DETERMINANTS OF THE ADOPTION OF INNOVATIVE FINTECH SERVICES BY MILLENNIALS

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dc.contributor.authorSolarz, Małgorzata
dc.contributor.authorSwacha-Lech, Magdalena
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2021-09-15T08:08:07Z
dc.date.available2021-09-15T08:08:07Z
dc.description.abstractFinTech Adoption Index, expressed as a percentage of the digitally active population, for 27 countries of the world in 2019 reached the level of 64%. Millennials are the generation which, compared to others, is characterized by the highest level of FinTech adoptions. In Poland, in 2019, about 75% of the Millennials used the services of FinTech. This paper aims to analyse and evaluate the selected determinants of using the innovative FinTech services by Millennials in Poland. To investigate how users adopt FinTech services, we have applied our own set of determinants – selected from an extensive literature review – covering both demographic, economic and behavioural characteristics. This approach allowed for an in-depth analysis of the examined issue. The essential empirical data were obtained based on the research using the CAWI method in December 2019 on a representative sample of Poles aged 25–40 at that time. Ultimately, 1,236 correctly completed questionnaires were used for the research. To analyse and evaluate the impact of selected determinants of FinTech adoption, a logistic regression model was used. The results obtained can thus be extremely important for managers of financial institutions. They provide information that can be used for activities aimed at maintaining FinTech’s customer base and allow to adjust the offer to the expectations of this group. Millennials most open to innovative FinTech services in Poland are young men with high and very high net income and not driven by low costs of financial services. They appreciate technological novelties, including the possibility of using a smartwatch, and when deciding on the choice of a financial institution, they do not care about the direct opinions of their relatives and friends, but take into account the opinions in social media.en
dc.formattext
dc.identifier.doi10.15240/tul/001/2021-3-009
dc.identifier.eissn2336-5604
dc.identifier.issn1212-3609
dc.identifier.urihttps://dspace.tul.cz/handle/15240/160963
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
dc.relation.isbasedonAarts, H., Verplanken, B., & van Knippenberg, A. (1998). Predicting Behavior from Actions in the Past: Repeated Decision Making or a Matter of Habit? Journal of Applied Social Psychology, 28(15), 1355–1374. https://doi.org/10.1111/j.1559-1816.1998.tb01681.x
dc.relation.isbasedonAjzen, I., & Fishbein, M. (1980). Attitudes and Predicting Social Behavior. Englewood Cliffs, NJ: Prentice-Hall.
dc.relation.isbasedonAlalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002
dc.relation.isbasedonAnderson, M. (2015). Technology Device Ownership: 2015. Pew Research Center. Retrieved July 20, 2020, from http://www.pewinternet.org/2015/10/29/technology-device-ownership-2015
dc.relation.isbasedonBlair, E., & Blair, J. (2015). Applied Survey Sampling. New York, NY: SAGE Publications. https://doi.org/10.4135/9781483394022
dc.relation.isbasedonBoot, A. W. (2017). The Future of Banking: From Scale & Scope Economies to Fintech 29. European Economy, 3(2), 77–95.
