Rozumowski, Anna
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Seeking empathy or suggesting a solution? Effects of chatbot messages on service failure recovery
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.
Active expectation management in chatbot conversations
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.
Digitale Transformation, Business Model Innovation und IT-Sicherheit. Veränderung als Chance für die kontinuierliche digitale Transformation nutzen
Die digitale Transformation hat die Bedürfnisse, die Erwartungen und insbesondere das Verhalten der Menschen nachhaltig verändert. Um diesen Veränderungen gerecht zu werden, sind Unternehmen gefordert, ihre Strategien und Geschäftsmodelle auf die digitalen Bedürfnisse auszurichten und ihr Leistungsversprechen an den veränderten Markt anzupassen. Mit der digitalen Transformation und mit Business Innovationen können Unternehmen neue Geschäftspotenziale identifizieren, aufbauen und damit den eigenen Markterfolg stärken. Dabei gilt es, Mehrwerte für Kundinnen und Kunden zu schaffen und zeitgleich die eigene Wettbewerbsfähigkeit zu steigern. Doch Transformation und Business Model Innovation bedeuten mehr, als Produktneuheiten oder neue Dienstleistungen anzubieten. Es handelt sich um die Transformation von Geschäftsmodellen. Hier gilt es auch, die möglichen Gefahren des digitalen Zeitalters rund um das Thema IT-Sicherheit zu kennen und Konzepte zur Stärkung der IT-Infrastruktur aufzubauen.
Now you see me: a quantitative study on the effects of ad blocker usage on users’ brand perception
An increasing amount of Web users is turning to ad blockers to avoid ads, which Web users perceive as annoying, an invasion of privacy, or as slackening their Web experience. Ad blocker users still encounter online advertising on their Web journey although using ad blockers. While there has been significant research into factors driving ad blocker adoption, the effects of online advertising on brand perception for ad blocker users are not well understood. To approach this white space, we conduct an online survey. We build two groups, ad blocker users and non-users. We then check for significant differences in likeability toward and perceived positive image of the brands the groups saw online ads. In our analysis, we did not find any significant difference neither in the first nor in the second variable between ad blocker users and non-users for when they see online advertising. We conclude that ad blocker users remain interesting targets for advertisers.