隨著科技的進步，以電子方式取得政府資訊也成為主流。這不僅造成人們溝通方式的重大改變，同時增進政府機構、企業、以及個人的資訊交換能力。在眾多的電子取得資訊方式中，全球資訊網是最有力的資訊傳播方式。
政府機關能夠利用網際網路來迅速、經濟、有效散佈電子文件。此外，新的溝通科技也使建立緊密的民眾與政府關係成為可能，網際網路在政治上扮演的角色似乎也不僅止於資訊傳播。
研究目的在於比較科技接受模式與原始的計劃行為理論，以及由本研究建構的解構計劃行為理論等三種模式對政府網站使用情形的解釋能力。本研究以207名學生為樣本，對七個市政府網站進行研究，以線性結構方程式分析的結果如下：
在解構計劃行為理論中，使用意向的判定係數約為0.4，亦即在線性的假設下，態度、主觀規範、以及知覺行為控制對政府網站行用意向的解釋能力大約為百分之四十。解釋能力與科技接受模式相當，而略高於原始的計劃行為理論。
本研究提供幾點管理上的建議：一、政府網站的建構者應該多注重使用者的資訊需求，而不是僅重視技術層面的問題。二、容易使用與可讀性高的政府網站是網站設計的要點。三、政府網站應豐富全球資訊網的內容以提高使用者的使用意向。

As the continuous waves of new technology, there has been an explosion of electronic access to government information. It has undeniably not only led to a dramatic change in the way people communicate, but also increased the ability of institutions, businesses and individuals to channel information. Among various formats of electronic access, the World Wide Web (WWW) is the most powerful way to disseminate information.
Governments are well placed to take advantage of the Internet's ability to disseminate electronic documents quickly, cheaply and efficiently. Moreover, as new communication technologies make it possible to establish a closer relationship between citizens and their governments, it is increasingly likely that the Internet's role in the political process will evolve beyond the mere dissemination of information.
The intention of this study is to compare the Technology Acceptance Model to a traditional version and a decomposed version of the Theory of Planned Behavior in terms of their contribution to the understanding of the government web sites usage. Data from a field study of 207 students are used to test these models using structural equation modeling. The results are concluded as follows:
The coefficient of determination R2BI of the Decomposed Theory of Planned Behavior is about 0.4, in other words, approximately 40% of the variation in behavioral intention is explained by linear regression of behavioral intention on attitude, subjective norm, and perceived behavioral control. In the view of behavioral intention, the explanatory power of the Decomposed Theory of Planned Behavior is equivalent to the Technology Acceptance Model, and is moderately better than the Theory of Planned Behavior.
There are several managerial implication. First, the designers of the government web sites should pay more attention to understand the information need of users, not just put effort on technical level. Second, Ease of use with readable format is the best discipline of the government web sites design. Third,. The designers may have to enrich the content of the government web sites so as to enhance intention of users.

Chapter 1 Introduction 1
1.1 Background 1
1.2 Research Purpose 2
1.3 Research Process 4
Chapter 2 Literature Review 7
2.1 Government Web Sites Evaluation Criteria 7
2.2 The Success of Information System 9
2.3 Model 1—The Technology Acceptance Model 10
2.4 Model 2--The Theory of Planned Behavior 13
2.5 Model 3—The Decomposed Theory of Planned Behavior 16
2.5.1. Decomposing Attitudinal Belief Structures 17
2.5.2. Decomposing Normative Belief Structure. 19
2.5.3. Decomposing Control Belief Structure 19
Chapter 3 The Study 21
3.1 The Local Government WWW 21
3.2 Research Hypotheses 21
3.3 Instrument Development 24
3.3.1 Instrument of Dependent Variables 25
3.3.2 Instruments of Independent Variables for Attitude 27
3.3.3 Instruments of Independent Variables for Subjective Norm 31
3.3.4 Instruments of Independent Variables for Perceived Behavioral Control 32
3.3.5 The Structure of Instrument 33
3.3.6 The Measurement scale of the Instrument 35
3.4 Participants 36
3.5 Setting and Data Collection Procedures 37
Chapter 4 Findings 39
4.1 Confirmatory Factor Analysis of Belief Constructs 39
4.1.1 Construct of Attitudinal Beliefs 39
4.1.2 Constructs of Normative Beliefs 45
4.1.3 Construct of Control Beliefs 46
4.2 The Decomposed Theory of Planned Behavior 49
4.2.1 Construct of Behavioral Intention 51
4.2.2 Construct of Attitudinal Beliefs 52
4.2.3 Construct of Normative Beliefs 54
4.2.4 Construct of Control Beliefs 54
4.3 Comparison of TAM, TPB, and DTPB 56
4.3.1 Technology Acceptance Model (TAM) 56
4.3.2 Theory of Planned Behavior (TPB) 57
4.3.3 Comparison of Three Models 58
4.4 Descriptive Analysis of Each Construct 60
4.4.1 Construct of Attitudinal beliefs 60
4.4.2 Construct of normative beliefs 64
4.4.3 Construct of control belief 66
4.5 Understanding Behavioral Intention 68
4.5.1 Difference in Factors Affect Usage Intention 68
