Exploring the behavior of online fitness users by using the Unified Theory of Acceptance and Use of Technology

Authors

  • Chi-Yueh Hsu Department of Leisure Services Management, Chaoyang University of Technology. 168, Jifeng E.Rd., Wufeng District, Taichung, 41349 Taiwan, R.O.C.
  • Ming-Yueh Wang Department of Athletic Performace, National University of Kaohsiung. 700, Kaohsiung University Rd., Nanzih District, Kaohsiung 811, Taiwan, R.O.C.
  • Ting-I Lee The General Educaion Center, Chaoyang University of Technology. 168, Jifeng E.Rd., Wufeng District, Taichung, 41349 Taiwan, R.O.C.
  • Hsiu-Hui Chiang Department of Leisure Services Management, Chaoyang University of Technology. 168, Jifeng E.Rd., Wufeng District, Taichung, 41349 Taiwan, R.O.C.
  • Chun-Yu Chien The General Education Center, Chaoyang University of Technology. 168, Jifeng E.Rd., Wufeng District, Taichung, 41349 Taiwan, R.O.C.
DOI: https://doi.org/10.6018/sportk.509231
Keywords: Facebook, UTAUT, Live streaming, Fitness

Abstract

The aim of this study was to explore the behavior of online fitness users by using an integrated technology acceptance model. We also discussed the significant impact of fitness live streaming users on the integrated technology acceptance model. A cross-sectional study was carried out on a sample of 150 users who used Facebook fitness live streaming platform to watch fitness live streaming videos and used the live message reply, like and tracking functions. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was utilized to examine the behavior of users of Facebook fitness live streaming platform. The results showed that there are statistically significant impacts in each structure of UTAUT, and the users of fitness live streaming have positive effects in UTAUT. In addition, the convenience and the infinity of Internet allows the social media users to obtain effective information through fast and real-time communication media and most users have the resources and knowledge required for live streaming.

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References

Alhabash, S., Chiang, YH., & Huang, K. (2014). MAM & U&G in Taiwan: Differences in the uses and gratifications of Facebook as a function of motivational reactivity. Computers in Human Behavior, 35, 423-430.

Amichai-Hamburger, Y., & Vinitzky, G. (2010). Social network use and personality. Computer in Human Behavior, 26(6), 1289-1295. https://doi.org/10.1016/j.chb.2010.03.018

Amichai-Hamburger, Y., Wainapel, G., & Fox, S. (2002). "On the Internet no one knows I'm an introvert": Extroversion, neuroticism, and Internet interaction. Cyberpsychology & Behavior, 5(2), 125-128. https://doi.org/10.1089/109493102753770507

Brouwer, B. (2015). What live streaming means for content publishers. EContent, 38(9), 11.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388. https://doi.org/10.2307/3150980

Gannes, L. (2009). YouTube Changes Everything: The Online Video Revolution. Springer, New York, NY. https://doi.org/10.1007/978-0-387-79978-0_11

Greenhow, C., Robelia, B., & Hughes, J. E. (2009). Learning, teaching, and scholarship in a digital age: Web 2.0 and classroom research: What path should we take now? Educational Researcher, 38(4), 246-259. https://doi.org/10.3102/0013189X09336671

Gruzd, A., Staves, K., & Wilk, A. (2012). Connected scholars: Examining the role of social media in research practices of faculty using the UTAUT model. Computers in Human Behavior, 28(6), 2340-2350. https://doi.org/10.1016/j.chb.2012.07.004

Hair, Jr. J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.

Kelly, L., Keaten, J. A., & Millette, D. (2020). Seeking safer spaces: The mitigating impact of young adults' Facebook and Instagram audience expectations and posting type on fear of negative evaluation. Computers in Human Behavior, 109(1), 106333.

Lin, S. S. J., & Tsai, C, C. (2002). Sensation seeking and internet dependence of Taiwanese high school adolescents. Computer in Human Behavior, 18(4), 411-426. https://doi.org/10.1016/S0747-5632(01)00056-5

Maduku, D. K. (2015). An empirical investigation of students' behavioral intention to use e-books. Management Dynamics: Journal of the Southern African Institute for Management Scientists, 24(3), 3-20.

Market Intelligence & Consulting Institute(2017).Live Survey Series: Internet users love Facebook、YouTube、17 Media the best. MIC. https://mic.iii.org.tw/IndustryObservations_PressRelease02.aspx?sqno=475

Rodriguez, F., Cohen, C., Ober, C. K., & Archer, L. (2014). Principles of polymer systems. CRC Press. https://doi.org/10.1201/b17873

Stragier, J., Abeele, M.V., Mechant, P., & De Marez, L. (2016). Understanding persistence in the use of online fitness communities: Comparing novice and experience users. Computers in Human Behavior, 64(12), 34-42. https://doi.org/10.1016/j.chb.2016.06.013

Terzis, V., & Economides, A. A. (2011). The acceptance and use of computer based assessment. Computers & Education, 56(4), 1032-1044. https://doi.org/10.1016/j.compedu.2010.11.017

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540

Published
01-02-2022
How to Cite
Hsu, C.-Y. ., Wang, M.-Y. ., Lee, T.-I. ., Chiang, H.-H. ., & Chien, C.-Y. . (2022). Exploring the behavior of online fitness users by using the Unified Theory of Acceptance and Use of Technology. SPORT TK-EuroAmerican Journal of Sport Sciences, 11, 14. https://doi.org/10.6018/sportk.509231
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Articles