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研究生: 郭仁宗
Ren-Zong Kuo
論文名稱: 影響知識管理系統使用意願因素之探討
Exploring the factors affecting the intention to use knowledge management system
指導教授: 李國光
Gwo-Guang Lee
口試委員: 陳鴻基
Houn-Gee Chen
余坤東
Kung-Don Ye
林娟娟
Judy Chuan-Chuan Lin
周子銓
Tzu-Chuan Chou
學位類別: 博士
Doctor
系所名稱: 管理學院 - 資訊管理系
Department of Information Management
論文出版年: 2011
畢業學年度: 99
語文別: 中文
論文頁數: 82
中文關鍵詞: 知識管理系統科技接受模式資訊品質任務科技配適度工作相容性
外文關鍵詞: Knowledge Management System, Technology Acceptance Model, Task-Technology Fit, Compatibility, Information Quality
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  • 伴隨著「知識」在組織中的重要性越來越高,企業紛紛尋求適當的資訊科技來輔助知識管理活動的推行,冀望藉由知識管理系統的協助來有效累積與應用組織內外部的知識,進而強化自身的競爭優勢。然而,知識管理系統要能發揮它的效益所在,最主要在於使用者要願意使用它,因此,本研究以科技接受度模式為研究推論的基礎,從資訊品質、任務科技配適度與工作相容性等角度,探討三者對系統有用性、易用性與使用意願等因素的影響,進而瞭解如何有效強化知識工作者對知識管理系統使用意願的相關管理措施與建議,以便協助組織成功推展知識管理系統,提高企業整體競爭力。
    研究結果發現,對於知識管理系統而言,若要讓知識工作者認為系統要對他們在工作上有所助益,僅僅只是考量系統的資訊品質是不夠的,還必須滿足使用者工作任務的知識需求特性。當系統資訊品質越高、且系統能夠提供所需的知識內容協助使用者完成工作任務,才能提高知識工作者對系統有用性的認知;相反的,如果系統無法滿足使用者工作任務上的知識需求時,即便系統的資訊品質高,系統有用性的認知程度也不會高。此外,系統必須要能夠符合知識工作者的知識工作方式與習慣,並提供適當的知識工具來協助他們工作的進行,而具備這些特性的知識管理系統才能真正滿足使用者他們在知識管理活動中的需要。


    Given the rising importance of considering knowledge as a key organizational asset, how to manage and leverage these assets appropriately is critically important. To enable organizations to implement and utilize the benefits to be gained from knowledge management activities, there is today an increasing demand for organizations to implement the knowledge management system (KMS) at an accelerating pace. However, to effectively exert the benefits of knowledge management system, users have to be willing to use it first. In order to understand how increase a knowledge worker’s intention to use a KMS, this study applies Technology Acceptance Mode as its theoretical framework to exploring the effects of external variables, i.e., information quality, task-technology fit, and compatibility.
    According to the results of this research, to enhance a knowledge worker’s perception of usefulness of a KMS, it should not only consider the information quality, but also consider the meet between the system and the knowledge requirements of his/her tasks. That is, if the fit between user tasks and KMS is high, the effect of information quality on user perception of usefulness will be more significant. Oppositely, even though information provided by a KMS is highly qualified, a knowledge worker will not perceive directly the KMS is usefulness if the system cannot fulfill the knowledge requirements of his/her tasks. Furthermore, a KMS should be compatible with user knowledge work style and habit, and provide appropriate knowledge tools to assist user work. A well-built KMS, which possesses these characteristics, can then be really tailored to user knowledge management activities.

