IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i9p5778-d811802.html
   My bibliography  Save this article

A Regulatory Game Analysis of Smart Aging Platforms Considering Privacy Protection

Author

Listed:
  • Tengfei Shi

    (Faculty of Management and Economics, Kunming University of Science and Technology, Kunming 650504, China)

  • Hanjie Xiao

    (School of Economics and Management, Huzhou University, Huzhou 313000, China)

  • Fengxia Han

    (Industrial Development Research Institute, Kunming University of Science and Technology, Kunming 650031, China)

  • Lan Chen

    (Faculty of Management and Economics, Kunming University of Science and Technology, Kunming 650504, China)

  • Jianwei Shi

    (Faculty of Management and Economics, Kunming University of Science and Technology, Kunming 650504, China)

Abstract

Privacy and information protection are important issues in the era of big data. At present, China’s elderly care industry is gradually adopting the supply model of smart elderly care to alleviate the contradiction between supply and demand. However, the low level of regulation of smart aging platforms may lead to a low level of privacy protection on the platforms. Therefore, in this paper, based on the evolutionary game and Lyapunov theory, we discuss the willingness of elderly people to participate in regulation, the privacy protection status of platform service providers, and the degree of government regulation, as well as the key factors affecting the equilibrium of the three-party game system, and conduct simulation analysis and game system optimization using MATLAB. The simulation results show that A 1 ( 0 , 0 , 1 ) and A 5 ( 0 , 0 , 0 ) can be transformed to A 8 ( 1 , 1 , 0 ) by adjusting the parameters, i.e., the optimal ESS is participation, high-quality protection, and low investment supervision; the service income of the elderly, the loss of privacy leakage, the investment cost of service providers, and the amount of government rewards and punishments are the key factors affecting the tripartite game system. By analyzing the impact of factors, such as benefits and costs, on privacy protection and the regulation of smart senior care platforms, the level of privacy protection of smart senior care platforms can be improved and the process of the comprehensive regulation of domestic senior care services can be promoted.

Suggested Citation

  • Tengfei Shi & Hanjie Xiao & Fengxia Han & Lan Chen & Jianwei Shi, 2022. "A Regulatory Game Analysis of Smart Aging Platforms Considering Privacy Protection," IJERPH, MDPI, vol. 19(9), pages 1-21, May.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5778-:d:811802
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/9/5778/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/9/5778/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ritzberger, Klaus & Weibull, Jorgen W, 1995. "Evolutionary Selection in Normal-Form Games," Econometrica, Econometric Society, vol. 63(6), pages 1371-1399, November.
    2. Xianghua Yue & Yuming Lin, 2019. "Effectiveness of Punishment and Operating Subsidy in Supervision of China’s Pension PPP Projects: An Evolutionary Game and Simulation Analysis," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-12, November.
    3. Jiahuan He & Xinggang Luo & Zhongliang Zhang & Yang Yu, 2021. "Strategic Analysis of Participants in the Provision of Elderly Care Services—An Evolutionary Game Perspective," IJERPH, MDPI, vol. 18(16), pages 1-27, August.
    4. Anabel Quan‐Haase & Dennis Ho, 2020. "Online privacy concerns and privacy protection strategies among older adults in East York, Canada," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(9), pages 1089-1102, September.
    5. Tingqiang Chen & Jinnan Pan & Yuanping He & Jining Wang, 2020. "Evolutionary Game Model of Integrating Health and Care Services for Elder People," Complexity, Hindawi, vol. 2020, pages 1-13, July.
    6. Zornitza Prodanoff & Cynthia White-Williams & Hongmei Chi, 2021. "Regulations and Standards Aware Framework for Recording of mHealth App Vulnerabilities," International Journal of E-Health and Medical Communications (IJEHMC), IGI Global, vol. 12(3), pages 1-16, May.
    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. Xiaoxiao Geng & Ling Lv & Yingchen Wang & Ran Sun & Xiangmei Wang, 2022. "Evolutionary Game Research on Green Construction Considering Consumers’ Preference under Government Supervision," IJERPH, MDPI, vol. 19(24), pages 1-27, December.

