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標題: 使用者對於語音上網接受度之研究
Investigating users acceptance of voice channel to web access
作者: 劉彥宏
Liu, Yen-Hong
關鍵字: Pervasive computing;普及式運算;Consumer attitudes;Technology acceptance theory;Voice recognition;消費者態度;科技接受理論;語音辨識
出版社: 電子商務研究所
引用: REFERENCE 1. G. Abowd, E. Mynatt, T. Rodden, The Human Eperience, IEEE Pervasive Computing 1 (1), 2002, pp. 48-57. 2. I. Ajzen, The theory of planned behavior, Organizational Behavior and Human Decision Processes 50, 1991, pp.179-211. 3. J.C Anderson, D.W. Gerbing, Structural equation modeling in practice: a review and recommended two step approach, Psychological bulletin 103 (3), 1988, pp. 411-423. 4. N. Anerousis, E. Panagos, Making voice knowledge pervasive, IEEE Pervasive Computing 1 (2), 2002, pp. 42-48. 5. S.J. Barnes, The mobile commerce value chain: analysis and future developments, International Journal of Information Management 22, 2002, pp. 91-108. 6. P. Bentler, D. Bornett, Significance tests and goodness of fit in the analysis of covariance structures, Psychological Bulletin 88, 1980, pp. 588-606. 7. A. Bhattacherjee, An empirical analysis of the antecedents of electronic commerce service continuance, Dicision Support Systems 32 (2), 2001, pp. 201-214. 8. G..C. II Bruner, A. Kumar, Explaining consumer acceptance of handheld Internet devices, Journal of Business Research 58, 2005, pp. 553-558. 9. P.Y.K. Chau, P.J.H. Hu, Information technology acceptance by individual professionals: a model comparison approach, Decision Science 32 (4), 2001, pp. 699-719. 10. P.Y.K. Chau, P.J.H. Hu, Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories, Information & Management 39, 2002, pp. 297-311. 11. H. Chen, M. Gillenson, D. Sherrell, Enticing on-line consumer: an extended technology acceptance perspective, Information & Management 39, 2002, pp. 705-719. 12. L. Cheng, and I. Marsic, Piecewise network awareness service for wireless/mobile pervasive computing, Mobile Networks and Application 7 (4), 2002, pp. 269-278. 13. T.L. Childers, C.L. Carr, J. Peck, S.Carson, Hedonic and utilitarian motivations for online retail shopping behavior, Journal of Retailing 77, 2001, pp. 511-535. 14. J. Choi, L.V. Geistfeld, A cross-cultural investigation of consumer e-shopping adoption, Journal of Economic Psychology 25, 2004, pp. 821-838. 15. I. Church, A.J. Newman, Using simulations in the optimisation of fast food service delivery, British Food Journal 102(5/6), 2000, pp. 398-403. 16. P.A. Dabholkar, R.P. Bagozzi, An attitudinal model of technology-based Self-Service: moderating effects of consumer traits and situational factors, Journal of the Academy of Marketing Science 30 (3), 2002, pp. 184-201. 17. F.D. Davis, Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly 13, 1989, 319-339. 18. F.D. Davis, R.P. Bagozzi, P.R. Warshaw, User acceptance of computer technology: a comparison of two theoretical models, Management Science 35, 1989, pp. 982-1003. 19. F.D. Davis, R.P. Bagozzi, P.R. Warshaw, Extrinsic and intrinsic motivation to use computers in the workplace, Journal of Applied Social Psychology 22, 1992, pp. 1111-1132. 20. DGT, Directorate General of Telecommunicate. 21. R.R. Dholakia, N. Dholakia, Mobility and markets: emerging outlines of m-commerce, Journal of Business Research 57, 2004, pp. 1391-1396. 22. M. Fishbein, I. Ajzen, Belief, attitude, intention and behavior: an introduction to theory and research, Addison-Wesley, Reading, MA, 1975. 23. C. Fornell, D. Larcker, Evaluating structural equation models with unobservable variables and measurement errors, Journal of Marketing Research 18, 1981, pp. 39-50. 24. T. Hansen, J.M. Jensenb, H.S. Solgaard, Predicting online grocery buying intention: a comparison of the theory of reasoned action and the theory of planned behavior, International Journal of Information Management 24, 2004, pp. 539-550. 25. J.F. Hair, R.E. Andeson, R.L. Tatham, W.C. Black, Multivariate Data Analysis, 5th ed., Prentice-Hall, Inc., Upper Saddle River, NJ,1998. 26. S.G. Hild, C. Binding, D. Bourges-Waldegg, C. Steenkeste, Application hosting for pervasive computing, IBM Systems Journal 40 (1), 2001, pp. 193-219. 