User Acceptance of Contact Tracing Apps: A Study During the Covid-19 Pandemic

The unpredicted coronavirus outbreak, termed COVID-19, has placed numerous governments worldwide in a difficult position. The scarcity of resources to tackle the outbreak, combined with the fear of overburdening the healthcare system, has forced most countries into a state of lockdown. Many governments have shown great interest in digital contact tracing applications that can help automate the demanding task of tracking newly infected individuals’ recent contacts. However, these apps have created a great deal of discussion, especially regarding their technology, architecture, and the adoption rate needed. This study aims to contribute to an increased understanding of the acceptance of this technology in the Norwegian population. Based on the unified theory of acceptance and use of technology (UTAUT) model, our research model incorporates the following five constructs: performance expectancy, effort expectancy, social influence, facilitating conditions, and privacy consideration. A survey was distributed amongst the Norwegian population, and the results were obtained from a sample of 258 respondents. The results from this study indicate that performance expectancy has the most significant impact on the intention to use a contact tracing application. Privacy considerations are also important, followed by effort expectancy and social influence. Facilitating conditions were found to be much less important.