Fluent voice, credible choice – how language embodiment and consumption goals shape voice commerce success
Year: 2025
Type: article
Abstract: Purpose Voice assistants (VAs) could be a game changer in conversational commerce. However, consumers often reject purchase recommendations by VAs due to disfluency and low credibility of VAs’ messages. To overcome these barriers and increase recommendation adoption, this study examines which language style leads to voice commerce success and how consumer-related boundary conditions shape this effect. Design/methodology/approach In three experiments, the authors collected data from consumers listening to VA recommendations in different styles and commerce settings. The first study examines the effect of figurative (vs literal) language on recommendation adoption, while the second study focuses on the moderating impact of consumers’ consumption goals (hedonic vs utilitarian). The third study delves into the underlying mechanisms leading to enhanced visual fluency in voice interactions. Findings The experiments demonstrate that figurative language increases visual fluency, with no differences across consumption goals (hedonic vs utilitarian). However, figurative language enhances credibility in a hedonic context while reducing it in a utilitarian one. Visual fluency and credibility mediate the effect of figurative language on recommendation adoption. The results further reveal the crucial role of arousal for triggering visual fluency in response to figurative language. Originality/value This research examines how and when using language styles from human-to-human communication context can enhance service interactions in the voice-driven marketplace. It shows that a VA’s figurative language can lead to a trade-off between visual fluency and credibility, but a match with the right consumer goal eliminates it. Therefore, this research provides new insights on when embodied voice systems either limit or boost voice commerce success.
Source: Journal of service management
Institutions: University of Göttingen, Saarland University
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408738089