dc.relation.isbasedonCapgemini & Efma. (2016). World Retail Banking Report 2016. Retrieved July 19, 2020, from https://worldretailbankingreport.com/resources/world-retail-banking-report-2020/
dc.relation.isbasedonCarlin, B., Olafsson, A., & Pagel, M. (2017). Fintech Adoption across Generations: Financial Fitness in the Information Age (NBER Working Paper No. 23798). Cambridge, MA: National Bureau of Economic Research. https://doi.org/10.3386/w23798
dc.relation.isbasedonCognizant, Marketforce and Pegasystems. (2016). The Future of Retail Financial Services. Retrieved July 15, 2020, from https://www.pega.com/future-of-finance
dc.relation.isbasedonDas, A., & Das, D. (2020). Perception, Adoption, and Pattern of Usage of FinTech Services by Bank Customers: Evidences from Hojai District of Assam. Emerging Economy Studies, 6(1), 7–22. https://doi.org/10.1177%2F2394901520907728
dc.relation.isbasedonDavis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation). Massachusetts Institute of Technology, Cambridge. Retrieved July 19, 2020, from https://dspace.mit.edu/handle/1721.1/15192
dc.relation.isbasedonDavis, 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
dc.relation.isbasedonDiana, N., & Leon, F. M. (2020). Factors Affecting Continuance Intention of FinTech Payment among Millennials in Jakarta. European Journal of Business and Management Research, 5(4). https://doi.org/10.24018/ejbmr.2020.5.4.444
dc.relation.isbasedonEndsley, F., Matthews, L., & Ward, C. (2020). An Analysis of Millennials and their Interactions with Financial Institutions. Atlantic Marketing Journal, 9(2), 1–18. Retrieved April 29, 2021, from https://digitalcommons.kennesaw.edu/amj/vol9/iss2/1
dc.relation.isbasedonErnst & Young. (2017). FinTech Adoption Index: FinTech services poised for mainstream adoption in the US with 1 in 3 digitally active consumers using FinTech. Retrieved July 20, 2020, from https://www.prnewswire.com/news-releases/ey-fintech-adoption-index-fintech-services-poised-for-mainstream-adoption-in-the-us-with-1-in-3-digitally-active-consumers-using-fintech-300481126.html
dc.relation.isbasedonErnst & Young. (2019). Global FinTech Adoption Index 2019. Retrieved August 6, 2020, from https://www.ey.com/en_gl/ey-global-fintech-adoption-index
dc.relation.isbasedonEuropean Parliament. (2017). Report on FinTech: The influence of technology on the future of the financial sector (2016/2243(INI)). (EP Resolution adopted text P8_TA (2017)0211). Official Journal of the European Union, C 307/57. Retrieved July 19, 2020, from https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52017IP0211&rid=1
dc.relation.isbasedonFinancial Stability Board. (2019). FinTech and market structure in financial services: Market developments and potential financial stability implications (Report). Retrieved July 25, 2020, from https://www.fsb.org/wp-content/uploads/P140219.pdf
dc.relation.isbasedonFlavián, C., Guinalíu, M., & Torres, E. (2006). How bricks-and-mortar attributes affect online banking adoption. International Journal of Bank Marketing, 24(6), 406–423. https://doi.org/10.1108/02652320610701735
dc.relation.isbasedonGimpel, H., Rau, D., & Röglinger, M. (2018). Understanding FinTech start-ups – a taxonomy of consumer-oriented service offerings. Electronic Markets, 28(3), 245–264. https://doi.org/10.1007/s12525-017-0275-0
dc.relation.isbasedonHosmer, D. W., & Lemesbow, S. (1980). Goodness of fit tests for the multiple logistic regression model. Communications in Statistics – Theory and Methods, 9(10), 1043–1069. https://doi.org/10.1080/03610928008827941
dc.relation.isbasedonHu, Z., Ding, S., Li, S., Chen, L., & Yang, S. (2019). Adoption Intention of Fintech Services for Bank Users: An Empirical Examination with an Extended Technology Acceptance Model. Symmetry, 11(3), 340. https://doi.org/10.3390/sym11030340
dc.relation.isbasedonHuei, 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(2.29), 166–169. https://doi.org/10.14419/ijet.v7i2.29.13310
dc.relation.isbasedonInternational Monetary Fund. (2018). The Bali Fintech Agenda (IMF Policy Paper 2018/050). Washington, DC: International Monetary Fund. https://doi.org/10.5089/9781498309950.007
dc.relation.isbasedonKarahanna, E., & Straub, D. W. (1999). The psychological origins of perceived usefulness and ease-of-use. Information & Management, 35(4), 237–250. https://doi.org/10.1016/S0378-7206(98)00096-2
dc.relation.isbasedonKim, Y., Choi, J., Park, Y. J., & Yeon, J. (2016). The adoption of mobile payment services for “Fintech”. International Journal of Applied Engineering Research, 11(2), 1058–1061.