4.5.2 Difference in Construct of Beliefs 69
4.6 Understanding External Variable 71
Chapter 5 Conclusion and Suggestion 73
5.1 Conclusion 73
5.2 Discussion 74
5.3 Managerial Implication 75
5.4 Limitations and Further Research 76

1. Ajzen, I. & B. L. Driver (1992). Application of the theory of planned behavior to leisure choice. Journal of Leisure Research, 24(3). 207-224
2. Ajzen, I. & T. J. Madden (1986). Prediction of goal-directed behavior: attitudes, intentions, and perceived behavior control. Journal of Experimental Social Psychology, 22, 453-474
3. Bagozzi, R. P. & Y. Yi (1988). On the evaluation of structure equation models. Acdemic of Marketing Science, 16, 76-94
4. Bailey, J. E. & S. W. Pearson (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29, 530-545
5. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2). 191-215
6. Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychology, 37(2). 122-147
7. Bergaer, I. (1993). A framework for understanding the relationship between environmental attitudes and consumer behaviors. Marketing Theory and Application, 4, Rajan Varadarjan & Bernard Jaworski (Eds). 157-163
8. Berghel, H. (2000). Digital politics 2000. Communication of the ACM, 43(11). 17-22
9. Chin W. W. & P. R. Newsted (1995). The importance of specification in casual modeling: The case of end-user computing satisfaction. Information Systems Research, 6(1). 73-81
10. Christian, E. (1999). Experiences with information locator services. Journal of Government Information, 26, 271-285
11. Cullen, R. & C. Houghton (2000). Democracy online: an assessment of new zeal government web sites. Government Information Quarterly, 17(3). 243-267
12. Cyberspace Policy Research Group (1998). Website attribute evaluation system. <http://www.cyprg.arizon.edu/waes.html> (26 December 2000)
13. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319-339
14. Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. Internal Journal of Man Machine Studies, 38, 475-487
15. Davis, F. D., R. P. Bagozzi, & P. R. Warshaw (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8). 982-1003
16. DeLone, W. H. & E. R. McLean (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1). 60-95
17. Doll, W. J. & G. Torkzadeh (1988). The measurement of end-user computing satisfaction. MIS Quarterly, 12(2). 259-274
18. Doll, W. J., W. Xia, & G. Torkzadeh (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MIS Quarterly, 18, 453-461
19. Dreze, X. & F. Zufryden (1997). Testing web site design & promotional content. Journal of Advertising Research, March/April, 77-91
20. Druse, J. (1991). Web site evaluation criteria. <http://www.washburn.edu /mabee/review.html> (3 April 2001)
21. Eschenfelder, K. R., J. C. Beachboard, C. R. McClure, & S. K. Wyman (1997). Assessing federal U.S. government websites. Government Information Quarterly, 14, 173-189
22. Evans, M. G. (1991). The problem of analyzing multiplicative composites. American Psychology, 46, 6-15
23. Fishbein, M. & I. Ajzen (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, MA
24. Fornell, C. & D. F. Lacker (1981). Evaluating structural equation model with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50
25. Gelderman, M. (1998). The relationship between user satisfaction, usage of information systems and performance. Information & Management, 34, 11-18
26. Goral, R. (1998). Web site evaluation checklist. <http://www.madison.k12. wi.us/webpub/evaluate.htm> (3 April 2001)
27. Hartwick, J. & H. Barki (1994). Explaining the role of user participation in information system use. Management Science, 40(4). 440-465
28. Hoffer, J. A. & M. B. Alex&er (1992). The diffusion of database machines. Data Base, 23(2). 13-20
29. Hwang, M. I. & R. G. Thorn (1999). The effect of user engagement on system success: A meta-analytical integration of research findings. Information & Management, 35, 229-236
30. Hwang, S. D., Y. Choi, & S. H. Myeong (1999). Electronic government in South Korea: Conceptual problems. Government Information Quarterly, 16, 277-285
31. Inter-Parliamentary Council (2000). Guidelines for the content and structure of parliamentary web sites. <http://www.ipu.org/cntr-e/web.pdf> (23 December 2000)
32. Ives, B.& M. Olson (1975). User involvement and MIS success: A review of research. Management Science, 30(5). 586-603
33. Joreskog, K. G. & D. Sorbom (1993). LISREL 8: Structural Equation Modeling with the SIMPLIS Command Language. Mooresville, in: Scientific Software, Inc
34. Karahanna, E. & D. Straub (1999). The psychology origins of perceived usefulness and ease-of-use. Information & Management, 35, 237-250
35. Laskowski, M. S. (2000). The impact of electronic access to government information: What users and documents specialists think. Journal of Government Information, 27, 173-185
36. Love, J. (1995). Pricing government information. Journal of Government Information, 22,363-387
37. Mscaulay, T. (1997). Cutting off access to government information: Loopholes in the access to information act generated by the information highway. Journal of Government Information, 24, 1-8
38. Madden, T. J., P. S. Ellen, & I. Ajzen (1992). A comparison of the theory of planned behavior and the theory of reasoned action. Personality and Social Psychology Bulletin, 18(1). 3-9
39. Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information System Research, 2(3). 173-191
40. McHaney, R. & T. P. Cronan (1998). Computer simulation success: On the use of the end-user computing satisfaction instrument: A comment. Decision Sciences, 29(2). 525-536
41. McMullen, S. (2000). US government information: Selected current issues in public access vs. Private competition. Journal of Government Information, 27, 581-593
42. Milward, H. B. & L. Q. Snyder (1996). Electronic government: Linking citizens to public organizations through technology. Journal of Public Administration Research and Theory, 6, 261-275
43. Moore, G. C. & I. Benbasat (1991). Development of an instrument to measure the perceptions of adopting and information technology innovation. Information Systems Research, 2(3). 192-222
44. Moore, G. C. & I. Benbasat (1993). An empirical examination of a model of the factors affecting utilization of information technology by end-users. Working paper, University of British Columbia, Faculty of Commerce, November
45. Nually, J. C., Psychometric Theory, New York: McGraw-Hill, 1978
46. Palvia, P. C. (1996). A model and instrument for measuring small business user satisfaction with information technology. Information & Management, 31, 151-163
47. Raymond, L. (1987). Validating and applying user satisfaction as a measure of MIS success in small organizations. Information & Management, 12, 173-179
48. Roger, E. M. (1983). Diffusion of Innovations: Third Edition, Free Press, New York
49. Ryker, R., R. Nath, & J. Henson (1997). Determinants of computer user expectations and their relationships with user satisfaction: an empirical study. Information Processing and Management, 33, 529-537
50. Safai-Amini, M. (2000). Information technologies: Challenges and opportunities for local governments. Journal of Government Information, 27, 471-479
51. Scavo, C. & Y. Shi (1999). World Wide Web Sites Design and Use in Public Management. Information Technology and Computer Applications in Public Administration: Issues and Trends, G. D. Garson, ed., Hersey: IDEA Group Publishing
52. Shannon, C. E. & W. Weaver (1949). The Mathematical Theory of Communication. University of Illinois Press, Urbana, IL
53. Shimp, T. & A. Kavas (1984). The theory of reasoned action applied to coupon usage. Journal of Consumer Research, 11, 795-809
54. Straub, D. W. (1989). Validating instruments in MIS Research. MIS Quarterly, 13(2). 147-166
55. Tate, M. & J. Alexander (1996). Teaching critical evaluation skills for world wide web resources. Computer in Libraries, 16(10). 49-55
56. Taylor, S. & P. A. Todd (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2). 144-176
57. Torkzadeh, G. & W. J. Doll (1991). Test-retest reliability of the end-user computing satisfaction instrument. Decision Sciences, 22, 26-37
58. Triandis, H. C. (1979). Values, attitudes, and interpersonal behavior. Nebraska on Motivation, 1979: Beliefs, Attitudes, & Values, University of Nebraska Press, Lincoln, NE, 195-259
59. UWEC McIntyre Library (2000). Ten c's for evaluating Internet sources. <http://www.uwec.edu/Admin/Library/Guides/tencs.html> (8 December 2000)
60. Venkadesh, V. & F. D. Davis (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3). 451-481
61. Vroom, V. (1969). Industrial social psychology. in G. Lindzey & E. Aronson (Eds.). The Handbook of Social Psychology, 5, 200-208
62. 吳俊毅 (2000). 科技接受模型之實徵研究—從動機角度，國立中央大學資訊管理研究所碩士論文
63. 吳肇銘 (1999). 影響網站使用意向之因素研究—以入門網站為例，國立中央大學資訊管理研究所博士論文
64. 陳正昌、程炳林 (1999). SPSS、SAS 、BMDP統計套裝軟體在多變量統計上的應用，五南圖書，台北
65. 黃俊英 (1999). 多變量分析，華泰，台北
66. 黃俊英 (1999). 企業研究方法，東華，台北
67. 葉旭榮 (1997). 志工參與行為意向模式的建構及其在志工人力資源招募的應用-以老人福利機構志工招募為例，國立中山大學公共事務管理研究所研士論文