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Paper Type
ERF
Description
Although AI-based chatbots have become increasingly prevalent in various business practices and show promise in providing emotional support, there is still limited understanding of the mechanism that underlies the relationship between the anthropomorphic attributes of AI-based relational chatbots and user engagement. To address this gap, we draw on the social judgment theory and propose that emotional judgment mediates the relationship between conversational styles of chatbots (agentic-style and communal-style) and user engagement. We also examine the potential boundary effect of two types of AI avatars (humanlike vs. cartoonlike) on this relationship. To test our hypotheses, we plan to conduct two studies, which will include online and lab experiments. We aim to extend existing theories involving social judgment theory and human reactivity to AI-based chatbots in emotional support settings and identify how different types of anthropomorphic attributes of AI-based relational chatbots may jointly impact user behaviors.
Paper Number
1451
Recommended Citation
Wang, Guoxin, "Can AI Chatbots with Anthropomorphic Attributes Enhance User Engagement in Emotional Support Settings? Investigating the Role of Conversational Styles and Avatar Type" (2023). AMCIS 2023 Proceedings. 8.
https://aisel.aisnet.org/amcis2023/sig_aiaa/sig_aiaa/8
Can AI Chatbots with Anthropomorphic Attributes Enhance User Engagement in Emotional Support Settings? Investigating the Role of Conversational Styles and Avatar Type
Although AI-based chatbots have become increasingly prevalent in various business practices and show promise in providing emotional support, there is still limited understanding of the mechanism that underlies the relationship between the anthropomorphic attributes of AI-based relational chatbots and user engagement. To address this gap, we draw on the social judgment theory and propose that emotional judgment mediates the relationship between conversational styles of chatbots (agentic-style and communal-style) and user engagement. We also examine the potential boundary effect of two types of AI avatars (humanlike vs. cartoonlike) on this relationship. To test our hypotheses, we plan to conduct two studies, which will include online and lab experiments. We aim to extend existing theories involving social judgment theory and human reactivity to AI-based chatbots in emotional support settings and identify how different types of anthropomorphic attributes of AI-based relational chatbots may jointly impact user behaviors.
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