臺灣博碩士論文加值系統

Galileo是全球分銷系統 (Global Distribution System：GDS) 的其中一個系統，提供旅遊相關之交通、住宿、行程等多功能的預訂平台，旅遊業者可透過系統平台為客戶提供相關服務。系統除了可以增加員工的工作效率，亦可作為有效的銷售與行銷工具。本研究的主要目的是探討台灣地區旅行社從業人員採用Galileo旅館訂房系統的影響因素；詳言之，以分解式計劃行為理論 (Decomposed Theory of Planned Behavior：DTPB) 為基礎，探討影響旅行社從業人員採用Galileo旅館訂房系統使用意願的前因變項，並瞭解這些因素影響使用意願的強弱程度。
本研究之研究對象為年滿18歲以上使用Galileo旅館訂房系統平台之旅行社從業人員，並以與Gelileo系統提供商Travleport簽訂合約的台北市與新北市、台中市以及高雄市之旅行社員工作為問卷發放的對象。至於個別旅行社選定，則以綜合及甲種的旅行社，為主要問卷發放單位；以該旅行社使用GDS系統的部門人數作為發放問卷數目的基礎：每5名使用者，發放2份問卷，5至10人發放4份問卷，以此類推，以便利抽樣方式進行。Galileo公司員工在拜訪客戶到場服務時協助問卷發放。本研究發放450份問卷，調查時間自100年3月7日起至5月7日止。
本研究總計獲得302份有效問卷，以結構方程模式進行資料分析。各變數影響關係為：行為態度與主觀規範均正向影響行為意願；其中行為態度具有較大的影響效果。在影響行為態度的因素上，認知有用性與認知易用性均具有正向影響效果，其中認知易用性的影響效果較大。此外，影響使用者主觀規範的因素包括：同儕影響及上級影響，而同儕影響的效果大於上級影響。同時本研究亦比較DTPB以及科技接受模式 (Technology Acceptance Model：TAM) 對於研究變項行為意願的解釋力，發現TAM優於DTPB。
根據本研究結果，提出對未來後續研究的建議，並提出實務意涵供Galileo系統商作為產品開發與行銷策略擬訂之參考，以及旅行社高階主管促使員工接受與使用系統平台的可行做法。

This study examines the factors influencing employees’ behavioral intention to use Galileo hotel reservation system (HRS) in the travel agencies. Decomposed theory of planned behavior (DTPB) is adapted from social psychology and integrated with theoretical and empirical findings from prior information systems (IS) usage research to theorize a conceptual model of Galileo HRS usage. Specifically, the research model decomposes the perceived behavioral control components of TPB into Galileo HRS self-efficacy and technical supports, the subjective norm component into peer’s influences and supervisor’s influence, and the attitude component into perceived usefulness, perceived ease of use, and compatibility. Ten research hypotheses were derived from this model and were then empirically tested by employing survey data that was collected from 302 Galileo HRS users among Taiwan travel industries. The structural equation modeling (SEM) was used as a data analysis method.
The findings suggest that, with the exception of several constructs that were included in the conceptual model (namely, perceived behavioral control, self-efficacy, technical supports and compatibility), the other constructs significantly influence employees when adopting Galileo HRS in travel agencies. On the aspect of influential factors of users toward Galileo HRS, attitude and subjective norm efficiently predict the behavioral intention. Perceived usefulness and perceived ease of use predicted attitude effectively. Both peer influence and superior’s influence operatively predict the subjective norm. Furthermore, in comparison with technology acceptance model (TAM) and DTPB, there is no significant increase on the explanatory power with the posterior. Therefore, if the key objective is to predict behavioral intention to use HIS, the TAM is preferable; however, if the key objective is to explain behavioral intention to use HIS, the DTPB is preferable.
This research has implications for Galileo HRS providers and travel agent managers since the results of this study can be exploited by the aforementioned stakeholders in order to encourage and promote the adoption and usage of Galileo HRS among travel agents.

