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Cited by 92Technology Adoption and User BehaviourHealth, Technology, Consumer BehaviorConsumer Behavior and Marketing Influence

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A Study of Factors Affecting the Intention to Use Mobile Payment Services in Vietnam

Open access
Gia-Shie Liu, Pham Tan Tai·2016·Economics World
DOI 10.17265/2328-7144/2016.06.001
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Abstract

The goal of this paper is to spot out factors affecting the intention to use mobile payment service plan in Vietnam.This study attempts to analyze the impact of various variables extracted from mobility, convenience, compatibility, M-payment knowledge, ease to use, usefulness, risk, trust, and safe to use on intention to use mobile payment.Quantitative questionnaire is used to measure responses of participants.The statistical analysis method employed in this study is to apply Structural Equation Modeling to test all hypotheses.The results indicate that the strong predictors of the intention to use M-payment are perceived ease of use and perceived usefulness.All respondents show that they do not care about risk when they have intention to use mobile payment services.Convenience of mobility, compatibility, and mobile payment knowledge have impacts on ease to use and usefulness.Among of them, compatibility has the most significant impact on ease to use and usefulness in the opinion of those surveyed.Specially, it proved that trust of safe to use has no significant impact on usefulness, but instead has direct impact on intension to use mobile payment services.The outcomes of this research have important connotations for the improvement and development of mobile payment services in Vietnam.Therefore, at the end of this paper, some suggestions based on research results are given for the future development of mobile payment service business in Vietnam.