    中文摘要 II 英文摘要 III 誌謝 IV 第一章 緒論 1 1.1 研究動機與目的 1 1.2 論文架構 4 第二章 文獻探討 6 2.1 知識的特性 6 2.2 知識管理系統 11 2.3 科技接受相關理論 20 2.3.1 科技接受模式理論 20 2.3.2 創新擴散理論 23 2.3.3 任務科技配適理論 26 2.5 結語 35 第三章 研究方法 36 3.1 研究變數操作性定義與問卷設計 36 3.1.1 認知有用性、認知易用性與使用意願 36 3.1.2 資訊品質 38 3.1.3 任務科技配適度 39 3.1.4 工作相容性 40 3.2 研究假說 42 3.2.1 認知有用性、認知易用性、工作相容性與使用意願之間的 假說 42 3.2.2 資訊品質與認知有用性之間的假說 43 3.2.3 任務科技配適度、資訊品質、工作相容性、認知有用性與 認知易用性之間的假說 44 3.3 研究樣本與資料分析方法 46 3.3.1 研究樣本 46 3.3.2 資料分析方法 46 第四章 實證結果與分析 48 4.1 樣本特性與資料分析 48 4.2 測量模式分析 51 4.3 結構模式分析 55 4.4 研究結果與討論 59 第五章 結論與建議 63 5.1 研究結果與結論 63 5.2 研究結果之管理意涵 65 5.3 研究限制 67 參考文獻 68 附錄一 問卷 79

    1.Abdullah, R., Sahibudin, S., Alias, R.A., & Selamat, M.H., (2005). Applying knowledge management system with agent technology to support decision making in collaborative learning environment. Journal of American Academy of Business, Cambridge, 7 (1), 181-188.
    2.Adams, D.A., Nelson, R.R. & Todd, P.A., (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Quarterly, 16 (2), 227-247
    3.Aggelidis, V. P., & Chatzoglou, P. D. (2009). Using a modified technology acceptance model in hospitals. International Journal of Medical Informatics, 78(2), 115-126.
    4.Agarwal, R. & Prasad, J., (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9 (2), 204-215
    5.Ahn, T., Ryu, S. & Han, I., (2007). The impact of web quality and playfulness on user acceptance of online retailing. Information & Management, 44 (3), 263-275
    6.Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage Publications.
    7.Alavi, M. & Leidner, D.E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25 (1), 107‐136.
    8.Bailey, J. E. & Pearson, S. W. (1983). Development of a Tool for Measuring and Analyzing Computer User Satisfaction. Management Science, 29(5), 530-545.
    9.Baloh, P., (2007). The role of fit in knowledge management systems: Tentative propositions of the kms design. Journal of Organizational and End User Computing, 19 (4), 22-41
    10.Bandura, A. (1982). Self-Efficacy Mechanism in Human Agency, Amer. Psychologist, 37, 122-147.
    11.Beckman, T. J., (1997) A Methodology for Knowledge Management, The International Associationof Science and Technology for Development (IASTED) AI and Soft Computing Conference, Banff, Canada.
    12.Beckman, T. J., (1999). The Current State of Knowledge Management, in J. Leibowitz (ed.), Knowledge Management Handbook, CRC Press, Florida.
    13.Benbasat, i., Dexter, A.S., and Todd, P. (1986). An Experimental Program Investigating Color-Enhanced and Graphical information Presentation: An Integration of the Findings. Communications of the ACM , 29(11), 1094-1105.
    14.Benbya, H. & Belbaly, N.A., (2005). Mechanisms for knowledge management systems effectiveness: An exploratory analysis. Knowledge and Process Management, 12 (3), 203
    15.Beverly, K.K., Diane, M.S. & Richard, Y.W., (2002). Information quality benchmarks. Association for Computing Machinery. Communications of the ACM, 45 (4), 184-192
    16.Bharati, P. & Chaudhury, A., (2004). An empirical investigation of decision-making satisfaction in web-based decision support systems. Decision Support Systems, 37 (2), 187-197
    17.Bolisani, E. and Scarso, E., (1999). Information technology management: A knowledge-based perspective. Technovation, 19 (4), 209-217.
    18.Brown, J.P., Anne, P.M., and Elizabeth, B., (2005). Evaluation of knowledge management systems: Insights from the study of a technical support knowledge base. Knowledge Management Research & Practice, 3 (2), 49-59.
    19.Bueno, S., & Salmeron, J. L. (2008). TAM-based success modeling in ERP. Interacting with Computers, 20(6), 515-523.
    20.Butler, T., Heavin, C., and O'donovan, F., (2007). A theoretical model and framework for understanding knowledge management system implementation. Journal of Organizational and End User Computing, 19 (4), 1-21.
    21.Butler, T., Feller, J., Pope, A., Emerson, B., and Murphy, C., (2008). Designing a core IT artefact for knowledge management systems using participatory action research in a government and a non-government organisation. The Journal of Strategic Information Systems, 17 (4), 249-267.
