Adoption of Fintech by Labuhanbatu Students

Ade Parlaungan  Nasution; Yudi Prayoga; Muhammad Yasir Arafat  Pohan; Zulkifli Musannif Efendi  Siregar

doi:10.23887/ijssb.v7i1.53599

Authors

Ade Parlaungan Nasution Universitas Labuhanbatu, Rantauprapat, Indonesia
Yudi Prayoga Universitas Labuhanbatu, Rantauprapat, Indonesia
Muhammad Yasir Arafat Pohan Universitas Labuhanbatu, Rantauprapat, Indonesia
Zulkifli Musannif Efendi Siregar Universitas Labuhanbatu, Rantauprapat, Indonesia

DOI:

https://doi.org/10.23887/ijssb.v7i1.53599

Keywords:

Fintech, Perceive Ease of Use, Perceive Usefulness

Abstract

The financial services industry is witnessing massive structural changes due to various technological innovations. The ubiquitous innovation known as Financial Technology (Fintech) is changing traditional banking and corporate finance. The use of Fintech has now become widespread and has changed people's financial patterns. Fintech provides various conveniences in various activities related to payments, money transfers, and even the management of savings itself, even the use of Fintech currently plays a significant role in the progress of small and medium enterprises. In various big cities in Indonesia, small community-owned businesses are familiar with using Fintech as payment. However, based on the observations of researchers, it is known that in Labuhanbatu, the use of Fintech is still infrequent. Therefore, this study aims to analyses the factors which affect the intention to use Fintech in Labuhanbatu. This study uses a quantitative approach and data analysis using the Smart PLS3 software. The sample in this study was students in Labuhanbatu. This study uses the PLS technique which is a variance-based SEM which is suitable for this study due to the sample size and complexity of the hypothesis. From the study's results, it was found that all predictive variables had a positive and significant influence on the intention to use Fintech by Labuhanbatu students.

References

Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22(5), 453–474. https://doi.org/https://doi.org/10.1016/0022-1031(86)90045-4. DOI: https://doi.org/10.1016/0022-1031(86)90045-4

Al-Okaily, M., Al Natour, A. R., Shishan, F., Al-Dmour, A., Alghazzawi, R., & Alsharairi, M. (2021). Sustainable FinTech innovation orientation: a moderated model. Sustainability, 13(24), 13591. https://doi.org/10.3390/su132413591. DOI: https://doi.org/10.3390/su132413591

Arpaci, I., & Basol, G. (2020). The impact of preservice teachers’ cognitive and technological perceptions on their continuous intention to use flipped classroom. Education and Information Technologies, 3503–3514. https://doi.org/10.1007/s10639-020-10104-8. DOI: https://doi.org/10.1007/s10639-020-10104-8

Barbu, C. M., Florea, D. L., Dabija, D.-C., & Barbu, M. C. R. (2021). Customer Experience in Fintech. Journal of Theoretical and Applied Electronic Commerce Research, 16(5), 1415–1433. https://doi.org/10.3390/jtaer16050080. DOI: https://doi.org/10.3390/jtaer16050080

Broby, D. (2019). Strategic Fintech. Journal Centre for Financial Regulation and Innovation, 1–13. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3404518.

Cooper, D. R., & Schindler, P. S. (2014). Business Research Methods 12th Edition. In Business Research Methods.

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–339. https://doi.org/10.2307/249008. DOI: https://doi.org/10.2307/249008

Feng, T., Tien, C., Feng, Z., & Lai, P. (2014). Web Site Quality and Online Trading Influences on Customer Acceptance of Securities Brokers. 19(March 1997), 6126. https://doi.org/10.6126/APMR.2014.19.1.02.

Glosten, L., & Rauterberg, G. (2018). Disrupting Finance FinTech and Strategy in the 21st Century. In The New Stock Market. https://doi.org/10.7312/fox-18196-006. DOI: https://doi.org/10.7312/fox-18196

Hair, Joe 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. https://doi.org/10.1108/EBR-10-2013-0128. DOI: https://doi.org/10.1108/EBR-10-2013-0128

Hair, Joseph F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203. DOI: https://doi.org/10.1108/EBR-11-2018-0203

He, D., Leckow, R., Haksar, V., Mancini-, T., Jenkinson, N., Kashima, M., Khiaonarong, T., Rochon, C., & Tourpe, H. (2017). Fintech and Financial Services : Initial Considerations. International Monetary Fund.

