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題名 創新科技Orbi使用意願性以國際電子產業科技展為例
The willing to use innovative technology, Orbi - Taking international electronics show for example
作者 黃貞瑜
貢獻者 洪叔民
黃貞瑜
關鍵詞 科技接受模型
創新
使用意願
日期 2010
上傳時間 3-Sep-2013 14:41:34 (UTC+8)
摘要 本研究以Davis (1986)的科技接受模型為基底架構，結合Ajzen (1985)的計畫行為理論，並加入Rogers (1983)之創新擴散理論，探討使用者對於「Orbi創新會展智慧服務平台系統」的使用意願以及使用者在使用Orbi時所在意的因素，分別探討系統品質對知覺有用性、資訊品質對知覺有用性、主觀規範對知覺有用性、個人創新特質對知覺易用性、知覺易用性對知覺有用性、知覺有用性對態度、主觀規範對態度、知覺易用性對其態度、態度對其使用意願關係。
　　本研究選擇第36屆國際電子產業科技展(TAITRONICS)做為個案展覽，此為一電子採購展，匯集國內外1,000家廠商展出年度新品，協助買主一次購足電子產業上中下游關鍵產品。在文獻探討以及與專家深度訪談後，進行問卷發展及樣本收集，總共回收118份有效問卷，並以Partial Least Square (PLS)進行分析，得到以下結論：
 系統品質對知覺有用性有顯著正向影響
 資訊品質對知覺有用性有顯著正向影響
 主觀規範對知覺有用性有顯著正向影響
 個人創新特質對知覺易用性有顯著正向影響
 知覺易用性對知覺有用性有顯著正向影響
 知覺有用性對態度有顯著正向影響
 主觀規範對態度有顯著正向影響
 知覺易用性對態度有顯著正向影響
 態度對使用意願有顯著正向影響
 使用意願對實際系統使用有顯著正向影響
　　資料量化後，本文再針對Orbi提出四點建議，提供Orbi作為後續發展參考。
The study structure is based on technology acceptance model (TAM), combined with the theory of planned behavior (TPB) and innovation diffusion theory (IDT). In this research we used TAITRONICS as the target to study the behavioral intention toward “Orbi Service Platform” through a survey on its users. The conceptual construct includes the dimension of system quality, perceived usefulness, information quality, subjective norm, compatibility, perceived ease of use, attitude, and one’s behavioral intention. In addition, we examined above factors’ effect upon each other.
The study chose the 36th International Electronics Show (TAITRONICS) as the target, which brings 1,000 international e-procurement exhibitiors and their new products together, to help buyers to buy anything they need at the same time. After intensive literature reviews and in-depth interviews, the questionnaire is developed and collected at the exhibition, TAITRONICS. A total amount of 118 valid questionnaires samples are analyzed via Partial Least Square (PLS) with the following conclusions:
 System quality has significantly positive effect on perceived usefulness.
 Information quality has significantly positive effect on perceived usefulness.
 Subjective norm has significantly positive effect on perceived usefulness.
 Compatibility has significantly positive effect on perceived ease of use.
 Perceived ease of use has significantly positive effect on perceived usefulness
 Perceived usefulness has significantly positive effect on attitude.
 Subjective norm has significantly positive effect on attitude.
 Perceived ease of use has significantly positive effect on attitude.
 Attitude has significantly positive effect on behavioral intention.
In summary, some management implications and recommendations are proposed, and further research directions are also identified.
參考文獻 英文文獻：
Ajzen, I. & Fishbein, M. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, MA: Addison-Wesley.
Ajzen, I. & Fishbein, M. (1980) Understanding Attitudes and Predicting Social Behavior, Englewood Cliffs, NJ: Prentice-Hall.
Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior, New York: Springer Verlag.
Ajzen, I. (1991). The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50(2), 179－211.
Ajzen, I. (1971). Attitudinal vs. normative messages: An investigation of the differential effects of persuasive communications on behavior, Sociometry, 34(2), 263－280.
