Abstract
The present study investigated the effect of colors red and blue on fair behavior in two economic games. Study 1 showed that the color red (vs. blue) could lead to a higher (vs. lower) offer in the ultimatum game, and that this effect was mediated by the perceived competitiveness. Study 2 introduced the impunity game and showed that the colors red and blue only affected offers in the ultimatum game, but not in the impunity game. These findings suggested that colors play a more influential role in strategic motives than in pure altruism in fair decision-making, and color-induced perceived competitiveness underlies this effect. This study presents the first empirical evidence of the relationship between colors and fairness in decision-making and offers a solution to nudge cooperative and fair behavior in allocation.
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Introduction
Color plays an important role in shaping human perception, serving as an essential part of our daily lives and influencing our interactions with both people and objects. Several seminal studies have demonstrated the impact of color on human behavior in various contexts, including cognitive tasks (Mehta and Zhu, 2009), dating (Elliot and Niesta, 2008), achievement (Elliot et al., 2007), and consumption (Bagchi and Cheema, 2013), where sometimes the same color may even lead to completely opposite effects in different contexts. Similarly, color is also ubiquitous in decision-making settings, from the color of walls to the hue of furniture, and even the color of an opponent’s clothing—each of which may sway the outcomes of decisions (Mao et al., 2018). Yet, little is known about whether and how color affects individual decision-making behavior, such as fair decision-making. We aim to expand this area of research by investigating the influence of red versus blue colors on individuals’ fair behavior in the ultimatum game (UG) and the impunity game (IG), and by exploring the underlying mechanisms of this process. Intuitively, one might expect that red, due to its associations with danger, threat perception, and distrust, would disrupt fair behavior than blue (Elliot and Maier, 2014). However, our findings suggest that red can actually enhance fairness in decision-making, rather than blue. This is because red can invoke an individual’s perceived competitiveness, which in turn increases their anticipation of being punished or resisted by others for violating fairness norms, thus leading to fairer behavior. This process is primarily driven by individual strategic motives rather than altruistic ones.
Red versus blue color and perceived competitiveness
Although color is objectively specified by brightness, saturation, and hue, it also carries subjective meanings within social contexts, thereby providing the potential to affect interpersonal perceptions (Elliot and Maier, 2014), such as the perception of competitiveness among individuals (Hong et al., 2024). To date, numerous studies from both humans (Hill and Barton, 2005; Little and Hill, 2007; Wiedemann et al., 2015) and non-humans (Cuthill et al., 1997; Setchell and Jean Wickings, 2005) have established the association between the color red and aggression, revealing that red can evoke higher levels of aggression. For example, Hill and Barton (2005), in their analysis of data from the 2004 Olympic Games, found that contestants wearing red outfits won more fights than their blue-outfit opponents when skill levels were controlled. They attributed this effect to the possibility that red clothing might stimulate aggression, thereby enhancing competitive performance. Even inanimate objects, such as red circles, are perceived as more aggressive and more dominant than blue ones (Little and Hill, 2007). This heightened aggression could intensify a sense of competition or increase competitive awareness among individuals (Anderson and Morrow, 1995). In one related study, Bagchi and Cheema (2013) found that red color (compared to blue or gray) leads to higher aggression in consumer contexts, and therefore can increase bid jumps in competitive auctions but decrease offers in cooperative negotiations. Additionally, from a physiological perspective, red has been found to induce feelings of arousal, excitement, and an increased heart rate (AL‐Ayash et al., 2016; Wilms and Oberfeld, 2018), all of which are consistent with the body’s responses when an individual enters a competitive state. Drawing on these insights, we infer that red may act as a competitive color in interpersonal interactions, potentially leading to a heightened sense of competition.
In contrast, blue highlights the side of relaxation and calmness (Elliot and Maier, 2014; Gorn et al., 2004). Studies have found that blue not only induces a physiological state of relaxation, evidenced by a reduced heart rate, lower skin conductivity, and smoother breathing (AL-Ayash et al., 2016; Wilms and Oberfeld, 2018), but also has a psychological relaxing effect (Elliot and Maier, 2014). For example, Gorn et al. (2004) discovered that users felt more relaxed when presented with a blue background compared to a red one. Consequently, this led to the users perceiving faster webpage downloads while they were waiting for the page to load. Considering that a relaxed atmosphere can help alleviate tense interpersonal relationships (Fletcher and Hanton, 2001), it is reasonable to speculate that blue may decrease perceived competitiveness in economic games. Actually, Aslam (2006) and Madden et al. (2000) have systematically established implicit associations with different colors and found that the color red is typically associated with meanings related to competition, whereas blue is associated with opposite meanings. Based on these findings, we propose the following hypothesis:
H1: The color red will increase perceived competitiveness (H1a), while the color blue will reduce perceived competitiveness (H1b) in economic games.
The motives behind fairness in decision-making
People frequently encounter decisions involving fairness in their daily lives, especially in scenarios that require the distribution of resources (Brosnan and de Waal, 2014; Sally and Hill, 2006). Given the importance of fair decision-making, understanding why people choose to act fairly has been a major focus of research. It is widely believed that two primary motivations drive fairness in human behavior. One suggests that fairness stems from altruistic motives. It posits that people exhibit fair behavior because of their innate pursuit of fairness and their concern for the well-being of others; this is a characteristic that comes naturally to them (Charness and Gneezy, 2008; Fehr and Fischbacher, 2003; Rand et al., 2012). As altruism towards one’s own kind can benefit the entire group’s reproductive success, this altruism has gradually become internalized as a code of conduct over the course of human evolution, thereby fostering a tendency towards fairness in decision-making (Brosnan and de Waal, 2014). Another perspective, based on self-regarding preferences, believes that fairness is driven by strategic motives. In fact, fair decision-making in daily life seldom takes place under entirely anonymous conditions (Franzen and Pointner, 2012). Since unfairness contradicts social norms, such behavior often leads to criticism or even punishment from others (Fehr and Gächter, 2002). Therefore, people exhibit fair behavior in interpersonal interactions because they hope to maintain a good reputation or avoid punishment for unfair actions, which essentially still maximize their own self-interest (Franzen and Pointner, 2012; Van Dijk et al., 2004). It is important to note that decision-makers vary in the extent of their altruistic and strategic motives. These two motives are not completely independent; rather, they interact in the process of fair decision-making, collectively shaping an individual’s behavior (Cutler and Campbell-Meiklejohn, 2019).
