Memahami Dimensi Ketidakpastian dari Layanan Perdagangan Saham Online di Indonesia

Authors

  • Umar Kholifa Al Ghifari Fakultas Ekonomi dan Bisnis, Universitas Trisakti, DKI Jakarta, Indonesia
  • Fanny Roswita Ria Fakultas Ekonomi dan Bisnis, Universitas Trisakti, DKI Jakarta, Indonesia
  • Zahrina Fajrina Fakultas Ekonomi dan Bisnis, Universitas Trisakti, DKI Jakarta, Indonesia
  • Farah Margaretha Leon Fakultas Ekonomi dan Bisnis, Universitas Trisakti, DKI Jakarta, Indonesia

DOI:

https://doi.org/10.32832/inovator.v11i2.7189

Keywords:

Ketidakpastian, Kepercayaan, Manfaat Yang Dirasakan, Perdagangan Saham Online.

Abstract

"Abstraksi
Pesatnya perkembangan teknologi membuat sebagian masyarakat beralih dari jual beli tradisional menjadi perdagangan online, termasuk dalam perdagangan saham. Terdapat beberapa ketidakpastian dalam perdagangan saham secara online. Penelitian ini bertujuan untuk mengetahui efek dari berbagai ketidakpastian terhadap niat adopsi perdagangan saham secara online di Indonesia. Penelitian juga menjelaskan pengaruh kepercayaan dan manfaat yang diterima sebagai moderasi antara berbagai dimensi ketidakpastian dengan niat adopsi perdagangan saham online. Sampel penelitian didapatkan melalui kuesioner terhadap 170 responden. Responden adalah pelaku perdagangan saham. Studi menemukan efek negatif yang signifikan dari ketidakpastian teknologi yang dirasakan, ketidakpastian peraturan yang dirasakan, dan layanan tidak berwujud yang dirasakan terhadap niat adopsi perdagangan saham online. Asimetris informasi yang dirasakan tidak memiliki efek yang signifikan terhadap niat adopsi perdagangan saham online. Variabel kepercayaan dan manfaat yang dirasakan, masing-masing secara signifikan memoderasi hubungan antara niat adopsi perdagangan saham online dengan ketidakpastian teknologi yang dirasakan, ketidakpastian peraturan yang dirasakan, dan layanan tidak berwujud.
Abstract
The rapid development of technology has made some people switch from traditional trading to online trading, including in stock trading. There are some uncertainties in online stock trading. This study aims to determine the effect of various uncer- tainties on the intentions to adopt online stock trading in Indonesia. The study also explains the effect of trust and perceived benefits as a moderator between various dimensions of uncertainty with the intentions to adopt online stock trading. The research sample was obtained through a questionnaire to 170 respondents. Re- spondents are stock traders. The study found a significant negative effect of per- ceived technology uncertainty, perceived regulatory uncertainty, and perceived service intangibility on intentions to adopt online stock trading. Perceived infor- mation asymmetry does not have a significant effect on intentions to adopt online stock trading. Trust and perceived benefits, significantly moderated the relation- ship between intentions to adopt online stock trading with perceived technology
uncertainty, perceived regulatory uncertainty, and perceived service intangibility.

"

References

"Barbosa, L., Ferrí£o, P., Rodrigues, A., & Sar- dinha, A. (2018). Feed-in tariffs with mini- mum price guarantees and regulatory un- certainty. Energy Economics, 72. https://doi.org/10.1016/j.en- eco.2018.04.028

Boateng, H., Adam, D. R., Okoe, A. F., & An- ning-Dorson, T. (2016). Assessing the de- terminants of internet banking adoption intentions: A social cognitive theory per- spective. Computers in Human Behavior, 65.

https://doi.org/10.1016/j.chb.2016.09.017

Chen, Y., Yan, X., Fan, W., & Gordon, M. (2015). The joint moderating role of trust propen- sity and gender on consumers' online shopping behavior. Computers in Human Behavior, 43.

https://doi.org/10.1016/j.chb.2014.10.020

Fransisca, D. (2019). Perlindungan Hukum Bagi Investor Online Trading Saham Akibat Penggunaan Sistem Aplikasi yang Bermasa- lah.

