in the ‘Node Type’ option, and once the software has finished running, a map of the frequently cited literature in the field of risk-taking behavior of construction workers for the period from 2012 to 2024 can be generated. This paper identified 13 publications with more than 10 citations in the co-citation map (Figure 6), which revealed the disciplinary development, research patterns, interdisciplinary cooperation, and innovative models and methods in the field, and promoted the accumulation of a knowledge base on construction workers’ risk-taking behaviors. Meanwhile, related studies on safety climate, safety behavior, safety performance, and safety outcomes have provided important support for the in-depth exploration of the field.

Among the 13 frequently cited publications, the following are some of the highlights. Alruqi, Wael M. et al. (2018) [29] reviewed 107 studies and included 11 meta-analyses. Five out of 14 safety climate dimensions were found to be associated with injury rates, namely the supervisor’s safety role, the management’s commitment to safety, safety rules and regulations, personal responsibility, and training. These dimensions contribute to a more effective assessment of the safety climate. In addition, Man, S. S. et al. (2017) [30] published an article in Safety Science that indicates that the risk-taking behavior of construction workers is influenced by three aspects: personal, behavioral, and environmental. Suggestions for improvement were also made, such as improving work efficiency, increasing comfort, enhancing safety training [31], strengthening safety supervision and real-time incentives. This publication became the most cited (cited 27 times). More and more articles are using the methods of conducting questionnaires or performing experiments to collect real construction workers’ data, which will make the research results more realistic. Loosemore, M. et al. (2019) [32] conducted a survey on 228 construction workers in Australia and found that the training improved the understanding of safety knowledge but did not significantly increase the importance of safety. Pandit, Bhavana, et al. (2019) [33] collected data from over 280 workers at 57 construction sites in the U.S. and found that workplaces with a positive safety climate were effective in improving workers’ hazard identification and safety risk perception. He, Changquan et al. (2020) [34] studied 119 supervisors and 536 workers from 22 construction projects in China, and the results found that supervisors outperformed construction workers in safety behavior but faced greater stress.

Research on the risk-taking behavior of construction workers varies significantly across countries, mainly in terms of cultural background, policies, research focus, and accident rates. Developed countries, such as the United States and Germany, usually have strict safety regulations and regulatory systems, and research focuses on reducing risk-taking behaviors through technological innovation, code enforcement, and safety training. In contrast, in developing countries such as India or Brazil, where workers are more likely to exhibit risk-taking behaviors due to cultural differences and insufficient regulation, research has mostly focused on increasing safety awareness, improving the work environment, and enhancing training. In addition, research in developed countries focuses mostly on the association between accident data analysis and risk-taking behavior, while research in developing countries focuses on reducing high-risk behaviors and upgrading safety management.

Modeling- and methodology-focused citations also make up a proportion of the overall literature [35,36,37,38], indicating that scholars in the field recognize the importance of using methodological models. Among them, Guo, Brian H. W., et al. (2016) [39] used structural equation modeling to study eight factors affecting the safety behavior of construction workers, and the results showed that management commitment to safety, social expenditures, and production pressure had a significant effect on the safety behavior of construction workers. Newaz, Mohammad Tanvi, et al. (2019) [40] presented the “Psychological Contract of Safety” (PCS) concept, which suggests that the safety climate originates from construction workers’ perception of safety, and PCS is based on mutual obligations between supervisors and workers. This study verified the positive effect of mutual obligation fulfillment on workers’ safety behaviors through structural equation modeling.

Accidents involving injuries to construction workers occur from time to time, and each country’s legal system attributes liability for injuries sustained differently. For example, the United States deals with it through workers’ compensation laws, the United Kingdom through common law and employers’ liability insurance, and both Germany and China through the workers’ compensation insurance system. The causes of accidents include poor site management, lack of supervision, and protective equipment. These factors are also closely related to the risk-taking behavior of the workers themselves. Rather than being independent, these elements interact with each other. This paper examines risk-taking behavior to make the safety system better.

5. Research Keywords Evolution

5.1. Co-Word Analysis

Co-word analysis is the study of the frequency of two keywords that appear simultaneously in the same article. It reflects the evolution and hotspots of research on risk-taking behavior, thus revealing changes in the popularity of certain research topics. After opening CiteSpace software, the researcher can select ‘Keywords’ in the ‘Node Type’ option, and after the software has finished running, it will generate a keyword co-occurrence map in the field of risk-taking behavior of construction workers for the period of 2012 to 2024. The co-occurring keyword network generated by CiteSpace, which contains 204 nodes and 388 chains, is shown in Figure 7.

Node size indicates how often each keyword appears. “construction workers” (Count = 82) was the most frequently used keyword and the subject of the article’s main research. The second most frequently used keywords were “behavior” (Count = 60) and “model” (Count = 60). This points to the fact that scholars mainly use empirical models to analyze behavioral data when studying risk-taking behavior. The third keyword is “health” (Count = 56), which reflects the human-centered concept that the purpose of this paper’s study of risk-taking behaviors of construction workers is for the sake of human safety and, ultimately, for the sake of human health. The fourth keyword is “risk” (Count = 50), which is the qualifier of the research topic and the main content of this paper.

