臺灣博碩士論文加值系統

在這個資訊爆炸的時代，資訊量不斷的增加，人們倚賴電腦找尋資訊，快速又省時，檔案管理局於2010年修訂了「文書及檔案管理電腦化作業規範」，建立電腦化的標準作業流程及準則，為了讓公文檔管系統能妥善保存各種文件內容，檔管局及機關人員制定了系統規範以建置公文檔管系統，本研究在數位連結規模的環境之下，討論檔管局與機關人員的互動性、資訊素養及涉入程度對系統規範及驗證制度的影響，以及其間接影響公文檔管系統使用者知覺的程度。

研究回收196份問卷，其中共有138份有效問卷，結果顯示，互動性與涉入程度能夠正向的影響系統規範與驗證制度的彈性及適用性有，而資訊素養則只能夠正向影響系統規範與驗證制度的適用性，而系統規範與驗證制度的彈性則能夠正向影響公文檔管系統的功能性與有用性，系統規範與驗證制度的適用性則對公文檔管系統的功能性、有用性與易用性皆有正向的影響。

因此本研究認為，建立系統規範與驗證制度時，應重視檔管局與機關人員的互動程度與、涉入程度與資訊素養，並在制定的過程中，應注意系統規範與驗證制度的彈性是否會帶來反效果，如此，則可讓公文檔管系統更能夠因應國家、政府、人民的需求！

In the times of information explosion, the amount of information has continued to increase. People relied on computers to search information, because it’s quickly and time-saving. National Archives Administration (NAA) revised “The Working Standard of Official and Documents Management Computerization” in 2010, and established the working standard of computerization and rules. In order to preserve the variety of file contents by documents and records management system, NAA and the agency personnel set up the system-rules to establish the documents and records management system. The study will discuss the influence with interactive, information literacy, and degree of involve about NAA and agency personnel over the system-rules in the Digital Connections Scale. It’s also to discuss the indirect influence with users perception about documents and records management system.

The study received 196 questionnaires, and contains 138 available questionnaires. The results show that interaction and the degree of involvement has direct influence with flexibility and versatility about the system-rules and verifiable system. Information literacy has only direct influence with versatility about the system-rules and verifiable system. Flexibility about the system-rules and verifiable system has only direct influence with functionality and usefulness about documents and records management system. Versatility about the system-rules and verifiable system has only direct influence with functionality, usefulness, and ease of use about documents and records management system.

Therefore, the study suggests that setting up the system-rules and verifiable system should pay attention to the interaction, degree of involvement, and information literacy about NAA and agency personnel. And pay attention to the counter-effect with flexibility about system-rules and verifiable system, so that the documents and records management system may in response to country, government, and people.

圖目錄 vi
表目錄 vii
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的與研究問題 2
第三節 研究流程 3
第二章 文獻回顧 5
第一節 公文檔案管理系統 5
第二節 數位連結規模 11
第三節 多變量析方法 22
第三章 研究方法 29
第一節 研究架構 29
第二節 研究假說 30
第三節 研究變項之操作型定義及衡量方法 37
第四章 研究結果 41
第一節 樣本分析 41
第二節 探索性因素分析 43
第三節 信度分析 46
第四節 相關分析 46
第五節 建構效度 48
第六節 結構方程式 48
第五章 結論與建議 53
第一節 研究結果與發現 53
第二節 管理意涵 58
第三節 研究限制 59
第四節 未來研究建議 60
參考文獻 61
中文文獻 61
其他文獻 62
英文文獻 63
附錄一 本研究之問卷內容 70
附錄二 本研究問卷之填答次數統計 74

李德治、童惠玲 (2009)。多變量分析：專題及論文常用的統計方法。台北：雙葉書廊有限公司。
邱吉鶴（2008）。行政首長領導策略與組織績效管理。公共行政學報，第26期，37-69頁。
林師模、陳苑欽（主編）（2003）。多變量分析：管理上的應用。台北：雙葉書廊有限公司。
葉英斌、李岳儒(2012)。探討供應鏈關係中關係治理與關係規範構面之整合衡量課題。育達科大學報，第30期，133-156頁。
郭莉真(2004)。策略領導對組織績效之影響－以學習型組織為中介變數。國立台北大學企業管理學系博士論文。
陳景堂(2006)。統計分析SPSS for Windows 入門與應用(第六版)。台北：儒林圖書有限公司。
陳振昌、程炳林、陳新豐、劉子鍵(2011年)。多變量分析方法－統計軟體應用。台北：五南圖書出版股份有限公司。
陳富強、方顯光、黃銘瑜（2007）。從智慧資本觀點探討非營利組織績效評估。全球商管研究，第2期，115-137頁。
陳謝裕(2001)。企業競爭的核心：IT Capability-構面的探討與衡量使度的建立。國立中山大學資訊管理所碩士論文。
陳耀茂(2004)。多變量分析的SPSS使用手冊。台北：鼎茂圖書。
楊世瑩(2005)。SPSS統計分析實務。台灣：旗標。
蕭文龍(2008)。多變量分析最佳入門實用書-SPSS+LISREAL(SEM)。台北：碁峰資訊股份有限公司。
公文及檔案管理資訊系統驗證網，2013/10/20，( available online at http://archives.cisanet.org.tw/know.aspx).
檔案管理局，2013/10/20 ，(available online at http://www.archives.gov.tw/)
Association of College and Research Libraries，2013/11/06，(available online at http://www.ala.org/acrl/standards/informationliteracycompetency)
Ajzen, I. 1985. From Intentions to Actions: a Theory of Planned Behavior, in Action Control: From Cognition to Behavior, Kuhl, J. and Bechmann, J. (eds.), Springer-Verlag Berlin Heidelberg, New York.
American Library Association Presidential Committee on InformationLiteracy. 1989. Final Report, ALA, Chicago.
Bagozzi, R. P., and Yi, Y. 1988. “On the evaluation of structural equation models,” Journal of the Academy of Marketing Science (16:1), pp.74-79.
Bloch, P. H., and Richins, M. L. 1983. “A Theoretical Model for the Study of Prosuct Important Perceptions,” Journal of Marketing (47:3), pp.69-81.
Bredrup, H. 1995. “Developing a Performance Management System, Performance Management : A Business Process Bench-marking Approach,” Chapman &; Hall. England, pp.84-87.
Browen, L., and Chaffee, S. H. 1974. “Product Involvement and Pertinent Advertising Appeals,” Journalism Quarterly (51), pp.613-621.
Browne, M. W., and Cudeck, R. 1993. Alternative Ways of Assessing Model Fit, in Testing Structural Equation Models, Bollen, K.A. and Long, J.S. (eds.), CA: Sage Publications, Newbury Park.
Block, P. H. 1981. “An Exploration into the Scaling of Consumers Involvement with a Product Class?” Advances in Consumer Research (8), pp.61-65.
Chan, W.K.V., and Hsu, C. 2009. “Service Scaling on Hyper-Networks,” Service Science (1:1), pp.17-31.
Chan, W.K.V., and Hsu, C. 2010. “How Hyper-Network Analysis Help Understand Human Networks,” Service Science (2:4), pp. 270-280.
Davis, F. D. 1989. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly (13:3), pp.319-340.
Davis, F. D., and Bagozzi, R. P. 1989. “User Acceptance of Computer Technology: a Comparison of Two Theoretical Models,” Management Science (35:8), pp.982-1003.
Davis, F. D., and Venkatesh, V. 1996. “A critical Assessment of Potential Measurement Biases in the Technology Acceptance Model: Three Experiments,” International Journal of Human- Computer Studies (45:1), pp.19-45.
Davis, G.B. 1982. “Strategies for Information Requirements Determination,” IBM Systems Journal (21:1), pp.4-30.
Davis, J. A., Brewer, J., and Atkin, D. 1992. “Pre-seasonal Physiological Characteristics of English First and Second Division Soccer Players.” Journal of Sports Science (10:6), pp.541-547.
DeLone, W. H., and McLean, E. R. 1992. “Information Systems Success: The Quest for the Dependent Variable,” Information Systems Research (3:1), pp. 60-95.
DeSanctis, G., and Poole, M. S. 1994. “Capturing the Complexity in Advanced Technology Use: Adaptive Structuration Theory,” Organization Science, (5:2), pp.121-147.
Dixon, N. M. 1999. The Organizational Learning Cycle: How We Can Learn Collectively, Gower, Aldershot.
