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    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/63651


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    題名: 企業資訊科技能力指標之研究
    A Study of Information Technology Capability Indicators
    作者: 林志弘
    Lin, Jyh Horng
    貢獻者: 曾淑峰
    Tseng, Shu Feng
    林志弘
    Lin, Jyh Horng
    關鍵詞: 資訊科技能力
    企業績效
    灰色熵
    典型相關分析
    Information Technology Capability
    Firm Performance
    Grey Entropy
    Canonical Correlation Analysis
    日期: 2013
    上傳時間: 2014-02-10 14:48:26 (UTC+8)
    摘要: 在全球化市場的激烈競爭環境中，資訊科技對企業而言已是一種提升競爭優勢的策略性設備，而先前文獻對於資訊科技能力的評估或與企業績效關聯性的探討，多以行為性問卷的認知數據量表進行研究，少有利用事實性問卷所收集的現象數據評估資訊科技能力及進一步分析資訊科技能力與企業績效關聯性之研究。故本研究基於資源基礎觀點理論，利用企業事實性現象填答問卷建立企業資訊科技能力評估模型，包含資訊科技的導入狀態、應用方式及使用經驗等現象相關問項，如硬體、網路、資訊系統應用程度及範圍等，並探討資訊科技能力與企業績效的關聯性。使用典型相關分析進行實證研究發現，針對先前政府委託調查所收集資料計算出來的企業資訊科技能力，與公開發行的上市櫃企業財務資料所計算出來的企業績效具有顯著關聯性，特別是會計型財務績效之經營能力，經檢定具統計顯著性。進一步進行產業別比較，先使用灰色熵權重分析對於各個子構面進行權重估計，並以權重加權法重新計算每一樣本之資訊科技能力，再進行單因子變異數分析，顯示各產業間之資訊科技能力及子構面能力多數呈現顯著差異。本研究所提出的資訊科技能力評估模型與企業績效關聯檢定模式，以及產業間資訊科技能力差異性分析模式，可提供政府或產業觀察機構建立長期觀測平台，以彙整各種產業資訊科技導入現象及應用範圍，使政府與企業可檢視整體產業整體或個別產業資訊科技能力之差異，藉以擬定資訊科技投資策略，提升企業競爭優勢。
    In the highly competitive globalization environment, information technology (IT) has become strategic equipment for leveraging a business’s competitive advantage. Most previous studies use perceptual questionnaire to collect behavioral data for evaluating IT capability, and furthermore to explore the relationship between IT capability and firm performance. Very few studies use factual questionnaire to collect the phenomenon data for analysis. In this study, we propose a model of evaluating IT capability based on Resource-Based View (RBV) theory and use factual phenomenon questionnaire including induction status, application approach, and usage experience, such as hardware, networks, IS application levels and scopes, etc. The research also explores the relationship between IT capability and firm performance. The IT capability data are calculated from the earlier government-sponsored survey. The firm performance data by financial indicators are collected or calculated from the open data of listed companies in Taiwan Stock Exchange and Over-the-Counter Agencies. The Canonical Correlation Analysis is used and shows significantly positive relationship for the IT capability affecting the firm performance, especially in Accounting-Based Financial Indicators. Before further analysis of industry comparison, Grey Entropy is used to estimate the weights of three sub-constructs and the overall IT capability is then re-calculated by integrating the weighted sub-construct capabilities. Afterwards, the One-Way ANOVA analysis is conducted and shows significant differences across industries in the overall IT capability of the firm and the IT capabilities of the sub-constructs. The proposed IT capability estimation model and the relationship analysis for the IT capability and firm performance can be used by the government or industry observation institution to continuously watch the industry IT capability phenomena and its relationship with the firm performance. The observation for the whole country and across industries can be used as a reference to pursue appropriate IT investments for strategic advantage.
    參考文獻: 1. Alpar, P. and Kim, M. (1990). A microeconomic approach to the measurement of information technology value. Journal of Management Information Systems, 7(2), pp. 55-69.
