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11 (2) 2021

Factors influence ease of use on Fintech adoption: Mediating by the role of attachment anxiety under Covid-19 pandemic


Author - Affiliation:
Le Thi Hong Minh - University of Economics Ho Chi Minh City , Vietnam
Corresponding author: Le Thi Hong Minh - minhlth@ueh.edu.vn
Submitted: 12-04-2021
Accepted: 28-05-2021
Published: 14-08-2021

Abstract
In recent times, Fintech has developed rapidly along with the development of technology. The Covid-19 lockdown has created a huge opportunity in terms of increasing the number of users, and users’ experience. Previous studies have shown a number of factors affecting the use of financial technology services. However, what are the factors that are caused by the Covid-19 epidemic, and the ability to enhance competitive advantage and retain users is still lacking. Data were collected in Vietnam, comprising 247 respondents, and the SEM model was used to predict the effects. This study shows that users' users’ beliefs, security and privacy, web design of Fintech services, customer value, and attachment anxiety during prolonged lockdown without a feasible solution to date increase intention to adopt Fintech. Both theoretical and practical applications were discussed in this study.

Keywords
attachment anxiety; consumer belief; Covid-19 pandemic; Fintech; security and privacy

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Cite this paper as:

Le, T. H. M. (2021). Factors influence ease of use on Fintech adoption: Mediating by the role of attachment anxiety under Covid-19 pandemic. Ho Chi Minh City Open University Journal of Science – Economics and Business Administration, 11(2), 137-155. doi:10.46223/HCMCOUJS.econ.en.11.2.1799.2021


References

Aladwani, A. (2006). An empirical test of the link between website quality and forward enterprise integration with web consumers. Business Process Management Journal, 12 (2), 178-190. doi:10.1108/14637150610657521


Alalwan, A., Dwivedi, Y., Rana, N., & Williams, M. (2016). Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, perceived risk and self-efficacy. Journal of Enterprise Information Management, 29 (1), 118-139. doi:10.1108/JEIM-04-2015-0035


Asian Development Bank. (2019). Fintech for Asian smes. Asian development bank institute. Retrieved May 20, 2019, from https://www.adb.org/publications/fintech-for-smes


Augeraud, E., Banerjee, M., Dhersin, J. S., D’Onofrio, A., Lipniacki, T., Petrovskii, S., ... Turinici, G. (2020). Heterogeneous social interactions and the Covid-19 lockdown outcome in a multi-group seir model. Mathematical Modelling of Natural Phenomena, 15(36), 1-18. doi:10.1051/mmnp/2020025


Asyhari, A., Pudjihastuti, S. H., & Marhaeni, D. (2018). Peran mediasi keunggulan kompetitif pada faktor determinan kinerja bisnis ukm di sentra tenun batik di jawa tengah. Jurnal Siasat Bisnis, 22 (2), 111. doi:10.20885/jsb.vol22.iss2.art1


Barth, S., de Jong, M. D. T., Junger, M., Hartel, P. H., & Roppelt, J. C. (2019). Putting the privacy paradox to the test: Online privacy and security behaviors among users with technical knowledge, privacy awareness, and financial resources. Telematics and Informatics, 41, 55-69. doi:10.1016/j.tele.2019.03.003


Bauer, H., Falk, T., & Hammerschmidt, M. (2006). eTransQual: A transaction process-based approach for capturing service quality in online shopping. Journal of Business Research, 59 (7), 866-875. doi:10.1016/j.jbusres.2006.01.021


Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88 (3), 588-606. doi:10.1037/0033-2909.88.3.588


Billore, S., & Billore, G. (2020). Consumption switch at haste: insights from Indian low-income customers for adopting Fintech services due to the pandemic. Transnational Marketing Journal, 8 (2), 197-218.


Blut, M. (2016). E- service quality: Development of a hierarchical model. Journal of Retailing, 92 (4), 500-517. doi:10.1016/j.jretai.2016.09.002


Cao, X., & Sun, J. (2018). Exploring the effect of overload on the discontinuous intention of social media users: An s-o-r perspective. Computers in Human Behavior, 81, 10-18. doi:10.1016/j.chb.2017.11.035


Chou, W.-P., Wang, P.-W., Chen, S.-L., Chang, Y.-P., Wu, C.-F., Lu, W.-H., & Yen, C.-F. (2020). Risk perception, protective behaviors, and general anxiety during the coronavirus disease 2019 pandemic among affiliated health care professionals in taiwan: Comparisons with frontline health care professionals and the general public. International Journal of Environmental Research and Public Health, 17 (24), 1-11. doi:10.3390/ijerph17249329


Chuang, L. M., Liu, C. C., & Kao, H. K. (2016). The adoption of fintech service: TAM perspective. International Journal of Management and Administrative Sciences, 3 (7), 1-15.