Burst strength refers to the strength of a keyword or reference during a specific period marked by a sudden increase in the frequency of occurrence or significant prominence. It reflects the strength of influence or research hotspot of the keyword or reference at a certain time. In this paper, burst strength is used to detect hot topics at a specific time (see Figure 8). On this network, “exposure” (burst strength = 3.96) received the highest value. This was followed by “stress” (burst strength = 3.25), “labor and personnel issues” (burst strength = 2.83), “construction workers” (burst strength = 2.74), and “workplace safety” (burst strength = 2.69). These keywords reflect topics that are widely valued in the field within a certain time frame.

5.2. Evolution of Keywords

By clustering these keywords, 11 major clusters were identified in this paper (Figure 9 and Figure 10). The clusters with the longest duration were “questionnaire survey”, “machine learning” and “construction safety” (2012–2024). The keyword “questionnaire survey” indicates that, over the years, scholars have used questionnaires to collect primary data for most of their studies on risk-taking behaviors of construction workers, which also suggests that most of the literature is based on empirical analyses based on questionnaires [41]. The term “machine learning” also incorporates machine learning algorithms in the risk-taking behavior of construction workers [42,43]. The terms “construction safety” and risk-taking behavior are inextricably linked, and risk-taking behavior can directly threaten construction safety, while good safety management and a reduction in risk-taking behavior can improve construction safety [44,45].

“Occupational health” (2016–2023) and “accident prevention” (2012–2022) maintained a significantly longer term focus in research. There are many studies on “occupational health” [46], and some scholars believe that construction workers’ safety perceptions are related to occupational health and propose a model of factors influencing safety perceptions that consists of four dimensions: social, organizational, situational, and personal factors [47]. There are many studies on “accident prevention”, in which some scholars have studied from the perspective of pre-service fatigue screening and proposed a method to detect mental fatigue in workers using wearable electroencephalography devices. By analyzing EEG spectral parameters such as gravity frequency and power spectrum entropy, four assessment indicators were achieved. This measure has had a significant effect on accident prevention [48].

The keywords “stress” (2013–2024) and “unsafe behavior” (2015–2024) have also been the focus of research on risk-taking behavior. Regarding stress research, many factors influence anxiety, including age, inappropriate safety equipment, safety culture, high workloads and long hours, etc. [49,50,51]. Regarding the study of unsafe behavior, scholars have derived five major causes of cognitive failure from the cognitive process of construction workers’ unsafe behavior, which are safety vigilance, hazard identification, knowledge of safety, attitude towards safe behavior, and professional skill [52]. In addition, unsafe behaviors have been linked to factors such as personality traits [53].

The terms “skin cancer” (2013–2024), “loneliness” (2012–2022), and “volatile organic compounds” (2012–2019) are also clusters with long durations, which represent extrinsic and intrinsic influences on the formation of risk-taking behavior. The keyword “skin cancer” describes occupations such as construction work, where ultraviolet testing has shown exposure levels two to three times higher than those of the general population [54]. In addition, the cumulative amount of sun exposure for outdoor workers is influenced not only by the amount of UV radiation but also by the specific tasks performed in the sun and the UV protection habits of the workers [55,56]. These are all closely related to skin cancer. The term “loneliness” is closely related to a psychological state and has a significant impact on behavior.” A new model has been developed for the study of “volatile organic compounds, specifically for assessing the risk of exposure of workers to volatile organic compounds during the excavation of contaminated soil, with an emphasis on the area of new exposure, the degree of saturation of the soil, and air circulation [57].

With the advancement of technology, the research direction of construction safety and occupational health is gradually shifting towards intelligent and data-driven management models. With the introduction of technologies such as machine learning and the Internet of Things (IoT), questionnaires survey and data analysis have enabled more accurate identification of safety risks and health hazards. Future research will focus on intelligent safety monitoring, behavioral intervention, and mental health management, especially real-time monitoring and the intervention of unsafe behaviors and work stress through AI and sensor technologies. In addition, the environmental health impacts of the construction industry will become an important topic, with research focusing on the health risks posed by hazardous chemicals, such as volatile organic compounds, to construction workers, as well as exploring the positive health impacts of green building materials and pollution control technologies. About emerging areas of research, mental health interventions and social support systems are likely to receive more attention, aiming to help construction workers link stress and loneliness at work. Taken together, the future of construction safety and health research will rely more on the integration of interdisciplinary technologies, which will drive the industry in a safer and healthier direction.

6. Conclusions and Future Prospects

In recent years, an increasing number of studies have been devoted to the risk-taking behaviors of construction workers, and the search for solutions to reduce risk-taking behaviors is a global challenge. Therefore, a comprehensive and quantitative literature review is needed to understand the current status and progress in the field. In this paper, 272 articles on the risk-taking behavior of construction workers were examined using bibliometric methods. A quantitative and visual review of the scholarship and progress in the field was also conducted using CiteSpace software, including co-citation, co-word analysis of the literature, and so on.

