References
- Technology and Information Promotion Agency. (2019). Technology Roadmap for SME 2019-2021 Fintech.
- Y. J. John. (2021). Security and Trust on Non-Contact Financial Transaction. Journal of Digital Convergence, 19(7), 147-154. DOI : 10.14400/jdc.2021.19.7.147
- J. H. Hong. (2020). A Study on the Institutional Plan on Financial Consumer Protection in the Case of Unfair Settlement due to Information Leak: Focusing on the Contents of the Comprehensive Digital Finance Innovation Plan. Korean Journal of Industrial Security, 10(3), 89-110. DOI : 10.33388/kais.2020.10.3.089
- The Bank of Korea. (2021). Domestic payment trends in the first half of 2021.
- The Bank of Korea(2021). Status of electronic payment service use during the first half of 2021.
- Samjong KPMG ERI. (2021). The financial industry became a battleground for dinosaurs: Big Tech's full-fledged financial advance.
- Bank of Korea(2020). Results of a survey on payment service and mobile financial service usage in 2019.
- Korea Investment & Securities. (2019). Fintech Industry Analysis.
- DCMREPORT, Survey on usage behavior of simple payment service in 2020.
- H. J. Hwang & J. K. Kim. (2018). The Study on the User Resistance Intention of Mobile Easy Money Transfer Service. The e-Business Studies, 19(1), 135-153. DOI : 10.20462/TeBS.2018.2.19.1.135
- H. S. Park & S. H. Kim. (2017). Impacts of Perceived Risks and Technical Traits of Mobile Easy Payment Service on Use Conflict and Acceptance Resistance. The Journal of Internet Electronic Commerce Resarch, 17(4), 119-138.
- K. K. Lee. (2020). Improvement of Domestic Mobile Payment Security Problem. The Journal of Korean Institute of Communications and Information Sciences, 45(10), 1720-1727. DOI : 7840/kics.2020.45.10.1720 https://doi.org/10.7840/kics.2020.45.10.1720
- Bank of Korea(2020). 2020 Payment Report.
- J. Hwang & H. S. Yu. (2016). A Study of Factors Affecting the Intention to use a Mobile Easy Payment Service: An Integrated Extension of TAM with Perceived Risk. Journal of Information Technology and Architecture, 13(2), 291-306.
- Bank of Korea(2019). Electronic payment service usage during the first half of 2019.
- Korea Consumer Agency. (2016). Survey on mobile simple payment service(fintech1).
- S. J. Chung & S. I. Kim. (2020). A study on the user experience of mobile Fintech service in Z generation:Focused on KakaoPay and Toss. Journal of Digital Convergence, 18(1), 315-320. DOI : 10.14400/jdc.2020.18.1.315
- N. R. Kim & J. Y. Yun. (2020). The Effect of Easiness and Security on Preference of Mobile Easy Payment Service. Journal of the HCI Society of Korea, 15(1), 29-37. DOI : 10.17210/jhsk.2020.03.15.1.29
- D. W. Heo & W. J. Sung. (2021). The Effect of Privacy Concerns on Using Mobile Payment Services: Moderating Effect of Multidimensional Consumer Innovativeness. Informatization Policy, 28(1), 22-42. DOI : 10.22693/niaip.2021.28.1.022
- D. H. Lee. (2021). A Study on the Intention to Use Mobile Payment Derived from FinTech during the Fourth Industrial Revolution. The e-Business Studies, 22(4), 3-17.
- S. H. Hwang & J. K. Kim. (2018). The Study of User Resistance to Fintech Payment Service: In the Perspective of Innovation Diffusion And Status Quo Bias Theory. The Journal of Information Systems, 27(1), 133-151. DOI : 10.5859/kais.2018.27.1.133
- S. H. Hwang & J. H. Kim. (2018). An Analysis of Factors Affecting Fintech Payment Service Acceptance Using Logistic Regression. Journal of the Korea Society for Simulation, 27(1), 51-60. DOI : 10.9709/jkss.2018.27.1.051
- Y. Kim, Y. J. Park & J. Choi. (2016). The adoption of mobile payment services for "fintech". International Journal of Applied Engineering Research, 11(2), 1058-1061.
- D. S. Ravindran. (2015). An empirical study on service quality perceptions and continuance intention in mobile banking context in india. The Journal of Internet Banking and Commerce, 17(1), 1-21.