We will adopt the ultimatum game (Güth et al., 1982) as the task context for fair decision-making in this study. Our choice of the UG is grounded in two reasons: first, the UG is considered to realistically simulate real-world scenarios involving resource allocation (Charness and Gneezy, 2008), thus enhancing the applicability of our findings to predict actual fair behavior; second, the UG has been widely employed in existing studies (Güth and Kocher, 2014), allowing our results to be more effectively compared with existing literature. In this game, two players are allotted a sum of money. The first player, called the “proposer,” can make an offer to the second player, called the “responder,” as to how that money should be split. Then, the responder can either accept or reject the proposer’s offer. If accepted, the money would be split as proposed; if rejected, then neither player receives anything.
From perceived competitiveness to fairness in the ultimatum game
The social information processing theory posits that the environment surrounding individuals supplies a variety of information that shapes their attitudes and behaviors (Salancik and Pfeffer, 1978). In other words, people’s perceptions of others and their subsequent decisions are not only determined by their own needs and goals, but are largely influenced by contextual information (Salancik and Pfeffer, 1978). This is particularly true in tasks that are ambiguous and uncertain, where individuals are more inclined to rely on cues provided by the environment to guide their decision-making (Tiedens and Linton, 2001). Therefore, in the UG, color, as a form of contextual cue, may enter the decision-making process and exert an influence. By altering the perception of competitiveness, color may influence the proposers’ attitudes toward the responders and, consequently, affect their proposal behavior.
Fair decision-making frequently occurs within social interaction contexts involving multiple individuals. Consequently, it requires dealing with the other agents’ presumed reactions, expectations, and preferences, which may conflict with one’s own (Fehr and Gächter, 2002; Sally and Hill, 2006). Thus, people have to choose between pursuing personal interests and accommodating others’ expectations (Li et al., 2018). In the UG, rejections are commonly used by responders to punish proposers who violate fairness norms (Calvillo and Burgeno, 2015). As a result, proposers are incentivized to consider responders’ expectations to avoid making offers below the acceptance thresholds of responders and risking rejection (Sally and Hill, 2006). Previous studies show that competition could heighten UG responders’ intolerance of unfairness, subsequently raising their acceptance thresholds (Barclay and Stoller, 2014). This may stem from increased hostility towards proposers and a reduced propensity to cooperate when responders perceive competition (Anderson and Morrow, 1995; Van Lange et al., 1997). When proposers take this into account, they may increase their offers to ensure cooperation and reach a distribution agreement. Thus, competition indirectly influences proposers’ behavior by modifying their expectations regarding responders’ willingness to cooperate, which in turn affects their offers. This demonstrates a fairness consideration motivated by strategic intentions. Indeed, empirical evidence indicates that perceived competitiveness can increase individuals’ generosity in distributions with punishment. This generosity helps cultivate a reputation as a good cooperator, thereby enhancing the likelihood of benefiting from mutual cooperation or indirect reciprocity in competitive environments (Barclay and Willer, 2006; Greco et al., 2024). Relevant to the present study, previous research on the UG also confirms that competition prompts proposers to make higher offers to responders (Chiang, 2010; Davies and Fafchamps, 2017; Roth et al., 1991).
We have inferred the association between color and perceived competitiveness, with red being positively correlated and blue negatively correlated. Based on this relationship and the impact of competition on proposers, it can be further speculated that the competitiveness associated with red may lead proposers to overestimate responders’ acceptance thresholds, thereby increasing their expectation of offers being rejected. This could result in proposers making higher offers in the UG. Conversely, since blue tends to reduce perceived competitiveness, it may have the opposite effect on proposers’ offers. Taken together, we propose the following hypothesis:
Hypothesis 2: Proposers will make higher offers in the UG when they are in red, while lower offers in blue (H2a), and this effect is mediated by the color-induced perceived competitiveness (H2b).
Introducing the impunity game to disentangle strategic and altruistic motives
However, the proposal behavior in the UG involves more than just strategic motives, but also altruistic motives (Güth and Kocher, 2014). When it comes to altruistic motives, the shift in perceived competitiveness induced by red versus blue could lead to results opposite to those driven by strategic motives. Competition, which is often seen as the antithesis of cooperative behavior (Cornaglia et al., 2019), tends to increase individuals’ focus on self-interest or to prioritize their own gains over the welfare of others (Stapel and Koomen, 2005; Van Lange et al., 1997). In other words, competition can impair people’s pro-sociality and cooperativeness. For example, Xu et al. (2020) found that competitive interactions reduced pro-sociality in pure allocation tasks, irrespective of whether the others involved were in-group or out-group members. Accordingly, the color red, by increasing perceived competitiveness, may inhibit altruistic motives and thus weaken fairness in decision-making.
To separate the strategic motives and altruistic motives behind the proposal behavior influenced by colors, we introduced the impunity game (Bolton and Zwick, 1995) into our study. The process of IG is similar to that of the UG, where a “proposer” first decides how to split a sum of money, followed by the “responder” choosing to accept or reject the offer. The only difference is that if the responder rejects the offer, only his/her own payoff is reduced to zero, while the proposer’s payoff remains unchanged. Therefore, proposers in the IG will not be punished for unfairness, indicating that their proposal behavior will not contain strategic motives and will more directly reflect their intrinsic sense of fairness (Crosetto and Güth, 2021; Scheres and Sanfey, 2006). The IG was selected because it differs from the UG only in terms of strategic motives while keeping other aspects completely consistent (Bolton and Zwick, 1995). By comparing these two games, we can more effectively discern the differences in how color influences fair decision-making when strategic motives are absent (leaving only altruistic motives) and when they are present, while controlling for other variables. Since red may undermine altruistic motives by increased perceived competitiveness, we refer that red will reduce the proposer’s offers in the IG. Conversely, given the calming effect of blue, which is associated with reduced perceived competitiveness, we speculated that blue may have the opposite effect on the IG. Thus, we propose the following hypothesis:
Hypothesis 3: In the IG, proposers will make lower offers when they are in red and higher offers when they are in blue.
