IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i12p7368-d839907.html
   My bibliography  Save this article

Analysis of Factors Influencing Miners’ Unsafe Behaviors in Intelligent Mines using a Novel Hybrid MCDM Model

Author

Listed:
  • Xinping Wang

    (School of Management, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Cheng Zhang

    (School of Management, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Jun Deng

    (School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Chang Su

    (School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Zhenzhe Gao

    (School of Management, Xi’an University of Science and Technology, Xi’an 710054, China)

Abstract

Coal mine accidents seriously affect people’s safety and social development, and intelligent mines have improved the production safety environment. However, safety management and miners’ work in intelligent mines face new changes and higher requirements, and the safety situation remains challenging. Therefore, exploring the key influencing factors of miners’ unsafe behaviors in intelligent mines is important. Our work focuses on (1) investigating the relationship and hierarchy of 20 factors, (2) using fuzzy theory to improve the decision-making trial and evaluation laboratory (DEMATEL) method and introducing the maximum mean de-entropy (MMDE) method to determine the unique threshold scientifically, and (3) developing a novel multi-criteria decision-making (MCDM) model to provide theoretical basis and methods for managers. The main conclusions are as follows: (1) the influence degree of government regulation, leadership attention, safety input level, safety system standardization, and dynamic supervision intensity exert the most significant influence on the others; (2) the causality of government regulation, which is the deep factor, is the highest, and self-efficacy displays the smallest causality, and it is the most sensitive compared to various other factors; (3) knowledge accumulation ability, man–machine compatibility, emergency management capability, and organizational safety culture has the highest centrality among the individual factors, device factors, management factors, and environmental factors, respectively. Thus, corresponding management measures are proposed to improve coal mine safety and miners’ occupational health.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:12:p:7368-:d:839907
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/12/7368/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/12/7368/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Ronggang Zhang & Sathishkumar V E & R. Dinesh Jackson Samuel, 2020. "Fuzzy Efficient Energy Smart Home Management System for Renewable Energy Resources," Sustainability, MDPI, vol. 12(8), pages 1-14, April.
    3. Dan Marlin & Bruce T. Lamont & James J. Hoffman, 1994. "Choice situation, strategy, and performance: A reexamination," Strategic Management Journal, Wiley Blackwell, vol. 15(3), pages 229-239, March.
    4. 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.
    5. Gülşen Aydın Keskin, 2015. "Using integrated fuzzy DEMATEL and fuzzy C: means algorithm for supplier evaluation and selection," International Journal of Production Research, Taylor & Francis Journals, vol. 53(12), pages 3586-3602, June.
    6. Ben Harvey, 2016. "The Oaks Colliery disaster of 1866: a case study in responsibility," Business History, Taylor & Francis Journals, vol. 58(4), pages 501-531, May.
    7. Paul Tae-Woo Lee & Cheng-Wei Lin, 2013. "The cognition map of financial ratios of shipping companies using DEMATEL and MMDE," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(2), pages 133-145, March.
    8. Chen, Liang-Hsuan & Chiou, Tai-Wei, 1999. "A fuzzy credit-rating approach for commercial loans: a Taiwan case," Omega, Elsevier, vol. 27(4), pages 407-419, August.
    9. James Flynn & Paul Slovic & C. K. Mertz, 1994. "Gender, Race, and Perception of Environmental Health Risks," Risk Analysis, John Wiley & Sons, vol. 14(6), pages 1101-1108, December.
    10. Liou, James J.H. & Yen, Leon & Tzeng, Gwo-Hshiung, 2008. "Building an effective safety management system for airlines," Journal of Air Transport Management, Elsevier, vol. 14(1), pages 20-26.
    11. Tong, Ruipeng & Yang, Xiaoyi & Li, Hongwei & Li, Jianfei, 2019. "Dual process management of coal miners’ unsafe behaviour in the Chinese context: Evidence from a meta-analysis and inspired by the JD-R model," Resources Policy, Elsevier, vol. 62(C), pages 205-217.
    12. Gwo-Hshiung Tzeng & Chi-Yo Huang, 2012. "Combined DEMATEL technique with hybrid MCDM methods for creating the aspired intelligent global manufacturing & logistics systems," Annals of Operations Research, Springer, vol. 197(1), pages 159-190, August.
    13. Chang, Y-H & Yeh, C-H & Cheng, J-H, 1998. "Decision Support for Bus Operations under Uncertainty: a Fuzzy Expert System Approach," Omega, Elsevier, vol. 26(3), pages 367-380, June.
    14. Jih-Kuang Chen, 2021. "Improved DEMATEL-ISM integration approach for complex systems," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-16, July.
    15. Pradeep Kumar Behera & Kampan Mukherjee, 2015. "Application of DEMATEL and MMDE for Analyzing Key Influencing Factors Relevant to Selection of Supply Chain Coordination Schemes," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 8(2), pages 49-69, April.
    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. Jun Xiao & Jianping Xian & Shuai Zou & Song Li & Yongshui Zhang, 2022. "Design and Working Performance Evaluation of a Combined Survey Platform under Strong Wave and Deep-Water Conditions," Sustainability, MDPI, vol. 14(21), pages 1-26, November.
    2. Wenqin Li & Rongmin Liu & Linhui Sun & Zigu Guo & Jie Gao, 2022. "An Investigation of Employees’ Intention to Comply with Information Security System—A Mixed Approach Based on Regression Analysis and fsQCA," IJERPH, MDPI, vol. 19(23), pages 1-19, November.
    3. Xin Ning & Jiwen Huang & Chunlin Wu & Tong Liu & Chao Wang, 2022. "The Double-Edged Sword of Safety Training for Safety Behavior: The Critical Role of Psychological Factors during COVID-19," IJERPH, MDPI, vol. 19(17), pages 1-17, September.
    4. Małgorzata Jasiulewicz-Kaczmarek & Katarzyna Antosz & Ryszard Wyczółkowski & Małgorzata Sławińska, 2022. "Integrated Approach for Safety Culture Factor Evaluation from a Sustainability Perspective," IJERPH, MDPI, vol. 19(19), pages 1-30, September.
    5. Lin He & Dongliang Yuan & Lianwei Ren & Ming Huang & Wenyu Zhang & Jie Tan, 2023. "Evaluation Model Research of Coal Mine Intelligent Construction Based on FDEMATEL-ANP," Sustainability, MDPI, vol. 15(3), pages 1-21, January.