- F. Liebana-Cabanillas, J. Sanchez-Fernandez & F. Munoz-Leiva. (2014). Role of gender on acceptance of mobile payment. Industrial Management & Data Systems, 114(2), 220-240. DOI : 10.1108/imds-03-2013-0137
- T. Zhou. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54(2), 1085-1091. DOI : 10.1016/j.dss.2012.10.034
- S. Yang, Y. Lu, S. Gupta, Y. Cao & R. Zhang. (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. DOI : 10.1016/j.chb.2011.08.019
- H. W. Kim, H. C. Chan & S. Gupta. (2007). Value-based adoption of mobile internet: an empirical investigation. Decision support systems, 43(1), 111-126. DOI : 10.1016/j.dss.2005.05.009
- J. H. You, J. C. Park & K. H. Kim. (2018). A Study on the Factors Affecting the Diffusion Intention of Fin-Tech Services : Focused on Mobile Simple Payment Services. Journal of Industrial Economics and Business, 31(1), 1-21. DOI : 10.22558/jieb.2018.02.31.1.1
- D. H. Son. (2020). The Effect of the Reliability and the Perceived Value on the Continuous Use of Fintech Service. The Journal of Internet Electronic Commerce Resarch, 20(4), 1-11. DOI : 10.37272/jiecr.2020.08.20.4.1
- S. B. Lee, J. Y. Lee & J. Y. Moon. (2018). What is the Switching Intention from Existing Payment to Mobile Payment Service?. Journal of the Korea society of computer and information, 23(6), 59-66. DOI : 10.9708/jksci.2018.23.06.059
- M. J. Kim & S. B. Lee. (2018). The effect of the perceived benefit and sacrifice of delivery application service users in the food industry on perceived value and behavioral intention : Using the value-based adoption model(VAM). International Journal of Tourism and Hospitality Research, 32(2), 217-233. DOI : 10.21298/ijthr.2018.02.32.2.217
- J. C. Oh. (2017). An Empirical Study on Use-Diffusion of AR Technology based on VAM : The Moderating Effects of Postive TRI. The e-Business Studies, 18(5), 225-244. DOI :10.20462/tebs.2017.10.18.5.225
- Y. G. Jo, J. E. Lee, M. S. Suh, J. G. Jung & K. H. Kim. (2016). A study on the formation factors of Continuance Intention of Real Estate Mobile App by Expectation-Confirmation Model and Value based Adoption Model, Korea Science & Art Forum, 25, 389-407. DOI : 10.17548/ksaf.2016.09.25.389
- J. H. Han, S. B. Kang & T. S. Moon. (2013). An empirical study on perceived value and continuous intention to use of smart phone, and the moderating effect of personal innovativeness. Asia Pacific Journal of Information Systems, 23(4), 53-84. DOI : 10.14329/apjis.2013.23.4.053
- D. H. Kim , J. H. Lee & Y. P. Park. (2012). A Study of Factors Affecting the Adoption of Cloud Computing. The Journal of Society for e-Business Studies, 17(1), 111-136. DOI : 10.7838/jsebs.2012.17.1.111
- H. Y. Wang, & S. H. Wan. (2010). Predicting mobile hotel reservation adoption: Insight from a perceived value standpoint. International Journal of Hospitality Management, 29(4), 598-608. DOI : 10.1016/j.ijhm.2009.11.001
- S. B. Im, B. L. Bayus & C. H. Mason. (2003). An empirical study of innate consumer innovativeness, personal characteristics, and new-product adoption behavior. Journal of the Academy of Marketing Science, 31, 61-73. DOI : 10.1177/0092070302238602
- Y. Lu, Y. Cao, B. Wang & S. Yang. (2011). A study on factors that affect users' behavioral intention to transfer usage from the offline to the online channel. Computers in Human Behavior, 27(1), 355-364. DOI : 10.1016/j.chb.2010.08.013
- R. Agarwal & J. Prasad. (1998). A Conceptual and Operational Definition of Personal Innovativeness in the Information Technology. Information Systems Research, 9(2), 204-215. DOI : 10.1287/isre.9.2.204
- K. Y. Lee. (2017). A Study of Structural Relationship between Technostress and Mobile Application Discontinuance Intention. Korean Jouranl of Business Administration, 30(10), 1835-1855. DOI : 10.18032/kaaba.2017.30.10.1835
