IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2019i1p221-d302724.html
   My bibliography  Save this article

Exploring the Impact of Unsafe Behaviors on Building Construction Accidents Using a Bayesian Network

Author

Listed:
  • Shengyu Guo

    (School of Economics and Management and Institute of Management Science and Engineering, China University of Geosciences, Wuhan 430000, China)

  • Jiali He

    (School of Economics and Management and Institute of Management Science and Engineering, China University of Geosciences, Wuhan 430000, China
    Business School, Central South University, Changsha 410000, China)

  • Jichao Li

    (School of Economics and Management and Institute of Management Science and Engineering, China University of Geosciences, Wuhan 430000, China)

  • Bing Tang

    (School of Economics and Management and Institute of Management Science and Engineering, China University of Geosciences, Wuhan 430000, China)

Abstract

Unsafe behavior is a critical factor leading to construction accidents. Despite numerous studies supporting this viewpoint, the process by which accidents are influenced by construction workers’ unsafe behaviors and the extent to which unsafe behaviors are involved in this process remain poorly discussed. Therefore, this paper selects cases from Chinese building construction accidents to explore the probabilistic transmission paths from unsafe behaviors to accidents using a Bayesian network. First, a list of unsafe behaviors is constructed based on safety standards and operating procedures. Second, several chains of unsafe behaviors are extracted from 287 accident cases within four types (fall, collapse, struck-by and lifting) to form a Bayesian network model. Finally, two accidents are specifically analyzed to verify the rationality of the proposed model through forward reasoning. Additionally, critical groups of unsafe behaviors leading to the four types of accidents are identified through backward reasoning. The results show the following: (i) The time sequence of unsafe behaviors in a chain does not affect the final posterior probability of an accident, but the accident attribute strength of an unsafe behavior, affects the growth rate of the posterior probability of an accident. (ii) The four critical groups of unsafe behaviors leading to fall, collapse, struck-by, and lifting are identified. This study is of theoretical and practical significance for on-site behavioral management and accident prevention.