    22.Chang, H.H., (2008). Intelligent agent's technology characteristics applied to online auctions' task: A combined model of ttf and tam. Technovation, 28 (9), 564-577
    23.Chang, H.H., 2010. Task-technology fit and user acceptance of online auction. International Journal of Human-Computer Studies, 68 (1-2), 69-89
    24.Chen, L.-D., Gillenson, M.L. & Sherrell, D.L., (2002). Enticing online consumers: An extended technology acceptance perspective. Information & Management, 39 (8), 705-719
    25.Chin, W. W., Marcolin, B.L., and Newsted, P.R., (2003). A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and an electronic mail emotion/adoption study. Information Systems Research, 14 (2), 189–217.
    26.Chua, A., (2004). Knowledge management system architecture: A bridge between km consultants and technologists. International Journal of Information Management, 24 (1), 87-98.
    27.Cyr, D., Head, M., and Ivanov, A., (2006). Design aesthetics leading to m-loyalty in mobile commerce. Information & Management, 43 (8), 950-963.
    28.D'ambra, J. & Wilson, C.S., (2004). Explaining perceived performance of the world wide web: Uncertainty and the task-technology fit model. Internet Research, 14 (4), 294
    29.Damodaran, L. and Olphert, W., (2000). Barriers and facilitators to the use of knowledge management systems. Behaviour & Information Technology, 19 (6), 405 - 413.
    30.Davenport, T.H., and Prusak, L., (1998). Working Knowledge, Boston: Harvard Business School Press.
    31.Davis, F. D. (1989). Perceived Usefulness, Perceived Ease Of Use, And User Accep. Minformation system Quarterly, 13(3), 319-340.
    32.Davis, F.D., (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38 (3), 475-487
    33.Davis, F. D., Bagozzi, R. P., and Warshaw, P. R., (1989). User Acceptance Of Computer Technology: A Comparison Of Two. Management Science, 35(8), 982‐1003.
    34.DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60-95.
    35.DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9-30.
    36.Dickson. G.W.. DeSanctis. G.. and McBride, D.J., (1986). Understanding the Effectiveness of Computer Graphics for Decision Support: A Cumulative Experimental Approach," Communications of the ACM 29 (1), pp. 40-47.
    37.Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task-technology fit constructs. Information & Management, 36(1), 9-21.
    38.Drucker, P.F. (1993). Post‐capitalist society. New York: Butterworth Heineman
    39.Feng, K., Chen, E. T., & Liou, W. (2004). Implementation of knowledge management systems and firm performance: an empirical investigation. The Journal of Computer Information Systems, 45(2), 92‐104.
    40.Fishbein, M. & Ajzen, I., (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, MA.
    41.Fornell, C., and Bookstein, F. L., (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440–452.
    42.Goodhue, D. L. and R. L. Thompson (1995). "Task‐technology fit and individual performance." MIS Quarterly 19(2): 213‐236.
    43.Gottschalk, P., (2006). Stages of knowledge management systems in police investigations. Knowledge-Based Systems, 19 (6), 381-387.
    44.Gray, P.H., (2000). The effects of knowledge management systems on emergent teams: Towards a research model. The Journal of Strategic Information Systems, 9 (2-3), 175-191
    45.Gumussoy, C.A. & Calisir, F., (2009). Understanding factors affecting e-reverse auction use: An integrative approach. Computers in Human Behavior, 25 (4), 975-988
    46.Hahn, J. & Wang, T., (2009). Knowledge management systems and organizational knowledge processing challenges: A field experiment. Decision Support Systems, 47 (4), 332-342
    47.Hair, J. E., Jr., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis with reading (5th ed.). Prentice-Hall, Upper Saddle River, NJ.
    48.Hall, D.J. and Paradice, D., (2005). Philosophical foundations for a learning-oriented knowledge management system for decision support. Decision Support Systems, 39 (3), 445-461.
    49.Halawi, L.A., Mccarthy, R.V. & Aronson, J.E., (2008). An empirical investigation of knowledge-management systems' succes. The Journal of Computer Information, 48 (2), p.121-135.
