How Can AI-Driven Customer Communication Mitigate Service Failures?
(A2025-124047)

AUTHORS

Mototaka Sakashita, Professor of Marketing, Graduate School of Business Administration, Keio University; Li Wang, Tongji University; Yirong Gu, Tongji University; Shu Wang, Tongji University; Zhiyong Yang, Miami University

ABSTRACT

This study investigates the relationship between AI communication styles and customer dissatisfaction in the context of service failures. It aims to clarify how the alignment of AI communication styles with different types of service failures influences customer dissatisfaction. Drawing on expectancy-disconfirmation theory, service failures are categorized into "process failures" and "outcome failures," while AI communication styles are classified as "interaction-oriented" and "task-oriented." Data collected from 343 undergraduate students in China were analysed. The findings reveal that an interaction-oriented communication style is more effective in mitigating customer dissatisfaction during process failures, while a task-oriented communication style is better suited for addressing outcome failures. Additionally, the mediating roles of warmth and competence in these effects were identified. This study contributes to elaborating on the service failure and AI communication literature.