Construction Safety Performance Research Articles

How Can Conflicts with Supervisors or Coworkers Affect Construction Workers’ Safety Performance on Site? Two Cross-Sectional Studies in North America

A safety plateau in the construction industry has been reported in the US and Canada, which has prompted researchers to seek new factors affecting construction safety performance. Tapping into advancements in the theory of human and organizational behaviors can yield valuable new perspectives. Therefore, by leveraging the advancement of the Job Demand Control Support model in the field of occupational safety and health, this paper firstly tested the impact of one newly added hindrance stressor (i.e., interpersonal conflicts on construction sites) by researchers on organizational behaviors on the safety performance of construction workers, based on two cross-sectional studies in the US and Canada. Differentiations were made between conflicts with supervisors and conflicts with coworkers. One personal resource factor, i.e., individual resilience, was also considered in this paper. A “causal” chain that shows the mitigation impact of individual resilience on conflicts with supervisors or coworkers, and the adverse impact of conflicts with supervisors or coworkers, on unsafe events were found to hold true for both US and Canadian construction sites, based on the results from measurement invariance tests and structural equation modelling. Recommendations regarding how to improve construction workers’ individual resilience and reduce interpersonal conflicts on site, thereby reducing safety incidents on site, are provided.

Development of a Framework for Risk-Based Integrated Safety Audit to Enhance Construction Safety Performance

Presently, there is a notable surge in infrastructure development, leading to a heightened occurrence of accidents within the construction sector. This trend has positioned the construction industry as one of the most accident-prone areas compared to other sectors. This suggests that the current construction safety audit procedures have not proven effective in preventing accidents. Typically, audits are conducted primarily during the construction phase, with infrequent assessments during the design phase. According to the Szymberski theory, actions taken during the design phase significantly influence the occurrence of accidents more than those taken during construction. Previous research has discussed a lot about safety management systems. However, it has not discussed how to assure the quality of its implementation. Considering this, the research aims to (a) identify the processes, elements, activities, sub-elements, objectives, criteria, and risks associated with construction safety audits and (b) formulate an integrated, risk-based audit process covering both the design and construction phases. This qualitative research employed the Delphi method to gather insights from construction safety experts, and the developed audit process utilized a risk management approach. The resulting audit process integrates principles from ISO 19011:2018 and Regulation of the Minister of Public Works and Housing Number 10 of 2021. The findings revealed 34 activities in audit program management, 34 activities in audit implementation, and 32 sub-elements in audit criteria. These components are incorporated into a comprehensive construction safety audit framework, organizing audit processes, activities, and criteria. This framework underscores that improving construction safety performance is not solely confined to the construction phase but extends to the design phase as well. The audit results serve as a foundation for continuous improvement, aiding in enhancing safety performance and preventing accidents within the construction industry. Doi: 10.28991/CEJ-2024-010-03-08 Full Text: PDF

A Resilience Approach to Improving Safety Performance in Construction

A Resilience Approach to Improving Safety Performance in Construction

Unmanned Aerial Systems and Deep Learning for Safety and Health Activity Monitoring on Construction Sites.

Construction is a highly hazardous industry typified by several complex features in dynamic work environments that have the possibility of causing harm or ill health to construction workers. The constant monitoring of workers' unsafe behaviors and work conditions is considered not only a proactive but also an active method of removing safety and health hazards and preventing potential accidents on construction sites. The integration of sensor technologies and artificial intelligence for computer vision can be used to create a robust management strategy and enhance the analysis of safety and health data needed to generate insights and take action to protect workers on construction sites. This study presents the development and validation of a framework that implements the use of unmanned aerial systems (UASs) and deep learning (DL) for the collection and analysis of safety activity metrics for improving construction safety performance. The developed framework was validated using a pilot case study. Digital images of construction safety activities were collected on active construction sites using a UAS, and the performance of two different object detection deep-learning algorithms/models (Faster R-CNN and YOLOv3) for safety hardhat detection were compared. The dataset included 7041 preprocessed and augmented images with a 75/25 training and testing split. From the case study results, Faster R-CNN showed a higher precision of 93.1% than YOLOv3 (89.8%). The findings of this study show the impact and potential benefits of using UASs and DL in computer vision applications for managing safety and health on construction sites.

