The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Relative visual saliency differences induce sizable bias in consumer choice
Abstract
Consumers often need to make very rapid choices among multiple brands (e.g., at a supermarket shelf) that differ both in their reward value (e.g., taste) and in their visual properties (e.g., color and brightness of the packaging). Since the visual properties of stimuli are known to influence visual attention, and attention is known to influence choices, this gives rise to a potential visual saliency bias in choices. We utilize experimental design from visual neuroscience in three real food choice experiments to measure the size of the visual saliency bias and how it changes with decision speed and cognitive load. Our results show that at rapid decision speeds visual saliency influences choices more than preferences do, that the bias increases with cognitive load, and that it is particularly strong when individuals do not have strong preferences among the options.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Computational modelling of visual attention
Itti, L., & Koch, C. (2001) · Nature Reviews Neuroscience · doi:10.1038/35058500 · Cited by 4,733
Self-citationThe Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks
Ratcliff, R., & McKoon, G. (2008) · Neural Computation · doi:10.1162/neco.2008.12-06-420 · Cited by 3,059
(2000) · doi:10.1017/cbo9780511803475 · Cited by 2,987
A framework for studying the neurobiology of value-based decision making
Rangel, A., Camerer, C., & Montague, P. R. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2357 · Cited by 2,184
Self-citationVisual fixations and the computation and comparison of value in simple choice
Krajbich, I., Armel, C., & Rangel, A. (2010) · Nature Neuroscience · doi:10.1038/nn.2635 · Cited by 1,408
Self-citationGaze bias both reflects and influences preference
Shimojo, S., Simion, C., Shimojo, E., & Scheier, C. (2003) · Nature Neuroscience · doi:10.1038/nn1150 · Cited by 924
Cited by
Wilson, A. L., Buckley, E., Buckley, J. D., & Bogomolova, S. (2016) · Food Quality and Preference · doi:10.1016/j.foodqual.2016.02.009 · Cited by 308
Attention, Reward, and Information Seeking
Gottlieb, J., Hayhoe, M., Hikosaka, O., & Rangel, A. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.3270-14.2014 · Cited by 168
Self-citation
Metadata
- Authors
- Milosavljevic, M., Navalpakkam, V., Koch, C., & Rangel, A.
- Venue
- Journal of Consumer Psychology
- Publisher
- Wiley
- Published
- 2011-12-03
- Volume
- 22
- Issue
- 1
- Pages
- 67-74
- ISSN
- 1057-7408 (ISSN-L)
- 1532-7663
- OpenAlex
- W1973769610
- Cited by
- 394
- References
- 6
- FWCI
- 3.88
- Type
- journal article
- Language
- en
- Open access
- closed
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Relative visual saliency differences induce sizable bias in consumer choice. https://app.cochat.ai/papers/10.1016/j.jcps.2011.10.002
- The paper
- Milosavljevic, M., Navalpakkam, V., Koch, C., & Rangel, A. (2012). Relative visual saliency differences induce sizable bias in consumer choice. Journal of Consumer Psychology. https://doi.org/10.1016/j.jcps.2011.10.002
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.