Collins, N., & Read, S. (1990). Adult attachment, working models, and relationship quality in dating couples. Journal of Personality and Social Psychology, 58 (4), 644-663. doi:10.1037/0022-3514.58.4.644


Daqar, M. A., Constantinovits, M., Arqawi, S., & Daragmeh, A. (2021). The role of Fintech in predicting the spread of Covid-19. Banks and Bank Systems, 16 (1), 1-16. doi:10.21511/bbs.16(1).2021.01


Darmansyah, D., Fianto, B. A., Hendratmi, A., & Aziz, P. F. (2020). Factors determining behavioral intentions to use islamic financial technology: Three competing models. Journal of Islamic Marketing, 12 (4), 794-812. doi:10.1108/JIMA-12-2019-0252


Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319-340. doi:10.2307/249008


Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35 (8), 982-1003.


DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 19 (4), 9-30.


Dennis, C., Merrilees, B., Jayawardhena, C., & Tiu Wright, L. (2009). E-consumer behaviour. European Journal of Marketing, 43 (9/10), 1121-1139. doi:10.1108/03090560910976393


Dickinger, A., & Stangl, B. (2013). Website performance and behavioral consequences: A formative measurement approach. Journal of Business Research, 66 (6), 771-777.


Dolbeault, J., & Turinici, G. (2020). Heterogeneous social interactions and the Covid-19 lockdown outcome in a multi-group seir model. Mathematical Modelling of Natural Phenomena, 15, Article 36. doi:10.1051/mmnp/2020025


Eastwick, P. W., & Finkel, E. J. (2008). The attachment system in fledgling relationships: An activating role for attachment anxiety. Journal of Personality and Social Psychology, 95 (3), 628-647. doi:10.1037/0022-3514.95.3.628


Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18 (3), 382-388. doi:10.1177/002224378101800313


Fu, J., & Mishra, M. (2020). Fintech in the time of Covid-19: Trust and technological adoption during crises. Swiss Finance Institute Research Paper, 20-38. doi:10.2139/ssrn.3588453


Gai, K., Qiu, M., Sun, X., & Zhao, H. (2016, December). Security and privacy issues: A survey on FinTech. In International Conference on Smart Computing and Communication (pp. 236-247). Cham, NY: Springer.


Gerbing, D. W., & Anderson, J. C. (1992). Monte carlo evaluations of goodness of fit indices for structural equation models. Sociological Methods & Research, 21 (2), 132-160. doi:10.1177/0049124192021002002


Gerrard, P., & Cunningham, J. B. (2003). The diffusion of internet banking among singapore consumers. International Journal of Bank Marketing, 21 (1), 16-28. doi:10.1108/02652320310457776


Hair, J. F. (2019). Multivariate data analysis (8th ed.). Hampshire, UK: Cengage.


Hair, J. F. (2014). A primer on partial least squares structural equation modeling (pls-sem) . Thousand Oaks, CA: SAGE Publications.


Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial Least Squares Structural Equation Modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26 (2), 106-121. doi:10.1108/EBR-10-2013-0128


Hair, J., Sarstedt, M., Matthews, L. M., & Ringle, C. M. (2016). Identifying and treating unobserved heterogeneity with FIMIX-PLS: part I – method. European Business Review, 28 (1), 63-76. https://doi.org/10.1108/EBR-09-2015-0094


Henseler, J., Ringle, C., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43 (1), 115-135. doi:10.1007/s11747-014-0403-8


Horváth, C., & Adıgüzel, F. (2018). Shopping enjoyment to the extreme: Hedonic shopping motivations and compulsive buying in developed and emerging markets. Journal of Business Research, 86 (5), 300-310. doi:10.1016/j.jbusres.2017.07.013


Howcroft, B., Hamilton, R., & Hewer, P. (2002). Consumer attitude and the usage and adoption of home based banking in the united kingdom. International Journal of Bank Marketing, 20 (3), 111-121.


Huei, C. T., Cheng, L. S., Seong, L. C., Khin, A. A., & Bin, R. L. L. (2018). Preliminary Study on consumer attitude towards FinTech products and services in Malaysia. International Journal of Engineering & Technology, 7, 166-169.


Irons, C., & Gilbert, P. (2005). Evolved mechanisms in adolescent anxiety and depression symptoms: The role of the attachment and social rank systems. Journal of Adolescence, 28 (3), 325-341.


