Investigating the Acceptance of Meta-Universe Technology for Football Course Training among University Physical Education Teachers: A UTAUT2 and TTF Model Approach

Abstract

This academic paper explores the integration of artificial intelligence (AI) and virtual reality (VR) in the sports industry, specifically in the context of improving the quality of football teaching in universities. The growing impact of the metaverse concept on science and technology necessitates the utilization of AI as a critical technology in virtual worlds. Furthermore, the success of AI in various fields, coupled with the advancements in information technology, underscores the inevitability of integrating AI and sports. As traditional sports undergo a quality revolution, the integration of AI and virtual reality becomes increasingly crucial. Therefore, this study focuses on the use of VR to enhance the quality of football teaching at the university level.Virtual reality, characterized by its immersive, interactive, and imaginative features, is deemed suitable for constructing physical education courses. This paper explores the strategies for improving the quality of university football courses within the context of the mobile Internet era. By combining physical education with virtual reality technology, the effects of virtual reality-based physical education curriculum and the factors influencing the willingness of physical education teachers to adopt virtual reality technology are examined. To enhance the interpretation of acceptance intentions, this study integrates the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model with the Task-Technology Fit Theory (TTF), resulting in a novel conceptual framework. Moreover, quantitative research based on collected data is conducted. The findings demonstrate that performance expectation, promotion conditions, hedonic motivation, price value, and individual innovation ability serve as significant predictors of acceptance intentions towards virtual reality technology.

Keywords

Metaverse / University football teaching / Virtual space / UTAUT2 / TFF

Funding

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

References

[1] Agag G., & El-Masry A. A. (2016). Understanding consumer intention to participate in online trav-el community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Computers in Human Behavior, 60, 97-111. https://doi.org/10.1016/j.chb.2016.02.038

[2] Agarwal R., & Prasad J. (1998). A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology. Information Systems Research, 9(2), 204-215. https://doi.org/10.1287/isre.9.2.204

[3] Al-Mamary Y. H., Al-nashmi M., Hassan Y. A. G., & Shamsuddin A. (2016). A Critical Review of Models and Theories in Field of Individual Acceptance of Technology. International Journal of Hybrid In-formation Technology, 9(6), 143-158. https://doi.org/10.14257/ijhit.2016.9.6.13

[4] Arain A. A., Hussain Z., Rizvi W. H., & Vighio M. S. (2019). Extending UTAUT2 toward acceptance of mobile learning in the context of higher education. Universal Access in the Information Society, 18(3), 659-673. https://doi.org/10.1007/s10209-019-00685-8

[5] Arpaci I., Karatas K., Kusci I., & Al-Emran M. (2022). Understanding the social sustainability of the Metaverse by integrating UTAUT2 and big five personality traits: A hybrid SEM-ANN approach. Technolo-gy in Society, 71, 102120. https://doi.org/10.1016/j.techsoc.2022.102120

[6] Chang C.-J., Yang S.-C., & Wolzok E. (2023). Examining the use of fitness apps in sports centers in Taiwan: Incorporating task-technology fit into a technology readiness acceptance model. Managing Sport and Leisure, 0(0), 1-19. https://doi.org/10.1080/23750472.2023.

[7] Cheng Y.-H., & Huang T.-Y. (2013). High speed rail passengers’ mobile ticketing adoption. Transporta-tion Research Part C: Emerging Technologies, 30, 143-160. https://doi.org/10.1016/j.trc.2013.02.001

[8] Cohen J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587

[9] Faqih K. M. S., & Jaradat M.-I. R. M. (2021). Integrating TTF and UTAUT2 theories to investigate the adoption of augmented reality technology in education: Perspective from a developing country. Technology in Society, 67, 101787. https://doi.org/10.1016/j.techsoc.2021.101787

[10] Fornell C., & Larcker D. F. (1981). Evaluating Structural Equation Models with Unobservable Vari-ables and Measurement Error. Journal of Marketing Research.

[11] Franke G., & Sarstedt M. (2019). Heuristics versus statistics in discriminant validity testing: A com-parison of four procedures. Internet Research, 29(3), 430-447. https://doi.org/10.1108/IntR-12-2017-0515

[12] García de Blanes Sebastián M., Sarmiento Guede J. R., & Antonovica A. (2022). Application and extension of the UTAUT 2 model for determining behavioral intention factors in use of the artificial intelli-gence virtual assistants. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.993935

[13] Girod B., Mayer S., & Nägele F. (2017). Economic versus belief-based models: Shedding light on the adoption of novel green technologies. Energy Policy, 101, 415-426. https://doi.org/10.1016/j.en-pol.2016.09.065

[14] Goodhue D. L., & Thompson R. L. (1995). Task-Technology Fit and Individual Performance. MIS Quarterly, 19(2), 213-236. https://doi.org/10.2307/249689

[15] Gupta A., & Dogra N. (2017). TOURIST ADOPTION OF MAPPING APPS: A UTAUT2 PERSPEC-TIVE OF SMART TRAVELLERS. Tourism and Hospitality Management, 23(2), 145-161. https://doi.org/10.20867/thm.23.2.6

