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Do red and blue colors in marketing contexts have differential effects on consumer attitudes and behaviors? Evidence from meta-analysis and experiments
LIU Wumei, WANG Lu, HUANG Lei
2026, 58 (10):
2121-2138.
doi: 10.3724/SP.J.1041.2026.2121
As crucial sensory cues, color marketing has long attracted sustained attention from marketing practitioners and scholars. Red and blue, as two frequently contrasted colors in marketing practice and academic research, are widely used in advertisements, product packaging, store decorations, and brand logos. Despite their practical and theoretical importance, existing findings on the effects of red and blue remain inconsistent. Moreover, relatively little attention has been paid to whether color effects differ across consumers' attitudinal responses and behavioral responses. While some studies suggest that blue outperforms red in enhancing consumer responses, others report the opposite. This inconsistency raises critical questions: Does blue, compared with red, exert an overall positive effect on consumer responses? Do its effects differ between attitudinal responses, such as brand favorability, and behavioral responses, such as ad clicks or purchase behavior? To address these questions, this meta-analysis interprets and calibrates the overall effects of blue versus red on consumers' attitudinal and behavioral responses. In addition, drawing on dual-system processing theory, this study proposes a four-quadrant theoretical framework to explain the mechanisms underlying the differential effects of red and blue on these two types of consumer responses.
A comprehensive literature search was conducted across EBSCO, Web of Science, Elsevier, and Wiley databases, yielding 51 eligible articles with 156 effect sizes. The sample spanned the U.S., China, the U.K., Japan, and other countries. Two independent coders systematically coded the included studies, recording each study's basic information, including authors, publication year, journal, effect size information, sample size, and moderator coding. Effect sizes were coded as correlation coefficients or converted from available statistics, such as F values, t values, Cohen's d, means, and standard errors. Using multilevel hierarchical linear modeling, the present meta-analysis accounted for the nested structure of multiple effect sizes within the same article. Data analysis was performed using the meta, metafor, and metaSEM packages in R 4.5.2. Prior to the formal analysis, publication bias was assessed using the Fail-Safe Number to ensure the robustness of the findings.
The meta-analysis revealed that blue, compared with red, had a positive effect on both consumers' attitudinal responses and behavioral responses. Specifically, blue exerted a stronger positive effect on attitudinal responses, r = 0.11, and a positive but relatively weaker effect on behavioral responses, r = 0.08. Thus, although blue generally elicited more positive consumer responses than red, its effect was stronger for attitudinal responses than for behavioral responses. This finding suggests that the influence of color is not uniform across different types of consumer outcomes. More importantly, the results indicate that the inconsistent conclusions in prior research can be better understood by distinguishing between attitudinal and behavioral responses and by considering how different moderators shape affective and rational processing.
Grounded in dual-system processing theory, this study further examined how four categories of moderators account for the inconsistent effects of red and blue on consumers' attitudinal and behavioral responses. Specifically, these moderators were classified into four categories: variables that influence affective processing, variables that influence rational processing, variables that simultaneously influence both affective and rational processing, and variables that influence neither affective nor rational processing. This four-quadrant framework helps explain why blue versus red may produce stronger, weaker, or even inconsistent effects across attitudinal and behavioral outcomes under different conditions. In addition, an online experiment was conducted to further examine the mechanism underlying the inconsistent effects of red and blue on consumers' attitudinal and behavioral responses, providing additional evidence for the proposed theoretical explanation.
Theoretically, this study makes several contributions. First, it reconciles inconsistent findings in prior color psychology research by quantitatively calibrating the overall effect of blue versus red on consumer responses. Second, by distinguishing between attitudinal and behavioral responses, this study reveals that blue has a stronger influence on consumer attitudes than on consumer behaviors, thereby offering a more nuanced understanding of color effects in marketing contexts. Third, the proposed four-quadrant framework extends dual-system processing theory to the domain of color marketing by showing how affective and rational processing jointly shape the boundary conditions of red and blue color effects. Finally, this study extends the application of connectionism theory and dual-system processing theory by demonstrating how color cues may activate different psychological associations and processing routes, which in turn produce differentiated consumer responses.
Practically, the findings provide actionable implications for color marketing. Since blue generally elicits more positive consumer responses than red, firms may consider using blue when the goal is to enhance overall consumer evaluations. However, because blue has a stronger effect on attitudinal responses than on behavioral responses, marketers should not assume that favorable attitudes will automatically translate into corresponding consumer behaviors. Instead, they should strategically match color choices with specific marketing objectives. For example, when the primary goal is to enhance brand favorability, product liking, or advertising evaluation, blue may be particularly effective. When the goal is to stimulate behavioral responses, such as clicks, purchases, or sharing, firms should consider whether additional contextual cues are needed to strengthen the translation from attitude to behavior. Overall, this study offers guidance for firms on how to use red and blue more appropriately in marketing practice.
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