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Drawing on the findings of coronial investigations, this research aimed to investigate the circumstances and causes of fatal incidents involving plant in the Australian construction industry. The analysis sought to provide greater insight into how and why fatal incidents occur and to inform recommendations for the prevention of fatal incidents involving plant.

Fatal incidents involving plant were identified from the National Coronial Information System. In each case, the decedent was a construction worker and the incident occurred at a construction worksite. A systemic incident causation model developed by Loughborough University informed the identification of originating influences, shaping factors and immediate circumstances in each incident.

Most of the incidents involved excavators, trucks and cranes, and different classifications of plant were associated with different types of incident. The most common incident types involved people being run over by moving plant or struck by a moving object. Site layout and unsafe actions were the most commonly identified immediate circumstances. Shaping factors included site constraints and the design of plant, particularly visibility issues relating to “blind spots”. Originating influences included the design of the permanent work and construction process.

The research highlights the usefulness of systemic incident causation models, such as the “Loughborough Model”, in the analysis of the causes of fatal incidents involving plant in the construction industry.

The results indicate that plant‐related fatalities occur as a result of a complex interplay of different causes, some of which are “upstream” of the construction work. The use of innovative new site planning methods and active monitoring technologies to reduce the risk of collisions between people and plant should be considered.

The analysis provides a more detailed qualitative analysis of the causes of fatal incidents involving excavators than would be possible using national compensation data, which restricts analysis to a classification of the mechanism and agency of injury.

The paper analyses the nature and causes of fatal incidents involving excavators occurring in the Australian construction industry. A three-level incident causation model developed by researchers at Loughborough University forms the theoretical framework for this analysis, which seeks to identify immediate circumstances, shaping factors and originating influences in selected incidents.

Case study incidents were identified from the National Coronial Information System database. These incidents were subjected to content analysis to identify causal factors.

Ten cases were analysed in total. In all of these cases immediate circumstances could be identified. These included the use of unsafe work methods and the condition, suitability or useability of plant. In several cases shaping factors, such as communication between work-team members and the design of work processes, were identified as likely contributors to the incidents. In none of the cases could originating influences be identified.

The research was limited by the relatively small number of cases for which detailed investigation reports were available and the fact that, for the most part, the reports focused on the immediate circumstances surrounding the incidents.

The circumstances of the fatal incidents in Australia are similar to those reported in the UK and the USA and the identified causes have known safety solutions. The persistence of these incidents in the Australian construction industry suggests that there may be underlying reasons why known safety solutions are not implemented. Further in-depth analysis of incident causes may help to identify organisational and/or cultural causes of incidents involving excavators.

The analysis provides a more detailed qualitative analysis of the causes of fatal incidents involving excavators than would is possible using national compensation data, which restricts analysis to a classification of the mechanism and agency of injury.

Quantifiable data produced in a national report by the Environment Agency of England and Wales entitled Water Pollution Incidents in England and Wales 1997 and published by the Stationery Office in 1998, identifies over 3,723 substantiated pollution incidents across England and Wales in 1997. Within the generic sector classed as “Industry” the construction industry was the most frequent polluter responsible for 22 percent of all substantiated water‐related pollution incidents in that sector. The report also identified that a significant number (28 percent) of all substantiated pollution incidents across England and Wales are directly attributable to mineral‐based fuels and oils, many of which are used extensively within the construction industry. This paper seeks to locate the possible causes and effects for some of that oil‐based pollution, discusses the issues and identifies a unique and radical client‐motivated solution within the UK to reduce and mitigate the undesirable impacts upon the environment. Evidence produced by the oil industry shows the enormous amount of one particularly aggressive pollutant – hydraulic oil – which remains annually, unaccounted for. Hydraulic oil is used in most tracked earthmoving machinery; the sort of machinery most closely associated with construction work carried out near to watercourses. Biodegradable hydraulic oil is much more considerate to the environment, but is more expensive and not usually installed in new plant and machinery. The paper argues that on a life cycle basis the use of biodegradable oil is viable and feasible and that there are many external factors that make its usage desirable.

With proper design and work planning, falls through fragile skylights are preventable. Skylights pose a hazard to workers when their work tasks for operations, maintenance and repair require them to be on roofs. The National Institute of Occupational Health and Safety produced guidelines and special alerts to address the dangers that are present around skylights, and the Occupational Safety and Health Administration regulations have prescriptive requirements for work performed around skylights, and yet incidents still occur. The purpose of this study is to investigate and raise awareness for the causality of the incidents involving skylights in the USA.

The authors investigated and analyzed 204 incidents involving skylights recorded by the Bureau of Labor Statistics to characterize their nature and to determine any correlation with the roof environment or the nature of the work performed. Using Google Earth and Google Maps roof geometry, proximity of skylights to roof edge and rooftop mechanical equipment was determined.

The majority of falls through skylights occur during roof maintenance and repair activities. Falls through skylights are underreported. Because of a general lack of good design to reduce or eliminate the risk of falling through skylights, facility managers carry the burden to properly assess work and access on roofs where fragile skylights are present.

The phenomenon of falling through skylights was made aware on a national level in the USA in 1989; however, little has been done from a design and planning perspective to reduce these incidents. This paper presents a unique perspective on the role of facility managers in understanding the hazards associated with roof maintenance near skylights.

Near misses are important references for the construction industry to move toward zero injuries, and are of great significance in reducing accidents and improving safety education. To fully improve the construction industry's understanding and standardize the management process of near-miss events, this paper describes a systematic review of the research front and intellectual basis of near-miss events based on scientometric technique and CiteSpace.