Suggested Citation

  • Shengyu Guo & Jiali He & Jichao Li & Bing Tang, 2019. "Exploring the Impact of Unsafe Behaviors on Building Construction Accidents Using a Bayesian Network," IJERPH, MDPI, vol. 17(1), pages 1-15, December.
  • Handle: RePEc:gam:jijerp:v:17:y:2019:i:1:p:221-:d:302724
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/1/221/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/17/1/221/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    2. Wu, Xianguo & Liu, Huitao & Zhang, Limao & Skibniewski, Miroslaw J. & Deng, Qianli & Teng, Jiaying, 2015. "A dynamic Bayesian network based approach to safety decision support in tunnel construction," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 157-168.
    3. Xiang Wu & Yuanlong Li & Yongzheng Yao & Xiaowei Luo & Xuhui He & Wenwen Yin, 2018. "Development of Construction Workers Job Stress Scale to Study and the Relationship between Job Stress and Safety Behavior: An Empirical Study in Beijing," IJERPH, MDPI, vol. 15(11), pages 1-12, October.
    4. Wu, Wei-Shing & Yang, Chen-Feng & Chang, Jung-Chuan & Château, Pierre-Alexandre & Chang, Yang-Chi, 2015. "Risk assessment by integrating interpretive structural modeling and Bayesian network, case of offshore pipeline project," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 515-524.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xun Liu & Xiaobo Li, 2022. "Exploring the Formation Mechanism of Unsafe Construction Behavior and Testing Efficient Occupational Health and Safety (OHS) Programs," IJERPH, MDPI, vol. 19(4), pages 1-19, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qazi, Abroon & Dickson, Alex & Quigley, John & Gaudenzi, Barbara, 2018. "Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 196(C), pages 24-42.
    2. Pan, Yue & Ou, Shenwei & Zhang, Limao & Zhang, Wenjing & Wu, Xianguo & Li, Heng, 2019. "Modeling risks in dependent systems: A Copula-Bayesian approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 416-431.
    3. Qingfeng Meng & Wenyao Liu & Zhen Li & Xin Hu, 2021. "Influencing Factors, Mechanism and Prevention of Construction Workers’ Unsafe Behaviors: A Systematic Literature Review," IJERPH, MDPI, vol. 18(5), pages 1-22, March.
    4. Sang-Guk Yum & Sungjin Ahn & Junseo Bae & Ji-Myong Kim, 2020. "Assessing the Risk of Natural Disaster-Induced Losses to Tunnel-Construction Projects Using Empirical Financial-Loss Data from South Korea," Sustainability, MDPI, vol. 12(19), pages 1-15, September.
    5. Yu, Shui & Wang, Zhonglai & Zhang, Kewang, 2018. "Sequential time-dependent reliability analysis for the lower extremity exoskeleton under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 45-52.
    6. Rasoul Amirzadeh & Dhananjay Thiruvady & Asef Nazari & Mong Shan Ee, 2023. "Dynamic Bayesian Networks for Predicting Cryptocurrency Price Directions: Uncovering Causal Relationships," Papers 2306.08157, arXiv.org, revised Oct 2024.
    7. Gaogeng Zhu & Guoming Chen & Jingyu Zhu & Xiangkun Meng & Xinhong Li, 2022. "Modeling the Evolution of Major Storm-Disaster-Induced Accidents in the Offshore Oil and Gas Industry," IJERPH, MDPI, vol. 19(12), pages 1-27, June.
    8. Jayaraman, Deepan & Ramu, Palaniappan, 2023. "L-moments and Bayesian inference for probabilistic risk assessment with scarce samples that include extremes," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    9. Wang, Fan & Li, Heng & Dong, Chao & Ding, Lieyun, 2019. "Knowledge representation using non-parametric Bayesian networks for tunneling risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    10. Lluís Sanmiquel & Marc Bascompta & Josep M. Rossell & Hernan Anticoi, 2021. "Analysis of Occupational Accidents in the Spanish Mining Sector in the Period 2009–2018," IJERPH, MDPI, vol. 18(24), pages 1-15, December.
    11. Chunchang Zhang & Hu Sun & Yuanyuan Zhang & Gen Li & Shibo Li & Junyu Chang & Gongqian Shi, 2023. "Fire Accident Risk Analysis of Lithium Battery Energy Storage Systems during Maritime Transportation," Sustainability, MDPI, vol. 15(19), pages 1-12, September.
    12. Kraidi, Layth & Shah, Raj & Matipa, Wilfred & Borthwick, Fiona, 2019. "Analyzing the critical risk factors associated with oil and gas pipeline projects in Iraq," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 14-22.
    13. Yongbo Li & Bathrinath Sankaranarayanan & D. Thresh Kumar & Ali Diabat, 2019. "Risks assessment in thermal power plants using ISM methodology," Annals of Operations Research, Springer, vol. 279(1), pages 89-113, August.
    14. Yin, Yuanbo & Yang, Hao & Duan, Pengfei & Li, Luling & Zio, Enrico & Liu, Cuiwei & Li, Yuxing, 2022. "Improved quantitative risk assessment of a natural gas pipeline considering high-consequence areas," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    15. 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).
    16. Guo, Qingjun & Amin, Shohel & Hao, Qianwen & Haas, Olivier, 2020. "Resilience assessment of safety system at subway construction sites applying analytic network process and extension cloud models," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    17. Haleh Sadeghi & Saeed Reza Mohandes & M. Reza Hosseini & Saeed Banihashemi & Amir Mahdiyar & Arham Abdullah, 2020. "Developing an Ensemble Predictive Safety Risk Assessment Model: Case of Malaysian Construction Projects," IJERPH, MDPI, vol. 17(22), pages 1-25, November.
    18. Zhou, Ying & Li, Chenshuang & Zhou, Cheng & Luo, Hanbin, 2018. "Using Bayesian network for safety risk analysis of diaphragm wall deflection based on field data," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 152-167.
    19. Yi Yang & John Dalsgaard Sørensen, 2020. "Probabilistic Availability Analysis for Marine Energy Transfer Subsystem Using Bayesian Network," Energies, MDPI, vol. 13(19), pages 1-27, October.
    20. Jamalnia, Aboozar & Gong, Yu & Govindan, Kannan & Bourlakis, Michael & Mangla, Sachin Kumar, 2023. "A decision support system for selection and risk management of sustainability governance approaches in multi-tier supply chain," International Journal of Production Economics, Elsevier, vol. 264(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2019:i:1:p:221-:d:302724. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.