一、中文部分
黃嘉勝(1994),創新觀念接受量表在教學科技上的應用,教學科技與媒體,第十五卷,頁31-36。
陳嘉彌(1996),中等學校教師接受創新程度之分析,教育研究資訊,第四卷,第三期,頁86-103。麥孟生(2000)《個人心理類型、自我效能及態度對電腦學習成效之影響》,國立中央大學資訊管理學系碩士論文。周文賢(2004)。多變量統計分析SAS/STAT使用方法。台北市:智勝文化。
董峰呈、張淑昭(2007)。A New Hybrid Technology Acceptance Approach for Exploring e-CRM System Adoption in the Financial Services Industry: An Empirical Study。致遠管理學院學報,2(2),41-62。
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 。電子商務學報,10 (1),173-200。資策會(2010)。2010年8月底止台灣行動上網人口。2010年9月16日,取自http://www.find.org.tw/find/home.aspx?page=many&id=257
二、西文部分
Aguilar, T. E.(1985). Social and environmental barriers to playfulness. In J. L. Frost, & S.Sunderlin, (Eds.), When children play. Weaton, MD: Association for Childhoon Education International. 73-76.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckman (Eds.), Action Control: From Cognition to Behavior(pp. 11-39). Heidelberg: Springer.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior & Human Decision Process, 50, 179-211.
Atkinson, M., and Kydd, C.(1997). "Individual Characteristics Associated with World Wide Web use: An Empirical Study of Playfulness and Motivation," The DATABASE for Advances in Information Systems, 28(2), pp. 53-62.
Agarwal, R., & Prasad, J.(1998). A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology. INFORMATION SYSTEMS RESEARCH, Vol. 9, No. 2.
Agarwal, R., & Prasad, J.(1999). Are individual differences Germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361–391.
Asvanund, A., Clay, K., Krishnan, R., & Smith, M.D. (2004). An empirical analysis of network externalities in peer-to-peer music-sharing networks. Information Systems Research, 15(2), 155–174.
Ahn, T., Ryu, S., and Han, I.(2007). "The Impact of Web Quality and Playfulness on User Acceptance of Online Retailing," Information & Management, 44(3), Apr, pp. 263-275.
Au, Y. A., & Kauffman, R. J.(2008). The economics of mobile payments: Understanding stakeholder issues for an emerging financial technology application. Electronic Commerce Research and Applications, 7, 141–164.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavior hange. Psychological review, 84(2), 191-215.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness-of-fit in the analysis of covariance structure. Psychological Bulletin, 88, 588-606.
Bentler, P. M. (1990). Comparative fit indices in structural models. Psychological Bulletin, 107, 238-246.
Bentler, P. M. (1995). EQS: Structural Equations Program Manual. Encino, CA: Multivariate Software.
Bandura, A. (1982). Self-efficacy mechanism in human Agency. American Psychologist, 37(2), 122-147.
Bandura, A. (1986). Social foundations of thought and action:A Social-Cognitive theory. Englewood Cliffs,NJ:Prentice-Hall.
Barron, F. M. and D. M. Harrington (1981). Creativity, in Telligence and Personality. Annual Review of Psychology, Paloalto, CA: Annual Review, Vol. 32, pp.439-476.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structure equations models. Academic of Marketing Science, 16(1), 76-94.
Brown, L. G. (1989). The Strategic and Tactical Implications of Convenience in Consumer Product Marketing. Journal of Consumer Marketing 6(Summer) 13-19.
Barnett, L. A. (1991) . The playful child: measurement of a disposition to play. Play and Culture , 4(1), 51-74.
Bhattacherjee, A.(2001). Understanding information systems continuance: An expectation confirmation model. MIS Quarterly, 25(3), pp. 351-370.
Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service convenience. Journal of Marketing, 66(3), 1–17.
Buehrer, Richard E., Senecal, Sylvain and Ellen Bolman Pullins (2005), Sales Force Technology Usage—Reasons, Barriers, and Support: An Exploratory Investigation, Industrial Marketing Management, 34(4), pp.389-398.
