60
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Exploring the influence of the learning Metaverse on student satisfaction: an integrated framework of dual-congruity theory and interactive learning environment features

ORCID Icon & ORCID Icon
Received 04 Jul 2023, Accepted 16 Apr 2024, Published online: 02 May 2024

References

  • Abbasi, A. Z., Shamim, A., Ting, D. H., Hlavacs, H., & Rehman, U. (2021). Playful-consumption experiences and subjective well-being: Children’s smartphone usage. Entertainment Computing, 36, 100390. https://doi.org/10.1016/j.entcom.2020.100390
  • Agustini, K., Putrama, I. M., Wahyuni, D. S., & Mertayasa, I. N. E. (2023). Applying gamification technique and virtual reality for prehistoric learning toward the Metaverse. International Journal of Information and Education Technology, 13(2), 247–256. https://doi.org/10.18178/ijiet.2023.13.2.1802
  • Ahuja, A. S., Polascik, B. W., Doddapaneni, D., Byrnes, E. S., & Sridhar, J. (2023). The digital Metaverse: Applications in artificial intelligence, medical education, and integrative health. Integrative Medicine Research, 12(1), 100917. https://doi.org/10.1016/j.imr.2022.100917
  • Akour, I. A., Al-Maroof, R. S., Alfaisal, R., & Slloum, S. A. (2022). A conceptual framework for determining Metaverse adoption in higher institutions of gulf area: An empirical study using hybrid SEM-ANN approach. Computers and Education: Artificial Intelligence, 3, 100052. https://doi.org/10.1016/j.caeai.2022.100052
  • Al-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A., & Habibi, A. (2023). Extending the technology acceptance model (TAM) to predict university students’ intentions to use Metaverse-based learning platforms. Education and Information Technologies, 28(11), 15381–15413. https://doi.org/10.1007/s10639-023-11816-3
  • Alpala, L. O., Quiroga-Parra, D. J., Torres, J. C., & Peluffo-Ordóñez, D. H. (2022). Smart factory using virtual reality and online multi-User: Towards a Metaverse for experimental frameworks. Applied Sciences, 12(12), 6258. https://doi.org/10.3390/app12126258
  • Arı, E., Yılmaz, V., & Dikec, B. E. (2020). An extensive structural model proposal to explain online gaming behaviors. Entertainment Computing, 34, 100340. https://doi.org/10.1016/j.entcom.2020.100340
  • Arpaci, I., & Bahari, M. (2023). Investigating the role of psychological needs in predicting the educational sustainability of Metaverse using a deep learning-based hybrid SEM-ANN technique. Interactive Learning Environments, 1–13. https://doi.org/10.1080/10494820.2022.2164313
  • Baragash, R. S., Al-Samarraieb, H., Alzahrani, A. I., & Alfarraj, O. (2020). Augmented reality in special education: A meta-analysis of single-subject design studies. European Journal of Special Needs Education, 35(3), 382–397. https://doi.org/10.1080/08856257.2019.1703548
  • Beck, D., Morgado, L., & O’Shea, P. (2024). Educational practices and strategies with immersive learning environments: Mapping of reviews for using the Metaverse. IEEE Transactions on Learning Technologies, 17, 319–341. https://doi.org/10.1109/TLT.2023.3243946
  • Braguez, J., Graguez, M., Moreira, S., & Filipe, C. (2023). The possibilities of changes in learning experiences with Metaverse. Procedia Computer Science, 219, 504–511. https://doi.org/10.1016/j.procs.2023.01.318
  • Chang, S. M., Hsieh, G. M. Y., & Lin, S. S. J. (2018). The mediation effects of gaming motives between game involvement and problematic Internet use: Escapism, advancement and socializing. Computers & Education, 122, 43–53. https://doi.org/10.1016/j.compedu.2018.03.007
  • Chen, Z. (2022). Exploring the application scenarios and issues facing Metaverse technology in education. Interactive Learning Environments, 1–13. https://doi.org/10.1080/10494820.2022.2133148
  • Cheung, G. W., & Lau, R. S. (2008). Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models. Organizational Research Methods, 11(2), 296–325. https://doi.org/10.1177/1094428107300343
  • Chung, N., Han, H., & Joun, Y. (2015). Tourists’ intention to visit a destination: The role of augmented reality (AR) application for a heritage site. Computers in Human Behavior, 50, 588–599. https://doi.org/10.1016/j.chb.2015.02.068
  • Curley, E., Lee, J., Kwak, D. H., & Polites, G. (2020). An empirical examination of dual-congruity perspectives in the gamified ERP training. AMCIS 2020 Proceedings: AI and Semantic Technologies for Intelligent Information Systems (SIGODIS).