    2. Babura, A. and Lee, B. (1997). The Information Technology Productivity Paradox Revisited: A Theoretical and Empirical Investigation in the Manufacturing SectorRevisited: A Theoretical and Empirical Investigation in the Manufacturing Sector. International Journal of Flexible Manufacturing Systems, 9(2), pp. 145-166.
    3. Bagozzi, R.P. and Yi, Y. (1988). On the Evaluation of Structural Equation Mdels. Academy of Marking Science, 16, pp. 76-94.
    4. Banker, R.D. ; Bardhan, I.R. and Asdemir, O. (2006). Understanding the impact of collaboration software on product design and development. Information Systems Research, 17(4), pp. 352-373.
    5. Barney, J. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17, pp. 99-120.
    6. Barua, A.; Kriebel, C. and Mukhopadhyay, T. (1995). Information Technologies and Business Value: An Analytic and Empirical Investigation. Information Systems Research, 6(1), pp. 3-23.
    7. Bentler, P. M. and Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structure. Psychological Bulletin, 88, pp. 588-606.
    8. Bernstein, L. (1989). Financial Statement Analysis, theory, application, and interpretation (4 ed.). Homewood, Illinois: Richard D. Irwin, Inc.,.
    9. Bharadwaj, A. S. (2000). A resource-based perspective on information technology and firm performance: an empirical investigation. Management Information Systems Quarterly, 24(1), pp. 169-196.
    10. Bharadwaj, A.S.; Bharadwaj, S.G. and Konsynski, B.R. (1999). Information Technology Effects on Firm Performance as Measured by Tobins q. Management Science, 45(7), pp. 1008-1024.
    11. Bhatt, G. D. and Grover, V. (2005). Types of Information Technology Capabilities and Their Role in Competitive Advantage: An Empirical Study. Joumal of Management Information Systems, 22(2), pp. 253-277.
    12. Blili, S. and Raymond L. (1993). Information Technology: Threats and Opportunities for Small and Medium-Sized Enterprises. International Journal of Information Management, 13(6), pp. 439-448.
    13. Browne, M. W. and Cudeck, R. (1992). Alternative Ways of Assessing Model Fit. Sociological Methods & Research, 21, pp. 230-258.
    14. Brynjolfsson E.; Malone, T.W.; Gurbaxani V. and Kambil, A. (1994). Does information technology lead to smaller firms. Management Science, 40(12), pp. 1628-1644.
    15. Brynjolfsson, E. (1993). The Productivity Paradox of Information Technology. Communications of the ACM, 35, pp. 66-77.
    16. Brynjolfsson, E. and Hitt, L. (1996). Paradox Lost? Firm-Level Evidence on the Returns to Information Systems Spending. Management Science, 42(4), pp. 541-558.
    17. Brynjolfsson, E. and Hitt, L.M. (2000). Beyond Computation: Information Technology, Organizational Transformation and Business Performance. The Journal of Economic Perspectives, 14(4), pp. 23-48.
    18. Chari, M.D.R., Devara, S. and David, P. (2007). International diversification and firm performance: Role of information technology investments. Journal of World Business, 42(2), pp. 184-197.
    19. Chari, M.D.R., Devaraj, S. and David, P. (2008). Research Note—The Impact of Information Technology Investments and Diversification Strategies on Firm Performance. Management Science, 54(1), pp. 224-234.
    20. Chung, K.H. and Pruitt, S.W. (1994). A simple approximation of Tobin`s q. Financial Management, 23(3), pp. 70-74.
    21. Darden, W. R. (1981). Review of Behavioral Modeling in Maretking. In Review of Marketing. Chicago: American Marketing Association.
    22. Davenport, T.H. and Prusak, L. (1999). Working Knowledge: How Organizations Manage what They Know. Boston,MA.: Harvard Business School Press.
    23. Dedrick, J. and Kraemer, K.L. (2010). Impacts of internal and interorganizational information systems on the outsourcing of manufacturing. The Journal of Strategic Information Systems, 19(2), pp. 78-95.
