Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/287213 
Year of Publication: 
2021
Citation: 
[Journal:] Electronic Markets [ISSN:] 1422-8890 [Volume:] 32 [Issue:] 1 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2021 [Pages:] 239-258
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
Conversational agents (CAs) are often unable to provide meaningful responses to user requests, thereby triggering user resistance and impairing the successful diffusion of CAs. Literature mostly focuses on improving CA responses but fails to address user resistance in the event of further response failures. Drawing on inoculation theory and the elaboration likelihood model, we examine how inoculation messages, as communication that seeks to prepare users for a possible response failure, can be used as an alleviation mechanism. We conducted a randomized experiment with 558 users, investigating how the performance level (high or low) and the linguistic form of the performance information (qualitative or quantitative) affected users' decision to discontinue CA usage after a response failure. We found that inoculation messages indicating a low performance level alleviate the negative effects of CA response failures on discontinuance. However, quantitative performance level information exhibits this moderating effect on users' central processing, while qualitative performance level information affected users' peripheral processing. Extending studies that primarily discuss ex-post strategies, our results provide meaningful insights for practitioners.
Subjects: 
Conversational agent
Chatbot
Inoculation messages
Elaboration likelihood model
Customer service
JEL: 
C91
D91
L86
M31
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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