  • Das, G. (2014). Impacts of retail brand personality and self-congruity on store loyalty: The moderating role of gender. Journal of Retailing and Consumer Services, 21(2), 130–138. https://doi.org/10.1016/j.jretconser.2013.07.011
  • Davis, R., & Lang, B. (2013). Does game self-congruity increase usage and purchase? Young Consumers, 14(1), 52–66. https://doi.org/10.1108/17473611311305485
  • Dreamson, N., & Park, G. (2023). Metaverse-based learning through children’s school space design. International Journal of Art & Design Education, 42(1), 125–138. https://doi.org/10.1111/jade.12449
  • Dwivedi, Y. K., Hughes, L., Baabdullah, A. M., Ribeiro-Navarrete, S., Giannakis, M., Al-Debei, M. M., … Wamba, S. F. (2022). Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 66, 102542. https://doi.org/10.1016/j.ijinfomgt.2022.102542
  • El Hedhli, K., Becheur, I., Zourrig, H., & Chaouali, W. (2021). Shopping well-being: The role of congruity and shoppers’ characteristics. Journal of Consumer Marketing, 38(3), 293–304. https://doi.org/10.1108/JCM-07-2020-3943
  • Feng, X., Wang, X., & Su, Y. (2024). An analysis of the current status of Metaverse research based on bibliometrics. Library Hi Tech, 42(1), 284–308. https://doi.org/10.1108/LHT-10-2022-0467
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
  • Galan-Casado, D., Moraleda, A., Martínez-Martí, M. L., & Pérez-Nieto, MÁ. (2020). Sustainable environments in education: results on the effects of the new environments in learning processes of university students. Sustainability, 12(7), 2668. https://doi.org/10.3390/su12072668
  • Gardiner, S., Vada, S., Yang, E. C. L., Khoo, C., & Le, T. H. (2022). Recreating history: The evolving negotiation of staged authenticity in tourism experiences. Tourism Management, 91, 104515. https://doi.org/10.1016/j.tourman.2022.104515
  • Ghasemy, M., Teeroovengadum, V., Becker, J. M., & Ringle, C. M. (2020). This fast car can move faster: A review of PLS-SEM application in higher education research. Higher Education, 80(6), 1121–1152. https://doi.org/10.1007/s10734-020-00534-1
  • Gim, G., Bae, H. K., & Kang, S. A. (2023). The effect of self-determination and quality of VR-based education in the Metaverse on learner satisfaction. In R. Lee (Ed.), Emotional artificial intelligence and Metaverse (pp. 41–54). 1067. Springer. https://doi.org/10.1007/978-3-031-16485-9_4
  • Goebert, C., & Greenhalgh, G. P. (2020). A new reality: Fan perceptions of augmented reality readiness in sport marketing. Computers in Human Behavior, 106, 106231. https://doi.org/10.1016/j.chb.2019.106231
  • Hadi, R., Melumad, S., & Park, E. S. (2024). The Metaverse: A new digital frontier for consumer behavior. Journal of Consumer Psychology, 34(1), 142–166. https://doi.org/10.1002/jcpy.1356
  • Hair, J. F., Babin, B. J., Anderson, R. E., & Black, W. C. (2018). Multivariate data analysis (8th ed.). Cengage.
