IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i18p5021-d267100.html
   My bibliography  Save this article

Study on the Relationship between Worker States and Unsafe Behaviours in Coal Mine Accidents Based on a Bayesian Networks Model

Author

Listed:
  • Zhaobo Chen

    (Key Research Bases for Humanities and Social Sciences in Shanxi: Research Center for Innovation and Development of Equipment Manufacturing Industry, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Gangzhu Qiao

    (Division of Big Data and Visual Computing, North University of China, Taiyuan 030051, China)

  • Jianchao Zeng

    (Division of Big Data and Visual Computing, North University of China, Taiyuan 030051, China)

Abstract

Unsafe behaviours, such as violations of rules and procedures, are commonly identified as important causal factors in coal mine accidents. Meanwhile, a recurring conclusion of accident investigations is that worker states, such as mental fatigue, illness, physiological fatigue, etc., are important contributory factors to unsafe behaviour. In this article, we seek to provide a quantitative analysis on the relationship between the worker state and unsafe behaviours in coal mine accidents, based on a case study drawn from Chinese practice. Using Bayesian networks (BN), a graphical structure of the network was designed with the help of three experts from a coal mine safety bureau. In particular, we propose a verbal versus numerical fuzzy probability assessment method to elicit the conditional probability of the Bayesian network. The junction tree algorithm is further employed to accomplish this analysis. According to the BN established by expert knowledge, the results show that when the worker is in a poor state, the most vulnerable unsafe behaviour is violation, followed by decision-making error. Furthermore, insufficient experience may be the most significant contributory factor to unsafe behaviour, and poor fitness for duty may be the principal state that causes unsafe behaviours.

Suggested Citation

  • Zhaobo Chen & Gangzhu Qiao & Jianchao Zeng, 2019. "Study on the Relationship between Worker States and Unsafe Behaviours in Coal Mine Accidents Based on a Bayesian Networks Model," Sustainability, MDPI, vol. 11(18), pages 1-16, September.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:18:p:5021-:d:267100
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/18/5021/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/18/5021/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Piercey, M. David, 2009. "Motivated reasoning and verbal vs. numerical probability assessment: Evidence from an accounting context," Organizational Behavior and Human Decision Processes, Elsevier, vol. 108(2), pages 330-341, March.
    2. Wang, Guan & Zheng, Ning & Wen, Pingping & Li, Liangsheng & Shi, Qingfan, 2014. "Scaling probability distribution of granular chains in two dimensions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 192-197.
    3. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    4. Huizingh, Eelko K. R. E. & Vrolijk, Hans C. J., 1997. "A Comparison of Verbal and Numerical Judgments in the Analytic Hierarchy Process," Organizational Behavior and Human Decision Processes, Elsevier, vol. 70(3), pages 237-247, June.
    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. Li Yang & Xue Wang & Junqi Zhu & Liyan Sun & Zhiyuan Qin, 2022. "Comprehensive Evaluation of Deep Coal Miners’ Unsafe Behavior Based on HFACS-CM-SEM-SD," IJERPH, MDPI, vol. 19(17), pages 1-29, August.
    2. Inmaculada Silla & Francisco J. Gracia & José M. Peiró, 2020. "Upward Voice: Participative Decision Making, Trust in Leadership and Safety Climate Matter," Sustainability, MDPI, vol. 12(9), pages 1-17, May.
    3. Ismail, Siti Noraishah & Ramli, Azizan & Aziz, Hanida Abdul, 2021. "Influencing factors on safety culture in mining industry: A systematic literature review approach," Resources Policy, Elsevier, vol. 74(C).
    4. Xinping Wang & Cheng Zhang & Jun Deng & Chang Su & Zhenzhe Gao, 2022. "Analysis of Factors Influencing Miners’ Unsafe Behaviors in Intelligent Mines using a Novel Hybrid MCDM Model," IJERPH, MDPI, vol. 19(12), pages 1-30, June.
    5. Xiaowei Li & Tiezhong Liu & Yongkui Liu, 2019. "Cause Analysis of Unsafe Behaviors in Hazardous Chemical Accidents: Combined with HFACs and Bayesian Network," IJERPH, MDPI, vol. 17(1), pages 1-15, December.
    6. Lei Chen & Hongxia Li & Shuicheng Tian, 2022. "Application of AHP and DEMATEL for Identifying Factors Influencing Coal Mine Practitioners’ Unsafe State," Sustainability, MDPI, vol. 14(21), pages 1-18, November.

