|
1.Abrazhevich, D. (2004). Electronic Payment Systems: A User-Centered Perspective and Interaction Design. Eindhoven: Technische Universiteit Eindhoven. 2.Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. 3.Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Englewood Cliffs: Prentice-Hall. 4.Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423. 5.Bagozzi, R. P., & Yi, Y. (1988). On the Evaluation of Structure Equation Models. Journal of the Academy of Marketing Science, 16(1), 74-94. 6.Benamati, J., Fuller, M. A., Serva, M. A., & Baroudi, J. (2010). Clarifying the Integration of Trust and TAM in E-Commerce Environments: Implications for Systems Design and Management. IEEE Transactions on Engineering Management, 57(3), 380-393. 7.Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351-370. 8.Bollen, K. A. (1987). Total, Direct, and Indirect Effects in Structural Equation Models. Sociological Methodology, 17, 37-69. 9.Brown, S. A., & Venkatesh, V. (2005). Model of Adoption of Technology in Households: A Baseline Model Test and Extension Incorporating Household Life Cycle. MIS Quarterly, 29(3), 399-426. 10.Central Bank of the Republic of China. (2009). Republic of China Payment and Clearing System. [Web document]. Available: https://www.cbc.gov.tw/public/Attachment/972016463871.pdf [2016, 16 Oct] 11.Chiu, C.-M., Lin, H.-Y., Sun, S.-Y., & Hsu, M.-H. (2009). Understanding costomers’ loyalty intentions towards online shopping: an integration of technology acceptance model and fairness theory. Behaviour & Information Technology, 28(4), 347-360. 12.Chou, Y., Lee, C., & Chung, J. (2004). Understanding M-commerce payment systems through the analytic hierarchy process. Journal of Business Research, 57(12), 1423-1430. 13.Comrey, A., Reise, S., & Waller, N. (2000). Factor Analysis and Scale Revision. Psychological Assessment, 12(3), 287-297. 14.Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334. 15.Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281-302. 16.Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340. 17.Denecker, O., Istace, F., & Niederkorn, M. (2013). Forging a path to payments digitization. [Web document]. Available: http://www.mckinsey.com/~/media/mckinsey/dotcom/client_service/financial%20services/latest%20thinking/payments/mop16_forging_a_path_to_payments_digitization.ashx [2016, 25 Nov] 18.Devaraj, S., Fan, M., & Kohli, R. (2002). Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics. Information Systems Research, 13(3), 316-333. 19.El-Gohary, H. (2012). Factors affecting E-Marketing adoption and implementation in tourism firms: An empirical investigation of Egyptian small tourism organisations. Tourism Management, 33(5), 1256-1269. 20.Financial Supervisory Commission. (2016a). Credit card, cash card and electronic ticket business information. [Web document]. Available: http://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=201607280005&aplistdn=ou=news,ou=multisite,ou=chinese,ou=ap_root,o=fsc,c=tw&dtable=News [2016, Nov 09] 21.Financial Supervisory Commission. (2016b). Financial Technology Development Strategy White Paper. [Web document]. Available: http://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=201605120002&aplistdn=ou=news,ou=multisite,ou=chinese,ou=ap_root,o=fsc,c=tw&dtable=News [2016, 19 Oct] 22.Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Boston: Addison-Wesley. 23.Flavian, C., & Guinaliu, M. (2006). Consumer trust, perceived security and privacy policy: Three basic elements of loyalty to a web site. Industrial Management & Data Systems, 106(5), 601-620. 24.Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservables and Measurement Error. Journal of Marketing Research, 18(1), 39-50. 25.Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: an integrated model. MIS Quarterly, 27(1), 51-90. 26.Gorsuch, R. L. (1990). Common factor analysis versus component analysis: Some well and little known facts. Multivariate Behavioral Research, 25(1), 33-39. 27.Gou, F.-Z., & Shi, W.-Q. (2014). Small payment big change: debit card. [Web document]. Available: https://www.fisc.com.tw/Upload/d8bcb29c-5c2c-4641-a3cb-9d126a0b75da/TC/7901.pdf [2016, 17 Oct] 28.Granello, D. H., & Wheaton, J. E. (2004). Online data collection: Strategies for research. Journal of Counseling & Development. Journal of Counseling & Development, 82(4), 387-393. 29.Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate data analysis. Upper Saddle River: Pearson Prentice Hall. 30.Heijden, H. v. d. (2003). Factors influencing the usage of Websites: the case of a generic portal in The Netherlands. Information and Management, 40(6), 541-549. 31.Hinton, P. R., McMurray, I., & Brownlow, C. (2004). SPSS Explained. London: Routledge. 