Bagozzi, R. P. and Fornell, C. (1982). Theoretical concepts, measurements, and meaning, in Fornell, C. (Ed.), A Second Generation of Multivariate Analysis, 1, Praeger, New York, NY, 24－38.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models, Journal of the Academy of Marketing Science, 16(1), 74－94.
Bandura, A. (1977). Self-efficacy toward a unifying theory of behavioral change, Psychological Review, 84(2), 91－125.
Barclay, D., Higgins, C. A., & Thompson, R. L. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration, Technology Studies, 2(2), 285－309.
Bhatti, T. (2007). Exploring factors influencing the adoption of mobile commerce, Journal of Internet Banking and Commerce, 12(3), 128－141.
Carmines, E. G. & Zeller, R. A. (1979). Reliability and Validity Assessment, Sage, CA: Beverly Hills.
Chesbrough, H. (2005). Toward a science of services, Harvard Business Review, 83, 16－17.
Chen, J.V., Yen, D. C., & Chen, K. (2009). The acceptance and diffusion of the innovative smart phone use: A case study of a delivery service company in logistics, Information & Management, 46(4), 241－248.
Chin, W. W. & Todd, P. A. (1995). On the use, usefulness, and ease of use of structural equation modeling in MIS research: A note of caution, MIS Quarterly, 19(2), 237－246.
Chin, W. W. (1998). Issues and opinion on structural equation modeling, MIS Quarterly, 22(1), VII-XVI.
Chin, W. W. (2001). PLS-Graph User’s Guide, Version 3.0.
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a montecarlo simulation study and an electronic-mail emotion/adoption study, Information Systems Research, 14(2), 189－217.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technologies, MIS Quarterly, 13(3), 319－340.
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.
Davis, F. D., Bagozzi, R., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models, Management Science, 35(8), 982－1003.
Dwyer, L., & Mistilis, N. (1997). Challenges to MICE tourism in the asia-pacific region, Pacific Rim Tourism, 219－230.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18(1), 39－50.
Gefen, D., Straub, D. W., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practives, Communication of the Association for Information Systems, 7(4), 1－79.
Hair, J. F., Anderson R. E., Tatham R.L., & Black W.C. (1998). Multivariate Data Analysis (5th ed.), Upper saddle river, NJ: Prentice Hall.
He, D., Lu,Y., & Zhou, D. (2008). Empirical study of consumers’ purchase intentions in C2C electronic commerce, Tsinghua Science and Technology, 13(3), 287－292.
Hong, S. J., Thong, J. Y. L., Moon, J. Y., & Tam, K. Y. (2008). Understanding the behavior of mobile data services consumers, Information Systems Frontiers, 10(4), 431－445.
Jackson, J. D., Yi, M. Y., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward and integrative view, Information & Management, 43(3), 350－363.
Jung, M. L. (2008). From health to E-health: Understanding citizens’ acceptance of online health care, Doctoral Thesis from Department of Business administration and Social Sciences Division of Industrial Marketing, E-commerce and Logistics.
Jung, Y., Begona, P. M., & Sonja, W. P. (2009). Consumer adoption of mobile TV: Examining psychological flow and media content, Computers in Human Behavior, 25(1), 123－129.
Kim, C., Mirusmonov, M., Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment, Computers in Human Behavior, 26(3), 310－322.
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.
Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model, Information & Management, 40(3), 191－204.
Lusch, R. F., Vargo S. L., & Wessels G. (2008). Toward a conceptual foundation for service science: Contributions from service-dominant logic, IBM Systems Journal 47(1), 5－14.
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.
Ma, W., Andersson, R., & Streith, K. (2005). Examining user acceptance of computer technology: An empirical study of student teachers, Journal of Computer Assisted Learning, 21(6), 387－395.
Ngai, E.W.T., Poon, J.K.L., & Chan, Y.H.C. (2007). Empirical examination of the adoption of WebCT using TAM, Computers & Education, 48(2), 250－267.
Nunnally, J. (Ed.). (1978). Psychometric Theory, New York: Mcgraw-Hill.
Nysveen, H., Pedersen, P. E., & Thorbjornsen, H. (2005). Intentions to use mobile services: Antecedents and cross-service comparisons, Journal of the Academy of Marketing Science, 33(3), 330－346.
