參考文獻 |
[1] Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision sciences, 30(2), 361-391.
[2] Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (pp. 11-39): Springer.
[3] Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
[4] Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418-430.
[5] Bauer, R. A. (1960). Consumer behavior as risk taking. Paper presented at the Proceedings of the 43rd National Conference of the American Marketing Assocation, June 15, 16, 17, Chicago, Illinois, 1960.
[6] Bond, R., & Smith, P. B. (1996). Culture and conformity: A meta-analysis of studies using Asch′s (1952b, 1956) line judgment task. Psychological bulletin, 119(1), 111.
[7] Brown, I., Cajee, Z., Davies, D., & Stroebel, S. (2003). Cell phone banking: predictors of adoption in South Africa—an exploratory study. International journal of information management, 23(5), 381-394.
[8] 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, 399-426.
[9] Chandra, S., Srivastava, S. C., & Theng, Y.-L. (2010). Evaluating the role of trust in consumer adoption of mobile payment systems: An empirical analysis. CAIS, 27(29), 27.
[10] Chen, K.-Y., & Chang, M.-L. (2013). User acceptance of ‘near field communication’mobile phone service: an investigation based on the ‘unified theory of acceptance and use of technology’model. The Service Industries Journal, 33(6), 609- 623.
[11] Chen, L.-d. (2008). A model of consumer acceptance of mobile payment. International Journal of Mobile Communications, 6(1), 32-52.
[12] Cox, D. F., & Rich, S. U. (1964). Perceived risk and consumer decision-making: The case of telephone shopping. Journal of marketing research, 32-39.
[13] Csikszentmihalyi, M. (1990). Flow. The Psychology of Optimal Experience. New York (HarperPerennial) 1990.
[14] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
[15] 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, 22(14), 1111- 1132.
[16] Dimitriadis, S., & Kyrezis, N. (2011). The effect of trust, channel technology, and transaction type on the adoption of self-service bank channels. The Service Industries Journal, 31(8), 1293-1310.
[17] Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers′ product evaluations. Journal of marketing research, 307-319.
[18] Dowling, G. R., & Staelin, R. (1994). A model of perceived risk and intended risk- handling activity. Journal of consumer research, 21(1), 119-134.
[19] Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International journal of human-computer studies, 59(4), 451-474.
[20] Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research.
[21] Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.
[22] Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis. In (6 ed.): New Jersey: Prentice Hall.
[23] Hofstede, G. (1980). Culture and organizations. International Studies of Management & Organization, 10(4), 15-41.
[24] Hofstede, G. (1984). Culture′s consequences: International differences in work-related values (Vol. 5): sage.
[25] Hofstede, G. (1994). The business of international business is culture. International business review, 3(1), 1-14.
[26] Hofstede, G. (1998). Attitudes, values and organizational culture: Disentangling the concepts. Organization studies, 19(3), 477-493.
[27] Hofstede, G. (2011). Dimensionalizing cultures: The Hofstede model in context. Online readings in psychology and culture, 2(1), 8.
[28] Hofstede, G., & Bond, M. H. (1988). The Confucius connection: From cultural roots to economic growth. Organizational dynamics, 16(4), 5-21.
[29] Hongxia, P., Xianhao, X., & Weidan, L. (2011). Drivers and barriers in the acceptance of mobile payment in China. Paper presented at the E-Business and E-Government (ICEE), 2011 International Conference on.
[30] Huang, C.-Y., Kao, Y.-S., Wu, M.-J., & Tzeng, G.-H. (2013). Deriving factors influencing the acceptance of Pad Phones by using the DNP based UTAUT2 framework. Paper presented at the Technology Management in the IT-Driven Services (PICMET), 2013 Proceedings of PICMET′13:.
[31] Hussain Chandio, F., Irani, Z., Abbasi, M. S., & Nizamani, H. A. (2013). Acceptance of online banking information systems: an empirical case in a developing economy. Behaviour & Information Technology, 32(7), 668-680.
[32] Jordan, J. V., & Surrey, J. L. (1986). The self-in-relation: Empathy and the mother- daughter relationship.
[33] Keramati, A., Taeb, R., Larijani, A. M., & Mojir, N. (2012). A combinative model of behavioural and technical factors affecting ‘Mobile’-payment services adoption: an empirical study. The Service Industries Journal, 32(9), 1489-1504.
[34] 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.
[35] Kim, S. S., & Malhotra, N. K. (2005). Predicting system usage from intention and past use: scale issues in the predictors. Decision sciences, 36(1), 187-196.
[36] Koenig-Lewis, N., Marquet, M., Palmer, A., & Zhao, A. L. (2015). Enjoyment and social influence: predicting mobile payment adoption. The Service Industries Journal, 35(10), 537-554.
[37] Koenig-Lewis, N., Palmer, A., & Moll, A. (2010). Predicting young consumers′ take up of mobile banking services. International journal of bank marketing, 28(5), 410-432.
[38] Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information systems research, 13(2), 205-223.
[39] Lapointe, L., & Rivard, S. (2005). A multilevel model of resistance to information technology implementation. MIS quarterly, 461-491.
[40] Lee, R., Murphy, J., & Swilley, E. (2009). The moderating influence of hedonic consumption in an extended theory of planned behaviour. The Service Industries Journal, 29(4), 539-555.
[41] Lim, N. (2003). Consumers’ perceived risk: sources versus consequences. Electronic Commerce Research and Applications, 2(3), 216-228.
[42] Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS quarterly, 705- 737.
[43] Lu, Y., Yang, S., Chau, P. Y., & Cao, Y. (2011). Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. Information & Management, 48(8), 393-403.
