臺灣博碩士論文加值系統

多媒體機台(Multiple Media Kiosk, MMK)除了能替組織省下諸多成本外，它同時也在自助式服務創新應用上扮演著相當重要的地位；本研究以台灣四大便利商店的多媒體機台作為主要討論對象，希望找出提升消費者對多媒體機台使用意願的因素，使臺灣未來能像日韓兩國一樣有更多的自助式服務創新成為可能。
本研究以科技接受模型(TAM)作為解釋MMK使用行為的主要理論架構，並認為在多通路與多媒體零售環境下，影響行為的因素不單只有MMK本身，它同時還會受到消費者對傳統網路服務的使用經驗以及對新科技應用的接受程度這兩個因素所影響，因此，本研究選用互動性(Interactive)與科技準備(Technology Readiness)這兩個構面作為TAM中影響行為的外部因素，其中互動性表示網路服務的使用經驗，科技準備則隱含應用行動裝置在消費行為上的接受程度，並透過結構方程模型(SEM)來驗證此一關係是否存在。
經由網路發放問卷調查並利用AMOS進行統計分析後，結果顯示除了TAM理論本身的知覺有用性與知覺易用性兩構面對使用多媒體機台的行為有所影響外，消費者願意應用行動裝置於消費行為的科技準備程度也會顯著影響上述兩構面進而影響使用行為，另外本研究假設消費者認知網路服務互動性的程度在整體行為中具有調節效果的作用，但統計的結果顯示此一關係並不成立。因此本研究在結論的部份建議，業者如要提升消費者對多媒體機台這類自助式服務的行為普及率，透過發展行動裝置端的通路也許將有不錯的效果。

A Multiple Media Kiosk (MMK) not only saves lots of cost for organization, but plays a role in innovating of self-service technology (SST). This research wanted to find factors of improving user intention in MMK by studying MMK in convenience stores in Taiwan, making more innovations in SST will come true in the future.
The research used Technology Acceptance Model (TAM) to explain the behavior of using MMK, in the meantime, we premised that user experience to the internet service and the acceptance to the application of the new technology could also affect it in the multichannel and multimedia retailing environment. So we used two dimensions, Interactive and Technology Readiness, to describe above circumstances and made assumption that these two dimensions could be the external variable of TAM. Fianl, confirming these relations by SEM was our research method in statistic.
After analyzing data from Online-survey by AMOS, the results indicated that perceived usefulness and perceived ease of use (two factors in TAM) were significant influence on the behavior of using MMK, moreover, Technology Readiness also could be antecedent variable to the TAM. But, as moderator, Interactive did not have the interaction effect in this research. Therefore, the conclusion implies that maybe it is a good idea to corporations who try to improve their usage in MMK via developing the mobile channel.

目錄
第一章 緒論 1
第一節 研究背景 1
第二節 研究動機 1
第三節 研究目的 3
第四節 研究流程 4
第二章 文獻探討 5
第一節 科技接受模型與其相關理論 5
第二節 多通路策略與多媒體零售環境 8
第三節 科技準備 11
第四節 互動性 14
第三章 研究方法 16
第一節 研究架構 16
第二節 變數的操作性定義與假說推論 17
第三節 抽樣設計與統計方法 20
第四章 研究結果與討論 25
第一節 敘述性統計 25
第二節 驗證性因素分析與信效度檢定 30
第三節 研究模型配適度與假說驗證 33
第四節 其他SEM相關檢定 40
第五章 結論與建議 44
第一節 研究結果與討論 44
第二節 研究貢獻與實務建議 46
第三節 研究限制與未來研究方向 48
參考文獻 50
附錄一 研究問卷 58

中文部分
于海、董大海、劉瑞明、原永丹(2008)。理性行為理論及其拓展研究的現狀與展望。心理科學進展，16(5)，796-802。
王貴賢 (2005)。消費者網路競標意圖研究－認知風險觀點。國立中央大學資訊管理學研究所碩士論文。
朱碧靜 (2012)。圖書館學與資訊科學大辭典。臺北市：國家教育研究院。
徐茂洲 (2012) 。結構方程模型的統計檢定力計算及樣本數決定在《大專體育學刊》之運用。大仁科技大學休閒運動管理系。
張世勳 (2009)。影響消費者對自助服務科技接受度之研究-以連鎖便利商店內多媒體資訊站為例。國立成功大學企業管理研究所碩士論文。
張偉豪 (2011)。SEM論文寫作不求人。鼎茂出版社。
蔣筱鈺 (2001)。臺灣KIOSK產業之研究。國立台灣大學商學研究所碩士論文。
英文部分
Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.
