self serving bias research article

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Immune to Situation: The Self-Serving Bias in Unambiguous Contexts

Xiaoyan wang.

1 School of Psychology and Cognitive Science, East China Normal University, Shanghai, China

2 Shanghai Key Laboratory of Magnetic Resonance, Department of Physics, East China Normal University, Shanghai, China

3 Key Laboratory of Brain Functional Genomics, Ministry of Education, Shanghai Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China

Yijie Zheng

Fanzhi a. zhou.

4 Zhejiang Yuying Education Group, Hangzhou, China

5 Shanghai Key Laboratory of Magnetic Resonance, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China

Traditionally, the self-serving bias has been investigated in ambiguous contexts in which participants work on tasks that measure novel abilities before making attributions without clear criteria for success or failure feedback. Prior studies have confirmed that the self-serving bias is pervasive in the general population, yet it varies significantly across situations involving ambiguous contexts. The present study features an unambiguous context encompassing interpersonal events that involved implicit causality (with the “self” as an actor or recipient), the inherent logic of which indicated attribution criteria. The aim of this study was to explore whether there is a self-serving bias in unambiguous contexts and to examine whether it is as sensitive to situation as it has been shown to be in ambiguous contexts. The results showed that, in an unambiguous context, participants exhibited self-serving bias in relation to attribution associated with negative interpersonal events. Additionally, the self-serving bias was greater in the actor condition relative to the recipient condition (Study 1), and this effect was not affected by the level of self-awareness, which was manipulated by the use or otherwise of a camera during the experiment (Study 2). Our findings provide evidence for the existence of the self-serving bias in unambiguous contexts. Moreover, the self-serving bias was shown to be immune to situation in unambiguous contexts, but it did depend on factors associated with the events per se , such as the actor versus recipient role that the self played in interpersonal events.

Introduction

It is thought to be a fundamental need of individuals to try to maintain positive beliefs about themselves ( Heine et al., 1999 ; Mezulis et al., 2004 ; Sedikides and Alicke, 2012 ). These positive beliefs about the self can be manifested through what is known as the “self-serving bias,” which refers to individuals taking responsibility for success but blaming others for failure ( Miller and Ross, 1975 ; Miller, 1976 , 1978 ; Larson, 1977 ; Bradley, 1978 , 1979 ; Sedikides et al., 1998 ; Duval and Silvia, 2002 ; Mezulis et al., 2004 ). Moreover, a self-serving bias is considered by many researchers to be essential for an individual’s mental health and adaptive functions ( Taylor and Brown, 1994 ; Heine et al., 1999 ; Mezulis et al., 2004 ; Sedikides and Alicke, 2012 ).

In previous studies on the self-serving bias, participants were often asked to work on a task, and then were given random “success” or “failure” outcome feedbacks ( Larson, 1977 ; Urban and Witt, 1990 ; Sedikides et al., 1998 ). In most cases, tasks measuring purportedly novel abilities or characteristics were adopted to make the outcome feedbacks more plausible in these studies ( Larson, 1977 ; Sedikides et al., 1998 ; Duval and Silvia, 2002 ). As a result, individuals had no clear clues or objective criteria with which to ascertain responsibility attribution for the outcome. For this reason, the attributional context can be seen as being ambiguous in these previous studies. Indeed, for many years, the self-serving bias has been investigated in such ambiguous contexts. Studies have confirmed that the self-serving bias is pervasive in the general population but that it demonstrates significant variability across age, culture, and situation ( Sedikides et al., 1998 ; Duval and Silvia, 2002 ; Mezulis et al., 2004 ; Coleman, 2011 ; Colonnello and Heinrichs, 2014 ). Other studies’ findings have suggested that individuals manifest a self-serving bias because they wish to enhance or protect their self-esteem, which has been identified as a “self-enhancement” or “self-protection” motivation ( Bradley, 1978 ; Cunningham et al., 1979 ; Sedikides et al., 1998 ). Such motivations have been shown to engender a preference for fostering a positive self-concept ( Duval and Silvia, 2002 ). In addition, it has been posited that people possess a “self-assessment” motivation to seek accurate information about the extent of their abilities and the correctness of their opinions, which can occasionally conflict with one’s self-enhancement/self-protection motivations ( Sedikides, 1993 ; Sedikides and Strube, 1997 ; Duval and Silvia, 2002 ). When there are few objective criteria with which to evaluate the correctness of attribution in an ambiguous context, self-assessment concerns are reduced, thus, conflict between self-enhancement/self-protection and self-assessment motivations tends to be weaker in ambiguous contexts.

Importantly, the self-serving bias can also be measured and manifested in an unambiguous context. At many moments in life, the inherent logic of interpersonal events can give people clues and criteria that they can use to attribute these events to a particular cause or causes, rendering the attributional context unambiguous. Considering the following two descriptions featuring “implicit causality verbs,” (i.e., verbs that carry important implications with regard to which person is perceived as being causally responsible for the described event) ( Garvey and Caramazza, 1974 ; Rudolph and Fõrsterling, 1997 ): “Mary hits Lisa” and “Mary protects Lisa.” Because of the causality implications of the verbs in these descriptions, most people will tend to attribute the former event to “Mary” (i.e., the actor of the event, and the subject of the sentence) and the latter to “Lisa” (i.e., the recipient of the event, and the object of the sentence) ( Caramazza et al., 1977 ; Rudolph and Fõrsterling, 1997 ). The present study features implicit causality events and substitutes “self” for the actor or recipient of the interpersonal event (e.g., “I hit YangLi” or “WangShan hits me”), in order that the self-serving bias could be examined in an unambiguous context. As the implicit causality of interpersonal events may provide attributional criteria, an individual’s self-assessment motivation might activate intensively, and, accordingly, there may be intensive conflicts between the self-enhancement/self-protection and the self-assessment motivations in an unambiguous context. In the present study, we aim to investigate whether the self-serving bias can be sufficiently robust to survive in an unambiguous context, such as people commonly experience in real life. Moreover, the unambiguous context provides a chance to set a conflict condition in which attributional clues and criteria may restrain an individual’s self-enhancement/self-protection motivations, and to investigate the self-serving bias with respect to such conflicts. Studies have shown that one’s self-enhancement/self-protection motivations are dominant among many motives ( Sedikides, 1993 ; Sedikides and Strube, 1997 ). Thus, we predict that there will be a self-serving bias in an unambiguous context.

