과제정보
This research was supported by the National Natural Science Foundation of China : (NSFC, 71871172), namely "Model of risk knowledge acquisition and platform governance in Fintech based on deep learning". In addition, we deeply appreciate the comments from the fellow members of Dr. Xia's project team and research center of Enterprise Decision Support, Key Research Institute of Humanities and Social Sciences in Universities of Hubei Province (DSS2021).
참고문헌
- Akter, S., D'Ambra, J., and Ray, P. (2013). Development and validation of an instrument to measure user perceived service quality of Health. Information & Management, 50(4), 181-195. https://doi.org/10.1016/j.im.2013.03.001
- Allen, F., McAndrews, J., and Strahan, P. (2002). E-finance: An introduction. Journal of Financial Services Research, 22(1), 5-27. https://doi.org/10.1023/A:1016007126394
- Alruwaie, M., El-Haddadeh, R., and Weerakkody, V. (2020). Citizens' continuous use of eGovernment services: The role of self-efficacy, outcome expectations and satisfaction. Government Information Quarterly, 37(3), 101485.
- Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Kizgin, H., and Patil, P. (2019). Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model. International Journal of Information Management, 44(1), 38-52. https://doi.org/10.1016/j.ijinfomgt.2018.09.002
- Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Advances in Behaviour Research &Therapy, 84(2), 191-215.
- Beldad, A. D., and Hegner, S. M. (2018). Expanding the technology acceptance model with the inclusion of trust, social influence, and health valuation to determine the predictors of german user's willingness to continue using a fitness app: A structural equation modeling approach. International Journal of Human-Computer Interaction, 34(9), 882-893. https://doi.org/10.1080/10447318.2017.1403220
- Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238-246. https://doi.org/10.1037/0033-2909.107.2.238
- Bhattacherjee, A. (2001). Understanding information systems continuance an expectation-confirmation model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921
- Bhattacherjee, A., Perols, J., and Sanford, C. (2008). Information technology continuance: A theoretic extension and empirical test. Journal of Computer Information Systems, 49(1), 17-26. https://doi.org/10.1080/08874417.2008.11645302
- Chen, Y., Yang, L., Zhang, M., and Yang, J. (2018). Central or peripheral? Cognition elaboration cues' effect on user's continuance intention of mobile health applications in the developing markets. International Journal of Medical Informatics, 116(8), 33-45. https://doi.org/10.1016/j.ijmedinf.2018.04.008
- Cheng, Y. M. (2014). Extending the expectation-confirmation model with quality and flow to explore nurses' continued blended e-learning intention. Information Technology & People, 27(3), 230-258. https://doi.org/10.1108/ITP-01-2013-0024
- Cheng, Y. M. (2018). What drives cloud ERP continuance? An integrated view. Journal of Enterprise Information Management, 31(5), 724-750. https://doi.org/10.1108/JEIM-02-2018-0043
- Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
- Delone, W. H., and Mclean, E. R. (1992). Information systems success: The quest for the dependent variable. Journal of Management Information Systems, 3(4), 60-95.
- DeLone, W. H., and McLean, E. R. (2004). Measuring e-commerce success: Applying the Delone & Mclean information systems success model. International Journal of Electronic Commerce, 9(1), 31-47. https://doi.org/10.1080/10864415.2004.11044317
- Doll, W. J., Raghunathan, T. S., Lim, J. S., and Gupta, Y. P. (1995). Research report-A confirmatory factor analysis of the user information satisfaction instrument. Information Systems Research, 6(2), 177-188. https://doi.org/10.1287/isre.6.2.177
- Fornell, C., and 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/10.1177/002224378101800104
- Huang, G., and Ren, Y. (2020). Linking technological functions of fitness mobile apps with continuance usage among Chinese users: Moderating role of exercise self-efficacy. Computers in Human Behavior, 3(2), 151-160. https://doi.org/10.1016/j.chb.2019.09.013
- Jia, L., Xue, G., Fu, Y., and Xu, L. (2018). Factors affecting consumers' acceptance of e-commerce consumer credit service. International Journal of Information Management, 40(3), 103-110. https://doi.org/10.1016/j.ijinfomgt.2018.02.002
- Johnson, V. L., Kiser, A., Washington, R., and Torres, R. (2018). Limitations to the rapid adoption of m-payment services: Understanding the impact of privacy risk on m-payment services. Computers in Human Behavior, 79(2), 111-122. https://doi.org/10.1016/j.chb.2017.10.035
- Joo, Y. J., So, H. J., and Kim, N. H. (2018). Examination of relationships among students' self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers & Education, 122(7), 260-272. https://doi.org/10.1016/j.compedu.2018.01.003
- Kim, B. (2012). Understanding key factors of user's intentions to repurchase and recommend digital items in social virtual worlds. Cyberpsychology, Behavior, and Social Networking, 15(10), 543-550. https://doi.org/10.1089/cyber.2012.0128
- Kim, K. J., and Shin, D. H. (2015). An acceptance model for smart watches. Internet Research Electronic Networking Applications & Policy, 25(4), 527-541. https://doi.org/10.1108/IntR-05-2014-0126
- Kim, K., Hwang, J., Zo, H., and Lee, H. (2016). Understanding user's continuance intention toward smartphone augmented reality applications. Information Development, 32(2), 161-174. https://doi.org/10.1177/0266666914535119
- Koo, C., Wati, Y., Park, K., and Lim, M. K. (2011). Website quality, expectation, confirmation, and end user satisfaction: The knowledge-intensive website of the Korean National Cancer Information Center. Journal of Medical Internet Research, 13(4), 1-13.