Csikszentmihalyi, M.(1975). Beyond boredom and anxiety. SF: Jossey-Bass.
Carmines, E. G., & McIver, J. P. (1981). Analysing models with unobservable variables. In G. W. Bohrnstedt & E. E. Borgatta (Eds.), Social Measurement Current Issues (pp. 65-115). Beverly Hills, CA: Sage.
Cohen Wesley M.; Levinthal, Daniel A.(1990).“Absorptive capacity: A new perspective on learning and innovation ,”Administrative Science Quarterly; Mar.
Cottrell, T. (1994). “Fragmented Standards and the Development of Japan’s Microcomputer Software Industry,” Research Policy, 23(2), pp. 143-174.
Compeau, D. R. & Higgins, C. A. (1995). Computer self-Efficacy: development of a measure and initial test. MIS Quarterly, 19 (2), 189-192.
Compeau, D. R., Higgins, C. A.,Huff, S. (1999). Social cognitive theory and Individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23 (2), 145-158.
Conner, M., Warren, R., Close, S., Sparks, P., (1999). Alcohol consumption and the theory of planned behavior: an examination of the cognitive mediation of past behavior. Journal of Applied Social Psychology, 29 (8), 1676–1704.
Clarke, I. (2001). Emerging value propositions for M-commerce. Journal of Business Strategies, 18(2), 133–149.
Chang, S.H. and Tung , F.C.(2008). “An empirical investigation of students’ behavioural intentions to use the online learning course websites”, British Journal of Educational Technology, 39(1), pp. 71–83.
Chou & Chen (2009). The influence of individual differences on continuance intentions of enterprise resource planning (ERP). Int. J. Human-Computer Studies 67 484–496.
Davis, F. D. (1986). A technology acceptance model of empirically testing new End-UserInformation Systems: theory and results. Doctoral Dissertation, Sloan School of Management, Massachusetts Institute of Technology.
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., Bagozzi, R. P. & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982-1003.
Davis, F.D., Bagozzi, R.P., Warshaw, P.R.,(1992). “Extrinsic and intrinsic motivation to use computers in the workplace, ” Journal of Applied Social Psychology, Vol. 22 Issue 14, pp.1111-1132, Jul.
Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perception, and behavior impacts. International Journal of Man Machine Studies, 38(3), 475–487.
DeLone, W. H. and E. R. McLean (1992). Information Systems Success: The Quest for the Dependent Variable, Information System Research, 3(1), pp.60-95.
Doll, W. J., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MIS Quarterly, 18(4), 453-462.
Ding, X., Ijima, J., & Ho, S. (2004). Unique features of mobile commerce. Tokyo 152- 8552, Japan: Graduate School of Decision Science and Technology, TITECH.
Economides, N.(1996). The economics of networks. International Journal of Industrial Organization, 14(6), 673–699.
Fishbein, M. & Ajzen, I. (1975). Belief, attitude, intentions and behavior:anintroduction to theory and research. Boston: 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.
Gardner, Donald G., Richard L. Dukes, and Richard Discenza. (1993) .“Computer Use, Self-Confidence, and Attitudes: A Causal Analysis,” Computers in Human Behavior, 9(4), 427–40.
Gohmann, Stephan F., Barker, Robert M., Faulds, David J. and Jian Guan (2005). Salesforce Automation, Perceived Information Accuracy and User Satisfactory, Journal of Business & Industrial Marketing, 20(1), pp.23-32.
Guriting, P., Ndubisi N.O. (2006), “Borneo online banking: Evaluating customer perceptions and behavioral intention” , Management Research News, 29(1/2), pp.6-15.
Hurt, H. Y., K. Joseph and C.D. Cook (1977), Scales for the Measurement of Innovativeness, Human Communication Research, Vol.4, pp.58-65.