Previous studies have demonstrated that some situational factors affect the self-serving bias in ambiguous contexts. For example, people’s self-serving biases have been found to be enhanced under the focus of a camera ( Duval and Silvia, 2002 ), and researchers have suggested that self-awareness levels are elevated in this situation ( Scheier and Carver, 1983 ; Govern and Marsch, 2001 ; Silvia and Duval, 2001 ; Duval and Silvia, 2002 ; Carver, 2012 ; Silvia and Phillips, 2013 ). Numerous studies have documented that high self-awareness can be induced through using a camera, a mirror, one’s own voice, mindfulness, the I-priming procedure, and self-face recognition ( Berkowitz, 1987 ; Duval and Silvia, 2002 ; Brown and Ryan, 2003 ; Ma and Han, 2009 , 2010 ; Wiekens and Stapel, 2010 ). Enhanced self-awareness beyond baseline levels can increase people’s positive emotional states and their willingness to help ( Berkowitz, 1987 ; Brown and Ryan, 2003 ). In addition, researchers have argued that an individual can be more aware of the current state of the self with increasing self-awareness, and discriminate the current state from the ideal standard more easily. This discrimination might threaten one’s self-esteem, and in turn led to increased motivation to enhance or protect it ( Duval and Lalwani, 1999 ; Duval and Silvia, 2002 ). Previous studies have discovered that, when making attributions in ambiguous context, one’s self-serving bias may be vulnerable to be influenced by the level of self-awareness ( Silvia and Duval, 2001 ; Duval and Silvia, 2002 ). A question remians unanswered of whether a self-serving bias in an unambiguous context is altered by the level of self-awareness operating in a similar manner as in ambiguous context. In the present study, our second goal is to test the impact of a camera on the self-serving bias in an unambiguous context. Numerous studies have claimed that individuals in a conflict task are motivated to devote their cognitive resources to conflict solving and not to expend these precious resources on features irrelevant to the task itself ( Botvinick, 2007 ; Dignath et al., 2015 ). In an unambiguous context, the inherent logic of the interpersonal events could provide people with clues and criteria that they can use to attribute these events to some cause or causes, activating their self-assessment motivation. People’s self-enhancement/self-protection motivations may conflict intensely with their self-assessment motivation, such that individuals might be motivated to devote cognitive resources to solving the conflict and bringing about self-harmony. In which case, one’s attribution would be barely any different across various situations in an unambiguous context. We anticipate that people’s self-serving bias will be hardly influenced by using a camera or not in an unambiguous attribution context.

To summarize, we conduct two studies to test our hypotheses. In Study 1, we examine the self-serving bias effect in an unambiguous context. Participants are presented with descriptions of self-relevant (wherein the “self” plays the role of an actor or recipient) and other-relevant implicit causality interpersonal events, and are asked to attribute the events to one of two interacting persons. The self-serving bias is measured through the difference between the probability of attribution to the self (self was an actor or recipient) and the probability of attribution to the other as actor or recipient for other-relevant events. In Study 2, we manipulate individual self-awareness levels by using or not using a video camera ( Duval and Silvia, 2002 ) in order to examine its impact on the self-serving bias in an unambiguous context.

In Study 1, we examined the self-serving bias in an unambiguous context. Participants were exposed to an implicit causality disambiguation task ( Caramazza et al., 1977 ; Blankenship and Craig, 2012 ) in which they were presented with descriptions of self-relevant and other-relevant implicit causality interpersonal events and were asked to attribute the events to one of the two interacting persons.

Materials and Methods

Participants.

Twenty-two right-handed volunteers from the university community with normal or corrected-to-normal vision participated in the study (of these, 12 were female, and all were between 19 and 23 years old, M = 20.6, SD = 0.82). Additionally, one participant was excluded because they provided insufficient button responses. All participants gave their informed consent before the test, and they were paid for their participation. This study was approved by the Ethical Committee of East China Normal University.

Materials and Design

Forty Chinese two-character implicit causality verbs—20 of which were positively valenced and 20 negatively valenced—were used in the present study. These verbs were selected from a pretest. Firstly, 162 implicit causality verbs were selected and translated from previous studies ( Garvey and Caramazza, 1974 ; Kasof and Lee, 1993 ; Goikoetxea et al., 2008 ; Ferstl et al., 2011 ). Secondly, 30 participants who did not participate in the formal experiment were presented with 162 sentence fragments in the format “NP1 V NP2 because Pro…,” in which “NP1” denotes the first noun phrase, “NP2” the second noun phrase, “V” refers to the verb, and “Pro” to the pronoun (e.g., “YangLi hits WangShan, because she…”). Then, the participants were asked to give a reason or motive for the action. Their responses were codified by two independent raters, and all of the verbs were found to fall into three types: NP1-biased, NP2-biased, and Indeterminable ( Garvey and Caramazza, 1974 ; Goikoetxea et al., 2008 ; Cozijn et al., 2011 ; Ferstl et al., 2011 ). “NP1-biased” means that the participants agreed in assigning the response to the question to the subject of sentence (NP1); “NP2-biased” denotes that participants agreed in assigning the pronoun to the object of the sentence (NP2); and “indeterminable” signifies that participants did not agree in assigning the pronoun, and neither NP1-biased or NP2-biased verb types predominated ( Garvey and Caramazza, 1974 ). A one-way chi-square test for each verb was calculated separately, testing the null hypothesis of equal expected frequencies across the two categories of bias responses ( Goikoetxea et al., 2008 ). Thus, 51 NP1-biased and 56 NP2-biased verbs were selected according the criteria mentioned above. Thirdly, the emotional valence of each of these implicit causality verbs was evaluated using a 9-point scale of unpleasant-pleasant ratings (1 = unpleasant, 9 = pleasant) from the Chinese Affective Words System ( Wang et al., 2008 ). As a result, 20 Chinese two-character positively (a “pleasant” ratings of more than 6) and 20 negatively (a “pleasant” ratings of less than 3.5) valenced implicit causality verbs were selected. These two sets of verbs differed in valence [positive ( M = 6.56, SE = 0.06), negative ( M = 2.93, SE = 0.03), t (19) = 75.22, p < 0.001] but were alike for arousal [positive: M = 5.33, SE = 0.16, negative: M = 5.47, SE = 0.10, t (19) = 0.80, p = 0.43], familiarity [positive: M = 5.86, SE = 0.09, negative: M = 5.60, SE = 0.08, t (19) = 2.00, p = 0.06], and frequency [positive: M = 22.65, SE = 3.01, negative: M = 22.80, SE = 6.21, t (19) = 0.02, p = 0.98]. Within each set, 10 verbs were NP1-biased and the others were NP2-biased.

