Exploring the competing influences of privacy concerns and positive beliefs on citizen acceptance of contact tracing mobile applications

The continued proliferation of information technology in all aspects of our lives fosters benefits but also generates risks to individuals’ privacy. In emerging contexts, such as government surveillance technologies, there is a dearth of research investigating the positive and negative drivers of citizens’ acceptance. This is an important gap given the importance of citizen acceptance to the success of these technologies and the need to balance potentially wide-reaching benefits with any dilution of citizen privacy. We conduct a longitudinal examination of the competing influences of positive beliefs and privacy concerns on citizens’ acceptance of a COVID-19 national contact tracing mobile application among 405 Irish citizens. Combining privacy calculus theory with social exchange theory, we find that citizens’ initial acceptance is shaped by their perceptions of health benefits and social influence, with reciprocity exhibiting a sustained influence on acceptance over time and privacy concerns demonstrating a negative, albeit weak influence on willingness to rely on the application. The study offers important empirical and theoretical implications for the privacy literature in the government surveillance, location-based services, and mobile health application contexts, as well as practical implications for governments and developers introducing applications that rely on mass acceptance and reciprocal information disclosur