- Kumar, A., Adlakaha, A., and Mukherjee, K. (2018). The effect of perceived security and grievance redressal on continuance intention to use M-wallets in a developing country. International Journal of Bank Marketing, 36(7), 1170-1189. https://doi.org/10.1108/IJBM-04-2017-0077
- Lee, J. M., and Kim, H. J. (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
- Liao, C., Huang, Y. J., and Hsieh, T. H. (2016). Factors influencing internet banking adoption. Social Behavior & Personality an International Journal, 44(9), 1443-1455. https://doi.org/10.2224/sbp.2016.44.9.1443
- Liebana-Cabanillas, F., Marinkovic, V., and Kalinic, Z. (2017). A SEM-neural network approach for predicting antecedents of m-commerce acceptance. International Journal of Information Management, 37(2), 14-24. https://doi.org/10.1016/j.ijinfomgt.2016.10.008
- Lien, C. H., Cao, Y., and Zhou, X. (2017). Service quality, satisfaction, stickiness, and usage intentions: An exploratory evaluation in the context of WeChat services. Computers in Human Behavior, 68(3), 403-410. https://doi.org/10.1016/j.chb.2016.11.061
- Lim, S. H., Kim, D. J., Hur, Y., and Park, K. (2019). An empirical study of the impacts of perceived security and knowledge on continuous intention to use mobile fintech payment services. International Journal of Human-Computer Interaction, 35(10), 886-898. https://doi.org/10.1080/10447318.2018.1507132
- Lin, C. H., Shih, K. H., Wang, W. C., Chuang, L. F., Tsai, W. C., and Huang, C. F. (2020). Factors influencing the purchase of travel insurance over mobile banking. International Journal of Mobile Communications, 18(2), 158-174. https://doi.org/10.1504/IJMC.2020.105843
- Lin, W. S., and Wang, C. H. (2012). Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit. Computers & Education, 58(1), 88-99. https://doi.org/10.1016/j.compedu.2011.07.008
- Lin, X., Featherman, M., and Sarker, S. (2017). Understanding factors affecting user's social networking site continuance: A gender difference perspective. Information & Management, 54(3), 383-395. https://doi.org/10.1016/j.im.2016.09.004
- Lin, X., Wu, R. Z., Lim, Y. T., Han, J. P., and Chen, S. C. (2019). Understanding the sustainable usage intention of mobile payment technology in Korea: Cross-countries comparison of Chinese and Korean users. Sustainability, 11(19), 1-23.
- MacCallum, R. C., Browne, M. W., and Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130-149. https://doi.org/10.1037/1082-989X.1.2.130
- Madden, G., Banerjee, A., Rappoport, P. N., and Suenaga, H. (2017). E-commerce transactions, the installed base of credit cards, and the potential mobile E-commerce adoption. Applied Economics, 49(1), 21-32. https://doi.org/10.1080/00036846.2016.1189507
- Marsh, H. W., Balla, J. R., and McDonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103(3), 391-410. https://doi.org/10.1037/0033-2909.103.3.391
- Masri, N. W., You, J. J., Ruangkanjanases, A., Chen, S. C., and Pan, C. I. (2020). Assessing the effects of information system quality and relationship quality on continuance intention in e-tourism. International Journal of Environmental Research and Public Health, 17(1), 174-190.
- Mohammadi, H. (2015). Investigating user's perspectives on e-learning: An integration of TAM and IS success model. Computers in Human Behavior, 45(4), 359-374. https://doi.org/10.1016/j.chb.2014.07.044
- Mu, H. L., and Lee, Y. C. (2017). Examining the influencing factors of third-party mobile payment adoption: A comparative study of Alipay and WeChat Pay. The Journal of Information Systems, 26(4), 247-284. https://doi.org/10.5859/KAIS.2017.26.4.247
- Nam, K., and Seong, N. (2020). A study on influencing factors for customer satisfaction and the continuing use of social network services in financial industry. Enterprise Information Systems, 14(4), 1-25. https://doi.org/10.1080/17517575.2019.1686656
- Nunally, J. C. (1978). Psychometric theory (2nd ed.). Mc Graw-Hill, New York.