  • Hair, J. F. H., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
  • Han, D. I. D., Bergs, Y., & Moorhouse, N. (2022). Virtual reality consumer experience escapes: Preparing for the Metaverse. Virtual Reality, 26(4), 1443–1458. https://doi.org/10.1007/s10055-022-00641-7
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
  • Hong, J.-C., Hwang, M.-Y., Szeto, E., Tsai, C.-R., Kuo, Y.-C., & Hsu, W.-Y. (2016). Internet cognitive failure relevant to self-efficacy, learning interest, and satisfaction with social media learning. Computers in Human Behavior, 55, 214–222. https://doi.org/10.1016/j.chb.2015.09.010
  • Hussain, U., Jabarkhail, S., Cunningham, G. B., & Madsen, J. A. (2021). The dual nature of escapism in video gaming: A meta-analytic approach. Computers in Human Behavior Reports, 3, 100081. https://doi.org/10.1016/j.chbr.2021.100081
  • Hwang, G. J., & Chien, S. Y. (2022). Definition, roles, and potential research issues of the Metaverse in education: An artificial intelligence perspective. Computers and Education: Artificial Intelligence, 3, 100082. https://doi.org/10.1016/j.caeai.2022.100082
  • Hwang, S., & Koo, G. W. (2023). Art marketing in the Metaverse world: Evidence from South Korea. Cogent Social Sciences, 9(1), 2175429. https://doi.org/10.1080/23311886.2023.2175429
  • İbili, E., Ölmez, M., Cihan, A., Bilal, F., İbili, A. B., Okumus, N., & Billinghurst, M. (2023). Investigation of learners’ behavioral intentions to use Metaverse learning environment in higher education: A virtual computer laboratory. Interactive Learning Environments, 1–26. https://doi.org/10.1080/10494820.2023.2240860
  • James, T. L., Wallace, L., & Deane, J. K. (2019). Using organismic integration theory to explore the associations between users’ exercise motivations and fitness technology feature set use. MIS Quarterly, 43(1), 287–312. https://doi.org/10.25300/MISQ/2019/14128
  • Jiang, Z., & Benbasat, I. (2004). Virtual product experience: Effects of visual and functional control of products on perceived diagnosticity and flow in electronic shopping. Journal of Management Information Systems, 21(3), 111–147. https://doi.org/10.1080/07421222.2004.11045817
  • Jiang, Z., & Benbasat, I. (2007). Research note—investigating the influence of the functional mechanisms of online product presentations. Information Systems Research, 18(4), 454–470. https://doi.org/10.1287/isre.1070.0124
  • Johar, J. S., & Sirgy, M. J. (1991). Value-Expressive versus utilitarian advertising appeals: When and why to use which appeal. Journal of Advertising, 20(3), 23–33. https://doi.org/10.1080/00913367.1991.10673345
  • Joo, Y. J., So, H. J., & Kim, N. H. (2018). Examination of relationships among students’ self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers & Education, 122, 260–272. https://doi.org/10.1016/j.compedu.2018.01.003
  • Jun, G. (2020). Virtual reality church as a new mission frontier in the Metaverse: Exploring theological controversies and missional potential of virtual reality church. Transformation: An International Journal of Holistic Mission Studies, 37(4), 297–305. https://doi.org/10.1177/0265378820963155
  • Kim, H. G., Lim, H. T., & Ro, Y. M. (2020). Deep virtual reality image quality assessment with human perception guider for omnidirectional image. IEEE Transactions on Circuits and Systems for Video Technology, 30(4), 917–928. https://doi.org/10.1109/TCSVT.2019.2898732
  • Kline, R. B. (2015). Principles and practice of structural equation modeling. The Guilford Press.
