Identifying behaviour patterns of construction safety using system archetypes

Analysis on coupling dynamic effect of human errors in aviation safety

Human factors have increasingly been the leading cause of aircraft accidents. In most cases, human factors are not working alone, instead they are coupled with complex environment, mechanical factors, physiological and psychological factors of pilots, and organizational management, all of which form a complex aviation safety system. It is vital to investigate the coupling impact of human errors to avoid the occurrence of aviation accidents. In view that the Human Factors Analysis and Classification System (HFACS) provides a hierarchical classification principle of human errors in aviation accidents, and the System Dynamics (SD) approach is helpful to describe the risk evolution process, this paper establishes a hybrid HFACS-SD model by employing the HFACS and the SD approach to reveal the aviation human factors risk evolution mechanism, in which the HFACS is first used to capture the causal factors of human errors risk, and a coupling SD model is then built to describe the evolution of aviation human factors risk supported by historical data. The eigenvalue elasticity analysis is taken to identify critical loops and parameters that have a substantial impact on the system structural behavior, and the influence of parameters and loops is assessed. Simulation results show that the evolution trend of the accident rate can be replicated by the proposed HFACS-SD model, and the structural dominance analysis can efficiently identify critical loops and parameters. Simulation results further show that, with the recommended safety enhancement measures, the stability of the aviation system is increased, and thus lowering the overall accident rate.

Evaluation and Improvement of Employee Performance with respect to Health, Safety, and Environment (HSE) Factors: A Case of Complex Transport Construction Project

Risk control in complex transport construction is complicated due to the dangerous nature of high variation and unpredictability. Most of the current research analysis focuses on the health, safety, and environment (HSE) risk assessment and employee performance evaluation, which neglects the impact of HSE risks on employee performance. Consequently, this research develops a framework to evaluate employee performance and identify key factors affecting performance. The employee performance indicators and HSE indicators are established by reviewing related literature. Using data from questionnaires, an artificial neural network- (ANN-) based model of employee activity effectiveness is then developed to evaluate employee performance. Sensitivity analysis is implemented to determine the key factors affecting employee performance. The Hong Kong-Zhuhai-Macau Bridge, a large-scale cross-sea channel project, is taken as a case study for validation. The model results show that the employees are satisfied with the effect of HSE management in general, but the psychological stress they perceive becomes large. The indicators of risk control and employee participation positively impact employee performance, while job satisfaction has a negative impact on performance. These findings indicate that operators should pay more attention to employees' psychological perception of work and form a standardized process management and control plan to prevent cumbersome processes from increasing employees' workload. This study helps construction systems and managers to identify the areas of strengths and weaknesses in their HSE management. The research only focuses on the impact of HSE risks on managers' performance in the complex transport construction project. In the future, further engineering projects and employee performance in composite scenarios can be investigated to improve the overall productivity.

System dynamics simulation of occupational health and safety management causal model based on NetLogo

The occupational health and safety management factors of construction enterprises are critical influencing factors in their training management, and their causal principles are topics that warrant profound exploration. Drawing upon the conventional five factors, this study initially posited and authenticated a causal model among them, subsequently employing system dynamics on the NetLogo platform to dynamically simulate the model, and ultimately scrutinizing the interrelations and dynamic influence degree among the factors. The results show that the direct causes of management factors include human factors (weight coefficient of 0.583) and method factors (weight coefficient of 0.405), and environmental factors directly affect human factors (weight coefficient of 0.994), whereas material factors directly affect method factors (weight coefficient of 0.918). At the same time, it can be seen from the dynamic simulation results that the influence of human factors and method factors on management factors increases sharply in the nascent phase of the simulation cycle (the highest slope is .90), gradually decreases in the intermediary phase (the slope of the inflection point is .11), and is relatively stable in the final phase (the slope is less than 0.11). Three main conclusions have been drawn from this. Firstly, management factors are directly and positively affected by human factors and method factors respectively. Secondly, the interplay between diverse factors evinces a confluence of periodicity and exponential attributes. Thirdly, in each management cycle (set at 381 steps), the main focus is on controlling the causal factors in the early stages of management, with pivotal control points in steps 25 and 100, and the principal management factors comprising the management organization, operating procedures, and protective measures.