If H3 is supported, it suggests that colors affect altruistic motives as we inferred; if red and blue do not influence the IG offer, it suggests that colors have no impact on altruistic motives.
The present study
We conducted two studies to test our hypotheses. Study 1 explored the effect of the red versus blue color on the offers made by proposers in the UG, and included a mediation analysis to examine the mediating process of perceived competitiveness. Since the proposer’s behavior in the UG mixes strategic and altruistic motives, Study 2 introduced the IG to disentangle the explanatory roles of these two motives by comparing the effects of red versus blue on proposals in both the UG and IG. Through these two studies, we can reveal the extent to which the effect of colors on proposal behavior is determined by strategic or altruistic motives, or a combination of both. The present study has been approved by the Ethics Committee of the researcher’s institution, and informed consent was obtained from all participants before the experiments.
Study 1
Method
Participants
We used G*power 3.0 (Faul et al., 2007) to estimate the required sample size for the present study. Based on the experimental design and effect sizes observed in previous studies on color effect (f ≈ 0.25; Jiang et al., 2014; Geng et al., 2022), a minimum of 171 participants was deemed necessary to achieve sufficient statistical power (1−β > 0.90) at α < 0.05. A total of 191 participants (Mage = 21.77 ± 2.63, Mfemale = 54.97%) were recruited and offered monetary rewards as compensation for their participation.
Design
Study 1 consisted of three conditions: red, blue, and a colorless condition serving as the control group. Therefore, Study 1 was a single factor (Color: red vs. blue vs. control) between-subjects design. Participants played the role of UG proposers in Study 1 and were randomly assigned to one of the three conditions.
Materials and Procedure
The experiment was computer-based and conducted in a quiet laboratory by one trained experimenter. Participants engaged in a one-shot UG with a responder to split 100 Chinese yuan (approximately 14 US dollars). To allow participants to interact with a real person and thus ensure their belief in the authenticity of the situation and elicit genuine behavior, the responders in this study were all played by trained graduate students. Following the methods of Bagchi and Cheema (2013) and Mehta and Zhu (2009), we manipulated the color conditions by changing the background color of the task, with red [RGB = (255, 0, 0)], blue [RGB = (0, 0, 255)], and colorless backgrounds, respectively. A pretest with 52 participants assessed their perceptions of esthetics, pleasantness, and appropriateness for the different color backgrounds. The results indicated no significant differences in these aspects across the color backgrounds (ps > 0.05), thus ruling out the interference of these factors.
The experimental procedure is shown in Fig. 1. The participant was first instructed on the experimental procedure, followed by role assignment, where he or she was assigned to the role of proposer and matched with a responder. Next, the participant and the responder were guided to separate rooms and provided with individual computers. Once ready, the UG was played, and the participant was asked to propose an offer as instructed. After that, the participant evaluated the perceived competitiveness during the task using a 3-item scale developed by Murayama and Elliot (2012) with minor wording changes. Example items included “In this task, it seems that I am competing with others” (1 = highly disagree, 7 = highly agree). The mean was used as the measure of perceived competitiveness (α = 0.90). After completing the evaluation, participants received feedback indicating whether their responses had been accepted or rejected. Before the formal experiment, they took part in two practice rounds without feedback to become familiar with the process. To encourage genuine effort, we informed participants that an additional reward based on their performance would be given to 10% of them, selected at random.
The experimental procedure of Study 1.
As previous studies have indicated that social value orientation (SVO) and socioeconomic status (SES) may influence individuals’ fair behavior (Henrich, 2000; Van Dijk et al., 2004), the present study would measure these two variables and take them as control variables in the analysis.
Results
The impact of color on perceived competitiveness
Following the method of Davis (2010), we employed multiple regression analysis with contrast coding to test for multiple groups mean differences in perceived competitiveness. We contrast-coded the Color, using the red condition as the treatment group. In Contrast 1 (C1), we coded red = 1, control = 0, and blue = −1; this contrast examined the differences in perceived competitiveness between the red and control conditions. In Contrast 2 (C2), we coded red = −1, control = −1, and blue = 2; this contrast tested whether the blue condition differed from the red and control conditions. Then, we ran linear regressions with perceived competitiveness as the dependent variable, using C1 and C2 as independent variables, respectively.
As shown in Fig. 2a, the results showed statistically significant effects for both C1 (β = −0.35, SE = 0.13, p = 0.009) and C2 (β = −0.33, SE = 0.08, p < 0.001). More specifically, the significant effect of C1 meant that the perceived competitiveness elicited by the red condition (MRed = 4.64 ± 1.39) was higher than that by the control condition (MControl = 3.92 ± 1.43); the significant effect of C2 suggested that the blue condition (MBlue = 3.29 ± 1.52) was lower than both the red and control conditions. Therefore, these findings supported H1a and H1b.
Mean differences between red, blue, and control conditions in terms of perceived competitiveness (a) and UG offers (b). *p < 0.05, **p < 0.01, ***p < 0.001), the same below.
Additionally, gender, SVO, and SES were also included as control variables. We integrated these variables, along with their respective interactions with C1 and C2, into the model. The results indicated that gender, SVO, and SES showed neither main effects nor interactions with C1 and C2 on perceived competitiveness. When we re-evaluated the model with the inclusion of these control variables, the main results remained consistent. For a comprehensive presentation of these results, please refer to Appendix A.
The impact of color on UG offers
We used the same multiple regression analysis and the same coding to further compare the mean differences in UG offers between multiple color groups. As shown in Fig. 2b, the results also revealed statistically significant effects for both C1 (β = −2.88, SE = 0.96, p = 0.003) and C2 (β = −2.26, SE = 0.55, p < 0.001). The effect of C1 indicated that UG offers in the red condition (MRed = 44.81 ± 10.68) was significantly higher than those in the control condition (MControl = 38.98 ± 9.70); while the effect of C2 indicated that UG offers in the blue condition (MBlue = 35.06 ± 10.91) were significantly lower than those in both the red and control conditions. Therefore, H2a was supported.
