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Paper Type

ERF

Description

As an emerging virtual platform. Metaverse is increasingly applied to various collaboration contexts such as group gaming, team collaboration in work, and online group learning. To investigate users’ group engagement in the Metaverse, this study applies a socio-technical perspective to the context of Metaverse gaming. We propose a theoretical model and test it with a multi-method approach, consisting of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The SEM results show that all the proposed social (social presence and group harmony), individual (demand toward social activities and acceptance toward virtual world), and technological factors (self-representation) positively determine users’ group engagement in Metaverse gaming. Our fsQCA results further reveal the interdependent relationships among those factors (i.e., multiple configurations), which are nuanced under different contexts of their gender and level of prior experience. While the current findings are insightful and useful, they should be further studied through future research.

Paper Number

1416

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Aug 10th, 12:00 AM

Exploring Socio-Technical Factors of Group Engagement in Metaverse Gaming: A Multi-Method Approach

As an emerging virtual platform. Metaverse is increasingly applied to various collaboration contexts such as group gaming, team collaboration in work, and online group learning. To investigate users’ group engagement in the Metaverse, this study applies a socio-technical perspective to the context of Metaverse gaming. We propose a theoretical model and test it with a multi-method approach, consisting of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The SEM results show that all the proposed social (social presence and group harmony), individual (demand toward social activities and acceptance toward virtual world), and technological factors (self-representation) positively determine users’ group engagement in Metaverse gaming. Our fsQCA results further reveal the interdependent relationships among those factors (i.e., multiple configurations), which are nuanced under different contexts of their gender and level of prior experience. While the current findings are insightful and useful, they should be further studied through future research.

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