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

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  • Guo, Shengyu
  • Zhou, Xinyu
  • Tang, Bing
  • Gong, Peisong

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.

Suggested Citation

  • Guo, Shengyu & Zhou, Xinyu & Tang, Bing & Gong, Peisong, 2020. "Exploring the behavioral risk chains of accidents using complex network theory in the construction industry," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    • Handle: RePEc:eee:phsmap:v:560:y:2020:i:c:s0378437120305264
    DOI: 10.1016/j.physa.2020.125012
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    References listed on IDEAS

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    1. Aneziris, O.N. & Topali, E. & Papazoglou, I.A., 2012. "Occupational risk of building construction," Reliability Engineering and System Safety, Elsevier, vol. 105(C), pages 36-46.
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    3. Meead Saberi & Hani S. Mahmassani & Dirk Brockmann & Amir Hosseini, 2017. "A complex network perspective for characterizing urban travel demand patterns: graph theoretical analysis of large-scale origin–destination demand networks," Transportation, Springer, vol. 44(6), pages 1383-1402, November.
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    Citations

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    Cited by:

    1. Wenxin Su & Xin Gao & Yukun Jiang & Jinrong Li, 2021. "Developing a Construction Safety Standard System to Enhance Safety Supervision Efficiency in China: A Theoretical Simulation of the Evolutionary Game Process," Sustainability, MDPI, vol. 13(23), pages 1-22, December.
    2. Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Deng, Wanyi, 2023. "Determining the critical risk factors for predicting the severity of ship collision accidents using a data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    3. Shaoqi Jiang & Weijiong Chen & Yutao Kang & Jiahao Liu & Wanglai Kuang, 2021. "Identifying Cognitive Mechanism Underlying Situation Awareness of Pilots’ Unsafe Behaviors Using Quantitative Modeling," IJERPH, MDPI, vol. 18(6), pages 1-17, March.
    4. Li, Weidong & Wang, Anjian & Zhong, Weiqiong & Xing, Wanli & Liu, Jinna, 2022. "The role of mineral-related industries in Chinese industrial pattern," Resources Policy, Elsevier, vol. 76(C).
    5. Wang, Wenhao & Wang, Yanhui & Wang, Guangxing & Li, Man & Jia, Limin, 2023. "Identification of the critical accident causative factors in the urban rail transit system by complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    6. Jiao Liu & Shuang Li & Weijun Bao & Kun Xu, 2022. "Could the Management System of Safety Partnership Change Miners’ Unsafe Behavior?," Sustainability, MDPI, vol. 14(20), pages 1-14, October.
    7. Zheng, Huiling & Zhou, Jinsheng & Gao, Xiangyun & Xi, Xian & Liu, Donghui & Zhao, Yiran, 2021. "Global impacts of the topological structure of industrial driving networks on energy intensity," Energy, Elsevier, vol. 225(C).
    8. Zhang, Hengqi & Geng, Hua, 2023. "A methodology to identify and assess high-risk causes for electrical personal accidents based on directed weighted CN," Reliability Engineering and System Safety, Elsevier, vol. 231(C).

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