AI Article Synopsis
- The study investigates how the metaverse impacts our lives and identifies factors influencing user acceptance through an integrated model based on flow theory and use and satisfaction theory.
- A survey gathered responses from 265 participants, employing PLS-SEM to analyze individual variable effects and fsQCA for combined variable effects.
- Key findings reveal that flow experience, perceived risk, and personal innovation boost acceptance, while perceived cost does not; additionally, specific configurations identified by fsQCA help understand high and low acceptance scenarios.
Article Abstract
As a rapidly developing information technology in recent years, the metaverse has significantly transformed how we live, learn, and work. In order to accelerate the use of metaverse technology and promote users' acceptance of the metaverse, this study constructs an integrated model based on flow theory and use and satisfaction theory, to further explore the factors affecting users' acceptance of the metaverse. A total of 265 valid questionnaires were obtained through a situational questionnaire survey. Considering the limitations of a single analysis technique, we use two methods to analyze the data. Among them, the symmetric PLS-SEM method is mainly used to analyze the effects of single variables, while the asymmetric fsQCA method is used to analyze the combined effects of variables. The PLS-SEM results manifest that flow experience, perceived risk, and personal innovation directly influence users' acceptance of the metaverse, while perceived cost has no effect. Simultaneously, interactivity, presence, and social presence indirectly affect users' acceptance of the metaverse, while informativeness and enjoyment have no indirect effect. Significantly, fsQCA unveiled five configurations resulting in a high user acceptance of the metaverse, as well as six configurations leading to a negative acceptance. The complementary findings from PLS-SEM and fsQCA offer valuable insights for both theoretical understanding and practical implementation.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11269873 | PMC |
| http://dx.doi.org/10.1016/j.heliyon.2024.e33394 | DOI Listing |
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