27. J. Hernick, Telephony 101: giving voice to your network, Network Computing 14 (20), 2003, pp. 75-77. 28. C.L Hsu, H.P. Lu, Why do people play on-line games? An extended TAM with social influences and flow experience, Information & Management 41, 2004, pp. 853-868. 29. P.J. Hu, P.Y.K. Chau, S.Liu, K.Y. Tam, Examining the technology acceptance model using physician acceptance of telemedicine technology, Journal of Management Information Systems, 16 (2), 1999, pp. 97-124. 30. S.Y. Hung, C.Y. Ku, C.M. Chang, Critical factors of WAP service adoption: an empirical study, Electronic Commerce Research and Applications 2, 2003, pp. 42-60. 31. S.Y. Hung, C.M. Chang, User acceptance of WAP services: test of competing theories, Computer Standards & Interfaces 27, 2005, pp. 359-370. 32. Institute for Information Industry, ACI-FIND, Focus on Internet News & Data. 33. K. Ishii, Internet use via mobile phone in Japan, Telecommunications Policy, 28, 2004, pp. 43-58. 34. A. Gunasekaran, E. Ngai, Special issue on mobile commerce : strategies, technologies and applications, Decision Support Systems 35, 2003, pp. 187-188. 35. K. Joreskog, D. Sorbom, LISREL 8 User's Reference Guide, Scientific Software, Inc., Chicago, IL, 1993. 36. H. Karppinen, Forest owners' choice of reforestation method: an application of the theory of planned behavior, Forest Policy and Economics 7, 2005, pp. 393- 409. 37. R.B. Kline, Principles and Practice of Structural Equation Modeling, The Guilford Press, NJ, 2000. 38. S. Kumar, C. Zahn, Mobile communications: evolution and impact on business operations, Technovation 23, 2003, pp. 515-520. 39. J. Larson, VoiceXML and the W3C speech interface framework, IEEE Multimedia 10, 2003, pp. 91-93. 40. C. Lee, B. Carpenter, W. Chou, J. Carroll, W. Reichl, A. Saad, Q.Zhou, On natural language call routing, Speech Communication 31, 2000, pp. 309-320. 41. P. Legris, J. Ingham, P. Collerete, Why do people use information technology? A critical review of the technology acceptance model, Information & Management 40(3), 2003, pp. 191-204. 42. P. Luarn, H.H. Lin, Toward an understanding of the behavioral intention to use mobile banking, Computers in Human Behavior 21, 2005, pp. 873-891. 43. W. Luo, D. Strong, Perceived critical mass effect on groupware acceptance, European Journal of Information Systems 9 (2), 2000, pp. 91-103. 44. J. Lynch, Computer-telephony integration, Work Study 44 (7), 1995, pp. 8-9. 45. R.C. MacCallum, M.W. Browne, H.W. Sugawara, Power analysis and determination of sample size for covariance structure modeling, Psychological Methods 1, 1996, pp. 130-149. 46. W. Mark, Turning pervasive computing into mediated spaces, IBM Systems Journal 38 (4), 1999, pp. 677-692. 47. K. Mathieson, Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior, Information Systems Research 2 (3), 1991, pp. 192-222. 48. K. Mathieson, E. Peacock, W. Chin, Extending the technology acceptance model: the influence of perceived user resources, The Data base for Advances in Information Systems 32 (3), 2001, pp. 86-112. 49. J. Moon, Y. Kim, Extending the TAM for a world-wide-web context, Information & Management 38 (4), 2001, pp. 217-230. 50. J.C.Nunnally, I.H.Bernstein, Psychometric theory, 3rd ed., McGraw-Hill, NY, 1994. 51. C.S. Ong, J.Y. Lai, Y.S. Wang, Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies, Information & Management, 41, 2004, pp. 795-804. 52. L.R. Rabiner, Applications of speech recognition in the area of telecommunications, Automatic Speech Recognition and Understanding, 1997. Proceedings., 1997 IEEE Workshop on, pp.501-510. 53. C.M.Jr. Rebman, M.W. Aiken, C.G.. Cegielski, Speech recognition in the human-computer interface, Information & Management 40, 2003, pp. 509-519. 54. R.E. Rhodes, K.S. Courneya, Threshold assessment of attitude, subjective norm, and perceived behavioral control for predicting exercise intention and behavior, Psychology of Sport and Exercise 6, 2005, pp.349-361. 55. C.K. Riemenschneider, D.A. Harrison, P.P. Mykytyn Jr., Understanding IT adoption decisions in small business: integrating current theories, Information & Management 40, 2003, pp. 269-285. 