Personality-driven trust and satisfaction in AI chatbots: a behavioral economics perspective

Purpose This study aims to investigate how Big Five personality traits shape satisfaction with artificial intelligence (AI) chatbots, focusing on trust as a mediating mechanism. It clarifies how stable psychological characteristics influence trust formation and evaluations of AI-mediated interactions. Design/methodology/approach Data were collected from consumers who had used chatbots within the past six months. Structural equation modeling (SEM) in AMOS 30.0 tested direct and indirect effects among personality traits, trust and satisfaction, informed by commitment-trust theory and expectation- disconfirmation theory. Findings Agreeableness and neuroticism significantly predicted trust, while conscientiousness and openness directly enhanced satisfaction. Trust mediated the effects of agreeableness and neuroticism on satisfaction. Extraversion showed no significant influence, highlighting personality effects. Originality The study demonstrates that trust functions as a psychological bridge between personality traits and satisfaction in AI-mediated services. It advances personality-based technology acceptance research and offers evidence for incorporating personality-driven trust mechanisms into chatbot design.