Is it a Match? Examining the Fit between Conversational Interaction Modalities and Task Characteristics

Rzepka Christine, Berger Benedikt, Hess Thomas


Abstract
Owing to technological advancements in artificial intelligence, specifically natural language processing, voice assistants (VAs) offer a new modality for interacting with computers. Compared to formalized and deliberate text-based interaction, speech is more natural and intuitive. As companies offer customers the possibility of communicating with them via VAs, it is important to determine the kind of tasks for which this interaction modality is beneficial. Drawing on cognitive fit and task-technology fit theory, we present a research model for examining the fit between speech- and text-based interaction modalities and task characteristics. To test this model, we propose a mixed design laboratory experiment with interaction modality serving as between-subject factor and task type serving as within-subject factor. For this purpose, we developed a VA using DialogFlow and trained it in two pre-tests. The results of the experiment will extend theory on cognitive fit and provide practical insight regarding the applicability of speech.

Keywords
voice assistant; conversational agent; speech interaction; cognitive fit



Publication type
Forschungsartikel in Sammelband (Konferenz)

Peer reviewed
Yes

Publication status
Published

Year
2020

Conference
41st International Conference on Information Systems (ICIS)

Venue
virtual

Language
English

Full text