- Q. Su, L. Li & Y. W. Cui. (2009). Analysing relational benefits in e-business environment from behavioural perspective. Systems Research and Behavioral Science, 26(2), 129-142. DOI : 10.1002/sres.965
- R. A. Ping. (1993). The effects of satisfaction and structural constraints on retailer exiting, voice, loyalty, opportunism, and neglect. Journal of Retailing, 69(3), 320-352. DOI : 10.1016/0022-4359(93)90010-g
- C. Kim, M. Mirusmonov & I. Lee. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322. DOI : 10.1016/j.chb.2009.10.013
- D. G. Mick & S. Fournier. (1998). Paradoxes of technology: Consumer cognizance, emotions, and coping strategies. Journal of Consumer Research, 25(2), 123-143. DOI : 10.1086/209531
- N. K. Malhotra, S. S. Kim & J. Agarwal. (2004). Internet users' information privacy concerns(IUIPC): the construct, the scale, and a causal model. Information Systems Research, 15(4), 336-355. DOI : 10.1287/isre.1040.0032
- T. Zhou & H. Li. (2014), Understanding mobile SNS continuance usage in China from the perspectives of social influence and privacy concern. Computers in Human Behavior, 37, 283-289. DOI : 10.1016/j.chb.2014.05.008
- Y. C. Ku, R. Chen & H. Zhang. (2013). Why do users continue using social networking sites? An exploratory study of members in the United States and Taiwan. Information & Management, 50(7), 571-581. DOI : 10.1016/j.im.2013.07.011
- D. H. McKnight, V. Choudhury & C. Kacmar. (2002). Developing and Validating Trust Measures for E-commerce: An Integrative Typology. Information Systems Research, 13(3), 334-359. DOI : 10.1287/isre.13.3.334.81
- K. M. Kim & Y. S. Park. (2020). A Study on Acceptance Intentions to Use the Mobile Payment Service Based on Biometric Authentication: Focusing on ApplePay. Journal of Digital Convergence, 18(7), 123-133. DOI : 10.14400/jdc.2020.18.7.123
- H. W. Kim & S. I. Kim. (2020). A study on User experience of Fintech Application Service : Focused on Toss and Kakaobank. Journal of Digital Convergence, 18(1), 287-293. DOI : 10.14400/jdc.2020.18.1.287
- S. J. Lee(2019). An Analysis of Factors Influencing Switching Intention toward Online Platform-based Easy Payment Service with Moderating Effects of Policy Expectations: Focusing on Kakao Pay. The Journal of the Korea Contents Association, 19(5), 426-442. DOI : 10.5392/jkca.2019.19.05.426
- T. Dinev & P. Hart. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61-80. DOI : 10.1287/isre.1060.0080
- J. F. Hair, W. C. Black, B. J. Babin & R. E. Anderson. (2009) Multivariate Data Analysis, 7th Edition. London: Prentice Hall.
- W. W. Chin. (2010). How to Write Up and Report PLS Analysis. Handbook of Partial Least Squares: Concepts, Methods and Applications, New York: Springer.
- C. M. Ringle, M. Sarstedt & D. Straub. (2012). A critical look at the use of PLS-SEM in MIS quarterly. MIS Quarterly, 36(1), 3-14. DOI : 10.2307/41410402
- M. Tenenhaus, E. V. Vincenzo, Y. M. Chatelin & C. Lauro. (2005). PLS Path Modeling. Computational Statistics and Data Analysis, 48(1), 159-205. DOI : 10.1016/j.csda.2004.03.005
- B. S. Kim. (2017). Effects of Brand Loyalty of Consumer Loyalty toward Loyalty Programs and Consumer Satisfaction:Focused on Coffee Chains. Journal of Korea Service Management Society, 18(1), 135-157. DOI : 10.15706/jksms.2017.18.1.00
- H. G. Kim. (2020). A Study on the Factors Influencing on the Intention to Continuously Use a Smart Factory. Journal of the Korea Industrial Information Systems Research, 25(2), 73-85. DOI : 10.9723/jksiis.2020.25.2.073
- J. H. Oh, J. H. Seo, J. D. Kim. (2019). The Effect of Both Employees' Attitude toward Technology Acceptance and Ease of Technology Use on Smart Factory Technology Introduction level and Manufacturing Performance. Journal of Information Technology Applications & Management, 26(2), 13-26. DOI : 10.21219/jitam.2019.26.2.013