The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach
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Citations
Cites
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
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
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Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
Alternative Ways of Assessing Model Fit
Browne, M. W., & Cudeck, R. (1992) · Sociological Methods & Research · doi:10.1177/0049124192021002005 · Cited by 27,200
On the Evaluation of Structural Equation Models
Bagozzi, R. P., & Yi, Y. (1988) · Journal of the Academy of Marketing Science · doi:10.1007/bf02723327 · Cited by 26,163
From Intentions to Actions: A Theory of Planned Behavior
Ajzen, I. (1985) · Action Control · doi:10.1007/978-3-642-69746-3_2 · Cited by 19,057
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Cited by
Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015) · Psychology & Marketing · doi:10.1002/mar.20823 · Cited by 922
A SEM-neural network approach for predicting antecedents of m-commerce acceptance
Liébana-Cabanillas, F., Marinković, V., & Kalinić, Z. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2016.10.008 · Cited by 583
Developing a general extended UTAUT model for M-payment adoption
Al-Saedi, K., Al-Emran, M., Ramayah, T., & Abusham, E. (2020) · Technology in Society · doi:10.1016/j.techsoc.2020.101293 · Cited by 523
Lo, P.-S., Dwivedi, Y. K., Wei-Han Tan, G., Ooi, K.-B., Cheng-Xi Aw, E., & Metri, B. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.04.013 · Cited by 396
Self-citationWhat catalyses mobile apps usage intention: An empirical analysis
Hew, J.-J., Lee, V.-H., Ooi, K.-B., & Wei, J. (2015) · Industrial Management & Data Systems · doi:10.1108/imds-01-2015-0028 · Cited by 383
Self-citation
Metadata
- Authors
- Leong, L.-Y., Hew, T.-S., Tan, G. W.-H., & Ooi, K.-B.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 40
- Issue
- 14
- Pages
- 5604-5620
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2030330997
- Cited by
- 482
- References
- 20
- FWCI
- 42.56
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. https://app.cochat.ai/papers/10.1016/j.eswa.2013.04.018
- The paper
- Leong, L.-Y., Hew, T.-S., Tan, G. W.-H., & Ooi, K.-B. (2013). Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2013.04.018
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