The analysis of control variables for gender, SVO, and SES found that SVO had main effects on UG offers (C1: β = 0.62, SE = 0.25, p = 0.013; C2: β = 0.63, SE = 0.24, p = 0.009). Besides, there were no main effects for gender and SES, and there were no interaction effects between gender, SVO, SES, and C1 and C2, respectively. When these control variables were included in the model, our main results remained unchanged. Detailed data can be found in Appendix A.
The mediating analysis of color-induced perceived competitiveness
To determine the mediating mechanism of Color on UG offers, we conducted two separate mediation analyses (PROCESS Model 4; Hayes, 2013) comparing red to control and blue to control, respectively. For each analysis, color served as the independent variable (for analysis 1: control = 0, red = 1; for analysis 2: control = 0, blue = 1), UG offers as the dependent variable, perceived competitiveness as the mediator, and SVO and SES as the covariate. The analyses utilized the bias-corrected bootstrapping method based on 5000 bootstraps and 95% confidence intervals.
The results are shown in Fig. 3. For the analysis 1, red versus control was positively associated with perceived competitiveness (β = 0.74, p < 0.01, 95% CI = [0.25, 1.23], a1), which in turn was positively associated with UG offers (β = 3.58, p < 0.001, 95% CI = [2.47, 4.69], a2). Although red versus control had a direct effect on offers (β = 3.39, p = 0.038, 95% CI = [0.20, 6.58], a3), the indirect effect through perceived competitiveness was also significant (indirect effect = 2.64, 95% CI = [0.79, 4.93]), suggesting that the effect of red on UG offers was partially mediated by perceived competitiveness. For the analysis 2, blue versus control was negatively associated with perceived competitiveness (β = −0.60, p = 0.02, 95% CI = [−1.10, −0.10], b1), which in turn was positively associated with UG offers (β = 3.34, p < 0.001, 95% CI = [2.24, 4.45], b2). In addition, blue versus control had no direct effect on offers (β = −2.04, p = 0.21, 95% CI = [−5.24, 1.17], b3), but the mediating effect by perceived competitiveness was significant (indirect effect = −2.00, 95% CI = [−4.12, −0.28]). To summarize, these findings reveal that the influence of color on UG offers is mediated by perceived competitiveness, thereby providing evidence for H2b.
Control variables are not shown in figure for parsimony. The dashed line represents the insignificant path.
Discussion
Study 1 demonstrated that, in the UG, participants exposed to red color made higher offers compared to those in the control group, whereas those exposed to blue color tended to make lower offers. This color effect was mediated by the color-induced perceived competitiveness. The findings of Study 1 provide greater support that the color effect may be driven by strategic motives. Next, we will introduce the IG in Study 2, to disentangle altruistic motives from strategic motives within proposal behavior, thereby offering deeper insights into how color influences fairness in decision-making.
Study 2
Method
Participants
Based on the calculation of G*power 3.0 (Faul et al., 2007), a total of 356 participants (Mage = 20.46 ± 1.77, Mfemal = 43.98%) were recruited and offered a small compensation for their participation.
Design
Study 2 was a 3 (Color: red vs. blue vs. control) × 2 (Game: UG vs. IG) between-subjects design, with the control group being a colorless condition. Participants played the role of proposers in Study 2 and were randomly assigned to one of the six conditions.
Materials and procedure
Study 2 was conducted in a quiet laboratory, with all stimuli and tasks presented through a computer. Participants were asked to divide 100 Chinese yuan (≈14 USD) in a one-shot UG or IG based on specific conditions that were assigned to them. They were informed that their offers would be presented to responders in a subsequent experiment (which was indeed the case). We manipulated the color condition in the same way as Study 1 (Bagchi and Cheema, 2013; Mehta and Zhu, 2009), that is, by changing the background color of the task. The experimental procedure was similar to Study 1, with participants first reading the experimental instructions, then entering the task and indicating their offers, followed by completing the perceived competitiveness scale that was the same as Study 1 (Murayama and Elliot, 2012; α = 0.92). Finally, participants completed the post-questionnaire, and the experiment ended. All participants were given two rounds of practice trials before the formal experiment began. We also measured their SVO and SES as control variables in the analysis. To encourage genuine performance, an additional reward would be given to 10% of them randomly based on their actual performance.
Results
We adopted the same multiple regression analysis as in Study 1 (Davis, 2010) to examine the interaction effect between Color and Game, as well as the multiple groups mean differences. We set the same contrasts for the color effect as in Study 1 (Contrast 1 (C1): red = −1, control = 0, and blue = 1; Contrast 2 (C2): red = −1, control = −1, and blue =2), and added one contrast for the game effect (Game: UG = −1, IG = 1). C1 was used to compare the mean differences between the red and control conditions, while C2 was used to test whether the blue condition differed from the red and control conditions.
The interaction effect of Color and Game on perceived competitiveness
We first ran two linear regressions with perceived competitiveness as the dependent variable, using C1, Game, and C1 × Game as the independent variables in one regression, and C2, Game, and C2 × Game as the independent variables in the other. The results indicated no significant interaction effects for C1 × Game (β = −0.05, SE = 0.12, p = 0.68) and C2 × Game (β = 0.01, SE = 0.07, p = 0.90), suggesting that the effect of color on perceived competitiveness followed a consistent pattern across both the UG and IG. Further analysis revealed significant effects for both C1 (β = 0.40, SE = 0.12, p = 0.001) and C2 (β = −0.34, SE = 0.07, p < 0.001), respectively, indicating that regardless of UG or IG, the red condition was significantly higher than the control condition, and the blue condition was significantly lower than both the red and control conditions. Mean differences in perceived competitiveness across color groups within each game are presented in Table 1. These results remained consistent when including control variables of gender, SVO, and SES, none of which had main effects or interactions with the primary variables (detailed results are available in Appendix B).
The interaction effect of Color and Game on proposal offers
Next, we applied the same method to run linear regressions again, with the proposal offer as the dependent variable. The results showed no significant effects for C1 (β = −1.85, SE = 1.01, p = 0.068) and C2 (β = −1.05, SE = 0.58, p = 0.071). This indicates that, overall, color does not affect proposal offers when not distinguishing between types of games. However, more importantly, significant interaction effects were observed for C1×Game (β = 2.22, SE = 1.01, p = 0.029) and C2×Game (β = 1.46, SE = 0.58, p = 0.012), suggesting that the influence pattern of color on proposal offers differs between the UG and IG. Therefore, a more detailed analysis of the color effects in UG and IG separately is required.
