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Accident analysis is used to discover the causes of workplace injuries and devise methods for preventing them in the future. There has been little discussion in the previous studies of the specific elements contributing to deadly construction accidents. In contrast to previous studies, this study focuses on the causes of fatal construction accidents based on management factors, unsafe site conditions, and workers' unsafe actions. The association rule mining technique identifies the hidden patterns or knowledge between the root causes of fatal construction accidents, and one hundred meaningful association rules were extracted from the two hundred and fifty-three rules generated. It was discovered that many fatal construction accidents were caused by management factors, unsafe site circumstances, and risky worker behaviors. These analyses can be used to demonstrate plausible cause-and-effect correlations, assisting in building a safer working environment in the construction sector. The study findings can be used more efficiently to design effective inspection procedures and occupational safety initiatives. Finally, the proposed method should be tested in a broader range of construction situations and scenarios to ensure that it is as accurate as possible.

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BACKGROUND: The data mining of construction accidents based on a robust modeling process can be used as a practical technique for reducing the frequency of construction accidents. OBJECTIVE: This study was designed to data-mine construction accidents. METHODS: This study was conducted in 2020 on construction accidents in Iran for ten years (2009-2018). The instruments to collect the required data were the checklists and descriptive reports of the accidents. The dependent variables of the study included reactive safety indicators related to construction accidents (lost working days (LWD) and total accident costs (TAC)). The independent variables consisted of four latent factors: personal variables, organizational variables, unsafe working conditions, and unsafe acts. The data were collected based on the conceptual model designed for data mining. The data mining process was carried out based on the structural equation modeling by IBM AMOS V. 23.0. RESULTS: A total of 5742 construction accidents occurring in 10 years were analyzed. The means of TAC and LWD indicators were estimated to be 248.20±52.60 days and 1893.10±152.22 $. These two indicators directly correlated with the two latent factors of unsafe conditions and unsafe acts and their related variables and were indirectly influenced by latent personal and organizational factors. The relationship between unsafe conditions and unsafe acts was significantly positive. The relationship between latent personal and organizational factors and the two construction accident indicators was significantly negative (p <0.05). CONCLUSION: The model results showed that personal and organizational variables could, directly and indirectly, affect reactive safety indicators in construction projects. Thus, these findings can be used to design and improve safety strategies to prevent and decrease construction accidents and incidents.

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In terms of safety management, the implementation of industrial parks construction projects (IPCPs) is incredibly challenging due to the special working conditions and the specific type of use of the buildings. On the other hand, the possibility of causing accidents in these areas based on human errors is high and important for project execution due to the risks of human errors and financial losses. Therefore, this study tries to fill this existing research gap by identifying and evaluating the effective key factors leading to the occurrence of construction accidents caused by human errors in the development of IPCPs. After a holistic review of the reported literature, four rounds of fuzzy Delphi survey were launched to capture the individual opinions and feedback from various project experts. Accordingly, 41 key factors affecting human errors in the implementation of industrial parks construction projects in Iran were identified and classified into nine main groups of wrong actions, observations/interpretations, planning/processes, equipment, organization, individual activities, environmental conditions, rescue, and technology. Then, the step-wise weight assessment ratio analysis (SWARA) method was adopted to rate and rank the identified factors of human errors in the implementation of IPCPs in Iran. The research findings indicated that among the elicited factors, time factor (0.1226), delayed interpretation (0.1080), and incorrect diagnosis/prediction (0.0990) are the three most crucial factors leading to human errors in the implementation of IPCPs in Iran. The results of this research study have provided various major project stakeholders with an effective decision-aid tool to make better-informed decisions in managing and reducing the occurrence of construction site accidents particularly caused by human errors associated with IPCPs.

