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인터넷 전문은행 사용자의 금융서비스 전환 의도에 미치는 영향에 관한 연구: 케이뱅크와 카카오뱅크를 중심으로

A study on the effect of Internet Primary bank users on their intention to switch to financial services: Focusing on K-Bank and Kakao Bank

  • Park, YoungGeun (Dept. of Business Administration, Pusan National University) ;
  • Ok, SeokJae (Dept. of Business Administration, Pusan National University)
  • 투고 : 2021.11.15
  • 심사 : 2022.02.20
  • 발행 : 2022.02.28

초록

인터넷 전문은행 관련 선행연구들은 법안, 규제 그리고 도입 기대효과 등의 연구들이 대부분이며, 금융 소비자의 금융 서비스 전환 의도에 관한 연구는 미비한 상태이다. 본 연구의 목적은 금융소비자들이 시중은행에서 인터넷 전문은행으로 서비스 전환 의도에 대해 영향을 미치는 요인을 알아보고자 PPM(Push-Pull-Mooring)이론을 적용하였다. 실제 서비스 이용자들을 대상으로 설문조사를 하였고, Smart PLS 3.0을 사용하여 1차 요인분석과 2차 요인분석을 하였다. 연구 결과 풀요인, 푸시요인 그리고 무어링요인은 전환 의도에 긍정적인 영향을 미쳤으며, 조절변수인 무어링요인은 푸시요인과 풀요인의 전환 의도에 조절효과가 나타나지 않았다. 서비스 전환 연구에 활용되던 PPM이론의 활용 범위를 핀테크 서비스로 확장 하였고, 인터넷 전문은행의 전략과 확산 등 여러 가지 실무적인 유용한 시사점을 제공 할 수 있으며, 소비자 태도를 연구하는 다양한 연구에서 활용할 수 있을 것이다.

Most of the preceding studies related to Internet Primary banks are studies on laws, regulations, and expected effects of introduction, and studies on financial consumers' intention to switch to financial services are insufficient. Apply to the PPM(Push-Pull-Mooring)theory to find out the factors that influence financial consumers' intention to switch services from commercial banks to Internet Primary banks. A survey was conducted service users, 1st-order and 2nd-order factor analysis were performed using Smart PLS 3.0. As a result, it was confirmed that the Pull, Push and Mooring had a positive (+) effect on the Intention to Switch, and the Mooring, which is a moderating variable, did not have a moderating effect on the Intention to Switch of the Push and the Pull. The scope of application of the PPM theory, which was used in the service conversion research, was extended to Fintech services, and it can provide various practical useful implications, such as the strategy and spread of Internet Primary banks, and it will be used in various studies to study consumer attitudes.

키워드

과제정보

This work was supported by a 2-Year Research Grant of Pusan National University.