    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. Zhiyong Zhang & Xiaodie Song & Yongqiang Shi, 2023. "Evolutionary Game Analysis of Behavior Strategies of Multiple Stakeholders in an Elderly Care Service System," IJERPH, MDPI, vol. 20(5), pages 1-22, February.
    2. Ianni, A., 2002. "Reinforcement learning and the power law of practice: some analytical results," Discussion Paper Series In Economics And Econometrics 203, Economics Division, School of Social Sciences, University of Southampton.
    3. Sandholm,W.H., 2003. "Excess payoff dynamics, potential dynamics, and stable games," Working papers 5, Wisconsin Madison - Social Systems.
    4. Viossat, Yannick, 2008. "Evolutionary dynamics may eliminate all strategies used in correlated equilibrium," Mathematical Social Sciences, Elsevier, vol. 56(1), pages 27-43, July.
    5. Hui Yu & Wei Wang & Baohua Yang & Cunfang Li, 2019. "Evolutionary Game Analysis of the Stress Effect of Cross-Regional Transfer of Resource-Exhausted Enterprises," Complexity, Hindawi, vol. 2019, pages 1-16, November.
    6. Daozhi Zhao & Jiaqin Hao & Cejun Cao & Hongshuai Han, 2019. "Evolutionary Game Analysis of Three-Player for Low-Carbon Production Capacity Sharing," Sustainability, MDPI, vol. 11(11), pages 1-20, May.
    7. Qipeng Sun & Yuqi He & Yongjie Wang & Fei Ma, 2019. "Evolutionary Game between Government and Ride-Hailing Platform: Evidence from China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-14, January.
    8. Aradhana Narang & A. J. Shaiju, 2019. "Evolutionary Stability of Polymorphic Profiles in Asymmetric Games," Dynamic Games and Applications, Springer, vol. 9(4), pages 1126-1142, December.
    9. 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.
    10. Oechssler, Jorg, 1997. "An Evolutionary Interpretation of Mixed-Strategy Equilibria," Games and Economic Behavior, Elsevier, vol. 21(1-2), pages 203-237, October.
    11. Yingrui Ma & Chao Wu & Xindong Wei & Weijun Gao & Lei Sun, 2024. "Evolutionary Dynamics of Passive Housing Initiatives in New Rural Construction," Sustainability, MDPI, vol. 16(13), pages 1-20, June.
    12. Demichelis, Stefano & Ritzberger, Klaus, 2003. "From evolutionary to strategic stability," Journal of Economic Theory, Elsevier, vol. 113(1), pages 51-75, November.
    13. Hauk, Esther & Hurkens, Sjaak, 2002. "On Forward Induction and Evolutionary and Strategic Stability," Journal of Economic Theory, Elsevier, vol. 106(1), pages 66-90, September.
    14. Yong Sun & Yalin Wang & Baoyin Liu & Zhongrui Sun, 2023. "Evolutionary game of destination brand co‐construction with government involvement," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 2125-2136, June.
    15. DeMichelis, Stefano & Germano, Fabrizio, 2000. "On the Indices of Zeros of Nash Fields," Journal of Economic Theory, Elsevier, vol. 94(2), pages 192-217, October.
    16. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2021. "Exploring the dilemma of overcapacity governance in China's coal industry: A tripartite evolutionary game model," Resources Policy, Elsevier, vol. 71(C).
    17. Freixas Xavier & Hurkens Sjaak & Morrison Alan D & Vulkan Nir, 2007. "Interbank Competition with Costly Screening," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 7(1), pages 1-27, May.
    18. Tao Li & Lei Ma & Zheng Liu & Chaonan Yi & Kaitong Liang, 2023. "Dual Carbon Goal-Based Quadrilateral Evolutionary Game: Study on the New Energy Vehicle Industry in China," IJERPH, MDPI, vol. 20(4), pages 1-16, February.
    19. Ponti, Giovanni, 2000. "Continuous-time evolutionary dynamics: theory and practice," Research in Economics, Elsevier, vol. 54(2), pages 187-214, June.
    20. Yuling Wang & Chunfu Wang & Xiaopeng Deng & Zezhou Wu, 2023. "Evolutionary Game Analysis of the Utilization of Construction Waste Resources Based on Prospect Theory," Sustainability, MDPI, vol. 15(3), pages 1-12, January.

    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:9:p:5778-:d:811802. 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.