Investigation of Demographic Factors in Construction Employees’ Safety Perceptions

Han, Yu; Jin, Ruoyu; Wood, Hannah; Yang, Tong

doi:10.1007/s12205-019-2044-4

Cited by 52 publications

(49 citation statements)

References 53 publications

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“…Safety perception is a core part of explicit safety cognition (Han et al 2019c), which is largely equal to safety climate in terms of the measurement criteria (Guldenmund 2000;Rowatt et al 2005). These measurement criteria include perceptions towards jobsite hazards (Han et al 2019c), individuals' perceptions of self-capability to identify, evaluate, and control site hazards (Han et al 2019b), as well as their awareness and knowledge of safety behaviors of themselves and their peers (Chen and Jin 2012).…”

Section: Safety Cognition In the Context Of Safety Culturementioning

confidence: 99%

Structural Equation Modeling Approach to Studying the Relationships among Safety Investment, Construction Employees’ Safety Cognition, and Behavioral Performance

Han

Cao

et al. 2020

J. Constr. Eng. Manage.

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This study aimed to investigate the internal relationships between safety investments and construction employees' behavioral performance with safety cognition as the mediating factor. A comprehensive methodology was adopted, including theoretical modeling of safety investments, questionnaire survey, and Structural Equation Modeling (SEM). In the theoretical model, four factors (i.e., personal protection equipment (PPE), safety education, insurance purchased for site employees, and safety incentives) were adopted as safety investment categories. These four categories were studied of their correlation to the overall safety investment, which was tested of its contribution to employees' behavioral safety performance in both direct and indirect ways. Indirectly, safety cognition was introduced as a mediator to bridge safety investments and behavioral performance. A questionnaire consisting of 28 indicators was adopted to describe safety investment, safety cognition, and behavioral performance. A random sampling approach and the top-down method were implemented to recruit construction site employees from the southeastern region of China. The follow-up SEM analysis revealed that all the four investment categories positively contributed to the overall safety investment, which was found significantly correlated to employees' safety cognition and behavioral performance. Safety incentive was identified as the most significant factor contributing to the overall investment. The current study extends

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Section: Safety Cognition In the Context Of Safety Culturementioning

confidence: 99%

Structural Equation Modeling Approach to Studying the Relationships among Safety Investment, Construction Employees’ Safety Cognition, and Behavioral Performance

Han

Cao

et al. 2020

J. Constr. Eng. Manage.

Self Cite

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“…The authors of [27] further study the effect of gender and education among Chinese workers and find that age and gender are significant to the recognition and perception of different hazards among workers where males had more confidence in confronting hazards which in other words means that they are more risk-takers. They also report that education level has a high correlation with the results of hazard recognition.…”

Section: Proactive Worker Safety and Behaviormentioning

confidence: 99%

Leading Indicators—A Conceptual IoT-Based Framework to Produce Active Leading Indicators for Construction Safety

Costin

Wehle

Adibfar

2019

Safety

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Active leading indicators (ALIs) have the potential to identify safety hazards and prompt immediate actions to prevent incidents. Currently, there is a major gap in research that incorporates a fully automated ALI system because implementation has been hindered by a lack of established industry thresholds of measurable performance that would trigger an actionable response. Therefore, this paper addresses this gap by presenting a new method that utilizes the Internet of Things (IoT) to collect quantifiable data which can trigger an actionable response in real time based on established thresholds. This novel method integrates the Construction Industry Institute (CII) active leading indicator framework with a prototype IoT-based system. Significantly, the ALI provides the physical–virtual feedback loop, which is an essential aspect of the IoT system because it provides real-time feedback to both the users and systems. This paper also identifies potential inputs to the ALI framework from emerging IoT-enabled systems. A case study was presented to initially validate the IoT-based ALI framework. Bluetooth-enabled heart rate monitors were issued to workers in a hazardous and critical mining construction site. The ALIs that were recorded included heart rate and body temperature. Thresholds were established that alerted the monitoring safety staff when a worker exhibited potentially unsafe conditions. The results of the study demonstrated the feasibility of the system. Additionally, other results included worker resistance; non-disclosing of medical conditions, and limitations for IoT connectivity.

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“…Identifying hazards was performed in many studies such as [11][12][13][14][15][16][17][18]. Gunduz et al [19] conducted an extensive literature review to identify 168 observable variables in 16 latent dimensions that affect safety.…”

Section: Literature Reviewmentioning

confidence: 99%

Construction Project Safety Performance Management Using Analytic Network Process (ANP) as a Multicriteria Decision-Making (MCDM) Tool

Gunduz

Khader

2020

Computational Intelligence and Neuroscience

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The paper addresses the context in which the construction industry is considered risky, as the intense labor and machine environment interacts with acceleration and overlapping activities. This situation results in accidents and fatalities. A high number of accidents and fatalities leads to additional costs and delays, detrimental to all stakeholders. Hazard identification and quantification of their impacts on building safety are crucial for planning. Classifying security risks is a complex process, and risks are interconnected. There is a gap in the literature to study the interconnections of these hazards along with the frequency of occurrences. To bridge this gap, the frequency-adjusted importance index and the ANP (Analytical Networking Process) tool were used to capture the 14 interconnections and their frequencies based on the results of a survey distributed to 106 construction professionals. The main contribution of this work to existing knowledge is to identify and prioritize potential risks in the construction sector, considering their interconnections and their level of occurrence frequency. This is the first study in the literature to combine the frequency-adjusted importance index and the ANP tool, both integrated. The results from the importance index was used as the base for pairwise comparison for the ANP model. Based on the results from the model, recommendations to industry professionals are provided and presented.

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Investigation of Demographic Factors in Construction Employees’ Safety Perceptions

Cited by 52 publications

References 53 publications

Structural Equation Modeling Approach to Studying the Relationships among Safety Investment, Construction Employees’ Safety Cognition, and Behavioral Performance

Structural Equation Modeling Approach to Studying the Relationships among Safety Investment, Construction Employees’ Safety Cognition, and Behavioral Performance

Leading Indicators—A Conceptual IoT-Based Framework to Produce Active Leading Indicators for Construction Safety

Construction Project Safety Performance Management Using Analytic Network Process (ANP) as a Multicriteria Decision-Making (MCDM) Tool

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