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Information Systems Frontiers

Erschienen in:

01.09.2008

Understanding the behavior of mobile data services consumers

verfasst von: Se-Joon Hong, James Y. L. Thong, Jae-Yun Moon, Kar-Yan Tam

Erschienen in: Information Systems Frontiers | Ausgabe 4/2008

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Abstract

Due to rapid advances in the Internet and wireless technologies, a ubiquitous computing world is becoming a reality in the form of mobile computing. At the center of this phenomenon is mobile data services which arise from the convergence of advanced mobile communication technologies with data services. Despite the rapid growth in mobile data services, research into consumers’ usage behavior is scarce. This study attempts to identify and empirically assess the factors that drive consumers’ acceptance of mobile data services. A research model based on the decomposed theory of planned behavior and incorporating factors that represent personal needs and motivations in using mobile data services is presented. The model is tested via an online survey of 811 consumers of four categories of mobile data services (i.e., communications, information content, entertainment, and commercial transactions) associated with different usage contexts. We found that attitude, social influence, media influence, perceived mobility, and perceived monetary value influence consumers’ intention to continue usage of mobile data services. In addition, perceived ease of use, perceived usefulness, and perceived enjoyment influence attitude toward continued usage of mobile data services. Finally, separate analysis of the different categories of mobile data services highlights the influence of individual usage context on consumers’ behavior.

Vorheriger Artikel Network effects as drivers of individual technology adoption: Analyzing adoption and diffusion of mobile communication services

Nächster Artikel Social networking and digital gaming media convergence: Classification and its consequences for appropriation

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Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.CrossRef

Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665–683.CrossRef

Benbasat, I., & Zmud, R. (2003). The identity crisis within the IS discipline: Defining and communicating the discipline’s core properties. MIS Quarterly, 27(2), 183–194.

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation–confirmation model. MIS Quarterly, 25(3), 351–370.CrossRef

Brislin, R. (1970). Back-translation for cross-cultural research. Journal of Cross-cultural Psychology, 1, 185–216.CrossRef

Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399–426.

Bruner II, G. C., & Kumar, A. (2005). Explaining consumer acceptance of handheld Internet devices. Journal of Business Research, 58(5), 553–558.CrossRef

Burnkrant, R. E., & Page, T. (1988). The structure and antecedents of the normative and attitudinal components of Fishbein’s theory of reasoned action. Journal of Experimental Social Psychology, 24, 66–87.CrossRef

Campbell, M. C., & Keller, K. L. (2003). Brand familiarity and advertising repetition effect. Journal of Consumer Research, 30(2), 292–304.CrossRef

Carroll, J., Howard, S., Vetere, F., Peck, J., & Murphy, J. (2002). Just what do the youth of today want? Technology appropriation by young people. Proceedings of the 35th Annual Hawaii International Conference on System Sciences, IEEE Computer Society, Washington, DC.

Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Mahwah, NJ: Erlbaum.

Cronin, J. J., Brady, M., & Hult, T. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intention in service environments. Journal of Retailing, 76(2), 193–218.CrossRef

Davis, G. (2002). Anytime/Anyplace computing and the future of knowledge work. Communications of the ACM, 45(12), 67–73.CrossRef

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982–1003.

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.CrossRef

Dholakia, R. R., & Dholakia, N. (2004). Mobility and markets: Emerging outlines of m-commerce. Journal of Business Research, 57(12), 1391–1396.CrossRef

Dodds, W. B., Monroe, K., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluation. Journal of Marketing Research, 28, 307–319.CrossRef

Fazio, R. H., & Zanna, M. P. (1981). Direct experience and attitude-behavior consistency. In L. Berkowitz (Ed.), Advances in experimental social psychology. New York, NY: Academic.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18(1), 39–50.CrossRef

Forrester Research (2002). Segmenting Europe’s mobile consumers. Retrieved from http://www.forrester.com/ER/Research/Report/Summary/0,1338,13279,00.html.

Hong, S. J., & Tam, K. Y. (2006). Understanding the adoption of multipurpose information appliances: The case of mobile data services. Information Systems Research, 17(2), 162–179.CrossRef

Hong, S. J., Thong, J. Y. L., & Tam, K. Y. (2006). Understanding continued information technology usage behavior: A comparison of three models in the context of mobile internet. Decision Support Systems, 42, 1819–1834.CrossRef

Imielinski, T., & Badrinath, B. R. (1994). Mobile wireless computing. Communications of the ACM, 37(10), 19–28.CrossRef

Islam, N., & Fayad, M. (2003). Toward ubiquitous acceptance of ubiquitous computing. Communications of the ACM, 46(2), 89–92.CrossRef

ITU (2002). ITU Internet reports: Internet for a mobile generation. International Telecommunication Union.

