6,182
Views
240
CrossRef citations to date
0
Altmetric
Articles

Enjoyment and social influence: predicting mobile payment adoption

, , &
Pages 537-554 | Received 01 Apr 2014, Accepted 21 Feb 2015, Published online: 12 May 2015

References

  • Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665–694. doi: 10.2307/3250951
  • Agarwal, R., & Prasa, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–301. doi:10.1287/isre.9.2.204
  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. doi: 10.1016/0749-5978(91)90020-T
  • Amin, H. (2008). Factors affecting the intentions of customers in Malaysia to use mobile phone credit cards. Management Research News, 31(7), 493–503. doi:10.1108/01409170810876062
  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. doi:10.1037/0033-2909.103.3.411
  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Academy of Marketing Science, 6(1), 74–94. doi:10.1007/BF02723327
  • Bauer, R. A. (1960). Consumer behavior as risk taking. In R. S. Hancock (Ed.), Dynamic marketing for a changing world, proceedings of the 43rd conference of the American Marketing Association (pp. 389–398). Chicago: American Marketing Association.
  • Baumgartner, H., & Homburg, C. (1996). Applications of structural equation modeling in marketing and consumer resarch. International Journal of Research in Marketing, 13(2), 139–161. doi:10.1016/0167-8116(95)00038-0
  • Benbasat, I., & Barki, H. (2007). Quo vadis TAM? Journal of the Association for Information Systems, 8(4), 211–218.
  • Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. doi:10.1037/0033-2909.88.3.588
  • Carmines, E. G., & McIver, J. P. (1981). Analyzing models with unobserved variables. In G. W. Bohrnstedt & E. F. Borgatta (Eds.), Social measurement: Current issues (pp. 63–115). Beverly Hills, CA: Sage.
  • Chang, Y., Chen, C., & Zhou, H. (2009). Smart phone for mobile commerce. Computer Standards & Interfaces, 31(4), 740–747. doi:10.1016/j.csi.2008.09.016
  • Chen, K.-Y., & Chang, M.-L. (2013). User acceptance of ‘near field communication’ mobile phone service: An investigation based on the ‘unified theory of acceptance and use of technology’ model. The Service Industries Journal, 33(6), 609–623. doi:10.1080/02642069.2011.622369
  • Chen, L.-D. (2008). A model of consumer acceptance of mobile payment. International Journal of Mobile Communications, 6(1), 32–52. doi: 10.1504/IJMC.2008.015997
  • Cox, A. D., Cox, D., & Anderson, R. D. (2005). Reassessing the pleasures of store shopping. Journal of Business Research, 58(3), 250–259. doi:10.1016/S0148-2963(03)00160-7
  • Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York, NY: Harper & Row.
  • Dahlberg, T., Mallat, N., Ondrus, J., & Zmijewska, A. (2008). Past, present and future of mobile payments research: A literature review. Electronic Commerce Research and Applications, 7(2), 165–181. doi:10.1016/j.elerap.2007.02.001
  • Davis, F. D. (1989). Perceived usefulness, perceived easy of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. doi: 10.2307/249008
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1002. doi:10.1287/mnsc.35.8.982
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132. doi:10.1111/j.1559-1816.1992.tb00945.x
  • Dickinger, A., Arami, M., & Meyer, D. (2008). The role of perceived enjoyment and social norm in the adoption of technology with network externalities. European Journal of Information Systems, 17(1), 4–11. doi:10.1057/palgrave.ejis.3000726
  • Dimitriadis, S., & Kyrezis, N. (2010). The effect of trust, channel technology, and transaction type on the adoption of self-service bank channels. The Service Industries Journal, 31(8), 1293–1310. doi:10.1080/02642060903437576
  • Eze, U. C., Gan, G. G. G., Ademu, J., & Tella, S. A. (2008). Modelling user trust and mobile payment adoption: A conceptual framework. Communications of the IBIMA, 3(29), 224–231.
  • Fang, K. (1998). An analysis of electronic-mail usage. Computer in Human Behavior, 14(2), 349–374. doi:10.1016/S0747-5632(98)00012-0
  • Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474. doi:10.1016/S1071-5819(03)00111-3
  • Fishbein, M., & Ajzen, I. (1975). Belief, intention and behavior: An introduction to theory and research. Reading: Addison Wesley.
  • Fornell, C., & Larcker, D. F. (1981, February). Evaluating structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18, 39–50. doi: 10.2307/3151312
  • Gefen, D. (2000). E-commerce: The role of familiarity and trust. Omega, 28(6), 725–737. doi:10.1016/S0305-0483(00)00021-9
  • Hsu, C.-L., & Lu, H.-P. (2007). Consumer behavior in online game communities: A motivational factor perspective. Computers in Human Behavior, 23(3), 1642–1659. doi:10.1016/j.chb.2005.09.001
  • Keil, M., Beranek, P. M., & Konsynski, B. R. (1995). Usefulness and ease of use: Field study evidence regarding task considerations. Decision Support Systems, 13(3), 75–91. doi:10.1016/0167-9236(94)E0032-M
  • Keramati, A., Taeb, R., Larijani, A. M., & Mojir, n. (2011). A combinative model of behavioural and technical factors affecting ‘Mobile’-payment services adoption: An empirical study. The Service Industries Journal, 32(9), 1489–1504. doi:10.1080/02642069.2011.552716
  • Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Journal of Computers in Human Behavior, 26(3), 310–322. doi:10.1016/j.chb.2009.10.013
  • Kim, H.-W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile Internet: An empirical investigation. Decision Support Systems, 43(1), 111–126. doi:10.1016/j.dss.2005.05.009