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Objectives. The construction sector is one of the sectors with the highest number of occupational accidents and diseases in the world in terms of working conditions. According to the 'Communiqué on Occupational Hazard Classes on Occupational Health and Safety' related to Occupational Health and Safety Law No. 6331, the construction sector is considered a 'very dangerous works' class. Methods. Occupational accidents that occurred between 2012 and 2019 are examined according to occupational groups, working environments, etc. Feature importance and Kendall, Pearson and Spearman correlations were used for analysis. Results. From the studies, it is determined that fatal accidents in the construction sector in Turkey are caused by falling from height with a high rate. When the correlation values were examined, it was determined that the column 'accident type' had a negative relationship with the 'injured part of the body' and a positive relationship with the 'accident environment' column. Conclusion. A total 51% of 3517 fatal accidents examined occurred in the construction of buildings. Most deaths in the construction sector in Turkey are caused by falling from height, like many countries (41.6%). Statistics shows that despite the relevant regulations, the construction sector in Turkey is seen as a weak safety culture.

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Many construction accidents occur in China each year, leading to a large number of deaths, injures, and property losses. Due to the outbreak of COVID-19, little attention is paid to construction safety, resulting in severe accidents. To prevent construction accidents and learn to how address safety issues in future pandemics, this study proposed an improved STAMP (Systems Theoretic Accident Modeling and Processes) model to analyze the collapse accident of the Xinjia Express Hotel used for COVID-19 quarantine in China. Through the application of the STAMP approach, the causes of the construction accident and the relationship between various causal factors are analyzed from a systematic perspective. The identified causes are divided into five categories: contractors, management of organizations, technical methods, participants, and interactive feedback. Finally, safety recommendations are drawn from this study to improve construction safety and safety management in pandemics.

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This study used methodologies of descriptive and quantitative statistics to identify the contributing factors most affecting occupational accident outcomes among electrical contracting enterprises, given an accident occurred. Accident reports were collected from the Occupational Safety and Health Administration's fatality and catastrophe database. To ensure the reliability of the data, the team manually codified more than 600 incidents through a comprehensive content analysis using injury-classification standards. Inclusive of both fatal and non-fatal injuries, the results showed that most accidents happened in nonresidential buildings, new construction, and small projects (i.e., $50,000 or less). The main source of injuries manifested in parts and materials (46%), followed by tools, instruments, and equipment (19%), and structure and surfaces (16%). The most frequent types of injuries were fractures (31%), electrocutions (27%), and electrical burns (14%); the main injured body parts were upper extremities (25%), head (23%), and body system (18%). Among non-fatal cases, falls (37%), exposure to electricity (36%), and contact with objects (19%) caused most injuries; among fatal cases, exposure to electricity was the leading cause of death (50%), followed by falls (28%) and contact with objects (19%). The analysis also investigated the impact of several accident factors on the degree of injuries and found significant effects from such factors such as project type, source of injury, cause of injury, injured part of body, nature of injury, and eventtype. In other words, the statistical probability of a fatal accident-given an accident occurrence-changes significantly based on the degree of these factors. The results of this study, as depicted in the proposed decision tree model, revealed that the most important factor for predicting the nature of injury (electrical or non-electrical) is: whether the source of injury is parts and materials; followed by whether the source of injury is tools, instruments, and equipment. In other words, in predicting (with a 94.31% accuracy) the nature of injury as electrical or non-electrical, whether the source of injury is parts and materials and whether the source of injury is tools, instruments, and equipment are very important. Seven decision rules were derived from the proposed decision tree model. Beyond these outcomes, the described methodology contributes to the accident-analysis body of knowledge by providing a framework for codifying data from accident reports to facilitate future analysis and modeling attempts to subsequently mitigate more injuries in other fields.

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The implementation of precursor management can improve safety performance of construction projects through effectively managing the correlations between construction accidents and their precursors. However, a system of comprehensive knowledge about what precursors mean within the context of construction safety is still lacking. This study aims to capture the nature of precursors in the construction industry and explore the process of a precursor event evolving into a construction accident to fill this gap. Based on 135 construction accident reports in China, this study adopts grounded theory to identify different types of accident precursors and explore their interactions with the development of the accident. An indicator system of precursors for construction accidents was developed, which included two major categories of precursors: behavioral factors and physical factors and five minor categories of precursors: individual behavior factors, organizational driving factors, objective physical factors, construction environmental factors, mechanical equipment factors. In addition, a precursor management strategy that includes the three stages of identification, response and effectiveness testing was established. The results of the study reveal the correlations between precursors and construction accidents, which can promote construction professionals' better understanding about precursors and improve their capabilities of managing precursors in practice.