32.Holak, S. L., & Lehmann, D. R. (1990). Purchase Intentions and the Dimensions of Innovation: An Exploratory Model. The Journal of Product Innovation Management, 7(1), 59-73. 33.Holden, R. J., & Karsh, B.-T. (2010). The Technology Acceptance Model: Its past and its future in health care. Journal of Biomedical Informatics, 43(1), 159-172. 34.Hoyle, R. H. (1995). The structural equation modeling approach: Basic concepts and fundamental issues. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications. Thousand Oaks: Sage Publications. 35.Hsieh, C. (2001). E-commerce payment systems: critical issues and management strategies. Human Systems Management, 20(2), 131-138. 36.Hu, L.-T., & Bentler, P. M. (1995). Evaluating model fit. Thousand Oaks: Sage Publications. 37.Humphrey, D., Willesson, M., Lindblom, T., & Bergendahl, G. (2003). What Does it Cost to Make a Payment? Review of Network Economics, 2(2), 1-16. 38.Jahangir, N., & Begum, N. (2008). The role of perceived usefulness, perceived ease of use, security and privacy, and customer attitude to engender customer adaptation in the context of electronic banking. African Journal of Business Management, 2(1), 32-40. 39.Kalakota, R., & Whinston, A. B. (1996). Frontiers of Electronic Commerce. Boston: Addison Wesley 40.Kanchanatanee, K., Suwanno, N., & Jarernvongrayab, A. (2014). Effects of Attitude toward Using, Perceived Usefulness, Perceived Ease of Use and Perceived Compatibility on Intention to Use E-Marketing. Journal of Management Research, 6(3), 1-13. 41.Khiaonarong, T. (2009). An Economic Analysis Of E-Payments Diffusion In Asia. In UK Academy for Information Systems Conference Proceedings 2009 (pp. 31-31). United Kingdom. 42.Kniberg, H. (2002). What Makes a Micropayment Solution Succeed? (Masters thesis), Institution for Applied Information Technology, Stockholm, Sweden. 43.Kolsaker, A., & Payne, C. (2002). Engendering trust in e‐commerce: a study of gender‐based concerns. Marketing Intelligence & Planning, 20(4), 206-214. 44.Kotler, P. (2003). Marketing Management. Englewood Cliffs: Prentice Hall. 45.Laforet, S., & Li, X. (2005). Consumers’ attitudes towards online and mobile banking in China. International Journal of Bank Marketing, 23(5), 362-380. 46.Laudon, K. C., & Traver, C. G. (2001). E-Commerce: Business, Technology, Society. Boston: Addison Wesley Publishing. 47.Lawrence, E., Newton, S., Corbitt, B., Braithwaite, R., & Parker, C. (2002). Technology of Internet Business. New York: John Wiley & Sons. 48.Lederera, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000). The Technology Acceptance Model and the World Wide Web. Decision Support Systems, 29(3), 269-282. 49.Lim, B., & Kurnia, S. (2007). Exploring the Reasons for a Failure of Electronic Payment Systems: A Case Study of an Australian Company. Journal of Research and Practice in Information Technology, 39(4), 34-67. 50.Lin, C.-P., & Bhattacherjee, A. (2010). Extending technology usage models to interactive hedonic technologies: a theoretical model and empirical test. Information Systems Journal, 20(2), 163-181. 51.Luarna, P., & Lin, H.-H. (2005). Toward an understanding of the behavioural intention to use mobile banking. Computers in Human Behavior, 21(6), 873-891. 52.Market Intelligence & Consulting Institute. (2016). Mobile payment consumer survey. [Web document]. Available: https://mic.iii.org.tw/IndustryObservations_PressRelease02.aspx?sqno=425 [2016, 06 Nov] 53.Mansour, K. B. (2016). An analysis of business’ acceptance of internet banking: an integration of e-trust to the TAM. Journal of Business & Industrial Marketing, 31(8), 982-994. 54.Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web Context. Information & Management, 38(4), 217–230. 55.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. 56.Moschis, G. P., Goldstucker, J. L., & Stanley, T. J. (1985). At-home shopping: Will consumers let their computers do the walking? Business Horizons, 28(2), 22-29. 57.Ngai, E. W. T., Poon, J. K. L., & Chan, Y. H. C. (2007). Empirical examination of the adoption of WebCT using TAM. Computers and Education, 48(2), 250-267. 58.Nielsen. (2014). Nelson: Less than 40% of Taiwan consumers spend their daily preferences on plastic currency payments. [Web document]. Available: http://www.nielsen.com/tw/zh/press-room/2014/newsTaiwanPayment0225.html [2016, 01 Nov] 59.O’Cass, A., & Fenech, T. (2003). Web retailing adoption: exploring the nature of internet users Web retailing behaviour. Journal of Retailing and Consumer Services, 10(2), 81-94. 60.Oh, S., Ahn, J., & Kim, B. (2003). Adoption of broadband Internet in Korea: the role of experience in building attitudes. Journal of Information Technology, 18(4), 267-280. 