The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
A model of consumer acceptance of mobile payment
Abstract
One promising area of mobile commerce (m-commerce) that is receiving growing attention globally is mobile payment (m-payment). m-payment refers to making payments using mobile devices. Understanding the determinants of consumer acceptance of m-payment will provide important theoretical contributions to the field and lead to the development of more effective m-payment devices and systems. By expanding the Technology Acceptance Model (TAM) and the Innovation Diffusion Theory (IDT), this study proposes a research model that examines the factors which determine consumer acceptance of m-payment. Significant support for the model was found in the data collected from a survey of 299 potential m-payment users. Implications for practice and suggestions for future research are provided.
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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
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
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
Significance tests and goodness of fit in the analysis of covariance structures.
Bentler, P. M., & Bonett, D. G. (1980) · Psychological Bulletin · doi:10.1037//0033-2909.88.3.588 · Cited by 19,023
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
(2003) · International Journal of Electronic Commerce · doi:10.1080/10864415.2003.11044275 · Cited by 5,715
Assessing IT Usage: The Role of Prior Experience
Taylor, S., & Todd, P. (1995) · MIS Quarterly · doi:10.2307/249633 · Cited by 2,891
Examining the technology acceptance model using physician acceptance of telemedicine technology
Hu, P. J., Chau, P. Y. K., Sheng, O. R. L., & Tam, K. Y. (1999) · Journal of Management Information Systems · doi:10.1080/07421222.1999.11518247 · Cited by 1,951
The Relative Importance of Perceived Ease of Use in IS Adoption: A Study of E-Commerce Adoption
Drexel University, Gefen, D., Straub, D., & Georgia State University (2000) · Journal of the Association for Information Systems · doi:10.17705/1jais.00008 · Cited by 1,833
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
An empirical examination of continuance intention of mobile payment services
Zhou, T. (2013) · Decision Support Systems · doi:10.1016/j.dss.2012.10.034 · Cited by 914
Yang, S., Lu, Y., Gupta, S., Cao, Y., & Zhang, R. (2012) · Computers in Human Behavior · doi:10.1016/j.chb.2011.08.019 · Cited by 679
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
Explain the intention to use smartphones for mobile shopping
Agrebi, S., & Jallais, J. (2015) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2014.09.003 · Cited by 414
Metadata
- Authors
- Chen, L. D.
- Venue
- International Journal of Mobile Communications
- Publisher
- Inderscience Publishers
- Published
- 2008
- Volume
- 6
- Issue
- 1
- Pages
- 32
- ISSN
- 1470-949X (ISSN-L)
- 1741-5217
- OpenAlex
- W2014506725
- Cited by
- 519
- References
- 11
- FWCI
- 30.13
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