Analysis of Relation Between Risk-Based Work Breakdown Structure (WBS) on Integrated Design and Construction Works of Design and Build Contract on Mechanical and Electrical Works of High Rise Building for Improving Safety Performance

The construction industry has had the highest accident rate worldwide for decades. Identifying risks as early as feasible during the pre-construction or design phase is essential to preventing construction accidents. To generate a structured list of risks, a Work Breakdown Structure (WBS) is used to identify risks. Although numerous studies have proposed using Work Breakdown Structure (WBS) to identify risks, no one has analyzed the relationship between Work Breakdown Structure (WBS) and risk to reduce construction accidents. Consequently, this study aimed to investigate the impact of Work Breakdown Structure (WBS) risk during the design and construction phases on construction safety performance. The analysis of relationships will be conducted using statistical methodologies. The study's findings will demonstrate that Work Breakdown Structure (WBS) risk affects construction safety performance.

Evaluating Building Construction Safety Performance in Different Regions in China

This article employs a three-stage slack-based data envelopment analysis (SBM-DEA) model to evaluate the construction safety performance (CSP) of 30 provinces and cities in China, focusing on enhancing the sustainable development of construction safety in the industry, in line with the concept of sustainable development. The research findings indicate that the supervision environment of each province and city exerts a more substantial influence on the sustainable development of construction safety compared with the level of socio-economic development. Significant changes have been observed in the regional distribution of construction safety management levels within the construction industry by eliminating the impact of economic development, the supervision environment, and random errors. The original pattern of “East > West > Central > Northeast” has shifted to “East > Central > Northeast > West.” Moreover, it has been discovered that high-efficiency values of safety performance in certain provinces and cities are partially attributed to external environmental (EE) pressure. In contrast, low-efficiency values cannot be solely attributed to their lack of willingness to implement safety management. Finally, the article proposes strategies, including government policy-led approaches, technology prioritization, and management prioritization, to enhance the sustainable development of construction safety in the construction industry based on the internal safety performance of each province.

Influence of Learning from Incidents, Safety Information Flow, and Resilient Safety Culture on Construction Safety Performance

Influence of Learning from Incidents, Safety Information Flow, and Resilient Safety Culture on Construction Safety Performance

Development of the Knowledge Base Information System for Integrated Risk-Based Audit of High-Rise Buildings Through Design-Build Method to Improve Construction Safety Performance

Development of the Knowledge Base Information System for Integrated Risk-Based Audit of High-Rise Buildings Through Design-Build Method to Improve Construction Safety Performance

Formal evaluation of construction safety performance metrics and a case for a balanced approach

Introduction: Measuring safety performance is crucial to making informed decisions that improve construction safety management. Traditional approaches to construction safety performance measurement primarily focus on injury and fatality rates, but researchers have recently proposed and tested alternative metrics such as safety leading indicators and safety climate assessments. Although researchers tend to extol the benefits of alternative metrics, they are studied in isolation and the potential weaknesses are rarely discussed, leaving a critical gap in knowledge. Method: To address this limitation, this study aimed to evaluate existing safety performance against a set of pre-determined criteria and explore how multiple metrics may be used together to optimize strengths and offset weaknesses. For a well-rounded evaluation, the study included three evidence-based assessment criteria (i.e., the extent to which the metric is predictive, objective, and valid) and three subjective criteria (i.e., the extent to which each metric is clear, functional, and important). The evidence-based criteria were evaluated using a structured review of existing empirical evidence in literature, while the subjective criteria were evaluated using expert opinion solicited through the Delphi method. Results: The results revealed that no construction safety performance measurement metric is strong in all evaluation criteria, but many weaknesses may be addressed through research and development. It was also demonstrated that combining multiple complementary metrics may result in a more complete evaluation of the safety systems because multiple metrics offset respective strengths and weaknesses. Practical Applications: The study provides a holistic understanding of construction safety measurement that may guide safety professionals in their selection of metrics and assist researchers who seek more reliable dependent variables for intervention testing and safety performance trending.

