政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/54288
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113822/144841 (79%)
Visitors : 51789327      Online Users : 608
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/54288


    Title: 會展廠商之創新技術持續使用意願研究
    Research on the continuance intention of companies attending exhibitions to use innovative technology
    Authors: 陳奕君
    Contributors: 洪叔民
    陳奕君
    Keywords: 持續使用意願
    資訊品質
    系統品質
    使用者滿意度
    資訊系統成功模型
    個人創新特質
    continuance intention
    information quality
    system quality
    user satisfaction
    IS success model
    personal innovativeness
    Date: 2011
    Issue Date: 2012-10-30 10:39:13 (UTC+8)
    Abstract: 本研究以針對B2B資訊系統設計之資訊系統成功模型(IS Success Model)作為假設架構，探討使用者滿意度與持續使用意願間的關係，並加入個人創新特質做為影響持續使用意願之假設，在研究架構中，分別探討資訊品質與系統品質與使用者滿意度的關係，以及使用者滿意度與個人創新特質分別對持續使用意願的關係。
    本研究透過問卷法抽樣進行資料蒐集，選擇2010台北國際電子產業科技展之參展廠商作為研究對象，在回顧大量文獻與研究架構，並且排除無效問項後，進行問卷調查與分析，總共回收117份有效問卷，以PLS(Partial Least Squares)法進行分析後，得到以下結論：
    使用者對於資訊系統的滿意度與系統品質及資訊品質呈現正相關，當資訊品質越高，也就是資訊系統產出的資訊之品質越好時；使用者滿意度會越高；當系統品質越高時，也就是資訊系統本身的特性越好時，使用者滿意度會越高。本研究更進一步發現，資訊系統持續使用意願受到使用者滿意度及個人創新特質影響，使用者滿意度與持續使用意願有正相關，滿意度越高時，持續使用的意願會越高；個人創新特質與持續使用意願也呈現正相關，當使用者之個人創新特質越強烈時，持續使用資訊系統的意願會越高。
    This research, based on the IS Success Model proposed by DeLone and McLean(1992), the B2B information system regarding the relationship between user satisfaction and continuance usage. Personal innovativeness was added to test its relationship with continuance usage. Within the hypothesized framework, the impacts of latent variables in system quality and information quality on user satisfaction are examined and tested, respectively.
    The research is conducted through sampling by a survey from companies attending the 2010 Taipei International Electronics Show. Of 121 samples collected, 117 are effective. By analyzing the samples with the PLS (Partial Least Squares) method, the research concluded the following:
    User satisfaction is positively influenced by system quality and information quality, which represents the characteristics of the information system itself and the form of information produced by the information system respectively. User satisfaction, together with personal innovativeness of the users, positively influence the continuance intentions to use the information systems.
    Reference: 中文文獻：
    1. 溫世仁文教基金會網站。http://www.saylingwen.org.tw/dispPageBox/SWFHP.aspx?ddsPageID=ROOTSWFHOME
    2. 潘瑛如 (2010)。部分最小平方路徑法在教育研究上的應用。教育人力與專業發展雙月刊。27 (5)，99-100。

    英文文獻：
    1. Agarwal, R., and Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.
    2. Agarwal, R., and Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694.
    3. Alloway, R. M. (1980). Defining success for data processing: A practical approach to strategic planning for the DP department. CISR Working Paper No. 52, Center for Information Systems Research, Massachusetts Institute of Technology.
    4. Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.
    5. Anderson, T. W., and Rubin, H. (1956). Statistical inference in factor analysis. In J. Neyman (Ed.). Proceedings of the third Berkeley symposium for mathematical statistics and probability, 5, 111-150. Berkeley: University of California Press.
    6. Ahituv, N. (1980). A systematic approach toward assessing the value of an information system. MIS Quarterly, 4(4), 61-75
    7. Ajzen, I., and Fishbein, M. (1973). Attitudinal and normative variables as predictors of specific behavior. Journal of Personality and Social Psychology, 27(1), 41-57.