    24. Dedrick, J., Gurbaxani, V. and Kraemer, K.L. (2003). Information Technology and Economic Performance: A Critical Review of the Empirical Evidence. ACM Computing Surveys, 35(1), pp. 1-28.
    25. Dehning, B., and Richardson, V. J. (2002). Return on investments in information technology: A research synthesis. Journal of Information Systems, 16(1), pp. 7-30.
    26. Delone, W. (1981). Firm size and the characteristics of computer use. Management Information Systems Quarterly, 5(4), pp. 65-77.
    27. Demsetz, H. and Villalonga, B. (2001). Ownership structure and corporate performance. Journal of Corporate Finance, 7, pp. 209-233.
    28. Deng, H., Yeh, C.H. and Willis, R.J. (2000). Inter-company comparison using modified topsis with objective weights. Computer and Operations Research, 27(10), pp. 963-973.
    29. Deng, J.L. (1982). Control problems of grey system. System and Control Letters, pp. 288-294.
    30. Deng, J.L. (1989). Introduction to grey system theory. The Journal of Grey System, 1(1), pp. 1-24.
    31. Devaraj, S. and Kohli, R. (2002). The IT payoff:Measuring the Business Value of Information Technology Investments. Upper Saddle River, New Jersey: Financial Times Prentice Hall Books.
    32. Devaraj, S. and Kohli, R. (2003). Performance Impacts of Information Technology: Is Actual Usage the Missing Link? Management Science, 49(3), pp. 273-289.
    33. Dos Santos, B.;Peffers, K.and Mauer, D. (1993). The impact of information technology investment announcements on the market value of the firms. Information Systems Research, 4(1), pp. 1-23.
    34. Drucker, P. F. (2006). The Effective Executive. New York: Harpercollins.
    35. Earl, M. J. (1994). The New and the Old of Business Process Redesign. The Journal of Strategic Information Systems, 3(1), pp. 5-22.
    36. E-Business W@tch. (2010). ICT and e-Business for an Innovativeand Sustainable Economy - 7th Synthesis. Report of the Sectoral e-Business Watch. European Commision.
    37. Farbey, B., Land, F. and Targett, D. (1992). Evaluating Investments in IT. Journal of Information Technology, 7(2), pp. 109-122.
    38. Feeny, D.F. and Willcocks , L.P. (1998). Core IS capabilities for exploiting information technology. Sloan Management Review, 39(3), pp. 9-21.
    39. Feng, C.M. and Wang, R.T. (2000). Performance evaluation for airlines including the consideration of financial ratios. Journal of Air Transport Management, 6(3), pp. 133-142.
    40. Floyd, S. W. and Wooldridge., B. (1990). Path analysis of the relationship between competitive strategy,information technology, and financial performance. Journal of Management Information Systems, 1, pp. 47-64.
    41. Gartner. (2007). Investor Relations Annual Report. Gartner.
    42. Golany, B. and Roll, Y. (1993). Some Extension of Techniques to Handle Non-discretionary Factors in Data Envelopment Analysis. Journal of Productivity Analysis, 4(4), pp. 419-432.
    43. Goo, J.; Kishore, R.; Nam, K.; Rao, H.R. and Song, Y. (2007). An investigation of factors that influence the duration of IT outsourcing relationships. Decision Support Systems, 42(4), pp. 2107-2125.
    44. Grant, R. M. (1995). Contemporary Strategy Analysis (8 ed.). Oxford, U.K.: Blackwell Publishers Inc.
    45. Grant, R.M. (1991). The resource-based theory of competitive advantage: Implications for strategy formulation. California Management Review, 33(3), pp. 114-135.
    46. Hair, J. F. J., Anderson, R. E., Tatham, R. L., and Black, W. C. (1998). Multivariate data analysis (5 ed.). Englewood Cliffs, New York: Prentice-Hall.