Ajzen, I., & Fishbein M. (1980). Understanding Attitudes and Predicting Social Behavior. Prentice-Hall Press.
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.
Babin, B. J., Hair, Jr. J.F., & Boles, J. S. (2008). Publishing research in marketing journals using structural. Journal of Marketing Theory and Practice, 16 (4), 279-285.
Bem, D.J. (1965). An experimental analysis of self-persuasion. Journal of Experimental Social Psychology, 1, 199-218.
Bentler, P.M. (1980). Multivariate analysis with latent variables: Causal modeling. Annual Review of Psychology, 3(1),419-456.
Bentler, P. M. (1989). EQS structural equations program manual. Los Angeles, CA: BMDP Statistical Software.
Bentler, P. M., & Chou, C-P (1987). Practical issues in structural modeling. Sociological Methods and Reseach. 16(1), 78-117.
Blue, C.L. (1995). The predictive capacity of the theory of reasoned action and the theory of planned behaviour in exercise research: an integrated literature review. Research in Nursing and Health, 18, 105–121.
Bolton, R. N.,& Saxena-Iyer, S. (2009). Interactive Services: a Framework, Synthesis and Research Direction. Journal of Interactive Marketing, 23(1), 91–104.
Bollen, K. A. and Stine, R. A. (1992). Bootstrapping goodness-of-fit measures in structural equation models. Sociological Methods and Research, 21, 205–229.
Busemeyer, J. R. & Jones, L. E. (1983). Analysis of Multiplicative Combination Rules when the Causal Variables are Measured with Error. Bulletin, 93, 549-62.
Byrne, B. B. (2010). Structural equation modeling using AMOS. Basic concepts ,applications, and programming (2nd Ed). New York: Routledge.
Casalo, L., Flavia´n, C., , M., (2007). The influence of satisfaction, perceived reputation and trust on a consumer’s commitment to a website. Journal of Marketing Communication, 13(1), 1–17.
Castañeda, J.A., Muñoz-Leiva F., Luque T.,(2007). Web Acceptance Model (WAM): Moderating effects of user experience. Information & Management, 44, 384–396.
Chen, S. C. (2011). Understanding the effects of technology readiness satisfaction and electronic word-of- mouth on loyalty in 3c products. Australian Journal of Business and Management Research, 1(3), 1–9.
Chen, S., Dhillon, G., (2003). Interpreting dimensions of consumer trust in e-commerce,” Information Management and Technology, 4, 303–318.
Cheng, Y. H., & Huang, T. Y. (2014). High speed rail passenger segmentation and ticketing channel preference. Transportation Research, Part A 66, 127–143.
Chiu, H. C., Hsieh, Y. C., Roan, J., Tseng, K. J., & Hsieh, J. K. (2011). The challenge for multichannel services: Cross-channel free-riding behavior. Electronic Commerce Research and Applications, 10, 268–277.
Cialdini, R. B., Reno, R. R., & Kallgren, C. A. (1990). A focus theory of normative conduct: Recycling the concept of norms to reduce littering in public places. Journal of Personality and Social Psychology, 58(6), 1015–1026.
Cortina, Jose M., Chen, G., & Dunlap, W. P. (2001). Testing Interaction Effects in LISREL: Examination and Illustration of Available Procedures. Organizational Research Methods, 4 (4), 324-360.
Cyr, D., Head, M. & Ivanov, A. (2009). Perceived interactivity leading to e-loyalty: Development of a model for cognitive–affective user responses. Human-Computer Studies, 67, 850–869.
Dabholkar, P. A. (1994). Technology-based service delivery: a classification scheme for developing marketing strategies. Advances in Services Marketing and Management, 30(3), 241–271.