56. R. Rodman, Computer speech technology, Artech House, Boston, 1999. 57. B.H. Sheppard, J. Hartwick, P.R. Warshaw, The theory of reasoned action: a meta-analysis of past research with recommendations for modifications and future research, The Journal of Consumer Research 15, 1988, pp. 325-343. 58. C. Sorin, D. Jouvet, C. Gagnoulet, D.Dubois, D. Sadek, and M. Toularhoat, Operational and experimental French telecommunication services using CNET speech recognition and text-to-speech synthesis, Speech communication 17 , 1995, pp. 273-286. 59. B.Suhm, J. Bers, D. McCarthy, B. Freeman, D. Getty, K. Godfrey, P. Peterson, A comparative study of speech in the call center: natural language call routing vs. touch-tone menus, Conference on Human Factors in Computing Systems, Proceedings of the SIGCHI conference on Human factors in computing systems: Changing our world, changing ourselves, 2002, pp. 283-290. 60. J. Takahashi, N. Sugamura, T. Hirokawa, S. Sagayama, S. Furui, Interactive voice technology development for telecommunications applications, Speech Communication 17, 1995, pp. 287-301. 61. S. Taylor, P.A. Todd, Understanding information technology usage: a test of competing models, Information System Research 6 (2), 1995a, pp. 144-76. 62. S. Taylor, P.A. Todd, Assessing IT usage: the role of prior experience, MIS Quarterly 19 (4), 1995b, pp. 561-570. 63. T.S.H. Teo, S.H. Pok, Adoption of WAP-enabled mobile phones among Internet users, Omega 31, 2003, pp. 483-498. 64. T. Teo, V. Lim, R. Lai, Intrinsic and extrinsic motivation in Internet usage, Omega 27 (1), 1999, pp. 25-37. 65. K.J. Turner, Analysing interactive voice services, Computer Networks 45, 2004, pp. 665-685. 66. V. Venkatesh, F.D. Davis, A theoretical extension of the technology acceptance model: four longitudinal field studies, Management Science 46 (2), 2000, pp. 186-204. 67. V. Venkatesh, C. Speier, M. Morris, User acceptance enablers in individual decision making about technology: toward an integrated model, Decision Science 33 (2), 2002, pp. 297-315. 68. M. Weiser, The computer for the 21st century, Scientific American 265,1991, pp. 94-101. 69. M. Weiser, Some computer science issues in ubiquitous computing, Communication of the ACM 36 (7), 1993, pp. 74-84. 70. Wirelessweek, Buying numbers, 2004, pp. 30. 71. M. Workman, Expert decision support system use, disuse, and misuse: a study using the theory of planned behavior, Computers in Human Behavior 21, 2005, pp. 211-231. 72. J.H. Wu, S.C. Wang, What drives mobile commerce? An empirical evaluation of the revised technology acceptance model, Information & Management 42, 2005, pp. 719-729. 73. J. Wetterau, CTI in the Corporate Enterprise, International Journal of Network Management 8, 1998, pp. 235-243. 74. K.C.C Yang, Exploring factors affecting the adoption of mobile commerce in Singapore, Telematics and Informatics 22, 2005, pp. 257-277.

While most users currently receive web services from web browser interfaces, pervasive computing is emerging and offering new ways of accessing Internet applications from any device at any location. As a result, there is a growing demand for technology that will allow users to be connected to the Internet from anywhere through devices that are not suitable for the use of traditional keyboard, mouse, and monitor. In this research, mobile phone was chosen as the pervasive device for accessing an Internet application prototype, a voice-enabled web system, through voice user interface technology. The impacts of the forthcoming pervasive computing technology on consumer attitudes, and the acceptance rate of consumers on new pervasive interface, were studied using technology acceptance theories. The study was undertaken in Taiwan, and the research findings may be referenced for the purpose of the design and development of successful business applications to catch the revolutionary opportunity and benefit of voice enabled web systems.
其他識別: U0005-2806200615500100
Appears in Collections:科技管理研究所

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