Causes Of Construction Accidents Research Articles

Exploring associations between accident types and activities in construction using natural language processing

Existing accident analysis methods often fail to integrate the relationship of construction accidents with construction activities, restrict the potential for visualizing the accidents frequency in Building Information Modelling (BIM). This study proposes a decision support system that provides visual insights, and the frequency of the core construction accidents in relation to typical construction activities. K-mean clustering and keyword-matching techniques are used to group the leading causes of construction accidents and then compare them with the construction activities. The average hit rate computed for construction accidents was 91%, whereas the hit rate calculated for construction activities connected to these frequent accidents was 75%. The classification models are integrated into the Power BI platform to offer decision-makers deeper insights regarding the relationship of prevalent construction accident types and associated activities. The practical application of the system is demonstrated with a case study, exemplifying the fall accident data integrated in a BIM environment.

Should We Depend on Expert Opinion or Statistics? A Meta-Analysis of Accident-Contributing Factors in Construction

International research overflows with studies looking into the causes of construction accidents. Hundreds of studies by postgraduate students in the past 20 years focus on identifying and assessing risks contributing to accidents on Greek construction workplace sites. Many base their work on results from questionnaire surveys that collect the opinions of construction site professionals or on the analysis of data from actual accident records or statistics. Consequently, this study seeks to determine if the data source leads to differing conclusions by using two techniques to synthesize individual results and rank the accident-contributing factors investigated in the original studies. The first utilizes their relative importance index (RII) values, and the second uses their overall ranking index (ORI) to execute meta-analyses. The professional opinion concludes that factors related to operative behavior are the most significant accident-contributing factors. At the same time, actual accident statistics point to site risk factors of the construction process itself as the most important, indicating that expert opinion of Greek professionals should be considered in conjunction with data from actual accident records to provide the focus points for mitigation and assurance of safe construction sites in Greece.

Identification of critical causes of construction accidents in China using a hybrid HFACS-CN model

Construction safety is of significance since construction accidents can result in loss of property and large numbers of casualties. This research aims to identify the critical causes of construction accidents by introducing a hybrid approach. The hybrid approach is developed to identify the critical causes of construction accidents by combining the human factors analysis and classification system (HFACS) model with complex network (CN) theory. A total of 863 construction accident cases were collected, and 46 causal factors were identified. Subsequently, the accident causal network was established, and six critical causal factors were extracted. The hybrid analysis approach is demonstrated with a real construction accident case, and the results demonstrate that the hybrid approach could better identify the critical causal factors. Consequently, this research enables the enhancement of understanding the HFACS framework and CN theory, as well as a contribution to safety management in the construction industry at different levels.

A conceptual framework for integrating QSHE in construction

Construction accidents become catastrophic in infrastructure development. Evidence shows that quality failures such as system, services, procedural, materials, equipment, and human failures within the business process of project delivery systems are contributing causes of construction accidents that negatively impact worker safety, public safety, building/asset, and environmental safety. The standardized quality management systems and safety management systems in construction are fragmented. The Indonesian authorities have integrated the Quality Safety Health and Environment (QSHE) management system since 2018, but the implementation of the integrated QSHE system is still questionable. This paper aims to propose a framework and methodology for integrating QSHE implementation. The framework is based on the literature review of international standards and the UK Construction Design & Management Regulation. This proposal is a part of research currently formulated to develop an operating system to integrate quality and construction safety best practices in the project delivery systems. This paper addresses the quality management framework, safety management framework and, the proposed conceptual framework for integrating quality and safety management systems. The development of an integrated QSHE management system has the potential to save resources and eliminate redundancy significantly. Thus, an organization’s net production, profitability, and efficiency can significantly be increased. The results of this paper are 51 key points that are needed for integrating QSHE in construction projects. In the pre-construction stage, there are 24 key points, which are the largest portion. During the construction stage, there are 19 key points, and during the post-construction stage, there are 8 key points. So, it is very important to carry out the QSHE integration during the pre-construction stage to minimize the defects and accidents in construction projects.