  • Koenig-Lewis, N., Palmer, A., & Moll, A. (2010). Predicting young consumers’ take up of mobile banking services. International Journal of Bank Marketing, 28(5), 410–432. doi:10.1108/02652321011064917
  • Koivumaki, T., Ristola, A., & Kesti, M. (2006). Predicting consumer acceptance in mobile services: Empirical evidence from an experimental end user environment. International Journal of Mobile Communications, 4(4), 418–435. doi:10.1504/IJMC.2006.008950
  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behaviour. Information Systems Research, 13(2), 205–223. doi:10.1287/isre.13.2.205.83
  • Lancaster, H. (2014). France – mobile market insights, statistics and forecasts. Paul Budde Communications, Retrieved September 12, 2014, from http://www.budde.com.au/Research/France-Mobile-Market-Insights-Statistics-and-Forecasts.html#sthash.g74cUf5C.dpuf
  • Lee, M. S. Y., McGoldrick, P. J., Keeling, K. A., & Doherty, J. (2003). Using ZMET to explore barriers to the adoptation of 3G mobile banking services. [Research article (78, PR+mobile phone)]. International Journal of Retail & Distribution Management, 31(6), 340–348.
  • Lee, R., Murphy, J., & Swilley, E. (2009). The moderating influence of hedonic consumption in an extended theory of planned behaviour. The Service Industries Journal, 29(4), 539–555. doi:10.1080/02642060802287189
  • Liu, S.-F., Huang, L.-S., & Chiou, Y.-H. (2011). An integrated attitude model of self-service technologies: Evidence from online stock trading systems brokers. The Service Industries Journal, 32(11), 1823–1835. doi:10.1080/02642069.2011.574695
  • Lu, Y., Yang, S., Chau, P. Y., & Cao, Y. (2011). Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. Information & Management, 48(8), 393–403. doi:10.1016/j.im.2011.09.006
  • Mitchell, V. W., & Greatorex, M. (1993). Risk perception and reduction in the purchase of consumer services. The Service Industries Journal, 13(4), 179–200. doi:10.1080/02642069300000068
  • Miyazaki, A. D., & Fernandez, A. (2000). Internet privacy and security: An examination of online retailer disclosures. Journal of Public Policy & Marketing, 19(1), 54–61.
  • Nysveen, H., Pedersen, P. E., Thorbjørnsen, H., & Berthon, P. (2005). Mobilizing the brand: The effects of mobile services on brand relationships and main channel use. Journal of Service Research, 7(3), 257–276. doi:10.1177/1094670504271151
  • Perreault, J. W. D. (1975). Controlling order-effect bias. The Public Opinion Quarterly, 39(4), 544–551.
  • Polasik, M., & Wisniewski, T. P. (2009). Empirical analysis of internet banking adoption in Poland. International Journal of Bank Marketing, 27(1), 32–52. doi:10.1108/02652320910928227
  • Raghunathan, R., & Corfman, K. P. (2006). Is happiness shared doubled and sadness shared halved? Social influence on enjoyment of hedonic experiences. Journal of Marketing Research, 43(3), 386–394. doi:10.1509/jmkr.43.3.386
  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.
  • Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209–216. doi:10.1016/j.elerap.2009.07.005
  • Shin, D.-H. (2007). User acceptance of mobile Internet: Implication for convergence technologies. Interacting with Computers, 19(4), 472–483. doi:10.1016/j.intcom.2007.04.001
  • Shin, D.-H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computer in Human Behavior, 25(6), 1343–1354. doi:10.1016/j.chb.2009.06.001
  • Shin, D.-H. (2010). Modelling the interaction of users and mobile payment system: Conceptual framework. International Journal of Human-Computer Interaction, 26(10), 917–940. doi:10.1080/10447318.2010.502098
  • Steiger, J. H. (1989). EzPath: Causal modelling. Evanston, IL: Systat.
  • Teo, T. S. H., Lim, V. K. G., & Lai, R. Y. C. (1999). Intrinsic and extrinsic motivation in Internet usage. Omega, 27(1), 25–37. doi:10.1016/S0305-0483(98)00028-0
  • Teo, T. S. H., & Pok, S. H. (2003). Adoption of WAP-enabled mobile phones among Internet users. Omega, 31(6), 483–498. doi:10.1016/j.omega.2003.08.005
  • Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695–704.
  • Venkatesh, V. (2000). Determinates of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365. doi:10.1287/isre.11.4.342.11872
  • Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Science, 27(3), 451–481. doi:10.1111/j.1540-5915.1996.tb00860.x
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. doi: 10.1287/mnsc.46.2.186.11926
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
  • Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.
  • Wang, L., & Yi, Y. (2012). The impact of use context on mobile payment acceptance: An empirical study in China. In A. Xie & X. Huang (Eds.), Advances in computer science & education (pp. 293–299). Berlin: Springer.
  • Wilson, A., & Laskey, N. (2003). Internet based marketing research: A serious alternative to traditional research methods? Marketing Intelligence & Planning, 21(2), 79–84. doi:10.1108/02634500310465380
  • Wu, J.-H., & Wang, S.-C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719–729. doi:10.1016/j.im.2004.07.001
  • Yang, S., Lu, Y., Gupta, S., & Zhang, R. (2012). Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits. Computer in Human Behavior, 28(1), 129–142. doi:10.1016/j.chb.2011.08.019
  • Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54(2), 1085–1091. doi:10.1016/j.dss.2012.10.034

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.