Oreilly, T. (2007). What is web 2.0: Design patterns and business models for the next generation of software, Communications & Strategies, 1(1), 17.
Park, Y. & Chen, J. V. (2007). Acceptance and adoption of the innovative use of smartphone, Industrial Management & Data Systems, 107(9), 1349－1365.
Robert, W. (2004). Diffusion of innovation theory for clinical change, MJA, 180(2), 55－57.
Schepers, J., & Wetzels, M. (2006). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects, Information & Management, 44(1), 90－103.
Taylor, S. & Todd, P. (1995). Assessing IT usage: the role of prior experience, MIS Quarterly, 19(4), 561－570.
Taylor, S. & Todd, P. (1995). Understanding information technology usage: A test of competing models, Information Systems Research, 6(2), 144－176.
Venkatesh V. & Davis F. D. (2000). A theoretical extension of the technologiy acceptance model: Four longitudinal field studies, Management Science, 46(2), 186－204.
Venkatesh V. & Davis F. D. (1994). Modeling the determinants of perceived ease of use, ICIS Proceedings, Paper 17.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view, MIS Quarterly, 27(3), 425－478.
Wold, H. (1982). Systems under indirect observation using PLS, a second generation of mutivariate analysis, Praeger, 325－347.
Wu, H. H. (2009). The recent development on service science, management and engineering, Quality Magazine, 45(3), 29－32.
Wu, I. L. & Wu, K. W. (2005). A hybrid technology acceptance approach for exploring E-CRM adoption in organizations, Behaviour & Information Technology, 24(4), 303－316.
Wu, I. L., & Chen, J. L. (2005). An extension of trust and TAM model with TPB in the initial adoption of on-line tax: An empirical study, Int. J. Human-Computer Studies, 62(6), 784–808.

Yu, J., Ha, I., Choi, M., & Rho, J. (2005). Extending the TAM for a t-commerce, Information & Management, 42(7), 965－976.
中文文獻：
台灣國際數據資訊網站 http://www.idc.com.tw/。
行政院全球資訊網 http://www.ey.gov.tw/。
柏雲昌(2010)。會議展覽產業之發展策略。臺北產經第一期。
經濟部國際貿易局網站 http://cweb.trade.gov.tw/。
描述 碩士
國立政治大學
企業管理研究所
98355037
99
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0098355037
資料類型 thesis
dc.contributor.advisor 洪叔民zh_TW
dc.contributor.author (Authors) 黃貞瑜zh_TW
dc.creator (作者) 黃貞瑜zh_TW
dc.date (日期) 2010en_US
dc.date.accessioned 3-Sep-2013 14:41:34 (UTC+8)-
dc.date.available 3-Sep-2013 14:41:34 (UTC+8)-
dc.date.issued (上傳時間) 3-Sep-2013 14:41:34 (UTC+8)-
dc.identifier (Other Identifiers) G0098355037en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/59786-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 企業管理研究所zh_TW
dc.description (描述) 98355037zh_TW
dc.description (描述) 99zh_TW
dc.description.abstract (摘要) 本研究以Davis (1986)的科技接受模型為基底架構，結合Ajzen (1985)的計畫行為理論，並加入Rogers (1983)之創新擴散理論，探討使用者對於「Orbi創新會展智慧服務平台系統」的使用意願以及使用者在使用Orbi時所在意的因素，分別探討系統品質對知覺有用性、資訊品質對知覺有用性、主觀規範對知覺有用性、個人創新特質對知覺易用性、知覺易用性對知覺有用性、知覺有用性對態度、主觀規範對態度、知覺易用性對其態度、態度對其使用意願關係。
　　本研究選擇第36屆國際電子產業科技展(TAITRONICS)做為個案展覽，此為一電子採購展，匯集國內外1,000家廠商展出年度新品，協助買主一次購足電子產業上中下游關鍵產品。在文獻探討以及與專家深度訪談後，進行問卷發展及樣本收集，總共回收118份有效問卷，並以Partial Least Square (PLS)進行分析，得到以下結論：
 系統品質對知覺有用性有顯著正向影響
 資訊品質對知覺有用性有顯著正向影響
 主觀規範對知覺有用性有顯著正向影響
 個人創新特質對知覺易用性有顯著正向影響
 知覺易用性對知覺有用性有顯著正向影響
 知覺有用性對態度有顯著正向影響
 主觀規範對態度有顯著正向影響
 知覺易用性對態度有顯著正向影響
 態度對使用意願有顯著正向影響
 使用意願對實際系統使用有顯著正向影響
　　資料量化後，本文再針對Orbi提出四點建議，提供Orbi作為後續發展參考。		zh_TW
dc.description.abstract (摘要) The study structure is based on technology acceptance model (TAM), combined with the theory of planned behavior (TPB) and innovation diffusion theory (IDT). In this research we used TAITRONICS as the target to study the behavioral intention toward “Orbi Service Platform” through a survey on its users. The conceptual construct includes the dimension of system quality, perceived usefulness, information quality, subjective norm, compatibility, perceived ease of use, attitude, and one’s behavioral intention. In addition, we examined above factors’ effect upon each other.