    8. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
    9. Bailey, J. E. and Pearson, S. W. (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29(5), 530-545.
    10. Baron, R.M. , and Kenny, D.A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.
    11. Barti, H. and Huff, S. (1985). Change, attitude to change, and decision support system success. Information & Management, 9(5), 261-268
    12. Belardo, S., Karwan, K. R., and Wallace, W. A. (1982). DSS component design through field experimentation: An application to emergency management. Proceedings of the Third International Conference on Information Systems, 93-108
    13. Bernroider, E. N. (2008). IT governance for enterprise resource planning supported by the DeLone–McLean model of information systems success. Information & Management, 45(5), 257-269.
    14. Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model, MIS Quarterly, 25(3), 351-370.
    15. Blaylock, B. K. and Rees, L. P. (1984). Cognitive style and the usefulness of information. Decision Sciences, 15(1), 74-91.
    16. Bock, G., Zmud, R., Kim, Y., and Lee, J. (2005). Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social-psychological forces, and organizational climate. MIS Quarterly, 29(1), 87-111
    17. Burton-Jones, A. and Straub, Jr. D.W. (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228-246.
    18. Cardozo, R. (1965). An experimental study of customer effort, expectation, and satisfaction. Journal of Marketing Research, 2(8), 244-249.
    19. Chin, W. W. (1998). The partial least squares approach to structural equation modeling in modern methods for business research. G. A. Marcoulides (ed.), Lawrence Eribaum Associates, Mahwah, NJ, 295-336.
    20. Chiu, C. M., Chiu, C. S., and Chang, H. C. (2007). Examining the integrated influence of fairness and quality on learners` satisfaction and web-based learning continuance intention. Information Systems Journal, 17, 271-287.
    21. Choi, J. N. (2004). Individual and contextual dynamics of innovation-use behavior in organizations. Human Performance, 17(4), 397-414.
    22. Counihan, A., Finnegan, P., and Sammon, D. (2002). Towards a framework for evaluating investments in data warehousing. Information Systems Journal, 12(4), 321-338. Wiley Online Library. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-0036405337&partnerID=40&md5=3c6dce3710881f4c2da509ab5314fcee
    23. Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-341．
    24. DeLone, W. H., and McLean, E. R. (1992). Information system success: The quest for the dependent variable. Information Systems Research , 3(1), 60-95.
    25. DeLone, W. H., and McLean, E. R. (2003). The DeLone and McLean model of information system success: A ten-year update. Journal of Management Information Systems, 19(4), 9-30.
    26. DeSanctis, G., and Gallupe, R. B. (1987). A foundation for the study of group decision support systems. Management Science, 33(5), 589-609
    27. Diamantopoulos, A. (1994). Modeling with LISREL: A guide for the uninitiated. Journal of Marketing Management, 10(1-3), 105-136.
    28. Emery, J. C. (1971). Cost/benefit analysis of information systems. SMIS Workshop Report Number I, The Society for Management Information Systems, Chicago. IL.
    29. 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.
    30. Gallagher, C. A. (1974). Perceptions of the value of a management information system. Academy of Management Journal, 17(1), 46-55
    31. Ginzberg, M. J. (1981). Early diagnosis of MIS implementation failure. Management Science, 27(4), 459-478.
    32. Goodhue, D.L. (1995). Understanding user evaluations of information systems. Management Science, 41(12), 1827-1844.
    33. Hamilton, S. and Chervany, N. L. (1981). Evaluating information system effectiveness - Part I: Comparing evaluation approaches. MIS Quarterly, 5(3), 55-69.
    34. Hofstede, G. (1983). The cultural relativity of organizational practices and theories. Journal of International Business Studies, 14(2), 75-89.
    35. Hong, W., Thong, J.Y. L., Chasalow, L., and Dhillon, G. (2011). Understanding user acceptance of agile information systems: A model and empirical test. Journal of Management Information Systems, 28 (1), 235-272.
    36. Hunton, J. E., and Flowers, L. (1997). Information technology in accounting: Assessing the impact on accountants and organizations. Advances In Accounting Information Systems, 5, 3-34.