These implicit causality verbs were used to construct three kinds of one-sentence interpersonal events. Each sentence comprised one subject, one verb, and one object. For self-relevant events, “self” was assigned as an actor or as a recipient. In the actor condition, “self” was the subject of the sentence, and a Chinese proper name was selected as the object of the sentence (e.g., “I hit YangMing because ______ am/is that kind of person”). In the recipient condition, “self” was the object of the sentence, and a Chinese proper name was selected as the subject of the sentence (e.g., “CaoHua hits me because ______ am/is that kind of person”). For other-relevant events, sentences were written in the third person and contained common Chinese names; these names were randomly placed as the subject or the object of the sentence (e.g., “WangShan hits LiMin because ______ is that kind of person”).

For self-relevant positive and negative events, the probability of attribution to the self (self was an actor or recipient) was calculated. The probability of attribution to an actor or to a recipient for other-relevant events were calculated separately, as the corresponding baselines. The delta values of attribution probability (self–other) were used to evaluate the self-serving bias in specific conditions. The experimental design was a 2 (Role: actor or recipient) × 2 (Valence: positive or negative) within-subject design.

Participants arrived individually and 120 sentences depicting interpersonal events were presented to them randomly via a computer screen. Participants were asked to read the sentence and to fill in the gap therein by selecting one of the two names in the sentence as quickly as possible. The positions of the two names were randomly assigned to the left or right side below the sentence. Participants were asked to press the “F” or “J” on the keyboard if they want to choose the left or right name, respectively. At the end of the process, participants were debriefed and thanked for their participation.

Results and Discussion

Attribution responses.

To examine the self-serving bias, the delta values of attribution probability (self–other) across conditions were calculated. A one-sample t -test revealed that the delta values were significantly lower than zero in negative events [actor: M = -0.30, SE = 0.04, t (21) = -8.70, p < 0.001; recipient: M = -0.15, SE = 0.03, t (21) = -4.86, p < 0.001] but not in positive events [actor: M = -0.05, SE = 0.02, t (21) = -1.96, p = 0.06; recipient: M = -0.05, SE = 0.03, t (21) = -1.63, p = 0.14]. These results suggest that people manifest a self-serving bias in evaluating negative events but not in evaluating positive events.

For the delta values across conditions, a 2 (Role: actor or recipient) × 2 (Valence: positive or negative) repeated measures analysis of variance (ANOVA) revealed the main effects of role [ F (1,21) = 5.65, p = 0.03, η p 2 = 0.21], and valence [ F (1,21) = 27.53, p < 0.001, η p 2 = 0.57]. The Role × Valence interaction was significant [ F (1,21) = 13.78, p = 0.001, η p 2 = 0.40]. See also Figure ​ Figure1 1 . Simple effect analysis revealed that there was greater self-serving bias in the actor relative to the recipient condition in negative events [ F (1,21) = 21.54, p < 0.001, η p 2 = 0.51] but not in positive events [ F (1, 21) = 0, p = 1.0].

Mean delta values (self–other) when the self was an actor or a recipient in positive and in negative interpersonal events ( ∗∗∗ p < 0.001; error bars indicate standard error of the mean) .

Reaction Times

Regarding the reaction times, participants’ attributional responses to the self (when self was an actor or recipient) in self-relevant events and their responses to other (when other was an actor or recipient) in these other-relevant events were calculated. A 2 (Target: self or other) × 2 (Role: actor or recipient) × 2 (Valence: positive or negative) repeated measures ANOVA revealed the main effects of target [ F (1,21) = 41.35, p < 0.001, η p 2 = 0.66] and valence [ F (1,21) = 14.34, p = 0.001, η p 2 = 0.41]. The Target × Valence interaction was significant [ F (1,21) = 12.87, p = 0.002, η p 2 = 0.38]. The Role × Valence interaction was also significant [ F (1,21) = 8.23, p = 0.009, η p 2 = 0.28]. There was no other significant main effect or interactions, all F < 3.61, all p > 0.07. Further simple effect analysis revealed that participants undertook faster responses for self-relevant positive events ( M = 2995 ms, SE = 180) relative to negative events ( M = 3775 ms, SE = 281) [ F (1,21) = 22.41, p < 0.001, η p 2 = 0.52]. There was no significant difference between their response times for other-relevant positive ( M = 3999 ms, SE = 237) and negative events ( M = 4118 ms, SE = 238) [ F (1,21) = 0.79, p = 0.39]. Additionally, participants completed faster responses for evaluating negative events in the actor ( M = 3733 ms, SE = 217) relative to the recipient ( M = 4161 ms, SE = 299) condition [ F (1,21) = 6.52, p = 0.02, η p 2 = 0.24]. There was no significant difference between the actor ( M = 3549 ms, SE = 213) and the recipient ( M = 3446 ms, SE = 209) condition for evaluating positive events [ F (1,21) = 0.75, p = 0.40].

These results suggest that participants are more likely to isolate the self from negative events, indicating there is a self-serving bias present in unambiguous contexts. Additionally, the self-serving bias in the present unambiguous context was greater when participants played the role of an actor relative to a recipient. Moreover, participants completed faster responses in the actor relative to the recipient condition for evaluating negative events, indicating that people may employ less cognitive resources to make attributions, and thus exhibit a relatively intuitive self-serving response in the actor condition.

In Study 2, we explored the effect of self-awareness on the attributional pattern in unambiguous contexts. Self-awareness levels were manipulated through the use or otherwise of a video camera during the experiment ( Alden et al., 1992 ; Duval and Silvia, 2002 ). Attributional patterns were measured using the same procedures as were used in Study 1.

The study’s participants were 48 volunteers from the university community with normal or corrected-to-normal vision (24 of whom were female, and all were between 17 and 28 years old, M = 19.9, SD = 1.84). Each participant was randomly assigned to either a high self-awareness group (25 volunteers) or a low self-awareness group (23 volunteers). All participants gave their informed consent before the study, and they were paid for their participation. This study was approved by the Ethical Committee of East China Normal University.

Participants arrived individually and were each told that the study was part of a research program sponsored by the National Institute for the Study of Attribution. The procedure used was almost identical to that used in Study 1, except that self-awareness was manipulated during the experiment.

Self-awareness manipulation

In the high self-awareness group, a tripod-mounted video camera was placed 80 cm away from the participants. Each was told that the National Institute requested the videotaping of a random sample of subjects, presumably to ensure standardization of testing conditions, and that he/she had been randomly selected for videotaping. In fact, the video would be erased after they completed the experimental task. In the low self-awareness group, the video camera was turned off and faced the wall. Participants were given the same information but were told they had not been randomly chosen for videotaping.

Following this manipulation of their self-awareness, participants completed the same disambiguation task that was used in Study 1. At the end of the task, participants were probed for suspicion and debriefed.

As in Study 1, the delta values (self–other) of attribution probability were calculated to examine the self-serving bias across conditions. A one-sample t -test revealed that, when self-awareness was high, the delta values were significant lower than zero in negative events [actor: M = -0.30, SE = 0.04, t (21) = -6.58, p < 0.001; recipient: M = -0.11, SE = 0.03, t (21) = -3.01, p < 0.001] but not in positive events [actor: M = -0.06, SE = 0.03, t (21) = -1.44, p = 0.16; recipient: M = -0.02, SE = 0.03, t (21) = -0.86, p = 0.40]. Similar results were observed when self-awareness was low. Thus, for positive events, actor ( M = -0.02, SE = 0.03), t (21) = -0.74, p = 0.47; recipient ( M = -0.02, SE = 0.03), t (21) = -0.52, p = 0.61. While, for negative events, actor ( M = -0.28, SE = 0.04), t (21) = -7.07, p < 0.001; recipient ( M = -0.16, SE = 0.04), t (21) = -5.49, p < 0.001. These results indicate that people manifest a self-serving bias in evaluating negative events but not in relation to positive events, irrespective of whether their self-awareness levels are high or low.

The 2 (Role: actor or recipient) × 2 (Valence: positive or negative) × 2 (Self-awareness: high or low) repeated measures ANOVA revealed the main effects of role [ F (1,46) = 13.66, p = 0.001, η p 2 = 0.23] and valence [ F (1,46) = 41.97, p < 0.001, η p 2 = 0.48]. The Role × Valence interaction was significant [ F (1,46) = 9.60, p = 0.003, η p 2 = 0.17]. There was no main effect of self-awareness or interactions between self-awareness and any other variables, all F < 1.37, all p > 0.25. Simple effect analysis revealed that there was greater self-serving bias in the actor relative to the recipient condition in negative events [ F (1,47) = 19.56, p < 0.001, η p 2 = 0.29] but not in positive events [ F (1,47) = 0.42, p = 0.52].

The 2 (Target: self or other) × 2 (Role: actor or recipient) × 2 (Valence: positive or negative) × 2 (Self-awareness: high or low) repeated measure ANOVA revealed the main effects of target [ F (1,46) = 63.56, p < 0.001, η p 2 = 0.58] and valence [ F (1,46) = 5.31, p = 0.03, η p 2 = 0.10]. There was no other significant main effect or interactions, all F < 3.08, all p > 0.09. Pairwise comparisons revealed that participants completed faster responses for positive events ( M = 3145 ms, SE = 114) relative to negative events ( M = 3329 ms, SE = 123), p = 0.03, and participants undertook faster responses for evaluating self-relevant ( M = 2899 ms, SE = 103) relative to other-relevant events ( M = 3575 ms, SE = 133), p < 0.001.

These results replicate the findings from Study 1, demonstrating that participants manifested a self-serving bias. Furthermore, the self-serving bias was found to be greater when participants played the role of an actor relative to that of a recipient. However, the appearance of the self-serving bias in this study’s unambiguous context was not affected by the use or otherwise of a camera.

General Discussion

Our study explored the self-serving bias and the impact of self-awareness on it in unambiguous contexts. We found that participants exhibited a self-serving in relation to negative interpersonal events in an unambiguous context, and that it was greater when the self played the role of an actor compared to that of a recipient. Moreover, this attributional pattern was not affected by the inclusion of a camera in an unambiguous context, but rather was mainly dependent upon factors associated with the events per se , such as the actor or recipient role the self played in the implicit causality interpersonal events.

The self-serving bias had been expounded in connection with taking credit for success (internal attribution of positive events: the “self-enhancing” bias) and with denying responsibility for failure (external attribution for negative events: the “self-protective” bias) ( Cunningham et al., 1979 ; Blackwood et al., 2003 ; Hepper and Sedikides, 2012 ). Our results suggest that, in an unambiguous context, people are more likely to isolate the self from negative events, and manifest only a self-protection bias. Previous studies have argued that striving to enhance a relationship with positive events serves self-enhancement, whereas endeavoring to avoid blame for negative events serves self-protection ( Cunningham et al., 1979 ; Blackwood et al., 2003 ; Alicke and Sedikides, 2009 ; Hepper and Sedikides, 2012 ). Generally, self-enhancement regulates the superordinate need to view oneself positively by making slight adjustments in response to environmental disturbances. Self-protection is, by contrast, an emergency system that operates when self-image is threatened below a particular tolerance point ( Alicke and Sedikides, 2009 ; Hepper and Sedikides, 2012 ). In an unambiguous context, attributional clues and criteria in implicit causality interpersonal events can cause one’s self-assessment motivation to become strongly activated, which promotes the seeking and favoring of information that provides accurate knowledge about the self, rather than flattering one’s self-concept ( Sedikides and Strube, 1997 ; Duval and Silvia, 2002 ). As a result, people manifest a self-protection bias rather than a self-enhancement bias for the very reason that one’s self-protection motivation is more intensive. Alternatively, previous studies have revealed that people do not like those who manifest a self-enhancement bias ( Hoorens, 2011 ). Individuals perceived the target as more immoral, unintelligent, and unfriendly when the target self-enhanced either intentionally or unintentionally, rather than self-presenting accurately ( Lafrenière et al., 2016 ).

Our study also found that, in an unambiguous context, the self-serving bias is immune to situation: the participants’ self-serving bias was not affected by their level of self-awareness, which was manipulated by the use or otherwise of a camera in the specified situation. Numerous studies have claimed that individuals in a conflict task are motivated to devote their cognitive resources to the conflict solving and not to expend these precious resources on features irrelevant to the task itself ( Botvinick, 2007 ; Dignath et al., 2015 ). We posit that, in an unambiguous context, people tend to isolate the self from negative events because of the self-protection motivation. Furthermore, they may also be likely to attribute events to a person recognized by the psychological causality implicit in the unambiguous context because of the self-assessment motivation. Thus, an individual’s self-protection motivation may conflict intensively with his/her self-assessment motivation in an unambiguous context. In such a conflict task, individuals might be motivated to devote cognitive resources to solving the conflict and in order to bring about self-harmony. A further point for consideration is that we did not manipulate the magnitude of the conflict in the unambiguous context. That is, what might happen if we were to reduce the conflicts between the self-enhancement/self-protection and self-assessment motivations in unambiguous contexts? Additionally, previous studies have shown that an individual’s self-serving bias is influenced by using or not using a camera when making attributions in an ambiguous context ( Silvia and Duval, 2001 ; Duval and Silvia, 2002 ), yet we did not replicate the effect of self-awareness on the self-serving bias in our study’s unambiguous context. We expect that there may be different attributional processes between these two attributional contexts. In an ambiguous context, because there are no clear attributional criteria, self-assessment concerns are reduced, an individual’s self-enhancement/self-protection motivations may play an important role in attribution. Conversely, in an unambiguous context, because the attributional criteria are relatively clear, an individual’s self-assessment motivation may activate intensively, and attribution might depend on self-enhancement/self-protection and self-assessment motivations simultaneously. Moreover, people exhibited self-protection bias in our study, indicating that this bias is so intensive that it is not influenced by external criteria, such as the implicit causality information available in an unambiguous context. In addition, in previous studies in which participants were given negative feedback and were asked to make attributions in relation to the feedback, individuals manifested the self-serving bias based on their self-protection motivations, which was enhanced by their increased self-awareness ( Silvia and Duval, 2001 ; Duval and Silvia, 2002 ). On the contrary, the self-protection bias was immune to the level of self-awareness present in our study, suggesting that it would not be heightened significantly. These results also point to the restraining effect of the self-assessment motivation in an unambiguous context. Although the effectiveness of a camera in enhancing self-awareness has been verified in previous studies (e.g., Silvia and Duval, 2001 ; Duval and Silvia, 2002 ), due to the lack of a manipulation check, the present study did not provide direct evidence that the camera enhanced self-awareness. Therefore, caution should be applied when interpreting these findings of the present study, and further research is needed to better understand the effect of self-awareness on the self-serving bias in an unambiguous context.

