隨著行動通訊證照的發放以及台灣行動通訊市場的成熟發展，行動通話用戶數持續不斷地攀升。至2010年第一季，全台手機門號人口普及率已達117.6%，已然呈現穩定飽含的狀態。是以通訊業者彼此之間的競爭顯得愈來愈激烈，台灣現行的電信業者都提供了月租費折抵通話費的優惠方案，更有不少業者提供了無限網內、甚至網外的通話時間。電信業者能靠著基礎的通話收費來獲取利潤的空間愈來愈狹礙， 發展行動通訊服務便成了唯一的一條出路。電信業者期待在3G的高速傳輸優勢下，能藉由提供行動加值服務（Mobile Data Services, MDS）來提高平均每戶貢獻度（Average Revenue Per User, ARPU）。然而現今台灣的3G用戶數已然超過1659萬戶，占總門號數的六成比例，但卻始終缺乏一個有效的殺手級應用，來吸引消費者使用並提升ARPU。
而本研究目的在於探討出影響消費者決定採用行動加值服務的重要因素，並對電信業者做出開發行動通訊服務應用之建議。以求開發出符合消費者需求，且能被消費者接受之行動加值服務內容。在本研究中透過文獻資料蒐集，分析行動通訊系統演進歷程與行動加值服務發展現況，並試著結合計劃行為理論（Theory of Planned Behavior, TPB）跟感知價值（Perceived value）以求更有效地解釋消費者採用意圖。並在結果發現享樂價值（Hedonic value）和移動性（Mobility）為最主要影響使用者意圖的因素。是以本研究認為現今的消費者決定採用行動加值服務，多是基於個人娛樂目的、為了休閒、放鬆心情。而非公務目標的使用，並且對於行動加值移動性的質疑將可能大幅降低消費者的採用意圖。是以建議電信業者應多開發娛樂導向之應用，並強化行動加值服務的連線品質，以吸引更多的消費者嚐試使用行動加值服務。

With the issuance of mobile operator licenses that resulted in intense competition, Taiwan’s mobile communication market has quickly matured. Today, there are 27.2 million cell phone numbers, compared to population of 2.3 million. A common marketing move is price competition. For example, monthly basis fee is redeemable towards mobile usage charge, unlimited calling within the same operator network and so on. These cut throat price competitions leave little room for profit for the operators. Thus, developing mobile data service (MDS) becomes an obvious way for the operators to improve their revenue. While 3G mobile network has higher transmission rate, mobile operators belief they can raise the ARPU (average revenue per user) through providing mobile data services. Taiwan already has more than 16.6 million 3G subscribers, but the operators still cannot seem to find the right formula and effective applications to achieve increased ARPU.
The purpose of this study is to explore the factors that affect consumer adoption of mobile data services. From the literature review, consumer acceptance of MDS is not fully explained by current technology acceptance model. In this study, we adopt the theory of planned behavior (TPB) and perceived value, attempting to explain consumer adoption intention. We found that hedonic value and perceived mobility are important factors that affect consumer intention. Results of data analysis revealed that consumer decide to adopt MDS, mostly for personal entertainment purpose, for fun, for relaxation, rather than official task-oriented usage. Finally, we suggest mobile operators should focus more on entertainment-oriented application development, and enhance the mobility quality of MDS.

一、中文文獻與書籍
1. 吳肇銘, 「影響網站使用意向之因素研究—以入門網站為例」, 1999.
2. 趙文彬, 「影響納稅人對綜合所得稅申報方式之使用意向研究」, 2002.
3. 鄭宗傑, 「影響網路交易顧客忠誠度之研究—以網路下單為例」, 2004.
二、英文文獻
1. Ajzen, I. “From Intentions to Actions: A Theory of Planned Behavior.” in Kuhl, J. and Beckmann, J. (Eds.), Action Controls: From Cognition to Behavior, NY: Springer Verlag, 1985.
