Understanding Consumers’ Negative Word-of-Mouth Intention in the Aftermath of AI-Based Service Failure Through Attribution Theory

This article explores the consequences of AI-based service failures on consumers’ negative word-of-mouth (NWOM) communication. Utilizing attribution theory, the study investigates how consumers’ attributions of failure, including locus, stability, and controllability, influence their NWOM intentions, taking into account their trust in AI-based services. Through eight scenario experiments and questionnaires, the research unveils that internal attributions or attributions to high stability and controllability increase NWOM intention, with controllability having a stronger negative impact. Interactive effects between locus and stability/controllability are observed, mediated by trust in AI-based services. This study contributes to understanding consumer behavior in AI-based service environments, providing theoretical and practical insights for service providers to navigate the impact of AI-based service failures.