    37. Igersheim, R. H. (1976). Managerial response to an information system. AFIPS Conference Proceedings, 45, National Computer Conference, 877-882
    38. Iivari, J. and Koskela, E. (1987). The PIOCO model for information systems design. MIS Quarterly, 11(3), 401-419.
    39. Ives, B., Olson, M. H., and Baroudi, J. J. (1983). The measurement of user information satisfaction. Communications of the ACM, 26(10), 785-793.
    40. Jacoby, J. (1978). Consumer research: A state of the art review. Journal of Marketing, 42(2), 87-96
    41. Jarvenpaa, S. L., Dickson, G. W., and DeSanctis, G. (1985). Methodological issues in experimental I/S research: Experiences and recommendations. MIS Quarterly, 9(2), 141-156
    42. Jarvis, C. B., Mackenzie, S. B., and Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research, 30(2), 199-218.
    43. Khayun, V., Ractham, P., and Firpo, D. (2012). Assessing e-excise success with DeLone and McLean’s model. Journal of Computer Information Systems, 52(3), 31-40.
    44. Kim, H. W., Chan, H. C., and Chan, Y. P. (2007). A balanced thinking-feelings model of information systems continuance. International Journal of Human-Computer Studies, 65(6), 511-525.
    45. King, W. R. and Epstein, B. J. (1983). Assessing information system value. Decision Sciences, 14(1), 34-45.
    46. Kline, R. (2005). Principle and practice of structural equation modeling. New York: The Guilford Press.
    47. Kriebel, C. A. and Raviv, A. (1980). An economics approach to modeling the productivity of computer systems. Management Science, 26(3), 297-311
    48. Larcker, D. F. and Lessig, V. P. (1980). Perceived usefulness of information: A psychometric examination. Decision Sciences, 11(1), 121-134
    49. Lewis, W., Agarwal, R., and Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: An empirical study of knowledge workers. MIS Quarterly, 27(4), 657-678.
    50. Liao, C. C., Chen, J. L., and Yen, D. C. (2007). Theory of planning behavior (TPB) and customer satisfaction in the continued use of e-service: An integrated model. Computers in Human Behavior, 23, 2804-2822.
    51. Limayem, M., Hirt, S. G., and Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705-737.
    52. Locke, E. A. (1976). The nature and causes of job satisfaction. In M. D. Dunnette (Ed.), Handbook of Industrial and Organizational Psychology, 1297-1349. Chicago, IL: Rand McNally.
    53. Lucas. H. C. Jr. (1978). Empirical evidence for a descriptive model of implementation. MIS Quarterly, 2(2), 27-41.
    54. Lucas, H. C. Jr. (1981). An experimental investigation of the use of computer-based graphics in decision-making. Management Science, 27(7), 757-768.
    55. Lucas, J. H. C. Jr., and Spitler, V. K. (1999). Technology use and performance: A field study of broker workstations. Decision Sciences, 30(2), 291- 311
    56. Lyytinen, K. and Yoo, Y. (2002). Issues and challenges in ubiquitous computing. Communications of the ACM, 45(12), 63-65.
    57. Mahmood, M. A., and Medewitz, J. N. (1985). Impact of design methods on decision support system success: An empirical assessment. Information & Management, 9(3), 137-151.
    58. Munro, M. C. and Davis, G. B. (1977). Determining management information needs: A comparison of methods. MIS Quarterly, 1(2), 55-67.
    59. Mason, R. O. (1978). Measuring information output: A communication systems approach. Information& Management, 1(5), 219-234
    60. McKinsey and Company. (1968). Unlocking the computer`s profit potential. McKinsey Quarterly, fall, 17-31.
    61. Millman, Z. and Hartwick, J. (1987). The impact of automated office systems on middle managers and their work. MIS Quarterly. 11(4), 479-491
    62. Murphy, K. E. and Simon, S. J. (2002). Intangible benefits evaluation in ERP projects. Information Systems Journal, 12(4), 301-320
    63. Nunnally, J. C. (1978). Psychometric Theory. McGraw-Hill, New York.
    64. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17, 460-464
    65. Olson, M. H. and Lucas, H. C. Jr. (1982). The impact of office automation on the organization: Some implications for research and practice. Communications of the ACM, 25(11), 838-847
    66. Parveen, F. and Sulaiman, A. (2008). Technology complexity, personal innovativeness and intention to use wireless internet using mobile devices in Malaysia. International Review of Business Research Papers, 4(5), 1-10
    67. Petter, S., and McLean, E. R. (2009). A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level. Information & Management, 46(3), 159-166.
