Why would consumers risk taking purchase recommendations from voice assistants?

Ransome Epie Bawack (), Emilie Bonhoure and Sabrine Mallek ()
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Ransome Epie Bawack: Audencia Business School
Emilie Bonhoure: Kedge BS - Kedge Business School
Sabrine Mallek: ICN Business School, CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - UL - Université de Lorraine

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Abstract: Purpose This study aims to identify and explore different risk typologies associated with consumer acceptance of purchase recommendations from voice assistants (VAs). Design/methodology/approach Drawing on components of perceived risk, consumer trust theory, and consumption value theory, a research model was proposed and tested using structural equation modeling (SEM) with data from 482 voice shoppers. Findings The results reveal that, unlike risks associated with physical harm, privacy breaches, and security threats, a variety of other concerns—including financial, psychological, social, performance-related risks, time loss, and the overall perceived risks—significantly influence consumers' willingness to accept VAs purchase recommendations. The effect is mediated by trust in VA purchase recommendations and their perceived value. Different types of risk affect various consumption values, with functional value being the most influential. The model explains 58.6% of the variance in purchase recommendation acceptance and significantly elucidates the variance in all consumption values. Originality/value This study contributes crucial knowledge to understanding consumer decision-making processes as they increasingly leverage AI-powered voice-based dialogue platforms for online purchasing. It emphasizes recognizing diverse risk typologies associated with VA purchase recommendations and their impact on consumer purchase behavior. The findings offer insights for marketing managers seeking to navigate the challenges posed by consumers' perceived risks while leveraging VAs as an integral component of modern shopping environments.

Date: 2024-04-02
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Published in Information Technology and People, 2024, ⟨10.1108/ITP-01-2023-0001⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04578873

DOI: 10.1108/ITP-01-2023-0001

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