Regarding the UG, we found significant effect for both C1 (β = −2.78, SE = 1.13, p = 0.015) and C2 (β = −2.26, SE = 0.65, p = 0.001). This indicates that in the UG, offers in the red condition were significantly higher than those in the control condition, while offers in the blue condition were significantly lower than both the red and control conditions. However, regarding the UG, the effects of C1 (β = −0.77, SE = 1.56, p = 0.63) and C2 (β = 0.89, SE = 0.91, p = 0.75) were not significant, suggesting no differences in offers across the red, blue, and control conditions in the IG. The mean differences in proposal offers between color groups are illustrated in Fig. 4. These findings highlight a divergence in color effects between the UG and IG. We obtained results in the UG that were consistent with those of Study 1, whereas, in the IG, we found that color does not affect proposal offers, thus contradicting H3.
Mean differences in proposal offers between red, blue, and control conditions in the UG and IG.
Additionally, we incorporated gender, SVO, and SES into the model to analyze their impact on the color effects. It was found that SVO exhibited main effects in both the UG and IG, while SES showed a main effect only in the UG. Furthermore, SES also interacted with C1 in the UG. Besides, there were no other main effects or interaction effects. These findings suggest that participants’ inherent SVO and SES may interact with color to influence their proposal behavior. Consequently, we controlled for gender, SVO, and SES in the model, and the results observed in this study remained unchanged. Detailed data can be found in Appendix B.
Discussion
In Study 2, regardless of whether it is in the UG or IG, the color red (vs. blue) increased (vs. decreased) perceived competitiveness. However, the influence of color on fair behavior diverged between the UG and IG, with red (vs. blue) increasing (vs. decreasing) UG proposers’ offers, but having no effect on IG proposers’ offers. Given that proposal behavior in the UG blends strategic and altruistic motives, while such behavior in the IG reflects only altruistic motives, the comparison between the two games reveals that the color effect on fair decision-making is more likely explained by strategic motives rather than altruistic motives. In other words, after color induces changes in perceived competitiveness, its impact on fair behavior is not by directly affecting individuals’ altruism, but rather by increasing their expectations of rejection for unfair allocations, thereby prompting them to make higher offers to avoid potential punishment. It is noteworthy that Study 2 also revealed that individuals’ inherent SVO and SES have main effects on their fair behavior. SVO is positively associated with both UG and IG offers, while SES is negatively associated with UG offers. Despite this, only SES showed an interaction with the red versus control in the UG. Thus, in this study, SVO and SES primarily exert a direct impact on proposal behavior and are unlikely to interact significantly with the color effect that this research emphasizes.
General discussion
Researchers have long been intrigued by the impact of colors on human behavior (Elliot and Maier, 2014; Hill and Barton, 2005; Labrecque et al., 2013; Mehta and Zhu, 2009). Through two studies, we extend the influence of color on behavior to the field of fair decision-making. In Study 1, we found that proposers in the UG tended to make higher (vs. lower) offers in the red (vs. blue) condition. Importantly, our findings indicate that this color effect is not directly caused by the color itself but is mediated by the color-induced perceived competitiveness. To the best of our knowledge, Study 1 provides the first empirical evidence of the relationship between colors, specifically red and blue, and fairness in decision-making. However, people’s fairness is driven by both altruistic and strategic motives, and the behavior of proposers in the UG is a mixture of these two motives (Güth and Kocher, 2014). To further disentangle the explanatory roles of altruistic and strategic motives in how color influences fair decision-making, Study 2 extended the investigation by introducing the IG. The results showed that color only affects the proposer’s offer in the UG, but not in the IG (where only altruistic motives exist without strategic motives). This suggests that the color effect observed in Study 1 can be better explained by strategic motives, rather than by altruistic motives. In sum, the two studies collectively reveal the underlying mechanism by which color influences fair decision-making. It suggests that color first changes the proposer’s perception of competitiveness in allocation. This change in perceived competitiveness then affects their expectation of unfair offers being rejected (reflected in strategic rather than altruistic motives), and ultimately results in higher offers in red and lower offers in blue.
Theoretical and practical implications
The primary theoretical contribution of the present study lies in the proposition that color can act as a significant contextual cue that influences fairness in decision-making, with this effect being mediated by perceived competitiveness. The relationship between color and human behavior has long captured the interest of researchers. Previous literature has identified the effects of color on decision-making in areas such as investment decisions (Jiang et al., 2014), risk decisions (Jiang et al., 2021; Mao et al., 2018), and intertemporal choices (Geng et al., 2022). Building on existing research, our study deepens the understanding of color’s influence, particularly in the context of fair decision-making. In addition, while previous studies on fair decision-making have largely focused on how the characteristics of gains (Cochard and Flage, 2024), the nature of tasks (Franzen and Pointner, 2012; Rand et al., 2012), or the traits of decision-makers (Charness and Gneezy, 2008; Van Dijk et al., 2004) influence fair behavior. This study indicates that, apart from these task-related factors, fair decision-making is also affected by external environmental cues, such as the colors red and blue, thus providing a supplementary perspective to the current theory on fair decision-making.
Secondly, the present study contributes to the literature on color and its impact on perceived competitiveness. Existing research has explored the influence of color on competitive performance (Elliot et al., 2007; Hill and Barton, 2005), but there is a gap in understanding its effects on perceived competitiveness. Building upon literature that suggests red can evoke aggression and blue can induce relaxation (Bagchi and Cheema, 2013; Elliot and Maier, 2014), we further investigate the relationship between red versus blue and perceived competitiveness in interpersonal interactions. This study highlights that red can serve as a cue to stimulate a sense of competitiveness, whereas blue acts as a contrasting cue that soothes competitiveness, particularly in the context of resource allocations. These findings, therefore, extend the current understanding of the psychological functions of color and enrich our knowledge of the diverse implicit associations associated with distinct colors.
