Human Factors Analysis of China’s Confined Space Accidents from 2013 to 2022: Ensuring the Safe and Sustainable Development of Enterprises

Confined space operations are inherently dangerous, leading to frequent accidents with serious consequences. This study utilizes an improved Human Factors Analysis and Classification System (HFACS) model to analyze the human factors contributing to confined space accidents, employing both chi-square tests and grey correlation analysis. The integration of these two analytical methods is essential for providing a comprehensive understanding of the causal relationships among human factors, thereby enabling more robust and validated conclusions. Initially, we identified human factors associated with confined space accidents based on the traditional HFACS model and the unique characteristics of confined space operations, resulting in the identification of 5 primary risk factors and 17 secondary risk factors. Subsequently, we employed chi-square tests and grey correlation analysis to examine the causal relationships among these human factors. The combined results of these methods reveal significant influence relationships within the HFACS model levels pertinent to confined space accidents, identifying 11 significant causal relationships and three paths of accident development. The primary aim of the statistical and correlation analyses is to identify and validate the significant causal relationships among the identified human factors, thereby enhancing our understanding of their impact on confined space accidents. The findings of this research are instrumental in reducing the risk of confined space accidents within enterprises, ultimately ensuring the safe and sustainable operation of production processes.

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Publication Details

Journal
Sustainability
Published
2024-11-21
DOI
https://doi.org/10.3390/su162310183
Citations
3
Primary Topic
Risk and Safety Analysis
Type
article
Field-Weighted Citation Impact
1.38

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article

Human Factors Analysis of China’s Confined Space Accidents from 2013 to 2022: Ensuring the Safe and Sustainable Development of Enterprises

Jishuo Li, Kaili Xu, Xiwen Yao
3 citations
Sustainability
Risk and Safety Analysis
1.38
article

Human Factors Analysis of China’s Confined Space Accidents from 2013 to 2022: Ensuring the Safe and Sustainable Development of Enterprises

Jishuo Li, Kaili Xu, Xiwen Yao
article en
3 citations

Abstract

Confined space operations are inherently dangerous, leading to frequent accidents with serious consequences. This study utilizes an improved Human Factors Analysis and Classification System (HFACS) model to analyze the human factors contributing to confined space accidents, employing both chi-square tests and grey correlation analysis. The integration of these two analytical methods is essential for providing a comprehensive understanding of the causal relationships among human factors, thereby enabling more robust and validated conclusions. Initially, we identified human factors associated with confined space accidents based on the traditional HFACS model and the unique characteristics of confined space operations, resulting in the identification of 5 primary risk factors and 17 secondary risk factors. Subsequently, we employed chi-square tests and grey correlation analysis to examine the causal relationships among these human factors. The combined results of these methods reveal significant influence relationships within the HFACS model levels pertinent to confined space accidents, identifying 11 significant causal relationships and three paths of accident development. The primary aim of the statistical and correlation analyses is to identify and validate the significant causal relationships among the identified human factors, thereby enhancing our understanding of their impact on confined space accidents. The findings of this research are instrumental in reducing the risk of confined space accidents within enterprises, ultimately ensuring the safe and sustainable operation of production processes.

SustainabilityVol. 16(23)
Ministry of Education of the People's Republic of China (CN), Northeastern University (CN)
Natural Science Foundation of Liaoning Province, Fundamental Research Funds for the Central Universities
Industry, innovation and infrastructure
Openalex Percentile: Top 16%
Risk and Safety Analysis
1.38
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