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http://hdl.handle.net/11455/22610| DC Field | Value | Language |
|---|---|---|
| dc.contributor | 林金賢 | zh_TW |
| dc.contributor | 李麗華 | zh_TW |
| dc.contributor.advisor | 張樹之 | zh_TW |
| dc.contributor.advisor | Shuchih Chang | en_US |
| dc.contributor.author | 劉彥宏 | zh_TW |
| dc.contributor.author | Liu, Yen-Hong | en_US |
| dc.contributor.other | 中興大學 | zh_TW |
| dc.date | 2007 | zh_TW |
| dc.date.accessioned | 2014-06-06T07:18:21Z | - |
| dc.date.available | 2014-06-06T07:18:21Z | - |
| dc.identifier | U0005-2806200615500100 | zh_TW |
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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. 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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. http://www.find.org.tw/ 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. | en_US |
| dc.identifier.uri | http://hdl.handle.net/11455/22610 | - |
| dc.description.abstract | 近來當大多數使用者透過網頁瀏覽器接收網路服務時，普及式運算成為提供一個任何地點、任何設備都可使用網路應用的新管道。普及式運算將使傳統的鍵盤、滑鼠以及螢幕無法再滿足消費者的需求，消費者需要的是能夠滿足普及式運算特性的新介面。本研究中，我們利用手機作為普及式運算的設備並設計一個整合網路和語音兩種管道的新系統雛形“網路暨語音系統”，接著運用科技接受理論探討普及式運算及新介面對於消費者接受度的影響。此研究樣本採樣於台灣，研究發現可以作為未來網路暨語音系統商業應用的參考。 | zh_TW |
| dc.description.abstract | 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. | en_US |
| dc.description.tableofcontents | 摘要 i ABSTRACT ii TABLE OF CONTENTS iii LIST OF FIGURES v LIST OF TABLES vi CHAPTER 1 INTRODUCTION 1 1.1 Background 1 1.2 Motivation 2 1.3 Objectives 4 1.4 Organization of Thesis 5 1.5 Research Procedure 6 CHAPTER 2 LITERATURE REVIEW 7 2.1 Voice Application 7 2.1.1 Interactive voice response 7 2.1.2 Speech Recognition 8 2.1.3 Computer telephony integration 9 2.2 Pervasive Computing 9 2.3 Competing Theories 10 2.3.1 Technology Acceptance Model 11 2.3.2 Theory of Planned Behavior 13 2.3.3 Integrated model 15 CHAPTER 3 THE PROPOSED SYSTEM 17 3.1 System Architectures 17 3.2 Applications 18 CHAPTER 4 RESEARCH DESIGN 20 4.1 Research Model and Hypotheses 20 4.2 Measures and Pretests 23 4.3 Survey Respondents 24 4.4 Statistical Analysis 24 CHAPTER 5 DATA ANALYSIS 25 5.1 Data Collection 25 5.2 Characteristics of Respondents 25 5.3 Measurement Assessment 27 5.4 Measurement Model 30 5.5 Model Comparison 33 CHAPTER 6 CONCLUSION 37 6.1 Discussion 37 6.2 Implications 38 6.3 Future Work 39 6.4 Limitation 40 REFERENCE 41 APPENDIX: Formal Questionnaire 47 LIST OF FIGURES Figure 1: The usage of mobile Internet services 2 Figure 2: Trend analysis on the penetration rates of major telecom services 3 Figure 3: Research procedure 6 Figure 4: Implementation of speech recognition (SR) 8 Figure 5: Technology acceptance model 12 Figure 6: Theory of planned behavior 14 Figure 7: The integrated model 16 Figure 8: The system architecture of the proposed system 17 Figure 9: Research models 20 Figure 10: Measurement model 30 Figure 11: Results of TAM 34 Figure 12: Results of TPB 35 Figure 13: Results of integrated model 35 LIST OF TABLES Table 1 Summary of studies using model comparison approaches 11 Table 2 Previous TAM studies 13 Table 3 Previous TPB studies 15 Table 4 Research constructs and measurements 23 Table 5 Collected samples 25 Table 6 Descriptive profile of respondents 26 Table 7 User experiences of mobile phone and Internet 27 Table 8 Summary of measurement scales 28 Table 9 Goodness-of-fit of the measurement model 31 Table 10 Assessing the measurement model 32 Table 11 Inter-construct correlations as discriminant validity 33 Table 12 Overall fit and explanatory power of the models 34 Table 13 Strengths of individual factors 36 | zh_TW |
| dc.language.iso | en_US | zh_TW |
| dc.publisher | 電子商務研究所 | zh_TW |
| dc.relation.uri | http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2806200615500100 | en_US |
| dc.subject | Pervasive computing | en_US |
| dc.subject | 普及式運算 | zh_TW |
| dc.subject | Consumer attitudes | en_US |
| dc.subject | Technology acceptance theory | en_US |
| dc.subject | Voice recognition | en_US |
| dc.subject | 消費者態度 | zh_TW |
| dc.subject | 科技接受理論 | zh_TW |
| dc.subject | 語音辨識 | zh_TW |
| dc.title | 使用者對於語音上網接受度之研究 | zh_TW |
| dc.title | Investigating users acceptance of voice channel to web access | en_US |
| dc.type | Thesis and Dissertation | zh_TW |
| item.openairetype | Thesis and Dissertation | - |
| item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
| item.languageiso639-1 | en_US | - |
| item.grantfulltext | none | - |
| item.fulltext | no fulltext | - |
| item.cerifentitytype | Publications | - |
| Appears in Collections: | 科技管理研究所 | |
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