참고문헌
- Al-Gahtani, S. S., & King, M. (1999). Attitudes, satisfaction and usage: Factors contributing to each in the acceptance of information technology. Behaviour & Information Technology, 18(4), 277-297. https://doi.org/10.1080/014492999119020
- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
- Bae, J. K. (2018). A study on the determinant factors of innovation resistance and innovation acceptance on internet primary bank services: Combining the theories of innovation diffusion and innovation resistance. The e-Business Studies, 19(2), 91-104. https://doi.org/10.20462/TeBS.2018.4.19.2.91
- Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of Political Economy, 100(5), 992-1026. http://dx.doi.org/10.1086/261849
- Bonabeau, E. (2004). The perils of the imitation age. Harvard Business Review, 82(6), 45-54.
- Breckler, S. J. (1984). Empirical validation of affect, behavior, and cognition as distinct components of attitude. Journal of Personality and Social Psychology, 47(6), 1191-1205. https://doi.org/10.1037/0022-3514.47.6.1191
- Chang, E. J., & Kim, J. K. (2017). What makes people keep using Fintech payment service? In the perspective of herding behavior theory and trust. The e-Business Studies, 18(2), 197-212. http://dx.doi.org/10.20462/TeBS.2017.04.18.2.197
- Chen, Y. F. (2008). Herd behavior in purchasing books online. Computers in Human Behavior, 24 (5), 1977-1992. https://doi.org/10.1016/j.chb.2007.08.004
- Chen, Y. F., & Wang, Y. J. (2010). Effect of herd cues and product involvement on bidder online choices. Cyberpsychology, Behavior, and Social Networking, 13(4), 423-428. https://doi.org/10.1089/cyber.2009.0304
- Choi, B. K. (2008). The effects of coffee shop image and perceived value on customer switching intentions and repurchasing intentions: Focused on the mediating effects of customer satisfaction (Unpublished master's thesis). Saejong University, Seoul, Korea.
- 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. https://doi.org/10.1287/mnsc.35.8.982
- de Luna, I. R., Liebana-Cabanillas, F., Sanchez-Fernandez, J., & MunozLeiva, F. (2019). Mobile payment is not all the same: The adoption of mobile payment systems depending on the technology applied. Technological Forecasting and Social Change, 146, 931-944. https://doi.org/10.1016/j.techfore.2018.09.018
- Ding, A. W., & Li, S. (2019). Herding in the consumption and purchase of digital goods and moderators of the herding bias. Journal of the Academy of Marketing Science, 47(3), 460-478. https://doi.org/10.1007/s11747-018-0619-0
- Elkaseh, A. M., Wong, K. W., & Fung, C. C. (2016). Perceived ease of use and perceived usefulness of social media for e-learning in Libyan higher education: A structural equation modeling analysis. International Journal of Information and Education Technology, 6(3), 192-199. https://doi.org/10.7763/IJIET.2016.V6.683
- 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. https://doi.org/10.1177/002224378101800104
- Gupta, A., Su, B. C., & Walter, Z. (2004). Risk profile and consumer shopping behavior in electronic and traditional channels. Decision Support Systems, 38(3), 347-367. https://doi.org/10.1016/j.dss.2003.08.002
- Ha, J., Park, K., & Park, J. (2016). Which restaurant should I choose? Herd behavior in the restaurant industry. Journal of Foodservice Business Research, 19(4), 396-412. https://doi.org/10.1080/15378020.2016.1185873
- Ha, L. D., & Lee, H. S. (2015). Perceived risk and user resistance of mobile wallet service. Entrue Journal of Information Technology, 14(3), 115-129.
- Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis. Upper Saddle River, NJ: Pearson Prentice Hall
- Hsu, C. L., & Lin, J. C. C. (2016). An empirical examination of consumer adoption of internet of things services: Network externalities and concern for information privacy perspectives. Computers in Human Behavior, 62, 516-527. https://doi.org/10.1016/j.chb.2016.04.023
- Huang, J. H., & Chen, Y. F. (2006). Herding in online product choice. Psychology & Marketing, 23(5), 413-428. https://doi.org/10.1002/mar.20119
- Hwang, H. J., & Kim, J. K. (2018). The study on the user resistance intention of mobile easy money transfer service. The e-Business Studies, 19(1), 135-153. https://doi.org/10.20462/TeBS.2018.2.19.1.135
- Jiang, Y., Ho, Y. C., Yan, X., & Tan, Y. (2018). Investor platform choice: Herding, platform attributes, and regulations. Journal of Management Information Systems, 35(1), 86-116. https://doi.org/10.1080/07421222.2018.1440770
- Johnson, V. L., Kiser, A., Washington, R., & Torres, R. (2018). Limitations to the rapid adoption of m-payment services: Understanding the impact of privacy risk on m-payment services. Computers in Human Behavior, 79, 111-122. https://doi.org/10.1016/j.chb.2017.10.035
- Jung, J. Y., Jeong, H. Y., & Jo, H. (2018). An empirical study on the acceptance-resistance motivation to use a mobile payment service: Applying multivariate discriminant analysis. The Journal of Information Systems, 27(3), 115-134. https://doi.org/10.5859/KAIS.2018.27.2.115
- Jung, B. N., Kim, S. W., & Kang, H. T. (2012). An empirical study on the use of and resistance to an enterprise resources planning system: Focused on the public company A. Management Education Review, 27(3), 397-420.
- Jung, Y. H., Kim, G., & Lee, C. J. (2015). Factors influencing user satisfaction and continuous usage intention on mobile credit card: Based on innovation diffusion theory and post acceptance model. The Journal of Society for e-Business Studies, 20(3), 11-28. https://doi.org/10.7838/jsebs.2015.20.3.011
- Kaushik, A. K., Agrawal, A. K., & Rahman, Z. (2015). Tourist behaviour towards self-service hotel technology adoption: Trust and subjective norm as key antecedents. Tourism Management Perspectives, 16, 278-289. https://doi.org/10.1016/j.tmp.2015.09.002
- Kim, D., & Kim, S. (2011). Factors influencing users' resistance to location based SNS application for smart phones. Korean Journal of Broadcasting and Telecommunication Studies, 25(3), 133-166.
- Kim, H. J. (2010). Study on healthcare service quality in health examination center affecting on switching intention (Unpublished master's thesis). Kyunghee University, Seoul, Korea.
- Kim, H. J., & Lee, S. S. (2019). Consumers' acceptance and resistance to virtual bank: views of non-users. Family and Environment Research, 57(2), 171-183. https://doi.org/10.6115/fer.2019.012
- Kim, H. J., & Rha, J. Y. (2017). Consumer resistance to smartwatches: Gender and age differences. The Journal of the Korea Contents Association, 17(12), 447-460. https://doi.org/10.5392/JKCA.2017.17.12.447
- Kim, H. W., Noh, S. E., Lee, Y. L., & Kwahk, K. Y. (2009). The effect of switching costs on user resistance in the adoption of open source software. Information Systems Review, 11(3), 125-146.
- Kim, J. K., & Kim, J. S. (2012, 06). The relationship of innovation diffusion: Characteristics of social construct which is Smartphone based mobile banking service. Paper presented at the 14th Conference of the Information Systems Review, Seoul, Korea.
- Kim, M. S., Kim, H. J., Kim, M. O., & Kim, H. J. (2010). A study on the user resistance to IPTV. The Journal of Society for e-Business Studies, 15(2), 205-217.
- 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. https://doi.org/10.1080/02642069.2015.1043278
- Kwon, S. H., & Lim, Y. W. (2012). A study for rejection and acceptance for information technology innovative products: Based on Smart phone usage intention of General mobile phone users. Journal of the Korea Society of Computer and Information, 17(1), 219-226. https://doi.org/10.9708/jksci.2012.17.1.219
- Lazarus, R. S. (1984). On the primacy of cognition. American Psychologist, 39(2), 124-129. https://doi.org/10.1037/0003-066X.39.2.124
- Lee, S. Y., & Park, J. W. (2016). A study on the intention of the use of mobile payment services: Application of the technology acceptance model. Korean Management Science Review, 33(2), 65-74. https://doi.org/10.7737/KMSR.2016.33.2.065
- Lee, H., Lee, S. H., & Chang, B. H. (2012). Factors affecting the resistance of DTV adoption; Combining the theory of diffusion of innovation and innovation resistance model. Journal of Broadcasting and Telecommunications Research, 2012(10) 78-111.
