The Paradox of Subjective Complexity: Why AI Automation Fails to Mitigate Adoption Barriers in the Circular Economy

Despite AI-driven algorithms simplifying C2C resale platforms, adoption rates among target users (predominantly mothers) for unused baby products remain low. This study decodes this resistance by integrating the Theory of Planned Behavior and Protection Motivation Theory within a two-stage mixed-methods design (qualitative interviews, N = 37; quantitative survey, N = 670) identifies three patterns refining technology adoption frameworks. First, we reveal a “paradox of subjective complexity”: platform operational self-efficacy remains the strongest predictor of adoption intention, overriding objective technological ease and demonstrating a persistent decoupling between automated simplicity and subjective capability beliefs. Second, perceived AI functionality efficacy serves as a cognitive precondition that significantly enhances users’ internalization of social proof. Third, spatial and economic threats were indirectly associated with adoption intention through perceived platform value, suggesting a pragmatic, threat-coping pathway to circular economy participation. These insights offer actionable blueprints for policymakers and platform designers: collaborative interfaces, explainable AI (XAI), and user competence scaffolding.