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Understanding the Adoption Dynamics of ChatGPT among Generation Z: Insights from a Modified UTAUT2 Model
Abstract
This research delves into the factors influencing the adoption of ChatGPT, a sophisticated AI-based chatbot, among Generation Z members in Croatia. Employing an extended UTAUT2 model, the impact of various factors on the behavioral intention to use ChatGPT is explored. The study included 694 Generation Z participants, and data were collected through an online survey featuring self-reporting questions. The analysis utilized statistical software packages for performing both confirmatory and exploratory factor analyses, in addition to hierarchical linear regression. Key findings reveal that performance expectancy, social influence, hedonic motivation, habit, and personal innovativeness significantly influence the behavioral intention to use ChatGPT. However, effort expectancy, facilitating conditions, and price value do not exhibit a significant impact. Notably, the study excludes the use behavior factor due to multicollinearity issues with behavioral intention. While the research does not focus on moderating factors, it reports that the adapted UTAUT2 model explains 65% of the variance in the adoption of ChatGPT by Generation Z users.
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“Social influence can reduce uncertainty by signalling that relevant others consider the technology acceptable and reliable (Krell et al., 2016); (Biloš & Budimir, 2024).”
From From search results to generative answers: A mixed-methods study of credibility assessment and trust formation in AI Overviews (2027) · cites this paper as Biloš & Budimir, 2024
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“Social influence is associated with trust rather than with intention to use because peer validation may reduce uncertainty before users form an independent assessment of the system's reliability (Krell et al., 2016); (Biloš & Budimir, 2024).”
From From search results to generative answers: A mixed-methods study of credibility assessment and trust formation in AI Overviews (2027) · cites this paper as Biloš & Budimir, 2024
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“Social influence was also associated with trust”
From From search results to generative answers: A mixed-methods study of credibility assessment and trust formation in AI Overviews (2027) · cites this paper as Biloš & Budimir, 2024
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Cited by
Sorted by citations
Faraon, M., Rönkkö, K., Milrad, M., & Tsui, E. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13492-x · Cited by 50
Casermeiro-Corpas, Y., Rejón-Guardia, F., Vallespín, M., & Molinillo, S. (2027) · Information Processing & Management · doi:10.1016/j.ipm.2026.105211
Metadata
- Authors
- Biloš, A., & Budimir, B.
- Affiliations
- Faculty of Economics and Business in Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Venue
- Journal of Theoretical and Applied Electronic Commerce Research
- Publisher
- MDPI AG
- Published
- 2024-04-13
- Volume
- 19
- Issue
- 2
- Pages
- 863-879
- ISSN
- 0718-1876
- Cited by
- 84
- References
- 13
- Language
- en
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![Figure 1 The initial version of the modified UTATU2 model. Source: based on Venkatesh Gansser & Reich [31]. Figure 1. The initial version of the modified UTATU2 model. Source: based on Venkatesh et al. [28]; Gansser & Reich [31].](/paper-figures/7e3cd71e561649b1850081837193b0a1/understanding-the-adoption-dynamics-of-chatgpt-among-generation-z-insights-from-figure-1.png)
