Satisfaction and Continuous Use Intention of Internet-only Banks

케이뱅크와 카카오뱅크 이용자들의 만족도와 지속 사용 의도의 결정 요인

  • Kim, Hyo Jung (Konkuk University Social Science Research Institute) ;
  • Lee, Seung Sin (Konkuk University Department of Global Trade and Consumer)
  • 김효정 (건국대학교/사회과학연구소) ;
  • 이승신 (건국대학교/글로벌비지니스학부 글로벌통상.소비자전공)
  • Received : 2018.09.26
  • Accepted : 2018.12.18
  • Published : 2019.02.28


Internet-based financial services are being increasingly integrated into consumers' daily lives. Internet-only banks have emerged as a powerful tool accelerating financial inclusion. This study investigates the satisfaction and continuous use intention predictors for Internet-only banks. We employed an extended post-acceptance model and used six antecedent factors that included perceived usefulness, perceived ease of use, privacy risk, functional risk, subjective norms, and network externality. All 351 participants used Internet-only banks and were 20-40 years of age. A self-administration online survey was conducted. SPSS 23.0 analyzed the frequency, description, and multiple regression analysis. The results of current study are as follows. The education, perceived usefulness, perceived ease of use, and network externality positively influenced the satisfaction of Internet-only banks. Privacy risk negatively influenced satisfaction with Internet-only banks. Perceived ease of use, subjective norm, network externality, and satisfaction positively influenced the continuous use intention of Internet-only banks. The results of our study provide a better explanation of important factors that could enhance the understanding of satisfaction and continuous use intention for Internet-only banks. Furthermore, this study extends the antecedent variables to the knowledge of financial services and enlarges the understanding of users' post-adoption behaviors.


