Despite the use of traditional and novel approaches to improve construction safety management, safety performance in the construction industry is still considered poor, especially when compared with other US industries. Poor safety performance is responsible in part for an observed decrease in work quality and employee productivity and an increase in project costs and completion time. The architectural, construction, and engineering (ACE) industry should adopt and implement innovative safety practices with high total capacities throughout the project life cycle to improve safety performance in construction. Currently, technologies exist that when used appropriately, have capabilities of notably enhancing safety. However, these technologies are not applied broadly in the industry for safety management. Researchers and professionals believe the limited adoption of these technologies across the life cycle of construction projects is a potential contribution to the recorded poor safety performance in construction. To bridge this gap in practice and encourage the adoption of emerging technologies, the present paper summarizes practical applications of different types of technologies for safety risk mitigation and management in construction. Practical information regarding effectiveness, perceived and actual cost implications of the technologies, and the enablers and barriers of technology adoption are discussed. The discussion of the practical implications of these technologies will assist construction managers in making informed decisions regarding what technologies to adopt and implement, which will ultimately lead to improved safety performance.

Technology use in the construction industry fosters improvements in schedule, safety, cost, productivity, and quality. In this domain, the construction technologies adoption highly depends on stakeholders, who may exhibit some resistance to operational use. This underscores the importance of determining technology integration success using effective methods such as predictive and explanatory modelling. Although existing literature has provided some critical insight into the use of these models and theories, there is no domain-based synthesis on the utility of these models and theories as tools to facilitate the integration of emerging construction technologies. Therefore, this paper provides a systematic review and content analysis showcasing different methods and theories for investigating technology acceptance and generates insights expected to guide future technology acceptance studies. Using a three-phase systematic review process, 35 relevant articles were identified and analysed. This review identified perceived ease of use, perceived usefulness, social norm, attitude, perceived behavioural control, and facilitating conditions as key constructs impacting workers’ intention to accept a construction technology. TAM, TPB, and UTAUT were identified as popular choices for developing hybrid models, while UTAUT provided a relatively higher predictive power. Finally, seven areas for further exploration were discussed. This study contributes to construction knowledge by providing a better understanding of technology acceptance research and generating fundamental insights needed to develop robust and effective predictive and explanatory models for advancing technology acceptance research which would support successful technology integration.

The use of robotics and automation (RA) within construction operations to combat stagnant productivity, high rates of injuries and fatalities, and a declining workforce is increasing. However, utilizing RA for construction operations creates human-robot interactions (HRIs) that can lead to the emergence of novel hazards or exacerbate existing safety risk levels. These hazards, if ignored, could worsen worker safety performance. This paper presents a study intended to identify critical HRI safety risks and develop a pre-task planning protocol for the assessment of safety risks associated with the use of RA. To achieve this goal, the authors utilized a sequential multi-phase approach relying on information obtained from a literature review, a 3-round Delphi process consisting of a panel of experts from industry and academia, and interviews with safety experts. Forty hazards associated with RA and 20 potential strategies for the mitigation of HRI safety risks were identified and evaluated. This information was used to develop a safety risk assessment tool that yields an overall risk rating of using RA. This study contributes to knowledge and practice by identifying and quantifying critical safety risks associated with HRI and developing a tool to assess and mitigate unique HRI safety risks. Utilizing insights developed in this study could improve construction worker safety and health and aid the industry’s increasing push towards a smart and safe workforce.

In a bid to optimize jobsite safety, wearable sensing devices (WSDs) are slowly emerging as a class of viable tools with strong potential to improve safety measurement and monitoring. While some industries have successfully utilized WSDs, such as smart personal protective equipment (PPE), to track data related to health, fitness, or even location, the construction industry has been relatively slow in implementing WSDs. Although some progress is expected, construction management research is yet to provide clear evidence of the impact of WSDs on vital project and organizational performance metrics such as safety and productivity. To fill this gap, the present study established the first WSD success model using multiple complementary frameworks and theories. The success model comprises individual adoption factors that influence individual WSD use and highlights implementation success indicators needed to evaluate adoption success. It was tested using survey questionnaires retrieved from 415 users of WSDs in the United States. Test results indicate the success model was a good fit. Moreover, findings suggest a strong positive relationship between the use of WSDs and individual performance, and project performance. This hybrid model provided critical insights on the impact of WSDs on workers’ performance, project metrics, as well as essential information for supporting the increased adoption of WSDs. It is believed that this framework will also guide construction practitioners in the effective integration of WSDs into their work processes.