Year: 2026
Type: article
Abstract: With the advancement of generative AI, Agentic AI with autonomous decision-making and proactive interaction has received extensive attention in e-commerce recommender systems. To investigate how Agentic AI influences consumers’ decision-making and usage intention, we designed a user study. This study conducted a 2 × 2 experiment based on the Media Are Social Actors (MASA) theory and the Stereotype Content Model (SCM). Results show that recommendation mode exerts its effect via warmth and competence perceptions, with warmth perception serving as the more stable mediator. Product type negatively moderates the warmth path, and AI usage frequency serves as a boundary condition for the competence path. This study extends the application of relevant theories in intelligent recommendation contexts and offers actionable operational insights for platforms to optimize recommendation strategies.
Authors: Wang, Yikai, Guan, Yue, Li, Zhiyong
Institution: Communication University of China
Language: English
Topic: AI in Service Interactions
Subfield: Marketing
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7223077283