Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
권호 표지
DOI QR코드

DOI QR Code

Relationship Between Perceived Risk and Continuous Use Intention of Internet Primary Banks : Moderating Effects of Acceptance Factors

인터넷전문은행의 지속적 이용의도에 있어서 지각된 위험의 영향력 : 수용요인의 조절효과 분석

  • Jung, Joowon (Department of Home Economics Education, Dongguk University) ;
  • Cho, SO Yeon (Department of Home Economics Education, Dongguk University)
  • 정주원 (동국대학교 사범대학 가정교육과) ;
  • 조소연 (동국대학교 사범대학 가정교육과)
  • Received : 2020.05.19
  • Accepted : 2020.08.20
  • Published : 2020.08.28
Download PDF
⟨ Previous Next ⟩

Abstract

The purpose of this study was to investigate the effect of perceived risk on continuous usage intention of Internet primary banks and to verify moderating effects of acceptance factors affecting customers' acceptance of Internet primary banks on the relationship between perceived risk and continuous usage intention. The study aims to find ways to cope with perceived risk and strategic measures of intention in order to increase the intention to continuous usage intention of Internet primary banks. For the analysis, interaction effect were conducted among a total of 457 surveys. As a results, First, perceived risks, acceptance factors and continuous usage intention of the customers of Internet primary banks were significantly correlated. Second, the types of perceived risks which have a significant effect on continued usage intention of Internet primary banks were found to be perceived financial and functional risks. Third, respect to moderating effects of moderator variables, usefulness was found to have a significant moderating effect on the relationship between perceived security risk and continuous usage intention. In addition, ease of use was shown to have a significant moderating effect on the relationship between each type of perceived risks and continuous usage intention. This study attempted to explore and seek strategies to reduce perceived risks and strategic plans for acceptance factors to increase continuous usage intention of Internet primary banks.

본 연구의 목적은 인터넷전문은행에 대한 지각된 위험이 지속적 이용의도에 미치는 영향을 분석하고, 지각된 위험과 지속적 이용의도의 관계에서 수용적 요인의 조절효과를 검증하는 것이다. 이를 통하여 인터넷전문은행의 지속적 이용의도를 높이기 위한 지각된 위험의 대처방안과 수용요인의 전략적 방안을 모색하고자 한다. 연구목적을 달성하기 위하여 인터넷전문은행 이용경험이 있는 20-50대 소비자 457명을 대상으로 중다회귀분석을 실시하였으며, 이를 근거로 수용요인의 상호작용효과를 분석하였다. 연구결과, 첫째, 인터넷전문은행이용 소비자의 지각된 위험, 수용요인과 지속적 이용의도 간에는 유의한 상관관계를 보였다. 둘째, 지각된 재무적, 기능적 위험은 인터넷전문은행의 지속적 이용의도에 유의한 영향을 미치는 것으로 나타났다. 셋째, 유용성은 보안적 위험과 지속적 이용의도의 관계에서 유의한 조절효과가 나타났으며, 편리성은 모든 지각된 위험과 지속적 이용의도의 관계에서 유의한 조절효과를 보였다. 인터넷전문은행의 안정적 정착을 확보하기 위해서는 소비자가 지각하는 재무적·기능적 위험을 완화하고 인터넷전문은행의 유용성과 편리성에 대한 확대가 이루어져야 한다.