    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. Rahman, Shaikh Moksadur, 2020. "Relationship between Job Satisfaction and Turnover Intention: Evidence from Bangladesh," Asian Business Review, Asian Business Consortium, vol. 10(2), pages 99-108.
    2. Naveena Prakasam & Louisa Huxtable-Thomas, 2021. "Reddit: Affordances as an Enabler for Shifting Loyalties," Information Systems Frontiers, Springer, vol. 23(3), pages 723-751, June.
    3. Valeriy Makarov & Albert Bakhtizin, 2014. "The Estimation Of The Regions’ Efficiency Of The Russian Federation Including The Intellectual Capital, The Characteristics Of Readiness For Innovation, Level Of Well-Being, And Quality Of Life," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 9-30.
    4. Kristine Edgar Danielyan & Samvel Grigoriy Chailyan, 2019. "Delineation of Effectors Impact on The Human Brain Derived Phosphoribosylpyrophosphate Synthetase-1 Activity," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 24(1), pages 17918-17926, December.
    5. Chuan Wang & Yupeng Liu & Wen Hou & Chao Yu & Guorong Wang & Yuyan Zheng, 2021. "Reliability and availability modeling of Subsea Autonomous High Integrity Pressure Protection System with partial stroke test by Dynamic Bayesian," Journal of Risk and Reliability, , vol. 235(2), pages 268-281, April.
    6. Sana Sadiq & Khadija Anasse & Najib Slimani, 2022. "The impact of mobile phones on high school students: connecting the research dots," Technium Social Sciences Journal, Technium Science, vol. 30(1), pages 252-270, April.
    7. Jascha-Alexander Koch & Michael Siering, 2019. "The recipe of successful crowdfunding campaigns," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(4), pages 661-679, December.
    8. Martins, José & Costa, Catarina & Oliveira, Tiago & Gonçalves, Ramiro & Branco, Frederico, 2019. "How smartphone advertising influences consumers' purchase intention," Journal of Business Research, Elsevier, vol. 94(C), pages 378-387.
    9. Wu, Bing & Yip, Tsz Leung & Yan, Xinping & Guedes Soares, C., 2022. "Review of techniques and challenges of human and organizational factors analysis in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    10. Zarei, Esmaeil & Khan, Faisal & Abbassi, Rouzbeh, 2021. "Importance of human reliability in process operation: A critical analysis," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    11. Bilgihan, Anil & Barreda, Albert & Okumus, Fevzi & Nusair, Khaldoon, 2016. "Consumer perception of knowledge-sharing in travel-related Online Social Networks," Tourism Management, Elsevier, vol. 52(C), pages 287-296.
    12. Géraldine Boué & Enda Cummins & Sandrine Guillou & Jean‐Philippe Antignac & Bruno Le Bizec & Jeanne‐Marie Membré, 2017. "Development and Application of a Probabilistic Risk–Benefit Assessment Model for Infant Feeding Integrating Microbiological, Nutritional, and Chemical Components," Risk Analysis, John Wiley & Sons, vol. 37(12), pages 2360-2388, December.
    13. Leila Tavakoli & Hamed Zamani & Falk Scholer & William Bruce Croft & Mark Sanderson, 2022. "Analyzing clarification in asynchronous information‐seeking conversations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(3), pages 449-471, March.
    14. Chiara Francalanci & Ajaz Hussain, 2016. "Discovering social influencers with network visualization: evidence from the tourism domain," Information Technology & Tourism, Springer, vol. 16(1), pages 103-125, March.
    15. Lutz, Christoph & Newlands, Gemma, 2018. "Consumer segmentation within the sharing economy: The case of Airbnb," Journal of Business Research, Elsevier, vol. 88(C), pages 187-196.
    16. van Weeghel, H.J.E. & Bos, A.P. & Jansen, M.H. & Ursinus, W.W. & Groot Koerkamp, P.W.G., 2021. "Good animal welfare by design: An approach to incorporate animal capacities in engineering design," Agricultural Systems, Elsevier, vol. 191(C).
    17. Cocoradă, Elena & Maican, Cătălin Ioan & Cazan, Ana-Maria & Maican, Maria Anca, 2018. "Assessing the smartphone addiction risk and its associations with personality traits among adolescents," Children and Youth Services Review, Elsevier, vol. 93(C), pages 345-354.
    18. Óscar Chiva-Bartoll & Honorato Morente-Oria & Francisco Tomás González-Fernández & Pedro Jesús Ruiz-Montero, 2020. "Anxiety and Bodily Pain in Older Women Participants in a Physical Education Program. A Multiple Moderated Mediation Analysis," Sustainability, MDPI, vol. 12(10), pages 1-12, May.
    19. George Momanyi & Maureen Adoyo & Eunice Mwangi & Dennis Mokua, 2017. "Strengthening Strategic Reward Framework in Health Systems: A Survey of Narok County, Kenya," Global Journal of Health Science, Canadian Center of Science and Education, vol. 9(1), pages 181-181, January.
    20. Alfano, Vincenzo & Cicatiello, Lorenzo & Gaeta, Giuseppe Lucio & Pinto, Mauro, 2019. "The gender wage gap among PhD holders: an empirical examination based on Italian data," GLO Discussion Paper Series 393, Global Labor Organization (GLO).

    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:jsusta:v:11:y:2019:i:18:p:5021-:d:267100. 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.