Accident; analysis and prevention
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Existing initiatives in the management of construction project safety are largely based on normative compliance and error prevention, a risk management approach. Although advantageous, these approaches are not wholly successful in further lowering accident rates. A major limitation lies with the approaches' lack of emphasis on the social and team processes inherent in construction project settings. ⋯ The results reveal that, while the structural dimension is not significant, the mediational thesis is generally supported with the cognitive and relational dimensions affecting project participants' adaptation and cooperation, and the latter two processes affect safety performance. However, the cognitive dimension also directly affects safety performance. The implications of these results for project safety management are discussed.
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There have been 30 years of research on Intelligent Speed Adaptation (ISA), the in-vehicle system that is designed to promote compliance with speed limits. Extensive trials of ISA in real-world driving have shown that ISA can significantly reduce speeding, users have been found to have generally positive attitudes and at least some sections of the public have been shown to be willing to purchase ISA systems. Yet large-scale deployment of a system that could deliver huge accident reductions is still by no means guaranteed.
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Construction project features (CPFs) are organisational, physical and operational attributes that characterise construction projects. Although previous studies have examined the accident causal influence of CPFs, the multi-causal attribute of this causal phenomenon still remain elusive and thus requires further investigation. Aiming to shed light on this facet of the accident causal phenomenon of CPFs, this study examines relevant literature and crystallises the attained insight of the multi-causal attribute by a graphical model which is subsequently operationalised by a derived mathematical risk expression that offers a systematic approach for evaluating the potential of CPFs to cause harm and consequently their health and safety (H&S) risk implications. The graphical model and the risk expression put forth by the study thus advance current understanding of the accident causal phenomenon of CPFs and they present an opportunity for project participants to manage the H&S risk associated with CPFs from the early stages of project procurement.
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Since the safety professionals are the key decision makers dealing with project safety and risk assessment in the construction industry, their perceptions of safety risk would directly affect the reliability of risk assessment. The safety professionals generally tend to heavily rely on their own past experiences to make subjective decisions on risk assessment without systematic decision making. Indeed, understanding of the underlying principles of risk assessment is significant. ⋯ The model (Q(2)REM) not only act as a useful supplementary guideline of risk assessment for the construction safety professionals, but also assists them to pinpoint the potential risks on site for the construction workers under respective trades of works through safety trainings and education. It, in turn, arouses their awareness on safety risk. As the Q(2)REM can clearly show the potential accident causes leading to different types of accident by trade of works, it helps the concerned safety professionals and parties to plan effective accident prevention measures with reference to the priority of the risk levels.
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Construction accident research involves the systematic sorting, classification, and encoding of comprehensive databases of injuries and fatalities. The present study explores the causes and distribution of occupational accidents in the Taiwan construction industry by analyzing such a database using the data mining method known as classification and regression tree (CART). ⋯ The results of this study show that the occurrence rules for falls and collapses in both public and private project construction industries serve as key factors to predict the occurrence of occupational injuries. The results of the study provide a framework for improving the safety practices and training programs that are essential to protecting construction workers from occasional or unexpected accidents.