Sharing Incident Experiences: A Roadmap towards Collective Safety Information in the Norwegian Construction Industry

This paper is a study on sharing practices after incidents across organisations in the Norwegian construction industry as a means towards improvement of occupational safety. Interviews were performed with safety personnel from different actors, including clients, contractors, and designers. The findings show that several arenas for sharing of safety-related information across actors exist, however the sharing is limited, not structured, and occurs occasionally. Furthermore, the information is not widely shared across all actors in the industry for whom the information could be valuable, e.g., early phase actors. As a willingness to share and an excitement for new technology is present, the work goes on to propose how and where the industry can improve on information sharing after incidents to move towards interorganisational learning. A roadmap for the Norwegian construction industry is suggested for collective information sharing with a focus on technological and digital solutions.

Grounded Theory and Social Psychology Approach to Investigating the Formation of Construction Workers’ Unsafe Behaviour

There have been limited studies analyzing the causes of construction workers' unsafe behaviour from the social psychology perspective. Based on a Grounded Theory approach, this study first identified and defined seven coded categories related to workers' dangerous behaviour on construction sites. The original qualitative data were obtained from individual site interviews conducted with 35 construction professionals. These main categories were found connected to workers' status of safety awareness and sense of danger, which affected the type of unsafe behaviours, i.e., proactive, passive, or reactive behaviour. By further integrating social cognitive psychology theories into workers' behavioural decision-making process, the formation mechanism framework and diagram were developed to describe construction workers' unsafe behaviours based on the dynamic process of balancing the individual desires and perceived safety risks. This study advances the body of knowledge in construction safety behavioural management by performing in-depth theoretical analysis regarding workers' internal desires, activated by external scenarios and intervened by a personal safety cognition system, which could result in different motivations and various behavioural outcomes. It is argued that safety cognition serves as a mediated moderation system affecting behavioural performance. Practical suggestions on developing a proper safety management system incorporating safety education in guiding construction workers' site behaviours are presented.

Exploring Empirical Rules for Construction Accident Prevention Based on Unsafe Behaviors

This paper is aimed at exploring rules for construction accident prevention based on unsafe behaviors. The literature review demonstrates a clear connection between construction accident prevention and unsafe behaviors, followed by a 2-year field investigation resulting in 2207 observations based on convenient sampling with 95% confidence and 5% limit of errors in the 50–50 category. There are 80.43% unsafe behaviors categorized into “Regulations for the Occupational Safety and Health Equipment and Measures”, where there are 66.37% of regulations and law VII violations, linking fall prevention with the most cases (94.48%) of Fall Protection and Structure Strengthening. The Apriori yields 13 association rules, where the top 3 rules show that 44.11% of the Passage and lighting category is linked to construction equipment inspections; 29.41% of the high-pressure gas category is linked to construction equipment inspections; 100% of the fire prevention category is linked to fire protection unsafe behavior. The findings clarify the association rules that can prevent workers from accidents in construction sites.

Flow-down of safety from general contractors to subcontractors working on commercial construction projects

Small and medium construction firms have high injury rates but lack resources to establish and maintain effective safety programs. General contractors with exemplary safety programs may serve as intermediaries to support development of smaller firm's safety programs. The purpose of this study was to examine the flow-down influence of general contractors' safety programs on the safety climate and safety behaviors among workers employed by small and medium sized subcontractors. This study collected workers' perception of safety climate and safety behaviors while working on projects with general contractors with exemplary safety programs and other general contractors. We also documented the safety program policies and practices of subcontractors, and recorded the changes in safety policies required from general contractors with exemplary programs. We examined differences in safety program changes between small and medium sized subcontractors. Results showed workers perceived general contractors with exemplary safety programs had stronger safety climates than other general contractors. Smaller subcontractors had less robust safety programs with fewer safety elements than larger subcontractors, and therefore, many of the smaller subcontractors had to adopt more safety policies and practices to work for general contractors than large subcontractors. These findings suggest that general contractors with robust safety programs can serve as intermediaries and influence the development of the safety programs of small sized firms. Future work will need to determine if smaller firms eventually adopt safety policies and practices as part of their permanent safety program.

