Acceptance of Avatar as Virtual Identity in the Roblox Metaverse: A Modified UTAUMT Model
The rapid growth of metaverse platforms has transformed how Generation Z constructs and expresses digital identity, with avatars serving as a primary medium of self-representation in commercial environments such as Roblox. However, the behavioral mechanisms underlying avatar acceptance as a form of virtual identity remain insufficiently explored. This study aims to analyze the factors influencing avatar behavioral intention and usage behavior in the Roblox metaverse by extending the Unified Theory of Acceptance and Use of Technology (UTAUT2) into a modified UTAUMT framework that explicitly incorporates avatar-based identity constructs. A quantitative approach was employed using a survey of 531 valid respondents, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that Metaverse Performance Expectancy, Social Influence, Price Value, and Self-Efficacy significantly influence Behavioral Intention, while Effort Expectancy, Facilitating Conditions, and Hedonic Motivation do not have significant effects, consistent with prior findings in digitally mature user contexts. Behavioral Intention and Facilitating Conditions significantly influence Use Behavior, with Behavioral Intention emerging as the strongest predictor. The model demonstrates moderate explanatory power, with R² values of 0.158 for Behavioral Intention and 0.456 for Use Behavior, indicating acceptable predictive capability in a commercial metaverse setting. This study contributes theoretically by extending UTAUT2 to capture avatar-based virtual identity formation better, highlighting a shift from usability and hedonic factors toward social, psychological, and value-based determinants. In practical terms, the findings provide insights for metaverse platform design, particularly in enhancing identity expression and social engagement.