IS in Healthcare
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Paper Number
1626
Paper Type
Completed
Description
In the unique context of an ongoing pandemic, this study aims to investigate the acceptance of mobile contact tracing applications (CTA) provided by the German government. Herein, the study develops and validates a research model based on established acceptance, privacy-, and health-related theories, which explains 80% of the variance of the intention to use CTA. The results of the structural equation model (n=656) indicate performance expectancy, effort expectancy, social influence, trust, privacy concerns, and anxiety to be relevant drivers of the intention to use CTA. This research contributes to theory and practical application by remarkable results, including the implementation of a collective-oriented task as an app performance, and identifying the effect of trust to be mediated via privacy concerns. Thereby, we offer valuable insights for research and institutions in charge of distributing the app.
Recommended Citation
Fortagne, Marius Arved; Reith, Riccardo; Diel, Soeren; Buck, Christoph; Eymann, Torsten; and Lis, Bettina, "COVID-19 Infection Tracing with Mobile Apps: Acceptance and Privacy Concerns" (2021). ICIS 2021 Proceedings. 10.
https://aisel.aisnet.org/icis2021/is_health/is_health/10
COVID-19 Infection Tracing with Mobile Apps: Acceptance and Privacy Concerns
In the unique context of an ongoing pandemic, this study aims to investigate the acceptance of mobile contact tracing applications (CTA) provided by the German government. Herein, the study develops and validates a research model based on established acceptance, privacy-, and health-related theories, which explains 80% of the variance of the intention to use CTA. The results of the structural equation model (n=656) indicate performance expectancy, effort expectancy, social influence, trust, privacy concerns, and anxiety to be relevant drivers of the intention to use CTA. This research contributes to theory and practical application by remarkable results, including the implementation of a collective-oriented task as an app performance, and identifying the effect of trust to be mediated via privacy concerns. Thereby, we offer valuable insights for research and institutions in charge of distributing the app.
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17-Health