How to initiate human-agent intervention for recovery when chatbots fail: A social information processing perspective

Service failures are inevitable in chatbot-based customer service. In hybrid customer service systems, when a chatbot fails, a human agent typically takes over and resume service for the customer. However, little is known about how to effectively initiate this transition from chatbot failure to human-agent intervention. This study identifies four initiation methods varying in service proactivity: passive initiation, text prompt initiation, button prompt initiation, and automatic initiation. Extending social information processing theory with a cognitive decision perspective, we develop a theoretical framework to examine how consumers attribute the observed initiation methods to organizational motives, which subsequently influence their satisfaction. We conduct three online experiments to examine how these initiation methods influence recovery satisfaction, as well as the underlying psychological mechanisms and boundary conditions. The results reveal significant differences in recovery satisfaction across initiation methods, mediated by customers' inferred selfish intent. Furthermore, compared with low task urgency, high task urgency significantly amplifies differences in recovery satisfaction and inferred selfish intent among various human-agent initiation methods. These findings advance understanding of recovery strategies for chatbot service failures, offering actionable guidance for designing effective transitions from chatbots to human agents in hybrid service settings.