Keywords

References

  1. J. K. Bae. (2018). A study on the effect of personal innovativeness, perceived relative advantage, perceived serviceability, and perceived security on satisfaction and continuance usage intention in Internet primary bank users. Logos Management Review, 16(4), 141-154. https://doi.org/10.22724/LMR.2018.16.4.141
  2. J. M. Lee. (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
  3. K. M. Koo (2018. 6. 20). Internet Primary Banks for international settlements capital ratio have taken a nosedive, 24% to 11%...all net loss. Money Today. https://news.mt.co.kr/mtview.php?no=2018062010342826470
  4. H. N. Park (2019. 3. 3). The purpose of establishing the 2nd Internet Primary Bank were ambiguous. It became a playground for existing financial holdings. Maeil Ilbo. http://www.m-i.kr/news/articleView.html?idxno=500583
  5. J. Y. Lee (2019. 7. 30.). Kakao Bank 2 years, Couldn't achieve Middle Interest Rate. Card.Listing...It's Still following the existing banks. Invest Chosun. http://www.investchosun.com/2019/07/30/3239967.
  6. E. G. Jang & J. M. Lee. (2019). A study on consumer usage pattern, satisfaction, and continuous use intention for internet-only banks: Application of use-diffusion model. Journal of Consumption Culture, 22(1), 69-94. https://doi.org/10.17053/jcc.2019.22.1.004
  7. J. A. Kim & J. W. Yoon. (2018). Study about the positive and negative affect on the continuance intention of internet only bank. Journal of Digital Convergence, 16(12), 267-281. https://doi.org/10.14400/JDC.2018.16.12.267
  8. A. Bhattacherjee. (2001). Understanding information systems continuance : An expectation - confirmation model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921
  9. H. I. Yoo, J. Y. An & C. C. Lee. (2018). A study factors affecting continuance intention of internet only bank: Using task-technology fit theory. The Journal of Society for e-Business Studies, 23(3), 11-128.
  10. K. S. Shin. (2017). The effect of perceived value and perceived risk of internet primary bank on satisfaction and intention to use continuously : Focusing on Kakao Bank. Master dissertation. Korea University, Seoul.
  11. C. S. Yum & J. B. Hong. (2004). An empirical study on the factors influencing customer satisfaction of internet banking. Industrial Engineers Interfaces, 17(3), 305-313.
  12. J. I, Choi (2016). Introduction of the internet-only bank and development direction proposal. Journal of Digital Convergence, 14(9), 139-147. https://doi.org/10.14400/JDC.2016.14.9.139
  13. S. J. Kim et al. (2017). Study on the developmental strategy of the korean internet primary bank. Journal of the Convergence on Culture Technology, 3(2), 37-42. https://doi.org/10.17703/JCCT.2017.3.2.37
  14. D. H. Cho. (2016). Internet specialty bank introduction and improvement tasks. NARS Issue Report.
  15. Kakao Bank (2019). Current status of Kakao Bank 2019. Kakao Bank. https://www.kakaobank.com/Corp/IR/Announcement/Business/pages/1
  16. K Bank (2019). Current status of K Bank 2019. K Bank. https://www.kbanknow.com/ib20/mnu/HOMBKI020101Current status of K Bank Korea
  17. H. E. Yoon(2019. 5. 28.). Internet primary banks blast in one year...Less than 1% of the banking industry. Korea Economic Daily. https://news.naver.com/main/read.nhn?oid=015&aid=0003949341.
  18. 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.
  19. H. Lu, C. Hsu & H. Hsu. (2005). An empirical study of the effects of perceived risk upon intention to use online applications. Information Management and Computer Security, 13(2), 106-120. https://doi.org/10.1108/09685220510589299
  20. R. M. W. Yeung & J. Morris. (2006). An empirical study of the impact of consumer perceived risk on purchase likelihood: modeling approach. International Journal of Consumer Studies, 30(3), 294-305. https://doi.org/10.1111/j.1470-6431.2006.00493.x
  21. S. H. Sim & H. K. Kim. (2011). Effects of e-coupon attributes, perceived risk in internet shopping malls on intention to continuously use online coupons through the user satisfaction: Moderating effects of coupon type and gender. Management & Information Systems Review, 30(2), 1-25.
  22. Y. W. Lee. (2009). A study on the online consumer's perceived risks according to the product characteristics. Journal of Communication Science, 9(4), 576-602.
  23. J. Jacoby & L. B. Kaplan. (1972). The components of perceived risk. Proceedings of the Annual Conference of the Association for Consumer Research, 10, 382-393.
  24. S. Y. Jun, J. H. Huh & S. J. Kang. (2003). The effects of risk perception on the relative role of brand and price in internet shopping mall. Journal of Consumer Studies, 14(2), 19-43.
  25. A. S. Cases. (2002). Perceived risk and risk reduction strategies in internet shopping. The International Review of Retail, Distribution and Consumer Research, 12(4), 375-394. https://doi.org/10.1080/09593960210151162
  26. S. L. Jarvenpaa & P. A. Todd. (1997). Consumer reaction to electronic shopping on the world wide web. Journal of Electronic Commerce, 1(2), 59-88.
  27. 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.
  28. D. H. Ren. (2015). A study on the influence of continuous smartphone banking-using intention by characteristics of smartphone banking. Master dissertation. Yonsei University, Seoul.
  29. T. H. Hsu & L. Lin. (2006). Using fuzzy set theoretic techniques to analyze travel risk. Tourism Management, 27(5), 968-981. https://doi.org/10.1016/j.tourman.2005.10.022
  30. L. Slevitch & S. Amit. (2008). Management of perceived risk in the context of destination choice. International Journal of Hospitality & Tourism Administration, 9(1), 85-103. https://doi.org/10.1080/15256480801910574