Knowledge Base Development of Knowledge Management Audit Process for High-Rise Building Projects with Design and Build Contracts to Improve Construction Safety Performance

Knowledge Base Development of Knowledge Management Audit Process for High-Rise Building Projects with Design and Build Contracts to Improve Construction Safety Performance

The impact of COVID-19 pandemic on construction safety in China and the U.S.: A comparative study

Many studies indicated that the COVID-19 pandemic had significant impacts on construction safety. However, the studies had differing views on whether the pandemic increased or decreased construction safety performance. Furthermore, past studies did not adopt a comparative time series approach to evaluate the impact of the pandemic on construction safety. Thus, this study explores the differences in the impact of the COVID-19 pandemic on construction safety in China and the United States. This study used SciNet to forecast the number of construction accidents without the pandemic. Subsequently, the forecast was compared with the actual number of accidents since the outbreak, and the analysis showed a reduced number of construction accidents during the pandemic. However, there were minimal changes and even a slight worsening of fatality rates. Moreover, the correlation analyses showed that the effect of the pandemic on construction safety was weak and lagging. Construction safety was significantly affected by the pandemic in China, and the impact is relatively rapid. In comparison, outbreaks did not have a major impact on construction safety in the U.S. in the early stage. Since the pandemic is still raging worldwide, this research helps governments or project stakeholders formulate more targeted and data-driven safety countermeasures to improve construction safety during the crisis. The study also helps nations respond to future pandemics and crises to prevent adverse effects on construction safety.

Identification of Building Architectural Work Construction Safety Risks

In Indonesia, the rate of workplace accidents in the construction industry is still relatively high. Unsupervised work activities, which result in the disregard of risk control for these work activities, are one of the factors contributing to the high rate of workplace accidents. Therefore, if WBS can be used to design construction safety planning, then all dangerous operations can be monitored. This study will employ the quantitative technique as its methodology. The WBS for architectural construction safety planning will be developed through case study work on the High Prosecutor's Office Building for DKI Jakarta Province and based on the Minister of Public Works and Public Housing Regulation No. 10 of 2021. This study aims to identify the risks in each architectural work activity using the WBS and produce a good construction safety management strategy in the form of a risk assessment for each architectural work activity to improve construction safety performance (K2) in building construction projects in Indonesia.

PREDICTORS TO INCREASE SAFETY TECHNOLOGY ADOPTION IN CONSTRUCTION: AN EXPLORATORY FACTOR ANALYSIS FOR MALAYSIA

Accidents and injuries continue to be major problems in the construction industry despite persistent endeavours over the years to improve health and safety management. Novel approaches using emerging technologies can enhance construction safety performance. Given their limited adoption and lack of empirical evidence in the context of developing countries, this paper examines the predictors influencing the successful adoption of safety technologies in the construction industry. Using a survey questionnaire involving 133 Malaysian construction professionals, the significance of the predictors is prioritised. A factor analysis is used to reduce the predictors involved into a fewer number of dimensions. The most influential predictors are presented. Four underlying dimensions of the surveyed predictors are uncovered, comprising organisational commitment/technology orientation, supporting technological attributes, personal perception/performance expectancy and government support. The rate of technology implementation to improve safety risk mitigation in construction is still limited. By taking cognisance of the critical influential predictors involved, the adoption level of safety technology could be raised. This paper bridges the identified knowledge gap regarding the dimensionality of safety technology adoption predictors in construction, with findings that shed new light on the factors influencing technology adoption in a developing country to stimulate technological innovations to streamline construction safety.