- Lee, J., & Hong, I. B. (2016). Predicting positive user responses to social media advertising: The roles of emotional appeal, informativeness, and creativity. International Journal of Information Management, 36(3), 360-373. https://doi.org/10.1016/j.ijinfomgt.2016.01.001
- Lee, S. B., Wang, Y. Q., & Suh, Y. H. (2015). Editorial: General quality research; Factors affecting the mobile instant messenger satisfaction, loyalty, and switching intention. Journal of Korean Society for Quality Management, 43(4), 545-558. https://doi.org/10.7469/JKSQM.2015.43.4.545
- Liebana-Cabanillas, F., Marinkovic, V., de Luna, I. R., & Kalinic, Z. (2018). Predicting the determinants of mobile payment acceptance: A hybrid sem-neural network approach. Technological Forecasting and Social Change, 129, 117-130. https://doi.org/10.1016/j.techfore.2017.12.015
- Liu, L. (2019). An empirical study on consumption propensity, selective attribute of mobile payment services and behavior intention: Focusing on Chinese consumers. The e-Business Studies, 20(2), 3-17.
- Liu, D., Brass, D., Lu, Y., & Chen, D. (2015). Friendships in online peerto-peer lending: Pipes, prisms, and relational herding. Mis Quarterly, 39(3), 729-742. http://dx.doi.org/10.2139/ssrn.2251155
- Liu, Y., Zhang, X., Zhang, Y., & Qiub, C. (2018, November). Research on influencing factors of consumer shopping behavior in online shopping festival . Paper presented at the 4th International Conference on Management Science and Engineering (MSE2018), Chongqing, Tianjin Normal University, China.
- Min, Q., & Kim, E. H. (2019). A study on factors influencing the continuous use intention of mobile easy payment service: Integration of information system post acceptance model and value model. The Journal of Information Systems, 28(1), 155-181. https://doi.org/10.5859/KAIS.2019.28.1.155
- Moon, M. A., Khalid, M. J., Awan, H. M., Attiq, S., Rasool, H., & Kiran, M. (2017). Consumer's perceptions of website's utilitarian and hedonic attributes and online purchase intentions: A cognitive-affective attitude approach. Spanish Journal of Marketing-ESIC, 21(2), 73-88. https://doi.org/10.1016/j.sjme.2017.07.001
- Mowen, J. C., & Minor, M. (1995). Customer behavior. Upper Saddle River, New Jersey: Prentice Hall.
- Mzoughi, N., & M'Sallem, W. (2013). Predictors of internet banking adoption: Profiling Tunisian postponers, opponents and rejectors. International Journal of Bank Marketing, 31(5), 388-408. https://doi.org/10.1108/IJBM-10-2012-0105
- Ooi, K. B., & Tan, G. W. H. (2016). Mobile technology acceptance model: An investigation using mobile users to explore smartphone credit card. Expert Systems with Applications, 59 , 33-46. https://doi.org/10.1016/j.eswa.2016.04.015
- Park, S. C., & Chae, S. W. (2014). A study on user's resist and productivity using smart device in the smartwork context. The Journal of Information Systems, 23(3), 143-164. https://doi.org/10.5859/KAIS.2014.23.3.143
- Qasim, M., Hussain, R., Mehboob, I., & Arshad, M. (2019). Impact of herding behavior and overconfidence bias on investors' decisionmaking in Pakistan. Accounting, 5(2), 81-90. https://doi.org/10.5267/j.ac.2018.7.001
- Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovations: The marketing problem and its solutions. Journal of Consumer Marketing, 6(2), 5-14. https://doi.org/10.1108/EUM0000000002542
- Rao, H., Greve, H. R., & Davis, G. F. (2001). Fool's gold: Social proof in the initiation and abandonment of coverage by wall street analysts. Administrative Science Quarterly, 46(3), 502-526. https://doi.org/10.2307/3094873
- Raza, S. A., Umer, A., & Shah, N. (2017). New determinants of ease of use and perceived usefulness for mobile banking adoption. International Journal of Electronic Customer Relationship Management, 11(1), 44-65. https://doi.org/10.1504/IJECRM.2017.086751
- Rivera, M., Gregory, A., & Cobos, L. (2015). Mobile application for the timeshare industry: The influence of technology experience, usefulness, and attitude on behavioral intentions. Journal of Hospitality and Tourism Technology, 6(3), 242-257. https://doi.org/10.1108/JHTT-01-2015-0002
- Rogers, E. M. (2010). Diffusion of Innovation. New York, The Free Press.