2. Ajzen, I. “Attitudes, Traits, and Actions: Dispositional Predictions of Behavior in Personality and Social Psychology.” in Berkowitz, L. (Eds.), Advances in Experimental Social Psychology, Volume 20, CA: Academic Press, 1987, pp. 1-64.
3. Ajzen, I. Attitudes, Personality, and Behavior, Chicago. IL: The Dorsey Press. 1988.
4. Ajzen, I. “Attitude Structure and Behavior.” in Pratkanis, A.R. Breckler, S.J. and Greenwald, A.G. (Eds.), “Attitude Structure and Function.” NJ: Lawrence Erlbaum Associates, 1989, pp. 241-274.
5. Ajzen, I. “The Theory of Planned Behavior.” Organization Behavior and Human Decision Processes, 1991, 50, pp. 179-211.
6. Ajzen, I. and Fishbein, M. Understanding Attitudes and Predicting Social Behavior. NJ:Prentice-Hall, 1980.
7. Ajzen, I. and Madden, T. J. “Prediction of Goal-Directed Behavior: Attitude, Intention, and Perceived Behavioral Control.” Journal of Experimental Social Psychology, 1986, 22, pp. 453-474.
8. Anderson, J. C. and Gerbing, D. W. “Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach.” Psychological Bulletin, 1988, 103, pp. 453-60.
9. Bandura and Albert. “Self-Efficacy: Toward a Unifying Theory of Behavioral Change.” Psychological Review, 1977, 84, pp. 191-215.
10. Bandura and Albert. “Self-Efficacy Mechanism in Human Agency.” American Psychologist, 1982, 37, pp. 122-147.
11. Barrick, M. R., Mount, M. K. and Strauss, J. P. “Conscientiousness and Performance of Sales Representatives: Test of the Mediating Effects of Goal Setting.” Journal of Applied Psychology, 1993, 78, pp. 715-722
12. Batra, R., Ahtola, OT. “Measuring the Hedonic and Utilitarian Sources of Consumer Attitudes.” Marketing letters, 1991.
13. Benbasat, I. and Zmud, R. “The Identity Crisis within the IS Discipline: Defining and Communicating the Discipline’s Core Properties.” MIS Quarterly, 2003, 27(2), pp. 183–194.
14. Bentler, P. M. “Structural Modeling and Psychometrika: on Growth and Achievements.” Psychometrika, 1986, 51:1, pp. 35-51.
15. Bhattacherjee, A. “Understanding Information Systems Continuance: An Expectation–Confirmation Model.” MIS Quarterly, 2001, 25(3), pp. 351– 370.
16. Brancheau, J. C. and Wetherbe, J. C. “The Adoption of Spreadsheet Software: Testing Innovation Diffusion Theory in the Context of End-User Computiong.” Information System Research, 1990, pp. 115-143.
17. Brown, S. A. and Venkatesh, V. “Model of Adoption of Technology in Households: A Baseline Model Test and Extension Incorporating Household Life Cycle.” MIS Quarterly, 2005, 29(3), pp. 399–426.
18. Browne, M. W. and Cudeck, R. “Alternative Ways of Assessing Model Fit.” Testing Structural Equation Models, Bollen, K. A. and Long, J. S. (eds.), Sage Publications, Newbury Park, CA, 1993, pp. 136-162.
19. Chin, W. W. and Todd, P. “On the Use, Usefulness and Ease of Use of Structural Equation Modeling in MIS Research: A Note of Caution.”
MIS Quarterly, 1995, (19:2), pp. 237-246.
20. Compeau, D. R. and Higgins C. A., “Computer Self-Efficacy: Development of a Measure and Initial Test.” MIS Quarterly. 1995, pp. 185-204.
21. Davis, F. D., Bagozzi, R. P. and Warshaw, P. R. “User Acceptance of Computer Technology: A Comparison of Two Theoretical Models.” Management Science, 1989, 35, pp. 982–1003.
22. Davis, F. D. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly, 1989, 13(3),
pp. 319–340.
23. Dholakia, R. R. and Dholakia, N. “Mobility and Markets: Emerging Outlines of M-Commerce.” Journal of Business Research, 2004, 57(12),
pp. 1391–1396.
