A multi-facet analysis of factors affecting the adoption of multimedia messaging service (MMS)

International Journal of Technology and Human Interaction

Volumn 5, Issue 4, 2009, Pages 18-36

  Lin, Judy Chuan Chuan ^a   Hsu, Chin Lung ^b  

^a SOOCHOW UNIVERSITY   (Taiwan)

^b DA YEH UNIVERSITY   (Taiwan)

Author keywords

Behavioral intention; Critical mass; Intrinsic motivation; MMS; Mobile services; Personal innovativeness

Indexed keywords

BEHAVIORAL INTENTION; CRITICAL MASS; INTRINSIC MOTIVATION; MMS; MOBILE SERVICES; PERSONAL INNOVATIVENESS;

MESSAGE PASSING; MULTIMEDIA SYSTEMS; TELECOMMUNICATION EQUIPMENT;

MOTIVATION;

EID: 70350072417     PISSN: 15483908     EISSN: 15483916     Source Type: Journal    
DOI: 10.4018/jthi.2009062502     Document Type: Article

References (66)

1. 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
2. Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204-215. doi:10.1287/isre.9.2.204 (Pubitemid 128120619)
3. Ahonen, T., & Moore, A. (n.d.). http://communities-dominate. blogs.com/brands/2008/09/ engagement-ma-1.html, accessed on November 15, 2008.
4. 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
5. Ajzen, I., & Fishbein, M. (1980). Understanding Attitude and Predicting Social Behavior. Englewood Cliffs, NJ: Prentice-Hall.
6. Bagozzi, R. P., & Yi, Y. (1998). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16, 74-94. doi:10.1007/BF02723327
7. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606. doi:10.1037/0033-2909.88.3.588
8. Bentler, R. M. (1989). EQS structural equations program manual (Los Angeles: BMDP Statistical Software).
9. Bonte, D. (2008, February 19). Is handset-based navigation the long awaited mobile data killer application? ABI Research.
10. Cellular.co.za. MMS has the potential to generate revenues in excess of $8.3bn by 2004.http://www.cellular.co.za/news-2004/Jan/011204-mms-has- the-potential-to-generat.htm, Jan. 7, 2004, Accessed on November 15, 2008.
11. Chau, P. Y. K., & Hu, H. P. (2002). Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories. Information & Management, 39, 297-311. doi:10.1016/S0378-7206(01)00098-2
12. Chen, L.-D., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: an extended technology acceptance perspective. Information & Management, 39, 705-719. doi:10.1016/S0378-7206(01)00127-6
13. Cheong, J. H., & Park, M. C. (2005). Mobile internet acceptance in Korea. Internet Research, 15(2), 125-140. doi:10.1108/10662240510590324
14. Constantinides, E. (2002). The 4S web-marketing mix model. Electronic Commerce Research and Applications, 1(1), 57-76. doi:10.1016/S1567-4223(02) 00006-6
15. Cyr, D., Head, M., & Ivanov, A. (2006). Design aesthetics leading to m-loyalty in mobile commerce. Information & Management, 43(8), 950-963. doi:10.1016/j.im.2006.08.009 (Pubitemid 44909370)
16. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319-339. doi:10.2307/249008
17. 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
18. Deci, E. L., & Ryan, R. M. (1987). Accessibility and stability of predictors in the theory of planned behaviour. Journal of Personality and Social Psychology, 63(5), 754-765.
19. Ebrahim, A.-H. (2004). Telecommunications in the 21st Century. ICT Week 2004 Arab Technology for Development Conference. http://www.pca.org.lb/docs/Mr. %20Ebrahim%20Haddad%20(2).ppt, Accessed on January 2, 2009.
20. FIND. (2004). http://www.find.org.tw/0105/howmany/howmany-disp.asp?id=93.
21. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.
22. Fornell, C. R. (1982). A second generation of multivariate analysis methods (Vol. I & II). New York: Praeger Special Studies.
23. Fornell, C. R., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error. JMR, Journal of Marketing Research, 18, 39-50. doi:10.2307/3151312
24. Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of E-mail: An extension to the technology acceptance model. MIS Quarterly, 21(4), 389-400. doi:10.2307/249720 (Pubitemid 127709777)
25. Hernandez, B., Jimenez, J., & Martin, M. J. (2008). Extending the technology acceptance model to include the IT decision-maker: A study of business management software. Technovation, 28(3), 112-121. doi:10.1016/j. technovation.2007.11.002
26. Hsu, C. L., & Lin, J. C.-C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45, 65-74. doi:10.1016/j.im.2007.11. 001
27. Hsu, C. L., & Lu, H. P. (2004). Why do people play online games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868. doi:10.1016/j.im.2003.08.014
28. Hsu, C. L., & Lu, H. P. (2007). Consumer behavior in on-line game communities: a motivational factor perspective. Computers in Human Behavior, 23, 1642-1659. doi:10.1016/j.chb.2005.09.001
29. Hsu, C. L., Lu, H. P., & Hsu, H. H. (2007). Adoption of the mobile internet: an empirical study of multimedia message service (MMS). OMEGA: International Journal of Management Science, 35, 715-726. doi:10.1016/j.omega. 2006.03.005
30. Hsu, M.-H., & Chiu, C.-M. (2004). Predicting electronic service continuance with decomposed theory of planned behaviour. Behaviour & Information Technology, 23(5), 359-373. doi:10.1080/01449290410001669969
31. Hsu, M. H., & Kuo, F. Y. (2003). An Investigation of Volitional Control in Information Ethics. Behaviour & Information Technology, 22(1), 53-62.
32. Husson, T., Fogg, I., & Mulligan, M. (2007, May 3). Multimedia messaging, Jupiter Research.
33. Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587-605. doi:10.1016/0305-0483(95)00035-6
34. Joreskog, K. G., & Sorbom, D. (1996). LISREL 8: Users' reference guide. Chicago: Scientific Software International.
35. Kaasinen, E. (2005). User acceptance of location-aware mobile guides based on seven field studies. Behaviour & Information Technology, 24(1), 37-49. doi:10.1080/01449290512331319049
36. Kim, B. G., Park, S. C., & Lee, K. J. (2007). A structural equation modeling of the Internet acceptance in Korea. Electronic Commerce Research and Applications, 6(4), 425-432. doi:10.1016/j.elerap.2006.08.005 (Pubitemid 350186141)
37. Kou, Y.-F., & Yu, C.-W. (2006). 3G telecommunication operators' challenges and roles: A perspective of mobile commerce value chain. Technovation, 26, 1347-1356. doi:10.1016/j.technovation.2005.08.004
38. Lai, V. S., & Li, H. (2005). Technology acceptance model for internet banking: an invariance analysis. Information & Management, 42(2), 373-386. doi:10.1016/j.im.2004.01.007
39. Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2005). Acceptance of internet-based learning medium: the role of extrinsic and intrinsic motivation. Information & Management, 42, 1095-1104. doi:10.1016/j.im.2003.10.007
40. Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2007). Understanding user acceptance of multimedia messaging services: An empirical study. Journal of the American Society for Information Science and Technology, 58(13), 2066-2077. doi:10.1002/asi.20670 (Pubitemid 350229709)
41. Liker, J. K., & Sindi, A. A. (1997). User acceptance of expert systems: a test of the theory of reasoned action. Journal of Engineering and Technology Management, 14, 147-173. doi:10.1016/S0923-4748(97)00008-8
42. Lin, J. C.-C., & Lu, H. (2000). Toward an understanding of the behavioural intention to use a web site. International Journal of Information Management, 20, 197-208. doi:10.1016/S0268-4012(00)00005-0
43. López-Nicola, Molina-Castillo, F. J., & Bouwman, H. (2008). An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models. Information and Management, 45, 359-364.
