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NFC mobile credit card: The next frontier of mobile payment?

Tan, Garry Wei-Han, Ooi, Keng-Boon, Chong, Siong-Choy, Hew, Teck-Soon·2014·Telematics and Informatics

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  1. Aguirre-Urreta, 2010, Is it really gender? An empirical investigation into gender effects technology adoption through the examination of individual differences, Human Technology, 6, 155, 10.17011/ht/urn.201011173090 · DOI
  2. Amin, 2007, An analysis of mobile credit card usage intentions, Information Management & Computer Security, 15, 260, 10.1108/09685220710817789 · DOI
  3. Amin, 2008, Factors affecting the intentions of customers in Malaysia to use mobile phone credit cards, Management Research News, 31, 193, 10.1108/01409170810876062 · DOI
  4. Amin, 2012, Patronage factors of Malaysian local customers toward Islamic credit cards, Management Research Review, 35, 512, 10.1108/01409171211238271 · DOI
  5. Anderson, 1988, Structural equation modelling in practice: a review and recommended two step approach, Psychological Bulletin, 49, 411, 10.1037/0033-2909.103.3.411 · DOI · Paper page
  6. Bharati, 2004, An empirical investigation of decision-making satisfaction in web-based decision support systems, Decision Support Systems, 37, 187, 10.1016/S0167-9236(03)00006-X · DOI · Paper page
  7. Calisir, 2009, Predicting the behavioral intention to use enterprise resource planning systems: an exploratory extension of the technology acceptance model, Management Research News, 32, 597, 10.1108/01409170910965215 · DOI
  8. Chang, 2010, Drivers and moderators of consumer behaviour in the multiple use of mobile phones, International Journal Mobile Communications, 8, 88, 10.1504/IJMC.2010.030522 · DOI
  9. Chen, 2011, User acceptance of NFC mobile phone service: an investigation based on the UTAUT model, The Service Industries Journal, 1
  10. Chen, W., Hancke, G.P., Mayes, K.E., Lien, Y., Chiu, J.H., 2010. NFC mobile transactions and authentication based on GSM network. In: Near Field Communication (NFC), 2010 Second International Workshop, pp. 83–89. · doi:10.1109/nfc.2010.15
  11. Chong, 2012, Predicting consumer decisions to adopt mobile commerce: cross country empirical examination between China and Malaysia, Decision Support Systems, 53, 34, 10.1016/j.dss.2011.12.001 · DOI · Paper page
  12. Costa, 2001, Gender differences in personality traits across cultures: robust and surprising findings, Journal of Personality and Social Psychology, 81, 322, 10.1037/0022-3514.81.2.322 · DOI · Paper page
  13. Crespo, 2008, Explaining B2C e-commerce acceptance: an integrative model based on the framework by Gatignon and Robertson, Interacting with Computers, 20, 212, 10.1016/j.intcom.2007.11.005 · DOI
  14. Cruz, 2010, Mobile banking rollout in emerging markets: evidence from Brazil, International Journal of Bank Marketing, 28, 342, 10.1108/02652321011064881 · DOI · Paper page
  15. Curran, 2008, A multilingual mobile university information portal designed to cater for visiting overseas students, Interactive Technology and Smart Education, 5, 4, 10.1108/17415650810871556 · doi:10.1108/17415650810871556
  16. Dahlberg, 2008, Past, present and future of mobile payment research: a literature review, Electronic Commerce Research and Applications, 7, 165, 10.1016/j.elerap.2007.02.001 · DOI · Paper page
  17. Davis, 1989, User acceptance of computer technology: a comparison of two theoretical models, Management Science, 35, 982, 10.1287/mnsc.35.8.982 · DOI · Paper page
  18. Eagly, 1991, Explaining sex differences in social behavior: a meta-analytic perspective, Personality and Social Psychology Bulletin, 17, 306, 10.1177/0146167291173011 · DOI · Paper page
  19. Feng, 2006, The impact of TQM practices on performance: a comparative study between Australian and Singaporean organizations, European Journal of Innovation Management, 9, 269, 10.1108/14601060610678149 · DOI · Paper page
  20. Fornell, 1981, Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18, 39, 10.1177/002224378101800104 · DOI · Paper page
  21. Gefen, 1997, Gender difference in the perception and use of e-mail: an extension to the Technology Acceptance Model, MIS Quarterly, 21, 389, 10.2307/249720 · DOI · Paper page
  22. Gefen, 2000, Structural equation modeling and regression: guidelines for research practice, Communications of the Association for Information Systems, 4, 1
  23. Goldsmith, 1991, Measuring consumer innovativeness, Journal of the Academy of Marketing Science, 19, 209, 10.1007/BF02726497 · DOI · Paper page
  24. Hashemi, M.R., Soroush, E., 2006. A Secure m-payment protocol for mobile devices. In: Proceedings of the Canadian Conference on Electrical and Computer Engineering, IEEE, Ottawa, pp. 294–297. · doi:10.1109/ccece.2006.277380