    68. Pirouz, D. M. (2006). Overview of Partial Least Squares. Retrieved May, 15, 2012, from http://ssrn.com/abstract=1631359
    69. Powers, R. F. and Dickson, G. W. (1973). MIS project management: Myths, opinions and reality. California Management Review, 15(3), 147-156
    70. Rogers, E. M. (1995). Diffusion of Innovations, 4th ed., New York: The Free Press.
    71. Sanders, G. L. and Garrity, E. J. (1998). Dimension of information system success. Information Systems Success Measurement, Idea Group Publishing, Harrisburg, PA, edited by E.J. Garrity and G.L. Sanders, 13-45.
    72. Seddon, P.B., and Yip, S. K. (1992). An empirical evaluation of user information satisfaction (UIS) measures for use with general ledger accounting software. Journal of Information Systems, 6(1), 75-92.
    73. Seddon, P. and Kiew, M. Y. (1994). A partial test and development of the DeLone and McLean model of IS success. Paper 9, ICIS 1994 Proceedings. Retrieved May, 15, 2012, from http://aisel.aisnet.org/icis1994/9
    74. Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8(3), 240-253.
    75. Shannon, C. E. and Weaver, W. (1949). The mathematical theory of communication. Illini books, 13. University of Illinois Press. Urbana. IL.
    76. Shang, S. S. C, and Seddon, P. B. (2002). Assessing and managing the benefits of enterprise systems: The business manager’s perspective. Information Systems Journal, 12 (4), 271-299.
    77. Simmel, G. (1990). The philosophy of money, 2nd Ed. London: Routlege.
    78. Soongeun, H., Jeoungkun, K., and Heeseok, L. (2008). Antecedents of use-continuance in information systems: Toward an integrative view. Journal of Computer Information Systems, 48(3), 61-73.
    79. Spearman, C. (1904). General intelligence objectively determined and measured. American Journal of Psychology, 15(2), 201-293.
    80. Swanson. E. B. (1974). Management information systems: Appreciation and involvement. Management Science, 21(2), 178-188.
    81. Tenenhaus, M. (2008). Component-based structural equation modeling. Total Quality Management & Business Excellence, 19(7-8), 871–886.
    82. Teo, T. S. H., Srivastava, S. C., and Jiang, L. (2008). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99-131.
    83. Wang, Y. S. (2008). Assessing e-commerce systems success: A respecification and validation of the DeLone and McLean model of IS success. Information Systems Journal, 18(5), 529-557.
    84. 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.
    85. Wold, H. (1975). Path models with latent variables: The NIPALS approach. Quantitative Sociology: International Perspectives on Mathematical and Statistical Modeling, Blalock, H. M., Aganbegian, A., Borodkin, F. M., Boudon, R., and Cappecchi, V. (eds). Academic Press, New York, 307-357.
    86. Wu, J., and Wang, Y. (2006). Measuring KMS success: A respecification of the DeLone and McLean`s model. Information & Management, 43(6), 728-739.
    87. Yi, M. Y., Fiedler, K. D., and Park, J. S. (2006). Understanding the role of individual innovativeness in the acceptance of IT-based innovations: Comparative analyses of models and measures. Decision Sciences, 37(3), 393-426.
    88. Zmud, R. W. (1978). An empirical investigation of the dimensionality of the concept of information. Decision Sciences, 9(2), 187-195.
    Description: 碩士
    國立政治大學
    企業管理研究所
    99355036
    100
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0099355036
    Data Type: thesis
    Appears in Collections:[Department of Business Administation] Theses

    Files in This Item:

    There are no files associated with this item.



    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback