Demarcating the Privacy Issues of Aarogya Setu App in Covid-19 Pandemic in India: An Exploration into Contact Tracing Mobile Applications from Elaboration Likelihood Model

Abstract

Demand for contract tracing applications is significantly increasing as governments across the globe are relying on these mobile apps to help combat the spread of the COVID-19 virus. However, while this technology has a potential benefit, there is widespread concern that consumers’ fears around privacy and data protection prevent them from downloading such apps. By focusing on this emerging crisis, in this study, we investigate the potential obstacles imposed by privacy concerns (i.e., the perceived risk of accepting the app permission, the perceived risk of providing the information). This study also investigates the popularity of Aarogya Setu, the Indian government’s COVID-19 app. In doing so, we examine privacy concerns through the theoretical lens of the Elaboration Likelihood Model and explore the download intentions of new users. Using the above dimensions of privacy, we then propose a conceptual framework that depicts the influence of privacy concerns over the download intention of new users. Lastly, this paper provides suggestions to allow the Aarogya Setu to improve its perceived reliability among its users and increase downloads.