Empirical Decision-Making Model of Intentional Unsafe Behavior of Construction Workers

This study aimed to develop a decision-making model for construction workers with regard to intentional unsafe behavior based on the theory of planned behavior. Unsafe behavior of workers is acknowledged as a major cause of accidents. It can be categorized based on intentionality. Intentional unsafe behavior can undermine accident prevention strategies, and thus become a critical cause of accidents at construction sites. Based on insights from interviews with construction workers, researchers, and managers and a literature review, a hypothetical model and questionnaire were developed. A survey was conducted at eight construction sites, and 444 responses were collected from construction workers. Structural equation modeling was employed to validate the proposed model. The results indicate that managers’ attitudes influence workers’ attitudes toward behavior, which directly predicts their intention to engage in unsafe behavior. Perceived behavioral control moderates the relationship between attitude and intention, whereas actual behavioral control moderates the relationship between intention and actual behavior. This study contributes to the existing body of knowledge in construction safety research because the current understanding of mechanisms underlying construction workers’ intentional unsafe behavior is limited. Furthermore, the findings of this study can serve as a foundation for developing practical intervention strategies aimed at mitigating intentionally unsafe behaviors in the construction industry.

Authors

Institutions

Publication Details

Journal
Journal of Management in Engineering
Published
2025-12-30
DOI
https://doi.org/10.1061/jmenea.meeng-7153
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Empirical Decision-Making Model of Intentional Unsafe Behavior of Construction Workers

Youngcheol Kang, Jeonghyeun Chae
Journal of Management in Engineering
Occupational Health and Safety Research
article

Empirical Decision-Making Model of Intentional Unsafe Behavior of Construction Workers

Youngcheol Kang, Jeonghyeun Chae
article en

Abstract

This study aimed to develop a decision-making model for construction workers with regard to intentional unsafe behavior based on the theory of planned behavior. Unsafe behavior of workers is acknowledged as a major cause of accidents. It can be categorized based on intentionality. Intentional unsafe behavior can undermine accident prevention strategies, and thus become a critical cause of accidents at construction sites. Based on insights from interviews with construction workers, researchers, and managers and a literature review, a hypothetical model and questionnaire were developed. A survey was conducted at eight construction sites, and 444 responses were collected from construction workers. Structural equation modeling was employed to validate the proposed model. The results indicate that managers’ attitudes influence workers’ attitudes toward behavior, which directly predicts their intention to engage in unsafe behavior. Perceived behavioral control moderates the relationship between attitude and intention, whereas actual behavioral control moderates the relationship between intention and actual behavior. This study contributes to the existing body of knowledge in construction safety research because the current understanding of mechanisms underlying construction workers’ intentional unsafe behavior is limited. Furthermore, the findings of this study can serve as a foundation for developing practical intervention strategies aimed at mitigating intentionally unsafe behaviors in the construction industry.

Journal of Management in EngineeringVol. 42(2)
Yonsei University (KR)
Openalex Percentile: Top 30%
Occupational Health and Safety Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.