Semantic Network Analysis Using Construction Accident Cases to Understand Workers’ Unsafe Acts

Suhyun Kang, Sunyoung Cho, Sungmin Yun and Sangyong Kim
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Suhyun Kang: School of Architecture, Yeungnam University, Gyeongsan-si 38541, Korea
Sunyoung Cho: School of Architecture, Yeungnam University, Gyeongsan-si 38541, Korea
Sungmin Yun: Department of Civil Engineering, Yeungnam University, Gyeongsan-si 38541, Korea
Sangyong Kim: School of Architecture, Yeungnam University, Gyeongsan-si 38541, Korea

IJERPH, 2021, vol. 18, issue 23, 1-14

Abstract: Unsafe acts by workers are a direct cause of accidents in the labor-intensive construction industry. Previous studies have reviewed past accidents and analyzed their causes to understand the nature of the human error involved. However, these studies focused their investigations on only a small number of construction accidents, even though a large number of them have been collected from various countries. Consequently, this study developed a semantic network analysis (SNA) model that uses approximately 60,000 construction accident cases to understand the nature of the human error that affects safety in the construction industry. A modified human factor analysis and classification system (HFACS) framework was used to classify major human error factors—that is, the causes of the accidents in each of the accident summaries in the accident case data—and an SNA analysis was conducted on all of the classified data to analyze correlations between the major factors that lead to unsafe acts. The results show that an overwhelming number of accidents occurred due to unintended acts such as perceptual errors (PERs) and skill-based errors (SBEs). Moreover, this study visualized the relationships between factors that affected unsafe acts based on actual construction accident case data, allowing for an intuitive understanding of the major keywords for each of the factors that lead to accidents.

Keywords: construction accident case; construction workers; unsafe acts; semantic network analysis; HFACS; human error (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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