臺灣博碩士論文加值系統

研究調查顯示，未來使用網路銀行人口有越來越多的趨勢。本研究以創新擴散理論為基礎，並納入使用經驗與安全性等因素，探討消費者使用網路銀行的行為。透過便利抽樣法發放網路問卷，本研究共蒐集有效問卷1030份。本研究以結構方程模式為主要研究方法，採用LISREL8.80進行驗證性因素分析和結構模式分析。研究結果顯示：「相對優勢」、「相容性」、「可試用性」、「可觀察性」、「安全性」及「使用經驗」均會顯著影響「態度」；「態度」和「使用經驗」會顯著影響「行為意圖」；「使用經驗」和「行為意圖」會顯著影響「實際使用行為」。因此，銀行管理者可透過強化消費者使用網路銀行的相對優勢、相容性、可試用性、可觀察性、安全性及使用經驗等，進而影響消費者實際使用網路銀行之行為，並可作為推廣網路銀行及制定行銷策略時的依據。

With the rapid growth internet users, the demand of web-banking is eager. Based on innovation of diffusion theory, this research wants to discuss the factors that influence consumer web-bank using behavior. Data collected from online survey and got 1030 usable samples. With the analysis of SEM, the analytic results showed that “Relative Advantage,” “Compatibility,” “Trialibility,” “Observability,” “Security,” and “Experience,” have positive significant effect on “Attitude;” in the meanwhile, both “Attitude,” and “Experience” have positive significant on “Behavioral Intention;” furthermore, both “Experience” and “Behavioral Intention” have positive significant effect on “Usage.” Based on the analytic results, suggestions are the managers of banks should enhance the attributes of web-bank by “Relative Advantage,” “Compatibility,” “Trialibility,” “Observability,” “Security” and “Experience,” in order to achieve both elevation of using behavior of web-bank and financial performance.

目 錄
謝 辭 i
摘 要 ii
Abstract iii
目 錄 iv
表 目 錄 vi
圖 目 錄 vii

第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究流程 2
第二章 文獻探討 5
2.1 網路銀行 5
2.1.1 網路銀行的起源 5
2.1.2 網路銀行的定義 6
2.1.3 網路銀行的特性 7
2.1.4 網路銀行的類型 7
2.2 科技接受模型 8
2.3 創新擴散理論 9
2.3.1 創新的定義 10
2.3.2 創新決策過程 11
2.3.3 創新擴散 12
2.4 其它外部影響因素 15
2.4.1 安全性 15
2.4.2 使用經驗 16
第三章 研究設計 18
3.1 研究架構 18
3.2 研究假說 19
3.2.1 創新特質與網路銀行使用態度之關係 19
3.2.2 消費者對網路銀行使用態度、行為意圖和實際使用行為之關係20
3.2.3 消費者對網路銀行的安全性認知與消費者使用網路銀行的使用態度、行為意圖 和實際使用行為之關係 21
3.2.4 消費者的網路銀行使用經驗與消費者對網路銀行的態度、行為 意圖和實際使用行為之關係 22
3.3 研究變數 22
3.3.1 自變數操作性定義與衡量 23
3.3.2 依變數操作性定義與衡量 28
3.4 問卷設計 31
3.4.1 預試問卷部份 31
3.4.2 因素分析 32
3.4.3 正式問卷 36
第四章 資料分析 37
4.1 樣本基本資料分析 37
4.2 資料分析方法 39
4.3 信度、效度分析 40
4.4 整體模式之適配度分析 43
4.5 結構模式分析 44
第五章 結論與建議 48
5.1 研究結果與討論 48
5.1.1 相對優勢、相容性、可試用性、可觀察性、安全性和使用經 驗對態度有正向關係 48
5.1.2 態度和使用經驗對消費者之行為意圖有正向關係 49
5.1.3 行為意圖和使用經驗對於消費者實際使用行為有正向關係 49
5.2 管理意涵 49
5.2.1 提升網路銀行的相對優勢，有助於業者推廣網路銀行之發展 50
5.2.2 強化網路銀行的相容性，有助於消費者實際使用網路銀行 50
5.2.3 開放虛擬測試使用區，強化網路銀行的可試用性 51
5.2.4 加速資訊流通，提高網路銀行的可觀察性 51
5.2.5 提高安全認證機制，強化網路銀行安全性 52
5.2.6 有使用網路銀行經驗之消費者，將會是業者未來潛在的客戶群52
5.3 研究限制 53
5.4 未來研究建議 53
參考文獻 55
附錄一 問卷調查表 65

