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

Author

Listed:
  • Martin Haupt

    (Justus-Liebig University
    Technische Hochschule Mittelhessen)

  • Anna Rozumowski

    (FHNW University of Applied Sciences and Arts Northwestern Switzerland)

  • Jan Freidank

    (Technische Hochschule Mittelhessen)

  • Alexander Haas

    (Justus-Liebig University)

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.

Suggested Citation

  • Martin Haupt & Anna Rozumowski & Jan Freidank & Alexander Haas, 2023. "Seeking empathy or suggesting a solution? Effects of chatbot messages on service failure recovery," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    • Handle: RePEc:spr:elmark:v:33:y:2023:i:1:d:10.1007_s12525-023-00673-0
    DOI: 10.1007/s12525-023-00673-0
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    References listed on IDEAS

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    Cited by:

    1. Won-Jun Lee, 2024. "Service Failure by Human, Service Recovery by AI Chatbot: The Impact of Justice, AI Efficacy on Recovery Effort," Virtual Economics, The London Academy of Science and Business, vol. 7(4), pages 48-63, December.

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    More about this item

    Keywords

    Artificial intelligence; Chatbot; Service failure; Failure recovery; Social cognitions; Digital platform;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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