Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/311013 
Year of Publication: 
2023
Citation: 
[Journal:] Electronic Markets [ISSN:] 1422-8890 [Volume:] 33 [Issue:] 1 [Article No.:] 56 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2023
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
Chatbots as prominent form of conversational agents are increasingly implemented as a user interface for digital customer-firm interactions on digital platforms and electronic markets, but they often fail to deliver suitable responses to user requests. In turn, individuals are left dissatisfied and turn away from chatbots, which harms successful chatbot implementation and ultimately firm's service performance. Based on the stereotype content model, this paper explores the impact of two universally usable failure recovery messages as a strategy to preserve users' post-recovery satisfaction and chatbot re-use intentions. Results of three experiments show that chatbot recovery messages have a positive effect on recovery responses, mediated by different elicited social cognitions. In particular, a solution-oriented message elicits stronger competence evaluations, whereas an empathy-seeking message leads to stronger warmth evaluations. The preference for one of these message types over the other depends on failure attribution and failure frequency. This study provides meaningful insights for chatbot technology developers and marketers seeking to understand and improve customer experience with digital conversational agents in a cost-effective way.
Subjects: 
Artificial intelligence
Chatbot
Service failure
Failure recovery
Social cognitions
Digital platform
JEL: 
C91
L86
M15
M31
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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