表 目 錄
表3.1 本研究之各變數 23
表3.2 相對優勢之衡量問項 24
表3.3 相容性之衡量問項 25
表3.4 複雜性之衡量問項 25
表3.5 可試用性之衡量問項 26
表3.6 複雜性之衡量問項 27
表3.7 安全性之衡量問項 28
表3.8 使用經驗之衡量問項 28
表3.9之衡量問項 29
表3.10行為意圖之衡量問項 30
表3.11實際使用行為之衡量問項 30
表3.12 原始問卷CRONBACH'S Α值 32
表3.13 創新特質部份之探索性因素分析結果 34
表3.13 創新特質部份之探索性因素分析結果 (續) 35
表3.14 其它變數之探索性因素分析結果 35
表3.14 其它變數之探索性因素分析結果 (續) 36
表4.1 樣本基本資料 38
表4.1 樣本基本資料 (續) 39
表4.2 測量尺度整理表 41
表4.2 測量尺度整理表 (續) 42
表4.3 配適度指標(GOODNESS OF FIT)列表 44
表4.4 潛在變數共變異矩陣 44
表4.5 假設檢定彙整 46

圖 目 錄

圖 1.1研究流程圖 4
圖 2.1科技接受模型 9
圖2.2創新決策過程 11
圖 2.3 ROGERS 對採用者的分類 14
圖3.1研究架構 19
圖 4.1模式路徑圖 47

一、中文部份

1. 吳明隆（2003），SPSS 統計應用學習實務：問卷分析與應用統計，知城數位科技。
2. 呂錦山（2008），「貨主使用定期海運業網際網路服務意願之研究—結構方程模式之應用」，成大研發快訊，第三卷，第八期。
3. 李素瑜（2006），「影響行動付款使用意願之探討」，輔仁大學未出版碩士論文。
4. 周景弘（1997），「網路銀行安全性對使用者知覺風險與使用意願之影響」，國立台灣大學未出版碩士論文。
5. 林如瑩（2000），「風險降低策略於網路購物之研究-以實驗室實驗法探討」，國立中央大學未出版碩士論文。
6. 林君育（2005），「影響採用個人網路ATM因素之研究」，國立中央大學未出版碩士論文。
7. 林玲玉（2001），「國內網路銀行現況發展及交易安全之研究」，國立交通大學未出版之碩士論文。
8. 林國平、黃雅歆、連佩婷、藍霈雯（2003），「從使用者觀點探討經營網路銀行業務之關鍵成功因素」，產業論壇，第4期，頁293-312。
9. 林繼正（1997），「網路銀行的來臨」，資訊與電腦，第204期，頁67-71。
10. 財政部（1999），個人電腦銀行業務及網路銀行業務服務契約範本，財政部
11. 張紹勳（2002），「電子商店之關係品質模式----融合交易成本理論及科技接受模式的觀點」，國立政治大學未出版博士論文。
12. 張裕淵（2000），「以生活型態觀點探討台灣地區銀行網路金融服務市場區隔之研究」，國立中央大學未出版之碩士論文。
13. 曹珩堉（2004），「電視購物消費者使用網路購物意圖－以搜尋品及經驗品為例」，國立台灣科技大學未出版碩士論文。
14. 陳一如、蘇法、張如億（2002），「國內網路銀行經營對策之探討」，台灣金融財務季刊，第三卷，第一期，頁1-19。
15. 陳正平 譯（1999），跨越鴻溝，臉譜出版
16. 陳儀珍（2005）， 「創新擴散之研究-以個人綜合所得稅網路申報為例」，國立台北大學未出版碩士論文。
17. 黃冠叡（2006），「消費者特性與虛擬通路購物意願關係之研究」，國立成功大學未出版碩士論文。
18. 劉昆鎧（2005），「網路銀行之信任建立模式：以臺灣地區使用者為例」，國立暨南國際大學未出版碩士論文。
19. 鄭伊雯（1997），「網路銀行環境下銀行業務發展之探討」，輔仁大學未出版之碩士論文。
20. 鄧維兆、廖明宗、馬郁淇（2007），「網路銀行關鍵服務品質屬性確認－三因子理論與IPA之應用」，品質學報，第14卷，第4期，頁351-365。
21. 鍾志強（2008），「大學校院運動會服務品質與參與者行為意圖之關係研究」，運動休閒管理學報，第五卷，第一期，頁73-83。
22. 104市調中心（2008） ，「07年網路銀行使用率逾5成最常使用查詢功能」http://www.104ad.com.tw/article_detail.jsp?id=217
23. 資策會FIND 研究組（2009），「2009年6月底止台灣上網人口」 http://www.find.org.tw/find/home.aspx?page=many&id=243