참고문헌

  1. Jeung, 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. https://doi.org/10.15719/GEBA.18.3.201706.75
  2. Kim, S. J., & Kim, C. B. (2017). A study on the relationships among SNS information characteristics, the characteristics of information provider and the intention to visit the restaurants: Focused on millennials generation. Korea Association of Business Education, 32(4), 279-299. https://doi.org/10.23839/kabe.2017.32.4.279
  3. Bansal, H., S., Taylor, S., F., & St. James, Y. (2005). "Migrating" to new service providers: Toward a unifying framework of consumers' switching behaviors. Journal of the Academy of Marketing Science, 33(1), 96-115. https://doi.org/10.1177/0092070304267928
  4. Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2002). Why customers stay: measuring the underlying dimensions of services switching costs and managing their differential strategic outcomes. Journal of business research, 55(6), 441-450. https://doi.org/10.1016/S0148-2963(00)00168-5
  5. Reichheld, F. F., & Sasser, W. E. (1990). Zero defeofions: Quoliiy comes to services. Harvard business review, 68(5), 105-111.
  6. Keaveney, S. M. (1995). Customer switching behavior in service industries: An exploratory study. Journal of marketing, 59(2), 71-82. https://doi.org/10.2307/1252074
  7. Fornell, C. (1992). A national customer satisfaction barometer: The Swedish experience. Journal of marketing, 56(1), 6-21. https://doi.org/10.2307/1252129
  8. Lattin, J. M., & McAlister, L. (1985). Using a variety-seeking model to identify substitute and complementary relationships among competing products. Journal of Marketing Research, 22(3), 330-339. https://doi.org/10.2307/3151429
  9. Njite, D., Kim, W. G., & Kim, L. H. (2008). Theorizing consumer switching behavior: A general systems theory approach. Journal of Quality Assurance in Hospitality & Tourism, 9(3), 185-218. https://doi.org/10.1080/15280080802412701
  10. Kim, J. W. (2010). A Study on The Switching Intention to the Internet Primary Bank affected by Internet Banking Users Satisfaction. Doctoral dissertation. Soongsil University, Seoul.
  11. Financial Supervisory Service. (2015). Plan to Support Convergence of Finance and Technology. Seoul : Financial Supervisory Service.
  12. 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.
  13. 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
  14. Park, C, J & Ryu, D, J. (2018). Internet-only Banks: An Introductory Overview. Korean Academic Society Of Business Administration, 47(3), 549-576.
  15. 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. https://doi.org/10.35736/jcs.29.4.7
  16. Amin, W., Parwani, A. V., Schmandt, L., Mohanty, S. K., Farhat, G., Pople, A. K., ... & Becich, M. J. (2008). National Mesothelioma Virtual Bank: a standard based biospecimen and clinical data resource to enhance translational research. BMC cancer, 8(1), 1-10. https://doi.org/10.1186/1471-2407-8-1
  17. Stokes, M. (2012). Globalization and the politics of world music. In The cultural study of music (pp. 129-138). Routledge.
  18. Diniz, E., Birochi, R., & Pozzebon, M. (2012). Triggers and barriers to financial inclusion: The use of ICT-based branchless banking in an Amazon county. Electronic Commerce Research and Applications, 11(5), 484-494. https://doi.org/10.1016/j.elerap.2011.07.006
  19. 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 Systems Research, 23(1), 97-108. https://doi.org/10.9723/JKSIIS.2018.23.1.097
  20. 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 the Korea Convergence Society, 9(1), 277-282. https://doi.org/10.15207/JKCS.2018.9.1.277
  21. Kim, S. R. (2017). A Review of Legal and Institutional issues related to the Establishment of an Internet professional bank. Korean Law Association, 17(3), 1-36.
  22. 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. https://doi.org/10.34274/KRABE.2017.31.6.005
  23. Kim, S. H., & Park, T. K. (2017). Acceptance factors of financial consumers on Internet Primary Banks. Journal of Industrial Economics and Business, 30(2), 589-622. https://doi.org/10.22558/jieb.2017.04.30.2.589