ITU (2006). ITU World Telecommunication/ICT Development Report 2006: Measuring ICT for Social and Economic Development. International Telecommunication Union.

Jacoby, J. R., & Olson, J. (1977). Consumer response to price: An attitudinal, information processing perspective. In T. Wind, & P. Greenberg (Eds.), Moving ahead with attitude research (pp. 73–86). Chicago, IL: American Marketing Association.

Kannan, P. K., Chang, A., & Whinston, A. (2001). Wireless commerce: Marketing issues and possibilities. Proceedings of the 34th Hawaii International Conference on System Science, IEEE Computer Society, Washington, DC.

Karahanna, E., Straub, D., & Chervany, N. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183–213.CrossRef

Kleinrock, L. (2001). Breaking loose. Communications of the ACM, 44(9), 41–45.CrossRef

Kraut, R. E., Mukhopadhyay, T., Szczypula, J., Kiesler, S., & Scherlis, W. (1999). Information and communication: Alternative uses of the Internet in households. Information Systems Research, 10(4), 287–303.CrossRef

Ling, R., & Yttri, B. (2001). Nobody sits at home and waits for the telephone to ring: Micro and hyper-coordination through the use of the mobile telephone. In J. Katz, & M. Aakhus (Eds.), Perpetual Contact. Cambridge: Cambridge University Press.

Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173–191.

Monroe, K. B. (1990). Pricing: Making profitable decisions (2nd ed.). NY: McGraw Hill.

Monroe, K. B., & Krishnan, R. (1985). The effect of price on subjective product evaluations. In J. Jacoby, & J. Olson (Eds.), Perceived quality (pp. 209–232). Lexington, MA: Lexington Books.

Moschis, G. P., & Moore, R. Y. (1982). A longitudinal study of television advertising effects. Journal of Consumer Research, 9(3), 279–286.CrossRef

Orlikowski, W. J., & Iacono, C. S. (2001). Research commentary: Desperately seeking the “IT” in IT research—Call to theorizing the IT artifact. Information Systems Research, 12(2), 121–134.CrossRef

Pedersen, P., Methlie, L., & Thorbjornsen, H. (2002). Understanding mobile commerce end-user adoption: A triangulation perspective and suggestions for an exploratory service evaluation framework. Proceedings of the 35th Hawaii International Conference on System Science, IEEE Computer Society, Washington, DC.

Pedersen, P. E., & Nysveen, H. (2003). Using the theory of planned behavior to explain teenagers’ adoption of text messaging services. Working Paper.

Reichheld, F. F., & Schefter, P. (2000). E-Loyalty: Your secret weapon on the Web. Harvard Business Review, 78, 105–113.

Sadeh, N. (2002). M-Commerce. New York: Wiley.

Suri, R., Long, M., & Monroe, K. B. (2003). The impact of the Internet on consumer motivation on evaluation of prices. Journal of Business Research, 56(5), 379–390.CrossRef

Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.

The Economist. (2001). A survey of the MDS: The Internet, untethered. (October 13).

Thong, J. Y. L., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human–Computer Systems, 64, 799–810.CrossRef

Trappey III, R. J., & Woodside, A. G. (2005). Consumer responses to interactive advertising campaigns coupling short-message-service direct marketing and TV commercials. Journal of Advertising Research, 45(4), 382–401.

Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695–704.

Varshney, U., & Vetter, R. (2001). A framework for the emerging mobile commerce applications. Proceedings of the 34th Annual Hawaii International Conference on System Sciences, IEEE Computer Society, Washington, DC.

Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the role of intrinsic motivation. MIS Quarterly, 23(2), 239–260.CrossRef

Venkatesh, V., & Brown, S. (2001). A longitudinal investigation of personal computers in homes: Adoption determinants and emerging challenges. MIS Quarterly, 25(1), 71–102.CrossRef

Venkatesh, V., & Morris, M. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and user behavior. MIS Quarterly, 24, 115–139.CrossRef

Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003a). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.

Venkatesh, V., Ramesh, V., & Massey, A. (2003b). Understanding usability in mobile commerce. Communications of the ACM, 46(12), 53–56.CrossRef

Venkatraman, M. (1991). The impact of innovativeness and innovation type on adoption. Journal of Retailing, 67(1), 51–67.

Weiser, M. (1991). The computer for the 21st century. Scientific American, September, (pp. 94–100).

Yankee Group Research. (2002). Mobile user survey results part 1.

Zeithaml, V. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52, 2–22.CrossRef

Titel: Understanding the behavior of mobile data services consumers
verfasst von: Se-Joon Hong
James Y. L. Thong
Jae-Yun Moon
Kar-Yan Tam
Publikationsdatum: 01.09.2008
Verlag: Springer US
Erschienen in: Information Systems Frontiers / Ausgabe 4/2008
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI: https://doi.org/10.1007/s10796-008-9096-1

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