二、英文部份

1. Agarwal. R. and J. Prasad. (1997), “The Role of Innovation Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies”, Decision Sciences, Vol. 28, No. 3, pp. 557-582.
2. Assael, H. (1998). Consumer Behavior and Marketing Action, (6th edition), Cincinnati, Oh: South-Western College Publishing.
3. Bagozzi, R. P. and Yi, Y. (1988), “On the Evaluation for Structural Equation Models”, Journal of the Academy of Marketing Science, Vol. 16, pp. 74-94.
4. Bajaj, A. and S. R. Nidumolu, (1998), “A feedback model to understand information system usage”, Information and Management, Vol. 33, No. 4, pp. 213-224.
5. Bander, A. A. (2009), “The Relative Importance of Trust Intentions and TrustBeliefs In Internet Banking Adoption”, International Review of Business Research Papers, Vol. 5, No. 5, pp. 257-272
6. Belanger, F., Hiller, J. S. and Smith, W. J. (2002), “Trustworthiness in electronic commerce: The role of privacy, security, and sit attributes”, Strategic Information Systems, Vol. 11 pp. 245–270.
7. Blackwell. R. D., Paul W. M. and James F. E. (2001), Consumer Behavior, (9th edition), Publisher: Ohio, Mike Roche.
8. Browne, M.W. and Cudeck, R. (1993). “Alternative ways of assessing model fit”, In testing structural equation models, Bollen KA, Long JS (Eds.). Sage: Newbury, CA, pp. 136-162.
9. Davis, F. D., Bagozzi, R. P. and Warshaw, P. R. (1989), “User acceptance of computer technology: a comparison of two theoretical models”, Management Science, Vol. 35, No. 8, pp. 982-1003.
10. Dickerson, M. D. and Gentry, J. W. (1983), “Characteristics of Adopters and Non-Adopters of Home Computers”, Journal of Consumer Research, Vol. 10, pp. 225-35.
11. Eagly, A. H. and Chaiken, S. (1993), The psychology of attitudes, Orlando, Florida: Harcourt Brace Jovanovich College Publishers.
12. Fishbein, M. and Ajzen, I. (1975), Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, Reading, MA: Addison-Wesley.
13. Furst, K., Lang, W. and Nolle, D. E. (2002), “Internet banking: developments and prospects, Working Paper”, Center for Information Policy Research, Harvard University Cambridge.
14. Garcia, R, and Calantone, R. (2002). “A critical look at technological innovation typology and innovativeness terminology: A literature review”, Journal of Product Innovation Management, Vol.19, NO.2, pp. 110-132
15. Gardner. C. and Amoroso. D. L. (2004), “Development of an Instrument to Measure the Acceptance of Internet Technology by Consumers “Proceedings of the 37th Annual Hawaii International Conference on System Sciences, IEEE Computer Society, Washington, DC, USA.
16. Hair, J. F. Jr., Anderson, R. E., Tatham, R. L., and Black, W. C. (1998 ), Multivariate Data Analysis , 5th , Englewood Cliffs, NJ : Prentice-Hall.
17. Hoffman, E., Novak, T. P. and Peralta, M. (1999), “Building consumer trust online”, Communication of the ACM, Vol. 42, No. 4, pp. 80-86.
18. Hoyer MacInnis. (1997), Consumer Behavior, Houghton Mifflin
19. Hu, L., and Bentler, P. M. (1999), “Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives”, Structural Equation Modeling, 6 (1), pp. 1-55.
20. Hu, P. J., P. Y. K. Chau., O. R. Liu Sheng & Tam, K.Y. (1999), “Examing the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology”, Journal of Management Information Systems, Vol. 16, No. 2, pp. 91-112.
21. Igbaria, M., Guimaraes, T. and Davis, G. B. (1995), ”Testing the determinants of microcomputer usage via a structural equation model”, Journal of Management Information Systems, Vol. 11 , No. 4, pp. 87-114.
22. Igbaria, M., T. Guimaraes and G. B. Davis. (1995), “Testing the Determinants of Microcomputer Usages via a Structural Equation Model”, Journal of Management Information Systems, Vol. 11, No. 4, pp. 87-114.
