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Modeling the Continuous Intention to Use the Metaverse as a Learning Platform: PLS-SEM and fsQCA Approach

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Current and Future Trends on Intelligent Technology Adoption

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1128))

Abstract

The current study explores Metaverse adoption among higher education institutions in the light of a theoretical framework to empower future perspectives of the Metaverse as a learning platform. Few attempts have been made to assess the impact of this technology despite its recent launch in the higher education sector. This study considers integrating the technology acceptance model (TAM) and self-determination theory (SDT) to investigate the factors influencing the continuous intention to use the Metaverse as a learning platform. In order to collect the data on the suggested model, a questionnaire was devised and administered to private university students. The effect of continuous intention (CI) to use the Metaverse as a learning platform is investigated using a hybrid approach consisting of partial least squares structural equation modeling (PLS-SEM) as symmetric assumptions and a fuzzy-set qualitative comparative analysis (fsQCA) method as asymmetric configurations. This method is designed to give a deeper understanding of the complicated relationships between the model’s antecedents and its targeted output. It takes into account how diverse configurations of exogenous constructs utilize a distinguished influence on an endogenous construct. The empirical evidence suggested that autonomy and perceived usefulness (PU) are significant factors in elucidating the CI to use the Metaverse as a learning platform in the Egyptian context. Perceived ease of use (PEOU), on the other hand, had no effect on the CI. In addition, theoretical and practical ramifications are addressed. From the configurational analysis, research findings indicate that none of the conditions alone is sufficient to explain a high level of Metaverse CI on their own. Instead, the study found three different configurations leading to an improved CI. This research was carried out in Egypt and hence added a piece of empirical evidence regarding the Metaverse as a learning platform in a developing country. Also, conclusions and suggestions for further study and practice are provided.

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Acknowledgements

The authors would like to greatly thank Prince of Songkla University (PSU) for providing any facilities for this study under the research project number ISL6602068S.

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Authors and Affiliations

  1. Prince of Songkla University (PSU), Pattani Campus, Pattani, Thailand

    Mohamed Soliman & Muhammadafeefee Assalihee

  2. Ahram Canadian University (ACU), 6th of October City, Egypt

    Reham Adel Ali

  3. Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Jamshed Khalid

  4. Daffodil International University, Dhaka, Bangladesh

    Imran Mahmud

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  1. Mohamed Soliman
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  2. Reham Adel Ali
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  5. Muhammadafeefee Assalihee
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Correspondence to Mohamed Soliman .

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  1. Universiti Tenaga Nasional (UNITEN), Selangor, Malaysia

    Mohammed A. Al-Sharafi

  2. The British University in Dubai, Dubai, United Arab Emirates

    Mostafa Al-Emran

  3. UCSI University, Kuala Lumpur, Malaysia

    Garry Wei-Han Tan

  4. UCSI University, Kuala Lumpur, Malaysia

    Keng-Boon Ooi

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Soliman, M., Ali, R.A., Khalid, J., Mahmud, I., Assalihee, M. (2023). Modeling the Continuous Intention to Use the Metaverse as a Learning Platform: PLS-SEM and fsQCA Approach. In: Al-Sharafi, M.A., Al-Emran, M., Tan, G.WH., Ooi, KB. (eds) Current and Future Trends on Intelligent Technology Adoption. Studies in Computational Intelligence, vol 1128. Springer, Cham. https://doi.org/10.1007/978-3-031-48397-4_3

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