Unfair but Insightful? The Paradoxical Impact of AI Mediator Stance on Mediation Outcomes in Online Dispute Resolution

This study investigates the impact of AI mediator stance on user responses in Online Dispute Resolution (ODR). Drawing on the Computers Are Social Actors (CASA) paradigm and the Elaboration Likelihood Model (ELM), we propose a dual-pathway model. We examine how different AI stances (Neutral vs. Favor User vs. Favor Opponent) influence Perceived Fairness (peripheral route) and Perceived Insight (central route), and how Mediation Context (Single vs. Joint) acts as a boundary condition.