The study chose the 36th International Electronics Show (TAITRONICS) as the target, which brings 1,000 international e-procurement exhibitiors and their new products together, to help buyers to buy anything they need at the same time. After intensive literature reviews and in-depth interviews, the questionnaire is developed and collected at the exhibition, TAITRONICS. A total amount of 118 valid questionnaires samples are analyzed via Partial Least Square (PLS) with the following conclusions:
 System quality has significantly positive effect on perceived usefulness.
 Information quality has significantly positive effect on perceived usefulness.
 Subjective norm has significantly positive effect on perceived usefulness.
 Compatibility has significantly positive effect on perceived ease of use.
 Perceived ease of use has significantly positive effect on perceived usefulness
 Perceived usefulness has significantly positive effect on attitude.
 Subjective norm has significantly positive effect on attitude.
 Perceived ease of use has significantly positive effect on attitude.
 Attitude has significantly positive effect on behavioral intention.
In summary, some management implications and recommendations are proposed, and further research directions are also identified.		en_US
dc.description.tableofcontents 第一章、緒論 1
1.1 研究背景與動機 1
1.2 研究目的 5
1.3 論文架構 6
1.4 新科技Orbi介紹 7
1.5 研究流程 9
第二章、文獻探討 11
2.1 服務科學 11
2.2 科技接受意願之整合分析 15
2.2.1 理性行為理論 15
2.2.2 計畫行為理論 17
2.2.3 科技接受模型 20
2.3 科技接受行為模型之延伸 26
2.3.1 結合科技接受模型與計畫行為理論 27
2.3.2 創新擴散理論 29
2.4 小結 30
第三章、研究架構與方法 32
3.1 研究架構 32
3.2 研究假說 34
3.3 變數之操作型定義與衡量方式 38
3.4 問卷設計與資料蒐集 40
3.4.1 問卷發展 40
3.4.2 資料蒐集 45
3.4.3 資料分析方法 45
第四章、研究發現 49
4.1 樣本基本資料分析 49
4.2 資料統計分析 53
4.2.1 敘述性統計分析 57
4.2.2 信效度分析 58
4.3 研究模型檢定 63
4.4 研究分析 65
第五章、結論與建議 65
5.1 研究結論 66
5.2 研究貢獻 69
5.3 管理實務意涵 70
5.4 研究限制與未來研究方向 72
參考文獻 74
附錄一 研究問卷(繁體中文版) 81
附錄二 研究問卷(英文版) 85		zh_TW
dc.format.extent 2012874 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0098355037en_US
dc.subject (關鍵詞) 科技接受模型zh_TW
dc.subject (關鍵詞) 創新zh_TW
dc.subject (關鍵詞) 使用意願zh_TW
dc.title (題名) 創新科技Orbi使用意願性以國際電子產業科技展為例zh_TW
dc.title (題名) The willing to use innovative technology, Orbi - Taking international electronics show for exampleen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 英文文獻：
Ajzen, I. & Fishbein, M. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, MA: Addison-Wesley.
