Abstract
This paper investigates the determinants of end-user adoption of the DuckDuckGo search engine coupling the standard UTAUT model with factors to reflect reputation, risk, and trust. An experimental approach was taken to validate our model, where participants were exposed to the DuckDuckGo product using a vignette. Subsequently, answering questions on their perception of the technology. The data was analyzed using the partial least squares-structural equation modeling (PLS-SEM) approach. From the nine distinct factors studied, we found that ‘Performance Expectancy’ played the greatest role in user decisions on adoption, followed by ‘Firm Reputation’, ‘Initial Trust in Technology’, ‘Social Influence’, and an individual’s ‘Disposition to Trust’. We conclude by exploring how these findings can explain DuckDuckGo’s rising prominence as a search engine.
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This research was funded in part through the New York University School of Professional Studies Full-Time Faculty Professional Development Fund.
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Saravanos, A. et al. (2022). Reputation, Risk, and Trust on User Adoption of Internet Search Engines: The Case of DuckDuckGo. In: Stephanidis, C., Antona, M., Ntoa, S., Salvendy, G. (eds) HCI International 2022 – Late Breaking Posters. HCII 2022. Communications in Computer and Information Science, vol 1654. Springer, Cham. https://doi.org/10.1007/978-3-031-19679-9_87
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