dc.relation.isbasedonKoufaris, M. (2002). Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior. Information Systems Research, 13(2), 205–223. https://doi.org/10.1287/isre.13.2.205.83
dc.relation.isbasedonKurek, R., Solarz, M., & Swacha-Lech, M. (2020). The Problem of Millennials’ Openness to Services Offered by FinTech in Poland. In K. S. Soliman (Ed.), Education Excellence and Innovation Management: A 2025 Vision to Sustain Economic Development during Global Challenges (pp. 11020–11033). Sevilla: International Business Information Management Association (IBIMA).
dc.relation.isbasedonLee, D. K. C., & Teo, E. G. S. (2015). Emergence of FinTech and the LASIC Principles. Journal of Financial Perspectives, 3(3), 1–26. https://doi.org/10.2139/ssrn.2668049
dc.relation.isbasedonLee, K. W., Tsai, M. T., & Lanting, M. C. L. (2011). From marketplace to marketspace: Investigating the consumer switch to online banking. Electronic Commerce Research and Applications, 10(1), 115–125. https://doi.org/10.1016/j.elerap.2010.08.005
dc.relation.isbasedonLi, B., Hanna, S. D., & Kim, K. T. (2020). Who Uses Mobile Payments: Fintech Potential in Users and Non-Users. Journal of Financial Counseling and Planning, 31(1), 83–100. https://doi.org/10.1891/JFCP-18-00083
dc.relation.isbasedonLiébana-Cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2014). Antecedents of the adoption of the new mobile payment systems: The moderating effect of age. Computers in Human Behavior, 35, 464–478. https://doi.org/10.1016/j.chb.2014.03.022
dc.relation.isbasedonLin, H. H., & Wang, Y. S. (2006). An examination of the determinants of customer loyalty in mobile commerce contexts. Information & Management, 43(3), 271–282. https://doi.org/10.1016/j.im.2005.08.001
dc.relation.isbasedonMallat, N. (2007). Exploring consumer adoption of mobile payments – A qualitative study. The Journal of Strategic Information Systems, 16(4), 413–432. https://doi.org/10.1016/j.jsis.2007.08.001
dc.relation.isbasedonMartins, C., Oliveira, T., & Popovič, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13. https://doi.org/10.1016/j.ijinfomgt.2013.06.002
dc.relation.isbasedonMontazemi, A. R., & Qahri-Saremi, H. (2015). Factors affecting adoption of online banking: A meta-analytic structural equation modeling study. Information & Management, 52(2), 210–226. https://doi.org/10.1016/j.im.2014.11.002
dc.relation.isbasedonMorris, M. G., Venkatesh, V., & Ackerman, P. L. (2005). Gender and age differences in employee decisions about new technology: An extension to the theory of planned behavior. IEEE Transactions on Engineering Management, 52(1), 69–84. https://doi.org/10.1109/TEM.2004.839967
dc.relation.isbasedonNangin, 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. https://doi.org/10.29244/jcs.5.2.124-138
dc.relation.isbasedonNiswah, F. M., Mutmainah, L., & Legowati, D. A. (2019). Muslim Millennial’s Intention of Donating for Charity using Fintech Platform. Journal of Islamic Monetary Economics and Finance, 5(3), 623–644. https://doi.org/10.21098/jimf.v5i3.1080
dc.relation.isbasedonOECD. (2018). Financial Markets, Insurance and Private Pensions: Digitalisation and Finance. Paris: OECD. Retrieved July 9, 2020, from https://www.oecd.org/finance/private-pensions/Financial-markets-insurance-pensions-digitalisation-and-finance.pdf
dc.relation.isbasedonPark, I., & Lee, H. (2006). Design Effects for the Weighted Mean and Total Estimators under Complex Survey Sampling. Quality Control and Applied Statistics, 51(4), 381–384.