Engel, J. F., and Blackwell, R. D. 1982. Consumer Behavior, Dryden Press, Chicago.
Fink, L., and Neumann, S. 2009. “Exploring the Perceived Business Value of the Flexibility Enabled by Information Technology Infrastructure,” Information &; Management (46:2), pp.90-99.
Fishbein, M., and Ajzen, I. 1975. Belief, Attitude, Intention and Behavior: an Introduction to Theory and Research, Reading, MA: Addision-Wesley.
Fornell, C. and Larcker, D. F. 1981. “Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics,” Journal of Marketing Research (18:3), pp.382-388.
Goodhue, D. L., and Thompson, R. L. 1995. “Task-Technology Fit and Individual Performance,” MISQuartely (19:2), pp.213-236.
Hair, J., Anderson, R., Tatham, R., and Black, W. 1998. Multivarite data analysis, Macmillan, New York.
Hsu, C. 2007. ”Scale With Connection: Service Innovation,” IEEE (7:10), pp.4057-4061.
Hsu, C. 2009. ”Service Science and Network Science,” Service Science (1:2), pp. 1-3.
Hsu, C. 2009. Service Science: Design for Scaling and Transformation, World Scientific and Imperial College Press, Singapore.
Hsu, C. and Spohrer, J. 2009. ”Improving Service Quality and Productivity: Exploring the Digital Connection Scaling Model,” International Journal of Service Technology and Management (11:3), pp. 272-292.
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.
Jarvenpaa, S. L., Tractinsky, N., and Vitale, M. 2000. “Consumer Trust in an Internet Store,” Information Technology and Management (1:1-2), pp.45-71.
Jones, L. B. 1992. Linking Undergraduate Education and Libraries: Minnesota’s Approach, in Farmer, D.W. and Mech, T. (Eds.), Information Literacy: Developing Students As Independent Learners, San Francisco: Jossey-Bass.
Joreskog, K.G. and Sorbom, D. 2000. LISREL VI, Analysis of Linear Structural Relationships by Maximum Likelihood, Instrumental Variables, and Least Squares Methods, (eds.), Mooresville, Indiana: Scientific Software.
Kenny, D.A., and McCoach, D.B. 2003. “Effect of the Number of Variables on Measures of Fit in Structural Equation Modeling,” Structural Equation Modeling (10:3), pp.333-351.
Kujala, S. 2003. “User Involvement: A Review of The Benefits and Challenges,” Behavior &; Information Technology (22:1), pp.1-16.
Lastovicka, J. L., and Gardner, D. M. 1979. Components of Involvement, in Attitude Research Plays for High Stakes. Maloney, J. C., and Silverm, B. (Eds.), American Marketing Association, Chicago.
Lewin, K. 1939. “The field Theory Approach to Adolescence,” American Journal of Sociology (44), pp.868-897.
Marsha, R. L., and Bloch, P. H. 1986. “After the New Wears off: The Temporal Context of Product Involvement,” Journal of Consumer Research (13:2), pp.280-285.
McClure, C. R. 1994. “Network Literacy: A Role for Libraries?” Information Technology and Libraries (13:2), pp.115-126.
McManus, J., and Wood-Harper, T. 2003. “Information Systems Project Management: The Price of Failure,” Management Services (47:5), pp.16-19.
McMillan, S. J., and Hwang, J. S. 2002. “Measures of Perceived Interactivity: an Exploration of the Role of Direction of Communication, User Control, and Time in Shaping Perceptions of Interactivity,” Journal of Advertising Research (31:3), pp.29-42.
Meyer, M. H., and Zack, M. H. 1996. “The Design and Development of Information Products,” Sloan Management Review (37:3), pp.43-59.
Mitchell, A. A. 1979. “Involvement: A Potentially Important Mediator of Consumer Behavior,” Advances in Consumer Research (6), pp.191-196.
