Seeking empathy or suggesting a solution? Effects of chatbot messages on service failure recovery

Martin Haupt (), Anna Rozumowski (), Jan Freidank () and Alexander Haas ()
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Martin Haupt: Justus-Liebig University
Anna Rozumowski: FHNW University of Applied Sciences and Arts Northwestern Switzerland
Jan Freidank: Technische Hochschule Mittelhessen
Alexander Haas: Justus-Liebig University

Electronic Markets, 2023, vol. 33, issue 1, No 55, 22 pages

Abstract: 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.

Keywords: Artificial intelligence; Chatbot; Service failure; Failure recovery; Social cognitions; Digital platform (search for similar items in EconPapers)
JEL-codes: C91 L86 M15 M31 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12525-023-00673-0

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