目 錄
中文摘要 I
英文摘要 III
誌 謝 IV
目 錄 V
表 目 錄 VII
圖目錄 VIII
第壹章 緒 論 1
第貳章　文獻探討 5
第一節Galileo系統介紹 5
第二節Galileo旅館訂房系統操作介面及功能 8
第三節 分解式計劃行為理論DTPB之介紹 16
第參章 研究方法 28
第一節 研究架構與假說 28
第二節 研究對象和抽樣方法 32
第三節 資料分析工具 34
第肆章 資料分析與討論 37
第一節 樣本資料敘述統計分析 37
第二節 驗證假說與模式 41
第伍章 結論與建議 64
參考文獻 68
附件一 76

表 目 錄
表2-1 應用DTPB相關文獻 27
表3-1 本研究變數操作型定義與題項內容 31
表3-1 本研究變數操作型定義與題項內容（續完） 32
表4-1 受訪者資料 40
表4-2 使用者使用Galileo訂房系統經驗 41
表4-3 測量模式配適度指標分析表 44
表4-5 潛在構面間的相關係數矩陣 48
表4-7 調整後DTPB測量模式配適度指標分析表 50
表4-8 調整後DTPB結構模式配適度指標分析表 50
表4-9 DTPB最終測量模式配適度指標分析表 52
表4-10 DTPB最終結構模式配適度指標分析表 53
表4-11 修正後假說與研究結果摘要表 53
表4-12 本研究結構模式之直接效果、間接效果與整體效果 57
表4-13 TAM測量模式配適度指標分析表 59
表4-14 TAM結構模式配適度指標分析表 59
表4-15 初始假說與研究結果摘要表 60
表4-16 TAM及DTPB 研究變項解釋力比較表 62
圖目錄
圖2.1 Galileo旅館查詢與預訂功能 9
圖2.2 Galileo使用者輸入基本條件查詢 9
圖2.3 Galileo系統旅館查詢結果 11
圖2.4 Galileo系統查詢所獲得之旅館名稱及所在位置 11
圖2.5 Galileo系統所提供之旅館參考照片 12
圖2.6 Galileo系統所提供之旅館房價與房間型態 13
圖2.7 Galileo系統所提供之房型價格明細及其他相關規定 14
圖2.8 Galileo系統完成房間預訂並取得旅館確認編號 14
圖2.9 TRA模型架構 16
圖2.10 TPB模型架構 19
圖2.11 TAM 理論架構 19
圖2.12 DTPB理論架構 25
圖3.1 研究架構圖 28
圖4.1 調整後模式架構圖 49
圖4.2調整後DTPB標準化估計值 51
圖4.3修正後模式架構圖 52
圖4.4本研究模式標準化估計值 54
圖4.5 TAM模式架構圖 58
圖4.6 TAM模式標準化估計值 61

中文部份：
朱斌妤、黃仟文、翁少白（2008）。以科技接受模式探討即時交通資訊系統之使用意願。Journal of e-Business。10（1），173-200。
任維廉、呂堂榮、劉柏廷（2009）。科技接受行為模式之整合分析：三個主要模式之比較。資管評論。15（1），101-138。
呂錦隆、凌佩娟（2009）。國籍旅客對國際航線自助報到服務之使用意圖研究。運輸學刊。 21（3），299-328。
林庭逸（2008）。 Travelport 精準資訊助旅業闢商機。旅奇雙週刋。上網日期民99年11月22日。取自：
http://b2b.travelrich.com/subject01/subject01_detail.aspx?Second_classification_id=14&Subject_id=5723
吳明隆（2003）。SPSS統計應用學習實務：問卷分析與應用統計。台北：知城數位科技。
柯清德（2004）。影響政府部門人員接受電子化政府服務之關鍵因素－以電子公文系統為例。未出版碩士論文，國立中正大學資訊管理學系，嘉義。
張鴻昌、郭倉義、賴美志（2004）。員工對企業內部網路接受度之研究－以中鋼公司為例。產業電子化運籌管理學術暨實務研討會。

