Analisis Faktor-Fator yang Mempengaruhi Penggunaan Aplikasi Investasi Reksadana Online pada Generasi Millenial dan Generasi Z
Abstract
This study aims to analyze the driving factors that can influence individuals in using mutual funds Bibit application. The proposed model has factors from the The theory of technology adoption (TAM) is implemented in this study to analyze how technology adoption of online mutual fund investment with millennial as the main object of research. This research is a quantitative research with a survey method by distributing online questionnaires. Sampling using purposive sampling method. This study Used 5 internal variables and 3 external variables which are Perceived Security, Perceived Trust and User Interface After gathering 168 data respondents, it is found that there are several factors that have positive significance to Actual System Use to adopt online mutual fund application, namely Perceived Security, User Interface, Perceived Usefulness, Perceived Ease of use, Attitude Toward Use and Behavioral Intention to Use. Meanwhile, Perceived Trust have no significance to Actual System Usage of Bibit application. This finding will be useful for online mutual fund application developers to transform conventional mutual fund to online platforms format.
Downloads
References
KSEI, “Statistik Pasar Modal,†Ksei, pp. 1–6, 2021, [Online]. Available: https://www.ksei.co.id/publications/demografi_investor.
R. A. Rahadi, E. K. Dewi, S. M. Damayanti, K. F. Afgani, I. Murtaqi, and D. Rahmawati, “Adoption Analysis of Online Mutual Fund Investment Platform for Millennials in Indonesia,†Rev. Integr. Bus. Econ. Res., vol. 10, pp. 74–81, 2021.
Capgemini Research Institute, “World FinTech Report 2020,†pp. 1–35, 2020, [Online]. Available: https://fintechworldreport.com/wp-content/uploads/sites/9/2020/04/World-FinTech-Report-WFTR-2020_Web.pdf.
IDN, “Indonesia Millennial Report,†IDN Res. Inst., vol. 01, p. 61, 2020, [Online]. Available: https://www.idntimes.com/indonesiamillennialreport2019.
B. P. S. (BPS), “BPS: 270,20 juta Penduduk Indonesia Hasil SP2020,†2021. https://www.bps.go.id/news/2021/01/21/405/bps--270-20-juta-penduduk-indonesia-hasil-sp2020.html (accessed Oct. 21, 2021).
E. K. Dewi and R. A. Rahadi, “A Conceptual Study of Technology Adoption of Online Mutual Fund Investment Platform,†Eur. J. Bus. Manag. Res., 2020, doi: 10.24018/ejbmr.2020.5.3.334.
B. K. Singh, “A study on investors ’ attitude towards mutual funds as an investment option,†J. Asian Bus. Strateg., 2011.
F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,†MIS Q. Manag. Inf. Syst., vol. 13, no. 3, pp. 319–340, 1989, doi: 10.2307/249008.
S. A. Nikou and A. A. Economides, “Mobile-based assessment: Investigating the factors that influence behavioral intention to use,†Comput. Educ., 2017, doi: 10.1016/j.compedu.2017.02.005.
L.-M. Chuang, C.-C. Liu, and H.-K. Kao, “The Adoption of Fintech Service: TAM perspective,†Int. J. Manag. Adm. Sci. (IJMAS, 2016.
F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “User acceptance of computer technology: A comparison of two theoretical models,†Manage. Sci., vol. 35, no. 8, pp. 982–1003, 1989.
H. M. Jogiyanto, “Sistem informasi keperilakuan,†Yogyakarta Andi Offset, 2007.
F. Shulhan and R. S. Oetama, “Analysis of Actual System Use from Bukareksa Mutual Fund Feature Using Technology Acceptance Model,†2019, doi: 10.1109/ICIMTech.2019.8843752.
V. Cho, T. C. E. Cheng, and W. M. J. Lai, “The role of perceived user-interface design in continued usage intention of self-paced e-learning tools,†Comput. Educ., 2009, doi: 10.1016/j.compedu.2009.01.014.
Y. M. Cheng, “Effects of quality antecedents on e-learning acceptance,†Internet Res., 2012, doi: 10.1108/10662241211235699.
G. T. Lau and S. H. Lee, “Consumers’ Trust in a Brand and the Link to Brand Loyalty,†J. Mark. Manag., 1999, doi: 10.1023/A:1009886520142.
D. Chawla and H. Joshi, “Consumer attitude and intention to adopt mobile wallet in India – An empirical study,†Int. J. Bank Mark., 2019, doi: 10.1108/IJBM-09-2018-0256.
S. Nambiar, C. T. Lu, and L. R. Liang, “Analysis of payment transaction security in mobile commerce,†2004, doi: 10.1109/iri.2004.1431506.
B. L. Handoko and L. A. A. Mozes, “Analysis of Factors Affecting Investor Intention to Use Mobile Online Mutual Fund Application,†2021, doi: 10.1145/3457640.3457658.
N. Yahyapour, “Determining factors affecting Internet to adopt banking recommender system,†Div. Ind. Mark. E-commerce, Master’s thesis, 2008.
M. N. Suseno, “PENGARUH PELATIHAN KOMUNIKASI INTERPERSONAL TERHADAP EFIKASI DIRI SEBAGAI PELATIH PADA MAHASISWA,†J. Interv. Psikol., 2009, doi: 10.20885/intervensipsikologi.vol1.iss1.art6.
A. Wibowo, “Kajian Tentang Perilaku Pengguna Sistem Informasi Dengan Pendekatan Technology Acceptance Model (TAM),†J. UBL, 2008.
G. Chandrarin, Metode Riset Akuntansi: Pendekatan Kuantitatif. 2017.
F. Joseph, H. Jr, B. J. Babin, R. E. Anderson, and W. C. Black, on Multivariate Data Analysis . Hair Jr . William C . Black Seventh Edition. 2014.
V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: Toward a unified view,†MIS Q. Manag. Inf. Syst., vol. 27, no. 3, pp. 425–478, 2003, doi: 10.2307/30036540.
I. Ghozali, “Structural equation modeling metode alternatif dengan partial least square (PLS) dilengkapi Software SmartPLS 3.00 Xistat 2014 dan WarpPLS 4.0,†Ed. ke-4. Semarang Badan Penerbit Univ. Diponegoro Semarang, 2014.
A. Leguina, “A primer on partial least squares structural equation modeling (PLS-SEM),†Int. J. Res. Method Educ., 2015, doi: 10.1080/1743727x.2015.1005806.
J. F. Hair, M. Sarstedt, L. Hopkins, and V. G. Kuppelwieser, “Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research,†European Business Review. 2014, doi: 10.1108/EBR-10-2013-0128.
M. A. Almaiah, M. A. Jalil, and M. Man, “Extending the TAM to examine the effects of quality features on mobile learning acceptance,†J. Comput. Educ., 2016, doi: 10.1007/s40692-016-0074-1