“Function or emotion?”: understanding smart shopping via voice AI based on the LVSEM approach

Purpose This research aims to identify consumers’ diverse motivations and the underlying psychological mechanism of smart shopping via voice AI. Design/methodology/approach The research used an online survey with 477 US participants and employed latent variables with observed items for structural equation modeling (LVSEM). Data analyses, including confirmatory factor analysis, invariance testing, common method bias testing, internal reliability testing and moderation and mediation analyses, were conducted. Findings The key findings showed that reducing decision-making time is crucial for predicting smart shopping loyalty, with utilitarian and technological value being more important than hedonic and social value. Originality/value This research contributes to the voice AI, smart retailing and uses-and-gratifications literature, offering implications for retailers, service providers and smart technology designers by highlighting voice AI as an efficient, convenient decision-aid tool.