    50.Hamner, M., & Qazi, R.-u.-R. (2009). Expanding the Technology Acceptance Model to examine Personal Computing Technology utilization in government agencies in developing countries. Government Information Quarterly, 26(1), 128-136.
    51.Hendriks, P. (1999), Why Share Knowledge? The Influence of ICT on the Motivation for Knowledge Sharing, Knowledge and Process Management, 6(2), 91-100.
    52.Hernandez, B., Jimenez, J., & Martin, M. J. (2008). Extending the technology acceptance model to include the IT decision-maker: A study of business management software. Technovation, 28(3), 112-121.
    53.Hjelmervik, O.R. and Wang, K., (2007). ICT-supported knowledge representation for development of routines in industry. Journal of Intelligent Manufacturing, 18 (4), 479-485.
    54.Holsapple, C. W., (2003), “Knowledge and Its Attributes,” in C. W. Holsapple (ed.), Handbook on Knowledge Management 1, Springer-Verlag, New York, pp.165-188.
    55.Hung, Y.-C., Huang, S.-M., Lin, Q.-P. & Tsai, M.L., (2005). Critical factors in adopting a knowledge management system for the pharmaceutical industry. Industrial Management + Data Systems, 105 (1/2), 164
    56.Hung, S.-Y., Huang, A.H., Yen, D.C. & Chang, C.-M., (2007). Comparing the task effectiveness of instant messaging and electronic mail for geographically dispersed teams in Taiwan. Computer Standards & Interfaces, 29 (6), 626-634
    57.Hsu, C.-L., Lu, H.-P. & Hsu, H.-H., (2007). Adoption of the mobile internet: An empirical study of multimedia message service (MMS). Omega, 35 (6), 715-726
    58.Hwang, H.-G., Chang, I. C., Chen, F.-J., and Wu, S.-Y., (2008). Investigation of the application of KMS for diseases classifications: A study in a Taiwanese hospital. Expert Systems with Applications, 34(1), 725-733.
    59.Jennex, M.E. & Olfman, L., (2004). Assessing knowledge management success/effectiveness models. Proceedings of the 37th Annual Hawaii International Conference on System Sciences. IEEE Computer Society.
    60.Jung, Y., Perez-Mira, B., & Wiley-Patton, S. (2009). Consumer adoption of mobile TV: Examining psychological flow and media content. Computers in Human Behavior, 25(1), 123-129.
    61.Kamla, A.A.‐B., & Lorne, O. (2005). An investigation of the determinants of knowledge management systems success in Omani organizations. Journal of Global Information Technology Management, 8(3), 8‐27.
    62.Karahanna, E., Agarwal, R. & Angst, C.M., (2006). Reconceptualizing compatibility beliefs in technology acceptance research. MIS Quarterly, 30 (4), 781-804
    63.Kim, H.-B., Kim, T. & Shin, S.W., 2009. Modeling roles of subjective norms and etrust in customers' acceptance of airline b2c ecommerce websites. Tourism Management, 30 (2), 266-277
    64.Kim, S.-K. & Trimi, S., (2007). It for km in the management consulting industry. Journal of Knowledge Management, 11 (3), 145-155
    65.Kim, G., Shin, B. & Grover, V., (2010). Investigating two contradictory views of formative measurement in information systems research. MIS Quarterly, 34 (2), 345-365
    66.Klein, B. D. (2001). User perceptions of data quality: Internet and traditional text sources. The Journal of Computer Information Systems; 41 (4), 9–18.
    67.Klopping, I. M., & McKinney, E. (2004). Extending the Technology Acceptance Model and the Task-Technology Fit Model to Consumer E-Commerce. Information Technology, Learning, and Performance Journal, 22(1), 35-48.
    68.Knight, S.-a., & Burn, J. (2005). Developing a framework for assessing information quality on the world wide web. Information Science Journal, 8, 149-172. retrieved from http://inform.nu/Articles/Vol8/v8p159-172Knig.pdf
    69.Kulkarni, U.R., Ravindran, S. & Freeze, R., (2006). A knowledge management success model: Theoretical development and empirical validation. Journal of Management Information Systems, 23 (3), 309-347
    70.Kuo, Y.-F., & Yen, S.-N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25(1), 103-110.