23. Jane, M. K., Jeanne, M. H. and Marianne, A. H. (2004), “The adoption of electronic banking technologies by US consumers”, The International Journal of Bank Marketing, Bradford: Vol. 22, pp. 238-259.
24. Kaiser, H. F. (1974), “An Index of Factorial Simplicity,” Psychometrika, Vol. 39, pp. 31-36.
25. Kalakota R. and Whinston, A. B. (1996), Frontier of Electronic Commerce , Addison-Wesley Publishing Company, Inc.
26. Kalakota, R. and Whinston, A. B. (1996), Frontiers of Electronic Commerce, Addison-Wesley, Reading, MA.
27. Kim, D. J., Steinfield, C. and Lai, Y. (2008), "Revisiting the role of web assurance seals inbusiness-to-consumer electronic commerce", Decision Support Systems, Vol. 44, No. 4, pp.1000-1015.
28. Kwak, H., Fox, R. J. and Zinkhan, G. M. (2002), “What Products Can Be Successfully Promoted and Sold via the Internet? ”, Journal of Advertising Research, Vol. 42. No. 1, pp. 23-39.
29. Li, Yan. (2004), Faculty perceptions about attributes and barriers impacting diffusion of Web-based distance education (WBDE) at the China Agricultural University, Ph.D. Dissertation, TEXAS A&M UNIVERSITY.
30. Lian, J. and Lin, T. (2008), "Effects of consumer characteristics on their acceptance of online shopping: Comparisons among different product types", Computers in Human Behavior, Vol. 24, No. 1, pp. 48-65.
31. Liao, Z. and M.T. Cheung. (2002), “Internet-based e-banking and consumer attitudes: an empirical study”, Information and Management, Vol. 39, No. 4, pp. 283-295.
32. Lin, J. C. C. and Lu, H. (2000), “Towards an understanding of the behavioral intention to use a web site”, International Journal of Information Management, Vol. 20, pp. 197-208.
33. Lin, J. C.C. and Lu, H. (2000), “Towards an understanding of the behavioral intention to use a web site”, International Journal of Information Management, Vol. 20, pp. 197-208.
34. MacCallum, R. C., M. Roznowski, C. M. Mar and J. V. Reith. (1994), “Alternative Strategies for Cross-Validation of Covariance Structure Models”, Multivariate Behavioral Research, Vol. 29, No. 1, pp. 1-32.
35. Mathieson, K., E. Peacock. and Chin, W. W. (2001), “Extending The TAM: The Influence of Perceived User Resources”, The DATA BASE for Advances in Information Systems, Vol. 32, No. 3, pp. 86-112.
36. Methieson. K., Peacock. E. and W. Chin. (2001), “Extending the Technology Acceptance Model: The Influence of Perceived User Resources”, DATA BASE for Advances in Information Systems, Vol. 32, No. 3, pp. 86-112.
37. Miville. N. D. (2005), “Factors influencing the diffusion of innovation and managerial adoption of new technology”, D.B.A, Nova Southeastern University, p. 131.
38. Miyazaki, A. D. and Fernandez, A. (2001), “Consumer perceptions of privacy and security risks for online shopping”, Journal of Consumer Affairs, Vol. 35, No. 1, pp. 27–44.
39. Moore, G. C., and Benbasat, I. (1991),”Development of an instrument to measure the perception of adopting an information technology innovation”, Information Systems Research, Vol. 2, No. 3, pp. 192-222.
40. Nor, K. M and Pearson, J. M. (2007) “The Influence of Trust on Internet Banking Acceptance”, Journal of Internet Banking and Commerce, vol. 12, No.2.
41. Nunnally, J. (1978), Psychometric Theory, New York: McGraw-Hill.
42. O’Callaghan. R., Kaufmann. P. J. and Konsynski. B.R. (1992), “Adoption Correlates and Share Effects of Electronic Data Interchange Systems in Marketing Channels”, Journal of Marketing, Vol. 56, No.2, pp. 45-56.
43. O’Cass, A. and Fenech, T. (2003), “Web retailing adoption: exploring the nature of internet users’ web retailing behaviour”, Journal of Retailing and Consumer Services, Vol. 10 No. 1, pp. 81-94.
44. Philip, Kotler. (2002), Marketing Management, Hall Inc.