In terms of research status and trends, the number of publications in this field has grown rapidly from 2012 to 2022, and despite a slight decline in the last two years, the field still attracts the attention of a large number of scholars, and the research results have been published in several internationally renowned journals, reflecting the continued high level of research fervor in the field. In terms of academic contributions and collaborations, this paper identifies, through detailed analysis, the leading positions of China (number of publications [Count] = 115), the United States (number of publications [Count] = 71), and Australia (number of publications [Count] = 41) in the field of risk-taking behaviors of construction workers and also explores the most influential institutions and their partnerships. In addition, scholars such as Chan, Alan H S (Count = 5), Chan, Alan Hoi Shou (Count = 5), and Li, Heng (Count = 4) were major contributors. This paper also investigated the research groups formed by researchers in the field and found that many prolific scholars have their research groups and work closely with other researchers, which indicates the importance of collaboration in advancing the field. In terms of the co-occurrence and evolution of keywords, this study showed that “construction workers “ (Count = 82) is the most frequently occurring word, and this kind of people have made many great contributions to the construction of cities, with scholars are paying more and more attention to them. As research in this field continues to deepen, more and more keywords have emerged in recent years, pointing to the diversity and depth of research in this field. The research in this paper also reveals many other important aspects.

It is worth noting that authors with higher co-citation frequency in the literature usually published more research results, which indicates that these authors continued their academic exploration in the field for a long time, and the continuous tracking of their works is of significant academic value to other researchers. Through the cluster analysis of the co-cited literature, this study reveals the research hotspots and future perspectives in the field of construction workers’ risk-taking behavior:

(1) The emergence of risk-taking behavior among construction workers is closely related to a variety of factors and has complexity. Within the group of construction workers, the formation of risk-taking behavior is influenced by many factors, such as work pressure, environmental factors, safety atmosphere, organizational culture, etc. Specifically, work pressure may indirectly promote the occurrence of risk-taking behaviors by affecting workers’ emotional state and decision-making ability. Environmental factors such as the danger of the construction site, the condition of the equipment, and its layout may also increase the risk-taking tendency of the workers. In addition, the creation of a safe atmosphere and the safety management system within the organization should not be ignored in terms of the impact on workers’ behaviors.

Future research should further explore how to comprehensively consider these multidimensional factors, and through the establishment of a more comprehensive theoretical framework, deeply analyze how various types of factors interact and jointly promote the occurrence of risk-taking behaviors to provide a theoretical basis and practical guidance for the reduction and prevention of risk-taking behaviors among construction workers.

(2) The research methods of construction workers’ risk-taking behavior have become increasingly diversified, and the research tools have shifted from a single empirical analysis to a comprehensive analysis combined with advanced equipment. These experiments usually combine a variety of advanced equipment, making the research process more rigorous and objective, thus reducing the influence of subjective factors.

Future research should strengthen the combination of experimental methods and traditional survey methods to form a more comprehensive research framework. For example, when it is necessary to explore human behavior or physiological responses, the use of equipment such as electroencephalography, eye tracker, and near-infrared spectroscopy is increased to verify and supplement the subjective data from questionnaires or interviews. In addition, in fields such as sociology and psychology, simulation experiments are combined with virtual reality technology to provide more immersive and realistic experimental scenarios and improve the external validity of experiments. In addition, emerging technological methods such as machine learning and artificial intelligence can be used for data mining and predictive analytics to enhance the depth and breadth of the research.

(3) The focus of research has gradually shifted from traditional adolescent behavioral patterns to occupational groups, especially construction workers, which is of great theoretical and practical significance for understanding the risk-coping styles and safety management of these groups.

Future research should encourage scholars to conduct risk-taking behavior studies in more high-risk industries to explore the psychological factors, behavioral patterns, and risk management styles of these groups to help develop more effective safety protocols. In addition, comparative studies across geographical regions should be conducted to understand the risk perception and coping styles of specific occupational groups in different cultures and to develop safety policies and measures adapted to different environments.

(4) The management model is also being gradually standardized, and in the future, the scope of the research can be extended to cover all stages of the occurrence of the behavior, with greater emphasis on precision and effectiveness in the methodology. The angle of thinking has shifted from a local and single perspective to a more global and comprehensive analysis. At the same time, the way of thinking increasingly takes into account the actual situation, rather than just remaining at the theoretical level.

Future research should enhance the management of risk-taking behavior and strengthen the comprehensive and systematic nature of management. For example, a more detailed and systematic safety management system can be formulated and combined with technologies such as big data and artificial intelligence to implement dynamic management and real-time monitoring. Secondly, the coordination and cooperation between different departments and industries can be strengthened to form a cross-departmental safety management mechanism, avoiding reliance on the management of a single department and enhancing the effectiveness of management.