    71.Kwan, M.M., and Balasubramanian, P., (2003). Knowledgescope: Managing knowledge in context. Decision Support Systems, 35 (4), 467-486.
    72.Lai, J.-Y. & Yang, C.-C., (2009). Effects of employees' perceived dependability on success of enterprise applications in e-business. Industrial Marketing Management, 38 (3), 263-274
    73.Lee, S. & Kim, K.-J., (2007). Factors affecting the implementation success of Internet-based information systems. Computers in Human Behavior, 23(4), 1853-1880.
    74.Lee, Y.W., Strong, D.M., Kahn, B.K. & Wang, R.Y., (2002). Aimq: A methodology for information quality assessment. Information & Management, 40 (2), 133-146
    75.Lepper, M. R., (1985). Microcomputers in Education: Motivational and Social Issues, Amer. Psychologist, 40, 1-18
    76.Liao, H.-L. & Lu, H.-P., (2008). The role of experience and innovation characteristics in the adoption and continued use of e-learning websites. Computers & Education, 51 (4), 1405-1416
    77.Lin, H.-F. (2007). The role of online and offline features in sustaining virtual communities: an empirical study. Internet Research, 17(2), 119-138.
    78.Lin, H.-F., & Lee, G.-G. (2005). Impact of organizational learning and knowledge management factors on e-business adoption. Management Decision, 43(2), 171-188.
    79.Lin, C.-C. & Lu, H., (2000). Towards an understanding of the behavioural intention to use a web site. International Journal of Information Management, 20 (3), 197-208
    80.Liu, P.-L. and Tsai, C.-H., (2007). Effect of knowledge management systems on operating performance: An empirical study of hi-tech companies using the balanced scorecard approach. International Journal of Management, 24 (4), 734-743.
    81.Lohmöller, J.B., (1989). Latent variable path modeling with partial least squares. Heidelberg: Physica-Verlag.
    82.Lu, Y., Deng, Z. & Wang, B., (2007). An empirical study on chinese enterprises' adoption of mobile servicesed. Proceedings of the IEEE International Conference on Wireless Communications, Networking and Mobile Computing; Sept, pp. 3629-3632
    83.Machlup, F., (1980). Knowledge: Its Creation, Distribution, and Economic Significance, Princeton University Press, New Jersey
    84.Maglitta, J. "Smarten Up!," Computerworld, 29(23), June 5 1995, pp. 84-86.
    85.Mao, E., & Palvia, P. (2008). Exploring the effects of direct experience on IT use: An organizational field study. Information & Management, 45(4), 249-256.
    86.Markus, M.L., (2001). Toward a theory of knowledge reuse: Types of knowledge reuse situations and factors in reuse success. Journal of Management Information Systems, 18 (1), 57-93
    87.Mccall, H., Arnold, V., and Sutton, S., 2008. Use of knowledge management systems and the impact on the acquisition of explicit knowledge. Journal of Information Systems, 22 (2), 77-101.
    88.Mcdermott, R., 1999. Why information technology inspired but cannot deliver knowledge management. California Management Review, 41 (4), 103-117.
    89.Mei, C., Qingyu, Z. & John, S., (2005). B2c e-commerce web site quality: An empirical examination. Industrial Management + Data Systems, 105 (5/6), 645
    90.Meso, P. and Smith, R., (2000). A Resource-based View of Organizational Knowledge Management Systems, Journal of Knowledge Management, 4(3), pp. 224-234.
    91.Michnik, J. & Lo, M.-C., (2009). The assessment of the information quality with the aid of multiple criteria analysis. European Journal of Operational Research, 195 (3), 850-856
    92.Moore, G.C. & Benbasat, I., (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2 (3), 192-222
    93.Negash, S., Ryan, T. & Igbaria, M., (2003). Quality and effectiveness in web-based customer support systems. Information & Management, 40 (8), 757-768
    94.Nelson, R.R., Peter, A.T. & Barbara, H.W., (2005). Antecedents of information and system quality: An empirical examination within the context of data warehousing. Journal of Management Information Systems, 21 (4), 199
    95.Nevo, D., & Chan, Y. E. (2007a). A Delphi study of knowledge management systems: Scope and requirements. Information & Management, 44(6), 583‐597.
