China
With the rapid development of metaverse technology in the marketing field, it has become increasingly important to understand consumer purchase intentions for AI Brand Endorsers (AIBEs) within this digital environment. Based on cognitive–affective–behavioral (CAB) theory, this study constructs a new theoretical framework to explore the key factors influencing consumer purchase intentions for AIBE-recommended products in the context of the metaverse. We conducted an online survey with 302 Generation MZ consumers who have purchasing experience, employing Partial Least Squares Structural Equation Modeling (PLS-SEM) for in-depth data analysis and model evaluation. Additionally, we performed Multi-Group Analysis (MGA) to reveal differences among various occupations and generations. The findings indicate that attractiveness (ATT), anthropomorphism (ANT), and interactivity (INT) significantly influence hedonic motivation (HM) and social presence (SP). Furthermore, authenticity (AUT) positively affects both SP and trust in AIBEs (TAI). Consumer purchase intention (PI) is significantly impacted by SP but is not directly influenced by HM and TAI. Notably, technology readiness (optimism and innovativeness) positively and significantly influences consumer PI but does not alter the potential moderating effects of HM, SP, and TAI. This study not only broadens and deepens the application of CAB theory but also elucidates the potential development of AIBEs in future metaverse research, providing practical implications and guidance for marketers to enhance consumer purchase intentions and boost product sales.
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