Investigating the impact of emerging technologies on construction safety performance

PurposeConstruction safety is heavily affected by using new technologies in this growing trend of technology adoption. Especially, safety performance is enhanced through the utilization of some effective technologies such as artificial intelligence, virtual reality, BIM and wearable devices. Therefore, the main purpose of this study is to investigate the influence of emerging technologies on construction safety performance and quantify the relationship between those. The proposed components of emerging technologies are BIM, GIS, VR, RFID, AI, ML, eye tracking and serious games and wearable devices, whereas the dimensions of construction safety performance are safety planning, safety training, safety inspection and monitoring, safety audits and reviews and safety leadership.Design/methodology/approachA structural model was composed consisting of emerging technologies and safety performance indicators. Then, a questionnaire was designed and administered to construction professionals, and data from 167 projects were analyzed using structural equation modeling. The data were analyzed by using software, called SPSS AMOS.FindingsThe analysis of the structural model proves that there is a positive and significant relationship between emerging technologies and construction safety performance. Moreover, the factor loadings for each factor were found to be high indicating a good representation of the construct by the components developed. Among the technologies, BIM, robotics and automation, AI and wearable devices were detected to be the most significant technologies in terms of impacting safety performance.Originality/valueThe study contributes to the body of knowledge in that it develops a conceptual framework consisting of specific technologies in terms of emerging technologies, reveals the impact of such technologies on safety performance and proposes several tools and strategies for enabling effective safety management along the project lifecycle. Industry practitioners may benefit from the framework developed by adopting such technologies to enhance their safety performance on construction projects.

Prediction on construction industry safety performance based on AHP and grey system

With the frequent occurrence of construction safety accidents, it is imperative to improve the safety performance of the construction industry. To predict safety performance scientifically, the number of construction accident fatalities was selected as an indicator of safety performance. This study combined the analytic hierarchy process (AHP) and grey relational analysis (GRA) to identify labor productivity, construction area of the house, and the number of construction enterprises and employees of the construction enterprises as the main factors affecting the number of construction accident fatalities. Then, this study used the grey prediction theory to establish a GM(1,5) model to predict the number of safety accident fatalities in 2013-2019. The results showed that the model has great prediction accuracy and can be used to predict future construction safety performance. Through the prediction of safety performance, managers can evaluate the development trends of construction projects. Therefore, they can take timely measures to reduce the occurrence of safety accidents. Meanwhile, the study provides a new optimization method for the development of the GM(1,N) model and the application of real data.

Critical Systems-Thinking-Based Leadership Competencies as Enablers to Better Construction Safety Performance

Safety is an essential success factor in construction projects. However, due to the complexity of construction projects, accidents typically occur randomly. Thus, efficient leadership based on a systematic approach is vital to reduce the possibility of accidents occurring. A combination of emotional, social, and cognitive competencies aligns with the Systems-Thinking concept. This concept enables safety leaders to influence their followers effectively. Systems-thinking-based leadership enables safety leaders to know how, when, and what leadership behaviors should be acquired and practiced. Therefore, it is essential to understand the interrelationships among those competencies. The main objective of this research study is to model the interpretive structure of critical Systems-Thinking-based leadership competencies as enablers to better construction safety performance. The Interpretive Structural Modeling (ISM) approach was followed to achieve the objective using safety experts’ opinion data collected via questionnaire. The questionnaire was designed using 14 Systems-Thinking-based leadership competencies to collect information on the direction of influence among the competencies. Results of the modeled interrelationships demonstrated that cognitive competencies are the preliminary building blocks to other social and emotional competencies enabling construction safety performance. The developed model provides a better understanding of how safety performance can be improved by building those competencies in construction personnel.