    96.Nevo, D. & Chan, Y.E., (2007b). A temporal approach to expectations and desires from knowledge management systems. Decision Support Systems, 44 (1), 298-312
    97.Newell, A., (1982) The Knowledge Level,” Artifical Intelligence, 18 (1), pp. 87-127.
    98.Nonaka, I. & Takeuchi, H., (1995). The Knowledge Creating Company: How Japanes Companies Create the Dynamics of Innovation, New York: Oxford University Press.
    99.Ong, C.-S. & Lai, J.-Y., (2007). Measuring user satisfaction with knowledge management systems: Scale development, purification, and initial test. Computers in Human Behavior, 23 (3), 1329-1346
    100.Park, Y. & Kim, S., 2006. Knowledge management system for fourth generation R&D: Knowvation. Technovation, 26 (5-6), 595-602
    101.Plouffe, C., R., Hullan, D., S. & Vandenbosch, M., (2001). Research report: Richness versus parsimony in modeling technology adoption decisions - understanding merchant adoption of a smart card-based payment system. Information Systems Research, 12 (2), 208-222
    102.Remus, U. & Lehner, F., (2000). The role of process-oriented enterprise modeling in designing process-oriented knowledge management systems. In Proceedings of the AAAI Symposium on Bringing Knowledge to Business Processes. Stanford, CA, USA.
    103.Pentiand. B.T., (1989). Use and Productivity in Personal Computers: An Empirical Test. Proceedings of the Tenth Intemational Conference on Information Systems, Boston, MA. December. pp. 211-222.
    104.Pirró, G., Mastroianni, C., and Talia, D., (2010). A framework for distributed knowledge management: Design and implementation. Future Generation Computer Systems, 26 (1), 38-49.
    105.Poston, R. S. and Speier, C. (2005). Effective use of knowledge management systems: A process model of content ratings and credibility indicators. MIS Quarterly, 29(2), 221-244.
    106.Quaddus, M. and J. Xu (2005). "Adoption and diffusion of knowledge management systems: field studies of factors and variables." Knowledge‐Based Systems 18(2‐3): 107‐115.
    107.Quinn, J.B., Anderson, P., and Finkelstein, S. (1996). Leverging intellect: Academy of Management Executives, 10(3), 7‐27.
    108.Remus, U. & Lehner, F., (2000). The role of process-oriented enterprise modeling in designing process-oriented knowledge management systems. In Proceedings of the AAAI Symposium on Bringing Knowledge to Business Processes. Stanford, CA, USA.
    109.Richardson, S.M., Courtney, J.F., and Haynes, J.D., (2006). Theoretical principles for knowledge management system design: Application to pediatric bipolar disorder. Decision Support Systems, 42 (3), 1321-1337.
    110.Ringle, C.M., Wende, S., and Will, A., (2005). SmartPLS 2.0 beta. University of Hamburg, Germany.
    111.Rinkus, S., Walji, M., Johnson-Throop, K.A., Malin, J.T., Turley, J.P., Smith, J.W. & Zhang, J., (2005). Human-centered design of a distributed knowledge management system. Journal of Biomedical Informatics, 38 (1), 4-17
    112.Rogers, E. M., (1995). The diffusion of innovation (4th ed.). Free Press: New York.
    113.Ryu, M.-H., Kim, S. & Lee, E., (2009). Understanding the factors affecting online elderly user's participation in video ucc services. Computers in Human Behavior, 25 (3), 619-632
    114.Van Rijnsoever, F.J., Van Hameren, D., Walraven, P.F.G. & Van Dijk, J.P., (2009). Interdependent technology attributes and the diffusion of consumer electronics. Telematics and Informatics, 26 (4), 410-420
    115.Saeed, K.A. & Abdinnour-Helm, S., (2008). Examining the effects of information system characteristics and perceived usefulness on post adoption usage of information systems. Information & Management, 45 (6), 376-386
    116.Sher, P.J. and Lee, V.C., (2004). Information technology as a facilitator for enhancing dynamic capabilities through knowledge management. Information & Management, 41 (8), 933-945.
    117.Shin, M. (2004). A framework for evaluating economics of knowledge management systems. Information & Management, 42(1), 179-196.
    118.Shin, D.-H. (2007). User acceptance of mobile Internet: Implication for convergence technologies. Interacting with Computers, 19(4): 472-483.
