Conversational Breakdown in a Customer Service Chatbot: Impact of Task Order and Criticality on User Trust and Emotion

While chatbots are increasingly used for customer service, there is a knowledge gap concerning the impact of Conversational Breakdown in such chatbot interactions. In a 2 \({\times}\) 4 factorial design online experiment, we studied how Conversational Breakdown impacts user emotion and trust in a chatbot for customer service, given variations in task criticality and breakdown task order. Here, 257 participants were randomly assigned to complete high- or low-criticality tasks with a prototype chatbot for customer service, experiencing Conversational Breakdown for the first, second, third or none of their tasks. The task set was decided from a 63-participant pre-study. We found significant impact of Conversational Breakdown, including a marked order effect on overall trust, as well as a bounce-back effect on task-specific trust and emotion after subsequent successful task completion. We found no post-interaction effect of Task Criticality. Based on our findings, we discuss theoretical and practical implications and suggest future research.

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Publication Details

Journal
ACM Transactions on Computer-Human Interaction
Published
2024-09-03
DOI
https://doi.org/10.1145/3690383
Citations
9
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
3.13

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article

Conversational Breakdown in a Customer Service Chatbot: Impact of Task Order and Criticality on User Trust and Emotion

Effie Lai‐Chong Law, Asbjørn Følstad, Nena van As
9 citations
ACM Transactions on Computer-Human Interaction
AI in Service Interactions
3.13
article

Conversational Breakdown in a Customer Service Chatbot: Impact of Task Order and Criticality on User Trust and Emotion

Effie Lai‐Chong Law, Asbjørn Følstad, Nena van As
article en
9 citations

Abstract

While chatbots are increasingly used for customer service, there is a knowledge gap concerning the impact of Conversational Breakdown in such chatbot interactions. In a 2 \({\times}\) 4 factorial design online experiment, we studied how Conversational Breakdown impacts user emotion and trust in a chatbot for customer service, given variations in task criticality and breakdown task order. Here, 257 participants were randomly assigned to complete high- or low-criticality tasks with a prototype chatbot for customer service, experiencing Conversational Breakdown for the first, second, third or none of their tasks. The task set was decided from a 63-participant pre-study. We found significant impact of Conversational Breakdown, including a marked order effect on overall trust, as well as a bounce-back effect on task-specific trust and emotion after subsequent successful task completion. We found no post-interaction effect of Task Criticality. Based on our findings, we discuss theoretical and practical implications and suggest future research.

ACM Transactions on Computer-Human InteractionVol. 31(5)
SINTEF (NO), Durham University (GB), Jaeder (Norway) (NO)
Norges Forskningsråd
Openalex Percentile: Top 7%
AI in Service Interactions
3.13
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