The influence of AI service robots’ humorous response strategies on consumer forgiveness following service failure

Abstract

As technology advances, more AI entities are deployed in public service roles. However, AI service robot failures are increasingly frequent, causing negative behaviors such as customer dissatisfaction or complaints. Service recovery plays a crucial role in shaping consumer experiences following AI failures. At present, the interplay between AI robots’ humorous recovery strategies and core consumer motivations in influencing forgiveness behavior remain unclear. Integrating mental accounting theory and social exchange theory, this study investigates how this interaction affects forgiveness, examining the mediating roles of perceived warmth and perceived competence, and the moderating influence of AI relationship paradigm orientation. We collected data from 780 subjects across three studies. Results demonstrate that consumers driven by hedonic motivations exhibit significantly stronger forgiveness behavior towards humorous responses, mediated by enhanced perceived warmth. Conversely, utilitarian-motivated consumers demonstrate greater forgiveness in response to non-humorous strategies, mediated by heightened perceived competence. Furthermore, AI relationship paradigm orientation moderates these effects on forgiveness. These findings uncover the psychological mechanisms underlying effective AI service recovery and provide differentiated theoretical and practical implications for enterprises in designing AI service recovery strategies, thereby facilitating consumer forgiveness.