DOI QR코드

DOI QR Code

Toward Developing a Mobile Channel Extension Model: Roles of Compatibility, Subjective Norm, and Media Influences

  • Lee, Hyun-Hwa (Dept. of Fashion Design & Textiles, Inha University) ;
  • Kim, Ji-Hyun (Dept. of Apparel, Housing, & Resource Management, Virginia Polytechnic Institute and State University)
  • Received : 2011.09.30
  • Accepted : 2011.12.22
  • Published : 2011.12.31

Abstract

The present research developed and empirically examined a theoretical model called a Mobile Channel Extension Model for consumer behavior toward mobile commerce. We proposed three antecedents: compatibility of, subjective norm regarding, and media influence regarding mobile use for communication purposes that influence the attitude toward the subjective norm and media influences of mobile use for shopping. These in turn positively influenced the consume's intention to use mobile devices for shopping. A Structural equation modeling analysis, using the data collected from a national online survey of 524 U. S. multichannel shoppers, confirmed the proposed model. The theoretical implications of these effects were discussed and managerial suggestions were made for both academicians and practitioners.

Keywords

References

  1. Toner, M. M., Sawka, M. N., Foley, M. E., & Pandolf, K. B. (1986). Effects of body mass and morphology on thermal responses in water. Journal of Applied Physiology, 60(2), 521-525. https://doi.org/10.1063/1.337441
  2. Ajzen, I., & Fishbein, M. (1980).Understanding attitudes and predicting social behavior. Englewood Cliff, NJ: Prentice-Hall.
  3. Armstrong, J. S., & Overton, T. S. (1977). Estimation nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396-402. https://doi.org/10.2307/3150783
  4. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. https://doi.org/10.1007/BF02723327
  5. Balabanis, G., & Reynolds, N. L. (2001). Consumer attitudes towards multichannel retailer's websites: The role of involvement, brand attitude, internet knowledge and visit duration. Journal of Business Strategies, 18(2), 105-129.
  6. Ball-Rokeach, S. J., & DeFleur, M. L. (1976). A dependency model of mass media effects. Communication Research, 3(1), 3-21. https://doi.org/10.1177/009365027600300101
  7. Binge, E., Ruiz, C., & Sanz, S. (2007). Key drivers of mobile commerce adoption: An exploratory study of Spanish mobile users. Journal of Theoretical and Applied Electronic Commerce Research, 2(2), 48-60.
  8. Bhattacherjee, A. (2000). Acceptance of e-commerce services: The case of electronic brokerages. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systemsand Humans, 30(4), 411-420. https://doi.org/10.1109/3468.852435
  9. Bruner II, G, C., & Kumar, A. (2005). Explaining consumer acceptance of handheld Internet devices. Journal of Business Research, 58(5), 553-558. https://doi.org/10.1016/j.jbusres.2003.08.002
  10. Chen, L. D., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: An extended technology acceptance perspective. Information and Management, 39(8), 705-719. https://doi.org/10.1016/S0378-7206(01)00127-6
  11. Chen, J. V., Yen, D. C., & Chen, K. (2009). The acceptance and diffusion of the innovative smart phone use: A case study of a delivery service company in logistics. Information and Management, 46(4), 241-248. https://doi.org/10.1016/j.im.2009.03.001
  12. Cheong, J. H., & Park, M. C. (2005). Mobile internet acceptance in Korea. Internet Research: Electronic Networking Applications and Policy, 15(2), 125-140. https://doi.org/10.1108/10662240510590324
  13. Constantiou, I. D., Damsgaard, J., & Knutsen, L. (2006). Exploring perceptions and use of mobile services: User differences in an advancing market. International Journal of Mobile Communications, 4(3), 231-247. https://doi.org/10.1504/IJMC.2006.008940