dc.relation.isbasedonRai, A., & Patnayakuni, R. (1996). A Structural Model for CASE Adoption Behavior. Journal of Management Information Systems, 13(2), 205–234. https://doi.org/10.1080/07421222.1996.11518129
dc.relation.isbasedonRogers, E. M. (2010). Diffusion of Innovations (4th ed.). New York, NY: The Free Press.
dc.relation.isbasedonRyu, H. S. (2018). Understanding Benefit and Risk Framework of Fintech Adoption: Comparison of Early Adopters and Late Adopters. In Proceedings of the 51st Hawaii International Conference on System Sciences (pp. 3864–3873). Waikoloa Village, Hawaii. Retrieved July 29, 2020, from https://scholarspace.manoa.hawaii.edu/bitstream/10125/50374/1/paper0487.pdf https://doi.org/10.24251/HICSS.2018.486
dc.relation.isbasedonSolarz, M., & Swacha-Lech, M. (2019). Mental accounting in the context of savings and credit decisions. Evidence from Poland. Argumenta Oeconomica, 2(43), 351–384. https://doi.org/10.15611/aoe.2019.2.15
dc.relation.isbasedonStewart, H., & Jürjens, J. (2018). Data security and consumer trust in FinTech innovation in Germany. Information & Computer Security, 26(1), 109–128. https://doi.org/10.1108/ICS-06-2017-0039
dc.relation.isbasedonSwacha-Lech, M. (2017). The main challenges facing the retail banking industry in the era of digitalisation. Rozprawy Ubezpieczeniowe. Konsument na rynku usług finansowych, 4(26), 94–116. Retrieved August 16, 2020, from https://depot.ceon.pl/handle/123456789/14336
dc.relation.isbasedonSzopiński, T. S. (2016). Factors affecting the adoption of online banking in Poland. Journal of Business Research, 69(11), 4763–4768. https://doi.org/10.1016/j.jbusres.2016.04.027
dc.relation.isbasedonTang, K. L., Ooi, C. K., & Chong, J. B. (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
dc.relation.isbasedonVenkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
dc.relation.isbasedonVenkatesh, V., & Davis, F. D. (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
dc.relation.isbasedonVenkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
dc.relation.isbasedonVenkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
dc.relation.isbasedonWu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719–729, https://doi.org/10.1016/j.im.2004.07.001
dc.relation.isbasedonYee, B. Y., & Faziharudean, T. M. (2010). Factors Affecting Customer Loyalty of Using Internet Banking in Malaysia. Journal of Electronic Banking Systems, 2010(2010), ID 592297, 1–21. https://doi.org/10.5171/2010.592297
dc.relation.isbasedonYu, C. S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13(2), 104–121. Retrieved July 20, 2020, from http://www.jecr.org/node/48
dc.relation.isbasedonZavolokina, L., Dolata, M., & Schwabe, G. (2016). FinTech – What’s in a Name? Paper presented at the Thirty Seventh International Conference on Information Systems, Dublin, Ireland. https://doi.org/10.5167/uzh-126806.
dc.relation.ispartofEkonomie a Managementcs
dc.relation.ispartofEconomics and Managementen
dc.relation.isrefereedtrue
dc.rightsCC BY-NC
dc.subjectFinTechen
dc.subjectMillennialsen
dc.subjectdeterminants of using FinTech servicesen
dc.subjectperceived benefiten
dc.subjectFinTech adoptionen
dc.subject.classificationG23
dc.subject.classificationO33
dc.subject.classificationD12
dc.subject.classificationG21
dc.titleDETERMINANTS OF THE ADOPTION OF INNOVATIVE FINTECH SERVICES BY MILLENNIALSen
dc.typeArticleen
local.accessopen
local.citation.epage166
local.citation.spage149
local.facultyFaculty of Economics
local.fulltextyes
local.relation.abbreviationE+Mcs
local.relation.abbreviationE&Men
local.relation.issue3
local.relation.volume24
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