Thirdly, our study deepens the understanding of how color influences fair decision-making by examining the underlying mechanisms that connect color, perceived competitiveness, and proposers’ behaviors in the UG and the IG. Our findings suggest that the color effect is primarily determined by strategic motives rather than altruistic ones. In other words, the sense of competitiveness induced by the color red strengthens people’s expectations of unfair offers being rejected or resisted, thereby motivating them to act more fairly to avoid potential punishment. Conversely, blue diminishes perceived competitiveness, leading to a contrasting effect along the same pathway. Our study focuses on perceived competitiveness and demonstrates its influence on fair decision-making through its role in strategic motives of fairness rather than altruistic motives. Thus, we also contribute to the theoretical understanding of the interplay between perceived competitiveness and fair decision-making.
In practice, this study provides a subtle yet impactful approach for governments and businesses to nudge people to behave more fairly in cooperation and allocation. Prior research has shown that explicit policies, inclusive of financial incentives or punitive measures, frequently fail to meet their intended goals and might even provoke public resistance or backlash (Cadario and Chandon, 2020). However, the influence of colors, often overlooked as mere background information, can unconsciously shape human behavior (Elliot and Maier, 2012). Thus, by strategically manipulating environmental colors, a more flexible method for promoting equitable behavior can be established. For instance, in situations where fairness needs to be emphasized, such as resource distribution, task delegation, or elections, increasing the presence of red in the environment or highlighting red elements can significantly enhance the sense of fairness among all stakeholders. Additionally, the tactical use of color is both cost-effective and easy to implement. As the platform economy grows, more people engage in economic activities online. By changing the background color of websites, it is possible to better guide behavior in prosocial contexts such as donations and altruistic consumption.
Limitations and future research
The present study has certain limitations. Firstly, there may be alternative explanations for the color effect observed in this study. For example, it is possible that red is associated with caution, prompting proposers to exhibit more balanced and less extreme behavior, which in turn results in fairer allocations in the UG. Nevertheless, the focus of this study is to explain the effect of colors from the perspective of perceived competitiveness. In our model, perceived competitiveness fully mediated the effect of the blue color on UG offers, while partially mediating the effect of the red color on UG offers. This indeed suggests that there may be other parallel factors beyond perceived competitiveness that can explain the effect of the red color.
Secondly, this study only considered a narrow range of colors, specifically red and blue. Throughout previous color studies, red and blue have commonly represented warm and cool colors, respectively (Labrecque et al., 2013). Hence, the findings of this study potentially have some applicability and can be somewhat generalized to other warm or cool colors. However, a more nuanced investigation is required to draw definitive conclusions when examining specific colors.
Thirdly, the examination of the color effects in this study was merely conducted within single-shot games. Future inquiries could broaden the scope of color’s impact to repeated games. In such games, decision-makers could adapt their strategies based on ongoing feedback from their decisions, which may elevate the salience of task-related information in their decision-making processes. This increased focus on the task at hand could, in turn, reduce the relative impact of external contextual cues, such as color. Therefore, it would be valuable for subsequent studies to examine whether the influence of color on fairness persists or diminishes in the dynamics of repeated interactions.
In addition, future research can further explore the following aspects. First, although this study has illustrated that color influences the fair behavior of proposers, it is worth investigating whether color affects the fair behavior and attitudes of responders, along with examining the underlying process and boundaries of such effects. Second, considering the increasing interest in cross-modal correspondence research (Hagtvedt and Brasel, 2016) and previous findings that suggest a better fit between the color red (vs. blue) and fast-tempo (vs. slow-tempo) music (Cho et al., 2019), as well as warm-toned (vs. cool-toned) scents (Kim, 2013), it merits future investigation into whether other sensory modalities, such as auditory and olfactory stimuli, likewise exhibit color-related influences on fair decision-making.
Conclusion
The present study examined the effect of color on fairness in decision-making. The results showed that the color red (vs. blue) could increase (vs. decrease) the offers made by proposers in the UG, and this effect is mediated by color-induced perceived competitiveness. However, color had no effect on offers in the IG. This suggests that the underlying mechanism of the color effect on fairness observed in this study is that color changes the perceived competitiveness in the allocation, which in turn influences fair behavior through proposers’ strategic motives rather than their pure altruism.
Data availability
The raw data and scales of this study are accessible at https://osf.io/u4a96 (Open Science Framework).
