User acceptance of media tablets: An empirical examination of perceived value
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Perceived usefulness is the most significant factor affecting the adoption of media tablets, particularly when moderated by perceived value.
“According to Yu et al. [28], the most significant factor affecting the adoption of media tablets is perceived usefulness, particularly when moderated by perceived value.”
From ChatGPT in Learning: Assessing Students’ Use Intentions through the Lens of Perceived Value and the Influence of AI Literacy (2024) · cites this paper as [28]
Perceived value is commonly acknowledged as a robust predictor of technology acceptance.
“In the field of information system research, perceived value is commonly acknowledged as a robust predictor of technology acceptance [17,28,31,32,53,54].”
From ChatGPT in Learning: Assessing Students’ Use Intentions through the Lens of Perceived Value and the Influence of AI Literacy (2024) · cites this paper as [28]
An inverse correlation exists between perceived risks and perceived value when predicting technology use intention.
“A growing body of research supports the notion that an inverse correlation exists between perceived risks and perceived value when predicting technology use intention [28,29,30,36,43]”
From ChatGPT in Learning: Assessing Students’ Use Intentions through the Lens of Perceived Value and the Influence of AI Literacy (2024) · cites this paper as [28]
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- Authors
- Yu, J., Lee, H., Ha, I., & Zo, H.
- Affiliations
- Electronics and Telecommunications Research Institute (KR)
- Dankook University (KR)
- Korea Electrotechnology Research Institute (KR)
- Korea Advanced Institute of Science and Technology (KR)
- Corresponding author
- Lee, Hwansoo
- Venue
- Telematics and Informatics
- Publisher
- Elsevier BV
- Published
- 2017-07
- Volume
- 34
- Issue
- 4
- Pages
- 206-223
- ISSN
- 0736-5853 (ISSN-L)
- OpenAlex
- W2220002701
- Cited by
- 161
- References
- 83
- Citations by year
- 2026: 10 · 2025: 18 · 2024: 16 · 2023: 20 · 2022: 15 · 2021: 23 · 2020: 18 · 2019: 15 · 2018: 18 · 2017: 8
- FWCI
- 17.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Telematics and Informatics (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Keywords
- user acceptance, perceived value, perceived usefulness, perceived enjoyment, social image, risk perception, brand names, product design, functionality, content, price, personal innovativeness, technology adoption, moderating effect
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.
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