- Ryu, S., Hong, M. G., & Lee, J. K. (2018). A study on factors influencing the use intention of mobile payment service based biometric authentication. Korean Management Science Review, 35(4), 65-86. https://doi.org/10.7737/KMSR.2018.35.4.065
- Salawu, K. J., Hammedi, W., & Castiaux, A. (2019). What about passive innovation resistance? Exploring user's resistance to technology in the healthcare sector. Journal of Innovation Economics Management, 30(3), 17-37.
- Sharma, S. K., Mangla, S. K., Luthra, S., & Al-Salti, Z. (2018). Mobile wallet inhibitors: Developing a comprehensive theory using an integrated model. Journal of Retailing and Consumer Services, 45, 52-63. https://doi.org/10.1016/j.jretconser.2018.08.008
- Slade, E. L., Williams, M. D., & Dwivedi, Y. K. (2013). Mobile payment adoption: Classification and review of the extant literature. The Marketing Review, 13(2), 167-190. https://doi.org/10.1362/146934713X13699019904687
- Solomon, M. R., & Rabolt, N. J. (2007). Consumer behavior: In fashion. London: Prentice Hall.
- Song, H., Jung, J. W., & Jung, J. (2016). Factors affecting web developers' resistance to HTML5 adoption. Korean Management Review, 45(3), 925-945. http://dx.doi.org/10.17287/kmr.2016.45.3.925
- Song, J., & Qu, H. (2019). How does consumer regulatory focus impact perceived value and consumption emotions? International Journal of Contemporary Hospitality Management, 31(1), 285-308. https://doi.org/10.1108/IJCHM-03-2017-0136
- Sun, H. (2013). A longitudinal study of herd behavior in the adoption and continued use of technology. Mis Quarterly, 37(4), 1013-1041. https://doi.org/10.25300/MISQ/2013/37.4.02
- Sung, S. J. (2019, April 17). Increasing easy payment. Digital Times. Retrieved January 20, 2020, from http://www.dt.co.kr/contents.html?article_no=2019041802100151029001
- Talke, K., & Heidenreich, S. (2014). How to overcome pro change bias: Incorporating passive and active innovation resistance in innovation decision models. Journal of Product Innovation Management, 31(5), 894-907. https://doi.org/10.1111/jpim.12130
- 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(2), 137-155. https://doi.org/10.1016/0167-8116(94)00019-K
- The Bank of Korea. (2019). Retrieve January 20, 2020, from http://www.bok.or.kr/portal/main/main.do
- 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. http://doi.org/10.2307/30036540
- Wang, G., Dou, W., & Zhou, N. (2008). Consumption attitudes and adoption of new consumer products: A contingency approach. European Journal of Marketing, 42(1/2), 238-254. https://doi.org/10.1108/03090560810840998
- 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. https://doi.org/10.1016/j.chb.2011.08.019
- Yoon, S. K., Kim, M. J., & Choi, J. H. (2014). Effects of innovation characteristics and user characteristics on the adopting e-books: Focused on innovation resistance model. The Journal of the Korea Contents Association, 14(8), 61-73. https://doi.org/10.5392/JKCA.2014.14.08.061
- Zhang, T. L., & Lee, J. H. (2016). A study on the use intention of easy mobile payment services. The e-Business Studies, 17(6), 203-218. https://doi.org/10.20462/tebs.2016.12.17.6.203