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PurposeConstruction Hazard Prevention through Design (CHPtD) is recognized as a pivotal strategy for enhancing workplace safety. Despite its theoretical potential, practical implementation faces challenges, particularly regarding designers' familiarity with field-level operations and hazard recognition. This study aims to investigate whether ChatGPT can address these challenges by assisting in hazard recognition during CHPtD sessions.Design/methodology/approachThe research utilized a randomized controlled experiment to assess ChatGPT as an intervention in supporting hazard recognition during CHPtD sessions. The study involves 162 civil and construction engineering student participants, representing future professionals. Participants engaged in hazard recognition during CHPtD sessions either with or without the assistance of ChatGPT.FindingsParticipants who utilized ChatGPT during CHPtD sessions demonstrated a significant improvement in hazard recognition, identifying approximately 40% more hazards compared to those who did not use ChatGPT. These findings underscore the efficacy of ChatGPT in supporting CHPtD efforts.Practical implicationsThe results highlight the practical utility of harnessing ChatGPT in CHPtD sessions to enhance hazard recognition and ultimately promote workplace safety. By leveraging ChatGPT, designers and engineers can better anticipate and mitigate potential hazards during the design phase, thus creating a safer working environment for field workers.Originality/valueThis research contributes to addressing the challenges associated with implementing CHPtD by introducing ChatGPT as a valuable tool to support hazard recognition. By demonstrating the effectiveness of ChatGPT in enhancing hazard identification during CHPtD sessions, this study offers a novel approach to promoting the adoption of CHPtD and advancing workplace safety initiatives.
PurposeConstruction Hazard Prevention through Design (CHPtD) is recognized as a pivotal strategy for enhancing workplace safety. Despite its theoretical potential, practical implementation faces challenges, particularly regarding designers' familiarity with field-level operations and hazard recognition. This study aims to investigate whether ChatGPT can address these challenges by assisting in hazard recognition during CHPtD sessions.Design/methodology/approachThe research utilized a randomized controlled experiment to assess ChatGPT as an intervention in supporting hazard recognition during CHPtD sessions. The study involves 162 civil and construction engineering student participants, representing future professionals. Participants engaged in hazard recognition during CHPtD sessions either with or without the assistance of ChatGPT.FindingsParticipants who utilized ChatGPT during CHPtD sessions demonstrated a significant improvement in hazard recognition, identifying approximately 40% more hazards compared to those who did not use ChatGPT. These findings underscore the efficacy of ChatGPT in supporting CHPtD efforts.Practical implicationsThe results highlight the practical utility of harnessing ChatGPT in CHPtD sessions to enhance hazard recognition and ultimately promote workplace safety. By leveraging ChatGPT, designers and engineers can better anticipate and mitigate potential hazards during the design phase, thus creating a safer working environment for field workers.Originality/valueThis research contributes to addressing the challenges associated with implementing CHPtD by introducing ChatGPT as a valuable tool to support hazard recognition. By demonstrating the effectiveness of ChatGPT in enhancing hazard identification during CHPtD sessions, this study offers a novel approach to promoting the adoption of CHPtD and advancing workplace safety initiatives.
No abstract
The construction sector is known to have the highest risks of occupational accidents. A rationale for this high occurrence of occupational risks can be related to legislative requirements to enforce safe construction practices within this sector. Within the context of excavation works in Turkey, this study investigates the leading risks for any compliance shortfalls and ultimately presents recommendations to mitigate occupational accidents’ occurrences during excavation works in the construction sector. Based on a quantitative methodology, a closed-ended survey consisting of 35 questions and based on legislative requirements was applied to project managers in the construction industry, such as site supervisors, occupational safety experts, auditors, and control personnel. A sample size of 277 responses was found to have stability and validity through a reliability analysis and an exploratory factor analysis, and was used for testing statistical significance via cross-tabulation analysis and chi-square tests. The findings revealed that the major deviation of safety in excavation works from legislative requirements is executing works during adverse weather conditions. Moreover, it was also noteworthy that protective curtains did not surround the excavation sites, and most of the employees encountered ground slippage during excavation work. Therefore, the findings revealed preliminary research that will contribute positively to providing incentives for a focus on and development of relevant security and technical measures. It also provided information to protect the safety and welfare of the workers involved in excavation works. Finally, though these findings may be considered context-specific, this research can be used for comparative purposes for similar studies into the safety practices of excavation works in different countries, where generalized findings can be later derived to inform academia and practice.
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