A Research Framework of Mitigating Construction Accidents in High-Rise Building Projects via Integrating Building Information Modeling with Emerging Digital Technologies

The construction of high-rise building projects is a dangerous vocation due to the uniqueness and nature of the activities, as well as the complexity of the working environment, yet safety issues remain crucial in the construction industry. Digital technologies, such as building information modeling (BIM), have been identified as valuable tools for increasing construction productivity, efficiency, and safety. This research aimed to mitigate the accident safety factors in high-rise building projects via integrating BIM with emerging digital technologies in the construction industry, such as photogrammetry, GPS, RFID, augmented reality, (AR), virtual reality (VR), and drone technology. Qualitative research was conceived in the ground theory approach. Forty-five online interviews with construction stakeholders and qualitative data analysis were carried out using the NVivo 11 software package. According to the findings, interviewees were more motivated to use photogrammetry and drone technologies in high-rise building projects in order to increase construction safety. Positive, negative, and neutral attitudes about BIM integration with emerging digital technologies were discovered. Furthermore, a research framework was developed by consolidating research findings that articulate the measures and future needs of BIM integration with other digital technologies to mitigate construction accidents in high-rise building projects. The framework also renders practical references for industry practitioners towards effective and safer construction.

A Decision Method for Construction Safety Risk Management Based on Ontology and Improved CBR: Example of a Subway Project

Early decision-making and the prevention of construction safety risks are very important for the safety, quality, and cost of construction projects. In the field of construction safety risk management, in the face of a loose, chaotic, and huge information environments, how to design an efficient construction safety risk management decision support method has long been the focus of academic research. An effective approach to safety management is to structuralize safety risk knowledge, then identify and reuse it, and establish a scientific and systematic construction safety risk management decision system. Based on ontology and improved case-based reasoning (CBR) methods, this paper proposes a decision-making approach for construction safety risk management in which the reasoning process is improved by integrating a similarity algorithm and correlation algorithm. Compared to the traditional CBR approach in which only the similarity of information is considered, this method can avoid missing important correlated information by making inferences from multiple sources of information. Finally, the method is applied to the safety risks of subway construction for verification to show that the method is effective and easy to implement.

Knowledge transfer for occupational health and safety: Cultivating health and safety learning culture in construction firms

Within the last decades the incidence of workspace injuries and fatalities in the UK construction industry has declined markedly following the developments in occupational health and safety (OHS) management systems. However, safety statistics have reached a plateau and actions for further improvement of OHS management systems are called for. OHS is a form of organizational expertise that has both tacit and explicit dimensions and is situated in the ongoing practices. There is a need for institutionalization and for the transfer of knowledge across and along construction supply chains to reduce OHS risks and facilitate cultural change. The focus of this article is the factors that facilitate OHS knowledge transfer in and between organizations involved in construction projects. An interpretative methodology is used in this research to embrace tacit aspects of knowledge transfer and application. Thematic analysis is supported by a cognitive mapping technique that allows understanding of interrelationships among the concepts expressed by the respondents. This paper demonstrates inconsistency in OHS practices in construction organizations and highlights the importance of cultivating a positive safety culture to encourage transfer of lessons learnt from good practices, incidents, near misses and failures between projects, from projects to programmes and across supply chains. Governmental health and safety regulations, norms and guidelines do not include all possible safety issues specific to different working environments and tied to work contexts. The OHS system should encourage employees to report near misses, incidents and failures in a 'no-blame' context and to take appropriate actions. This research provides foundation for construction project practitioners to adopt more socially oriented approaches towards promoting learning-rich organizational contexts to overcome variation in the OHS and move beyond the current plateau reached in safety statistics.

Modeling the effects of production pressure on safety performance in construction projects using system dynamics

INTRODUCTION

Construction incidents occur due to system failures, not due to a single factor such as unsafe behavior or condition. Therefore, construction safety should be investigated using a systematic view capable of illustrating the complex nature of incidents. Construction projects are also often behind their planned schedule and suffer from various pressures caused by contractual deadlines or clients. Previous studies demonstrated that such pressures negatively affect safety performance; however, the process of how production pressure influences safety performance is not fully investigated.