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  1. Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Quarterly, 16, 227-247.
  2. Alsajjan, B., & Dennis, C. (2006). The impact of trust on acceptance of online banking. European Association of Education and Research in Commercial Distribution, pp. 27-30, June 2006 Brunel University, West London, United Kingdom.
  3. Amberg, M., Hirschmeier, M., & Wehrmann, J. (2004). The compass acceptance model for the analysis and evaluation of mobile services. International Journal of Mobile Communications, 2(3), 248-259.
  4. Anckar, B., & D'Incau, D. (2002). Value creation in mobile commerce. Findings from a consumer survey. JITTA: Journal of Information Technology Theory & Application, 4(1), 43-65.
  5. Antovski, L., & Gusev, M. (2003). M-payments. Proceedings of The 25th International Conference on Information Technology Interfaces. Cavtat, Croatia, 16-19 June, 95-100.
  6. Au, Y. A., & Kauffman, R. J. (2008). The economics of mobile payments: Understanding stakeholder issues for an emerging financial technology application. Electronic Commerce Research and Applications, 7(2), 141-164.
  7. Awamieh, R., & Fernandes, C. (2005). Internet Banking: An empirical investigation into the extent of adoption by banks and the determinants of customer satisfaction in the United Arab Emirates. Journal of Internet Banking and Commerce, 10(1), 1-12.
  8. Bagozzi, R. P., & Foxall, G. R. (1996). Construct validation of a measure of adaptive-innovative cognitive styles in consumption. International Journal of Research in Marketing, 13, 201-213.
  9. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606.
  10. Carmines, E. G., & McIver, J. P. (1981). Unobserved variables. In G. W. Bohrnstedt and E. F. Borgatta (Eds.). Beverly Hills: Sage.
  11. Chellappa, R. K., & Pavlou, P. A. (2002). Perceived information security, financial liability and consumer trust in electronic commerce transactions. Logistics Information Management, 15(5/6), 358-368.
  12. Clarke, I. (2001). Emerging value propositions for M-commerce. Journal of Business Strategies, 18(2), 133-149.
  13. Cronbach, L. J. (1971). Test validation. In R. L. Thorndikp (Ed.), Educational Measurement, 443-507.
  14. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two. Management Science, 35(8), 982-1002.
  15. Egger, F. N. (2001). Affective design of e-commerce user interfaces: How to maximize perceived trustworthiness. Proceeding of CAHD: Conference on Affective Human Factors Design, Singapore, 317-324.
  16. Field, A. (2000). Discovering Statistics using SPSS for Windows. London-Thousand Oaks-New Delhi: Sage Publications.
  17. Garcia-Murillo, M., & Annabi, H. (2002). Customer knowledge management. Journal of the Operational Research Society, 53, 875-884.
  18. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51-90.
  19. Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(2), 186-192.
  20. Gong, M., & Xu, Y. (2004). An enhanced technology acceptance model for web-based learning. Journal of Information Systems Education, 15(4), 365-374.
  21. Grabner-Krauter, S., & Kalusha, E. (2003). Empirical research in on-line trust: A review and critical assessment. International Journal of Human Computer Studies, 58(6), 783-812.
  22. Hair, J. F. J., Anderson, E. R., Tatham, L. R., & Black, C. W. (1998). Multivariate data analysis (5th ed.). London: Prentice-Hall.
  23. Havlena, W. J., & DeSarbo, W. S. (1991). On the measurement of perceived consumer risk. Decision Sciences, 22(4), 927-939.
  24. Kassim, N. M., & Abdullah, M. A. A. (2006). The influence of attraction on Internet banking: An extension to the trust-relationship commitment model. International Journal of Bank Marketing, 24(6), 424-442.
  25. Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322.
  26. Kim, G., Shin, B., & Lee, H. G. (2009). Understanding dynamics between initial trust and usage intentions of mobile banking. Information Systems Journal, 19(3), 283-311.
  27. Lee, M. S. Y., McGoldrick, P. J., Keeling, K. A., & Doherty, J. (2003). Using ZMET to explore barriers to the adoption of 3G mobile banking services. International Journal of Retail and Distribution Management, 31(6), 340-348.
  28. Luarn, P., & Lin, H. H. (2005), Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873-891.
  29. Mallat, N. (2007). Exploring consumer adoption of mobile payments-A qualitative study. The Journal of Strategic Information Systems, 16(4), 413-432.
  30. Mallat, N., Rossi, M., & Tuunainen, V. K. (2006). The impact of use situation and mobility on the acceptance of mobile ticketing services. In Proceedings of The 39th Hawaii International Conference on System Sciences. Hawaii.
  31. Mallat, N., Rossi, M., & Tuunainen, V. K. (2004). Mobile banking services. Communications of the ACM, 47(5), 42-46.
  32. Marcketti, S., & Shelley, M. (2009). Consumer concern, knowledge and attitude towards counterfeit apparel products. International Journal of Consumer Studies, 33(3), 327-337.
  33. Mathwick, C., Malhotra, N. K., & Rigdon, E. (2001). The effect of dynamic retail experiences on experiential perceptions of value: An Internet and catalog comparison. Journal of Retailing, 78(1), 51-60.
  34. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 173-191.
  35. Munoz, J. L., Esparza, O., Aguilar, M., Carrascal, V., & Forne, J. (2010). Reliable dynamic source routing for video-streaming over mobile ad hoc networks. Computers Networks, 54(1), 79-96.
  36. Ndubisi, N. O., & Jantan, M. (2003). Evaluating IS usage in Malaysian small and medium-sized firms using TAM. Logistics Information Management, 16(6), 440-450.
  37. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York, NY: McGraw-Hill.
  38. Ondrus, J., & Pigneur, Y. (2006). Towards a holistic analysis of mobile payments: A multiple perspectives approach. Electronic Commerce Research and Applications, 5(3), 246-257.
  39. Peter, J. P., & Tarpey, L. Z. S. (1975). A comparative analysis of three consumer decision strategies. Journal of Consumer Research, 2, 29-37.
  40. Rogers, E. M. (1962). Diffusion of innovations (1st ed.). London: The Free Press.
  41. Schreier, M., & Prügl, R. (2008). Extending lead-user theory: Antecedents and consequences of consumers' lead userness. Journal of Product Innovation Management, 25(4), 331-346.
  42. Sharma, S., & Gutiérrez, J. A. (2010). An evaluation framework for viable business models for M-commerce in the information technology sector. Electronic Markets, 20(1), 33-52.
  43. Siau, K., & Shen, Z. (2002). Building consumer trust in mobile commerce. Communications of the ACM, 46(4), 91-94.
  44. Steenkamp, J. E. M., & van Trijp, H. C. M. (1991). The use of LISREL in validating marketing constructs. International Journal of Research in Marketing, 8, 283-299.
  45. Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research, 25(2), 173-180.
  46. Suh, B., & Han, I. (2002). Effect of trust on consumer acceptance of Internet banking. Electronic Commerce Research and Applications, 1(3), 247.
  47. Tan, M., & Teo, T. S. H. (2000). Factors influencing the adoption of Internet banking. Journal of the Association for Information Systems, 1(5), 1-42.
  48. Teo, T., & Pok, S. (2003). Adoption of WAP-enabled mobile phones among Internet users. Omega, 31(6), 483-498.
  49. Tornatzky, L., & Klein, K. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management, 29(1), 28-45.
  50. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 45(2), 186-204.
  51. Xu, G., & Gutierrez, J. A. (2006). An Exploratory study of killer applications and critical success: Factors in M-commerce. Journal of Electronic Commerce in Organizations, 4(4), 63-79.
  52. Zhou, T. (2011). An empirical examination of initial trust in mobile banking. Internet Research, 21(5), 527-540.

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Metadata

Authors
Liu, G.-S., & Tai, P. T.
Affiliations
Lunghwa University of Science and Technology (TW)
ORCID
Gia-Shie Liu
Venue
Economics World
Publisher
David Publishing Company
Published
2016-06-28
Volume
4
Issue
6
ISSN
2328-7144 (ISSN-L)
DOI
10.17265/2328-7144/2016.06.001
OpenAlex
W2516720885
Cited by
92
References
5
Citations by year
2026: 1 · 2025: 4 · 2024: 12 · 2023: 13 · 2022: 22 · 2021: 24 · 2020: 8 · 2019: 5 · 2018: 2 · 2017: 1
FWCI
5.06
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
Economics World (publishedVersion, cc-by-nc)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
  • Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
Keywords
mobile payment, intention to use, technology acceptance, perceived ease of use, perceived usefulness, perceived compatibility, perceived convenience, risk perception, trust, Vietnam

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