    119.Shin, D. H. (2008). Understanding purchasing behaviors in a virtual economy: Consumer behavior involving virtual currency in Web 2.0 communities. Interacting with Computers, 20(4-5), 433-446.
    120.Solow, R.M. (1997). Learning from learning by doing: Lessons for economic growth. Stanford, CA: Standford University Press.
    121.Spiegler, I., (2000). Knowledge Management: A New Idea or A Recycled Concept? Communications of the AIS, 3(14), pp. 1-24.
    122.Stewart, T.A. (1997). Intellectual capital: The new welth of organizations. London: Doubleday.
    123.Strong, D.M., Dishaw, M.T. & Bandy, D.B., (2006). Extending task technology fit with computer self-efficacy. Database for Advances in Information Systems, 37 (2/3), 96-107
    124.Sveiby, K.E. (1997). The new organizational wealth: Managing & measuring knowledge‐based assets. San Francisco: Berrett‐Koehler Publisher.
    125.Tenenhaus, M., Vinzi, V.E., Chatelin, Y.-M. and Lauro, C., (2005). PLS path modeling. Computational Statistics & Data Analysis, 48 (1), 159-205.
    126.Thurow, L.C. (1997). The future of capitalism. Nicholas: Breeley publishing.
    127.Tiwana, A., (2002). The Knowledge Management Toolkit: Orchestrating IT, Strategy, and Knowledge Platforms, Prentice Hall, New Jersey.
    128.Tiwana, A. & Ramesh, B., (2001). A design knowledge management system to support collaborative information product evolution. Decision Support Systems, 31 (2), 241-262
    129.Tornatzky, L.G. & Klein, K.J., (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on engineering management, 29 (1), 28-45.
    130.Tseng, S.-M., (2008). The effects of information technology on knowledge management systems. Expert Systems with Applications, 35 (1-2), 150-160
    131.Tung, F.-C., Chang, S.-C. & Chou, C.-M., (2008). An extension of trust and tam model with idt in the adoption of the electronic logistics information system in his in the medical industry. International Journal of Medical Informatics, 77 (5), 324-335
    132.Van Lohuizen, C. W. W., (1986) Knowledge Management and Policymaking, Knowledge: Creating, Diffusion, Utilization, 18 (1), pp. 12-38.
    133.Venkatesh, V. & Davis, F.D., (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46 (2), 186-204
    134.Vessey. I. (1991). Cognitive Fit: A Theory-Based Analysis of the Graphs Vs. Tables Literature, Decision Sciences, 22 (2), pp. 219-240.
    135.Vijayasarathy, L.R., (2004). Predicting consumer intentions to use on-line shopping: The case for an augmented technology acceptance model. Information & Management, 41 (6), 747-762
    136.Walsham, G. (2001). Knowledge Management: The Benefits and Limitations of Computer Systems, European Management Journal, 19(6) , pp. 599-608.
    137.Wasko, M.M. and Faraj, S., 2005. Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, 29 (1), 35-57.
    138.Wiig, K. M., (1993). Knowledge Management Foundation, Schema Press, Texas.
    139.Wu, J.-H. and Wang, Y.-M., (2006). Measuring kms success: A respecification of the delone and mclean's model. Information & Management, 43 (6), 728-739.
    140.Wu, J.-H., Chen, Y.-C. & Lin, L.-M., (2007a). Empirical evaluation of the revised end user computing acceptance model. Computers in Human Behavior, 23 (1), 162-174
    141.Wu, J.H., Wang, S.C., and Lin, L.M., (2007b). Mobile computing acceptance factors in the healthcare industry: A structural equation model. International Journal of Medical Informatics, 76(1), 66-77.
    142.Yen, D.C., Wu, C.-S., Cheng, F.-F. & Huang, Y.-W., (2010). Determinants of users' intention to adopt wireless technology: An empirical study by integrating ttf with tam. Computers in Human Behavior, 26 (5), 906-915
    143.林東清 (2008),知識管理,台北:智勝出版社。
    144.陳永隆、莊宜昌(2005),知識價值鏈(更新版),台北:中國生產力中心。
    145.張紹勳 (2001),研究方法(修訂版),台北:滄海出版社。

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