  • Kuo, Y. C., Walker, A. E., Schroder, K. E., & Belland, B. R. (2014). Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20, 35–50. http://dx.doi.org/10.1016/j.iheduc.2013.10.001
  • Lee, C. S., Wang, M. H., Reformat, M., & Huang, S. H. (2023). Human intelligence-based Metaverse for co-learning of students and smart machines. Journal of Ambient Intelligence and Humanized Computing, 14(6), 7695–7718. https://doi.org/10.1007/s12652-023-04580-2
  • Lee, H., Jung, T. H., tom Dieck, M. C., & Chung, N. (2020). Experiencing immersive virtual reality in museums. Information & Management, 57(5), 103229. https://doi.org/10.1016/j.im.2019.103229
  • Lee, H., Woo, D., & Yu, S. (2022). Virtual reality Metaverse system supplementing remote education methods: Based on aircraft maintenance simulation. Applied Sciences, 12(5), 2667. https://doi.org/10.3390/app12052667
  • Lee, N., & Jo, M. (2023). Exploring problem-based learning curricula in the Metaverse: The hospitality students’ perspective. Journal of Hospitality, Leisure, Sport & Tourism Education, 32, 100427. https://doi.org/10.1016/j.jhlste.2023.100427
  • Li, M., & Liu, L. (2023). Students’ perceptions of augmented reality integrated into a mobile learning environment. Library Hi Tech, 41(5), 1498–1523. https://doi.org/10.1108/LHT-10-2021-0345
  • Liang, H., Saraf, N., Hu, Q., & Xue, Y. (2007). Assimilation of enterprise systems: The effect of institutional pressures and the mediating role of top management. MIS Quarterly, 31(1), 59–87. https://doi.org/10.2307/25148781
  • Lindell, M. K., & Whitney, D. J. (2001). Accounting for common method variance in cross-sectional research designs. Journal of Applied Psychology, 86(1), 114–121. https://doi.org/10.1037/0021-9010.86.1.114
  • Liu, C., Zhang, Y., & Zhang, J. (2020). The impact of self-congruity and virtual interactivity on online celebrity brand equity and fans’ purchase intention. Journal of Product & Brand Management, 29(6), 783–801. https://doi.org/10.1108/JPBM-11-2018-2106
  • Liu, D., & Yu, J. (2022). Impact of perceived diagnosticity on live streams and consumer purchase intention: Streamer type, product type, and brand awareness as moderators. Information Technology and Management, 1–14. https://doi.org/10.1007/s10799-022-00375-7
  • Liu, Y., Sun, J. C. Y., & Chen, S. K. (2023). Comparing technology acceptance of AR-based and 3D map-based mobile library applications: A multigroup SEM analysis. Interactive Learning Environments, 31(7), 4156–4170. https://doi.org/10.1080/10494820.2021.1955271
  • Lo, S. C., & Tsai, H. H. (2022). Design of 3D virtual reality in the Metaverse for environmental conservation education based on cognitive theory. Sensors, 22(21), 8329. https://doi.org/10.3390/s22218329
  • Locurcio, L. (2022). Dental education in the Metaverse. British Dental Journal, 232(4), 191. https://doi.org/10.1038/s41415-022-3990-7
  • Merle, A., Senecal, S., & St-Onge, A. (2012). Whether and how virtual try-on influences consumer responses to an apparel web site. International Journal of Electronic Commerce, 16(3), 41–64. https://doi.org/10.2753/JEC1086-4415160302
  • Mosco, V. (2023). Into the Metaverse: Technical challenges, social problems, utopian visions, and policy principles. Javnost - The Public, 30(2), 161–173. https://doi.org/10.1080/13183222.2023.2200688
  • Mystakidis, S. (2022). Metaverse. Encyclopedia, 2(1), 486–497. https://doi.org/10.3390/encyclopedia2010031
  • Ng, D. T. K. (2022). What is the Metaverse? Definitions, technologies and the community of inquiry. Australasian Journal of Educational Technology, 38(4), 190–205. https://doi.org/10.14742/ajet.7945
  • Nikkei Asia. (2023). Metaverse education blossoms in South Korea, Japan, Taiwan. https://asia.nikkei.com/Business/Education/Metaverse-education-blossoms-in-South-Korea-Japan-Taiwan accessed 5.10
  • Nitzl, C., Roldan, J. L., & Cepeda, G. (2016). Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models. Industrial Management & Data Systems, 116(9), 1849–1864. https://doi.org/10.1108/IMDS-07-2015-0302
