The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology
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Citations
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
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
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012) · MIS Quarterly · doi:10.2307/41410412 · Cited by 15,756
Valente, T. W. (2003) · Genetics in Medicine · doi:10.1097/01.gim.0000061743.67794.c4 · Cited by 13,723
The use of partial least squares path modeling in international marketing
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009) · Advances in International Marketing · doi:10.1108/s1474-7979(2009)0000020014 · Cited by 10,926
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
An assessment of the use of partial least squares structural equation modeling in marketing research
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-011-0261-6 · Cited by 8,088
Cited by
Patil, P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102144 · Cited by 820
Tamilmani, K., Rana, N. P., Wamba, S. F., & Dwivedi, R. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102269 · Cited by 660
Merhi, M., Hone, K., & Tarhini, A. (2019) · Technology in Society · doi:10.1016/j.techsoc.2019.101151 · Cited by 555
An innovation resistance theory perspective on mobile payment solutions
Kaur, P., Dhir, A., Singh, N., Sahu, G., & Almotairi, M. (2020) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102059 · Cited by 487
Johnson, V. L., Kiser, A., Washington, R., & Torres, R. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2017.10.035 · Cited by 441
Metadata
- Authors
- Oliveira, T., Thomas, M., Baptista, G., & Campos, F.
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2016-08
- Volume
- 61
- Pages
- 404-414
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W2914711619
- Cited by
- 1,361
- References
- 60
- FWCI
- 112.06
- Type
- journal article
- Language
- en
- Open access
- closed
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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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- CoChat. (2026). Citation check: Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. https://app.cochat.ai/papers/10.1016/j.chb.2016.03.030
- The paper
- Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2016.03.030
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.