24. Dwivedi, Y. K., Khoumbati, K., Williams, M. D. and Lal, B. “Factors Affecting Consumers’ Behavioural Intention to Adopt Broadband in Pakistan.” Transforming Government: People, Process and Policy, 2007, (13),
pp. 285–297.
25. Fisher, R. J. and Price, L. L. “An Investigation into the Social Context of Early Adoption Behavior.” Journal of Consumer Research, 1992, 19(3),
pp. 477–486.
26. Fornell, C. and Larcker, D. F. “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error.” Journal of Marketing Research, 1981, (18:3), pp. 39-50.
27. Furse, D. H., Punj, G. N. and Stewart, D. W. “A Typology of Individual Search Strategies among Purchasers of New Automobiles.” Journal of Consumer Research, 1984, 10(4), pp. 417–431.
28. Galletta, D. F., Ahuja, M., Hartman, A., Teo, T. and Peace, A. G. “Social Influence and End-User Training.” Communications of the ACM, 1995,
pp. 70-79.
29. Ha, I., Yoon, Y. and Choi, M. “Determinants of Adoption of Mobile Games under Mobile Broadband Wireless Access Environment.” Information and Management, 2007, 44(3), pp. 276–286.
30. Hair, J. F., Anderson, R. E., Tatham, R. L., and Black, W. C. Multivariate Data Analysis (5th ed.), Englewood Cliffs, NJ：Prentice-Hall, 1998.
31. Harrison, David A., Peter P. Mykytyn, Jr. and Cynthia K. Riemenschneider. “Executive Decisions About Adoption of Information Technology in Small Business: Theory and Empirical Tests.” Information Systems Research, 1997, 8(2), pp. 171-195.
32. Heijden, H. “User Acceptance of Hedonic Information Systems.” MIS Quarterly, 2004, 28(4), pp. 695–703.
33. Heijden H. “Factors Influencing the Usage of Website: the Case of Generic Portal in the Netherlands.” Information & Management, 2003, 40 (6),
pp. 541–549
34. Higgins, C. A., Howell, J. M. and Compeau, D. R. “An Empirical Test of Bandura''s Model of Innovation Adoption.” paper presented at a workshop of the Diffusion Interest Group on Information Technology, Copenhagen, Denmark, December 16, 1990.
35. Hoch, S. J. and Ha, Y. W. “Consumer Learning: Advertising and the Ambiguity of Product Experience.” Journal of Consumer Research, 1986, 13(2), pp. 221–233.
36. Holbrook, M. B. and Batra, R. “Assessing the Role of Emotions as Mediators of Consumer Responses to Advertising.” Journal of Consumer Research, 1987, 14(3), pp. 404–420.
37. Holbrook, M. B. and Hirschman, E. C. “The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun.” Journal of Consumer Research, 1982, 9(2), pp. 132–140.
38. Hong, S. J., Thong, Y. L., Moon, J. Y. and Tam, K. Y. “Understanding the Behavior of Mobile Data Services Consumers.” Information Systems Frontiers, 2008, 10(4), pp. 431–445.
39. Hong, S. J. and Tam, K. Y. “Understanding the Adoption of Multipurpose Information Appliances: The Case of Mobile Data Services.” Information Systems Research, 2006, 17(2), pp. 162–179.
40. Hulland, J. “Use of Partial Least Square PLS in Strategic Management Research: a Review of Four Recent Studies.” Strategic Management Journal, 1999, 20, pp. 195-204.
41. Imielinski, T. and Badrinath, B. R. “Mobile Wireless Computing.” Communications of the ACM, 1994, 37(10), pp. 19–28.
42. ITU Internet reports: Internet for a Mobile Generation. International Telecommunication Union. 2002.
43. ITU World Telecommunication/ICT Development Report: Measuring ICT for Social and Economic Development. International Telecommunication Union. 2006.