  • Ohno, S. (2016). Internet escapism and addiction among Japanese senior high school students. International Journal of Culture and Mental Health, 9(4), 399–406. https://doi.org/10.1080/17542863.2016.1226911
  • Pallasena, R. K., Sharma, M., & Krishnaswamy, V. (2022). A study of interaction, visual canvas, and immersion in AR design: A DSR approach. AIS Transactions on Human-Computer Interaction, 14(3), 390–425. https://doi.org/10.17705/1thci.00173
  • Papakostas, C., Troussas, C., Krouska, A., & Sgouropoulou, C. (2023). Exploring users’ behavioral intention to adopt mobile augmented reality in education through an extended technology acceptance model. International Journal of Human–Computer Interaction, 39(6), 1294–1302. https://doi.org/10.1080/10447318.2022.2062551
  • Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63(1), 539–569. https://doi.org/10.1146/annurev-psych-120710-100452
  • Rauschnabel, P. A., Felix, R., & Hinsch, C. (2019). Augmented reality marketing: How mobile AR-apps can improve brands through inspiration. Journal of Retailing and Consumer Services, 49, 43–53. https://doi.org/10.1016/j.jretconser.2019.03.004
  • Ritterbusch, G. D., & Teichmann, M. R. (2023). Defining the Metaverse: A systematic literature review. IEEE Access, 11, 12368–12377. https://doi.org/10.1109/ACCESS.2023.3241809
  • Sarıtaş, M. T., & Topraklıkoğlu, K. (2022). Systematic literature review on the use of Metaverse in education. International Journal of Technology in Education, 5(4), 586–607. https://doi.org/10.46328/ijte.319
  • Šegota, T., Chen, N., & Golja, T. (2022). The impact of self-congruity and evaluation of the place on WOM: Perspectives of tourism destination residents. Journal of Travel Research, 61(4), 800–817. https://doi.org/10.1177/00472875211008237
  • Sharma, T. G., Hamari, J., Kesharwani, A., & Tak, P. (2022). Understanding continuance intention to play online games: Roles of self-expressiveness, self-congruity, self-efficacy, and perceived risk. Behaviour & Information Technology, 41(2), 348–364. https://doi.org/10.1080/0144929X.2020.1811770
  • Shen, D., Cho, M.-H., Tsai, C.-L., & Marra, R. (2013). Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction. The Internet and Higher Education, 19, 10–17. https://doi.org/10.1016/j.iheduc.2013.04.001
  • Shu, X., & Gu, X. (2023). An empirical study of a smart education model enabled by the Edu-Metaverse to enhance better learning outcomes for students. Systems, 11(2), 75. https://doi.org/10.3390/systems11020075
  • Sirgy, M. J. (1985). Using self-congruity and ideal congruity to predict purchase motivation. Journal of Business Research, 13(3), 195–206. https://doi.org/10.1016/0148-2963(85)90026-8
  • Sirgy, M. J. (2018). Self-congruity theory in consumer behavior: A little history. Journal of Global Scholars of Marketing Science, 28(2), 197–207. https://doi.org/10.1080/21639159.2018.1436981
  • Sirgy, M. J., Grzeskowiak, S., & Su, C. (2005). Explaining housing preference and choice: The role of self-congruity and functional congruity. Journal of Housing and the Built Environment, 20(4), 329–347. https://doi.org/10.1007/s10901-005-9020-7
  • Sirgy, M. J., Johar, J. S., Samli, A. C., & Claiborne, C. B. (1991). Self-congruity versus functional congruity: Predictors of consumer behavior. Journal of the Academy of Marketing Science, 19(4), 363–375. https://doi.org/10.1007/BF02726512
  • Siricharoen, W. V. (2019). The effect of virtual reality as a form of escapism. In International Conference on Information Resources Management, Auckland, New Zealand.
  • Sop, S. A., & Kozak, N. (2019). Effects of brand personality, self-congruity and functional congruity on hotel brand loyalty. Journal of Hospitality Marketing & Management, 28(8), 926–956. https://doi.org/10.1080/19368623.2019.1577202
  • Sopher, H., & Lescop, L. (2023). Learning in Metaverse: The immersive atelier model of the architecture studio. Archnet-IJAR: International Journal of Architectural Research, 17(3), 536–553. https://doi.org/10.1108/ARCH-10-2022-0213
  • Stephenson, N. (1992). Snow crash: A novel. Spectra.
