A critical review of the feasibility of emerging technologies for improving safety behavior on construction sites.

INTRODUCTION: Advancements in the modern construction industry have contributed to the development of a range of technology-based interventions to improve the safety behavior of front-line construction workers. Notwithstanding the extensive research on safety behavior, there is still a paucity of research on assessing technology interventions of safety behavior to provide an overview of their strengths and limitations. The present study aims to bridge this gap in the literature and identify the main trends of research. METHOD: A systematic review and critical content analysis are adopted to capture an overview of the state of knowledge on safety behavior technologies. As a result of searching Scopus, Web of Science, and Google Scholar databases in the period from Jan 2010 to Feb 2023, a total of 359 potential studies went through the systematic screening process and finally, 48 representative studies were selected followed by an assessment of the feasibility and applicability of the safety behavior technologies. RESULTS: It was found that safety behavior technology is characterized by seven technologies including virtual-reality simulation (T1), eye-tracking technology (T2), prediction modeling of safety behavior (T3), computer-based training (T4), drone/sensor-based hazard monitoring (T5), vision-based behavior monitoring (T6), and real-time positioning (T7). CONCLUSIONS: This research improves understanding of the status of safety behavior technologies and provides a critical review of their feasibility from the perspective of four assessment criteria including application, limitation, benefit, and feasibility. PRACTICAL APPLICATIONS: The categorizations of technologies add value to the body of knowledge in terms of generic requirements for their implementation and adaptation on construction sites.

Resilience Engineering Indicators and Safety Management: A Systematic Review.

A safe work environment is crucial in high-risk industries, such as construction refurbishment. Safety incidents caused by uncertainty and unexpected events in construction refurbishment systems are difficult to control using conventional safety management techniques. Resilience engineering (RE) is proposed as an alternative to traditional safety management approaches. It presents a successful safety management methodology designed to deal with uncertainty in high-risk work environments. Despite the fact that RE resides in the safety domain, there is no common set of RE indicators to measure and assess resilient in the work environment. The main aim of this research is to explore RE indicators that have been identified as important in developing and assessing the resilient work environment in high-risk industries, particularly in construction refurbishment. Indicators have been attained through a systematic literature review of research and scholarly articles published between the years 2004 and 2019. The literature review explored RE indicators in various industries. Descriptive analysis and co-occurrence-based network visualization were used for data analysis. The findings revealed 28 RE indicators in 11 different high-risk industries. The results show that the four commonly used indicators were: top-management commitment, awareness, learning, and flexibility, all of which have a strong relationship with RE. The findings of this study are useful for stakeholders when making decisions concerning the most important RE indicators in the context of their research or practice as this would avoid the ambiguity and disparity in the identification of RE indicators.

Using a psychological contract of safety to predict safety climate on construction sites.

INTRODUCTION: The fact that safety climate impacts safety behavior and delivers better safety outcomes is well established in construction. However, the way workers safety perception is inclined and developed is still unclear. METHOD: In this research, the influence of supervisors' developing safety climate and its impact on workers' safety behavior and their conceptualization of safety is explored through the lens of the 'Psychological Contract' (PC). More specifically, it is argued that 'Psychological Contract of Safety' (PCS) is a vital factor in explaining how workers attach meaning to a supervisor behavior. Extant research suggests: (a) safety climate is based on the perception of workers regarding safety; and (b) PCS is based on perceived mutual obligations between workers and supervisors. As a result, this research argues that if PCS or mutual obligations between workers and supervisors are fulfilled, then safety climate of the workers will be positively influenced. A model is presented depicting PCS as an alternative intervention in understanding how safety climate could be influenced and predicted by the level of fulfillment of mutual safety obligations. Using Structural Equation Modeling (SEM) the model of the PCS is validated with data collected from a mega-construction project in Australia. RESULTS: The results suggest that to have a positive and strong safety climate, top-level managers must ensure that mutual safety obligations between supervisor and workers are fulfilled. This enables the PCS to be introduced as a new 'predictor' of safety climate. Practical applications: The novel outcome of the research could be considered as a management intervention to modify supervisors' behavior to produce better safety outcomes.