AI-WOM Echo Pathway Model: Unveiling the Role of Cognitive and Emotional Resonance in Shaping eWOM and Purchase Intention
Pham Thi Phuong Dung, Long Cuu Hoang, An Ho Minh, Khanh Nguyen Phuc · International Journal of Human-Computer Interaction · 2025
This study advances understanding of how Artificial Intelligence Word-of-Mouth (AI-WOM) stimuli shape consumer responses through cognitive and emotional resonance. Drawing on the Stimulus-Organism-Response (SOR) framework, Resonance Theory, and Media Richness Theory (MRT), the research investigates six AI-WOM stimuli: personalization, interactivity, responsiveness, anthropomorphism, conversational tone, and content quality. Data from 872 online respondents were analyzed using structural equation modeling. Results show that all six stimuli significantly strengthen emotional resonance, whereas only responsiveness and conversational tone meaningfully influence cognitive resonance. Emotional resonance strongly predicts both electronic word-of-mouth (eWOM) and purchase intention, suggesting that emotional mechanisms dominate cognitive ones in AI-mediated persuasion. Furthermore, self-expressiveness moderates the link between emotional resonance and eWOM, indicating that highly self-expressive consumers more readily translate resonant experiences into sharing behavior. The study enriches theory by integrating SOR, Resonance Theory, and MRT, and offers practical insights for designing emotionally intelligent AI-driven communication that deepens customer connection and enhances advocacy.