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Exploring Factors Influencing Scenarios Evolution of Waste NIMBY Crisis: Analysis of Typical Cases in China

Author

Listed:
  • Ling He

    (School of Management, Wuhan University of Technology, Wuhan 430070, China)

  • Qing Yang

    (School of Management, Wuhan University of Technology, Wuhan 430070, China
    School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China)

  • Xingxing Liu

    (School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China)

  • Lingmei Fu

    (School of Management, Wuhan University of Technology, Wuhan 430070, China)

  • Jinmei Wang

    (School of Management, Wuhan University of Technology, Wuhan 430070, China)

Abstract

As the impact factors of the waste Not-In-My-Back Yard (NIMBY) crisis are complex, and the scenario evolution path of it is diverse. Once the crisis is not handled properly, it will bring adverse effects on the construction of waste NIMBY facilities, economic development and social stability. Consequently, based on ground theory, this paper takes the waste NIMBY crisis in China from 2006 to 2019 as typical cases, through coding analysis, scenario evolution factors of waste NIMBY crisis are established. Furtherly, three key scenarios were obtained, namely, external situation (E), situation state (S), emergency management (M), what is more, scenario evolution law of waste NIMBY crisis is revealed. Then, the dynamic Bayesian network theory is used to construct the dynamic scenario evolution network of waste NIMBY crisis. Finally, based on the above models, Xiantao waste NIMBY crisis is taken as a case study, and the dynamic process of scenario evolution network is visually displayed by using Netica. The simulation results show that the scenario evolution network of Xiantao waste NIMBY crisis is basically consistent with the actual incident development process, which confirms the effectiveness and feasibility of the model.

Suggested Citation

  • Ling He & Qing Yang & Xingxing Liu & Lingmei Fu & Jinmei Wang, 2021. "Exploring Factors Influencing Scenarios Evolution of Waste NIMBY Crisis: Analysis of Typical Cases in China," IJERPH, MDPI, vol. 18(4), pages 1-16, February.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:4:p:2006-:d:502020
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    References listed on IDEAS

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    1. Qingfeng Tian & Shuo Zhang & Huimin Yu & Guangming Cao, 2019. "Exploring the Factors Influencing Business Model Innovation Using Grounded Theory: The Case of a Chinese High-End Equipment Manufacturer," Sustainability, MDPI, vol. 11(5), pages 1-16, March.
    2. Zhang, Xiang & Xu, Jian-gang & Ju, Yang, 2018. "Public participation in NIMBY risk mitigation: A discourse zoning approach in the Chinese context," Land Use Policy, Elsevier, vol. 77(C), pages 559-575.
    3. Khakzad, Nima & Landucci, Gabriele & Reniers, Genserik, 2017. "Application of dynamic Bayesian network to performance assessment of fire protection systems during domino effects," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 232-247.
    4. Qing Yang & Yanxia Zhu & Xingxing Liu & Lingmei Fu & Qianqian Guo, 2019. "Bayesian-Based NIMBY Crisis Transformation Path Discovery for Municipal Solid Waste Incineration in China," Sustainability, MDPI, vol. 11(8), pages 1-21, April.
    5. Kammouh, Omar & Gardoni, Paolo & Cimellaro, Gian Paolo, 2020. "Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
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    Cited by:

    1. Pengxia Zhao & Tie Li & Biao Wang & Ming Li & Yu Wang & Xiahui Guo & Yue Yu, 2022. "The Scenario Construction and Evolution Method of Casualties in Liquid Ammonia Leakage Based on Bayesian Network," IJERPH, MDPI, vol. 19(24), pages 1-22, December.
    2. Fangkun Xin & Xingyue Wan, 2023. "A sustainable solution to promote interest-based municipal solid waste management," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-9, December.

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