45. Raymond, L. and Blili, S. (1997), “Adopting EDI in a Network Enterprise: The Case of Subcontracting SMEs”, European Journal of Purchasing and Supply Management, Vol. 3, No. 3, pp. 165-175.
46. Rick. B., Reagan. J., Pickleton. B and Jackson. K. (1999), “Factors Affecting Internet Use in a Saturaed-Access Population”, Telematics and Informatics , Vol. 16 , pp. 45-58.
47. Robert, A. Westbrook and Richard, L. Oliver. (1991), “The Dimensionality of Consumption Emotion Pattern and Consumer Satisfaction”, Journal of Consumer Research Vol. 18, pp. 84-91.
48. Rogers, E. M. (1995), Diffusion of Innovation, (5th ed.), New York: The Free Press.
49. Rogers, E. M. and Allbritton, M. M. (1995), “Interactive Communication Technologies in Business Organizations”, Journal of Business Communication, Vol. 32, pp. 175-195.
50. Rogers, E. M., and David, G. C. (1962), “Methods of measuring opinion leadership”, Public Opinion Quarterly, Vol. 26, pp. 435-441.
51. Rogers, E.M. (1983), The Diffusion of Innovations, (3th edition), Free Press, New York.
52. Rouse, P. (2004), Technology acceptance and sensemaking: Exploring the antecedents and moderating trigger conditions related to perceived usefulness and perceived ease of use, Ph.D. Dissertation, St. Ambrose University
53. Salisbury. W. D., Pearson. R. A., Pearson. A. W and Miller. D. W. (2001) “Perceived security and World Wide Web purchase intention”, Industrial Management + Data Systems, Vol. 101, No. 3, pp. 165-176.
54. Shin, D. H. (2009), “Towards an understanding of the consumer acceptance of mobile wallet”, Computers in Human Behavior, Vol. 25, No.6, pp. 1343-1354.
55. Sin, L. and A. Tse. (2002), “Profiling Internet Shoppers in Hong Kong: Demographic, Psychographic, Attitudinal and Experiential Factors”, Journal of International Consumer Marketing, Vol. 15, No.1, pp. 7-28.
56. Sneddon, M. (1997), “Cyberbanking: Remote banking using the Internet”, Australian Business Law Review, Vol. 25, No. 1, pp. 64-67.
57. Stoel, L. and Lee, K. H. (2003), “Modeling the effect of experience on student acceptance of web-based courseware”, Electronic Networking Applications and Policy, Vol. 13, No. 5, pp. 364-74.
58. Straub, D. W. (1989), “Validating Instruments in MIS Research”, MIS Quarterly, Vol. 13, No. 2, pp. 147-169.
59. Straub, D. W. (1989), “Validating Instruments in MIS Research”, MIS Quarterly, Vol. 13, No. 2, pp. 147-169.
60. Suh, B. and Han, I. (2003), “The impact of customer trust and perception of security control on the acceptance of electronic commerce”, International Journal of Electronic Commerce, Vol.7, No. 3, pp. 135–161.
61. Szajna, B. (1996), “Empirical Evaluation of the Revised Technology Acceptance Model”, Management Science, Vol. 42, No. 1, pp. 85-92.
62. Tan, M. and Teo, T. S. H. (2000), “Factors influencing the adoption of Internet Banking,” Journal of Association for Information Systems, Vol. 1, No. 5, pp. 23-38.
63. Taylor, S. and Todd, P. A. (1995), “Understanding information technology usage: A test of competing models”, Information Systems Research, Vol. 6, No. 2, pp. 144-176.
64. Taylor, S. and Todd, P. A. (1995b), “Assessing IT Usage: The Role of Prior Experience”, MIS Quarterly, Vol.19 No. 4, pp. 561-570.
65. To, M. L and Ngai, E. W. T. (2007) “The Role of Managerial Attitudes in the Adoption of Technological Innovations: An Application to B2C E-Commerce”, International Journal of Enterprise Information Systems, Vol.3, NO.2, pp. 23-32.
66. Tornatzky, L. and Klein, K. J. (1982), “Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings,” IEEE Transactions on Engineering Management, Vol. 29, No. 1, pp. 28-45.
67. Venkatesh, V. and Davis, F. D. (1996), “A Model of the Antecedents of Perceived Ease of Use: Development and Test”, Decision Sciences, Vol. 27, No. 3, pp. 451-481.