IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i1p805-d1022732.html
   My bibliography  Save this article

Symbiotic Mechanism of Multiple Subjects for the Resource-Based Disposal of Medical Waste in China in the Post-Pandemic Context

Author

Listed:
  • Shuwen Zhao

    (School of Architecture and Engineering, Changzhou Vocational Institute of Engineering, Changzhou 213164, China)

  • Guojian Ma

    (School of Management, Jiangsu University, Zhenjiang 212013, China)

  • Juan Ding

    (School of Management, Jiangsu University, Zhenjiang 212013, China)

Abstract

In the post-pandemic era, the continuous growth in the rate of medical waste generation and the limited capacity of traditional disposal methods have posed a double challenge to society and the environment. Resource-based disposal is considered an efficient approach for solving these problems. Previous studies focused on the methods of medical waste disposal and the behavior of single stakeholders, lacking consideration of cooperation among different stakeholders. This study establishes an evolutionary game model of the resource-based disposal of medical waste to analyze the behavioral decision evolution of governments, medical institutions, and disposal enterprises. This study also explores the influencing factors in the achievement of the symbiotic state and investigates the conditions that participants need to meet. The results show that joint tripartite cooperation can be achieved when the subsidies and penalties from governments are sufficient, as well as the efficiency of resource-based disposal, which can effectively promote the evolution of the three subjects from the state of “partial symbiosis” to the state of “symbiosis”. However, the resource-based classification level cannot directly change the symbiotic state of the system due to the goal of minimizing cost and risk. When evolutionary subjects have reached the state of “symbiosis”, the improvement in the classification level can enhance the willingness of disposal enterprises to choose the resource-based classification strategy. Under such circumstances, governments reduce their corresponding level of intervention. At this time, the whole system is in a more idealized symbiotic state.

Suggested Citation

  • Shuwen Zhao & Guojian Ma & Juan Ding, 2023. "Symbiotic Mechanism of Multiple Subjects for the Resource-Based Disposal of Medical Waste in China in the Post-Pandemic Context," Sustainability, MDPI, vol. 15(1), pages 1-19, January.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:1:p:805-:d:1022732
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/1/805/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/1/805/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hao, Xinyu & Liu, Guangfu & Zhang, Xiaoling & Dong, Liang, 2022. "The coevolution mechanism of stakeholder strategies in the recycled resources industry innovation ecosystem: the view of evolutionary game theory," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    2. Georgios Giakoumakis & Dorothea Politi & Dimitrios Sidiras, 2021. "Medical Waste Treatment Technologies for Energy, Fuels, and Materials Production: A Review," Energies, MDPI, vol. 14(23), pages 1-30, December.
    3. Daniel Friedman, 1998. "On economic applications of evolutionary game theory," Journal of Evolutionary Economics, Springer, vol. 8(1), pages 15-43.
    4. Haiyan Shan & Junliang Yang & Guo Wei, 2019. "Industrial Symbiosis Systems: Promoting Carbon Emission Reduction Activities," IJERPH, MDPI, vol. 16(7), pages 1-23, March.
    5. Zhiqi Xu & Yukun Cheng & Shuangliang Yao & Sundarapandian Vaidyanathan, 2021. "Tripartite Evolutionary Game Model for Public Health Emergencies," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-14, May.
    6. Hao Liu & Zhong Yao, 2018. "Research on Mixed and Classification Simulation Models of Medical Waste—A Case Study in Beijing, China," Sustainability, MDPI, vol. 10(11), pages 1-16, November.
    7. Youqing Lv & Guojian Ma & Juan Ding, 2022. "Evolutionary Game Analysis of Medical Waste Disposal in China under Different Reward and Penalty Models," Sustainability, MDPI, vol. 14(8), pages 1-19, April.
    8. Ruguo Fan & Yibo Wang & Jinchai Lin, 2021. "Study on Multi-Agent Evolutionary Game of Emergency Management of Public Health Emergencies Based on Dynamic Rewards and Punishments," IJERPH, MDPI, vol. 18(16), pages 1-22, August.
    9. Chen, Heng & Li, Jiarui & Li, Tongyu & Xu, Gang & Jin, Xi & Wang, Min & Liu, Tong, 2022. "Performance assessment of a novel medical-waste-to-energy design based on plasma gasification and integrated with a municipal solid waste incineration plant," Energy, Elsevier, vol. 245(C).
    10. Ziyuan Liu & Zhi Li & Weiming Chen & Yunpu Zhao & Hanxun Yue & Zhenzhen Wu, 2020. "Path Optimization of Medical Waste Transport Routes in the Emergent Public Health Event of COVID-19: A Hybrid Optimization Algorithm Based on the Immune–Ant Colony Algorithm," IJERPH, MDPI, vol. 17(16), pages 1-18, August.
    11. Chen, Jingxian & Liang, Liang & Yao, Dong-Qing & Sun, Shengnan, 2017. "Price and quality decisions in dual-channel supply chains," European Journal of Operational Research, Elsevier, vol. 259(3), pages 935-948.
    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. Xinpei Qiao & Hyukku Lee & Qi Shen & Yuchao Li, 2023. "Research on the Tripartite Evolutionary Game of Zero-Waste City Construction in China," Sustainability, MDPI, vol. 15(13), pages 1-19, July.