44. Lu, J., Yao, J. E., & Yu, C.-S. (2005). Personal innovativeness, social influences and adoption of wireless internet services via mobile technology. The Journal of Strategic Information Systems, 14, 245-268. doi:10.1016/j.jsis.2005.07.003 (Pubitemid 41400614)
45. Luarn, P., & Lin, H.-H. (2005). Toward an understanding of the behavioral to use mobile banking. Computers in Human Behavior, 21, 873-891. doi:10.1016/j.chb.2004.03.003 (Pubitemid 40319865)
46. Lucas, H. C., & Spitler, V. K. (2000). Implementation in a world of workstations and networks. Information & Management, 38(2), 119-128. doi:10.1016/S0378-7206(00)00059-8
47. Luo, W., & Strong, D. (2000). Perceived critical mass effect on groupware acceptance. European Journal of Information Systems, 9(2), 91-103. doi:10.1057/palgrave/ejis/3000358
48. Mobiletracker. Fee slow MMS adoption. January 19, 2007, http://www.mobiletracker.net/archives/2007/01/19/nyc-picture-messaging
49. Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230. doi:10.1016/S0378-7206(00)00061-6
50. 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), 192-222. doi:10.1287/isre.2.3.192
51. Pavlou, P. A., & Fygenson, M. (2006). Understanding and Predicting Electronic Commerce Adoption: An Extension of the Theory of Planned Behavior. MIS Quarterly, 30(1), 115-143.
52. Pikkarainenk, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model. Internet Research, 14(3), 224-235. doi:10.1108/ 10662240410542652 (Pubitemid 38882668)
53. Pin, L., & Lin, H.-H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873-891. doi:10.1016/j.chb.2004.03.003
54. Riemenschneider, C. K., Harrison, D. A., & Jr, P. P. M. (2003). Understanding it adoption decisions in small business: integrating current theories. Information & Management, 40, 269-285. doi:10.1016/S0378-7206(02) 00010-1
55. th ed.). New York: Free Press.
56. Seyal, A. H., Rahman, M. N., & Rahim, M. M. (2002). Determinants of academic use of the Internet: a structural equation model. Behaviour & Information Technology, 21(1), 71-86. doi:10.1080/01449290210123354
57. Shapiro, C., & Varian, H. (1999). Information Rules: A Strategic Guide to the Network Economy. Harvard Business School Press.
58. Strother, N., & Ask, J. (2008, September 9). MMS marketing. JupiterResearch.
59. Teo, T. S. H., Lim, V. K. G., & Lai, R. Y. C. (1999). Intrinsic and extrinsic motivation in Internet usage. OMEGA: International Journal of Management Science, 27(1), 25-37. doi:10.1016/S0305-0483(98)00028-0
60. Teo, T. S. H., & Pok, S. H. (2003). Adoption of WAP-enabled mobile phones among Internet users. OMEGA: International Journal of Management Science, 31, 483-498. doi:10.1016/j.omega.2003.08.005 (Pubitemid 37325114)
61. Vellerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motivation. Advances in Experimental Social Psychology, 29, 271-360. doi:10.1016/S0065-2601(08)60019-2
62. Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? gender, social Influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139. doi:10.2307/3250981
63. Venkatesh, V., Speier, C., & Morris, M. G. (2002). User Acceptance Enablers in Individual Decision Making About Technology: Toward an Integrated Model. Decision Sciences, 33(2), 297-315. doi:10.1111/j.1540-5915.2002.tb01646.x
64. Verkasalo, H., & Hämmäinen, H. (2007). A handset-based p latform f o r measuring mobile service usage . Info, 9(1), 80-96. doi:10.1108/14636690710725085 (Pubitemid 46140401)
65. Wang, Y. S., Lin, H. H., & Luarn, P. (2006). Predicting consumer intention to use mobile service. Information Systems Journal, 16, 157-179. doi:10.1111/j.1365-2575.2006.00213.x
66. Yang, Z., Cai, S., Zhou, Z., & Zhou, N. (2005). Development and validation of an instrument to measure user perceived service quality of information presenting web portal. Information & Management, 42, 575-589. doi:10.1016/S0378-7206(04)00073-4 (Pubitemid 40114727)