Ajzen, I. & Fishbein, M. (1980) Understanding Attitudes and Predicting Social Behavior, Englewood Cliffs, NJ: Prentice-Hall.
Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior, New York: Springer Verlag.
Ajzen, I. (1991). The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50(2), 179－211.
Ajzen, I. (1971). Attitudinal vs. normative messages: An investigation of the differential effects of persuasive communications on behavior, Sociometry, 34(2), 263－280.
Bagozzi, R. P. and Fornell, C. (1982). Theoretical concepts, measurements, and meaning, in Fornell, C. (Ed.), A Second Generation of Multivariate Analysis, 1, Praeger, New York, NY, 24－38.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models, Journal of the Academy of Marketing Science, 16(1), 74－94.
Bandura, A. (1977). Self-efficacy toward a unifying theory of behavioral change, Psychological Review, 84(2), 91－125.
Barclay, D., Higgins, C. A., & Thompson, R. L. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration, Technology Studies, 2(2), 285－309.
Bhatti, T. (2007). Exploring factors influencing the adoption of mobile commerce, Journal of Internet Banking and Commerce, 12(3), 128－141.
Carmines, E. G. & Zeller, R. A. (1979). Reliability and Validity Assessment, Sage, CA: Beverly Hills.
Chesbrough, H. (2005). Toward a science of services, Harvard Business Review, 83, 16－17.
Chen, J.V., Yen, D. C., & Chen, K. (2009). The acceptance and diffusion of the innovative smart phone use: A case study of a delivery service company in logistics, Information & Management, 46(4), 241－248.
Chin, W. W. & Todd, P. A. (1995). On the use, usefulness, and ease of use of structural equation modeling in MIS research: A note of caution, MIS Quarterly, 19(2), 237－246.
Chin, W. W. (1998). Issues and opinion on structural equation modeling, MIS Quarterly, 22(1), VII-XVI.
Chin, W. W. (2001). PLS-Graph User’s Guide, Version 3.0.
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a montecarlo simulation study and an electronic-mail emotion/adoption study, Information Systems Research, 14(2), 189－217.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technologies, MIS Quarterly, 13(3), 319－340.
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.
Davis, F. D., Bagozzi, R., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models, Management Science, 35(8), 982－1003.
Dwyer, L., & Mistilis, N. (1997). Challenges to MICE tourism in the asia-pacific region, Pacific Rim Tourism, 219－230.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research, 18(1), 39－50.
Gefen, D., Straub, D. W., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practives, Communication of the Association for Information Systems, 7(4), 1－79.
Hair, J. F., Anderson R. E., Tatham R.L., & Black W.C. (1998). Multivariate Data Analysis (5th ed.), Upper saddle river, NJ: Prentice Hall.
He, D., Lu,Y., & Zhou, D. (2008). Empirical study of consumers’ purchase intentions in C2C electronic commerce, Tsinghua Science and Technology, 13(3), 287－292.
Hong, S. J., Thong, J. Y. L., Moon, J. Y., & Tam, K. Y. (2008). Understanding the behavior of mobile data services consumers, Information Systems Frontiers, 10(4), 431－445.
Jackson, J. D., Yi, M. Y., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward and integrative view, Information & Management, 43(3), 350－363.
Jung, M. L. (2008). From health to E-health: Understanding citizens’ acceptance of online health care, Doctoral Thesis from Department of Business administration and Social Sciences Division of Industrial Marketing, E-commerce and Logistics.
Jung, Y., Begona, P. M., & Sonja, W. P. (2009). Consumer adoption of mobile TV: Examining psychological flow and media content, Computers in Human Behavior, 25(1), 123－129.
Kim, C., Mirusmonov, M., Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment, Computers in Human Behavior, 26(3), 310－322.
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.
Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model, Information & Management, 40(3), 191－204.
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中文文獻：
台灣國際數據資訊網站 http://www.idc.com.tw/。
行政院全球資訊網 http://www.ey.gov.tw/。
柏雲昌(2010)。會議展覽產業之發展策略。臺北產經第一期。
經濟部國際貿易局網站 http://cweb.trade.gov.tw/。		zh_TW