Noteworthily, of particular interest is our finding that the study’s participants manifested greater self-serving bias when the attributional target took the role of an actor relative to the role of a recipient in an unambiguous context. That is, the self-serving bias was modulated by factors associated with the event itself. In prior research, the self-serving bias has been considered as a heuristic judgment ( Dunning et al., 1989 ; Chambers and Windschitl, 2004 ; Beer and Hughes, 2010 ) that is made more quickly and requires fewer cognitive resources than accurate self-evaluation ( Beer and Hughes, 2010 ). In our study, finding a reduced self-serving bias in the recipient condition suggests that more complicated self-evaluation processes, which are more cognitively demanding than heuristic judgments, are involved in the judgments. This inference is generally consistent with those reported by Wang et al. (2015) , whose neuroimaging results illustrated that dorsal medial prefrontal cortex engagement corresponding to self-evaluation shows greater activity when people take longer reaction time to make less self-serving evaluations in the recipient condition.

In conclusion, the present study provides evidence for the existence of the self-serving bias in unambiguous context. Allowing that people’s self-enhancement/self-protection and self-assessment motivations may conflict intensely, the self-serving bias was immune to a situation in an unambiguous context, and, instead, was mainly dependent upon factors associated with the events per se , such as the actor or recipient role the self played in the interpersonal events.

Ethics Statement

This study was carried out in accordance with the recommendations of the Ethical Committee of East China Normal University with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Ethical Committee of East China Normal University.

Author Contributions

XW, LZ, LL, and XG devised the concept and supervised the study. XW and YZ collected the data. XW, LZ, LL, PS, and XG joined in the interpretation of data. XW, LZ, LL, FZ, and XG carried out the writing of the manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

This research was supported by the National Natural Science Foundation of China [31271090; 71371180]; and the Key Program of the National Social Science Foundation of China [14AZD106].

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The Self-Serving Bias: Definition, Research, and Antidotes

Learn the definition of the self-serving bias and how to overcome it..

Posted January 9, 2013 | Reviewed by Jessica Schrader

The self-serving bias is defined as people's tendency to attribute positive events to their own character but attribute negative events to external factors. It's a common type of cognitive bias that has been extensively studied in social psychology.

Positive event - You get an A for an essay and you attribute it to your own awesomeness (internal attribution).

Negative event - You get a C on an essay and you attribute it to your professor not having explained what they wanted well enough (external attribution).

Depression and the Self-Serving Bias

Sometimes when people are depressed or have low self-esteem , their attribution style is flipped.

They attribute positive events to chance or external help, and attribute negative events to their own character.

If someone is feeling irritable, they might attribute negative events to a combination of internal and external factors, (i.e., "I suck and everybody sucks.").

For example, "I got a C because I'm useless and professors are unfair anyway." Or, another example, "I'm having problems in my relationship because I'm a defective person and because other people are generally untrustworthy."

Overall, research on the self-serving bias and depression suggests that the bias isn't completely flipped in people with depression, but the magnitude of the bias is less than in the general population—it's smaller.

Antidotes to the Self-Serving Bias?

Here are some tips for avoiding the self-serving attribution bias:

• Mindful awareness helps. When you learn about common cognitive biases, you can start to notice yourself doing them, and self-correct.
• Self-compassion is an extremely useful skill for reducing defensiveness and increasing your self-improvement motivation .
• Rumination causes people to think about the causes of problems over and over again, without moving forward. You can use these types of cognitive behavioral therapy techniques for reducing rumination .

Research on the Self-Serving Bias

This 2004 m eta-analysis examined the relationship between the self-serving bias and psychopathology (including depression and anxiety ). The free full text of the article can be found here .

This 2011 study uses a slightly different definition of the self-serving bias to relate it to climate change policy. The definition used here is a bias towards thinking "what benefits you is also fair." Free full text here.

To receive free email updates when Dr. Alice Boyes publishes a new post, sign up at this link .

Alice Boyes, Ph.D., translates principles from Cognitive Behavioral Therapy and social psychology into tips people can use in their everyday lives.

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• Published: 29 March 2018

The effect of result publicity on self-serving attributional bias —— a social comparison perspective

• Shanshan Wen   ORCID: orcid.org/0000-0003-1319-8186 1  

Frontiers of Business Research in China volume  12 , Article number:  7 ( 2018 ) Cite this article

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Self-serving bias suggests that people tend to attribute success to internal factors and attribute failure to external factors (Bradley, J Pers Soc Psychol 36:56–71,1978; Miller and Ross, Psychol Bull 82:213–225,1975). However, the results of the attribution of failure are not always consistent. Some studies have found that people attribute failure to external factors (Snyder, Stephan, & Rosenfileld, 1976 ) and others suggest that people attribute failure to internal factors (Ross et al., J Pers Soc Psychol 29:609–618, 1974 ). I tested self-serving bias in two different contexts in mainland China: in one, test results were public (students had access to each other’s test results) and in the other, test results were private (students only had access to his/her own results). When a context triggers individuals to compare themselves to others, individuals may alter their attribution of failure in order to preserve their self-image and self-esteem. Data were analyzed by repeated measure ANOVA, and the results show that in a public context people tend to attribute failure more to external factors than to themselves. Also, results suggest that people attribute failure less to themselves in a public context than in a private context.

