Assessing the Adoption of Metaverse Platforms: A Structural Equation Modeling Approach with Mediating Effects of Switching Costs

The adoption of Metaverse platforms, a burgeoning technological innovation, holds significant potential for transforming various sectors, yet its uptake in emerging markets like Indonesia remains underexplored. This study addresses this gap by investigating the key factors influencing the Intention to Use (IU) Metaverse platforms in Indonesia, focusing on the roles of Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Relative Advantage (RA), and the mediating effect of Switching Costs (SC). The primary objective of this research was to develop and validate a model that explains the relationships between these factors and how they collectively impact user adoption decisions. Specifically, the study aimed to understand how PE, EE, SI, and RA influence the intention to use Metaverse platforms, with SC acting as a mediator. A quantitative research design was employed, utilizing Structural Equation Modeling (SEM) with Partial Least Squares (PLS) to analyze data collected from 380 distributed questionnaires. Of these, 361 were valid and used in the analysis, providing a robust sample to examine the study’s hypotheses. Participants were surveyed on their perceptions and intentions regarding Metaverse platforms. The analysis focused on examining the direct effects of PE, EE, SI, and RA on the intention to use, as well as the indirect effects mediated by SC. The findings revealed that PE, EE, SI, and RA significantly influence the intention to adopt Metaverse platforms, with SC playing a crucial mediating role. The study underscores the importance of reducing perceived switching barriers to enhance adoption, especially in a culturally diverse market like Indonesia. These results contribute to the broader understanding of technology adoption in emerging markets and offer practical implications for developers and marketers aiming to promote Metaverse platforms. Future research should explore additional factors such as technological anxiety or perceived risk and consider longitudinal designs to capture changes in user perceptions over time. This study provides a foundational model that can guide further exploration and application of Metaverse technologies in similar contexts.