References
AL-Ayash A, Kane RT, Smith D, Green-Armytage P (2016) The influence of color on student emotion, heart rate, and performance in Learning Environments. Color Res Appl 41(2):196–205. https://doi.org/10.1002/col.21949
Anderson C, Morrow M (1995) Competitive aggression without interaction: effects of competitive versus cooperative instructions on aggressive behavior in video games. Personal Soc Psychol Bull 21(10):1020–1030. https://doi.org/10.1177/01461672952110003
Aslam M (2006) Are you selling the right colour? A cross‐cultural review of colour as a marketing cue. J Mark Commun 12(1):15–30. https://doi.org/10.1080/13527260500247827
Bagchi R, Cheema A (2013) The effect of red background color on willingness-to-pay: the moderating role of selling mechanism. J Consum Res 39(5):947–960. https://doi.org/10.1086/666466
Barclay P, Stoller B (2014) Local competition sparks concerns for fairness in the ultimatum game. Biol Lett 10(5):20140213. https://doi.org/10.1098/rsbl.2014.0213
Barclay P, Willer R (2006) Partner choice creates competitive altruism in humans. Proc R Soc B: Biol Sci 274(1610):749–753. https://doi.org/10.1098/rspb.2006.0209
Bolton G, Zwick R (1995) Anonymity versus punishment in Ultimatum Bargaining. Games Econ Behav 10(1):95–121. https://doi.org/10.1006/game.1995.1026
Brosnan SF, de Waal FB (2014) Evolution of responses to (un)fairness. Science, 346 (6207). https://doi.org/10.1126/science.1251776
Cadario R, Chandon P (2020) Which healthy eating nudges work best? A meta-analysis of field experiments. Mark Sci 39(3):465–486. https://doi.org/10.1287/mksc.2018.1128
Calvillo DP, Burgeno JN (2015) Cognitive reflection predicts the acceptance of unfair ultimatum game offers. Judgm Decis Mak 10(4):332–341. https://doi.org/10.1017/s1930297500005143
Charness G, Gneezy U (2008) What’s in a name? anonymity and social distance in dictator and ultimatum games. J Econ Behav Organ 68(1):29–35. https://doi.org/10.1016/j.jebo.2008.03.001
Chiang Y-S (2010) Self-interested partner selection can lead to the emergence of fairness. Evol Hum Behav 31(4):265–270. https://doi.org/10.1016/j.evolhumbehav.2010.03.003
Cho CH, Mattila A, Bordi P, Kwon E (2019) It tastes better when Bach meets red: the role of music and Plate Color on food evaluation. Br Food J 122(1):14–25. https://doi.org/10.1108/bfj-02-2018-0100
Cochard F, Flage A (2024) Sharing losses in dictator and ultimatum games: a meta-analysis. J Econ Psychol 102:102713. https://doi.org/10.1016/j.joep.2024.102713
Cornaglia F, Drouvelis M, Masella P (2019) Competition and the role of Group Identity. J Econ Behav Organ 162:136–145. https://doi.org/10.1016/j.jebo.2019.04.022
Crosetto P, Güth W (2021) What are you calling intuitive? subject heterogeneity as a driver of response times in an impunity game. J Econ Psychol 87:102419. https://doi.org/10.1016/j.joep.2021.102419
Cuthill IC, Hunt S, Cleary C, Clark C (1997) Colour bands, dominance, and body mass regulation in male zebra finches (Taeniopygia guttata). Proc R Soc Lond Ser B: Biol Sci 264(1384):1093–1099. https://doi.org/10.1098/rspb.1997.0151
Cutler J, Campbell-Meiklejohn D (2019) A comparative fMRI meta-analysis of altruistic and strategic decisions to give. NeuroImage 184:227–241. https://doi.org/10.1016/j.neuroimage.2018.09.009
Davies E, Fafchamps M (2017) Who gains from competition? The ultimatum game in a labor-market setting in Ghana. Soc Econ. https://doi.org/10.7551/mitpress/9780262035651.003.0003
Davis MJ (2010) Contrast coding in multiple regression analysis: strengths, weaknesses, and utility of popular coding structures. J Data Sci 8(1):61–73. https://doi.org/10.6339/jds.2010.08(1).563
Elliot A, Maier M (2014) Color psychology: effects of perceiving color on psychological functioning in humans. Annu Rev Psychol 65(1):95–120. https://doi.org/10.1146/annurev-psych-010213-115035
Elliot AJ, Maier MA (2012) Color-in-context theory. Adv Exp Soc Psychol, 61–125. https://doi.org/10.1016/b978-0-12-394286-9.00002-0
Elliot AJ, Niesta D (2008) Romantic red: red enhances men’s attraction to women. J Personal Soc Psychol 95(5):1150–1164. https://doi.org/10.1037/0022-3514.95.5.1150
Elliot AJ, Maier MA, Moller AC, Friedman R, Meinhardt J (2007) Color and psychological functioning: the effect of red on performance attainment. J Exp Psychol: Gen 136(1):154–168. https://doi.org/10.1037/0096-3445.136.1.154
Faul F, Erdfelder E, Lang A-G, Buchner A (2007) G*Power 3: a flexible statistical power analysis program for the social, behavioral, and Biomedical Sciences. Behav Res Methods 39(2):175–191. https://doi.org/10.3758/bf03193146
Fehr E, Fischbacher U (2003) The nature of human altruism. Nature 425(6960):785–791. https://doi.org/10.1038/nature02043
Fehr E, Gächter S (2002) Altruistic punishment in humans. Nature 415(6868):137–140. https://doi.org/10.1038/415137a
Fletcher D, Hanton S (2001) The relationship between psychological skills usage and competitive anxiety responses. Psychol Sport Exerc 2(2):89–101. https://doi.org/10.1016/s1469-0292(00)00014-5
Franzen A, Pointner S (2012) Anonymity in the dictator game revisited. J Econ Behav Organ 81(1):74–81. https://doi.org/10.1016/j.jebo.2011.09.005
Geng X, Zhang K, Ma J, Yang H, Chen Z, Li S (2022) Blue, rather than red light can nudge employees to choose delayed but larger wage payment. Environ Behav 54(9–10):1227–1250. https://doi.org/10.1177/00139165231153160
Gorn G, Chattopadhyay A, Sengupta J, Tripathi S (2004) Waiting for the web: how screen color affects time perception. J Mark Res 41(2):215–225. https://doi.org/10.1509/jmkr.41.2.215.28668
Greco C, Esposito A, Cordasco G, Matarazzo O (2024) Reciprocity versus self-interest in a competitive interaction context: an experimental study. Psychol Rep. 127(2):827–850. https://doi.org/10.1177/00332941221129137
Güth W, Kocher M (2014) More than thirty years of ultimatum bargaining experiments: motives, variations, and a survey of the recent literature. J Econ Behav Organ 108:396–409. https://doi.org/10.1016/j.jebo.2014.06.006
Güth W, Schmittberger R, Schwarze B (1982) An experimental analysis of ultimatum bargaining. J Econ Behav Organ 3(4):367–388. https://doi.org/10.1016/0167-2681(82)90011-7
Hayes A (2013) Introduction to mediation, moderation, and conditional process analysis: a regression‐based approach. The Guilford Press, New York
Hagtvedt H, Brasel SA (2016) Cross-modal communication: sound frequency influences consumer responses to color lightness. J Mark Res 53(4):551–562. https://doi.org/10.1509/jmr.14.0414
