Mengukur Prilaku Pinjaman Online Melalui Literasi Keuangan Digital, Preferensi Risiko dan Faktor Demografi Sebagai Variabel Moderasi

  • Maivalinda Maivalinda Fakultas Ekonomi dan Bisnis Universitas Dharma Andalas
  • Henny Sulistianingsih Fakultas Ekonomi dan Bisnis Universitas Dharma Andalas
  • Tri Rachmat Riski Fakultas Ekonomi dan Bisnis Universitas Dharma Andalas
Keywords: Demographic Factors, Digital Financial Literacy, Risk Preferences, Online Loan Financial Behavior, Faktor Demografi, Literasi Keuangan Digital, Preferensi Risiko, Prilaku Keuangan Pinjaman Online

Abstract

This study aims to measure the financial behavior of online loans through digital financial literacy variables, risk preferences and demographic factors. This research also looks at the positive interaction of digital financial literacy with financial behavior and risk preference with financial behavior and demographic factors as a moderation. The number of samples was selected using the convenience sampling method. The analytical method uses Structural Equation Modeling Partial Least Square (SEM PLS) analysis. The results of this study conclude that digital financial literacy and demographic factors have a significant effect on online loan financial behavior. Digital financial literacy has a significant effect on online loan financial behavior but demographic factors do not affect risk preference. Likewise, risk preference has no effect on online loan financial behavior. Demographic factors moderate digital financial literacy and financial behavior but demographic factors do not moderate risk preferences for online loan financial behavior.

 

ABSTRAK

Penelitian ini bertujuan untuk mengukur prilaku keuangan pinjaman online melalui variabel variabel literasi keuangan digital, preferensi risiko dan faktor demografi. Penelitian ini juga melihat interaksi positif dari literasi keuangan digital dengan prilaku keuangan dan preferensi risiko dengan prilaku keuangan dengan faktor demografi sebagai moderasinya. Jumlah sampel dipilih dengan menggunakan metode convenience sampling. Metode analisis menggunakan analisis Structural Equation Modelling Partial Least Square (SEM PLS). Hasil penelitian ini menyimpulkan bahwa literasi keuangan digital dan faktor demografi berpengaruh signifikan terhadap prilaku keuangan pinjaman online. Literasi keuangan digital berpengaruh signifikan terhadap prilaku keuangan pinjaman online tetapi faktor demografi tidak berpengaruh terhadap preferensi risiko. Demikian juga preferensi risiko tidak berpengaruh terhadap prilaku keuangan pinjaman online. Faktor demografi memoderasi literasi keuangan digital dan perilaku keuangan namun faktor demografi tidak memoderasi preferensi risiko terhadap prilaku keuangan pinjaman online.