Isaac, M. S., Brough, A. R., & Grayson, K. (2016). Is top 10 better than top 9? The role of expectations in consumer response to imprecise rank claims. Journal of Marketing Research, 53 (3), 338-353. doi:10.1509/jmr.14.0379


Jayawardhena, C., & Wright, L. T. (2009). An empirical investigation into e-shopping excitement: antecedents and effects. European Journal of Marketing, 43 (9/10), 1171-1187. doi:10.1108/03090560910976429


Jiwasiddi, A., Adhikara, C., Adam, M., & Triana, I. (2019). Attitude toward using Fintech among Millennials. In The 1st Workshop on Multimedia Education, Learning, Assessment and Its Implementation in Game and Gamification in Conjunction with COMDEV 2018. doi:10.4108/eai.26-1-2019.2283199


Joseph, M., & Stone, G. (2003). An empirical evaluation of US bank customer perceptions of the impact of technology on service delivery in the banking sector. International Journal of Retail & Distribution Management, 31 (4), 190-202. doi:10.1108/09590550310469185


Joseph, M., McClure, C., & Joseph, B. (1999). Service quality in the banking sector: The impact of technology on service delivery. International Journal of Bank Marketing, 17 (4), 182-193.


Kang, J. (2018). Mobile payment in Fintech environment: Trends, security challenges, and services. Human-Centric Computing and Information Sciences, 8 (1), 1-16. doi:10.1186/s13673-018-0155-4


Karjaluoto, H., Mattila, M., & Pento, T. (2002). Factors underlying attitude formation towards online banking in Finland. International Journal of Bank Marketing, 20 (6), 261-272. doi:10.1108/02652320210446724


Kim, D. (2019). “How do you feel about a disease?” The effect of psychological distance towards a disease on health communication. International Journal of Advertising, 38 (1), 139-153. doi:10.1080/02650487.2018.1438031


Kim, H., Lee, J., Mun, J., & Johnson, K. (2017). Consumer adoption of smart in-store technology: Assessing the predictive value of attitude versus beliefs in the technology acceptance model. International Journal of Fashion Design, Technology and Education, 10 (1), 26-36. doi:10.1080/17543266.2016.1177737


Lai, A. W. (1995). Consumer values, product benefits and customer value: a consumption behavior approach. ACR North American Advances, 22 (6), 381-388.


Lee, C., Li, X., Yu, C., & Zhao, J. (2021). Does fintech innovation improve bank efficiency? Evidence from China’s banking industry. International Review of Economics & Finance, 74 (4), 468-483. doi:10.1016/j.iref.2021.03.009


Lee, Y., Park, J., Chung, N., & Blakeney, A. (2012). A unified perspective on the factors influencing usage intention toward mobile financial services. Journal of Business Research, 65 (11), 1590-1599. doi:10.1016/j.jbusres.2011.02.044


Lee, J., Ryu, M., & Lee, D. (2019). A study on the reciprocal relationship between user perception and retailer perception on platform-based mobile payment service. Journal of Retailing and Consumer Services, 48 (C), 7-15. doi:10.1016/j.jretconser.2019.01.007


Li, G., Dai, J., Park, E., & Park, S. (2017). A study on the service and trend of Fintech security based on text-mining: Focused on the data of Korean online news. Journal of Computer Virology and Hacking Techniques, 13 (4), 249-255. doi:10.1007/s11416-016-0288-9


Nguyen, L. T. K., Doan, T. T. T., & Bui, T. N. (2020). Fintech and banking: Evidence from Vietnam. The Journal of Asian Finance, Economics, and Business, 7 (9), 419-426. doi:10.13106/JAFEB.2020.VOL7.NO9.419


Lim, S., Kim, D., Hur, Y., & 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. doi:10.1080/10447318.2018.1507132


Liu, Q., Yang, X., Zhu, X., & Zhang, D. (2019). Attachment anxiety, loneliness, rumination and mobile phone dependence: A cross-sectional analysis of a moderated mediation model. Current Psychology (New Brunswick, N.J.), 1(11) . doi:10.1007/s12144-019-00464-x


Luchetti, M., Lee, J., Aschwanden, D., Sesker, A., Strickhouser, J., Terracciano, A., & Sutin, A. (2020). The trajectory of loneliness in response to Covid-19. The American Psychologist, 75 (7), 897-908. doi:10.1037/amp0000690


Maes, J., Leroy, H., & Sels, L. (2014) Gender differences in entrepreneurial intentions: A tpb multi-group analysis at factor and indicator level. European Management Journal, 32 (5), 784-794.


