The unsafe behavior of construction workers is one of the main causes of safety accidents at construction sites. To reduce the incidence of construction accidents and improve the safety performance of construction projects, there is a need to identify risky factors by monitoring the behavior of construction workers. Computer vision (CV) technology, which is a powerful and automated tool used for extracting images and video information from construction sites, has been recognized and adopted as an effective construction site monitoring technology for the identification of risky factors resulting from the unsafe behavior of construction workers. In this article, we introduce the research background of this field and conduct a systematic statistical analysis of the relevant literature in this field through the bibliometric analysis method. Thereafter, we adopt a content-based analysis method to depict the historical explorations in the field. On this basis, the limitations and challenges in this field are identified, and future research directions are proposed. It is found that CV technology can effectively monitor the unsafe behaviors of construction workers. The research findings can enhance people’s understanding of construction safety management.

Unsafe behaviors of construction workers are one of the main causes of accidents at construction sites. The research on unsafe behaviors of workers helps to reduce the incidence of accidents and has attracted much attention. However, a systematic literature review in this field is still lacking, which hinders stakeholders’ comprehensive understanding of the unsafe behaviors of construction workers. Therefore, the aim of this study is to address this research gap based on retrieved literature from the Web of Science. First, the study conducted a descriptive analysis of the year, quantity, publishing organization, and keywords of the literature. In addition, three research topics were identified and discussed, including the influencing factors of construction workers’ unsafe behaviors, the formation mechanism of unsafe behaviors, and the pre-control methods of unsafe behaviors. Moreover, a research framework was proposed and future research directions were also suggested. The research findings promote stakeholders’ understanding of the influencing factors, formation mechanism, and pre-control methods of construction workers’ unsafe behaviors, and lead to future research directions in the studied field.

The unsafe behavior of construction workers is one of the most important and direct causes of safety accidents. Managers usually develop effective incentives aimed at regulating worker safety behavior. Due to the large number of workers in construction projects, there are multiple differences in fairness preference, risk preference and ability level, which will lead to the complex effect of the traditional mechanism to regulate workers’ safety behavior. In order to improve the effectiveness of incentive measures for worker safety behavior, this paper takes into account the multiple differences of individual workers’ fairness preference, risk preference and ability level, based on the tournament mechanism to construct a competition incentive model. By designing a tournament reward and salary distribution for heterogeneous workers, the occurrence of unsafe behaviors can be reduced. The study found that in terms of the optimal level of safety investment, workers with risk aversion attitude generally invest higher than that of workers with risk preference, no matter whether they have a strong fairness preference or not; In terms of the distribution of tournament rewards, workers with a risk aversion attitude and a higher level of fairness preference need to be given higher incentives.