Mittal, B. I., and Lee, M. S. 1989. “A Causal Model of Consumer Involvement,” Journal of Economic Psychology (10:3), pp.363-389.
Park, C. W., and Young, S. M. 1983. “Types and Levels of Involvement and Brand Attitude Formation,” Advances in Consumer Research (10:1), pp.320-324.
Petty, R.E., Cacioppo, J. T., and Schumann , D. 1983. “Central and Peripheral Route to Advertising Effectiveness: The Moderating Role of Involvement,” Journal of Consumer Research (9:5), pp.135-146.
Poole, M. S., and Desantics, G. 1990. Understanding the Use of Group Decision Support Systems: the Theory of Adaptive Structuration, in Organizations and Communication Technology, Steinfield C., Fulk, J. and Hill, B. (eds.), CA: Sage Publications, Newbury Park.
Rafaeli, S. 1988. Interactivity: From New Media to Communication, in Hawkins, R. P. Wiemann, J. M., and Pingree, S. (eds.), Advertising Communication Science: Merging Mass and Interpersonal Process, CA: Sage, Newbury Park.
Repschlaeger, J., Wind, S., Zarnekow, R., and Turowski, K. 2011. “A Reference Guide to Cloud Computing Dimensions: Infrastructure as a Service Classification Framework,” Hawaii International Conference on System Sciences. pp.2178-2188.
Rice, R. E. 1984. Development of New Media Technology: Growth and Integration, in Rice, R. E. (eds.), The New Media: Communication, Research, and Technology, CA: Sage, Beverly Hills.
Robertson, T. S., Zielinski, J. and Ward, S. 1984. Consumer Behavior, Scort Foresman, Glenview.
Selim, H. M. 2003. “An empirical investigation of student acceptance of course websites,” Computers &; Education (40:4), pp.343-360.
Sharma, S., Mukherjee, S., Kumar, A., and Dillon, W. R. 2005. “A Simulation Study to Investigate the Use of Cutoff Values for Assessing Model Fit in Covariance Structure Models,” Journal of Business Research (58:7), pp.935-943.
Sherif, M., and Cantril, H. 1947. The Psychology of Ego-Involvement, John Wiley and Sons, New York.
Smith, P. 1999. “The Learning Organization Ten Years on: A Case Study,” The Learning Organization (6:5), pp.217-223.
Steuer, J. 1992. “Defining Virtual Reality: Dimensions Determining Telepresence,” Journal of Communication (42:4), pp.73-93.
Telem, M. 1988. “Information Requirements Specification I: Brainstorming Collective Decision-Making Approach,” Information processing and Management (24:5), pp.549-557.
Tse, A.C.B., and Chan, C.-F. 2004. “The Relationship Between Interactive Functions and Website Ranking,” Journal of Advertising Research (44:4), pp.369-374.
Warrington , P., and Shim, S. 2000. “An Empirical Investigation of the Relationship between Product Involvement and Brand Commitment,” Psychology &; Marketing (17:9), pp.761-782.
Wiegers, K. 1988. Software Requirements, Addison-Wesky.
Wixom, B. H., and Todd, P. A. 2005. “A Theoretical Integration of User Satisfaction and Technology Acceptance,” Information System Research 16, pp.88-102.
Winner, N.1948. Cybernetics, Wiley, New York.
Wu, G. 1999. “Perceived Interactivity and Attitude toward Websit.” 1999 Annual Conference of American Academy of Advertising Albuquerque.
Yeo, R. 2003. “The Tangibles and Intangibles of Organizational Performance,” Team Performance Management (7:8), pp. 199-204.
Zaichkowsky, J. L. 1985. "Familiarity: Product Use, Involvement or Expertise?" Association for Consumer Research (12), pp.296-299.
Zaichkowsky, J. L. 1985. ”Measuring the Involvement Construct,” Journal of Consumer Research (12), pp.341-352.
Zaichkowsky, J. L. 1986. “Conceptualizing Involvement,” Journal of Advertising (15:2), pp.4-14.