The Impact of AI’s Response Method on Service Recovery Satisfaction in the Context of Service Failure

Zengmao Yang (), Jinlai Zhou and Hongjun Yang
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Zengmao Yang: School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China
Jinlai Zhou: School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China
Hongjun Yang: School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China

Sustainability, 2023, vol. 15, issue 4, 1-18

Abstract: In order to perpetuate service sustainability and promote sustainable growth in the service sector, it is important to resolve service failures. AI technology is being applied to service jobs in more and more industries, but AI will inevitably fail while providing service. How to carry out service recovery and obtain the understanding and forgiveness of customers is a problem that urgently needs solving in the practice and research of AI services. The purpose of this study was to explore the artificial intelligence remediation mechanism in the context of service failure and to explore the remedial utility of AI’s self-deprecating humor responses. The study conducted data collection through three experiments to test our hypotheses: study 1 verified the main effect of self-deprecating humor responses and the mediating effect of perceived sincerity and perceived intelligence; study 2 verified the moderated effect of the sense of power; and study 3 verified the moderated effect of failure experience. The experimental results show that, in the context of AI for service recovery, self-deprecating humor responses can improve customers’ willingness to tolerate failure, with perceived intelligence and perceived sincerity found to play a mediating role in this. The sense of power also plays a moderating role by affecting perceived sincerity, and failure experience has a moderate effect by affecting perceived intelligence. The theoretical contribution of the article is to introduce the perspective of AI’s self-deprecating humor service recovery, which complements theoretical research in the field of AI services. The management significance of the article is to provide new AI communication strategies and practical suggestions for enterprises and technical personnel.

Keywords: artificial intelligence; digital challenge; self-deprecating humor; self-destruction; service recovery satisfaction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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