What drives purchase intention in the context of online content services? The moderating role of ethical self-efficacy for online piracy
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The degree of perceived fees has a notable influence on customers' perceived value.
“Research indicates that the degree of perceived fees has a notable influence on customers’ perceived value [29,43,45,46,47].”
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 [47]
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · see citing works
Extrinsic and Intrinsic Motivation to Use Computers in the Workplace <sup>1</sup>
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.1992.tb00945.x · Cited by 6,231 · see citing works
Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value
Babin, B. J., Darden, W. R., & Griffin, M. (1994) · Journal of Consumer Research · doi:10.1086/209376 · Cited by 6,020 · see citing works
Agarwal, R., & Karahanna, E. (2000) · MIS Quarterly · doi:10.2307/3250951 · Cited by 4,726 · see citing works
Value-based Adoption of Mobile Internet: An empirical investigation
Kim, H.-W., Chan, H. C., & Gupta, S. (2007) · Decision Support Systems · doi:10.1016/j.dss.2005.05.009 · Cited by 2,084 · see citing works
Hong, I. B., & Cho, H. (2011) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2011.02.001 · Cited by 590 · see citing works
Understanding consumer ethical decision making with respect to purchase of pirated software
Tan, B. (2002) · Journal of Consumer Marketing · doi:10.1108/07363760210420531 · Cited by 333 · see citing works
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Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations
Pillai, R., & Sivathanu, B. (2020) · Benchmarking: An International Journal · doi:10.1108/bij-04-2020-0186 · Cited by 422 · see citing works
Wang, W.-T., Wang, Y.-S., & Liu, E.-R. (2016) · Information & Management · doi:10.1016/j.im.2016.01.006 · Cited by 375 · see citing works
Self-citationAdoption of AI-empowered industrial robots in auto component manufacturing companies
Pillai, R., Sivathanu, B., Mariani, M., Rana, N. P., Yang, B., & Dwivedi, Y. K. (2022) · Production Planning & Control · doi:10.1080/09537287.2021.1882689 · Cited by 195 · see citing works
Liao, Y.-K., Wu, W.-Y., Le, T. Q., & Phung, T. T. T. (2022) · Sustainability · doi:10.3390/su14020815 · Cited by 123 · see citing works
Self-citationAl-Abdullatif, A. M., & Alsubaie, M. A. (2024) · Behavioral Sciences · doi:10.3390/bs14090845 · Cited by 126 · see citing works
“Their ability to leverage the tool efficiently contributes to their perception of the AI tool as highly useful [22,58,62].”
Reviews, trust, and customer experience in online marketplaces: the case of Mercado Libre Colombia
Peña-García, N., Losada-Otálora, M., Auza, D. P., & Cruz, M. P. (2024) · Frontiers in Communication · doi:10.3389/fcomm.2024.1460321 · Cited by 38 · see citing works
Kim, J., & Kim, J. (2021) · Sustainability · doi:10.3390/su132312974 · Cited by 29 · see citing works
- Authors
- Wang, Y.-S., Yeh, C.-H., & Liao, Y.-W.
- Affiliations
- National Changhua University of Education (TW)
- Chia Nan University of Pharmacy and Science (TW)
- Corresponding author
- Wang, Yi-Shun
- Venue
- International Journal of Information Management
- Publisher
- Elsevier BV
- Published
- 2013-02
- Volume
- 33
- Issue
- 1
- Pages
- 199-208
- ISSN
- 0268-4012 (ISSN-L)
- OpenAlex
- W2080113488
- Cited by
- 222
- References
- 7
- Citations by year
- 2026: 9 · 2025: 16 · 2024: 20 · 2023: 24 · 2022: 29 · 2021: 16 · 2020: 19 · 2019: 23 · 2018: 16 · 2017: 13 · 2016: 11 · 2015: 15 · 2014: 6 · 2013: 5
- FWCI
- 23.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Information Management (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Science Council
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Copyright and Intellectual Property
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Keywords
- purchase intention, perceived value, perceived enjoyment, perceived usefulness, moderating effect, value-based adoption model, consumer purchase behavior, digital piracy
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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