  31. P. Luarn & H. H. Lin. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873-891. https://doi.org/10.1016/j.chb.2004.03.003
  32. D. L.Hoffman, T. P. Novak & M. Peralta. (1999). Building consumer trust in online environments: The case for information privacy. Communcations of The ACM, 42(4), 80-85.
  33. H. S. Lee & Y. I. Chae. (2003). Factors influencing the customer satisfaction and re-purchasing intention of mobile shopping mall. Korea Society of IT Services, 12(2), 215-229.
  34. J. A. Manzano, C. L. Navarre, C. R. Mafe & S. S. Blas. (2009). The role of consumer innovativeness and perceived risk in online banking usage. International Journal of Bank Marketing, 27 (1), 53-75. https://doi.org/10.1108/02652320910928245
  35. S. Liao, Y. P. Wang, H. Wang & A. Chen. (1999). The adoption of virtual banking : An empirical study. International Journal of Information Management, 19(1), 63-74. https://doi.org/10.1016/S0268-4012(98)00047-4
  36. C. Jayawardhena & P. Foley. (2000). Changes in the banking sector the case of internet banking in the UK. Internet Research: Electronic Networking. Applications and Policy, 10(1), 19-31.
  37. R. Agarwal & J. Prasad. (2007). Are individual differences germane to the acceptance of new information technologies. Decision Sciences, 30(2), 361-391. https://doi.org/10.1111/j.1540-5915.1999.tb01614.x
  38. H. R. Choi, K. B. Lee & J. S. Shin. (2006). An empirical study On factors influencing the use intention of mobile banking service. The Journal of Society for e-Business Studies, 11(3), 13-34.
  39. J. C. Koo, Y. H. Suh, S. C. Lee & N. H. Kim. (2006). Factors affecting user acceptance in mobile banking: An empirical study using extended TAM and trust. Asia Pacific Journal of Information Systems, 16(2), 159-181.
  40. F. D. Davis. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339. https://doi.org/10.2307/249008
  41. M. Igbaria, J. Iivari & H. Maragahh. (1995). Why do individuals use computer technology? A Finnish case study. Information and Management, 29(5), 227- 23 https://doi.org/10.1016/0378-7206(95)00031-0
  42. D. A. Adams, R. R. Nelson & P. A. Todd. (1992). Perceived usefulness, ease of use, and usage of information technology : A replication. MIS Quarterly, 16(2), 227-247. https://doi.org/10.2307/249577
  43. M. Igbaria, P. C. N. Zinatelli & A. L. M. Cavaye. (1997). Personal computing acceptance factors in small firm s : A structural equation mode. MIS Quarterly, 21(3), 279-305. https://doi.org/10.2307/249498
  44. H. Sun & P. Zhang. (2006). Causal relationships between perceived enjoyment and perceived ease of use : An alternative approach. Journal of the Association for Information Systems, 7(9), 618-645. https://doi.org/10.17705/1jais.00100
  45. Y. H. Jung, G. Kim & C. C. Lee. (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
  46. V. Venkatesh & F. D. David. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
  47. R. N. Bolton & K. N. Lemon. (1999). A dynamic model of customers' usage of services : Usage as an antecedent and consequence of satisfaction. Journal of Marketing Research, 36(2), 171-186. https://doi.org/10.2307/3152091
  48. H. Y. Shin & K. S. Kim. (2010). A study of factors affecting the continued usage intention of internet portal sites. The Journal of Information Systems, 19(3), 35-58. https://doi.org/10.5859/KAIS.2010.19.3.035
  49. D. K. Tse & P. C. Wilton. (1988). Models of consumer satisfaction formation : An extension. Journal of Marketing Research, 25(2), 204-212. https://doi.org/10.1177/002224378802500209
  50. J. S. Kim. (2018). The impact of consumption value and social capital of SNS on consumers' satisfaction and continuous use intention. Master dissertation. Konkuk University, Seoul.
  51. H. Gewald & J. Dibbern. (2009). Risks and benefits of business process outsourcing: A study of transaction services in the German banking industry. Information & Management, 46(4), 249-257. https://doi.org/10.1016/j.im.2009.03.002
  52. Y.S. Seo. (2013). Study on consumer satisfaction and willingness to recommend at different technology adoption stages of smartphone. Doctoral dissertation. Konkuk University, Seoul.
  53. B. S. Hong & Y. K. Na. (2008). The effect of the perceived hedonic value, usefulness and ease of use on attitude toward using in internet shopping mall and purchase intention of the fashion merchandise. Journal of the Korean Society of Clothing and Textiles, 32(1), 147-156. https://doi.org/10.5850/JKSCT.2008.32.1.147
  54. Y. H. Moon. (2017). Factors affecting intention to use internet primary bank : An exploratory difference of demographic characteristics. Journal of Business Education, 31(6), 95-108. https://doi.org/10.34274/KRABE.2017.31.6.005
  55. J. M. Lee & H.J. Kim. (2020). Determinants of adoption and continuance intentions toward Internet-only banks. International Journal of Bank Marketing, 38(4), 843-865. https://doi.org/10.1108/IJBM-07-2019-0269
  56. K. L. Tang, C. K. Ooi& J. B. Chong. (2020). Perceived risk factors affect intention to use FinTech. Journal of Accounting and Finance in Emerging Economies, 6(2), 453-463. https://doi.org/10.26710/jafee.v6i2.1101
  57. Z. S. Asnakew. (2020). Customers' continuance intention to use mobile banking: Development and testing of an integrated model. Rev Socionetwork Strat 14, 123-146 https://doi.org/10.1007/s12626-020-00060-7
  58. L. S. Aiken & S. G. West. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA, US: Sage Publications, Inc.
  59. K. K Lee(2019. 8. 1.). Kakao Bank Medium Credit Loan Up to 50 million won. naeil ilbo. http://www.naeil.com/news_view/?id_art=321371.