Hannan, T., and McDowell, J. (1984). The determinants of technology adoption: The case of the banking firm. Rand Journal of Economics, 15(3), 328–335.
Holak, S. L. (1988), Determinants of Innovative Durables Adoption an Empirical Study with Implications for Early Product Screening, Journal of Product Innovation Management, Vol. 5,No. 1, pp.59-73.
Hartwick, J. & Barki, H., (1994). “Explaining the Role of User Participation in Information System Use,” Management Science, 40(4), pp.440-465.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black W. C. (1998). Multivariate data analysis. UK: Prentice Hall.
Hu, L., & 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.
Hong, W., Thong, James Y. L., Wong, W. M. & Tam, K. Y. (2001). Determinants of User Acceptance Digital Libraries: An Empirical Examination of Individual Differences and System Characteristics, Journal of Management Information Systems, 18(3), pp.97-124.
Hung, S. Y., Ku, C. Y. & Chang, C. M., (2003), “Critical factors of WAP services adoption: an empirical study”, Electronic Commerce Research and Application, Vol.2, pp.42-60.
Heijden, H., (2004), “User acceptance of hedonic information systems”, MIS Quarterly, Vol.28, No.4, pp.695-704.
Hasan, B.(2006). Delineating the effects of general and system-specific computer self-efficacy beliefs on IS acceptance Information & Management, 43 565–571.
Hirunyawipada, T. & Paswan,A. K.(2006). Consumer innovativeness and perceived risk: implications for high technology product adoption. Journal of Consumer Marketing, 23(4), 182–198.
Horst, M., Kuttschreuter, M. & Gutteling, J. M.(2007). Perceived usefulness, personal experiences, risk perception and trust as determinants of adoption of e-government services in The Netherlands. Computers in Human Behavior 23 1838–1852.
Hsin Hsin Chang.(2008). Intelligent agent’s technology characteristics applied to online auctions’ task: A combined model of TTF and TAM. Technovation, 28, 564–577.
Hsu, C.L., and Lin, J.C.C.(2008). "Acceptance of Blog Usage: The Roles of Technology Acceptance, Social Influence and Knowledge Sharing Motivation," Information & Management, 45(1), Jan, p 65-74.
Jih, W.-J. (2007). Effects of consumer-perceived convenience on shopping intention in mobile commerce. An empirical study. International Journal of E-Business Research, 3(4), 33–48.
Jung & Berthon(2009). Fulfi lling the promise: A model for delivering successful online health care. Journal of Medical Marketing Vol. 9, 3, 243–254.
Kirton, M. J. (1976), Adaptors and Innovators:A Description and Measure. Journal of Applied Psychology, Vol.61, pp. 622-629.
Katz, M.L., and Shapiro, C. (1985). Network externalities, competition, and compatibility. American Economic Review, 75(3), 424–440.
Kauffman, R.J.; McAndrews, J.; and Wang, Y.M. (2000). Opening the “black box” of network externalities in network adoption. Information Systems Research, 11(1), 61–82.
Kim, B. G., Park, S. C., & Lee, K. J.(2007).A structural equation modeling of the Internet acceptance in Korea.Electronic Commerce Research and Applications 6 425–432.
Kim, C., Mirusmonov, M. & Lee. I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior 26, 310–322.
Liebowitz, S.J., and Margolis, S.E. (1995). Are network externalities a new source of market failure? Research in Law and Economics, 17, 1–22.
Lederer, A. L., Maupin, D. J., Sena M. P. & Zhuang, Y., (2000), “The Technology Acceptance Model and the World Wide Web”, Decision Support System, Vol.29, No.3, pp.269-282.
Luis L.Martins; Franz Willi Kellermanns,(2004). ”A model of business school students’acceptance of a Web-Based course management system,”Academy of Management Learning and Education.
Lu, J., Yao, J. E., & Yu, S. H.(2005).Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. Journal of Strategic Information Systems, 14, 245–268.
Lee,Y. C. (2006), “An empirical investigation into the factors influencing the adoption of an e-learning system" , Online Information Review, 30(5), pp. 517-541.
