Factors Influencing Intention to use the COVID-19 Contact Tracing Application

Abstract

Due to the emergence of the COVID-19 pandemic, governments have implemented several urgent steps to minimize the disease’s effect and transmission. Supportive measures to trace contacts and warn people infected with COVID-19 were also implemented such as the COVID-19 contact tracing application. This study investigated the effects of variables influencing the intention to use the COVID-19 tracker. The extended Unified Theory of Acceptance and Use of Technology model was used to investigate user behavior using the COVID-19 tracker application. Google Form was used to construct and distribute the online survey to participants. Experiment results from 224 individuals revealed that performance expectations, trust, and privacy all have an impact on app usage intention. However, social impact, effort expectation, and facilitating conditions were not shown to be statistically significant. The conceptual model explained 60.07% of the amount of variation, suggesting that software developers, service providers, and policymakers should consider performance expectations, trust, and privacy as viable factors to encourage citizens to use the app. This study work’s recommendations and limitations are thoroughly discussed.