Exploring the behavioral risk chains of accidents using complex network theory in the construction industry

Shengyu Guo, Xinyu Zhou, Bing Tang and Peisong Gong

Physica A: Statistical Mechanics and its Applications, 2020, vol. 560, issue C

Abstract: Accident causation theories explain the possible causation mechanisms of accidents, and unsafe behavior is a major component of such causes. Considering the limitation that existing studies rarely discuss the interactions among unsafe behaviors in accidents, this paper uses a case study in the Chinese building construction industry to explore the behavioral risk chains of accidents based on complex network (CN) theory. First, accident cases are collected from government websites, and the extracted unsafe acts are classified according to a list summarized based on several safety standards and operating procedures. Second, the rules for forming behavioral risk chains are defined, and then, a behavioral risk chain network of accidents (BRCNA) is established. In addition, Pajek is used to construct the network model. Finally, the topological parameters are calculated and analyzed in the BRCNA. The results show that the BRCNA has the properties of a scale-free and small-world network. These findings indicate the robustness of the BRCNA for random attacks and the high transmission and diffusion efficiency of behavioral risk in the BRCNA, which reflects that some unsafe acts must be critically controlled and that their related unsafe acts in a chain must be collaboratively controlled through safety management. This study is of theoretical and practical significance for accident prevention in the construction industry.

Keywords: Behavioral risk chain; Unsafe behavior; Accident prevention; Complex network; Building construction (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:560:y:2020:i:c:s0378437120305264

DOI: 10.1016/j.physa.2020.125012

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