Ghozali, I. (2018). Aplikasi Analisis Multivari- ate dengan Program IBM SPSS 25 (ke-9th ed.). Semarang: Badan Penerbit Universi- tas Diponegoro. In (Edisi 9). Semarang: Ba- dan Penerbit Universitas Diponegoro.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sar- stedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Second Edition. In California: Sage.

Jansen, J., & van Schaik, P. (2018). Testing a model of precautionary online behaviour: The case of online banking. Computers in Human Behavior, 87.

https://doi.org/10.1016/j.chb.2018.05.010

Johnson, V. L., Kiser, A., Washington, R., & Torres, R. (2018). Limitations to the rapid adoption of M-payment services: Under- standing the impact of privacy risk on M- Payment services. Computers in Human Be- havior, 79.

https://doi.org/10.1016/j.chb.2017.10.035

Kemenkominfo. (2021, September). https://aptika.kominfo.go.id/2021/09/warga- net-meningkat-indonesia-perlu-tingkatkan- nilai-budaya-di-internet/.

Khan, S. U., Liu, X. dong, Liu, C., Khan, I. U., & Hameed, Z. (2021). Understanding uncer- tainty dimensions and Internet stock trad- ing service in China from a social cognitive perspective. Information Technology and People, 34(2), 812–834.

https://doi.org/10.1108/ITP-02-2019- 0062

Khan, S. U., Liu, X., Khan, I. U., Liu, C., & Rasheed, M. I. (2020). Assessing the inves- tors' acceptance of electronic stock trading in a developing Country: The mediating role of perceived risk dimensions. Infor- mation Resources Management Journal, 33(1). https://doi.org/10.4018/IRMJ.202001010 4

Khedmatgozar, H. R., & Shahnazi, A. (2018). The role of dimensions of perceived risk in adoption of corporate internet banking by customers in Iran. Electronic Commerce Re- search, 18(2).

https://doi.org/10.1007/s10660-017- 9253-z

KSEI. (2021). Statistik Pasar Modal Indonesia. www.ksei.co.id

Nepomuceno, M. V., Laroche, M., & Richard,

M. O. (2014). How to reduce perceived risk when buying online: The interactions be- tween intangibility, product knowledge, brand familiarity, privacy and security concerns. Journal of Retailing and Consumer Services, 21(4).

https://doi.org/10.1016/j.jretcon- ser.2013.11.006

Ranaldo, A., & Somogyi, F. (2021). Asymmetric information risk in FX markets. Journal of Financial Economics, 140(2). https://doi.org/10.1016/j.jfineco.2020.12. 007

Shen, J., & Shafiq, M. O. (2020). Short-term stock market price trend prediction using a com- prehensive deep learning system. Journal of Big Data, 7(1). https://doi.org/10.1186/s40537-020- 00333-6

Vidayana. (2012). Faktor-Faktor Yang Mempengaruhi Minat Investor Dalam Menggunakan Sistem Perdagangan Sa- ham Online. Journal of Business Strategy and Execution, 5(1).

Wong, K. H., Chang, H. H., & Yeh, C. H. (2019).

The effects of consumption values and re- lational benefits on smartphone brand switching behavior. Information Technology and People, 32(1). https://doi.org/10.1108/ITP-02-2018- 0064

Yang, Y., Liu, Y., Li, H., & Yu, B. (2015). Under- standing perceived risks in mobile pay- ment acceptance. Industrial Management and Data Systems, 115(2). https://doi.org/10.1108/IMDS-08-2014- 0243

"

Downloads

Published

2022-05-09

How to Cite

Al Ghifari, U. K., Ria, F. R., Fajrina, Z., & Leon, F. M. (2022). Memahami Dimensi Ketidakpastian dari Layanan Perdagangan Saham Online di Indonesia. Inovator, 11(2), 331–340. https://doi.org/10.32832/inovator.v11i2.7189

Issue

Section

Artikel