Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/287062 
Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Information Systems Frontiers [ISSN:] 1572-9419 [Volume:] 24 [Issue:] 3 [Publisher:] Springer US [Place:] New York, NY [Year:] 2021 [Pages:] 839-856
Verlag: 
Springer US, New York, NY
Zusammenfassung: 
Owing to technological advancements in artificial intelligence, voice assistants (VAs) offer speech as a new interaction modality. Compared to text-based interaction, speech is natural and intuitive, which is why companies use VAs in customer service. However, we do not yet know for which kinds of tasks speech is beneficial. Drawing on task-technology fit theory, we present a research model to examine the applicability of VAs to different tasks. To test this model, we conducted a laboratory experiment with 116 participants who had to complete an information search task with a VA or a chatbot. The results show that speech exhibits higher perceived efficiency, lower cognitive effort, higher enjoyment, and higher service satisfaction than text-based interaction. We also find that these effects depend on the task's goal-directedness. These findings extend task-technology fit theory to customers' choice of interaction modalities and inform practitioners about the use of VAs for information search tasks.
Schlagwörter: 
voice assistant
conversational agent
speech interaction
cognitive fit
customer service
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