Analysis of the causes of construction accidents as a component of building safety management

Analysis of the causes of construction accidents as a component of building safety management

Causes of Accidents in Construction Industries during Covid -19

Construction industry is the most critical industry which deals with high-risk activities every day. In fact, this industry reported the highest death rate for five years in a row, with 63 deaths in 2017, 118 deaths in 2018, 84 deaths in 2019, 58 deaths in 2020 and 23 deaths until March 2021. Although significant improvements have been made in occupational safety, the management and monitoring of the risks of such workplace activities are still challenging. Besides, working at construction site during pandemic increase the risk of accident when employees attempt to comply with both safety measures at the construction site and during the pandemic. Therefore, this paper intends to risk level of the selected accident types, investigate the causes of construction accidents and the correlation between the likelihood of the factors of accidents. Result shows that the most to the least risky types of accidents ranking are falling from height, falling objects, slips, trips, and falls, getting caught-in or -between moving or stationary objects, getting struck by moving objects, electric shock, exposure to chemical and sunstroke. Result also shows that eight subfactors are found to be the most influence root causes of accidents while three subfactors are the least influence. Six out of eight type of accidents are found to have a positive correlation with several factors of the accidents.

Identifikasi Penyebab Kecelakaan Kerja Konstruksi Menggunakan Accident Root Cause Tracing Model (ARCTM) dan Fault Tree Analysis (FTA)

The construction sector greatly contributed to the increase in the number of injuries and even deaths of workers. This study aims to identify unsafe conditions and unsafe acts and to analyze the causes of work accidents on the Talago Embung Project in the village of Sikabu kabu, Luhak, District of Limo Puluh Kota by using the Accident Root Cause Tracing Model (ARCTM) and Fault Tree Analysis (FTA). Data were collected through observation, in-depth interviews, and documentation. The causes of construction accidents identified are as follows; a) environmental factors i.e. weather or climate, lack of lighting, b) tools and facilities factors i.e. equipment life cycle, availability of Personnel Protective Equipment (PPE), and negligence in maintaining it, c) human factors i.e. personal issues, work pressure, and physical condition of workers, lack of skills and experience of workers, and d) management factors i.e. ineffective communication between the management team and workers and among workers, inadequate SOP and inappropriate material layout planning. Based on the results, it is expected that there will be training directly related to tasks and work safety, adequate project layout planning, proper supervision, and adequate maintenance of work safety equipment.

Tunnel Construction Workers’ Cognitive Biases and Unsafe Behaviors: The Mediating Effects of Risk Perceptions

The poor safety performance of the construction industry is a global concern. Workers’ unsafe behaviors (WUBs) are viewed as critical causes of construction accidents. Thus, it has been a leading research topic to identify antecedents of WUBs and establish reliable models to explain WUBs. Cognitive biases (CBs) are salient antecedents of WUBs. However, the relationships between CBs and WUBs are not further explored in construction safety management. As such, this study selected three prevalent CBs, i.e., availability bias (AB), confirmation bias (FB), and overconfidence, and investigated the relationships between the three CBs and WUBs and the functions of RPs in these relationships among tunnel construction workers. We established six multiple regression models. Research results show that CBs can directly influence RPs and WUBs, RPs are antecedents of WUBs, and the mediating effect of RPs on the relationships between CBs and WUBs is salient. In detail, AB and FB explain more ERP and overconfidence explains more BRP. AB and FB indirectly influence more WUBs through ERP, while overconfidence indirectly affects more WUBs through BRP. The study provides a novel theoretical paradigm for conceptualizing CBs and their relationships with RPs and WUBs. The research results can also guide managers to take debiasing measures to decrease workers’ unsafe behaviors on the construction site.

Causes of accidents and benefit of safety to local masons in Wukari, Nigeria

The objective of this research is to ascertain the causes of accidents to native construction workers (masons) in Wukari, Nigeria and to enumerate the benefits of such safety practices. Forty questionnaires were carefully analysed using a four-point ranking strategy that is predicated on a mid-rank method. According to this research, shortages and lack of equipment have been the major causes of construction accidents. Masons climb ladders without even wearing their tops, boots or helmet. In fact, they are proud of this madness. Moreover, horseplay and lack of training have also significantly contributed to the accident cases. The major benefit of safety is that it raises the professional image of the construction workers and the contractor that employed them. This increases their chances of getting more projects. Government and well-meaning leaders in Taraba state are advised to enforce safety measures on the stubborn construction workers in Wukari.