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INTRODUCTION: It is necessary to clearly understand construction accidents for preventing a rise in Chinese construction accidents and deaths. Better analysis methods are required for Chinese construction sector accidents. METHODS: Choosing and analyzing a typical construction accident based on four popular contemporary accident causation models: STAMP, AcciMap, HFACS, and the 2-4 Model. Then we evaluated the models' applicability to construction accidents, including their usability, reliability, and validity. RESULTS: STAMP addressed how complexity within the accident system influenced the accident development, and its output makes the responsibilities clearer for the accident. AcciMap described the entire system's failure, the entire accident's trajectory, and the relationship between them. AcciMap showed that the accident was a dynamic developing process, and this method has a high usability. The taxonomic nature of HFACS is an important feature that provides it with a high reliability. In the accident reviewed here, we found that poor management was a critical factor rather than the individual factor in the accident. The 2-4 Model provided detailed causes of the accident and established the relationship among the accident causes, the safety management system, and the safety culture. It also avoided capturing all of the complexity in the large sociotechnical system and revealed a dynamic analysis and developing process. We confirmed that it has a high usability and validity. Therefore, the 2-4Model is recommended for future Chinese construction accident analysis efforts. PRACTICAL APPLICATIONS: The study provides a useful, reliable, and effective analysis method for Chinese construction accidents.

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Globally, falls from height (FFH) are a substantial public health jeopardy and are among the important leading causes of serious and fatal injuries for construction workers. A comprehensive understanding of the causal factors in FFH incidents is urgently required; however, the literature appears to lack a scientific review of FFH. In this study, 297 articles that contribute to the topic of fall incidents were reviewed. Seventy-five (75) articles met the criteria for relevance and were aggregated in a database to support a critical review. A synthesis of macro-variables approach was adopted rather than a structured meta-analysis. Such a method of analysis provides the flexibility to combine previous studies' findings. The most common factors associated with FFH are risky activities, individual characteristics, site conditions, organizational characteristics, agents (scaffolds/ladders) and weather conditions. The outcomes contributed to identifying the most significant research area for safety enhancement by improving engineering facilities, behaviour investigations and FFH prevention methods.

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Climatic heat stress leads to accidents on construction sites brought about by a range of human factors emanating from heat induced illness, and fatigue leading to impaired capability, physical and mental. It is an occupational characteristic of construction work in many climates and the authors take the approach of re-engineering the whole safety management system rather than focusing on incremental improvement, which is current management practice in the construction industry. From a scientific viewpoint, climatic heat stress is determined by six key factors: (1) air temperature, (2) humidity, (3) radiant heat, and (4) wind speed indicating the environment, (5) metabolic heat generated by physical activities, and (6) "clothing effect" that moderates the heat exchange between the body and the environment. By making use of existing heat stress indices and heat stress management processes, heat stress risk on construction sites can be managed in three ways: (1) control of environmental heat stress exposure through use of an action-triggering threshold system, (2) control of continuous work time (CWT, referred by maximum allowable exposure duration) with mandatory work-rest regimens, and (3) enabling self-paced working through empowerment of employees. Existing heat stress practices and methodologies are critically reviewed and the authors propose a three-level methodology for an action-triggering, localized, simplified threshold system to facilitate effective decisions by frontline supervisors. The authors point out the need for "regional based" heat stress management practices that reflect unique climatic conditions, working practices and acclimatization propensity by local workers indifferent geographic regions. The authors set out the case for regional, rather than international, standards that account for this uniqueness and which are derived from site-based rather than laboratory-based research.

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