Author Identifier

Sanjit K. Roy: https://orcid.org/0000-0003-4932-2222

Document Type

Journal Article

Publication Title

Psychology and Marketing

Publisher

Wiley

School

School of Business and Law

Comments

Basu, B., Roy, S. K., & Apostolidis, C. (2025). Unveiling the charisma of artificial intelligence: How voice assistants captivate users and emotionally influence user experience. Psychology & Marketing. Advance online publication. https://doi.org/10.1002/mar.22233

Abstract

Although studies have explored user experience (UX) with artificial intelligence (AI)-powered voice assistants (VAs), the cognitive, psychological, and emotional factors affecting user engagement and experience with VAs have yet to be investigated in depth. Drawing on cognitive absorption and broaden-and-build theories, this study investigates how VAs captivate users, enhance positive emotions, and influence the overall UX. To address these questions, we conduct three types of analyses—exploratory, confirmatory, and configurational—utilizing data from 125,600 user reviews on a popular VA platform (Google Assistant) from 2017 to 2024. First, we employ bidirectional encoder representations from the transformers (BERT)topic modeling to unearth relevant cognitive and psychological factors and use multiple regression analyses to test their impact on UX. Our findings both confirm and contradict previous affirmations about these factors' influence on user engagement and experience with VAs. Next, we apply fuzzy-set qualitative comparative analysis (fsQCA) to explore counterfactual causal configurations that contribute to a higher UX. Contributing to existing theory and knowledge of the psychological antecedents of user experiences with AI, our study identifies several combinations of cognitive and emotional factors that can improve user interactions with VAs.

DOI

10.1002/mar.22233

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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Marketing Commons

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Link to publisher version (DOI)

10.1002/mar.22233