Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
When using conversational agents (CAs), the interaction is typically either text- or speech-based. Existing research focuses on the effects of these interaction modalities or the general adoption of either text- or speech-based interaction, leaving an important research gap regarding users’ underlying preferences for interaction modalities. Therefore, this study investigates the influence of task, context, and individual user characteristics on user preferences for interaction modalities. We use a two-step approach consisting of exploratory interviews to identify 14 influencing factors, followed by a scenario-based experiment to quantitatively assess the impact of the identified task, context, and user characteristics. The results provide insights into the drivers for users’ preferences for interaction modalities when interacting with CAs. Thereby, we contribute to a more holistic understanding of human-CA interaction and provide a starting point for future research. The findings can further guide practitioners regarding which factors to consider in their decisions when investing in CAs.
Recommended Citation
Riefle, Lara and Benz, Carina, "User Preferences for Interaction Modalities: The Influence of Task, Context, and User Characteristics when Interacting with Conversational Agents" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 2.
https://aisel.aisnet.org/hicss-57/in/ai_based_assistants/2
User Preferences for Interaction Modalities: The Influence of Task, Context, and User Characteristics when Interacting with Conversational Agents
Hilton Hawaiian Village, Honolulu, Hawaii
When using conversational agents (CAs), the interaction is typically either text- or speech-based. Existing research focuses on the effects of these interaction modalities or the general adoption of either text- or speech-based interaction, leaving an important research gap regarding users’ underlying preferences for interaction modalities. Therefore, this study investigates the influence of task, context, and individual user characteristics on user preferences for interaction modalities. We use a two-step approach consisting of exploratory interviews to identify 14 influencing factors, followed by a scenario-based experiment to quantitatively assess the impact of the identified task, context, and user characteristics. The results provide insights into the drivers for users’ preferences for interaction modalities when interacting with CAs. Thereby, we contribute to a more holistic understanding of human-CA interaction and provide a starting point for future research. The findings can further guide practitioners regarding which factors to consider in their decisions when investing in CAs.
https://aisel.aisnet.org/hicss-57/in/ai_based_assistants/2