Jiang, C., Zhao, W., Sun, X., Zhang, K., Zheng, R., & Qu, W. (2016). The effects of the self and social identity on the intention to microblog: An extension of the theory of planned behavior. Computers in Human Behavior, 64, 754–759. https://doi.org/https://doi.org/10.1016/j.chb.2016.07.046. DOI: https://doi.org/10.1016/j.chb.2016.07.046

Jiang, M. Y.-C., Jong, M. S.-Y., Lau, W. W.-F., Meng, Y.-L., Chai, C.-S., & Chen, M. (2021). Validating the General Extended Technology Acceptance Model for E-Learning: Evidence From an Online English as a Foreign Language Course Amid COVID-19. Frontiers in Psychology, 12, 671615. https://doi.org/10.3389/fpsyg.2021.671615. DOI: https://doi.org/10.3389/fpsyg.2021.671615

Kaba, B., & Touré, B. (2014). Understanding Information and Communication Technology Behavioral Intention to Use : Applying the UTAUT Model to Social Networking Site Adoption by Young People in a Least Developed Country. 65(8), 1662–1674. https://doi.org/10.1002/asi. DOI: https://doi.org/10.1002/asi.23069

Kline, R. B. (2011). Principles and practice of structural equation modeling, 3rd ed. In Principles and practice of structural equation modeling, 3rd ed. Guilford Press.

Kumar, P., Pillai, R., Kumar, N., & Tabash, M. I. (2022). The interplay of skills, digital financial literacy, capability, and autonomy in financial decision making and well-being. Borsa Istanbul Review. https://doi.org/10.1016/j.bir.2022.09.012. DOI: https://doi.org/10.1016/j.bir.2022.09.012

Lee, I., & Shin, Y. J. (2018). Fintech: Ecosystem, business models, investment decisions, and challenges. Business Horizons, 61(1), 35–46. https://doi.org/10.1016/j.bushor.2017.09.003. DOI: https://doi.org/10.1016/j.bushor.2017.09.003

Leong, C., Tan, B., Xiao, X., Tan, F. T. C., & Sun, Y. (2017). Nurturing a FinTech ecosystem: The case of a youth microloan startup in China. International Journal of Information Management, 37(2), 92–97. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2016.11.006. DOI: https://doi.org/10.1016/j.ijinfomgt.2016.11.006

McKim, C. A. (2017). The Value of Mixed Methods Research: A Mixed Methods Study. Journal of Mixed Methods Research, 11(2). https://doi.org/10.1177/1558689815607096. DOI: https://doi.org/10.1177/1558689815607096

Mention, A. L. (2019). The Future of Fintech. Research Technology Management. Research Technology Management, 62(4), 59–63. https://doi.org/10.1080/08956308.2019.1613123. DOI: https://doi.org/10.1080/08956308.2019.1613123

Nurhayati, S., Nurjamil, N., & Fadhillah, M. H. (2022). Measuring Opportunities and Challenges in Dispute Resolution of Fintech Sharia Business Through LAPS. Batulis Civil Law Review, 3(1), 1–7. https://doi.org/10.47268/ballrev.v3i1.929. DOI: https://doi.org/10.47268/ballrev.v3i1.929

Ooi, K., & Tan, G. W.-H. (2016). Mobile technology acceptance model: An investigation using mobile users to explore smartphone credit card. Expert Syst. Appl., 59, 33–46. https://doi.org/10.1016/j.eswa.2016.04.015. DOI: https://doi.org/10.1016/j.eswa.2016.04.015

