ACCEPTANCE OF STREAMING APPLICATIONS: INFLUENCING ONLINE TRADING BY INVESTORS ON THE STOCK EXCHANGE OF THAILAND

Authors

  • Amornratn Gosanlawidr Suan Sunandha Rajabhat University
  • Samanan Rattanasirivilai Suan Sunandha Rajabhat University
  • Wanphen Kuensman Suan Sunandha Rajabhat University

Keywords:

Investor Readiness, Personality Traits, Intelligent Applications, Application Acceptance

Abstract

This research employed the mixed-method approach, combining quantitative and qualitative research methods, with the objective of studying causal factors influencing the acceptance of streaming applications for online trading by investors on the Stock Exchange of Thailand. In-depth interviews with key informants were conducted for qualitative research. For the quantitative research, the researcher defined the population as online investors on the Stock Exchange of Thailand, numbering no more than 2,299,494 individuals. A stratified random sampling method was used to select a sample size of 311 individuals to determine the research area and conduct population sampling. Research tools included questionnaires, with a questionnaire reliability coefficient of 0.924. Data analysis from the questionnaire included mean, standard deviation, percentage, and structural equation modeling analysis.

Findings were as follows: investors attitudes and perceived streaming efficiency significantly influenced the acceptance of streaming applications for online trading on the Stock Exchange of Thailand. Additionally, investors’ readiness indirectly affected acceptance through investor attitudes. Among these factors, investors attitudes were found to be the most significant factors of totally affecting the acceptance of streaming applications, followed by investor readiness and perceived streaming efficiency, respectively.

References

Agustina, D. (2019). Extension of technology acceptance model (Etam): Adoptoin of cryptocurrency online trading technology. Jurnal Ekonomi, 24(02), 227-287. doi: 10.24912/je/v24i2.590

Best, J. W. & Kahn, J. V. (1993). Research in education. Boston: Allyn and Bacon.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.

Dastan, I., & Gurler, C., (2016). Factors affecting the adoption of mobile payment systems: An empirical analysis. Emerging Markets Journal, 6(1), 17-24. Doi: 10.5195/emaj.2016.95.

Douglas, M. (2015). Trading in the zone: Master the market with confidence, discipline and a winning attitude (Thanersawatta, S. Trans.) (Hussarangsri, E. & Hussarangsri, K. Eds.). BKK: Nsix.

Fan, L., & Chatterjee, S. (2020). The utilization of robo-advisors by individual investors: An analysis using diffusion of innovation and information search frameworks. Journal of Financial Counselling and Planning, 31(1), 130-145.

Glaser, B. & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research. New York: Aldine De Gruyter.

Guba, E. G. & Lincoln, Y. S. (1994). Competing paradigms in qualitative research. In Denzin, N. K. and Lincoln, Y. S. (Eds), Handbook of qualitative research. Thousand Oaks, CA: Sage.

Kline, R. B. (2005). Principle and practice of structural equation modeling. New York: Guilford.

Lai, C. (2019). Personality traits and stock investment of individuals. Sustainability, 11(19), 5474.

Markowitz, H. (1952, March). Portfolio selection. The Journal of Finance, 7(1), 77-91. JSTOR. https://www.jstor.org/about/terms.html

Nair, P. S., Shiva, A., Yadav, N., & Tandon, P. (2023). Determinants of moblie apps adoption by retail investors for online trading in emerging financial markets. Benchmarking An International Journal, 30(5), 1623-1648. https://doi.org/10.1108/BIJ-01-2022-0019

Parasuraman, A., & Colby, C. L. (2014). An updated and streamlined technology readiness index: TRI 2.0. Journal of Service Research, 18(1), 59-74, doi: 10.1177/1094670514539730

Razak, L. A., Pontoh, G. T., Imran, H., & Yamin, M. (2018). The effect to XBRL adoption on the investors’ trading behavior in Indonesia Stock Exchange (pp. 156-162). In Proceedings of the 3rd International Conference on Accounting, Management and Economics. Makassar, Indonesia.

SET. (2023). Market data and statistics. https://www.set.or.th/market/statistics

Swanson, R. A. (1999). The foundations of performance improvement and implicatio. Torraco (Ed.), The theory and practice of performance improvement. Berret: San Francisco.

Swanson, R. A., & Gradous, D. (1988). Forecasting financial benefits of human resource development. San Francisco: Jossey-Bass.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F., (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://nwresearch.wikispaces.com

Vaddadi, K. M. & Pratima, M. (2016). Investor’s attitude towards adoption of online trading: (A study on online investors behaviour in Visakhapatnam City). Asian Jouranl of Research in Business Economics and Management, 6(2), 12-31. Doi: 10.2958/2249-7307.2016.00008.6

Vits, J. & Gelders, L. (2002). Performance improvement theory. International Journal of Production Economics, 77(3), 285-298, https://www.sciencedirect.com

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Published

2024-11-05

How to Cite

Gosanlawidr, A., Rattanasirivilai, S. ., & Kuensman, W. . (2024). ACCEPTANCE OF STREAMING APPLICATIONS: INFLUENCING ONLINE TRADING BY INVESTORS ON THE STOCK EXCHANGE OF THAILAND. Journal of Interdisciplinary Innovation Review, 7(6), 181–194. retrieved from https://so04.tci-thaijo.org/index.php/jidir/article/view/271871