Chatbot symbolic recovery and customer forgiveness: a moderated mediation model

Purpose Artificial intelligence-based chatbots are frequently used to handle customer complaints in the hospitality and tourism sectors; however, little is known about their recovery strategies. Further, the widespread usage of chatbots is anticipated to affect customers' favorable responses. Therefore, this study aims to examine how chatbots’ symbolic recovery influences customer forgiveness through customer empathy and explore the moderating effect of time pressure on it. Moreover, it investigates the effect of customer forgiveness on customer reconciliation and customer continuous trust. Design/methodology/approach Structural equation modeling was used to analyze data collected from 994 customers who have experienced chatbot recovery in tourism and hospitality during the past four months. Findings The results show that chatbots’ symbolic recovery stimulates customer forgiveness, which subsequently positively affects customer reconciliation and customer continuous trust. Moreover, customer empathy partially mediates the effect of chatbots’ symbolic recovery on customer forgiveness, and time pressure plays a moderating role in the relationship between chatbots’ symbolic recovery and customer forgiveness. Practical implications The results offer highly persuasive insights that may be used to promote chatbots’ symbolic recovery in tourism organizations. The effectiveness of chatbots’ symbolic recovery in achieving customer forgiveness will motivate tourism organizations to use chatbots efficiently in service recovery. Originality/value This study extends the theoretical scope of chatbot research by investigating the symbolic recovery capabilities of chatbots. Moreover, it expands the application of SOR theory in the context of chatbot service recovery and reveals the underlying mechanism behind the impact of chatbots’ symbolic recovery on customer forgiveness, thus building and testing an integrative model of chatbot service recovery.