Lim, A. S. (2007). Inter-consortia battles in mobile payments standardization. Electronic Commerce Research and Applications, 2(2), 15–23.
Lee, K. C., Kang, I., Kim, J. S.(2007).Exploring the user interface of negotiation support systems from the user acceptance perspective. Computers in Human Behavior, 23, 220–239.
Lin, C. P. & Bhattacherjee, A. (2008). Elucidating Individual Intention to Use Interactive Information Technologies: The Role of Network Externalities. International Journal of Electronic Commerce, 13(1), pp. 85–108.
Lu, Y., Zhou, T. & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavio,r 25, 29–39.
Lee, Y. H., Hsieh, Y. C., & Ma, C. Y.(2011).A model of organizational employees’ e-learning systems acceptance Knowledge-Based Systems, 24, 355–366.
Midgley, D. F. and G. R. Dowling (1978), Innovativeness: The Concept and Its Measurement, Journal of Consumer Research, Vol.4, No. 4, pp. 229-242.
Mumford, M. D. and S. B. Gustafson (1988), Creativity Syndrome: Integration, Application, and Innovation. Psychological Bulletin, Vol.103, No. 27.
Mathieson, K. (1991). “Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior,” Information Systems Research, 2(3), pp.173-191.
Martocchio, J. J., & Webster, J. (1992). Effects of feedback and cognitive playfulness on performance in microcomputer software training. Personnel Psychology , 45(3), 553-578.
Moon, J. W. & Kim, Y. G. (2001) , Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230.
May, P. (2001). Mobile commerce: Opportunities, applications, and technologies of wireless business. Cambridge University Press.
Mallat, N. (2004). Theoretical constructs of mobile payment adoption. Paper presented at the 27th Information Systems Research Seminar in Scandinavia (IRIS), Falkenberg, Sweden, August, 14–17.
Mallat, N., & Dahlberg, T. (2005). Consumer and merchant adoption of mobile payment solutions. Managing business in a multi-channel world: Success factors for e-Business. Hershey, PA 17033, USA: Idea Group Publishing.
Meuter,M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W.(2005). Choosing Among Alternative Service Delivery Modes: An Investigation of Customer Trial of Self-Service Technologies. Journal of Marketing, Vol. 69, 61–83.
Mallat, N., Rossi, M., & Tuunainen, V.K. (2006). The impact of use situation and mobility on the acceptance of mobile ticketing services. In Proceedings of the 39th Hawaii international conference on system sciences. Hawaii.
O’reilly, C. A. III (1982). Variations in Decision Makers’ Use of Information Sources: The Impact of Quality and Accessibility of Information, Academy of Management Journal, 25(4), pp.756-771.
O’Cass, A. & Fenech, T. (2003). Webretailing adoption: exploring the nature of internet users Webretailing behavior. Journal of Retailing and Consumer Services, 10, 81–94.
Obe, O. O., & Balogu, V. F. (2007). Practice, trends and challenges of mobile commerce in Nigeria. Information Technology Journal, 6(3), 448–456.
Perry, M., O’hara, K., Sellen, A., Brown, B., & Harper, R. (2001). Dealing with mobility: Understanding access anytime, anywhere. ACM Transactions on Computer–Human Interaction, 8(4), 323–347.
Raju, P. S. (1980), Optimum Stimulation Level: Its Relations hip to Personality, Demographics, and Exploratory Behavior, Journal of Consumer Research, Vol. 7, pp. 272-282.
Rogers, Everett M. (1995). Diffusion of Innovations, 4th ed. New York: The Free Press.
Robinson, L., Marshall, G. W., & Stamps, M. B.(2005). Sales force use of technology: antecedents to technology acceptance Journal of Business Research, 58, 1623–1631.
Roca, J. C. & Gagne, M.(2008). Understanding e-learning continuance intention in the workplace: A self-determination theory perspective. Computers in Human Behavior, 24, 1585–1604.