- Ofori, K. S., Boateng, H., Okoe, A. F., and Gvozdanovic, I. (2017). Examining customers' continuance intentions towards internet banking usage. Marketing Intelligence & Planning, 35(6), 756-773. https://doi.org/10.1108/MIP-11-2016-0214
- Oghuma, A. P., Libaque-Saenz, C. F., Wong, S. F., and Chang, Y. (2016). An expectation-confirmation model of continuance intention to use mobile instant messaging. Telematics and Informatics, 33(1), 34-47. https://doi.org/10.1016/j.tele.2015.05.006
- Oliver, R. L. (1980). A cognitive model for the antecedents and consequences of satisfaction. Journal of Marketing Research, 17(4), 460-469. https://doi.org/10.1177/002224378001700405
- Pricewaterhouse Coopers. (2014). Five key sharing economy sectors could generate £9 billion of UK revenues by 2025. Retrieved from https://pwc.blogs.com/press_room/2014/08/five-key-sharing-economy-sectors-could-generate-9-billion-ofuk-revenues-by-2025.html
- Rai, A., Lang, S. S., and Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13(1), 50-69. https://doi.org/10.1287/isre.13.1.50.96
- Roca, J. C., Chiu, C. M., and Martinez, F. J. (2006). Understanding e-learning continuance intention: An extension of the technology acceptance model. International Journal of Human-Computer Studies, 64(8), 683-696. https://doi.org/10.1016/j.ijhcs.2006.01.003
- Sevillano-Garcia, M. L., and Vazquez-Cano, E. (2015). The impact of digital mobile devices in higher education. Journal of Educational Technology & Society, 18(1), 106-118.
- Shang, D., and Wu, W. (2017). Understanding mobile shopping consumers' continuance intention. Industrial Management & Data Systems, 117(1), 213-227. https://doi.org/10.1108/IMDS-02-2016-0052
- Sharma, S. K., and Sharma, M. (2019). Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation. International Journal of Information Management, 44(1), 65-75. https://doi.org/10.1016/j.ijinfomgt.2018.09.013
- Shaw, N., and Sergueeva, K. (2019). The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value. International Journal of Information Management, 45(2), 44-55. https://doi.org/10.1016/j.ijinfomgt.2018.10.024
- Singh, N., and Liebana-Cabanillas, F. J. (2020). Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use and social influence. International Journal of Information Management, 50(1), 191-205. https://doi.org/10.1016/j.ijinfomgt.2019.05.022
- Susanto, A., Chang, Y., and Ha, Y. (2016). Determinants of continuance intention to use the smartphone banking services. Industrial Management & Data Systems, 116(3), 508-525. https://doi.org/10.1108/IMDS-05-2015-0195
- Urbach, N., Smolnik, S., and Riempp, G. (2010). An empirical investigation of employee portal success. Journal of Strategic Information Systems, 19(3), 184-206. https://doi.org/10.1016/j.jsis.2010.06.002
- Wang, L., Zhao, W., Sun, X., Zheng, R., Qu, W., and Sun, X. (2016). Modeling of causes of Sina Weibo continuance intention with mediation of gender effects. Frontiers in Psychology, 7(13), 619-630.
- Wixom, B. H., and Watson, H. J. (2001). An empirical investigation of the factors affecting data warehousing success. MIS Quarterly, 25(1), 17-41. https://doi.org/10.2307/3250957
- Wu, I. L., and Huang, C. Y. (2015). Analyzing complaint intentions in online shopping: The antecedents of justice and technology use and the mediator of customer satisfaction. Behavior & Information Technology, 34(1), 69-80. https://doi.org/10.1080/0144929X.2013.866163
- Xie, J., Latif, Z., Jianqiu, Z., and Ul Waraa, K. (2019, December). Analysis of influencing factors of internet lending adoption in China: Internet lending adoption in China. In 2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistic (MACS), IEEE, 1-8.
- Xu, H., and Belanger, F. (2013). Information systems journal special issue on: Reframing privacy in a networked world. Information Systems Journal, 23(4), 371-375. https://doi.org/10.1111/isj.12026
- Yang, M., Shao, Z., Liu, Q., and Liu, C. (2017). Understanding the quality factors that influence the continuance intention of students toward participation in MOOCs. Educational Technology Research & Development, 65(5), 1195-1214. https://doi.org/10.1007/s11423-017-9513-6
- Yen, Y. S. (2015). Managing perceived risk for customer retention in e-commerce: The role of switching costs. Information & Computer Security, 23(2), 145-160. https://doi.org/10.1108/ICS-12-2013-0088
- Yu, G., Qiqi, Q., and Cho, N. (2019). A study on the sustained use of mobile payment services: Comparison of Alipay and WeChat pay in China. Journal of Information Technology Applications & Management, 26(5), 1-12.
- Zhao, Y., and Bacao, F. (2020). What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period? International Journal of Hospitality Management, 91(8), 1-12.
- Zhao, Y., Deng, S., and Zhou, R. (2015). Understanding mobile library apps continuance usage in China: A theoretical framework and empirical study. Libri, 65(3), 161-173.
- Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54(2), 1085-1091. https://doi.org/10.1016/j.dss.2012.10.034
- Zhu, X., Ren, W., Chen, Q., and Evans, R. (2021). How does internet usage affect the credit consumption among Chinese college students? A mediation model of social comparison and materialism. Internet Research, 31(3), 1083-1101. https://doi.org/10.1108/INTR-08-2019-0357