Visual attention during brand choice: The impact of time pressure and task motivation
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The gaze bias effect suggests that preference for the AI suggestion and adoption of the AI suggestion means longer gaze duration on the AI suggestion.
“Furthermore, the gaze bias effect suggests that preference for the AI suggestion and adoption of the AI suggestion means longer gaze duration on the AI suggestion [58].”
From Understanding User Reliance on AI in Assisted Decision-Making (2022) · cites this paper as [58]
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- Authors
- Pieters, R., & Warlop, L.
- Affiliations
- Tilburg University (NL)
- KU Leuven (BE)
- Corresponding author
- Pieters, Rik
- Venue
- International Journal of Research in Marketing
- Publisher
- Elsevier BV
- Published
- 1999-02
- Volume
- 16
- Issue
- 1
- Pages
- 1-16
- ISSN
- 0167-8116 (ISSN-L)
- OpenAlex
- W2234649517
- Cited by
- 603
- References
- 36
- Citations by year
- 2026: 26 · 2025: 23 · 2024: 26 · 2023: 23 · 2022: 33 · 2021: 46 · 2020: 54 · 2019: 43 · 2018: 36 · 2017: 37 · 2016: 38 · 2015: 33 · 2014: 37 · 2013: 25 · 2012: 31
- FWCI
- 17.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Research in Marketing (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Packaging Perceptions and Trends
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Retail Behavior Studies
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Keywords
- visual attention, brand choice, time pressure, task motivation, eye movements, information filtering, saccades, fixation duration, consumer attention
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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