61.Ozkan, S., Bindusara, G., & Hackney, R. (2004). Facilitating the adoption of e‐payment systems: theoretical constructs and empirical analysis. Journal of Enterprise Information Management, 23(3), 305-325. 62.Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). E-S-QUAL: a multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213-233. 63.Park, S. Y. (2009). An Analysis of the Technology Acceptance Model in Understanding University Students’ Behavioral Intention to Use e-Learning Educational Technology & Society, 12(3), 150-162. 64.Pavlou, P., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: an extension of the theory of planned behavior. MIS Quarterly, 30(1), 115-143. 65.Plouffe, C. R., Vandenbosch, M., & Hulland, J. (2001). Intermediating technologies and multi-group adoption: A comparison of consumer and merchant adoption intentions toward a new electronic payment system. Journal of Product Innovation Management, 18(2), 65-81. 66.Porter, C. E., & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59(9), 999–1007. 67.Rogers, E. M. (1995). Diffusion of Innovations (Fourth ed.). New York: Free Press. 68.Tarhini, A., Hone, K., Liu, X., & Tarhini, T. (2017). Examining the moderating effect of individual-level cultural values on users’ acceptance of E-learning in developing countries: a structural equation modeling of an extended technology acceptance model. Interactive Learning Environments, 25(3), 306-328. 69.Schneider, F. (2013). The Shadow Economy in Europe, 2013. [Web document]. Available: https://www.atkearney.com/documents/10192/1743816/The+Shadow+Economy+in+Europe+2013.pdf [2016, 12 Dec] 70.Sekaran, U., & Bougie, R. (2010). Research Methods for Business: A Skill Building Approach. United Kingdom: John Wiley & Sons. 71.Slyke, C. V., Belanger, F., & Comunale, C. L. (2004). Factors influencing the adoption of web-based shopping: the impact of trust. ACM SIGMIS Database, 35(2), 32-49. 72.Stern, B. B., Royne, M. B., Stafford, T. F., & Bienstock, C. C. (2008). Consumer Acceptance of Online Auctions: An Extension and Revision of the TAM. Psychology and Marketing, 25(7), 619–636. 73.Stroborn, K., Heitmann, A., Leibold, K., & Frank, G. (2004). Internet payments in Germany: a classificatory framework and empirical evidence. Journal of Business Research, 57(12), 1431–1437. 74.Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176. 75.Tee, H.-H., & Ong, H.-B. (2016). Cashless payment and economic growth. Financial Innovation, 2(1), 4-13. 76.Tong, X. (2010). Across-national Investigation of an Extended Technology Acceptance Model in the Online Shopping Contenxt. Retail and Distribution Management, 38(10), 742-759. 77.Udo, G. J., Bagchi, K. K., & Kirs, P. J. (2010). An assessment of customers’ e-service quality perception, satisfaction and intention. International Journal of Information Management, 30(6), 481–492. 78.Venkatesh, V. (2000). Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research, 11(4), 342-365. 79.Venkatesh, V. (2001). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365. 80.Venkatesh, V., & Davis, F. D. (1996). A Model of the Antecedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27(3), 451-481. 81.Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186-204. 82.Verhoefa, P. C., & Langerak, F. (2001). Possible determinants of consumers’ adoption of electronic grocery shopping in the Netherlands. Journal of Retailing and Consumer Services, 8(5), 275–285. 83.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 Behaviour, 7(2), 101-110. 84.Wang, H., & Zhang, Y. (2001). Untraceable Off-line Electronic Cash Flow in E-Commerce. 191-198. 85.Whiteley, D. (2000). E-Commerce: Strategy, Technologies And Applications. London: McGraw‐Hill International. 86.Wright, D. (2002). Comparative Evaluation Of Electronic Payment Systems. INFOR, 40(1), 71-85. 87.Wu, J.-H., & Wang, S.-C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729. 88.Yang, H.-d., & Yoo, Y. (2004). It’s all about attitude: revisiting the technology acceptance model. Decision Support Systems, 38(1), 19-31. 89.Yenisey, M., Ozok, A., & Salvendy, G. (2005). Perceived security determinants in e-commerce among Turkish university students. Behaviour & Information Technology, 24(4), 259-274. 90.Yoon, Y., & Uysal, M. (2005). An examination of the effects of motivation and satisfaction on destination loyalty: a structural model. Tourism Management, 26(1), 45-56. 91.Zandi, M., Singh, V., & Irving, J. (2013). The Impact of Electronic Payments on Economic Growth. [Web document]. Available: http://www.nocash.info.ro/wp-content/uploads/2013/02/moodys-economy-white-paper1.pdf [2016, 11 Nov]
|