Rozumowski, Anna

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Anna
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Anna Rozumowski

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2021 - 20232
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Autor:in: Haupt, Martin ×

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    Publikation
    Seeking empathy or suggesting a solution? Effects of chatbot messages on service failure recovery
    (Springer, 2023) Haupt, Martin; Rozumowski, Anna; Freidank, Jan; Haas, Alexander [in: Electronic Markets]
    Chatbots as prominent form of conversational agents are increasingly implemented as a user interface for digital customer 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.
    01A - Beitrag in wissenschaftlicher Zeitschrift
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    Publikation
    Active expectation management in chatbot conversations
    (University of Melbourne, 2021) Haupt, Martin; Rozumowski, Anna; Bove, Liliana L.; Bell, Simon J.; Hito, Abraham [in: Something Different. ANZMAC 2021, Conference Proceedings]
    Chatbots have gained strong popularity in customer service, although users regularly experience unsatisfactory interactions and service failures, often due to highly exaggerated performance expectations. As a viable option, firms might therefore consider using ‘active expectations management’ by describing chatbot limitations. However, the question remains whether this strategy has a positive or negative impact on customer satisfaction and reuse intentions. Drawing on expectancy violation theory and the computers are social actors (CASA) paradigm, we empirically examine the effects of different expectation management strategies on user satisfaction and reuse intention. The results of a between-subjects experiment (n = 346) demonstrate that expectation management is an effective strategy to at least partly recover the failure. Furthermore, we show that different message types (i.e., ‘adapt’ vs. ‘understand’) have differential effects, whereas message positioning was found to be irrelevant. Our results enrich the service and chatbot literature and give managerial guidance for successful chatbot design.
    04B - Beitrag Konferenzschrift