    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. Lo, Huai-Wei & Liou, James J.H. & Huang, Chun-Nen & Chuang, Yen-Ching & Tzeng, Gwo-Hshiung, 2020. "A new soft computing approach for analyzing the influential relationships of critical infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 28(C).
    2. David Opresnik & Maurizio Fiasché & Marco Taisch & Manuel Hirsch, 0. "An evolving fuzzy inference system for extraction of rule set for planning a product–service strategy," Information Technology and Management, Springer, vol. 0, pages 1-17.
    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. Carlo Alberto Magni & Stefano Malagoli & Andrea Marchioni & Giovanni Mastroleo, 2020. "Rating firms and sensitivity analysis," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(12), pages 1940-1958, December.
    5. David Opresnik & Maurizio Fiasché & Marco Taisch & Manuel Hirsch, 2017. "An evolving fuzzy inference system for extraction of rule set for planning a product–service strategy," Information Technology and Management, Springer, vol. 18(2), pages 131-147, June.
    6. Oralhan Burcu & Kirdök Nur & Oralhan Zeki, 2022. "Evaluation of Ski Centers’ Performance Using Multiple-Criteria Decision-Making Methods," Polish Journal of Sport and Tourism, Sciendo, vol. 29(3), pages 29-35, September.
    7. Yeh, Chung-Hsing & Deng, Hepu & Chang, Yu-Hern, 2000. "Fuzzy multicriteria analysis for performance evaluation of bus companies," European Journal of Operational Research, Elsevier, vol. 126(3), pages 459-473, November.
    8. Dong-Shang Chang & Sheng-Hung Chen & Chia-Wei Hsu & Allen H. Hu, 2015. "Identifying Strategic Factors of the Implantation CSR in the Airline Industry: The Case of Asia-Pacific Airlines," Sustainability, MDPI, vol. 7(6), pages 1-22, June.
    9. Beynon, Malcolm J. & Peel, Michael J. & Tang, Yu-Cheng, 2004. "The application of fuzzy decision tree analysis in an exposition of the antecedents of audit fees," Omega, Elsevier, vol. 32(3), pages 231-244, June.
    10. B. Kirubakaran & M. Ilangkumaran, 2016. "Selection of optimum maintenance strategy based on FAHP integrated with GRA–TOPSIS," Annals of Operations Research, Springer, vol. 245(1), pages 285-313, October.
    11. Ozer, Muammer, 2001. "User segmentation of online music services using fuzzy clustering," Omega, Elsevier, vol. 29(2), pages 193-206, April.
    12. Vuciterna, Rina & Thomsen, Michael & Popp, Jennie & Musliu, Arben, 2017. "Efficiency and Competitiveness of Kosovo Raspberry Producers," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252770, Southern Agricultural Economics Association.
    13. Berna Tektas Sivrikaya & Ferhan Cebi & Hasan Hüseyin Turan & Nihat Kasap & Dursun Delen, 2017. "A fuzzy long-term investment planning model for a GenCo in a hybrid electricity market considering climate change impacts," Information Systems Frontiers, Springer, vol. 19(5), pages 975-991, October.
    14. Collan, Mikael, 2008. "New Method for Real Option Valuation Using Fuzzy Numbers," Working Papers 466, IAMSR, Åbo Akademi.
    15. Kim, Jong Soon & Whang, Kyu-Seung, 1998. "A tolerance approach to the fuzzy goal programming problems with unbalanced triangular membership function," European Journal of Operational Research, Elsevier, vol. 107(3), pages 614-624, June.
    16. Berna Tektaş & Hasan Hüseyin Turan & Nihat Kasap & Ferhan Çebi & Dursun Delen, 2022. "A Fuzzy Prescriptive Analytics Approach to Power Generation Capacity Planning," Energies, MDPI, vol. 15(9), pages 1-26, April.
    17. Chen, Lisa Y. & Wang, Tien-Chin, 2009. "Optimizing partners' choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR," International Journal of Production Economics, Elsevier, vol. 120(1), pages 233-242, July.
    18. Víctor G. Alfaro-García & Anna M. Gil-Lafuente & Gerardo G. Alfaro Calderón, 2017. "A fuzzy approach to a municipality grouping model towards creation of synergies," Computational and Mathematical Organization Theory, Springer, vol. 23(3), pages 391-408, September.
    19. Aghayi, Nazila & Maleki, Bentolhoda, 2016. "Efficiency measurement of DMUs with undesirable outputs under uncertainty based on the directional distance function: Application on bank industry," Energy, Elsevier, vol. 112(C), pages 376-387.
    20. Wenyao Niu & Yuan Rong & Liying Yu & Lu Huang, 2022. "A Novel Hybrid Group Decision Making Approach Based on EDAS and Regret Theory under a Fermatean Cubic Fuzzy Environment," Mathematics, MDPI, vol. 10(17), pages 1-30, August.

    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:19:y:2022:i:12:p:7368-:d:839907. 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.