Artikel
Voice Assistant vs. Chatbot – Examining the Fit Between Conversational Agents’ Interaction Modalities and Information Search Tasks
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.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Information Systems Frontiers ; ISSN: 1572-9419 ; Volume: 24 ; Year: 2021 ; Issue: 3 ; Pages: 839-856 ; New York, NY: Springer US
- Klassifikation
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Allgemeines, Wissenschaft
- Thema
-
voice assistant
conversational agent
speech interaction
cognitive fit
customer service
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Rzepka, Christine
Berger, Benedikt
Hess, Thomas
- Ereignis
-
Veröffentlichung
- (wer)
-
Springer US
- (wo)
-
New York, NY
- (wann)
-
2021
- DOI
-
doi:10.1007/s10796-021-10226-5
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Rzepka, Christine
- Berger, Benedikt
- Hess, Thomas
- Springer US
Entstanden
- 2021
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