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Learning From the Past to Improve the Future

Author

Listed:
  • Dana Naous

    (University of Lausanne)

  • Manus Bonner

    (University of Lausanne)

  • Mathias Humbert

    (University of Lausanne)

  • Christine Legner

    (University of Lausanne)

Abstract

Contact tracing apps were considered among the first tools to control the spread of COVID-19 and ease lockdown measures. While these apps can be very effective at stopping transmission and saving lives, the level of adoption remains significantly below the expected critical mass. The public debate as well as academic research about contact tracing apps emphasizes general concerns about privacy (and the associated risks) but often disregards the value-added services, as well as benefits, that can result from a larger user base. To address this gap, the study analyzes goal-congruent features as drivers for user adoption. It uses market research techniques – specifically, conjoint analysis – to study individual and group preferences and gain insights into the prescriptive design. While the results confirm the privacy-preserving design of most European contact tracing apps, they emphasize the role of value-added services in addressing heterogeneous user segments to drive user adoption. The findings thereby are of relevance for designing effective contact tracing apps, but also inform the user-oriented design of apps for health and crisis management that rely on sharing sensitive information.

Suggested Citation

  • Dana Naous & Manus Bonner & Mathias Humbert & Christine Legner, 2022. "Learning From the Past to Improve the Future," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(5), pages 597-614, October.
    • Handle: RePEc:spr:binfse:v:64:y:2022:i:5:d:10.1007_s12599-022-00742-2
    DOI: 10.1007/s12599-022-00742-2
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    References listed on IDEAS

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