Chatbots are increasingly prevalent in the service frontline. Due to advancements in artificial intelligence, chatbots are often indistinguishable from humans. Regarding the question whether firms should disclose their chatbots' nonhuman identity or not, previous studies find negative consumer reactions to chatbot disclosure. By considering the role of trust and service-related context factors, this study explores how negative effects of chatbot disclosure for customer retention can be prevented.
This paper presents two experimental studies that examine the effect of disclosing the nonhuman identity of chatbots on customer retention. While the first study examines the effect of chatbot disclosure for different levels of service criticality, the second study considers different service outcomes. The authors employ analysis of covariance and mediation analysis to test their hypotheses.
Chatbot disclosure has a negative indirect effect on customer retention through mitigated trust for services with high criticality. In cases where a chatbot fails to handle the customer's service issue, disclosing the chatbot identity not only lacks negative impact but even elicits a positive effect on retention.
The authors provide evidence that customers will react differently to chatbot disclosure depending on the service frontline setting. They show that chatbot disclosure does not only have undesirable consequences as previous studies suspect but can lead to positive reactions as well. By doing so, the authors draw a more balanced picture on the consequences of chatbot disclosure.
This is a submission for the JOSM special section on “Living and Working with (Ro)bots – The Impact of (Ro)bots on the Service Frontline”.
The authors thank Thorsten Hennig-Thurau, Michael Paul, Tillmann Wagner, Gianfranco Walsh, and all participants of the 2019 and 2020 Research Bootcamp on Marketing for their valuable feedback on earlier drafts of the manuscript.
Mozafari, N., Weiger, W.H. and Hammerschmidt, M. (2022), "Trust me, I'm a bot – repercussions of chatbot disclosure in different service frontline settings", Journal of Service Management, Vol. 33 No. 2, pp. 221-245. https://doi.org/10.1108/JOSM-10-2020-0380
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