  14. Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychology Bulletin, 52, 281-302. https://doi.org/10.1037/h0040957
  15. Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
  16. Dillman, D. A. (2007). Mail and internet surveys: The tailored design method (2nd ed.). New York: John Wiley and Sons.
  17. Frattaroli, M. (2009). Compete blog: Cross-channel retail-what are online customers doing today? RetailWire. Retrieved April 3, 2010, from http://www.retailwire.com/Discussions/Sngl_Discussion.cfm/13922
  18. Fornell, C., & Larcker D. F. (1981). Evaluating structural equation models with unobservable variables and measurement models. Journal of Marketing Research, 18(1),39-50. https://doi.org/10.2307/3151312
  19. Grant, A. E., Guthrie, K. K., & Ball-Rokeach, S. J. (1991). Television shopping: A media system dependency perspective. Communication Research, 18(6), 773-798. https://doi.org/10.1177/009365091018006004
  20. Hair, J. F., Tatham, R. L., Anderson R. E., & Black, W. (1998). Multivariate data analysis. Upper Saddle River, NJ: Prentice-Hall
  21. Hung, S. Y., Chang, C. M., & Yu, T. J. (2006). Determinantsof user acceptance of the e-government services: The case of online tax filing and payment system. Government Information Quarterly, 23(1), 97-122. https://doi.org/10.1016/j.giq.2005.11.005
  22. IANS. (2010, February 16). Five billion people to use cell phones in 2010: UN. Thaindian News. Retrieved April 1, 2011, from http://www.thaindian.com/newsportal/sci-tech/five-billion-people-to-use-cell-phones-in-2010-un_100320649.html
  23. Kim, J. H., Ma, Y. J., & Park, J. H. (2009). Are U. S. consumers ready to adopt mobile technology for fashion goods? An integrated theoretical approach. Journal of Fashion Marketing and Management, 13(2), 215-230. https://doi.org/10.1108/13612020910957725
  24. Kim, J. H., & Park, J. H. (2005). A consumer shopping channel extension model: Attitude shift toward the online retailer. Journal of Fashion Marketing and Management,9(1), 106-121. https://doi.org/10.1108/13612020510586433
  25. Ko, E. J., Kim, E. Y., & Lee, E. K. (2009). Modeling consumer adoption of mobile shopping for fashion products in Korea. Psychology and Marketing, 26(7), 669-687. https://doi.org/10.1002/mar.20294
  26. Kulviwat, S., Bruner, G. C. II, Kumar, A., Nasco, S. A., & Clark, T. (2007). Toward a unified theory of consumer acceptance of technology. Psychology and Marketing, 24(12), 1067-1092.
  27. Lee, H. H., & Kim, J. H. (2010). Investigating dimensionality of multichannel retailer's cross-channel integration practices and effectiveness: Shopping orientation and loyalty intention. Journal of Marketing Channels, 17(4), 281-312. https://doi.org/10.1080/1046669X.2010.512859
  28. Lee, H. H., & Lee, S. E. (2007). Mobile commerce: An analysis of key success factors. Journal of Shopping Center Research, 14(2), 29-62.
  29. Lee, H. H., & Lee, S. E. (2010). Internet vs. mobile services: Comparisons of gender and ethnicity. Journal of Research in Interactive Marketing, 4(4), 346-375. https://doi.org/10.1108/17505931011092835
  30. Li, W., & McQueen, R. J. (2008). Barriers to mobile commerce adoption: An analysis framework for a country-level perspective. International Journal of Mobile Communication, 6(2), 231-257. https://doi.org/10.1504/IJMC.2008.016579
  31. Lu, J., Yu, C. S., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless Internet. Internet Research: Electronic Networking Applications and Policy, 13(3), 206-222. https://doi.org/10.1108/10662240310478222
  32. Mallata, N., Rossia, M., Tuunainen, V. K., & Oorni, A. (2009). The impact of use context on mobile services acceptance: The case of mobile ticketing. Information and Managementm, 46(3), 190-195. https://doi.org/10.1016/j.im.2008.11.008