[44] Lunsford, D. A., & Burnett, M. S. (1992). Marketing product innovations to the elderly: Understanding the barriers to adoption. Journal of Consumer Marketing, 9(4), 53-62.
[45] Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision support systems, 49(2), 222-234.
[46] Mathieson, K., Peacock, E., & Chin, W. W. (2001). Extending the technology acceptance model: the influence of perceived user resources. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 32(3), 86-112.
[47] Mehra, R. (2010). Paying for goods and services using a mobile phone: Exploring mobile payment use and adoption. Auckland University of Technology,
[48] Miyazaki, A. D., & Fernandez, A. (2000). Internet privacy and security: An examination of online retailer disclosures. Journal of Public Policy & Marketing, 19(1), 54-61.
[49] Nunally, J. (1978). Psychometric. McGraw Hill, New YorkOCallaghan R, Kaufmann P, Konsynski (1992) Adoption correlates and share effects of electronic data interchange systems in marketing channels. J Mark, 56, 4556Parkhe.
[50] Nysveen, H., Pedersen, P. E., Thorbjørnsen, H., & Berthon, P. (2005). Mobilizing the brand: The effects of mobile services on brand relationships and main channel use. Journal of Service Research, 7(3), 257-276.
[51] Pedersen, P. E. (2005). Adoption of mobile Internet services: An exploratory study of mobile commerce early adopters. Journal of organizational computing and electronic commerce, 15(3), 203-222.
[52] Pookulangara, S., & Koesler, K. (2011). Cultural influence on consumers′ usage of social networks and its′ impact on online purchase intentions. Journal of Retailing and Consumer Services, 18(4), 348-354.
[53] Ram, S. (1987). A model of innovation resistance. ACR North American Advances.
[54] Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovations: the marketing
problem and its solutions. Journal of Consumer Marketing, 6(2), 5-14.
[55] Refaat El Said, G., & Galal-Edeen, G. H. (2009). The role of culture in e-commerce use
for the Egyptian consumers. Business Process Management Journal, 15(1), 34-47.
[56] Riquelme, H. E., & Rios, R. E. (2010). The moderating effect of gender in the adoption
of mobile banking. International journal of bank marketing, 28(5), 328-341.
[57] Roberts, A. R. (1991). Contemporary perspectives on crisis intervention and prevention: Prentice Hall.
[58] Rouibah, K. (2008). Social usage of instant messaging by individuals outside the workplace in Kuwait: A structural equation model. Information Technology & People, 21(1), 34-68.
[59] Rouibah, K., & Abbas, H. (2011). Effect of personal innovativeness, attachment motivation and social norms on the acceptance of camera mobile phones: an empirical study in an Arab country. International Journal of Handheld Computing Research (IJHCR), 2(1), 72-93.
[60] Rouibah, K., Lowry, P. B., & Hwang, Y. (2016). The effects of perceived enjoyment and perceived risks on trust formation and intentions to use online payment systems: New perspectives from an Arab country. Electronic Commerce Research and Applications, 19, 33-43.
[61] Sheth, J. N. (1981). PSYCHOLOGY OF INNOVATION RESISTANCE: THE LESS DEVELOPED CONCEPT (LDC) IN DIFFUSION RESEARCH. In Research in Marketing, 273-382.
[62] Shin, D.-H. (2010). Modeling the interaction of users and mobile payment system: Conceptual framework. International Journal of Human-Computer Interaction, 26(10), 917-940.
[63] Slade, E., Williams, M., Dwivedi, Y., & Piercy, N. (2015). Exploring consumer adoption of proximity mobile payments. Journal of Strategic Marketing, 23(3), 209-223.
[64] Sorrentino, R. M., Bobocel, D. R., Gitta, M. Z., Olson, J. M., & Hewitt, E. C. (1988). Uncertainty orientation and persuasion: Individual differences in the effects of personal relevance on social judgments. Journal of Personality and social Psychology, 55(3), 357- 371.
[65] Sripalawat, J., Thongmak, M., & Ngramyarn, A. (2011). M-banking in metropolitan Bangkok and a comparison with other countries. Journal of computer information systems, 51(3), 67-76.
[66] Srite, M., & Karahanna, E. (2006). The role of espoused national cultural values in technology acceptance. MIS quarterly, 679-704.
[67] Srivastava, S. C., Chandra, S., & Theng, Y.-L. (2010). Evaluating the role of trust in consumer adoption of mobile payment systems: An empirical analysis. Communications of the Association for Information Systems, 27, 561-588.
[68] Straub, D., Loch, K., Evaristo, R., Karahanna, E., & Srite, M. (2002). Toward a theory- based measurement of culture. Human factors in information systems, 10(1), 61-65.
[69] Sun, Q., Cao, H., & You, J. (2010). Factors influencing the adoption of mobile service in China: An integration of TAM. JCP, 5(5), 799-806.
[70] Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176.
[71] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
[72] Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.
[73] 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.
[74] Yang, S., Lu, Y., Gupta, S., Cao, Y., & Zhang, R. (2012). Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits. Computers in Human Behavior, 28(1), 129-142.
[75] Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision support systems, 54(2), 1085-1091.
[76] 許傳勇. (2017). 以延伸科技接受模式探討消費者使用行動支付意圖. 東吳大學
[77] 黃敬玶. (2015). 運用 UTAUTII探討消費者對行動支付之接受程度. 國立臺北科技大學
[77] 鍾興祺. (2015). 以科技接受模式探討使用者採用 NFC 行動支付之意圖. 國立高雄應用科技大學
[78] 羅巧娜. (2017). 以科技接受模型探討消費者行動支付之使用意圖. 東吳大學 |