Davis, F.D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Dholakia, U. M., Kahn, B. E., Reeves, R., Rindfleisch, A., Stewart, D. & Taylor, E. (2010).Consumer Behavior in a Multichannel, Multimedia Retailing Environment. Journal of Interactive Marketing, 24(2), 86–95.
Diamantopoulos, A. & Siguaw, J.A. (2000). Introducing LISREL. London: Sage Publications.
Elliott, K., Meng, G.& Hall, M. (2012). The Influence of Technology Readiness on the Evaluation of Self-Service Technology Attributes and Resulting Attitude Toward Technology Usage. Services Marketing Quarterly, 33, 311–329.
Festinger, L. and Carlsmith, J. M. (1959). Cognitive consequences of forced compliance. Journal of Abnormal and Social Psychology, 58, 203-211.
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading. MA: Addison- Wesley
Fornell, C., & Larcker, D.F., (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Godin, G. (1993). The theories of reasoned action and planned behaviour: overview of findings, emerging research problems and usefulness for exercise promotion. Journal of Applied Sport Psychology, 5, 141–157.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate data analysis. Upper Saddle River, NJ: Prentice Hall.
Hancock, G. R., & Nevitt, J. (1999). Bootstrapping and the identification of exogenous latent variables within structural equation models. Structural Equation Modeling, 6, 394–399.
Hoyle, R. H. & Panter, A. T. (1995). Writing about structural Equation models. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications.Thousand Oaks, CA: Sage, 158-176.
Jaccard, J., Turrisi, R. & Wan, C. (1990). Interaction Effects in Multiple Regression. Newbury Park, CA: Sage Publications. Inc.
Jiang, Z., & Benbasat, I. (2007). Investigating the influence of the functional mechanisms of online product presentations. Information Systems Research, 18(2), 1–16.
Johnson, G.J., Bruner, G.C., Kumar, A. (2006). Interactivity and its facets revisited. Journal of Advertising, 35(4), 35–52.
Kenny, D., & Judd, C. M. (1984). Estimating the nonlinear and interactive effects of latent variables. Psychological Bulletin, 96, 201-210.
Kilcourse, B., & Rowen, S. (2008). Finding the Integrated MultiChannel Retailer. Miami: Retail Systems Research.
Kim, J., & Forsythe, S. (2008). Adoption of Virtual Try-On Technology for Online Apparel Shopping. Journal of Interactive Marketing, 22(2), 45–59
Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd Ed.). New York: Guilford Press.
Konus, U., Verhoef, P. C., & Neslin, S. A. (2008). Multichannel Shopper Segments and their Covariates. Journal of Retailing, 84(4), 398–413.
Ku, C. S., & Chen C. D. (2012). Fitting facilities to self-service technology usage: Evidence from kiosks in Taiwan airport. Journal of Air Transport Management, 32, 87–94.
Kushwaha, T. & Shankar, V. (2007). Single Channel vs. Multichannel Customers: Determinants and Value to Retailers. Working paper, Texas A&M University.
Lee, D., Moon, J., Kim, Y. J., & Yi, M.Y. (2015). Antecedents and consequences of mobile phone usability: Linking simplicity and interactivity to satisfaction, trust, and brand loyalty. Information & Management, in press, corrected proof.
Lee, T. (2005). The impact of perceptions of interactivity on customer trust and transaction intentions in mobile commerce. Journal of Electronic Commerce Research, 6(3), 165–180.
Levy, M. & Weitz, B. A. (2009), Retailing Management. (7th ed.). New York, N.Y: The McGraw-Hill/Irwin Companies, Inc.
Lin, J.C. & Hsieh, P.L. (2007). The influence of technology readiness on satisfaction and behavioral intentions toward self-service technologies. Computers in Human Behavior, 23(3), 1597-1615.
Lin, C.H., Shih, H.Y. & Sher, P.J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing, 24(7), 641–657.
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.
McDonald, R. P., & Ho, M. H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7, 64–82.
Mick, D. G., & Fournier, S. (1998). Paradoxes of technology: consumer cognizance, emotions, and coping strategies. Journal of Consumer Research, 25(2), 123–144.
Parasuraman, A. (2000). Technology readiness index (TRI): a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307-320.
Parasuraman, A., & Colby, C. L. (2001). Techno-ready marketing: How and why your customers adopt technology. New York: Free Press.