  24. Kwak, N. Y., Yoo, H., & 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. https://doi.org/10.14400/JDC.2018.16.2.157
  25. Kim, S. J., & Kim, C. B. (2018). The Effects of the Mobile-banking Characteristics and Internet-only bank Benefits on the Switching Value and the Use Intention. The Journal of the Korea Contents Association, 18(8), 109-117. https://doi.org/10.5392/JKCA.2018.18.08.109
  26. Kim, H. J., & Rha, J. Y. (2018). Consumers' adoption and resistance of branchless bank: Non-users perspective. Journal of Consumer Studies, 29(4), 97-118. https://doi.org/10.35736/jcs.29.4.5
  27. Lee, H. G., & Han, M. S. (2019). An Empirical Study on the Consumer Acceptance of Internet Primary Bank: The Application of UTAUT Model. The Journal of Business Education, 33(1), 59-87. https://doi.org/10.34274/krabe.2019.33.1.003
  28. Jung, J. H., & Shin, J. I. (2019). The Effect of Choice Attributes of Internet primary bank on Satisfaction and Behavioral Intention. Journal of The Korea Society of Computer and Information, 24(9), 143-150. https://doi.org/10.9708/jksci.2019.24.09.143
  29. Jung, J., & Cho, S. O. (2020). Relationship Between Perceived Risk and Continuous Use Intention of Internet Primary Banks: Moderating Effects of Acceptance Factors. Journal of Digital Convergence, 18(8), 133-149. https://doi.org/10.14400/JDC.2020.18.8.133
  30. Lee, S., & Lee, J. (2020). Why People Adopt the Virtual Bank?-An Empirical Study on Motivational Factors. Journal of Digital Convergence, 18(12), 205-216. https://doi.org/10.14400/JDC.2020.18.12.205
  31. Lewis, G. J. (1982). Human migration: a geographical perspective. Routledge.
  32. Longino, C. F. (1992). The forest and the trees: micro-level considerations in the study of geographic mobility in old age. Elderly migration and population redistribution, 23- 34.
  33. Moon, B. (1995). Paradigms in migration research: Exploring "moorings" as a schema. Progress in human geography, 19(4), 504-524. https://doi.org/10.1177/030913259501900404
  34. Chiu, H. C., Hsieh, Y. C., Roan, J., Tseng, K. J., & Hsieh, J. K. (2011). The challenge for multichannel services: Cross-channel free-riding behavior. Electronic Commerce Research and Applications, 10(2), 268-277. https://doi.org/10.1016/j.elerap.2010.07.002
  35. Kim, E., & Park, M. C. (2015). Antecedents of Cross-Channel Free-Riding Intention: The Moderating Effect of Product Categories Using Push-Pull-Mooring Framework. Proceedings of the Korea Society of Management Information Systems, 2015.
  36. Choi, H. S., & Yang, S. B. (2016). An empirical study on influencing factors of switching intention from online shopping to webrooming. Journal of Intelligence and Information Systems, 22(1), 19-41. https://doi.org/10.13088/JIIS.2016.22.1.019
  37. Zhang, K. Z., Lee, M. K., Cheung, C. M., & Chen, H. (2009). Understanding the role of gender in bloggers' switching behavior. Decision Support Systems, 47(4), 540-546. https://doi.org/10.1016/j.dss.2009.05.013
  38. Zengyan, C., Yinping, Y., & Lim, J. (2009, January). Cyber migration: An empirical investigation on factors that affect users' switch intentions in social networking sites. In 2009 42nd Hawaii International Conference on System Sciences (pp. 1-11). IEEE.
  39. Hou, A. C., Chern, C. C., Chen, H. G., & Chen, Y. C. (2011). 'Migrating to a new virtual world': Exploring MMORPG switching through human migration theory. Computers in Human Behavior, 27(5), 1892-1903. https://doi.org/10.1016/j.chb.2011.04.013
  40. Hsieh, J. K., Hsieh, Y. C., Chiu, H. C., & Feng, Y. C. (2012). Post-adoption switching behavior for online service substitutes: A perspective of the push-pull-mooring framework. Computers in Human Behavior, 28(5), 1912-1920. https://doi.org/10.1016/j.chb.2012.05.010
  41. Jung, J., Han, H., & Oh, M. (2015). Understanding Customer Switching Behavior in the Airline Industry : A Perspective of the Push-Pull-Mooring Framework. Korean Journal of Hospitality & Tourism, 24(1), 261-280
  42. Lim, B., & Yook, R. (2012). A comparative study on user satisfaction and service quality of mobile commerce service between Korea and China. The Journal of Internet Electronic Commerce Research, 12(4), 335-359.