Mariño-Mesías, R., Rodríguez-Antón, J., & Rubio-Andrada, L. (2015). How does human capital influence service quality? An application to the Andorran banking sector. Revista Española De Financiación Y Contabilidad, 44 (2), 146-179. doi:10.1080/02102412.2014.991126


Moutinho, L., & Smith, A. (2000). Modelling bank customer satisfaction through mediation of attitudes towards human and automated banking. International Journal of Bank Marketing, 18 (3), 124-134.


Nangin, M. A., Barus, I. R. G., & Wahyoedi, S. (2020). The effects of perceived ease of use, security, and promotion on trust and its implications on fintech adoption. Journal of Consumer Sciences, 5 (2), 124-138.


Persaud, A., & Azhar, I. (2012). Innovative mobile marketing via smartphones: Are consumers ready? Marketing Intelligence & Planning, 30 (4), 418-443. doi:10.1108/02634501211231883


Peteet, J. R. (2020). Covid-19 anxiety. Journal of Religion and Health, 59 (5), 2203-2204.


Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88 (5), 879-903. doi:10.1037/0021-9010.88.5.879


Ponte, E. B., Carvajal-Trujillo, E., & Escobar-Rodríguez, T. (2015). Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents. Tourism Management, 47 (2), 286-302.


Prati, G., & Mancini, A. (2021). The psychological impact of Covid-19 pandemic lockdowns: A review and meta-analysis of longitudinal studies and natural experiments. Psychological Medicine, 51 (2), 201-211. doi:10.1017/S0033291721000015


Revathy, C., & Balaji, P. (2020). Determinants of behavioural intention on e-wallet usage: An empirical examination in amid of Covid-19 lockdown period. International Journal of Management (IJM), 11 (6), 92-104.


Rodríguez-Hidalgo, A., Pantaleón, Y., Dios, I., & Falla, D. (2020). Fear of Covid-19, stress, and anxiety in university undergraduate students: A predictive model for depression. Frontiers in Psychology, 11 (3), 591797-591797. doi:10.3389/fpsyg.2020.591797


Rubin, K. H., Coplan, R. J., & Bowker, J. C. (2009). Social withdrawal in childhood. Annual Review of Psychology, 60 (1), 141-171. doi:10.1146/annurev.psych.60.110707.163642


Saadé, R., & Kira, D. (2007). Mediating the impact of technology usage on perceived ease of use by anxiety. Computers and Education, 49 (4), 1189-1204. doi:10.1016/j.compedu.2006.01.009


Simpson, J., Rholes, W., & Nelligan, J. (1992). Support seeking and support giving within couples in an anxiety-provoking situation: The role of attachment styles. Journal of Personality and Social Psychology, 62 (3), 434-446. doi:10.1037/0022-3514.62.3.434


Singh, S., Sahni, M., & Kovid, R. (2020). What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model. Management Decision, 58 (8), 1675-1697. doi:10.1108/MD-09-2019-1318


Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in relational exchanges. Journal of Marketing, 66 (1), 15-37.


Sreejesh, S., & Roy, S. (2015). A new consumer brand relationships framework. In Consumer brand relationships (pp. 165-197). London, UK: Palgrave Macmillan.


Stewart, H., & Jürjens, J. (2018). Data security and consumer trust in FinTech innovation in Germany. Information Management & Computer Security, 26 (1), 109-128. doi:10.1108/ICS-06-2017-0039


Sweeney, J., & Soutar, G. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77 (2), 203-220. doi:10.1016/S0022-4359(01)00041-0


Talwar, S., Dhir, A., Khalil, A., Mohan, G., & Islam, A. (2020). Point of adoption and beyond. Initial trust and mobile-payment continuation intention. Journal of Retailing and Consumer Services, 55 (4), Article 102086. doi:10.1016/j.jretconser.2020.102086


Trivedi, R., Patel, J., & Acharya, N. (2018). Causality analysis of media influence on environmental attitude, intention and behaviors leading to green purchasing. Journal of Cleaner Production, 196 (25), 11-22. doi:10.1016/j.jclepro.2018.06.024


Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11 (4), 342-365.


Vučinić, M. (2020). Fintech and financial stability potential influence of Fintech on financial stability, risks and benefits. Journal of Central Banking Theory and Practice (Podgorica), 9 (2), 43-66. doi:10.2478/jcbtp-2020-0013


Wójcik, D., & Ioannou, S. (2020). Covid-19 and finance: Market developments so far and potential impacts on the financial sector and centres. Tijdschrift Voor Economische En Sociale Geografie, 111 (3), 387-400. doi:10.1111/tesg.12434



DOI: https://doi.org/10.46223/HCMCOUJS.econ.en.11.2.1799.2021
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