Introduction

Human beings cannot live without motivation. We need a reason when we make a decision or make an evaluation or judgment of our actions. Much research has been done on how people attribute their success or failure to different causes in different contexts. For example, actor/observer differences: people involved in an action (actors) view things differently from people not involved (observers). People’s judgments of attribution are often distorted along those lines (Block & Funder, 1986 ). Kelley & Michela ( 1980 ) examines how people decide whether an internal or an external attribution will be made.

Many researchers have found empirical support for a self-serving attribution bias—attributing success internally and failure externally (Brown & Rogers, 1991 ). More specifically, many studies show consistent results for success attribution—attributing to self (Miller & Ross, 1975 ). However, failure attribution seems a bit more complex. Some studies show external attributions for failure (Snyder, Stephan, & Rosenfileld, 1976 ) while other research establishes internal attributions for failure (Ross, Bierbrauer, & Polly, 1974 ). Duval and Silvia ( 2002 ) study the moderating effects of self-awareness and probability of improvement on success and failure causal attributions. Results show that failure is attributed internally when people can improve and failure is attributed externally when people cannot improve.

Despite the effect of improvement probability, we do not know much about why and how people attribute their failures differently. In this study, I argue that public or private contexts may affect an individual’s attributions for failure and success. In the current working environment, competition is fierce and unavoidable. When people succeed or fail in their work projects, results may be publicly known (people know each other’s results) or may be kept private (people do not know each other’s results). In a public context, knowing other’s results and results being known by others, may easily trigger comparison behavior. In order to preserve their self-esteem, individuals tend to attribute their failure to external factors more than to internal factors. Also, they tend to attribute success to internal factors. In a private context, without the knowledge of their peers’ results and without being known by others, comparisons will not be salient, and individuals may analyze the reasons for their failure in more self-effacing and reflective ways. Therefore, they may tend to attribute failure more to internal factors than they do in public contexts. Two experiments were designed to test the interaction effects of public/private contexts and self-serving bias processes to test the above relationships.

This study contributes to attribution research in the following ways: Firstly, it investigates the possible conditions that would affect self-serving bias, especially for failure attribution, showing that the attribution may alter in different contexts. Secondly, it tries to explain the reasons behind different failure attribution types. Thirdly, it tests these hypothetical relationships in a Chinese context to see whether self-serving bias is generalizable in Chinese culture.

• Self-serving bias

Individuals tend to explain the reasons for the positive or negative outcomes of their behavior in a way that serves their self-interests (Mezulis et al., 2004 ). Self-serving bias refers to a pattern by which individuals attribute positive outcomes to internal factors (e.g., ability, effort) and negative outcome to external factors (e.g., task difficulty, luck) (Miller & Ross, 1975 ). Self-serving bias not only helps individuals to maintain a positive self-evaluation, but also affects individuals’ public image (Bradley, 1978 ). People may use self-serving bias to maintain a socially-desirable public image in order to maintain and strengthen self-esteem. For example, individuals from East Asian cultures may show less self-serving bias when their attributions are public. In East Asian cultures which emphasize collectivism and endorse self-criticism and self-reflection, individuals prefer to present an image of modesty or humility in public (Hu, Zhang & Ran, 2016). More specifically, individuals in Asian cultures may be more self-effacing in their attributions than their western counterparts to manage their impressions on others (Crittenden & Bae, 1994 ). In western cultures which emphasize individualism and self, individuals have a strong need for positive self-regard (Heine & Hamamura, 2007 ). In Mezulis et al.’s meta-analytic review of self-serving bias (2004), they find a significantly different effect size between western and eastern cultures, though people in general tend to attribute success more to internal factors than they do for failure. Therefore, for individuals in East Asian cultures, they engage in self-serving attributions at a similar level to their counterparts in western cultures. However, they prefer to present an image of modesty to the public which may not reflect their true feelings.

Previous research has also studied the effects of age and gender on self-serving bias dynamics. Children 8 to 11 years old and adults above 55 have strong tendencies for self-serving attribution, which may be due to their need for competence and expectations of future success (Mezulis et al., 2004 ; Guo et al., 2011 ). The relationship between gender and self-serving bias is complicated. If tasks are interdependent, men show a stronger self-serving bias than women because they have a stronger desire for success (Campbell & Sedikides, 1999 ).

Self-enhancement and social comparison

The literature suggests that self-enhancement is one of the major causes of self-serving attribution (Sanjuan & Magallares, 2014 ). When a task is perceived as important, individuals tend to attribute success to internal factors because it can greatly increase positive self-evaluations (Von Hippel, Lakin, & Shakarchi, 2005 ).

Festinger ( 1954 ) theorized that human beings have a drive to evaluate their own opinions and abilities through comparison with similar others. The social comparison literature suggests three basic motives underlie social comparison behavior: self-evaluation, self-enhancement, and self-improvement (e.g., Festinger, 1954 ; Suls & Miller, 1977 ; Wills, 1981 ). Individuals with low self-esteem—whose self-concept is particularly unstable or uncertain—are thought to be especially interested in social comparison (Wayment & Taylor, 1995 ). Those who feel their self-concept threatened in particular use self-serving bias as a self-esteem protection strategy (Hu et al., 2016 ).

In this paper, result publicity refers to the context or situation in which the evaluated outcomes of one’s performance or endeavor (individual, team or organization) is known by others (colleagues, family members or social acquaintances) and in which one also knows one’s peers’ evaluated outcomes. When an individual’s performance or test result is known by others and he/she know others’ performance or test results (referred to as the public context), he/she is exposed to a context that is similar to his/her own and where others’ information is available to use in comparison. If their performance feedback or test results are positive, to strengthen one’s self-esteem, individuals are likely to take credit for the success. If the performance feedback or test results are negative, to protect one’s self-esteem, individuals may tend to attribute failure to external factors.

When an individual’s performance or test results are kept private and he/she does not know others’ performance or test results (referred to as the private context), he/she is not exposed to a comparison context. In this situation, an individual’s self-concept is less sensitive to threat than in a public context. Individuals are likely to analyze the causes of their results more objectively. They may make more modest attributions — attributing success to both internal and external factors as well as attributing failure to internal factors and external factors.

More specifically, when facing negative results or failure, individuals more easily feel threatened in an interpersonal comparison context (public context). To protect their self-esteem, individuals tend to attribute failure externally rather than internally. They may feel more responsible for failure in a private context than in a public context.

Based on the above theoretical arguments, I propose that:

Hypothesis 1a . Result publicity (public or private) moderates the self-serving bias process, such that the self-serving bias process is more pronounced in a public context—individuals attribute success more to internal factors than to external factors and attribute failure more to external factors than to internal factors in comparison to individuals in a private context.