METHOD

The present research aimed to understand the feedback mechanism of how production pressure interactively affects safety performance and safety-related managerial components in a construction project. Ground theory method (GTM) is used to create a conceptual causal loop diagram that shows the relationship between incident rate and other variables such as labor hour, actual and planned progress, safety climate, rework, and safety training. Moreover, a power plant construction project was used as a case study to practically investigate the conceptual model; a case study is employed to build a System Dynamics (SD) model. The simulation model was then validated using behavior reproduction and sensitivity analysis.

RESULTS

The results of the inequality statistics show that the simulation model can be used to forecast trends in the incident rate.

Risk Profiling from the European Statistics on Accidents at Work (ESAW) Accidents' Databases: A Case Study in Construction Sites

The number of accidents and victims in the construction sector has not decreased significantly despite the increasingly stricter laws and regulations. The analysis of accidents, as well as their root causes and determinants can certainly contribute to the development of more effective preventive interventions. The present study proposes a methodology for the analysis and synthesis of data provided by accidents statistics with the goal of defining specific risk profiles based on the accidents determinants, their variables, and how they interact with one another in influencing the occurrence of an accident. For this purpose, a procedure capable of extracting this type of information from the European Statistics on Accidents at Work (ESAW) database was developed. In particular, data processing and aggregation are performed by means of the synergic use of the Matrix of Descriptors (MoD) and cluster analysis. To validate such a procedure, the analysis of fatalities due to electrical shocks was carried out. The results achieved allowed us to elicit valuable information for both safety managers and decision makers. The proposed methodology can facilitate a systemic analysis of accidents databases reducing the difficulties in managing reports and accident statistics.

System dynamics applications to injury and violence prevention: a systematic review

Purpose of review

System dynamics (SD) is an approach to solving problems in the context of dynamic complexity. The purpose of this review was to summarize SD applications in injury prevention and highlight opportunities for SD to contribute to injury prevention research and practice.

Recent findings

While SD has been increasingly used to study public health problems over the last few decades, uptake in the injury field has been slow. We identified 18 studies, mostly conducted in the last 10 years. Applications covered a range of topics (e.g., road traffic injury; overdose; violence), employed different types of SD tools (i.e., qualitative and quantitative), and served a variety of research and practice purposes (e.g., deepen understanding of a problem, policy analysis).

Summary

Given the many ways that SD can add value and complement traditional research and practice approaches (e.g., through novel stakeholder engagement and policy analysis tools), increased investment in SD-related capacity building and opportunities that support SD use are warranted.

Preliminary Human Safety Assessment (PHSA) for the Improvement of the Behavioral Aspects of Safety Climate in the Construction Industry

Occupational safety in the construction industry still represents a relevant problem at a global level. In fact, the complexity of working activities in this sector requires a comprehensive approach that goes beyond normative compliance to guarantee safer working conditions. In particular, empirical research on the factors influencing the unsafe behavior of workers needs to be augmented. Thus, the relationship between human factors and safety management issues following a bottom-up approach was investigated. In particular, an easy-to-use procedure that can be used to better address workers’ safety needs augmenting the company’s safety climate and supporting safety management issues was developed. Such an approach, based on the assessment of human reliability factors, was verified in a real case study concerning the users of concrete mixer trucks. The results showed that the majority of human failures were action and retrieval errors, underlining the importance of theoretical and practical training programs as a means to improve safety behavior. In such a context, information and communication activities also resulted beneficially to augment the company’s safety climate. The proposed approach, despite its qualitative nature, allows a clearer understanding of workers’ perceptions of hazards and their risk-taking behavior, providing practical cues to monitor and improve the behavioral aspects of safety climate. Hence, these first results can contribute to augmenting safety knowledge in the construction industry, providing a basis for further investigations on the causalities related to human performances, which are considered a key element in the prevention of accidents.