    47. Han, H.S.; Lee, J.N. and Seo, Y.W.;. (2008). Analyzing the impact of a firm`s capability on outsourcing success: a process perspective. Information and Management, 45(1), pp. 31-42.
    48. Hayes, D. C.; Hunton, J. E. and Reck, J. L. (2001). Market Reaction to ERP Implementation Announcements. Journal of Information Systems, 15(1), pp. 3-18.
    49. Hitt, L. M. and Brynjolfsson, E. (1996). Productivity, business profitability, and consumer surplus: Three different measures of information technology value. Management Information Systems Quarterly, 20(2), pp. 121-142.
    50. Hitt, L.M., Wu, D.J. and Zhou,X. (2002). Investment in Enterprise Resource Planning: Business Impact and Productivity Measures. Journal of Management Information Systems, 19(1), pp. 71-98.
    51. Ho, C. B. (2011). Measuring dot com efficiency using a combined DEA and GRA approach. Journal of the Operational Research Society, 62, pp. 776-783.
    52. Hotelling, H. (1935). The most predictable criterion. Journal of Educational Psychology, 26(2), pp. 139-142.
    53. Hu, L.T. and Bentler, P.M. (1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Structural Equation Modeling, 1, pp. 1-55.
    54. Huang, S.M.; Ou, C.S.; Chen, C.M. and Lin, B. (2006). An empirical study of relationship between IT investment and firm performance: A resource-based perspective. European Journal of Operational Research, 173(3), pp. 984-999.
    55. Huber, G. (1990). A Theory of the Effects of Advanced Information Technologies on Organizational Design, Intelligence, and Decision Making. The Academy of Management Review, 15(1), pp. 47-71.
    56. Im, K.S.; Dow, K.E. and Grover, V. (2001). A Reexamination of IT Investment and the Market Value of the Firm – An Event Study Methodology. Information Systems Research, 12(1), pp. 103-117.
    57. Im, K.S.; Grover, V. and Teng, T.C. James. (2013). Research Note—Do Large Firms Become Smaller by Using Information Technology? Information Systems Research, 24(2), pp. 470-491.
    58. Ives, B. and Learmonth, G.P. (1984). The Information System as a Competitive Weapon. Communications of the ACM, 27(12), pp. 1193 - 1201.
    59. Jee, D.H. and Kang, K.J. (2000). A method for optimal material selection aided with decision making theory. Materials and Design, 21(3), pp. 199-206.
    60. Kao, L.F.; Chiou, J.R. and Chen A. (2004). The agency problems, firm performance and monitoring mechanisms: The evidence from collateralized shares in Taiwan. Corporate Governance: An International Review, 12(3), pp. 389-402.
    61. King, W. (2002). IT capabilities, business processes, and impact on the bottom line. Information Systems Management, 19(2), pp. 85-87.
    62. Kivijarvi, H. and Saarinen, T. (1995). Investment in Information Systems and the Financial Performance of the Firm. Information and Management, 28(3), pp. 143-163.
    63. Kudyba, S. and Diwan, R. (2002). Increasing returns to information technology. Information Systems Research, 13(1), pp. 104-111.
    64. Lai, F.; Li, D.; Wang, Q. and Zhao, X. (2008). The information technology capability of third-party logistics providers: a resource-based view and empirical evidence from china. Journal of Supply Chain Management, 44(3), pp. 22-39.
    65. Lai, K.H. ; Wong, Christina W.Y. and Cheng, T.C.E. (2008). A coordination-theoretic investigation of the impact of electronic integration on logistics performance. Information and Management, 45(1), pp. 10-20.
    66. Laudon, K.C. and Laudon, J.P. (2000). Management Information Systems: Organization Theory in the Networked Enterprise (6 ed.). Prentice-Hall.
    67. Leavitt , H.J. and Whisler , T.L. (1958, 11). Management in the 1980`s. Harvard Business Review.
    68. Lee, S. and Kim, S.H. (2006). A Lag Effect of IT Investment on Firm Performance. Information Resources Management Journal, 19(1), pp. 43-69.
