Objectives: Digital contact tracing (DCT) was touted as an effective alternative to lockdown and other restrictive measures in controlling the spread of the COVID-19 pandemic. Despite considerable investments in research and development, the usage of DCT apps was found to be phenomenally low across the world. In this context, the current study investigates the factors influencing citizens’ continuance intentions to use the DCT app. Methods: A theoretical framework was developed by extending the Expectation-confirmation model (ECM) of Information system continuance with Technology trust theory and a contextual factor perceived security and privacy to predict citizens’ continuance intentions to use the DCT app. The model was empirically tested using data from a field survey of 206 actual users of a DCT app implemented in India. Results: The findings reveal that user satisfaction, trust in government, and trust in technology are significant predictors of citizens’ continuance intention. The model demonstrates high explanatory power by explaining 57.8% of the variance of continuance intention. It also validates the role of perceived security and privacy and trust in technology in determining user satisfaction. Conclusion: The study makes a theoretical contribution by extending the ECM framework to predict DCT app continuance behavior. The insights from the study could be helpful for developers and policymakers in crafting strategies to improve the usage of DCT apps during future disease outbreaks.
All Science Journal Classification (ASJC) codes
- Biomedical Engineering
- Health Policy