Implementing safety leading indicators in construction: Toward a proactive approach to safety management

Safety leading indicators have been investigated as a proactive management approach to managing construction safety. However, there is a lack of insight into the implementation of safety leading indicators in construction projects and organizations. This causes difficulties in the adoption and consistent use of safety leading indicators in the construction industry. The aim of the research is to explore what and how safety leading indicators can be implemented to improve safety management in the construction industry. Built upon Xu et al. (2021), the study prioritized the relative importance of 17 safety leading indicators through a three-round Delphi survey and voting analytic hierarchy process (VAHP). It was found that organization commitment; client, designer and contractor engagement; training and orientation; safety climate and competence were most critical to safety performance in construction. Furthermore, operational, organizational and strategic barriers to the effective implementation of safety leading indicators were identified through the focus group discussion. The study suggested strategies for addressing these barriers and moving toward a proactive safety management approach. This study contributes to the theories and practices of construction safety management by linking the deployment of safety leading indicators with organizational and strategic issues at firm and project levels and addressing the root causes of poor performance. The effective deployment of safety leading indicators needs the engagement of clients, contractors, designers and supply chains to develop organizational capabilities to drive improvements from the project front-end to completion.

Identification of accident-injury type and bodypart factors from construction accident reports: A graph-based deep learning framework

Accident reports provide information to understand why and how events occur. Learning from past accident reports is critical for preventing accidents or injuries in construction safety management. However, there are two issues: (1) manual analysis of such accident reports is time-consuming and labor-intensive; and (2) previous research mainly focused on analyzing the causal factors of accidents. Not much research concentrates on the injury effect in an accident and the influential relationship between accident cause and injury effect. To tackle this problem, a graph-based deep learning framework is proposed to identify accident-injury type and bodypart factors automatically to enable managers to make timely and better-informed decisions to prevent accidents and injuries for on-site safety. In this framework, a graph-based deep learning approach (specifically, the Graph Convolutional Network) is developed to automatically classify accident reports labeled with accident_type and injury_type, whereas the traversal method is developed to identify the bodypart factors. To further intuitively visualize these safety risk factors (e.g., accident_type, injury_type, and bodypart factors), the co-occurrence networks are drawn to further intuitively reveal the interdependency in accident-injury and injury-bodypart types respectively. From the perspective of theoretical and practical contributions, the framework proposed in this study not only represents a substantial data-driven advancement in construction accident report classification and keyword extraction tasks, but also enables managers to get knowledge of construction safety performance (i.e., accident causes and injury effects) and further formulate corresponding strategies to prevent accidents and injuries in on-site safety management.

The Influence of Mutual Assistance of Construction Workers with Different Personality Traits on Team Safety.

Construction workers' unsafe behaviors are closely related to construction safety performance. Most existing studies on construction workers' personality traits and safety behaviors have ignored the flexibility of worker mix at construction sites, the dynamics of workers' behaviors, and the complexity of environmental risks at construction sites. Based on the cognitive process of construction workers' safety behaviors and from the perspective of personality traits, this research establishes an agent-based model of steelworkers' mutual assistance behavior. The AnyLogic platform is adopted to show emerging phenomena in complex problems. Through simulation experiments, the optimized configuration of construction team members under different risk environments can be obtained. This research is conducive to project managers to understand the influence of construction workers' mutual assistance on team safety, assess workers' potential for safe work before recruitment, and carry out active safety management from the source instead of looking for the cause of the accident afterward, making safety management theory more realistic and dynamic.

Process evaluation of construction methods to quantify safety

The use of off-site construction methods is increasing within the construction industry. While this method has been captured by a variety of terms, they all refer to the process of producing project components in a manufacturing-like facility off-site and transporting completed units to site to be assembled to achieve the desired end-product. To support the quantification of safety performance in off-site construction versus conventional on-site methods, the research has developed a generalized model for capturing and evaluating construction methods. The methodology was developed in partnership with local practitioners to define, assess and compare on-site and off-site construction practices with a safety lens, and the methodology is partially validated in collaboration with various project owners to assess case study projects that employed off-site construction into their processes. The evaluation methodology takes a construction product-focused approach with emphasis on defining a complete material supply chain and capturing the data needed to support quantifiable safety evaluations of the process. As such, the approach takes a unique approach to establish an evaluation methodology for future comparisons.