Adoption of Covid-19 contact tracing app by extending UTAUT theory: Perceived disease threat as moderator

Abstract

Objectives: Contact tracing applications are technological solutions that can quickly trace and notify users of their potential exposure to the Covid-19 virus and help contain the spread of the disease. However, extant research delineating the various factors predicting the adoption of contact tracing apps is scant. The study's primary objective is to develop and validate a research model based on the unified theory of acceptance and use of technology (UTAUT), health belief model (HBM), perceived privacy risk and perceived security risk to understand the adoption of contact tracing application.

Methods: An online survey was carried out among users of the 'Aarogya Setu' contact tracing app in India. The partial least squares structural equation modelling (PLS-SEM) tool was employed to analyze data from 307 respondents.

Results: The results showed that performance expectancy, social influence, and facilitating conditions positively influenced users' intention to adopt the app. In contrast, perceived privacy and security risks were significant barriers to app adoption. Perceived disease threat as a moderator mitigated the adverse impact of perceived privacy risk on users' intention to adopt contact tracing apps.

Conclusions: The current study gives insights on both drivers and barriers to the adoption of contract tracing applications. Various theoretical and practical implications of significance are provided for academicians and practitioners to effectively promote app adoption to tackle the Covid-19 pandemic.

Keywords: Contact tracing application; Health belief model; Perceived disease threat; Privacy risk; Security risk; UTAUT.

Fig. 1

Research model Notes: → Direct effect → Moderating effect.

Fig. 2

Structural model results Notes: → Direct effect → Moderating effect **p < 0.01; ***p < 0.001 (two-tailed)