    69. Lee, S. and Lim, G. G. (2005). The impact of partnership attributes on EDI implementation success. Information and Management, 42(4), pp. 503-516.
    70. Lee, S.; Kim, S. H.;. (2006). A Lag Effect of IT Investment on Firm Performance. Information Resource Management Journal, 19(1), pp. 43-69.
    71. Lee, T.W. Pual; Lin, C.W. and Shin, S.H. (2012). A comparative study on financial positions of shipping companies in Taiwan and Korea using entropy and grey relation analysis. Expert Systems with Applications, 39(5), pp. 5649-5657.
    72. Li, M. and Ye, R. (1995). Information Technology and Firm Performance: Linking with Environmental Strategic and Managerial Contexts. Information and Management, 35(1), pp. 43-51.
    73. Liang, T.P.; You, J.J.; Liu, C.C. (2010). A resource-based perspective on information technology and firm performance: a meta analysis. Industrial Management & Data Systems, 110(8), pp. 1138-1158.
    74. Lim, J.H., Dehning, B., Richardson, V.J. and Smith, R.E. (2011). A Meta-Analysis of the Effects of IT Investment on Firm Financial Performance. Journal of Information Systems, 25(2), pp. 145-169.
    75. Mahmood, M.A., Mann, G.J., Dubrow, M. and Skidmore, J. (1998). Information Technology Investment and Organizational Performance: A Lagged Data Analysis. Proceedings of the Information Resources Management Association, (pp. 19-22).
    76. Masli, A.,nRichardson, V.J., Sanchez, J.M. and Smith, R.E. (2011). Returns to IT excellence: Evidence from financial performance around information technology excellence awards. International Journal of Accounting Information Systems, 12(3), pp. 189-205.
    77. Melville, N. ; Kraemer, K. ; Gurbaxani, V. (2004). Information technology and organizational performance: an integrative model of it business value. MIS Quarterly, 28(2), pp. 283-320.
    78. Melville, N. Kraemer, K. and Gurbaxani, V. (2004). Review: Information Technology and Organizational Performance: An Integrative Model of IT Business Value. Management Information Systems Quarterly, 28(2), pp. 283-322.
    79. Mithas, S., Ramasubbu, N., & Sambamurthy, V. (2011). How Information Mnanagement Capability Influences Firm Performance. Management Information Systems Quarterly, 35(1), pp. 237-256.
    80. Mithas, S., Tafti, A.R., Bardhan, I. and Goh, J.M. (2012). Information Technology and Firm Profitability: Mechanisms and Empirical Evidence. Management Information Systems Quarterly, 36(1), pp. 205-224.
    81. Morris, S.A. and Strickland, T.H. (2009). Exploration of information system process improvements and firm performance. Journal of Computer Information Systems, 49(2), pp. 86-91.
    82. Neufville, D. (1979). Social Indicators amd Public Policy : Interactive Process of Design and Application. New York: Elsevier.
    83. Nolan, R. L. (1973). Managing the Computer Resource:A Stage Hypothesis. Communications of the ACM, 16(7), pp. 399-405.
    84. Patrakosol, B., & Lee, S. M. (2009). IT capabilities, interfirm performance, and the state of economic development. Industrial Management & Data Systems, 109(9), pp. 1231-1245.
    85. Powell, T.C.; Dent-Micallef, A.;. (1997). Information technology as competitive advantage: the role of human, business, and technology resources. Strategic Management Journal, 18(5), pp. 375-405.
    86. Rai, A.; Patnayakuni, R. and Patnayakuni, N. (1997). Technology investment and business performance. Communications of the ACM, 40(7), pp. 89-97.
    87. Rai, A.; Patnayakuni, R. and Seth, N. (2006). Firm Performance Impacts of Digitally Enabled Supply Chain Integration Capabilities. Management Information Systems Quarterly, 30(2), pp. 225-246.