Palinggi, S., & Allolinggi, L. R. (2020). Analisa Deskriptif Industri Fintech di Indonesia: Regulasi dan Keamanan Jaringan dalam Perspektif Teknologi Digital. Ekonomi Dan Bisnis, 6(2), 177. https://doi.org/10.35590/jeb.v6i2.1327. DOI: https://doi.org/10.35590/jeb.v6i2.1327

Palmié, M., Wincent, J., Parida, V., & Caglar, U. (2020). The evolution of the financial technology ecosystem: An introduction and agenda for future research on disruptive innovations in ecosystems. Technological Forecasting and Social Change, 151. https://doi.org/10.1016/j.techfore.2019.119779. DOI: https://doi.org/10.1016/j.techfore.2019.119779

Persada, S. F., Miraja, B. A., & Nadlifatin, R. (2019). Understanding the Generation Z Behavior on D-Learning: A Unified Theory of Acceptance and Use of Technology (UTAUT) Approach. International Journal of Emerging Technologies in Learning (IJET), 14(05 SE-Papers), 20–33. https://doi.org/10.3991/ijet.v14i05.9993. DOI: https://doi.org/10.3991/ijet.v14i05.9993

Prasojo, L. D., Habibi, A., Mukminin, A., Sofyan, Indrayana, B., & Anwar, K. (2020). Factors influencing intention to use web 2.0 in Indonesian vocational high schools. International Journal of Emerging Technologies in Learning, 15(5), 100–118. https://doi.org/10.3991/ijet.v15i05.10605. DOI: https://doi.org/10.3991/ijet.v15i05.10605

Purwanto, A. (2020). Revealing the Intervening Effect of Fintech Lending between Entrepreneurial Education and Entrepreneurial Intentions. . International Journal of Advanced Science and Technology. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3986615.

Qekaj-Thaqi, A., & Thaqi, L. (2021). The Importance of Information and Communication Technologies (ICT) during the COVID-19—Pandemic in Case of Kosovo (Analytical Approach of Students Perspective). OALib, 08(07), 1–15. https://doi.org/10.4236/oalib.1106996. DOI: https://doi.org/10.4236/oalib.1106996

Reinartz, W., Haenlein, M., & Henseler, J. (2009). Intern . J . of Research in Marketing An empirical comparison of the ef fi cacy of covariance-based and variance-based SEM. International Journal of Research in Marketing, 26(4), 332–344. https://doi.org/10.1016/j.ijresmar.2009.08.001. DOI: https://doi.org/10.1016/j.ijresmar.2009.08.001

Ribeiro, N., Nguyen, T., Duarte, A. P., Torres de Oliveira, R., & Faustino, C. (2021). How managerial coaching promotes employees’ affective commitment and individual performance. International Journal of Productivity and Performance Management, 70(8), 2163–2181. https://doi.org/10.1108/IJPPM-10-2018-0373. DOI: https://doi.org/10.1108/IJPPM-10-2018-0373

Shin, D.-H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25(6), 1343–1354. https://doi.org/https://doi.org/10.1016/j.chb.2009.06.001. DOI: https://doi.org/10.1016/j.chb.2009.06.001

Suni Astini, N. K. (2020). Tantangan Dan Peluang Pemanfaatan Teknologi Informasi Dalam Pembelajaran Online Masa Covid-19. Cetta: Jurnal Ilmu Pendidikan, 3(2), 241–255. https://doi.org/10.37329/cetta.v3i2.452. DOI: https://doi.org/10.37329/cetta.v3i2.452

Venkatesh, 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. DOI: https://doi.org/10.1287/mnsc.46.2.186.11926

Weston, R., & Gore, P. A. (2006). A Brief Guide to Structural Equation Modeling. The Counseling Psychologist, 34(5), 719–751. https://doi.org/10.1177/0011000006286345. DOI: https://doi.org/10.1177/0011000006286345

Yuniarti, S., & Rasyid, A. (2020). Consumer Protection in Lending Fintech Transaction in Indonesia: Opportunities and Challenges. Journal of Physics: Conference Series, 1477(5). https://doi.org/10.1088/1742-6596/1477/5/052016itle. DOI: https://doi.org/10.1088/1742-6596/1477/5/052016