Penerapan Aplikasi Investasi Online untuk Masyarakat Indonesia (Studi Kasus di Jawa)

Masno Marjohan, Jeni Andriani, Annisa Nurlita Putri

Abstract


This study aims to analyze and determine the effect of performance goals, intention to use, business expectations, social conditions, trust and perceptions of risk affecting intentions to use online investment applications among Indonesian people, especially the people of Banten, West Java and Special Region of Jakarta. This research is an explanatory research where quantitative data for hypothesis testing is obtained through a cross-sectional survey using an online questionnaire. This study uses a questionnaire, quantitative research centers on statistical analysis of numerical data collected using large-scale survey research, from the results of 511 users of online investment applications analyzed using PLS-SEM. The results revealed that performance expectations, effort expectations, facilitation conditions, trust, and perceived risk had a significant positive effect on intentions to use online investment applications in Indonesia. Meanwhile, social influence has no significant effect on the intention to use online investment in Indonesia. The findings of this study may be useful for the private sector, which can learn more about their customers' preferences in choosing online investment applications to invest their money in Indonesia. In addition, research findings can be used to identify opportunities, mitigate risks, assess reputation, and uncover barriers such as lack of awareness, deception, and skepticism.

Keywords


Online Investment Application; Perceived Risk; Trust; UTAUT

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References


Ahmed, K., Kurnitski, J., & Olesen, B. (2017). Data for occupancy internal heat gain calculation in main building categories. Data in Brief, 15, 1030–1034.

Alalwan, A. A., Dwivedi, Y. K., & Williams, M. D. (2016). Customers’ intention and adoption of telebanking in Jordan. Information Systems Management, 33(2), 154–178.

Arias-Oliva, M., Pelegrín-Borondo, J., & Matías-Clavero, G. (2019). Variables influencing cryptocurrency use: a technology acceptance model in Spain. Frontiers in Psychology, 10, 475.

Chen, R.-S., Sun, C.-M., Helms, M. M., & Jih, W.-J. K. (2008). Aligning information technology and business strategy with a dynamic capabilities perspective: A longitudinal study of a Taiwanese Semiconductor Company. International Journal of Information Management, 28(5), 366–378.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.

Engotoit, B., Kituyi, G. M., & Moya, M. B. (2016). Influence of performance expectancy on commercial farmers’ intention to use mobile-based communication technologies for agricultural market information dissemination in Uganda. Journal of Systems and Information Technology.

Ghalandari, K. (2012). The effect of performance expectancy, effort expectancy, social influence and facilitating conditions on acceptance of e-banking services in Iran: The moderating role of age and gender. Middle-East Journal of Scientific Research, 12(6), 801–807.

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

Hamid, M. R., Sami, W., & Sidek, M. H. M. (2017). Discriminant validity assessment: Use of Fornell & Larcker criterion versus HTMT criterion. Journal of Physics: Conference Series, 890(1), 12163.

Hanif, Y., & Lallie, H. S. (2021). Security factors on the intention to use mobile banking applications in the UK older generation (55+). A mixed-method study using modified UTAUT and MTAM-with perceived cyber security, risk, and trust. Technology in Society, 67, 101693.

Li, X., Gu, X. J., & Liu, Z. G. (2009). A strategic performance measurement system for firms across supply and demand chains on the analogy of ecological succession. Ecological Economics, 68(12), 2918–2929.

Luarn, P., & Lin, H.-H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873–891.

Madan, K., & Yadav, R. (2016). Behavioural intention to adopt mobile wallet: a developing country perspective. Journal of Indian Business Research.

Manuel, H. (2019). The Effect of Convenience, Security, Trust And Quality Of Information On Online Investment Applications On Stock Investment Interest. Brawijaya University.

Martins, 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.

Nisa, E. L. K., & Juliprijanto, W. (2022). Analisis Faktor Yang Mempengaruhi Investasi Asing Langsung Di Indonesia Pada Tahun 1989 - 2019. Transekonomika, 2(1), 29–44.

Ooi, K.-B., Lee, V.-H., Tan, G. W.-H., Hew, T.-S., & Hew, J.-J. (2018). Cloud computing in manufacturing: The next industrial revolution in Malaysia? Expert Systems with Applications, 93, 376–394.

Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101–134.

Ramón-Rodríguez, C. L. (2021). Factors Affecting Blockchain Technology Acceptance in Mobile Financial Transactions and Services. Universidad Ana G Méndez-Gurabo.

Riffai, M., Grant, K., & Edgar, D. (2012). Big TAM in Oman: Exploring the promise of on-line banking, its adoption by customers and the challenges of banking in Oman. International Journal of Information Management, 32(3), 239–250.

Riquelme, H. E., & Rios, R. E. (2010). The moderating effect of gender in the adoption of mobile banking. International Journal of Bank Marketing, 28(5), 328–341.

San Martin-Reyna, J. M., & Duran-Encalada, J. A. (2012). The relationship among family business, corporate governance and firm performance: Evidence from the Mexican stock exchange. Journal of Family Business Strategy, 3(2), 106–117.

Sánchez-Torres, D. A. (2017). Accesibilidad a los servicios de salud: debate teórico sobre determinantes e implicaciones en la política pública de salud. Revista Médica Del Instituto Mexicano Del Seguro Social, 55(1), 82–89.

Shulhan, F., & Oetama, R. S. (2019). Analysis of Actual System Use from Bukareksa Mutual Fund Feature Using Technology Acceptance Model. 2019 International Conference on Information Management and Technology (ICIMTech), 1, 186–191.

Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015). Modeling consumers’ adoption intentions of remote mobile payments in the United Kingdom: extending UTAUT with innovativeness, risk, and trust. Psychology & Marketing, 32(8), 860–873.

Suryono, R. R., Budi, I., & Purwandari, B. (2020). Challenges and trends of financial technology (Fintech): a systematic literature review. Information, 11(12), 590.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425–478.




DOI: http://dx.doi.org/10.29040/jap.v23i2.6863

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Jurnal Akuntansi dan Pajak, ISSN 1412-629X l E-ISSN 2579-3055

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