The authors reviewed and summarized the research wave and definitions of near-miss events in construction. The science mapping approach is used to conduct quantitative analyses of 120 relevant articles published between 2009 and 2019. Three research themes are identified via author analysis, keyword analysis and co-citation analysis: the construction of near-miss management systems, near-miss events research and characteristic research.

It is found that improving the data collection method to maximize the quality of near-miss reports, optimizing and verifying the event analysis model considering the characteristics of near-miss events in construction, establishing a more comprehensive framework for the analysis of near-miss events and building a highly inclusive technology integration platform are the four main development directions for the future.

According to Heinrich's law, incidents are mainly blamed on near-miss events such as workers' unsafe behaviors. Due to the complexity and variability of the construction site, near-miss events in construction may have different features. This article helps promote the understanding of near misses in academia, standardizing the management process of near-miss events, which is conducive to mining the potential value of such events in practice. Some insights into the research front and the intellectual base of near-miss research in construction are proposed.

Central to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management applications over the last decades, construction industry still accounts for a considerable percentage of all workplace fatalities across the world. This study aims to predict occupational accident outcomes based on national data using machine learning (ML) methods coupled with several resampling strategies.

Occupational accident dataset recorded in Turkey was collected. To deal with the class imbalance issue between the number of nonfatal and fatal accidents, the dataset was pre-processed with random under-sampling (RUS), random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). In addition, random forest (RF), Naïve Bayes (NB), K-Nearest neighbor (KNN) and artificial neural networks (ANNs) were employed as ML methods to predict accident outcomes.

The results highlighted that the RF outperformed other methods when the dataset was preprocessed with RUS. The permutation importance results obtained through the RF exhibited that the number of past accidents in the company, worker's age, material used, number of workers in the company, accident year, and time of the accident were the most significant attributes.

The proposed framework can be used in construction sites on a monthly-basis to detect workers who have a high probability to experience fatal accidents, which can be a valuable decision-making input for safety professionals to reduce the number of fatal accidents.

Practitioners and occupational health and safety (OHS) departments of construction firms can focus on the most important attributes identified by analysis results to enhance the workers' quality of life and well-being.

The literature on accident outcome predictions is limited in terms of dealing with imbalanced dataset through integrated resampling techniques and ML methods in the construction safety domain. A novel utilization plan was proposed and enhanced by the analysis results.

The purpose of this paper is to propose a practical framework to measure the safety performance of workers in the Indian construction industry. The key safety performance indicators are identified and ordered on the premise that the higher order assignment of an indicator implies a strong indication of an effective safety performance.

Various indicators of safety performance in the construction industry were identified from extant literature review combined with author's personal viewpoint. The identified variables were inquired for appropriateness for the Indian construction scenario by consultation with experts. Fuzzy Technique for order preference by similarity to ideal solution (TOPSIS) technique was considered for the ranking of the indicators from most to least important.

The most important highlight of the study was the importance of the role of management by participating in informing workers about the safety rules and compliance toward safety measures. Proper and timely safety training to the workers and equipping them with sophisticated safety equipment for daily activities is perceived to be highly important in ensuring a safe and healthy workplace environment. Controlling the absenteeism rate reduces the burden of extra work on the employees, thereby, encouraging safe work-related behavior.

Senior management should make safety induction programs compulsory at the time of joining of the employees. The guidelines for safety practices, rules and information about the safety equipment should be properly documented and arranged in safety manuals. Periodical drills involving visual demonstration of the safety practices should be followed to ensure safety at workplace.

Given the growing concern about employees' well-being, numerous researchers have investigated the causes and effects of occupational stress. However, a review study on identifying existing research topics and gaps is still deficient in the extant literature. To fill this gap, this review study aims to present a bibliometric and science mapping approach to review the state-of-the-art journal articles published on occupational stress in the construction industry.

A three-fold comprehensive review approach consisting of bibliometric review, scientometric analysis and in-depth qualitative discussion was employed to review 80 journal articles in Scopus.

Through qualitative discussions, mainstream research topics were summarized, research gaps were identified and future research directions were proposed as follows: versatile stressors and stress model; an extended subgroup of factors in safety behavior; adaptation of multiple biosensors and bio-feedbacks; evaluation and comparison of organizational stress interventions; and incorporation of artificial intelligence and smart technologies into occupational stress management in construction.

The findings of this review study present a well-rounded framework to identify the research gaps in this field to advance research in the academic community and enhance employees' well-being in construction.

This study highlights the findings of an empirical study to investigate waste factors (WFs) affecting the performance and delivery of construction projects in developing countries. The objectives of this study are to identify non-physical WFs in developing nations and rank the identified factors based on their degree of influence on the key performance indicators (KPIs) of cost, quality and time.

In total, 34 WFs were identified through a detailed literature review and consolidated using semi-structured interviews with construction practitioners. The statistical analysis involved a normality test using the Shapiro–Wilk test to determine if sample data have been drawn from a normally distributed population, ranking the WFs using the Frequency Index (FI), Severity Index (SI) and Importance Index (IMPI), ranking the WFs based on their effect on the project KPIs of cost, quality and time, and identify clustering structures for the identified WFs to using factor analysis (FA).

The results revealed ineffective planning and scheduling, rework/repair of defective work and resource quality problems (human, material and equipment) as the three most important WFs affecting construction projects. The factor analyses showed that WFs can be grouped into five interrelated components, suggesting the need for integrated and holistic strategies to overcome the identified WF.

Understanding the effects of WFs on construction projects is a first step towards designing holistic solutions to ensuring projects deliver value to the clients and other stakeholders. The findings of this study provide direction to construction practitioners on where to focus appropriate strategies to manage the identified WFs effectively and, therefore, improve the productivity of construction projects.

This study provides the first holistic analysis of WFs affecting the productivity of construction projects in developing countries.