When social influence leads to trust – Investigating determinants of usage intentions of COVID-19 contact tracing apps
(A2021-94704)

AUTHORS

Kira Heimann, Bielefeld University; Nicola Bilstein, Bielefeld University

ABSTRACT

COVID-19 led to substantial financial losses for service providers and merchants. New innovations like contact tracing apps appear as means to contain the spread of the virus. Still, little is known about decisive factors encouraging a critical mass to use those apps which is important to reduce the scope of future lockdowns and alleviate economic consequences. Therefore, we investigate factors influencing usage intention of the German Corona-Warn-App (CWA) for nonusers, based on a modified UTAUT model enhanced by privacy concerns and two trust dimensions. Our results identify performance expectancy, Internet privacy concerns, trust in system and trust in others as important factors influencing CWA’s usage intention. Interestingly, social influence only effects usage intention indirectly via the two trust dimensions. Consequently, practitioners should focus on transparent data security and performance of the app and pursue strategies increasing WOM and thus social influence of the app.