44. Islam, N. and Fayad, M. “Toward Ubiquitous Acceptance of Ubiquitous Computing.” Communications of the ACM, 2003, 46(2), pp. 89–92.
45. Kannan, P. K., Chang, A. and Whinston, A. “Wireless Commerce: Marketing issues and Possibilities.” Proceedings of the 34th Hawaii International Conference on System Science, IEEE Computer Society, Washington, DC. 2001.
46. Karahanna, E., Straub, D. and Chervany, N. “Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-adoption and Post-adoption Beliefs.” MIS Quarterly, 1999, 23(2), pp. 183–213.
47. Keaveney, S. M. and Parthasarathy, M. “Customer Switching Behavior in Online Services: An Exploratory Study of the Role of Selected Attitudinal, Behavioral, and Demographic Factors.” Journal of the Academy of Marketing Science, 2001, 29(4), pp. 374–390.
48. Kim, B. and Han, I. “What Drives The Adoption of Mobile Data Services? An Approach from A Value Perspective.” Journal of Information Technology, 2009.
49. Kim, H. W., Chan, H. C. and Gupta, S. “Value-based Adoption of Mobile Internet: An Empirical Investigation.” Decision Support Systems, 2007, 43(1), pp. 111–126.
50. Mathieson, K. “Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior.” Information System Research, 1991, 2(3), pp. 173-191.
51. Orlikowski, W. J. and Iacono, C. S. “Research Commentary: Desperately Seeking the IT in IT research—Call to Theorizing the IT Artifact.” Information Systems Research, 2001, 12(2), pp. 121–134.
52. Pavri, F. N. A Study of the Factors Contributing Microcomputer Usage, Unpublished doctoral dissertation, The University of Western Ontario, London, Ontario, Canada, 1988.
53. Pedersen P., Methlie L., and Thorbjornsen H. “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. 2002.
54. Reichheld, F. F. and Schefter, P. “E-Loyalty: Your Secret Weapon on the Web.” Harvard Business Review, 2000, 78, pp. 105–113.
55. Rice, R. E. and Katz, J. E. “Comparing Internet and Mobile Phone Usage: Digital Divides of Usage, Adoption, and Dropouts.” Telecommunications Policy, 2003, 27(8/9), pp. 597–623.
56. Robertson, D. C. “Social Determinants of Information System Use.” Journal of Management Information System, 1989, 5(4), pp. 55-71.
57. Sadeh, N. M-Commerce. New York: Wiley. 2002,
58. Sweeney, J. C. and Soutar, G. N. “Consumer Perceived Value: the Development of a Multiple Item Scale.” Journal of Retailing, 2001, 77(2),
pp. 203–220.
59. Taylor, S. and Todd, P. A. “Understanding Information Technology Usage: A Test of Competing Models.” Information System Research, 1995a, 6(2),
pp. 144-176.
60. Taylor, S. and Todd, P. A. “Assessing IT Usage: the Role of Prior Experience.” MIS Quarterly, 1995b, Dec., pp. 561-570.
61. The Economist. A survey of the MDS: The Internet, untethered. 2001,
October 13.
62. Turel, O., Serenko, A. and Bontis, N. “User Acceptance of Wireless Short Messaging Services: Deconstructing Perceived Value.” Information & Management, 2007, 44(1), pp. 63–73.
63. Varshney, U. and Vetter, R. “A Framework for the Emerging Mobile Commerce Applications.” Proceedings of the 34th Annual Hawaii International Conference on System Sciences, IEEE Computer Society, Washington, DC. 2001.
64. Venkatesh, V. and Brown. “A Longitudinal Investigation of Personal Computers in Homes: Adoption Determinants and Emerging Challenges.” MIS Quarterly, 2001, 25(1), pp. 71–102.
65. Wolfson, S. and Case, G. “The Effects of Sound and Color on Responses to a Computer Game.” Interacting with Computers, 2000, 13 (2), pp. 183–192.
66. White W. “What’s that Funny Noise—Video-Games in the Library.” Library Journal, 1981, 106 (8), pp. 859–860.