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Cited by 299

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Understanding the Effects of Color: How the Correspondence between Available and Required Resources Affects Attitudes

Meyers-Levy, Joan, Peracchio, Laura A.·1995·Journal of Consumer Research

Abstract

The impact of presenting full-color, black-and-white, and color-highlighted ad photos is examined under different processing resource conditions. When viewers devote few resources to processing, ads with some color outperform black-and-white ads. However, when viewers engage in more effortful ad processing, attitudes are sensitive to the match between available and required resources. When the substantial resources devoted to ad processing are inadequate for thorough ad scrutiny, black-and-white ads or those that color highlight aspects highly relevant to ad claims are more persuasive. By contrast, when available resources better approximate those required for extensive ad scrutiny, full-color ads or ads that color highlight ad photo elements that are highly relevant to the ad claims are more persuasive than either black-and-white ads or ads that color highlight aspects of low relevance to ad claims. These outcomes are interpreted by extending notions offered by elaboration-likelihood and resource theories.

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Metadata

Authors
Meyers-Levy, J., & Peracchio, L. A.
Venue
Journal of Consumer Research
Published
1995-09
Volume
22
Issue
2
Pages
121
ISSN
  • 0093-5301 (ISSN-L)
  • 1537-5277
OpenAlex
W2076733806
Cited by
299
References
0
FWCI
9.01
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Understanding the Effects of Color: How the Correspondence between Available and Required Resources Affects Attitudes. https://app.cochat.ai/papers/10.1086/209440
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Meyers-Levy, J., & Peracchio, L. A. (1995). Understanding the Effects of Color: How the Correspondence between Available and Required Resources Affects Attitudes. Journal of Consumer Research. https://doi.org/10.1086/209440

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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.