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Research on Users’ Privacy-Sharing Intentions in the Health Data Tracking System Providing Personalized Services and Public Services

Author

Listed:
  • Shugang Li

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Kexin Peng

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Boyi Zhu

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Ziyi Li

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Beiyan Zhang

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Hui Chen

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Ruoxuan Li

    (School of Management, Shanghai University, Shanghai 200444, China)

Abstract

The utilization of user privacy data in the health data tracking system (HDTS) offers numerous benefits for businesses and public services, contingent upon users’ privacy sharing intentions. However, previous research neglected users’ preferences for public services and focused mainly on personalized services. Additionally, traditional privacy calculus theory has a limited focus on data security, leaving gaps in understanding individual and societal aspects. This study aims to fill these gaps by examining the influence of risk perception and factors like potential loss expectations, perceived personalized service benefits, group value identification, perceived public service utility, and perceived privacy on privacy sharing intentions in the context of personalized and public services. The results indicate a positive relationship between individual privacy protection perception and data sharing intention, as well as a positive relationship between group value identification and perceived public service utility with individuals’ privacy sharing intentions. Moreover, this research uncovers the moderating effect of information type sensitivity on the impact of perceived privacy and perceived public service utility on privacy sharing intentions, while there is no moderating effect of information type sensitivity on the relationship between group value identification and privacy sharing intentions. We recommend improving individual privacy education, ensuring data use transparency, and fostering identification with common group values to increase users’ privacy sharing intentions.

Suggested Citation

  • Shugang Li & Kexin Peng & Boyi Zhu & Ziyi Li & Beiyan Zhang & Hui Chen & Ruoxuan Li, 2023. "Research on Users’ Privacy-Sharing Intentions in the Health Data Tracking System Providing Personalized Services and Public Services," Sustainability, MDPI, vol. 15(22), pages 1-21, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:22:p:15709-:d:1275814
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    References listed on IDEAS

    as
    1. Tamara Dinev & Paul Hart, 2006. "An Extended Privacy Calculus Model for E-Commerce Transactions," Information Systems Research, INFORMS, vol. 17(1), pages 61-80, March.
    2. Naresh K. Malhotra & Sung S. Kim & James Agarwal, 2004. "Internet Users' Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model," Information Systems Research, INFORMS, vol. 15(4), pages 336-355, December.
    3. Rohm, Andrew J. & Milne, George R., 2004. "Just what the doctor ordered: The role of information sensitivity and trust in reducing medical information privacy concern," Journal of Business Research, Elsevier, vol. 57(9), pages 1000-1011, September.
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