Voice Assistant vs. Chatbot – Examining the Fit Between Conversational Agents’ Interaction Modalities and Information Search Tasks

Christine Rzepka (), Benedikt Berger () and Thomas Hess ()
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Christine Rzepka: Ludwig-Maximilians-Universität München (LMU Munich)
Benedikt Berger: University of Münster
Thomas Hess: Ludwig-Maximilians-Universität München (LMU Munich)

Information Systems Frontiers, 2022, vol. 24, issue 3, No 7, 839-856

Abstract: Abstract 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.

Keywords: voice assistant; conversational agent; speech interaction; cognitive fit; customer service (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10796-021-10226-5

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