  25. Hew, 2011, An empirical analysis of Malaysian pre-university students’ ICT competency gender differences, International Journal of Network and Mobile Technologies, 2, 15
  26. Karahanna, 1999, Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs, MIS Quarterly, 23, 183, 10.2307/249751 · DOI · Paper page
  27. Kuo, 2009, Towards an understanding of the behavioral intention to use 3G mobile value-added services, Computers in Human Behavior, 25, 103, 10.1016/j.chb.2008.07.007 · DOI · Paper page
  28. LaRose, 2007, Closing the rural broadband gap: promoting adoption of the Internet in rural America, Telecommunications Policy, 31, 359, 10.1016/j.telpol.2007.04.004 · DOI · Paper page
  29. Leavitt, 2010, Payment applications make e-commerce mobile, Computer, 43, 19, 10.1109/MC.2010.357 · doi:10.1109/mc.2010.357
  30. Lee, O., 2004. Sound-based mobile payment system. In: Proceedings of the IEEE International Conference on Web Services (ICWS), pp. 820–882. · doi:10.1109/icws.2004.1314958
  31. Lee, 2009, Understanding the behavioural intention to play online games: an extension of the theory of planned behavior, Online Information Review, 33, 849, 10.1108/14684520911001873 · DOI · Paper page
  32. Leong, 2011, Influence of individual characteristics, perceived usefulness and ease of use on mobile entertainment adoption, International Journal Mobile Communications, 9, 359, 10.1504/IJMC.2011.041141 · DOI
  33. Leong, 2011, Influence of gender and English proficiency on Facebook mobile adoption, International Journal of Mobile Communications, 9, 495, 10.1504/IJMC.2011.042456 · DOI
  34. Leong, 2012, The determinants of customer loyalty in Malaysian mobile telecommunication services: a structural analysis, International Journal of Services, Economics and Management, 4, 209, 10.1504/IJSEM.2012.048620 · DOI
  35. Leong, 2013, Predicting the determinants of the NFC-enabled mobile credit card acceptance: a neural networks approach, Expert Systems with Applications, 40, 5604, 10.1016/j.eswa.2013.04.018 · DOI · Paper page
  36. Leong, 2013, Modeling the stimulators of the behavioral intention to use mobile entertainment: does gender really matter?, Computers in Human Behavior, 29, 2109, 10.1016/j.chb.2013.04.004 · DOI · Paper page
  37. Liu, 2010, Factors driving the adoption of m-learning: an empirical study, Computers & Education, 55, 1211, 10.1016/j.compedu.2010.05.018 · DOI · Paper page
  38. Loke, 2011, Credit card averters and amassers: evidence from Malaysia, Asian Economic Journal, 25, 397, 10.1111/j.1467-8381.2011.02068.x · doi:10.1111/j.1467-8381.2011.02068.x
  39. Lopez-Nicolas, 2008, An assessment of advanced mobile services acceptance: contributions from TAM and diffusion theory models, Information & Management, 45, 359, 10.1016/j.im.2008.05.001 · DOI · Paper page
  40. Lu, 2003, Technology acceptance model for wireless internet, Internet Research: Electronics Networking Applications and Policy, 13, 206, 10.1108/10662240310478222 · DOI · Paper page
  41. Lu, J., Yu, C.S., Liu, C., 2006. Gender and age differences in individual decisions about wireless mobile data services: a report from China. China Mobile Value-Added Services Analysis Report. URL: <http://helsinkimobility.aalto.fi/papers/Mobile%20Services_1_3.pdf> (accessed 11.02.12). · DOI
  42. Lu, 2008, Determinants of accepting wireless mobile data services in China, Information & Management, 45, 52, 10.1016/j.im.2007.11.002 · DOI · Paper page
  43. Lu, 2011, Dynamics between the trust transfer process and intention to use mobile payment services: a cross-environment perspective, Information & Management, 48, 393, 10.1016/j.im.2011.09.006 · DOI · Paper page
  44. Luarn, 2005, Toward an understanding of the behavioral intention to use mobile banking, Computer in Human Behaviour, 21, 873, 10.1016/j.chb.2004.03.003 · DOI · Paper page
  45. Mallat, 2007, Exploring consumer adoption of mobile payments – a qualitative study, Journal of Strategic Information Systems, 16, 413, 10.1016/j.jsis.2007.08.001 · DOI · Paper page
  46. Mardia, 1974, Applications of some measures of multivariate skewness and kurtosis in testing normality and robustness studies, Sankhya, Series B, 36, 115
  47. McCoy, 2005, Integrating national culture into individual IS adoption research: the need for individual level measures, Communications of the Association for Information Systems, 15, 211, 10.17705/1CAIS.01512 · DOI · Paper page
  48. Nicole, 2010, Predicting young consumers’ take up of mobile banking services, International Journal of Bank Marketing, 28, 342