  • Suh, K. S., Kim, H., & Shu, E. K. (2011). What if your avatar looks like you? Dual-congruity perspectives for avatar use. MIS Quarterly, 35(3), 711–729. https://doi.org/10.2307/23042805
  • Tawira, L., & Ivanov, A. (2023). Leveraging personalization and customization affordances of virtual try-on apps for a new model in apparel m-shopping. Asia Pacific Journal of Marketing and Logistics, 35(2), 451–471. https://doi.org/10.1108/APJML-09-2021-0652
  • Tomita, K. (2018). Does the visual appeal of instructional media affect learners’ motivation toward learning? TechTrends, 62(1), 103–112. https://doi.org/10.1007/s11528-017-0213-1
  • Tran, N. C., Wang, J., Vu, T. H., Tai, T. C., & Wang, J. C. (2023). Anti-aliasing convolution neural network of finger vein recognition for virtual reality (VR) human–robot equipment of Metaverse. The Journal of Supercomputing, 79(3), 2767–2782. https://doi.org/10.1007/s11227-022-04680-4
  • Turel, O., Serenko, A., & Bontis, N. (2010). User acceptance of hedonic digital artifacts: A theory of consumption values perspective. Information & Management, 47(1), 53–59. https://doi.org/10.1016/j.im.2009.10.002
  • Uhm, J. P., Kim, S., Do, C., & Lee, H. W. (2022). How augmented reality (AR) experience affects purchase intention in sport E-commerce: Roles of perceived diagnosticity, psychological distance, and perceived risks. Journal of Retailing and Consumer Services, 67, 103027. https://doi.org/10.1016/j.jretconser.2022.103027
  • Verhagen, T., Feldberg, F., van den Hooff, B., Meents, S., & Merikivi, J. (2012). Understanding users’ motivations to engage in virtual worlds: A multipurpose model and empirical testing. Computers in Human Behavior, 28(2), 484–495. https://doi.org/10.1016/j.chb.2011.10.020
  • Vidal-Tomás, D. (2023). The illusion of the Metaverse and meta-economy. International Review of Financial Analysis, 86, 102560. https://doi.org/10.1016/j.irfa.2023.102560
  • Waheed, M., Kaur, K., & Kumar, S. (2016). What role does knowledge quality play in online students’ satisfaction, learning and loyalty? An empirical investigation in an eLearning context. Journal of Computer Assisted Learning, 32(6), 561–575. https://doi.org/10.1111/jcal.12153
  • Wang, M., Yu, H., Bell, Z., & Chu, X. (2022). Constructing an Edu-Metaverse ecosystem: A new and innovative framework. IEEE Transactions on Learning Technologies, 15(6), 685–696. https://doi.org/10.1109/TLT.2022.3210828
  • Wang, S. J., Hsu, C. P., Huang, H. C., & Chen, C. L. (2015). How readers’ perceived self-congruity and functional congruity affect bloggers’ informational influence: Perceived interactivity as a moderator. Online Information Review, 39(4), 537–555. https://doi.org/10.1108/OIR-02-2015-0063
  • Wu, T., & Hao, F. (2023). Edu-Metaverse: Concept, architecture, and applications. Interactive Learning Environments, 1–28. https://doi.org/10.1080/10494820.2023.2198567
  • Xi, N., Chen, J., Gama, F., Riar, M., & Hamari, J. (2023). The challenges of entering the Metaverse: An experiment on the effect of extended reality on workload. Information Systems Frontiers, 25, 659–680. https://doi.org/10.1007/s10796-022-10244-x
  • 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
  • Yang, T., Yang, F., & Men, J. (2023). Understanding consumers’ continuance intention toward recommendation vlogs: An exploration based on the dual-congruity theory and expectation-confirmation theory. Electronic Commerce Research and Applications, 59, 101270. https://doi.org/10.1016/j.elerap.2023.101270
  • Yu, J. E. (2022). Exploration of educational possibilities by four Metaverse types in physical education. Technologies, 10(5), 104. https://doi.org/10.3390/technologies10050104
  • Zhao, Y., Li, Y., Wang, N., Zhou, R., & Luo, X. (2022). A meta-analysis of online impulsive buying and the moderating effect of economic development level. Information Systems Frontiers, 24(5), 1667–1688. https://doi.org/10.1007/s10796-021-10170-4
  • Zhong, J., & Zheng, Y. (2022). Empowering future education: Learning in the Edu-metaverse. In 2022 International Symposium on Educational Technology (ISET), IEEE, Hong Kong (pp. 292–295).
  • Zhou, B. (2022). Building a smart education ecosystem from a Metaverse perspective. Mobile Information Systems, 2022, 1938329, 1–10. https://doi.org/10.1155/2022/1938329
  • Zhu, Z., Zhang, X., Wang, J., & Chen, S. (2023). Research on the influence of online photograph reviews on tourists’ travel intentions: Rational and irrational perspectives. Asia Pacific Journal of Marketing and Logistics, 35(1), 17–34. https://doi.org/10.1108/APJML-08-2021-0547

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.