Causes of accidents and evaluation of safety system in Northern Iraq construction projects

Construction work involves some of the most complex operational actions, where many activities require to be carried out at the same time and place. The nature of this type of work, subsequently, makes it an extremely hazardous environment for workers. By constructing sophisticated and intelligent safety systems to make construction work and sites safer, and bypasses any unforeseen costs caused by accidents that can occur during the construction work. To construct such systems, it is required to know the causes behind accidents. So that, to improve the overall safety performance, there is a need to investigate the causes of construction accidents and to evaluate the current safety systems used to give a picture of the weak points in systems currently adopted. The awareness of these things can be used in formulating safer working environments for construction work. This paper identifies the causes of the accident and evaluates the present safety systems in different construction projects in Northern Iraq. The study has been conducted by reviewing literature from articles and books, plus applied quantitative approaches to collect data by applying a questionnaire survey prepared for this study to collect data from the sites’ users. The results of the current study show that the overall evaluation of the safety system is in poor condition, also found that there are many causes behind accidents. The most severe cause is considering safety as a second priority, and the study classified the causes into, unsafe actions and unsafe conditions.

Analysis of Fatal Accidents and Their Causes in the Korean Construction Industry

The construction industry is one of the most hazardous industries in many countries. Many studies have asserted that industrial accidents could be prevented by eliminating their root causes. However, given that accident occurrence processes are considerably complex and often invisible, it is difficult to identify and eliminate the root causes. Based on this recognition, this paper aims to analyze the causality of construction accidents on the basis of direct causes that are classified into unsafe actions (UA) and unsafe conditions (UC). A logistic regression is applied to examine associations between UAs and UCs and their significances in triggering construction accidents. Then, a Delphi method is applied to determine the relationships between direct and root causes of construction accidents. This study contributes to an improved understanding of the complex causal process of construction accidents, which is a necessary stepping-stone to prevent construction accidents. Meanwhile, only one-to-one combinations of UCs and UAs are considered in this paper. Thus, follow-up studies to examine the impact of one-to-many or many-to-many combinations are needed.

Identification of critical causes of construction accidents in China using a model based on system thinking and case analysis

Hundreds of accidents occur each year in the construction industry and result in large numbers of injuries, deaths, and loss of property. Although construction safety management aims for zero accidents, this is difficult to achieve because of multiple factors influencing the occurrence of accidents. To clarify the framework for construction accident prevention, this study uses accident causation theory and the system thinking method to build a construction accident causation system (CACS) model and identify critical accident causes. Construction accident causes are considered as a whole system and then decomposed into 6 subsystems, 16 factors, and 39 subfactors. The investigation reports of 571 construction accidents in China are collected, and a grey relational analysis (GRA) of accident causes is conducted. Based on these results, the 39 subfactors are classified into 3 severity levels: critical, important, and ordinary. A case study is then conducted with respect to the particularly serious collapse accident that occurred during the Fengcheng Power Plant project. The occurrence process, major reasons for the accident, and related management defects are investigated and causes are identified. The results about accident cause identification of the case study are found to be consistent with the GRA of 571 accidents. Finally, recommendations for construction safety management and accident prevention in practice are proposed.

Causes of Accident at Construction Sites in Bangladesh

Abstract Bangladeshi construction industry suffers more safety issues than other developing countries in the world. Among many of these, accidents at the construction site go far beyond and shape a horrific figure of death every year. The aims of this study are to identify and prioritize the causes of accidents. This study also analyses and discusses causes of accident at the construction site in Bangladesh. A widespread literature review and open discussion took place to identify the causes and design the questionnaire. The questionnaire-based survey was used to elicit the attitude of four stakeholders such as workers, owners, consultants and contractors towards the causes of accident. Mean and relative importance index (RII) were used to determine the rank of causes, and Statistical Package for the Social Sciences (SPSS) 23 was used to perform the data validation test. This study identifies 77 causes under 14 major groups and ranked them based on the mean and RII. The top five major groups of causes are management-, consultant-, technology-, labour- and contractor-related causes. The top five causes are unawareness of safety-related issue, lack of personal protective equipment, lack of safety eliminating/avoiding design, unfit equipment, lack of knowledge and training on equipment. This study will help the project participants and authorities to know and understand the various characteristics and linkage of causes of construction accidents to improve the construction safety management. It contributes to the body of knowledge, as it reveals for the first time the causes of accidents in the Bangladeshi construction industry.

