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Health vs. privacy? The risk-risk tradeoff in using COVID-19 contact-tracing apps

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  • Tran, Cong Duc
  • Nguyen, Tin Trung

Abstract

In the midst of the COVID-19 pandemic, contact-tracing apps have emerged as reliable tools for public health communication and the promotion of preventative health. However, to function properly, contact-tracing apps require users to provide sensitive information, which has raised concerns about data disclosure, misuse and social surveillance. Little is known about how different types of risk perception simultaneously hinder and motivate individuals' engagement in mobile health apps, particularly in the context of a pandemic. Based on the privacy calculus theory and the risk-risk tradeoff concept, this study examined the risk-risk tradeoff model to enhance the understanding of COVID-19 contact-tracing app users’ decision from the perspective of risk minimization. Findings from PLS-SEM and fsQCA revealed that users engage in health risk-privacy risk tradeoff when evaluating and deciding to use the apps. The focal study therefore contributes to the research on privacy calculus theory and calls for a balanced managerial solution to mitigate this tradeoff dilemma.

Suggested Citation

  • Tran, Cong Duc & Nguyen, Tin Trung, 2021. "Health vs. privacy? The risk-risk tradeoff in using COVID-19 contact-tracing apps," Technology in Society, Elsevier, vol. 67(C).
    • Handle: RePEc:eee:teinso:v:67:y:2021:i:c:s0160791x2100230x
    DOI: 10.1016/j.techsoc.2021.101755
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    Cited by:

    1. Eunji Lee & Jin-young Kim & Junchul Kim & Chulmo Koo, 2023. "Information Privacy Behaviors during the COVID-19 Pandemic: Focusing on the Restaurant Context," Information Systems Frontiers, Springer, vol. 25(5), pages 1829-1845, October.
    2. Fontes, Catarina & Corrigan, Caitlin & Lütge, Christoph, 2023. "Governing AI during a pandemic crisis: Initiatives at the EU level," Technology in Society, Elsevier, vol. 72(C).
    3. van der Waal, Nadine Elisa & de Wit, Jan & Bol, Nadine & Ebbers, Wolfgang & Hooft, Lotty & Metting, Esther & van der Laan, Laura Nynke, 2022. "Predictors of contact tracing app adoption: Integrating the UTAUT, HBM and contextual factors," Technology in Society, Elsevier, vol. 71(C).
    4. Laura Grassi, 2024. "In a world of Open Finance, are customers willing to share data? An analysis of the data-driven insurance business," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 14(3), pages 727-753, September.
    5. Esmaeilzadeh, Pouyan, 2022. "Identification of barriers affecting the use of health information exchange (HIE) in clinicians' practices: An empirical study in the United States," Technology in Society, Elsevier, vol. 70(C).
    6. Mwesiumo, Deodat & Halpern, Nigel & Bråthen, Svein & Budd, Thomas & Suau-Sanchez, Pere, 2023. "Perceived benefits as a driver and necessary condition for the willingness of air passengers to provide personal data for non-mandatory digital services at airports," Transportation Research Part A: Policy and Practice, Elsevier, vol. 171(C).
    7. Saheb, Tahereh & Sabour, Elham & Qanbary, Fatimah & Saheb, Tayebeh, 2022. "Delineating privacy aspects of COVID tracing applications embedded with proximity measurement technologies & digital technologies," Technology in Society, Elsevier, vol. 69(C).
    8. Fontes, Catarina & Hohma, Ellen & Corrigan, Caitlin C. & Lütge, Christoph, 2022. "AI-powered public surveillance systems: why we (might) need them and how we want them," Technology in Society, Elsevier, vol. 71(C).
    9. Eunji Lee & Chul Woo Yoo & Jahyun Goo & Kichan Nam & Chulmo Koo, 2024. "Is Contact Tracing for Pandemic Relief or Privacy Menace?: a Lens of Dual-Calculus Decision," Information Systems Frontiers, Springer, vol. 26(4), pages 1435-1451, August.

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