The acceptance of metaverse system: a hybrid SEM-ML approach
The outbreak of COVID-19 led to the foundation of modern techniques of learning which involves metaverse. Specifically in the medical field, where cross-border medical training became out of question. Opportunities for medical students to practice were greatly reduced as there was very less physical interaction with patients due to the COVID-19 pandemic. However, metaverse proved to be of great help for medical staff to gain education virtually who came to the UAE to acquire proficient skills related to medical technology. New digital approaches based on metaverse technology are evolving in the UAE medical groups to address restrictions arising by using current teleconferencing platforms like Zoom in providing effective medical training. The goal of this research is to find out the effect of using the metaverse system for medical training in the UAE and students’ perceptions of it. The adoption features of trialability, observability, perceived pleasure, perceived ubiquity, perceived worth, personal innovativeness, and Technology Acceptance Model (TAM) components are all included in the conceptual model. The study’s novelty comes from its conceptual model, which links both personal and technology-based elements. Furthermore, the present work will employ a novel approach of hybrid analysis to perform machine-learning (ML) based structural equation modeling analysis (SEM). In addition, this study is assisted by importance-performance map analysis (IPMA) to evaluate the performance and importance of presumed factors. As this work is one of the rare attempts to utilize machine learning algorithms in predicting the intention to use metaverse systems, the methodological aspect of the study is also of great use. The adoption of a complementary multi-analytical approach is thought to provide a novel contribution to the information systems (IS) field. This study is also significant in assisting medical authorities to judge the importance of each factor and guiding them to opt for relevant strategies and techniques depending on the significance of the factors.
Volume & Issue
Vol. Volume 1 / Iss. Issue 1