  33. Moorman, J. (2009). Industry surveys: Telecommunications, wireless. New York: Standard & Poor's Industry surveys.
  34. Mort, G. S., & Drennan, J. (2002). Mobile digital technology: Emerging issues for marketing. Journal of Database Marketing, 10(1), 9-23. https://doi.org/10.1057/palgrave.jdm.3240090
  35. Murphy, S. (2007). Getting iReady. Chain Store Age, 83(8), 84.
  36. Nysveen, H., Pedersen, P. E., & Thorbjørnsen, H. (2005a). Intentions to use mobile services: Antecedents and cross-service comparisons. Journal of the Academy of Marketing Science, 33(3), 330-346. https://doi.org/10.1177/0092070305276149
  37. Nysveen, H., Pedersen, P. E., & Thorbjørnsen, H. (2005b). Explaining intention to use mobile chat services: Moderating effects of gender. Journal of Consumer Marketing, 22(5), 247-256. https://doi.org/10.1108/07363760510611671
  38. Pentina, I., & Hasty, R. W. (2009). Effects of multichannel coordination and e-commerce outsourcing on online retail performance. Journal of Marketing Channels, 16(4), 359-374. https://doi.org/10.1080/10466690903188021
  39. Premkumar, G., Ramamurthy, K., & Liu, H. N. (2008). Internetmessaging: An examination of the impact of attitudinal, normative, and control belief systems. Information and Management, 45(7), 451-457. https://doi.org/10.1016/j.im.2008.06.008
  40. Rangaswamy, A., & Van Bruggen, G. H. (2005). Opportunities and challenges in multichannel marketing: An in-troduction to the special issue. Journal of Interactive Marketing, 19(2), 5-11. https://doi.org/10.1002/dir.20037
  41. Rogers, E. M. (1995). Diffusion of Innovations (4th ed.). NewYork, NY: Free Press.
  42. Shankar, V., & Winer, R. S. (2005). Interactive marketing goes multichannel. Journal of Interactive Marketing, 19(2), 2-3. https://doi.org/10.1002/dir.20038
  43. Shao, Y. P. (1999). Expert systems diffusion in British banking: Diffusion models and media factor. Information and Management, 35(1), 1-8. https://doi.org/10.1016/S0378-7206(98)00071-8
  44. Skumanich, S. A., & Kintsfather, D. P. (1998). Individual media dependency relations within television shopping programming: A causal model reviewed and revised. Communication Research, 25(2), 200-219. https://doi.org/10.1177/009365098025002004
  45. Tsang, M. M., Ho, S. C., & Liang, T. P. (2004). Consumer attitudes toward mobile advertising: An empirical study. International Journal of Electronic Commerce, 8(3), 65-78.
  46. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176. https://doi.org/10.1287/isre.6.2.144
  47. Vijayasarathy, L. R. (2004). Predictong consumer intentions to use on-line shopping: The case for and augmented technology acceptance model. Information and Management, 41(6), 747-762.
  48. Vollmer, C. (2008). Always on: Advertising, marketing and media in an era of consumer control. New York: McGraw-Hill.
  49. Wakefield, K. L., & Baker, J. (1998). Excitement at the mall: Determinants and effects on shopping response. Journal of Retailing, 74(4), 515-539. https://doi.org/10.1016/S0022-4359(99)80106-7
  50. Wei, R., Xiaoming, H., & Pan, J. (2010). Examining user behavioral response to SMS ads: Implications for the evolution of the mobile phone as a bona-fide medium. Telematics and Informations, 27(1), 32-41. https://doi.org/10.1016/j.tele.2009.03.005
  51. Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management, 42(5), 719-729. https://doi.org/10.1016/j.im.2004.07.001

Cited by

  1. The effects of self-monitoring tendency on young adult consumers’ mobile dependency vol.50, 2015, https://doi.org/10.1016/j.chb.2015.04.009
  2. Under the sway of a mobile device during an in-store shopping experience vol.34, pp.7, 2017, https://doi.org/10.1002/mar.21019
  3. Salient antecedents of mobile shopping intentions: Media dependency, fashion/brand interest and peer influence vol.4, pp.4, 2013, https://doi.org/10.1080/20932685.2013.817140