Developing safety archetypes of construction industry at project level using system dynamics

INTRODUCTION

Safe behavior and work conditions are a major concern in construction projects. However, accidents occur due to system failures, not a single factor such as unsafe behavior or condition. Construction safety should be investigated by a systematic view capable of illustrating the complex nature of accidents.

METHOD

The present research aims to detect and categorize behavior patterns recurring in construction safety management continuously. Content analysis and ground theory method (GTM) were adopted to achieve the study objectives. In total, 90 articles were reviewed to explore the factors influencing safety in construction projects all over the world. Furthermore, 20 interviews were conducted on participants with rich experience in construction health and safety. Four archetypes were identified from data collection process, including delay in design, number of subcontractors, cost and safety of project, and supervisors and safety. Each archetype is completely discussed at different steps of dynamic complexity, behavior over time, and the leverage point to show how to deal with the archetype.

Factors influencing unsafe behaviors: A supervised learning approach

Despite its potential, the use of machine learning in safety studies had been limited. Considering machine learning's advantage in predictive accuracy, this study used a supervised learning approach to evaluate the relative importance of different cognitive factors within the Theory of Reasoned Action (TRA) in influencing safety behavior. Data were collected from 80 workers in a tunnel construction project using a TRA-based questionnaire. At the same time, behavior-based safety (BBS) observation data, % unsafe behavior, was collected. Subsequently, with the TRA cognitive factors as the input attributes, six widely-used machine learning algorithms and logistic regression were used to develop models to predict % unsafe behavior. The receiver operating characteristic (ROC) curves show that decision tree provides the best prediction. It was found that intention and social norms have the biggest influence on whether a worker was observed to work safely or not. Thus, managers aiming to improve safety behaviors need to pay specific attention to social norms in the worksite. The study also showed that a TRA survey can be used to extend a BBS to facilitate more effective interventions. Lastly, the study showed that machine learning algorithms provide an alternative approach for analyzing the relationship between the cognitive factors and behavioral data.

Does company size matter? Validation of an integrative model of safety behavior across small and large construction companies

INTRODUCTION

Previous safety climate studies primarily focused on either large construction companies or the construction industry as a whole, while little is known about whether company size has significant effects on workers' understanding of safety climate measures and relationships between safety climate factors and safety behavior. Thus, this study aims to: (a) test the measurement equivalence (ME) of a safety climate measure across workers from small and large companies; (b) investigate if company size alters the causal structure of the integrative model developed by Guo, Yiu, and González (2016).

METHOD

Data were collected from 253 construction workers in New Zealand using a safety climate measure. This study used multi-group confirmatory factor analyses (MCFA) to test the measurement equivalence of the safety climate measure and structure invariance of the integrative model.

RESULTS

Results indicate that workers from small and large companies understood the safety climate measure in a similar manner. In addition, it was suggested that company size does not change the causal structure and mediational processes of the integrative model.

CONCLUSIONS

Both measurement equivalence of the safety climate measure and structural invariance of the integrative model were supported by this study. Practical applications: Findings of this study provided strong support for a meaningful use of the safety climate measure across construction companies in different sizes. Safety behavior promotion strategies designed based on the integrative model may be well suited for both large and small companies.

Strategies for improving safety performance in construction firms

Over the years many prevention management practices have been implemented to prevent and mitigate accidents at the construction site. However, there is little evidence of the effectiveness of individual or combined practices used by companies to manage occupational health and safety issues. The authors selected a sample of 1180 construction firms and 221 individual practices applied in these companies to analyze their effectiveness reducing injury rates over a period of four years in Chile. Different methods were used to study this massive database including: visual analyses of graphical information, statistical analyses and classification techniques. Results showed that practices related to safety incentives and rewards are the most effective from the accident rate viewpoint, even though they are seldom used by companies; on the other hand, practices related to accidents and incidents investigation had a slight negative impact on the accident rate because they are frequently used as a reactive measure. In general, the higher the percentage of prevention practices implemented in a strategy, the lower the accident rate. However, the analysis of the combined effect of prevention practices indicated that the choice of the right combination of practices was more important than just the number of practices implemented.