Supported by : National Research Foundation of Korea


  1. Aldosari, H. S., & MEKHEIMER, M. (2018). The bandwagon effect in the adoption of e-learning systems in language learning-an appraisal. GSTF Journal on Computing, 2(4), 61-81.
  2. 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 Association, 19(2), 91-104.
  3. Bae, Y., Park, S., & Lee, D. H. (2009). Network effects in the diffusion and consumption of internet media. Cybercommunication Academic Society, 26(1), 159-189.
  4. Bhattacherjee, A. (2001). Understanding and evaluating relevance in IS research. Communications of the Association for Information Systems, 6(1), 25-30.
  5. Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. MIS Quarterly, 28(2), 229-254.
  6. Cho, J. (2016). The impact of post-adoption beliefs on the continued use of health apps. International Journal of Medical Informatics, 87, 75-83.
  7. Choi, J. I. (2016). Introduction of the internet-only bank and development direction proposal. Journal of Digital Convergence, 14(9), 139-147.
  8. Chong, A. Y. L. (2013). Understanding mobile commerce continuance intentions: an empirical analysis of Chinese consumers. Journal of Computer Information Systems, 53(4), 22-30.
  9. Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61-80.
  10. Eriksson, K., & Nilsson, D. (2007). Determinants of the continued use of self-service technology: the case of Internet banking. Technovation, 27(4), 159-167.
  11. Ewe, S. Y., Yap, S. F., & Lee, C. K. C. (2015). Network externalities and the perception of innovation characteristics: mobile banking. Marketing Intelligence & Planning, 33(4), 592-611.
  12. Fan, Y. L., Chung, J. E., & Moon, H. C. (2018). An empirical study on the determinants of user satisfaction and continuous use intention of mobile payment services by Chinese consumers. International Commerce and Information Review, 20 (1), 277-296.
  13. 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.
  14. Gachter, S., Nosenzo, D., & Sefton, M. (2013). Peer effects in pro-social behavior: Social norms or social preferences? Journal of the European Economic Association, 11(3), 548-573.
  15. George, A., & Kumar, G. G. (2013). Antecedents of customer satisfaction in internet banking: Technology acceptance model (TAM) redefined. Global Business Review, 14(4), 627-638.
  16. Gunst, R. F., & Mason, R. L. (1980). Regression analysis and its application: a data-oriented approach (Vol. 34). New York: Marcel Dekker, Inc.
  17. Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1995). Multivariate data analyses with readings. New Jersey: Englewood Cliffs.
  18. Jang, H. Y., & Park, K. J. (2012). Impact of virtual competence and network effect on SNS continuous use intention: focus on the multidimensional perspective of virtual competence. The Journal of Internet Electronic Commerce Research, 12(2), 165-187.
  19. Jung, E. G., & Park, H. S. (2017). An empirical study on the user acceptance of internet primary bank based on UTAUT2. The e-Business Studies, 18(3), 75-95.
  20. Jun, J., & Yeo, E. (2015). Analysis on the effects of introduction of Korean internet bank from and industrial organizational perspective. Journal of Money & Finance, 29(4), 199-234.
  21. Jung, Y. H., Kim, G., & Lee, C. C. (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.
  22. Kim, B. (2011). Understanding antecedents of continuance intention in social-networking services. Cyberpsychology, Behavior, and Social Networking, 14(4), 199-205.
  23. Kim, D. H., & Park, N. (2016). Effects of OTT service users’use motivations on satisfaction and intention of continued use. Journal of Broadcasting and Telecommunication Research, 93, 77-110.
  24. Kim, D., & Kim, S. (2017). Factors to influence switching intention to Internet-only bank from legacy bank: focused on financial consumers'asset management. Information Society & Media, 18(1), 105-134.
  25. Kim, S. H., & Park, T. K. (2017). Acceptance factors of financial consumers on Internet Primary Banks. Journal of Industrial Economics Business, 30(2), 589-622.
  26. Ko, M. H., & Kwon, S. D. (2008). A study on the social network service. Industry and Management, 21(1), 1-17.
  27. Kotler, P., & Armstrong, G. (2012). Principles of marketing (14th Global Edition) New Jersey: Prentice Hall.
  28. Kwak, N. Y., Yoo, H. I., & Lee, C. C. (2018). Study on factors affecting financial customer's switching intention to internet only bank: focus on Kakao bank. Journal of Digital Convergence, 16(2), 157-167.
  29. Kwon, H. G., & Lee, M. B. (2018). A study of factors influencing on the intention to use Internet Primary Bank. Journal of the Korea Industrial Information, 23(1), 97-108.
  30. Lee, E. J., Kwon, K. N., & Schumann, D. W. (2005). Segmenting the non-adopter category in the diffusion of internet banking. International Journal of Bank Marketing, 23(5), 414-437.
  31. Lee, J. M. (2018). The effects of consumers'perceived value and network externality on continuous use intention of internet primary bank. Journal of Consumer Studies, 29(4), 139-159.
  32. Lee, S. I. (2018, January 04). Second year of Internet-only Banks. Digital daily. Retrieved September 10, 2018, from
  33. Lee, K., & Kim, S. I. (2018). A study on the factors affecting the reliability of user’s confidence in Korean internet professional bank: focused on Kakao Bank and K Bank. Journal of Korea Convergence Society, 9(1), 277-282.
  34. Liao, Z., & Cheung, M. T. (2008). Measuring consumer satisfaction in internet banking: a core framework. Communications of the ACM, 51(4), 47-51.
  35. Liebana-Cabanillas, F., Munoz-Leiva, F., & Rejon-Guardia, F. (2013). The determinants of satisfaction with e-banking. Industrial Management & Data Systems, 113(5), 750-767.
  36. Lin, H. F. (2011). An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust. International journal of information management, 31(3), 252-260.
  37. Lu, J., Yao, J. E., & Yu, C. S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245-268.
  38. 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.
  39. Moon, Y. H. (2017). Factors affecting intention to use Internet Primary Bank: An exploratory difference of demographic characteristics. The Journal of Business Education, 31(6), 95-108.
  40. Nam, S. W., & Hong, E. J. (2018). Gender difference on trust in Internet-only Banks using the multi-group path analysis. Journal of Convergence for Information Technology, 8(3), 99-105.
  41. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469.
  42. Park, C., & Ryu, D. (2018). Internet-only Banks: an introduction overview. Korean Management Review, 47(3), 549-576.
  43. Polites, G. L., & Karahanna, E. (2012). Shackled to the status quo: the inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS Quarterly, 36(1), 21-42.
  44. Seo, H. S., & Song, I. K. (2011). The study on the acceptance intention of smart and mobile device: Based on two-sided network effect. The KIPS Transactions: Part D, 18(4), 287-298.
  45. Son, Y. S. (2018, September 21). Internet-only Banks enter into a test board. ZDNet Korea. Retrieved September 20, 2018, from
  46. 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.
  47. 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.
  48. Yoo, H., An, J, & Lee, C. C. (2018). A study factors affecting continuance intention of internet only bank: Using task-technology fit theory. The Journal of Society for e-Business, 23(3), 111-128.
  49. Yoon, C. (2010). Antecedents of customer satisfaction with online banking in China: the effects of experience. Computers in Human Behavior, 26(6), 1296-1304.
  50. Yuan, S., Liu, Y., Yao, R., & Liu, J. (2016). An investigation of users’continuance intention towards mobile banking in China. Information Development, 32(1), 20-34.
  51. Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54(2), 1085-1091.
  52. Zhou, T. (2014). Understanding continuance usage intention of mobile internet sites. Universal Access in the Information Society, 13(3), 329-337.
  53. Zhu, K., Kraemer, K. L., Gurbaxani, V., & Xu, S. X. (2006). Migration to open-standard interorganizational systems: network effects, switching costs, and path dependency. Mis Quarterly, 30, 515-539.