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An Evolutionary Game-Theoretic Approach for Assessing Privacy Protection in mHealth Systems

Author

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  • Guang Zhu

    (School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
    China Institute of Manufacturing Development, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Hu Liu

    (School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Mining Feng

    (China Institute of Manufacturing Development, Nanjing University of Information Science and Technology, Nanjing 210044, China)

Abstract

With the rapid deployment of mobile technologies and their applications in the healthcare domain, privacy concerns have emerged as one of the most critical issues. Traditional technical and organizational approaches used to address privacy issues ignore economic factors, which are increasingly important in the investment strategy of those responsible for ensuring privacy protection. Taking the mHealth system as the context, this article builds an evolutionary game to model three types of entities (including system providers, hospitals and governments) under the conditions of incomplete information and bounded rationality. Given that the various participating entities are often unable to accurately estimate their own profits or costs, we propose a quantified approach to analyzing the optimal strategy of privacy investment and regulation. Numerical examples are provided for illustration and simulation purpose. Based upon these examples, several countermeasures and suggestions for privacy protection are proposed. Our analytical results show that governmental regulation and auditing has a significant impact on the strategic choice of the other two entities involved. In addition, the strategic choices of system providers and hospitals are not only correlated with profits and investment costs, but they are also significantly affected by free riding. If the profit growth coefficients increase to a critical level, mHealth system providers and hospitals will invest in privacy protection even without the imposition of regulations. However, the critical level is dependent on the values of the parameters (variables) in each case of investment and profits.

Suggested Citation

  • Guang Zhu & Hu Liu & Mining Feng, 2018. "An Evolutionary Game-Theoretic Approach for Assessing Privacy Protection in mHealth Systems," IJERPH, MDPI, vol. 15(10), pages 1-27, October.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:10:p:2196-:d:174189
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    References listed on IDEAS

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    Cited by:

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    2. Qiang Mu & Peng Guo & Ding Wang, 2022. "Optimal Subsidy Support for the Provision of Elderly Care Services in China Based on the Evolutionary Game Analysis," IJERPH, MDPI, vol. 19(5), pages 1-20, February.
    3. 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.

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