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AI-Assisted Shopping on Voice Assistants: The Efficiency–Autonomy Consumer Decision Trade-Off

Alex Mari et al.

Journal of Interactive Marketing2025https://doi.org/10.1177/10949968251400616article
AJG 3ABDC A
Weight
0.50

Abstract

AI-based voice assistants (VAs), such as Amazon Alexa, are emerging as powerful mediators of AI-assisted shopping processes, yet their influence on consumer decision autonomy remains underexplored. To examine whether and how consumers delegate decisions to AI-powered assistants within an efficiency–autonomy trade-off, this study employed a single-session online experiment (n = 484) using a custom Alexa shopping app. To account for the role of the first recommended option, the brand (private label vs. national) and price (cheap vs. premium) were varied. Contrary to other shopping environments, when purchasing low-involvement and utilitarian products through VA-assisted shopping, evaluating fewer alternatives (indicative of greater efficiency) is associated with higher decision satisfaction and a greater intention to cede decision autonomy to the VA. The findings reveal that the number of alternatives evaluated is negatively associated with consumers’ intentions to delegate tasks to the VA and trust its product recommendations, both directly and indirectly, through decision satisfaction. Notably, the effect of streamlined choice persists across brand types and price levels. The results highlight consumers’ willingness to trade autonomy for efficiency in AI-assisted voice shopping, which has strategic implications for national brands operating in voice commerce environments.

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https://doi.org/https://doi.org/10.1177/10949968251400616

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@article{alex2025,
  title        = {{AI-Assisted Shopping on Voice Assistants: The Efficiency–Autonomy Consumer Decision Trade-Off}},
  author       = {Alex Mari et al.},
  journal      = {Journal of Interactive Marketing},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/10949968251400616},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.