References

AFI. (2021). Digital Financial Literacy: Guideline Note. 45, 1–24.
Brown, Sarah, P. S. and K. T. (2008). Debt and Referense: A Household Level Analysis (Issue January).
Brown, S., Garino, G., Simmons, P., & Taylor, K. (2008). Debt and Risk Preference: A Household Level Analysis. In TheSurvey of Consumer Finances. www.shef.ac.uk/economics
Calvo-pardo, H., & Haliassos, M. (2019). INFORMATIVE SOCIAL INTERACTIONS. https://doi.org/Cambridge Working Papers in Economics: 1911
Carlsson, H., Larsson, S., Svensson, L., & Åström, F. (2017). Consumer Credit Behavior in the Digital Context: A Bibliometric Analysis and Literature Review. Journal of Financial Counseling and Planning, 28(1), 76–94. https://doi.org/10.1891/1052-3073.28.1.76
Cwynar, A., Cwynar, W., Kowerski, M., Filipek, K., & Szuba, P. (2020). Debt literacy and debt advice-seeking behaviour among Facebook users: The role of social networks. Baltic Journal of Economics, 20(1), 1–33. https://doi.org/10.1080/1406099X.2019.1693142
Dorresteijn, F. van. (2017). Which socio-demographic factors determine risk taking behaviour of investors ? 37.
Ghozali, I. (2014). Structural Equation Modeling: Metode alternatif dengan Partial Least Squares (PLS) Dilengkapi Sofware Smartpls 3.0 Xlstat 2014 dan WarpPLS 4.0. Badan Penerbit-UNDIP.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202
Huston, S. J. (2010). Measuring Financial Literacy. Journal of Consumer Affairs, 44(2), 296–316. https://doi.org/10.1111/j.1745-6606.2010.01170.x
Iriani, A. R., Rahayu, C. W. E., & Rahmawati, C. H. T. (2021). The influence of demographic factors and financial literacy on the financial behavior. Jurnal Kajian Manajemen Bisnis, 10(1), 33. https://doi.org/10.24036/jkmb.11220500
Johnen, C., Parlasca, M., & Mußhoff, O. (2021). Promises and pitfalls of digital credit: Empirical evidence from Kenya. PLoS ONE, 16(7 July), 1–14. https://doi.org/10.1371/journal.pone.0255215
Karaa, I. E., & Kuğu, T. D. (2016). Determining advanced and basic financial literacy relations and overconfidence, and informative social media association of university students in Turkey. Kuram ve Uygulamada Egitim Bilimleri, 16(6), 1865–1891. https://doi.org/10.12738/estp.2016.6.0415
Kass-Hanna, J., Lyons, A. C., & Liu, F. (2022). Building financial resilience through financial and digital literacy in South Asia and Sub-Saharan Africa. Emerging Markets Review, 51, 100846. https://doi.org/10.1016/j.ememar.2021.100846
Leuermann, A. (2012). Essays on Risk Preferences and Behavioral Finance. August.
Lusardi, A., & Tufano, P. (2015). Debt literacy, financial experiences, and overindebtedness. In Journal of Pension Economics and Finance (Vol. 14, Issue 4). https://doi.org/10.1017/S1474747215000232
Mudzingiri, C., Muteba Mwamba, J. W., & Keyser, J. N. (2018a). Financial behavior, confidence, risk preferences and financial literacy of university students. Cogent Economics and Finance, 6(1), 1–25. https://doi.org/10.1080/23322039.2018.1512366
Mudzingiri, C., Muteba Mwamba, J. W., & Keyser, J. N. (2018b). Financial behavior, confidence, risk preferences and financial literacy of university students. Cogent Economics and Finance, 6(1), 1–25. https://doi.org/10.1080/23322039.2018.1512366
Prasad, H., Meghwal, D., & Dayama, V. (2018). Digital Financial Literacy: A Study of Households of Udaipur. Journal of Business and Management, 5(January), 23–32. https://doi.org/10.3126/jbm.v5i0.27385
Raaij, W. F. van. (2016). R i s k P re f e re n c e. In Chapter 14.
Rahmah, S., Nazir Ahmad, G., & Gurendrawati, E. (n.d.). THE EFFECT OF FINANCIAL LITERACY AND DEMOGRAPHIC FACTORS ON THE DECISION MAKING OF ONLINE CREDIT ON MILLENNIALS IN JABODETABEK.
Rahman, M., Azma, N., Masud, M. A. K., & Ismail, Y. (2020). Determinants of indebtedness: Influence of behavioral and demographic factors. International Journal of Financial Studies, 8(1). https://doi.org/10.3390/ijfs8010008
Remund, D. L. (2010). Financial Literacy Explicated: The Case for a Clearer Definition in an Increasingly Complex Economy. Journal of Consumer Affairs, 44(2), 276–295. https://doi.org/10.1111/j.1745-6606.2010.01169.x
Risna Kartika. (2020). Analisis Peer To Peer Lending Di Indonesia. AKUNTABILITAS: Jurnal Ilmiah Ilmu-Ilmu Ekonomi, 12(2), 75–86. https://doi.org/10.35457/akuntabilitas.v12i2.902
Setiawan, M., Effendi, N., Santoso, T., Dewi, V. I., & Sapulette, M. S. (2022). Digital financial literacy, current behavior of saving and spending and its future foresight. Economics of Innovation and New Technology, 31(4), 320–338. https://doi.org/10.1080/10438599.2020.1799142
Setyorini, R., Wijayangka, C., Haikal, F., & Nugraha, N. (2021). The Relationship Between Financial Literation Towards Users Of Loan Transacted Applications In The Millennial Generation. Jurnal Manajemen Indonesia, 21(3), 238. https://doi.org/10.25124/jmi.v21i3.3571
STATISTIK Fintech Lending Periode Februari 2022. (n.d.).
Stavins, J. (n.d.). The effect of demographics on payment behavior: Panel data with sample selection. http://hdl.handle.net/10419/171759http://www.bostonfed.org/economic/wp/index.htm.
Yang, Y., Sun, Y., Xu, Y., Wu, F., Zhuang, Y., Wang, C., & Gu, M. (2019). Understanding default behavior in online lending. International Conference on Information and Knowledge Management, Proceedings, 2043–2052. https://doi.org/10.1145/3357384.3358052
Published
2023-07-31