Browse > Article
http://dx.doi.org/10.14400/JDC.2020.18.8.133

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

Jung, Joowon (Department of Home Economics Education, Dongguk University)
Cho, SO Yeon (Department of Home Economics Education, Dongguk University)
Publication Information
Journal of Digital Convergence / v.18, no.8, 2020 , pp. 133-149 More about this Journal
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.
Keywords
Internet primary bank; perceived risk; acceptance; continuous use intention; Moderating Effect;
Citations & Related Records
Times Cited By KSCI : 9  (Citation Analysis)
연도 인용수 순위
1 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.   DOI
2 A. Bhattacherjee. (2001). Understanding information systems continuance : An expectation - confirmation model. MIS Quarterly, 25(3), 351-370.   DOI
3 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.
4 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.
5 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.
6 J. I, Choi (2016). Introduction of the internet-only bank and development direction proposal. Journal of Digital Convergence, 14(9), 139-147.   DOI
7 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.   DOI
8 D. H. Cho. (2016). Internet specialty bank introduction and improvement tasks. NARS Issue Report.
9 Kakao Bank (2019). Current status of Kakao Bank 2019. Kakao Bank. https://www.kakaobank.com/Corp/IR/Announcement/Business/pages/1
10 K Bank (2019). Current status of K Bank 2019. K Bank. https://www.kbanknow.com/ib20/mnu/HOMBKI020101Current status of K Bank Korea
11 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.
12 D. K. Tse & P. C. Wilton. (1988). Models of consumer satisfaction formation : An extension. Journal of Marketing Research, 25(2), 204-212.   DOI
13 V. Venkatesh & F. D. David. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.   DOI
14 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.   DOI
15 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.   DOI
16 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.
17 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.   DOI
18 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.   DOI
19 Y.S. Seo. (2013). Study on consumer satisfaction and willingness to recommend at different technology adoption stages of smartphone. Doctoral dissertation. Konkuk University, Seoul.
20 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.   DOI
21 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.
22 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.
23 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.   DOI
24 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.   DOI
25 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.
26 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.
27 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.
28 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.   DOI
29 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.
30 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.   DOI
31 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.   DOI
32 Z. S. Asnakew. (2020). Customers' continuance intention to use mobile banking: Development and testing of an integrated model. Rev Socionetwork Strat 14, 123-146   DOI
33 L. S. Aiken & S. G. West. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA, US: Sage Publications, Inc.
34 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.
35 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.
36 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.
37 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.
38 T. H. Hsu & L. Lin. (2006). Using fuzzy set theoretic techniques to analyze travel risk. Tourism Management, 27(5), 968-981.   DOI
39 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.   DOI
40 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.   DOI
41 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.
42 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.   DOI
43 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.   DOI
44 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.
45 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.   DOI
46 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.   DOI
47 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.   DOI
48 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
49 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
50 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.
51 M. Igbaria, J. Iivari & H. Maragahh. (1995). Why do individuals use computer technology? A Finnish case study. Information and Management, 29(5), 227- 23   DOI
52 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.
53 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.
54 F. D. Davis. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.   DOI
55 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.   DOI
56 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.   DOI
57 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.   DOI
58 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.   DOI
59 R. Agarwal & J. Prasad. (2007). Are individual differences germane to the acceptance of new information technologies. Decision Sciences, 30(2), 361-391.   DOI