Henrich J (2000) Does culture matter in economic behavior? Ultimatum game bargaining among the Machiguenga of the Peruvian Amazon. Am Econ Rev 90(4):973–979. https://doi.org/10.1257/aer.90.4.973
Hill R, Barton R (2005) Red enhances human performance in contests. Nature 435(7040):293–293. https://doi.org/10.1038/435293a
Hong X, Xiang Y, Wang Z, Li J, Zou R, Gao P (2024) Contextual modulation of the red-attractiveness effect: Differences in affiliation and competitive settings. Acta Psychol 243:104171. https://doi.org/10.1016/j.actpsy.2024.104171
Jiang F, Lu S, Yao X, Yue X, Au Wtung (2014) Up or down? How culture and color affect judgments. J Behav Decis Mak 27(3):226–234. https://doi.org/10.1002/bdm.1800
Jiang F, Zhang R, Lu S (2021) Red and risk preferences: the effects of culture and individual differences. J Behav Decis Mak 34(5):625–638. https://doi.org/10.1002/bdm.2233
Kim Y-J (2013) Can eyes smell? cross-modal correspondences between color hue-tone and fragrance family. Color Res Appl 38(2):139–156. https://doi.org/10.1002/col.20717
Labrecque LI, Patrick VM, Milne GR (2013) The marketers’ prismatic palette: a review of color research and future directions. Psychol Mark 30(2):187–202. https://doi.org/10.1002/mar.20597
Li O, Xu F, Wang L (2018) Advantageous inequity aversion does not always exist: the role of determining allocations modulates preferences for advantageous inequity. Front Psychol 9. https://doi.org/10.3389/fpsyg.2018.00749
Little A, Hill R (2007) Attribution to red suggests special role in dominance signalling. J Evolut Psychol 5(1):161–168. https://doi.org/10.1556/jep.2007.1008
Madden T, Hewett K, Roth M (2000) Managing images in different cultures: a cross-national study of color meanings and preferences. J Int Mark 8(4):90–107. https://doi.org/10.1509/jimk.8.4.90.19795
Mao T, Yang J, Ru T, Chen Q, Shi H, Zhou J, Zhou G (2018) Does red light induce people to be riskier? Exploring the colored light effect on the balloon analogue risk task (BART). J Environ Psychol 57:73–82. https://doi.org/10.1016/j.jenvp.2018.07.001
Mehta R, Zhu R (Juliet) (2009) Blue or red? Exploring the effect of color on cognitive task performances Science 323(5918):1226–1229. https://doi.org/10.1126/science.1169144
Murayama K, Elliot AJ (2012) The competition–performance relation: a meta-analytic review and test of the opposing processes model of competition and performance. Psychol Bull 138(6):1035–1070. https://doi.org/10.1037/a0028324
Rand DG, Greene JD, Nowak MA (2012) Spontaneous giving and calculated greed. Nature 489(7416):427–430. https://doi.org/10.1038/nature11467
Roth AE, Prasnikar V, Okuno-Fujiwara M, Zamir S (1991) Bargaining and market behavior in Jerusalem, Ljubljana, Pittsburgh, and Tokyo: an experimental study. Am Econ Rev 81(5):1068–1095. https://www.jstor.org/stable/2006907
Salancik GR, Pfeffer J (1978) A social information processing approach to job attitudes and task design. Adm Sci Q 23(2):224. https://doi.org/10.2307/2392563
Sally D, Hill E (2006) The development of interpersonal strategy: autism, theory-of-mind, cooperation and fairness. J Econ Psychol 27(1):73–97. https://doi.org/10.1016/j.joep.2005.06.015
Scheres A, Sanfey A (2006) Individual differences in decision making: drive and reward responsiveness affect strategic bargaining in economic games. Behav Brain Funct 2(1):35. https://doi.org/10.1186/1744-9081-2-35
Setchell JM, Jean Wickings E (2005) Dominance, status signals and coloration in male mandrills (Mandrillus Sphinx). Ethology 111(1):25–50. https://doi.org/10.1111/j.1439-0310.2004.01054.x
Stapel DA, Koomen W (2005) Competition, cooperation, and the effects of others on me. J Personal Soc Psychol 88(6):1029–1038. https://doi.org/10.1037/0022-3514.88.6.1029
Tiedens LZ, Linton S (2001) Judgment under emotional certainty and uncertainty: the effects of specific emotions on information processing. J Personal Soc Psychol 81(6):973–988. 10.1037//0022-3514.81.6.973
Van Dijk E, De Cremer D, Handgraaf MJJ (2004) Social value orientations and the strategic use of fairness in ultimatum bargaining. J Exp Soc Psychol 40(6):697–707. https://doi.org/10.1016/j.jesp.2004.03.002
Van Lange PA, De Bruin EM, Otten W, Joireman JA (1997) Development of prosocial, individualistic, and competitive orientations: theory and preliminary evidence. J Personal Soc Psychol 73(4):733–746. 10.1037//0022-3514.73.4.733
Wiedemann D, Burt D, Hill R, Barton R (2015) Red clothing increases perceived dominance, aggression and anger. Biol Lett 11(5):20150166. https://doi.org/10.1098/rsbl.2015.0166
Wilms L, Oberfeld D (2018) Color and emotion: effects of hue, saturation, and brightness. Psychol Res 82(5):896–914. https://doi.org/10.1007/s00426-017-0880-8
Xu X, Potters J, Suetens S (2020) Cooperative versus competitive interactions and in-group bias. J Econ Behav Organ 179:69–79. https://doi.org/10.1016/j.jebo.2020.08.041
Acknowledgements
This work was supported by the Hangzhou Key Research Base of Philosophy and Social Sciences “Research Center for Innovation and Development of Platform Economy” (No. 24JD024), the Humanities and Social Science Research Project of the Ministry of Education of China (No. 23YJC630086), the National Natural Science Foundation of China (No. 72302072), and the Zhejiang Provincial Philosophy and Social Sciences Planning Project (No. 24NDQN118YBM).
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The first author contributed to Conceptualization, Methodology, Software, Formal analysis, Investigation, Writing—Original Draft, and Supervision. The second author contributed to Software, Formal analysis, and Writing—Review & Editing. The third author contributed to Investigation, Resources, and Writing - Review & Editing. All authors have read and agreed to the published version of the manuscript.
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This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the Alibaba Business School at Hangzhou Normal University (Date January 13, 2023/No. 20230006).
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Li, O., Shi, Y. & Li, K. Red, rather than blue can promote fairness in decision-making. Humanit Soc Sci Commun 12, 94 (2025). https://doi.org/10.1057/s41599-025-04407-9
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DOI: https://doi.org/10.1057/s41599-025-04407-9