    88. Ravichandran, T. and Lertwongsatien, C. (2005). Effect of information systems resources and capabilities on firm performance: a resource-based perspective. Journal of Management Information Systems, 21(4), pp. 237-276.
    89. Ravichandran, T., Liu, Y., Han, S. and Hasan, I. (2009). Diversification and Firm Performance: Exploring the Moderating Effects of Information Technology Spending. Journal of Management Information Systems, 25(4), pp. 205-240.
    90. Ross, J. W.; Beath, C. M. and Goodhue, D. (1996). Develop long-term competitiveness through IT assets. Sloan Management Review, pp. 31-42.
    91. Sabherwal, R. (1999). The relationship between information system planning sophistication and information system success: An empirical assessment. Decision Sciences, 30(1), pp. 137-167.
    92. Sanders, N. R. and Premus, R. (2005). Modeling the relationship between firm IT capability:collaboration, and performance. Journal of Business Logistics, 26(1), pp. 1-23.
    93. Santhanam, R. and Hartono, E. (2003). Issues in linking information technology capability to firm performance. Management Information Systems Quarterly, 27(1), pp. 125-153.
    94. Saraf, N. ; Langdon, C.S. and Gosain, S. (2007). IS application capabilities and relational value in interfirm partnerships. Information Systems Research, 18(3), pp. 320-339.
    95. Shannon, C.E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27, pp. 379-423 & 623-656.
    96. Sharma, S. (1996). Applied multivariate techniques. John Wiley & Sons, Inc.
    97. Shuaia, J.J. and Wu, W.W. (2011). Evaluating the influence of E-marketing on hotel performance by DEA and grey entropy. Expert Systems with Applications, 38(7), pp. 8763-8769.
    98. Sircar, S.; Turnbow, J.L. and Bordoloi, B. (2000). A framework for assessing the relationship between information technology investments and firm performance. Journal of Management Information Systems, 16(4), pp. 69-97.
    99. Stratopoulos, T. and Dehning, B. (2000). Does successful investment in information technology solve the productivity paradox? Information and Management, 38(2), pp. 103-117.
    100. Straub, D.; Boudreau, M.C. and Gefen, D. (2004). Validation Guidelines for IS Positivist Research. Communications of the Association for Information Systems, 13, pp. 380-427.
    101. Subramani, M. (2004). How do suppliers benefit from information technology use in supply chain relationships? Management Information Systems Quarterly, 28(1), pp. 45-73.
    102. Subramani, M. and Walden, E. (2001). The Impact of E-Commerce Announcements on the Market Value of Firms. Information System Research, 12(2), pp. 135-154.
    103. Tam, K.Y. (1998). The impact of information technology investments on firm performance and evaluation: Evidence from newly industrialized economics. Information Systems Research, 9(1), pp. 85-89.
    104. Tippins, M.J.; and Sohi, R.S. (2003). IT Competency and Firm Performance: is Organisational Learning a Missing Link? Strategic Management Journal, 24(8), pp. 745-761.
    105. Tobin, J. (1969). A General Equilibrium Approach to Monetary Theory. Journal of Money, Credit and Banking, 1, pp. 15-29.
    106. Tseng, S.F. and Lin, J.H. (2012). Evaluating Information Technology Impact on Business Performance of Biotechnology Industry Using Grey Relation Entropy Analysis. Journal of Convergence Information Technology, 17(4), pp. 297-305.
    107. Turban, E., Mclean, E., and Wetherbe, J. (2001). Information Technolog for Management: Making Connections for Strategic Advantage (Second Edition ed.). New York: John Wiley & Sons.
    108. Venkatraman, N.and Ramanujam, V. (1986). Measurement of business performance in strategy research: A comparison of approaches. Academy of Management Review, 11, pp. 801-814.
    109. Wang, R,T,; Ho, C.T. Bruce Ho, and Oh, K. (2010). Measuring Production and Marketing Efficiency Using Grey Relation Analysis and Data Envelopment Analysis. International Journal of Production Research, 4(1), pp. 183-199.