Hypothesis 1b . For failure attribution, there is an interaction effect between result publicity (public or private) and attribution type (internal or external), such that in a public context, people attribute failure more to external factors than to themselves, while in a private context, people attribute failure to both internal and external factors.

The whole experiment was separated into two stages. In stage one, participants were asked to take a test on “spatial awareness evaluation (see Additional file 1 )”. After the test, the experimenter collected all the tests and pretended to grade them. At stage two, the experimenter returned a feedback sheet with test results to participants and asked them to take a self-evaluation questionnaire about attribution process.

Participants and procedure

Participants in this study were undergraduate students ( N  = 28; 21 women and 7 men) enrolled in an organizational behavior class in Hong Kong. The average age of participants was 21.5 (ranging from 19 to 25). Most students were from the School of Business, and the rest came from the Science or Psychology Departments. All students volunteered to participate in this study during a normal class session in their organizational behavior classroom.

At stage one, during the first break of the class, I distributed the so-called “spatial awareness” test to each student. Students were told that this research was going to investigate spatial cognition among college students: the ability to make quantitative judgments in three dimensions. This task was adapted from Duval and Silvia’s experiment on self-serving bias (2002). In this two-page paper test, students were asked to visually estimate 10 cuboids’ three dimensions based on the printed pictures. At the beginning of this test, I introduced the research purpose and what was needed for the participants to finish as follows:

This research aims to investigate college students’ spatial awareness. Please focus on the figures below and then write down your quantitative judgments on their three dimensions. You’ll have about 120 s to observe them and write down your answers (estimate the size of the subjects based on these pictures but not the size in reality). After the test, we will provide feedback on your judgments. (Please don’t use rulers or discuss with others).

At the end of this test, students were asked to fill in their names, gender, age, major and other information. About 5 min later, finished tests were collected by the experimenter and participants were told that they would receive a feedback sheet during the second break. The function of this “spatial awareness” test is deception— to hide the real purpose of this experiment. Through this event, the feedback sheet which indicated successful or failing results was designed to make participants feel a real sense of success or failure.

Test results & context manipulation

After all the tests were collected, the organizational behavior course began. The experimenter sat at the last row of the room and pretended to carefully grade the tests. Feedback sheets with bogus test result (success or failure) and exposure type (public or private) were randomly assigned to the 28 students. In other words, these students were randomly assigned to one of the four conditions: a) success and results publicly known; b) success and results kept private; c) failure and results publicly known; d) failure and results kept private. The four conditions were described as follows:

Results for xxxx: Great! Your score ranks in the top 5%! (Sorry! Your score is lower than the average level by 10%.)

You’ve been randomly chosen to be a “ public one” . In order to enhance teaching and understanding of students’ needs on this particular subject, your results (with your name) will be uploaded to Web CT. These results can be seen only by students in this class and will be available for only one week (until April 1st, 2 pm). Also, we can provide you with lecture notes on spatial awareness training if you are interested.☺

(You’ve been randomly chosen to be a “private one” . Your results will be carefully kept for research use and won’t be announced to other students. You can only see your results on Web CT and the data will be available for only one week (until April 1st, 2 pm). Also, we can provide you with lecture notes on spatial awareness training if you are interested.☺

After reading the above information, participants were asked to sign a mock consent form indicating that participants authorized the researcher to use their data and indicated whether they were willing to publish their results and self-evaluation records. Then students turned over the page and finished a self-evaluation form.

Debriefing process

Right after the class, the experimenter sent a debriefing email to all students in the class (irrespective of whether he/she participated in the experiment) revealing the real research purpose of the study—self-serving bias in public or private contexts but not a spatial awareness/cognition test. I also promised the students that all information included in this experiment would be kept confidential and questions or inquiry were welcomed. One week later, no questions were raised by students and some students still indicated that they thought that the experiment was a real test on “spatial awareness”.

Causal attributions for success or failure were measured by two items: “To what extent was your performance on the test due to factors associated with yourself?” “To what extent was your performance on the test due to factors associated with external factors?” Each question was answered on a 7-point scale ranging from 1 ( not at all ) to 7 ( very much ). As a check on the exposure degree manipulation, participants were also asked, “how likely will other students know your results (name, feedback, etc.)?” The question was answered on a 7-point scale anchored by not at all and very likely .

Manipulation check

Participants in the public context felt it was more likely that others would see his/her results ( M  = 4.79, SD  = 1.05) than those in the private context ( M  = 2.71, SD  = 1.68), F (1,26) = 15.248, MSE  = 1.97, p  < 0.05. The results show that the manipulation of context was successful.

Test of hypotheses

To analyze the moderating effect of context, I conducted a 2 (test results: success/failure) × 2 (context: public/private) × 2 (attribution type: internal/external) ANOVA with attribution type as a repeated measure. Results show that there is no three-way interaction and the moderating effect of context is non-significant, F (1, 24) = 0.17, p  > 0.1, which indicates that Hypothesis 1a is rejected; the interaction effect of test results and attribution type is significant, F (1, 24) = 13.58, p  < 0.01 and so is the interaction effect of context and attribution type ( F (1, 24) = 5.39, p  < 0.05). Then a 2 (test results: success/failure) × 2 (attribution type: internal/external) ANOVA with attribution type as a repeated measure was conducted separately in two different contexts. A significant interaction effect is observed between the test results and attribution type in the public context ( F (1, 12) = 7.94, p  < 0.05) and in the private context ( F (1, 12) = 5.68, p  < 0.05). Thus, Hypothesis 1a is not supported.

To test Hypothesis 1b, a 2 (context: public/private) × 2 (attribution type: internal/external) ANOVA (with attribution type as a repeated measure) for failure attribution was conducted. Results indicate that for failure attribution, there is a significant interaction effect of context and attribution type ( F (1, 12 = 13.64, p  < 0.01). Subsequently, paired-sample t -tests were conducted to analyze the simple main effect of within subject factor (attribution type): in the public context, people tend to attribute failure more to external factors ( M  = 5.00, SD  = 0.58) than to themselves ( M  = 3.71, SD  = 0.76), t (6) = − 4.50, p  < 0.01; in the private context, no significant difference is found between internal attribution ( M  = 5.29, SD  = 0.95) and external attribution ( M  = 5.14, SD  = 1.07), which shows that people attribute failure to both themselves and external factors. Thus, Hypothesis 1b is supported (Table  1 ).

The experiment in study 2 comprised two stages as in study 1—“spatial awareness evaluation (see Additional file 1 )” (stage 1) and manipulation of social context in order to test the attribution process (stage 2).