  43. M. J. Noh. (2011). An effects of perceived risk and value on the trust and use intention of smart phone banking: Mediating effect of the trust. Korean Journal of Business Administration, 24(5), 2599-2615.
  44. J. Y. Yang, J. H. Ahn & C. W. Park. (2006). The effect of perceived risk on the intention to adopt mobile banking services. Journal of Technology Innovation, 14(3), 183-208.
  45. Carpenter, G. S., & Lehmann, D. R. (1985). A model of marketing mix, brand switching, and competition. Journal of marketing research, 22(3), 318-329. https://doi.org/10.2307/3151428
  46. Gerrard, P., & Cunningham, J. B. (2004). Consumer switching behavior in the Asian banking market. Journal of Services Marketing.
  47. Bitner, M. J. (1990). Evaluating service encounters: the effects of physical surroundings and employee responses. Journal of marketing, 54(2), 69-82. https://doi.org/10.2307/1251871
  48. Blinn, J. D., Duncan, S. R., & Goodwin, B. (1991). 1990 cost of risk survey: a yardstick for managers. Risk management, 38(2), 46.
  49. Lee, E. S. (1966). A theory of migration. Demography, 3(1), 47-57. https://doi.org/10.2307/2060063
  50. Stimson, R. J., & Minnery, J. (1998). Why people move to the'sun-belt': A case study of long-distance migration to the Gold Coast, Australia. Urban Studies, 35(2), 193-214. https://doi.org/10.1080/0042098984943
  51. Anton, C., Camarero, C., & Carrero, M. (2007). Analysing firms' failures as determinants of consumer switching intentions: The effect of moderating factors. European Journal of Marketing.
  52. Kim, J. K., & Lee, D. H. (2005). A research on information security risk-based antecedents influencing electronic commerce user's trust. Asia pacific journal of information systems, 15(2), 65-96.
  53. Swaminathan, V., Lepkowska-White, E., and Rao, B.P.(1999), "Browsers or Buyers in Cyberspace? An Investigation of Factors Influencing Electronic Exchange," Journal of Computer-Mediated Communication, 5(2)
  54. Kim, S. S., Lee, C. K., & Klenosky, D. B. (2003). The influence of push and pull factors at Korean national parks. Tourism management, 24(2), 169-180. https://doi.org/10.1016/S0261-5177(02)00059-6
  55. Kim, G., Shin, B., & Lee, H. G. (2006). A study of factors that affect user intentions toward email service switching. Information & Management, 43(7), 884-893. https://doi.org/10.1016/j.im.2006.08.004
  56. Kim, K., Seo, H., Yu, H., & Choi, J. (2017). A Study on the Factors Affecting Switching Intention of Public Certificate Storage: Focused on Smart Certificate (USIM). Journal of Information Technology Services, 16(1), 99-118. https://doi.org/10.9716/KITS.2017.16.1.099
  57. Choi, G. B. (2012). An Empirical Study on the Post Acceptance of Mobile Banking Service. The Journal of Internet Electronic Commerce Resarch, 12(3), 1-27.
  58. Han, H., & Hyun, S. S. (2013). Image congruence and relationship quality in predicting switching intention: Conspicuousnes of product use as a moderator variable. Journal of Hospitality & Tourism Research, 37(3), 303-329. https://doi.org/10.1177/1096348012436381
  59. Han, K. H. (2001). A study on the evolution of mobile business model. The 2X2.
  60. Kim, N. H., Kim, B. S., Seo, J. H., & Kim, J. K. (2008). A Preferencee Analysis of IT Components for Mobile Banking Service. Journal of Information Technology Services, 7(1), 89-101.
  61. Parasuraman, A., Zeithaml, V. A., & Berry, L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. 1988, 64(1), 12-40.
  62. Baek, T. H., & King, K. W. (2011). Exploring the consequences of brand credibility in services. Journal of Services Marketing.
  63. Kim, S. H. (2013). Moderating effects of switching cost on the IT service switching intention. The Journal of the Korea Contents Association, 13(10), 452-460. https://doi.org/10.5392/JKCA.2013.13.10.452
  64. Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
  65. 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/10.2307/3151312
  66. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Academic press.