Bridging the divide: using UTAUT to predict multigenerational tablet adoption practices
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This study examined the "Unified Theory of Acceptance and Use of Technology" (UTAUT) in the context of tablet devices across multiple generations. We tested the four UTAUT determinants, performance expectancy, effort expectancy, social influence, and facilitating conditions, to determine their contributions for predicting behavioral intention to use tablets with age, gender, and user experience as moderators. 899 respondents aged 19-99 completed the survey. We found consistent generational differences in UTAUT determinants, most frequently between the oldest and youngest generations. Effort expectancy and facilitating conditions were the only determinants that positively predicted tablet use intentions after controlling for age, gender, and tablet use. We also discuss the implications of ageism and gender discrimination of technology adoption. Finally, we argue that our findings can be extended to create effective training programs for the teaching, learning, and adoption of new technologies in a variety of organizational settings.
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Negative social influence can create doubts and concerns about the effectiveness and reliability of digital technologies and reinforce the user's resistance to change.
“On the other hand, negative social influence can create doubts and concerns about the effectiveness and reliability of digital technologies and reinforce the user's resistance to change [91].”
From “Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model (2023) · cites this paper as [91]
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- Authors
- Magsamen-Conrad, K., Upadhyaya, S., Joa, C. Y., & Dowd, J.
- Affiliations
- Bowling Green State University (US)
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2015-09
- Volume
- 50
- Pages
- 186-196
- ISSN
- 0747-5632 (ISSN-L)
- PMC
- PMC4412023
- OpenAlex
- W4251087003
- Cited by
- 241
- References
- 58
- Citations by year
- 2026: 18 · 2025: 18 · 2024: 27 · 2023: 26 · 2022: 29 · 2021: 28 · 2020: 29 · 2019: 21 · 2018: 25 · 2017: 12 · 2016: 5 · 2015: 3
- FWCI
- 29.38
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Computers in Human Behavior (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- ScholarWorks@BGSU (Bowling Green State University) (submittedVersion)
- Funders
- Bowling Green State University
- National Institutes of Health
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24HD050959)
- Office of the Vice President for Research and Economic Development, University at Buffalo
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Demography › Technology Use by Older Adults
- Social Sciences › Gender Studies › Gender and Technology in Education
- Keywords
- UTAUT, generational differences, effort expectancy, facilitating conditions, social influence, performance expectancy, behavioral intention, user experience
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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