A Conceptual Study of Technology Adoption of Online Mutual Fund Investment Platform
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Mutual Funds is an alternative investment designed as a means to raise funds from people who have capital and have the desire to invest, but only have limited time and knowledge. In addition, Mutual Funds are also expected to increase the role of local investors to invest in the capital market. To encourage an increase in the number of investors, the first online mutual fund investment platform was launched in Indonesia in 2016. Over time, similar platforms began to appear. The theory of technology adoption is implemented in this study to analyze how technology adoption of online mutual fund investment with millennials as the main object of research. Based on various literacies, there are several factors that influence a person to adopt online mutual fund investment, namely performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habits, content design quality, user interface and perceived trust.
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References
-
Ajzen, I. (1991), “The theory of planned behaviour”, Organizational Behaviour and Human Decision Processes, Vol.50, No.2, pp.179–211.
Google Scholar
1
-
Aladwani, A. M., & Palvia, P. C. (2002). Developing and validating an instrument for measuring user-perceived web quality. Information & management, 39(6), 467-476.
Google Scholar
2
-
Aladwani, A. M. (2006). An empirical test of the link between web site quality and forward enterprise integration with web consumers. Business Process Management Journal.
Google Scholar
3
-
Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018). Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40, 125-138.
Google Scholar
4
-
Ali, Hasanuddin & Purwandi, Lilik. (2016). Indonesia 2020: The Urban Middle Class Millennials.
Google Scholar
5
-
Almawadi, I. (2019, October 31). Bareksa. From Bareksa: https://www.bareksa.com/id/text/2019/10/31/jumlah-investor-melesat-dana-kelolaan-reksadana-tembus-rp5523-triliun/23492/news
Google Scholar
6
-
Alshamaila, Y., Papagiannidis, S. & Li, F. (2013), “Cloud computing adoption by smes in the North East of England: A multi-perspective framework”, Journal of Enterprise Information Management, Vo. 26, No. 3, pp. 250–275.
Google Scholar
7
-
Amoroso, D. L., & Magnier-Watanabe, R. (2012), “Building a research model for mobile wallet consumer adoption: the case of Mobile Suica in Japan”, Journal of theoretical and applied electronic commerce research, Vol. 7, No.1, pp. 94-110.
Google Scholar
8
-
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS quarterly, 399-426.
Google Scholar
9
-
Carter, L., & Weerakkody, V. (2008). E-government adoption: A cultural comparison. Information systems frontiers, 10(4), 473-482.
Google Scholar
10
-
Chang, H. H., & Chen, S. W. (2008). The impact of online store environments cues on purchase intention. Online information review.
Google Scholar
11
-
Chiu, C. C., & Yang, H. E. (2016). The impact of website design features on behavioral intentions. International journal of scientific & technology research, 5(9), 71-78.
Google Scholar
12
-
Chong, A. Y. L., Chan, F. T., & Ooi, K. B. (2012). Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia. Decision support systems, 53(1), 34-43.
Google Scholar
13
-
Chong, A. Y. L. (2013). A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption. Expert Systems with Applications, 40(4), 1240-1247.
Google Scholar
14
-
Davis, F. D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13, pp. 319–339.
Google Scholar
15
-
Dhiranty, A., Suharjo, B., & Suprayitno, G. (2017). An analysis on customer satisfaction, trust and loyalty toward online shop (a case study of tokopedia. com). Indonesian Journal Of Business And Entrepreneurship (IJBE), 3(2), 102.
Google Scholar
16
-
Flavian, C., Gurrea, R., & Orus, C. (2009). Web design: a key factor for the website success. Journal of Systems and Information Technology.
Google Scholar
17
-
Gefen, D., & Straub, D. (2003). Managing user trust in b2c e-services. E-Service, 2 (2), 7-24.
Google Scholar
18
-
Gong, W., & Li, Z. G. (2008), “Mobile Youth in China: A cultural perspective and marketing implications”, International Journal of Electronic Business, Vol. 6, No.3, pp. 261–81.