黃燕芬（2003）。中學英語教師資訊融入英語教學之認知、關注階層、行為及相關因素之研究。
葉美春、阮明淑（2007）。使用者採用知識管理系統之影響因素研究─理論模型的比較取向。圖書資訊期刊。5（1），69-50。
楊正甫、戴維舵（1991），使用者觀點之資訊系統績效評估模式，管理科學學報，8（1），109-118。
電子化迎接全球化市場速度決定競爭力（2009）。 TTN 旅報 Taiwan。上網日期民99年10月10日。取自：http://www.ttnmedia.com/magazine/frontmagazinecontroller?func=find&magtitlenbr=6968&contentpage=1
蔡忠佑（2009）。家長對孩童網路分級過濾系統使用意向之研究。未出版碩士論文，國立成功大學電信管理研究所，台南。
蔣德誼（2008）。加利略再度榮獲年度亞洲最佳GDS。旅奇雙週刋。上網日期民100年01月18日。取自：http://b2b.travelrich.com/subject01/subject01_detail.aspx?Second_classification_id=9&Subject_id=5142
觀光局（2010）。「2010 年 10 月旅行業家數統計」。台北市：交通部。上網日期民99年11月5日。取自：http://admin.taiwan.net.tw/statistics/month_show.asp?selno=27&selyear=2010&selmonth=10&sikey=1



英文部份：
About Travelport (n.d.). Travelport.com. Retrieved Oct 05, 2010, from the World Wide Web:http://www.travelport.com/about.aspx

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.

Ajzen, I. & Fishbein, M. (1980). Understanding attitude and predicting social behavior. Prentice-Hall, New Jersey.

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J.Kuhl and J.Bechmann (Eds.), Action Control: From Cognition to Behavior (11-39). Berlin;New York: Springer-Verlag.

Ajzen, I. (1988). Attitude, personality, and behavior. Open University Press, Milton Keynes.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2), 179-211.

Ajzen, I. & Driver, B.L. (1992). Application of the theory of planned behavior to leisure choice. Journal of Leisure Research, 24 (3), 207-224.

Anderson, J.C. & Gerbing, D.W. (1988). Structural equation modeling in practice: A review and Recommended two-step. Psychological Bulletin, 103 (3), 411-423




Average Daily Rates Can Now Be Viewed for Over 400 Cities (2003). TravelCLICK.net. Retrieved Oct 30, 2010, from the World Wide Web: http://www.hotel-online.com/News/PR2003_1st/Feb03_TravelClickData.html

Bagozzi, R. P. (1981). ”Attitudes, intentions, and behavior: A test of some key hypotheses,” Journal of Personality and Social Psychology. 1(October),
607-627.

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation structural equation models. Academic of Marketing Science, 16, 74-94.

Bentler, P. M. (1995). EQS: Stuctural equations program manual. Encino, CA: Multivariate Software Inc.

Bhattacherjee, A. & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 28 (2), 229-254.

Camison, C. (2000). Strategic attitudes and information technologies in the hospitality business: an empirical analysis. International Journal of Hospitality Management, 19 (2), 125-43.

Carrier M. (2007). Effective GDS use can maximize revenue. Hotel & Motel Management. Retrieved Nov 03, 2010, from the World Wide Web: http://www.britannica.com/bps/additionalcontent/18/25246373/Effective-GDS-use-can-maximize-revenue

Cheung, W., Chang, M. K., & Lai V. S. (2000). "Prediction of internet and world wide web usage at work: A Test of an extended triandis model", Decision Support Systems , 30(1), 83-100.
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.

Colby, C. L. & Parasuraman, A. (2003). Technology still matters, Marketing Management, 12(4), 2003, 28-33.

Compeau, D. R. & Higgins, C. A. (1995). Application of social cognitive theory to training for computer skills. Information Systems Research, 6(2), 118-143.

Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319-339.

Davis, F.D., Bagozzi, R.P. & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35 (8), 982-1003.

Fishbein, M. & Ajzen, I. (1975). Beliefs, Attitude, intention, and behavior: An Introduction to Theory and Research. Addison-Wesley, Reading, MA.

Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable and measurement error. Journal of Marketing Research, 18 (1), 39-50.