    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. Wenke Wang & Xiaoqiong You & Kebei Liu & Yenchun Jim Wu & Daming You, 2020. "Implementation of a Multi-Agent Carbon Emission Reduction Strategy under the Chinese Dual Governance System: An Evolutionary Game Theoretical Approach," IJERPH, MDPI, vol. 17(22), pages 1-21, November.
    2. Youqing Lv & Guojian Ma & Juan Ding, 2022. "Evolutionary Game Analysis of Medical Waste Disposal in China under Different Reward and Penalty Models," Sustainability, MDPI, vol. 14(8), pages 1-19, April.
    3. Guojian Ma & Juan Ding & Youqing Lv, 2022. "SEIR Evolutionary Game Model Applied to the Evolution and Control of the Medical Waste Disposal Crisis in China during the COVID-19 Outbreak," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    4. Zhang, Qinchunxue & Shu, Lan & Jiang, Bichuan, 2023. "Moran process in evolutionary game dynamics with interval payoffs and its application," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    5. Matsui, Kenji, 2020. "Optimal bargaining timing of a wholesale price for a manufacturer with a retailer in a dual-channel supply chain," European Journal of Operational Research, Elsevier, vol. 287(1), pages 225-236.
    6. Lichi Zhang & Yanyan Jiang & Junmin Wu, 2022. "Evolutionary Game Analysis of Government and Residents’ Participation in Waste Separation Based on Cumulative Prospect Theory," IJERPH, MDPI, vol. 19(21), pages 1-16, November.
    7. Dehai Liu & Hongyi Li & Weiguo Wang & Chuang Zhou, 2015. "Scenario forecast model of long term trends in rural labor transfer based on evolutionary games," Journal of Evolutionary Economics, Springer, vol. 25(3), pages 649-670, July.
    8. Liang Liu & Cong Feng & Hongwei Zhang & Xuehua Zhang, 2015. "Game Analysis and Simulation of the River Basin Sustainable Development Strategy Integrating Water Emission Trading," Sustainability, MDPI, vol. 7(5), pages 1-21, April.
    9. Zhiguo Wang & Lufei Huang & Cici Xiao He, 2021. "A multi-objective and multi-period optimization model for urban healthcare waste’s reverse logistics network design," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 785-812, November.
    10. Zou, Chen & Huang, Yongchun & Hu, Shiliang & Huang, Zhan, 2023. "Government participation in low-carbon technology transfer: An evolutionary game study," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    11. Liu, Jicheng & Sun, Jiakang & Yuan, Hanying & Su, Yihan & Feng, Shuxian & Lu, Chaoran, 2022. "Behavior analysis of photovoltaic-storage-use value chain game evolution in blockchain environment," Energy, Elsevier, vol. 260(C).
    12. Zhinan Li & Qinming Liu & Chunming Ye & Ming Dong & Yihan Zheng, 2022. "Achieving Resilience: Resilient Price and Quality Strategies of Fresh Food Dual-Channel Supply Chain Considering the Disruption," Sustainability, MDPI, vol. 14(11), pages 1-24, May.
    13. Jin, Tao & Jiang, Yulian & Liu, Xingwen, 2023. "Evolutionary game analysis of the impact of dynamic dual credit policy on new energy vehicles after subsidy cancellation," Applied Mathematics and Computation, Elsevier, vol. 440(C).
    14. Zhou, Yuxun & Rahman, Mohammad Mafizur & Khanam, Rasheda & Taylor, Brad R., 2022. "The impact of penalty and subsidy mechanisms on the decisions of the government, businesses, and consumers during COVID-19 ——Tripartite evolutionary game theory analysis," Operations Research Perspectives, Elsevier, vol. 9(C).
    15. Xiongwei Quan & Gaoshan Zuo & Helin Sun, 2022. "Risk Perception Thresholds and Their Impact on the Behavior of Nearby Residents in Waste to Energy Project Conflict: An Evolutionary Game Analysis," Sustainability, MDPI, vol. 14(9), pages 1-20, May.
    16. Haitao Chen & Zhaohui Dong & Gendao Li, 2020. "Government Reward-Penalty Mechanism in Dual-Channel Closed-Loop Supply Chain," Sustainability, MDPI, vol. 12(20), pages 1-15, October.
    17. Ning, Jiajun & Xiong, Lixin, 2024. "Analysis of the dynamic evolution process of the digital transformation of renewable energy enterprises based on the cooperative and evolutionary game model," Energy, Elsevier, vol. 288(C).
    18. Al-Amin Abba Dabo & Amin Hosseinian-Far, 2023. "An Integrated Methodology for Enhancing Reverse Logistics Flows and Networks in Industry 5.0," Logistics, MDPI, vol. 7(4), pages 1-26, December.
    19. Wei Wang & Yanbin Li & Jinzhong Li & Yun Li, 2024. "Can pumped-storage power stations stimulate rural revitalization? Evidence from the four-party evolutionary game," Journal of Evolutionary Economics, Springer, vol. 34(3), pages 595-645, July.
    20. Yan, Yingchen & Zhao, Ruiqing & Xing, Tiantian, 2019. "Strategic introduction of the marketplace channel under dual upstream disadvantages in sales efficiency and demand information," European Journal of Operational Research, Elsevier, vol. 273(3), pages 968-982.

    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:15:y:2023:i:1:p:805-:d:1022732. 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.