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, 619–632.
Shurmer, M. (1993). “An Investigation into Sources of Network Externalities in the Packaged PC Software Market,” Information Economics & Policy, 5(3), 1993, pp. 231-251.
Saloner, G., and Shepard, A. (1995). Adoption of technologies with network effects: An empirical examination of the adoption of automated teller machines. Rand Journal of Economics, 26(3), 479–501.
Shapiro,C & Varian, H.(1999),Information Rules:A Strategic Guide to the Network Economy, Harvard Business School Press, Boston, Massachusetts.
Steenkamp, E. M., F. Hofstede and M. Wedel (1999), A Cross-National Investigation Into the Individual and NationalCultural Antecedents of Consumer Innovativeness, Journal of Marketing, Vol.63. No. 2, pp.55-69.
Siau, K., Lim, E.P. & Shen, Z. (2001). “Mobile Commerce: Promises, Challenges, and Research Agenda.” Journal of Database Management, 12(3), pp. 4-13.
Shy, O.(2001), The Economics of Network Industries. Cambridge University press.
Schiffman, L. G. (2003), Consumer Behavior, 9th ed. Prentice-Hall, Inc.
Subin I, B. L. Bayus and C. H. Mason (2003), An Empirical Study of Innate Consumer Innovativeness, Personal Characteristics, and New-Product Adoption Behavior, Journal of Academy of Marketing Science, Vol.31, No.1, pp.61-73.
Seyal, A. H., Rahman, N. A.(2007), “The influence of external variables on the executives' use of the internet” , Business Process Management Journal, 13(2), pp. 263-278.
Serenko (2008). A model of user adoption of interface agents for email notification. Interacting with Computers, 20, 461–472.
Scott, J. E., & Walczak, S. (2009). Cognitive engagement with a multimedia ERP training tool: Assessing computer self-efficacy and technology acceptance. Information & Management, 46(4), 221–232.
Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9, 209–216.
Taylor, S. & Todd, P. (1995). Assessing IT usage: the role of prior experience. MIS Quarterly, 19(4), 561-570.
Thong, J. Y. L., Hong, W. & Tam, K. Y. (2002). Understanding user acceptance of digital libraries: what are the roles of interface characteristics, organizational context, and individual differences?. International Journal of Human-Computer Studies, 57(3), 215-242.
Taylor, N. J.(2007). Public grid computing participation: An exploratory study of determinants. Information & Management 44 12–21.
Venkatraman, M. P. (1991), The Impact of Innovativeness and Innovation Type on Adoption, Journal of Retailing, pp. 51-67.
Venkatesh, V. & F. D. Davis, (1996). “A model of the antecedents of perceived ease of use: Development and Test”, Decision Sciences, 27(3), pp.451-481.
Venkatesh, V., and Davis, F.D., (2000). “A Theoretical Extension of the echnology Acceptance Model: Four Longitudinal Field Studies”, Management Science, vol. 46, pp.186-204.
Venkatesh, V. (2000). Determinants of perceived ease of use. Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information System Research, 11(4), 342–365.
Wu, J. H., Chen, Y.C., & Lin, L.M. (2007). Empirical evaluation of the revised end user computing acceptance model. Computers in Human Behavior 23 162–174.
Wang, C. C., Lo, S. K., & Fang, W. (2008). Extending the technology acceptance model to mobile telecommunication innovation: The existence of network externalities.Journal of Consumer Bcliaviour J. Consumer Behav. 7, 101-110.
Xu, G., & Gutierrez, J. A. (2006). An exploratory study of killer applications and critical success factors in M-commerce. Journal of Electronic Commerce in Organizations, 4(3), 63–79.
Yang, C. C.(2005). Exploring factors affecting the adoption of mobile commerce in Singapore. Telematics and Informatics, 22, 257–277.
Zmud, R. W. (1979). Individual differences and MIS success: a review of the empirical literature. Management Science, 25(10), 966–979.
Zhou & Lu (2010). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior.