Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/107462
Title: A Model to Predict Users’ Intentions to Adopt Contact-Tracing Apps for Prevention from COVID-19
Authors: Ezzaouia, Imane 
Bulchand Gidumal, Jacques 
UNESCO Clasification: Investigación
Keywords: Covid-19
Contact-tracing apps
Intentions to use
Issue Date: 2021
Publisher: Springer 
Conference: 28th Annual International eTourism Conference ENTER21 
Abstract: Technological advances are increasingly progressing and have brought unprecedented solutions for real-world problems for various domains, particularly, when it comes to a health-related domain. This study aims to examine the predictors of users’ intentions to adopt contact-tracing apps for prevention from COVID-19. Based on the extended unified theory of acceptance and use of technology (UTAUT2), our research model incorporates the following eight constructs: performance expectancy, effort expectancy, social influence, facilitating conditions, perceived privacy, perceived value, safety and accuracy. The empirical results were obtained from a sample of 93 questionnaires (currently still in course). We used the partial least squares approach to test our hypotheses. The results reveal that performance expectancy has the strongest impact on the intentions to use contact-tracing apps. The accuracy, effort expectancy and social influence are also important, followed by perceived value, safety and perceived privacy. Facilitating condition is listed as much less important. The theoretical and managerial implications of these results are discussed.
URI: http://hdl.handle.net/10553/107462
ISBN: 978-3-030-65784-0
DOI: 10.1007/978-3-030-65785-7_51
Source: Information and Communication Technologies in Tourism / Wörndl W., Koo C., Stienmetz J.L. (eds), p. 543-548
Appears in Collections:Actas de congresos
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