[16] Prabhakar G., Ramakrishnan A., Madan M. et al. (2020). Interactive gaze and finger controlled HUD for cars. Journal on multimodal user interfaces, 14(1), 101-121. https://doi.org/10.1007/s12193-020-00335-w

[17] Hair J. F., Howard M. C., & Nitzl C. (2020). Assessing measurement model quality in PLS-SEM us-ing confirmatory composite analysis. Journal of Business Research, 109, 101-110. https://doi.org/10.1016/j.jbusres.2019.11.069

[18] Hair J., Hult G. T. M., Ringle C. M., & Sarstedt M. (2016). A Primer on Partial Least Squares Struc-tural Equation Modeling (Second edition). SAGE Publications, Inc.

[19] Kock N. (2015). Common Method Bias in PLS-SEM: A Full Collinearity Assessment Approach. Inter-national Journal of E-Collaboration (IJeC), 11(4), 1-10. https://doi.org/10.4018/ijec.2015100101

[20] Kock N., & Lynn G. (2012). Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations. Journal of the Association for Information Systems, 13(7). https://doi.org/10.17705/1jais.00302

[21] Lin H.-C., Han X., Lyu T., Ho W.-H., Xu Y., Hsieh T.-C., Zhu L., & Zhang L. (2020). Task-tech-nology fit analysis of social media use for marketing in the tourism and hospitality industry: A systematic literature review. International Journal of Contemporary Hospitality Management, 32(8), 2677-2715. https://doi.org/10.1108/IJCHM-12-2019-1031

[22] Mazman Akar S. G. (2019). Does it matter being innovative: Teachers'technology acceptance. Educa-tion and Information Technologies, 24(6), 3415-3512. https://doi.org/10.1007/s10639-019-09933-z

[23] Paulo M. M., Rita P., Oliveira T., & Moro S. (2018). Understanding mobile augmented reality adop-tion in a consumer context. Journal of Hospitality and Tourism Technology, 9(2), 142-157. https://doi.org/10.1108/JHTT-01-2017-0006

[24] Podsakoff P. M., & Organ D. W. (1986). Self-reports in organizational research: Problems and pros-pects. Journal of Management, 12, 531-544. https://doi.org/10.1177/014920638601200408

[25] Sagnier C., Loup-Escande E., Lourdeaux D., Thouvenin I., & Valléry G. (2020). User Acceptance of Virtual Reality: An Extended Technology Acceptance Model. International Journal of Human-Computer Interaction, 36(11), 993-1007. https://doi.org/10.1080/10447318.2019.1708612

[26] Schmitz A., Díaz-Martín A.M., & Yagüe Guillén M.J. (2022). Modifying UTAUT2 for a cross-coun-try comparison of telemedicine adoption. Computers in Human Behavior, 130, 107183. https://doi.org/10.1016/j.chb.2022.107183

[27] Schomakers E.-M., Lidynia C., Vervier L. S., Valdez A. C., & Ziefle M. (2022). Applying an Ex-tended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study. JMIR MHealth and UHealth, 10(1), e27095. https://doi.org/10.2196/27095

[28] Seong B.-H., & Hong C.-Y. (2022). Corroborating the effect of positive technology readiness on the intention to use the virtual reality sports game "Screen Golf": Focusing on the technology readiness and acceptance model. Information Processing & Management, 59(4), 102994. https://doi.org/10.1016/j.ipm.2022.102994

[29] Farsoni S., Landi C. T., Ferraguti F., Secchi C., & Bonfe M. (2017). Compensation of load dynamics for admittance controlled interactive industrial robots using a quaternion-based kalman filter. IEEE Robot-ics and Automation Letters, 2(2), 672-679. https://doi.org/10.1109/LRA.2017.2640359

[30] Tamilmani K., Rana N. P., Wamba S. F., & Dwivedi R. (2021). The extended Unified Theory of Ac-ceptance and Use of Technology (UTAUT2): A systematic literature review and theory evaluation. Interna-tional Journal of Information Management, 57, 102269. https://doi.org/10.1016/j.ijinfomgt.2020.102269

[31] Venkatesh V., Thong J. Y. L., & Xu X. (2012). Consumer Acceptance and Use of Information Tech-nology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412

[32] Wu B., & Chen X. (2017). Continuance intention to use MOOCs: Integrating the technology accep-tance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221-232. https://doi.org/10.1016/j.chb.2016.10.028

[33] Yang F., Ren L., & Gu C. (2022). A study of college students’ intention to use metaverse technology for basketball learning based on UTAUT2. Heliyon, 8(9), e10562. https://doi.org/10.1016/j.heliyon.2022.e10562

[34] Han DD-I, Tom Dieck MC (2019) Calling for user-centric VR design research in hospitality and tour-ism. Hospital Soc 9(2):237-246

[35] Han D. I. D., Bergs Y., & Moorhouse N. (2022). Virtual reality consumer experience escapes: Prepar-ing for the metaverse. Virtual Reality. https://doi.org/10.1007/s10055-022-00641-7