The Persuasive Power of AI Avatars Through Trust Transfer and the Elaboration Likelihood Model
Year: 2025
Type: article
Study design: Observational Study
Abstract: Drawing upon the Elaboration Likelihood Model (ELM) and Trust Transfer Theory, this study investigates how AI digital avatars influence consumer trust and purchase intention. Using survey data collected from 378 valid respondents, the proposed model was tested with Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that brand awareness and perceived quality significantly affect purchase intention through product trust, while social endorsement cues, anthropomorphism, and interaction quality indirectly influence purchase intention through AI Avatar trust. Furthermore, both AI Avatar trust and product trust have significant direct effects on purchase intention, highlighting the critical role of trust in AI-driven persuasion processes. This study validates the dual-route persuasion mechanism of the ELM in AI marketing contexts and extends the application of trust theory to human–AI interactions, offering valuable insights for future research on AI brand endorsement and consumer psychology.
Authors: Ching-Jui Keng, Hsiao-Po Bao, Chia-Hung Lin
Institution: National Taipei University of Technology
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,207
OpenAlex ID: W7108320100