Digital engineering potential in addressing causes of construction accidents

With the emergence of digital engineering in the construction context, significant opportunities have arisen for safer project execution. Several studies in recent years have described various applications of digital engineering to improve safety performance. However, what is missing is a systematic review that shows the direct links between the potential of these approaches and how they address the causes of construction accidents. This study is an attempt to fill this gap by conducting a realist systematic review of the literature published since 2012. The study draws from the Loughborough Construction Accident Causation (ConAC) model to create a comprehensive list of accident causes and relates these causes to the identified digital engineering potential, as reflected in the literature. This approach identifies the research gaps and neglected research domains, particularly six endemic problems, within the current digital engineering literature pertaining to safety, while introducing future areas associated with the identified gaps. This study provides useful insights to investigators who gain direction towards the top priorities for future research. In practical terms, the study collates and presents various areas of potential within digital engineering to address the causes of accidents on construction sites, providing a concise source of knowledge for practitioners.

Transfer learning and deep convolutional neural networks for safety guardrail detection in 2D images

Abstract Safety has been a concern for the construction industry for decades. Unsafe conditions and behaviors are considered as the major causes of construction accidents. The current safety inspection of conditions and behaviors heavily rely on human efforts which are limited onsite. To improve the safety performance of the industry, a more efficient approach to identify the unsafe conditions on site is required to supplement the current manual inspection practice. A promising way to supplement the current manual safety inspection is automated and intelligent monitoring/inspection through information and sensing technologies, including localization techniques, environment monitoring, image processing and etc. To assess the potential benefits of contemporary technologies for onsite safety inspection, the authors focused on real-time guardrail detection, as unprotected edges are the ones cause for workers falling from heights. In this paper, the authors developed a safety guardrail detection model based on convolutional neural network (CNN). An augmented data set is generated with the addition of background image to guardrail 3D models and used as training set. Transfer learning is utilized and the Visual Geometry Group architecture with 16 layers (VGG-16) model is adopted to construct the basic features extraction for the neural network. In the CNN implementation, 4000 augmented images were used to train the proposed model, while another 2000 images collected from real construction jobsites and 2000 images from Google were used to validate the proposed model. The proposed CNN-based guardrail detection model obtained a high accuracy of 96.5%. In addition, this study indicates that the synthetic images generated by augment technology can be used to create a large training dataset, and CNN-based image detection algorithm is a promising approach in construction jobsite safety monitoring.

The factors contributing to construction accidents in Pakistan

PurposeThe highest number of accidents in proportion to the employment rate is found in construction industry among all industries in Pakistan. The purpose of this paper is to identify and prioritize the contributory factors of accident causation that can significantly reduce the rate of accident in the construction industry.Design/methodology/approachIn total, 32 contributory factors of accident causation were identified through a triangulation strategy comprising eight face-to-face semi-structured interviews with the academic and industry experts coupled with a comprehensive literature review. Delphi survey was then conducted among the four respondent groups (clients, contractors, safety official and academia) to prioritize these factors. A consensus was achieved among the respondent groups after conducting two rounds of Delphi survey. Finally, the results were validated using the technique of inter-rater agreement (IRA) analysis.FindingsAll the shortlisted accident causation factors were graded as “important” to “extremely important”. Moreover, a “moderate” to “strong level” agreement was developed among the respondent groups. The three most significant factors were highlighted as “poor enforcement of safety rules and regulations by the Government agencies”, “insufficient allocation of safety budget and safety incentives by the client”, and “insufficient provision of safety training and resources by the contractor”.Practical implicationsThe findings will help the key stakeholders to prioritize their energies towards achieving zero accident in the construction industry. Moreover, addition of academic experts as one of the respondent groups will enhance the linkages between the academia and the industry practitioners.Originality/valueBesides highlighting the underlying causes of construction accidents in Pakistan, a detailed methodology is presented in this study for the analysis and validation of the Delphi survey data, which can be extrapolated in other regions and industries for elements prioritization. The findings of the study can also be generalized for other developing countries having similar work environment. The results validation through the use of IRA analysis is an addition to the field of construction safety research. The study also authenticates the applicability of IRA analysis to assess the agreement level among the respondents.