Peter, J. P. & Olson, C. J. (1987). Consumer Behavior: Marketing strategy perspective. Illinois: Irwin.
Ping, R. A. (1995). A parsimonious estimating technique for interaction and quadratic latent variables. Journal of Marketing Research, 32, 336-347.
Rosenberg, M. J. and Hovland, C. I. (1960). Cognitive, Affective and Behavioral Components of Attitudes. In M. J. Rosenberg, C. I. Hovland (eds.). Attitude Organization and Change: An Analysis of Consistency Among Attitude Components. New Haven: Yale University Press.
Schreiber, J.B. (2008). Core reporting practices in structural equation modeling. A dministrative Pharmacy, 4, 83-97.
Schumacker, R. E., & Lomax, R. G. (2004) , A beginner’s guide to structural equation modeling. New Jersey: Lawrence Erlbaum Associates.
Schumann, J. H., Nancy V. W., & Florian W. (2012). Technology mediation in service delivery: A new typology and an agenda for managers and academics. Technovation, 32, 133–143.
Shah, J. R., & Murtaza, M. B. (2005). Effective Customer Relationship Management Through Web Services. Journal of Computer Information Systems, 46(1), 98–109.
Shankar, V., & Balasubramanian, S. (2009). Mobile Marketing: Synthesis and Prognosis. Journal of Interactive Marketing, 23(2), 118–129.
Shankar, V., Venkatesh, A., Hofacker, C. & Naik, P. (2010). Mobile Marketing in the Retailing Environment: Current Insights and Future Research Avenues. Journal of Interactive Marketing, 24(2), 111–120.
Shankar, V., & Yadav, M. S. (2010). Emerging Perspectives on Marketing in a Multichannel and Multimedia Retailing Environment. Journal of Interactive Marketing, 24, 55–57.
Shina D.H., Jungb J., Changc B.H. (2012). The psychology behind QR codes: User experience perspective. Computers in Human Behavior, 28, 1417–1426.
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 145-176.
Thompson, B. (2004). Exploratory and confi rmatory factor analysis: Understanding concepts and applications. Washington, DC: American Psychological Association.
Torkzadeh, G., Koufteros, X., & Pflughoeft, K. (2003). Confirmatory analysis of computer self-efficacy. Structural Equation Modeling, 10(2), 263-275.
Tsikriktsis, N. (2004). A Technology Readiness-Based Taxonomy of Customers: A Replication and Extension. Journal of Service Research, 7(1), 42-52.
Varadarajan, R., Srinivasan, R., Vadakkepatt, G. G., Yadav, M. S., Pavlou, P. A., Krishnamurthy S., & Krause, T. (2010). Interactive Technologies and Retailing Strategy: A Review, Conceptual Framework and Future Research Directions. Journal of Interactive Marketing, 24(2), 96–110.
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.
Werner, P. (2004). Reasoned Action and Planned Behavior. in S.J. Peterson & T.S. Bredow (eds), Middle range Theories: Application to Nursing Research. Lippincott Williams & Wilkins, Philadelphia, 125-147.
White, K., Smith, J., Terry, D., Greenslade, J., & McKimmie, B. (2009). Social influence in the theory of planned behaviour: The role of descriptive, injunctive, and in-group norms. British Journal of Social Psychology, 48(1), 135-158.
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce. An empirical evaluation of the revised technology acceptance model. Information and Management, 42(5), 719–729.
Wu, G., Hu, X., & Wu, Y. (2010). Effects of perceived interactivity, perceived web assurance and disposition to trust on initial online trust. Journal of ComputerMediated Communication, 16(1), 1–26.
Zhang, J., Paul W. Farris, John W. Irvin, Tarun Kushwaha, Thomas J. Steenburgh, and Barton A. Weitz (2010). Crafting Integrated Multichannel Retailing Strategies. Journal of Interactive Marketing, 24(2), 168–180.
Zhao, L., & Lu, Y. (2012). Enhancing perceived interactivity through network externalities: An empirical study on micro-blogging service satisfaction and continuance intention. Decision Support Systems, 53(4), 825–834.
Zwass, Vladimir (1996). Electronic Commerce: Structures and Issues. International Journal of Electronic Commerce, 1, 3–23.