  49. Nysveen, 2005, Intentions to use mobile services: antecedents and cross-service comparisons, Journal of the Academy of Marketing Science, 33, 330, 10.1177/0092070305276149 · DOI · Paper page
  50. Ondrus, J., Pigneur, Y., 2007. An assessment of NFC for future mobile payment systems. In: Proceedings of the Sixth International Conference on Mobile Business (ICMB), IEEE. · DOI
  51. Pasquet, M., Reynaud, J., Rosenberger, C., 2008. Secure payment with NFC mobile phone in the smart touch project. In: Collaborative Technologies and Systems (CTS) International Symposium, IEEE, pp. 121–126. · DOI
  52. Pope, 2011, Mobile payments: the reality on the ground in selected Asian countries and the United States, International Journal of Mobile Marketing, 6, 88
  53. Ruijun, G., Yao, J., 2010. Comparison and tendency of main mobile payment technologies in China. In: International Conference on Future Information Technology and Management Engineering, IEEE, pp. 434–437. · doi:10.1109/fitme.2010.5656561
  54. Sarel, 2003, Marketing online banking services: the voice of the customer, Journal of Financial Services Marketing, 8, 106, 10.1057/palgrave.fsm.4770111 · DOI
  55. Saxena, A., Das, M.L., Gupta, A., 2005. MMPS: a versatile mobile-to-mobile payment system. In: Proceedings of the International Conference on Mobile Business (ICMB), IEEE, Australia, pp. 400–405. · doi:10.1109/icmb.2005.61
  56. Serenko, 2008, A model of user adoption of interface agents for email notification, Interacting with Computers, 20, 461, 10.1016/j.intcom.2008.04.004 · DOI · Paper page
  57. Sim, 2011, Exploring the individual characteristics on the adoption of broadband: an empirical analysis, International Journal of Network and Mobile Technologies, 2, 1
  58. Sun, 2000, The role of moderating factors in user technology acceptance, International Journal of Human-Computer Studies, 64, 53, 10.1016/j.ijhcs.2005.04.013 · DOI · Paper page
  59. Tan, 2010, The adoption of online banking in Malaysia: an empirical analysis, International Journal of Business and Management Science, 3, 169
  60. Tan, 2012, Determinants of mobile learning adoption: an empirical analysis, Journal of Computer Information Systems, 52, 82
  61. Teo, 2003, Adoption of WAP-enabled mobile phones among Internet users, Omega: The International Journal of Management Science, 31, 483, 10.1016/j.omega.2003.08.005 · DOI · Paper page
  62. Teo, E., Fraunholz, B., Unnithan, C., 2005. Inhibitors and facilitators for mobile payment adoption in Australia: a preliminary study. In: Proceedings of the International Conference on Mobile Business (ICMB), pp. 663–666. · doi:10.1109/icmb.2005.47
  63. Teo, 2012, What matters most in mobile payment acceptance? A structural analysis, International Journal of Network and Mobile Technologies, 3, 49
  64. Teo, 2012, Can the demographic and subjective norms influence the adoption of mobile banking?, International Journal of Mobile Communications, 10, 578, 10.1504/IJMC.2012.049757 · DOI
  65. Venkatesh, 2000, A theoretical extension of the Technology Acceptance Model: four longitudinal field studies, Management Science, 46, 186, 10.1287/mnsc.46.2.186.11926 · DOI · Paper page
  66. Venkatesh, 2000, Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behaviour, MIS Quarterly, 24, 115, 10.2307/3250981 · DOI · Paper page
  67. Wang, 2006, Predicting consumer intention to use mobile services, Information Systems Journal, 16, 157, 10.1111/j.1365-2575.2006.00213.x · DOI · Paper page
  68. Wong, 2012, Predicting the consumers’ intention to adopt mobile-shopping: an emerging market perspective, International Journal of Network and Mobile Technologies, 3, 24
  69. Zhou, 2011, Examining the critical success factors of mobile website adoption, Online Information Review, 35, 636, 10.1108/14684521111161972 · DOI · Paper page
  70. Zmijewska, A., 2005. Evaluating wireless technologies in mobile payments – a customer centric approach. In: Proceedings of the fourth International Conference on Mobile Business (ICMB), Sydney, Australia.

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Metadata

Authors
Tan, G. W.-H., Ooi, K.-B., Chong, S.-C., & Hew, T.-S.
Venue
Telematics and Informatics
Publisher
Elsevier BV
Published
2014-05
Volume
31
Issue
2
Pages
292-307
ISSN
0736-5853 (ISSN-L)
OpenAlex
W2139199149
Cited by
350
References
12
FWCI
43.28
Type
journal article
Language
en
Open access
closed
Licence
  • www.elsevier.com/tdm/userlicense/1.0/ (tdm)
  • www.elsevier.com/legal/tdmrep-license (tdm)

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Tan, G. W.-H., Ooi, K.-B., Chong, S.-C., & Hew, T.-S. (2014). NFC mobile credit card: The next frontier of mobile payment? Telematics and Informatics. https://doi.org/10.1016/j.tele.2013.06.002

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