    110. Wen, K.L., Chang, T.C. and You, M.L. (1998). The grey entropy and its application in weighting analysis. IEEE International Conference on Systems, Man, and Cybernetics, 2, pp. 1842-1844.
    111. Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management Journal, 5(2), pp. 171-180.
    112. Willcock, L. (1994). Evaluating the Feasibility of Information Systems Investments: Recent UK Evidence and New Approaches. In In Information Management: The Evaluation of Information Systems Investments (pp. 49-77). Chapman & Hall.
    113. Willcocks, L. (1994). Managing information systems in UK public administration - trends and future prospects. Public administration, 72(1), pp. 3-32.
    114. Wright, S. (1921). Correlation and causation. Journal of Agricultural Research(7), pp. 557-585.
    115. Yang, Y. and Wu, L. (2007). Grey Entropy Method for Green Supplier Selection. International Conference on Wireless Communications, Networking and Mobile Computing, (pp. 4682 - 4685). Shanghai, China.
    116. Yeh, C. H., Lee, G. G., & Pai, J. C. (2012). How information system capability affects e-business information technology strategy implementation: An empirical study in Taiwan. Business Process Management Journal, 18(2), pp. 197-218.
    117. Zhu, D.S.; Ho, C.T. Bruse; Lin, L.H. (2005). A Study on the Performance Evaluation of Taiwan`s Newly Reorganized Banks. Sun Yat-Sen Management Review, pp. 125-157.
    118. Zhu, K . and Kraemer, K. L. (2002). E-commerce metrics for net-enhanced organizations: Assessing the value of e-commerce to firm performance in the manufacturing sector. lnformation Systems Research, 13(3), pp. 275-295.
    119. 余民寧. (2005). 心理與教育統計學 (第 修訂二版 版). 台北市: 三民書局.
    120. 吳漢雄、鄧聚龍、溫坤. (1996). 灰色分析入門. 台北市: 高立圖書有限公司.
    121. 林義夫. (2003). 數位經濟發展現況與展望. 國家政策季刊, 2(1), 頁 91-114.
    122. 高麗萍. (2004). 企業E 化宣告效果之研究-以台灣上市公司為例. 電子商務學報, 6(1), 頁 53-73.
    123. 張紹勳. (2007). 研究方法 (第 2 版). 滄海書局.
    124. 陳智凱. (2005). 知識經濟指標之信度與效度研究. 管理評論, 24(3), 頁 17-41.
    125. 傅粹馨. (1996). 事後比較的方法. 教育學刊, 頁 149-174.
    126. 曾淑峰、鄭天澤及林志弘. (2009). 建立我國企業e 化成熟度指標之研究. 電子商務研究, 7(4), 頁 405-426.
    127. 黃俊英. (2000). 多變量分析. 中國經濟企業研究所.
    128. 溫坤禮、趙忠賢、張宏志、陳曉瑩及溫惠筑. (2009). 灰色理論與應用. 台中市: 五南出版社.
    129. 經濟部技術處. (2011). 科技應用與服務. 2013年03月21日 擷取自 http://investtaiwan.nat.gov.tw/doc/itech/2012/2011_2_5_3.pdf
    130. 經濟部商業司. (2007). 中華民國電子商務年鑑. 中華民國(台灣)台北市：經濟部.
    131. 葉啟弘. (2011). 科技-組織-環境因素、資訊科技能力與資訊科技策略實施關聯之研究. 國立台灣科技大學資訊管理研究所.
    132. 廖奕雯. (2010). 以智慧資本架構探討公司資訊科技投資策略對組織經營績效的影響. 國立中山大學資訊管理學系研究所博士論文.
    133. 榮泰生. (2007). Amos 與研究方法. 台北市: 五南出版社.
    134. 蔡琬瑛. (2004). 台灣地區社會指標建構之研究. 國立中山大學公共事務管理研究所碩士論文.
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    國立政治大學
    資訊管理研究所
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