Galileo CRS (n.d.). Wikipedia. Retrieved Oct 29, 2010, from the World Wide Web: http://en.wikipedia.org/wiki/Apollo_Reservation_System#cite_note-0

Galileo Room Master for Agency (n.d.). Travelport.com. Retrieved Oct 29, 2010, from the World Wide Web: http://www.travelport.com/Global%20Repository/Products%20and%20Services/Galileo%20RoomMaster%E2%84%A2%20for%20Agency.aspx
Garson, G. D. (2006). Public information technology and e-governance: Managingthe virtual state. Jones and Bartlett Publishers, MA.

Goodhue, D. L. & Thompson, R. L (1995). Task-Technology fit and individual
Performance. MIS Quarterly, 19(2),213-236.

Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. (1998). Multivariate Data Analysis.Englewood Cliffs, NJ: Prentice-Hall.

Hartshorne, R. & Ajjan, H. (2009). Examining student decisions to adopt Web 2.0 technologies: theory and empirical tests. J Comput High Educ , 21, 183-198.

Herr, P. M., Kardes F. R. & Kim J. (1991). Effects of Word-of-Mouth and product-attribute Information on persuasion: An accessibility-diagnosticity perspective. Journal of Consumer Research, 4(17), March, 454-462.

How Customer Focused Is Your Technology? (May 2010). The Pegasus View. Retrieved Oct 30, 2010, from the World Wide Web:
http://www.pegs.com/ThoughtLeadership/The Pegasus View/docs/The Pegasus View May 2010 Final.pdf

Huh, H. J., Kim, T. & Law, R. (2009). A comparison of competing theoretical models for understanding acceptance behavior of Information systems in upscale hotel. International Journal of Hospitality Management, 28, 121-134.

Hu, L.T. & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling, 6 (1), 1-55.



Hsu, M. H. & Chiu, C. M. (2004). Predicting electronic service continuance with a decomposed theory of planned behavior. Behavior & Information Technology. 23(5). 359-373.

International GDS Bookings Deliver Highest Average Daily Rate Increase for 2010 at +7.5% over 2009 (June, 2010). The Pegasus View. Retrieved Oct 15, 2010, from the World Wide Web: http://www.hotel-online.com/News/PR2010_3rd/Jul10_PegasusView.html

Kim, T.G., Lee, J.H. & Law, R. (2008). An empirical examination of the acceptance behavior of hotel front office systems: an extended technology acceptance model. Tourism Management, 29 (3), 500-513.

MacCallum, R. C., Browne, M. W. & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1 (2), 130-149.

Morosan, C. & Jeong, M. (2008). Users’ perceptions of two types of hotel reservation Web sites. International Journal of Hospitality Management, 27 (2), 284-292.

Morre, 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.

Mulaik, S. A., James, L. R., Van Altine, J., Bennett, N., Lind, S. & Stilwell, C. D. (1989). Evaluation of goodness-of-fit indices for structural equation models. Psychological Bulletin, 105 (3), 430-445.

Reisinger, Y. & Turner, L. (1999). Structural equation modeling with LISREL: Application in tourism. Tourism Management, 20, 71-88.

Roca, J.C. & Gagne, M. (2007). Understanding e-learning continuance intention in the workplace: A self-determination theory perspective. Computers in Human Behavior. 24 (2008), 1585-1604.


Rogers, E. M. (1983). Diffusion of Innovations.New York, NY: The Free Press.

Shimp, T.A., & Kavas A. (1984). “The theory of reasoned action applied to coupon usage, Journal of Consumer Research, 11(3), 795-809.

Taylor, R. S. (1986). Value-Added Processes in Information Systems, Westport. CT: Greenwood.

Taylor, S. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly. 4 (1995), 561-570.

Taylor, S., & Todd, P. (1995). Decomposition and crossover effects in the theory of planned behavior: a study of consumer adoption intentions, International Journal of Research in Marketing, 12: 137-155.

Taylor, S., & Todd, P. (1995). Understanding information technology usage: A test of competing models, Information systems research, 6(2), 144-176.

Triandis, H.C. (1980). Values, attitudes and interpersonal behavior. Lincoln: University of Nebraska Press.

Vessey, I. & Galletta (1991). Cognitive fit: An empirical study of information
acquisition. Information Systems Research, 1.2(1), 63-86.