Google Scholar
19
-
Gu, J. C., Lee, S. C., & Suh, Y. H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605-11616.
Google Scholar
20
-
Hasan, B., & Ahmed, M. U. (2007). Effects of interface style on user perceptions and behavioral intention to use computer systems. Computers in Human Behavior, 23(6), 3025-3037.
Google Scholar
21
-
Khan, I. U., Hameed, Z., & Khan, S. U. (2017). Understanding online banking adoption in a developing country: UTAUT2 with cultural moderators. Journal of Global Information Management (JGIM), 25(1), 43-65.
Google Scholar
22
-
Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS quarterly, 705-737.
Google Scholar
23
-
Madan, K., & Yadav, R. (2016). Behavioral intention to adopt mobile wallet: a developing country perspective. Journal of Indian Business Research.
Google Scholar
24
-
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.
Google Scholar
25
-
Pramisti, N. Q., & Chandra, Y. (2017, April 17). Ramai-ramai Jualan Reksa Dana via Fintech. Retrieved from https://tirto.id/ramai-ramai-jualan-reksa-dana-via-fintech-cmRa
Google Scholar
26
-
Priyoharto, G. (2019, July 27). Investasi Tinggi Dorong Pertumbuhan Ekonomi dan Lapangan Kerja? Retrieved from https://news.detik.com/kolom/d-4641798/investasi-tinggi-dorong-pertumbuhan-ekonomi-dan--lapangan-kerja
Google Scholar
27
-
Raines, C. (2002). Managing Millennials.
Google Scholar
28
-
Rathnamani, V. (2013). Investor’s preferences towards mutual fund industry in Trichy. IOSR Journal of Business and Management, 6(6), 48-55.
Google Scholar
29
-
Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic commerce research and applications, 9(3), 209-216.
Google Scholar
30
-
Shatnawi, R., & Alzu'bi, A. (2011). A verification of the correspondence between design and implementation quality attributes using a hierarchical quality model. IAENG International Journal of Computer Science, 38(3), 225-233.
Google Scholar
31
-
Semuel, H., & Wijaya, S. (2019). The Analysis Website Quality, Intention to Use The Website and Behavioral Intention Netizen Indonesia Batik-Tenun Traditional Product of Indonesia (Doctoral dissertation, Petra Christian University).
Google Scholar
32
-
Shulhan, F., & Oetama, R. S. (2019, August). Analysis of Actual System Use from Bukareksa Mutual Fund Feature Using Technology Acceptance Model. In 2019 International Conference on Information Management and Technology (ICIMTech) (Vol. 1, pp. 186-191). IEEE.
Google Scholar
33
-
Singh, B. K. (2011). A Study on Investors’ Attitude towards Mutual Funds as an Investment Option . Journal Of Asian Business Strategy, VOL. 1(2), 8-15.
Google Scholar
34
-
Tornatzky, L. and Fleischer, M. (1990), The process of technology innovation, Lexington Books, Lexington, MA.
Google Scholar
35
-
Utomo, W. P. (2019). Indonesia Millennial Report 2019. IDN Research Institute.
Google Scholar
36
-
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
Google Scholar
37
-
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.
Google Scholar
38
-
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.
Google Scholar
39
-
Wakefield, R. L., Stocks, M. H., & Wilder, W. M. (2004). The role of web site characteristics in initial trust formation. Journal of Computer Information Systems, 45(1), 94-103.
Google Scholar
40
-
Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): a literature review. Journal of enterprise information management.
Google Scholar
41
-
Wu, J. H., & Wang, S. C. (2005), “What drives mobile commerce?: An Empirical evaluation of the revised technology acceptance model”, Information & Management, Vol. 42, No.5, pp.719-729.
Google Scholar
42
-
Zhang, L., Zhu, J., & Liu, Q. (2012), “A meta-analysis of mobile commerce adoption and the moderating effect of culture”, Computers in Human Behaviour, Vol. 28, No.5, pp. 1902-1911.
Google Scholar
43
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