Decision Making Method Based on Importance-Dangerousness Analysis for the Potential Risk Behavior of Construction Laborers

Unsafe behavior contributes to 90% of the causes of construction accidents. To prevent construction accidents, studies on existing unsafe behaviors have been regularly conducted. However, existing studies generally tend to average the survey results and conduct analyses thereon, and such a method cannot consider the potential risk as regards people’s anxiety about a certain unsafe behavior. Thus, this research suggests an Importance-Dangerousness Analysis (IDA) technique so that potential risks due to unsafe behaviors of laborers working in the construction sector could be evaluated. In order to verify the applicability of the suggested technique, an actual survey was conducted, and the results of Importance-Performance Analysis (IPA) and IDA were compared with each other. It was found that, unlike IPA, unsafe behaviors that could pose potential risks were confirmed by IDA. Further, unsafe behaviors in the construction sector that should be urgently addressed were also studied. Finally, the IDA suggested in this research could contribute to effective construction safety management on-site by supporting the decisions of the safety manager based on the unsafe behavior analysis of construction laborers.

Understanding the Causation of Construction Workers’ Unsafe Behaviors Based on System Dynamics Modeling

AbstractThe unsafe behaviors of construction workers are often the immediate causes of construction accidents, but the underlying causation of such behaviors are not well understood. This research regards the management of construction safety as a system, and seeks to use system dynamics to demonstrate how the system influences construction workers in terms of unsafe behaviors. First, individual and environmental conditions that can lead to an unsafe behavior are identified through a holistic cognitive analysis and management conditions that affect such conditions are identified. Second, a system dynamics model for the causation of unsafe behaviors (SD-CUB) is developed to characterize the causal structure of the system. The SD-CUB model involves relationships among management, individuals, and environmental conditions that can eventually lead to workers’ unsafe behaviors. Third, a variety of model tests are conducted to build the confidence of the SD-CUB model. A five-week survey and observation on a bui...

Spatial analysis of construction accidents in Kampala, Uganda

Construction work is one of the leading sources of occupational injuries and fatalities in Uganda. This paper set out to investigate the causes of construction accidents in Kampala, Uganda using ordinary least squares regression and spatial regression modeling. A cross-sectional survey of 201 large-size building projects commissioned by Kampala City Council in 2008 was undertaken. Data collected from the survey was supplemented by building records from Kampala City Council, safety statistics from the Department of Occupational Safety and Health, and accident investigation reports. The injury rate for Kampala is deduced to be 3797 per 100,000 workers and the fatality rate is 84 per 100,000 workers. The three most prevalent causes of accidents in Kampala are mechanical hazards (i.e. struck by machines, vehicles, hand tools, cutting edges, etc.), being hit by falling objects and falls from height. Congestion, a phenomenon which arises when there is evidence of high building density amidst many fulltime workers on site, is discussed. Through spatial statistical analysis, construction accidents that occur at one location were found to be related to those that occur in the neighborhood. To mitigate accidents occurrence, policies on regulating working hours, provision of safety equipment, equipment maintenance and on standards of acceptable building densities are suggested.

Relationship between Unsafe Working Conditions and Workers’ Behavior and Impact of Working Conditions on Injury Severity in U.S. Construction Industry

AbstractUnsafe acts of workers (e.g., misjudgment or inappropriate operation) become the major root causes of construction accidents when they are combined with unsafe working conditions (e.g., work surface conditions or weather) on a construction site. The overarching goal of the research presented in this paper is to explore ways to prevent unsafe acts of workers and reduce the likelihood of construction accidents occurring. The study specifically aims to (1) understand the relationships between human behavior related and working condition related risk factors, (2) identify the significant behavior and condition factors and their impacts on accident types (e.g., struck by/against, caught in/between, falling, shock, inhalation/ingestion/absorption, or respiratory failure) and injury severity (e.g., fatality, hospitalized, or nonhospitalized), and (3) analyze the fundamental accident-injury relationship on how each accident type contributes to the injury severity. The study reviewed 9,358 accidents that o...