Participants in this study were undergraduate students in a university in southern China ( N  = 89; 43 women and 46 men) enrolled in a principles of management class. The age of participants ranged from 18 to 22. Most students were from the School of Management; the rest of the students came from other schools. All students volunteered to participate in this research during class.

At stage one, during the first break of the class, the experimenter (myself) distributed the “spatial awareness” test (the same test as the one used in study1) to each student. Students were also told that this research was going to investigate spatial cognition among college students: the ability to make quantitative judgments in three dimensions. I also declared that this test had nothing to do with their scores in this course, so that participation was voluntary. Similarly, students were asked to visually estimate three dimensions of 10 cuboids based on printed pictures. At the end of this test, students were asked to fill in their names, gender, age and major. Students had about 5 min to finish the test. Later, finished tests were collected by the experimenter and participants were told that they would receive a feedback sheet in next week’s class. The function of this “spatial awareness” test was also deception— to hide the real purpose of this experiment. Through this event, the feedback sheet which indicated successful or failing results would give participants a sense of success or failure.

After all the tests were collected, the tests were put away and the students were told that the test results would be ready next week. One week later, feedback sheets with bogus test results (success or failure) and exposure type (public or private) were randomly assigned to the 89 students. These students were randomly assigned to one of the four condition: a) success and results publicly known; b) success and results kept private; c) failure and results publicly known; d) failure and results kept private. The four conditions were described as follows:

Results for xxxx: Excellent! Your score is above average! (Sorry! Your score is below average..)

In order to enhance teaching and understanding of students’ needs in this particular subject, your results (with your name) have been chosen to be uploaded to Blackboard. Once uploaded, your results can be seen by your classmates and you can see other students’ results. This information will be available for one week (until 11/28, 5 pm). To thank you for participating, we can provide you some lecture notes on spatial awareness training.☺

(In order to enhance teaching and understanding of students’ needs in this particular subject, your results (with your name) will be uploaded to Blackboard. Your results will only be available to yourself and you will not be able to see other students’ result. This information will be available for one week (until 11/28, 5 pm). To thank you for participating, we can provide you some lecture notes on spatial awareness training.☺

After reading the above information, participants were asked to turn over the page and finish a self-evaluation form about their attribution for their success or failure in this test.

Debriefing process. Right after the students submitted their self-evaluation forms, I explained the real research purpose of the study to the students—self-serving bias in public or private contexts as opposed to a spatial awareness/cognition test. I also told the students that all information included in this experiment would be kept confidential and questions or inquiry were welcomed.

Measures. Causal attributions for success or failure were measured separately by three items: e.g., “To what extent was your performance on the test due to factors associated with yourself?” “To what extent was your performance on the test due to factors associated with external factors?” Each question was answered on a 5-point scale ranging from 1 ( not at all ) to 5 ( very much ). As a check on the exposure degree manipulation, participants were also asked, “How likely is it that other students know your results (name, feedback, etc.)?” The question was answered on a 5-point scale anchored by not at all and very likely .

Participants in the public context felt it was more likely that others would see his/her results ( M  = 3.86, SD  = 0.71.) than those did in the private context ( M  = 2.11, SD  = 1.12), F (1, 87) = 7.30, p  < 0.001). The results show the manipulation of context was successful.

To analyze the moderating effect of context, I conducted a 2 (test results: success/failure) × 2 (context: public/private) × 2 (attribution type: internal/external) ANOVA with attribution type as a repeated measure. Results show that there is no three-way interaction, and the moderating effect of context is non-significant, F (1, 85) = 3.49, p  > 0.05), which indicates that Hypothesis 1a is not supported in study 2; the interaction effect of test results and attribution type is significant, F (1, 85) = 110.82, p  < 0.001 and so is the interaction effect of context and attribution type ( F (1, 85) = 6.84, p  < 0.05). Then a 2 (test results: success/failure) × 2 (attribution type: internal/external) ANOVA with attribution type as a repeated measure was conducted separately in two different contexts. In this case, there is a significant interaction effect of test results and attribution type in the public context ( F (1, 41) = 72.39, p  < 0.001) and in the private context ( F (1, 44) = 39.79, p  < 0.001).

To test Hypothesis 1b, a 2 (context: public/private) × 2 (attribution type: internal/external) ANOVA (with attribution type as a repeated measure) for failure attribution was conducted. Results indicate that for failure attribution, there is a significant interaction effect of context and attribution type ( F (1, 42) = 19.59, p  < 0.001). Subsequently, paired-sample t -tests were conducted to analyze the simple main effect of within subject factor (attribution type): in the public context, people tend to attribute failure more to external factors ( M  = 3.78, SD  = 0.46) than to themselves ( M  = 2.80, SD  = 0.44), t (21) = 10.08, p  < 0.001; in the private context, no significant difference was found between internal attribution ( M  = 2.97, SD  = 0.65) and external attribution ( M  = 3.22, SD  = 0.64), which shows that people attribute failure to both themselves and external factors in a private context. Thus, Hypothesis 1b is supported in study 2 (Table  2 ).

Theoretical implications

In recent years, self-serving bias has attracted more and more attention from management scholars. We can see that it has been examined in different areas of management research such as leadership (Martinko, Harvey & Douglas, 2007 ) and entrepreneurship (Rogoff, Lee & Suh, 2004 ). Self-serving bias is a robust phenomena that can be observed in people’s daily lives and work. More importantly, it can affect individuals’ cognition and behavior in a substantial way, producing counterproductive work behavior (Johns & Xie, 1998), depression (Brown & Siegel, 1988 ), etc. This study aims to explore in certain social contexts how individuals attribute their success and failure, and to test the influence of context on self-serving bias. I tested the relationship of self-serving bias to causal attribution in two different contexts (public and private). The results show that contexts (public or private) could serve as one possible reason for inconsistent findings of failure attribution. Failure may be attributed more externally in a public context and attributed to internal or external factors at roughly the same level in a private context.

In summary, this paper contributes to the research on attribution in the following ways. Firstly, I did not find three-way interaction effects between social context (public or private), test results (success or failure) and attribution type (internal and external), indicating that the self-serving process could be observed in both public and private social contexts. Secondly, the results suggest that individuals tend to attribute failure more to external factors than to themselves in a public context, that is, they attribute failure less to themselves in a public context than in a private context. Integrating these results with a social comparison framework, I argue that individuals have a stronger desire to protect their self-esteem when facing failure in conditions of interpersonal comparison. Thirdly, conducted in a Chinese context this study provides some empirical support to the self-serving bias research in Chinese samples. Self-serving bias is not specific to western cultures but also exists in Chinese culture. More specifically, the results reveal that individuals may explain the reasons for failure differently in different social contexts in Chinese culture.

Practical implications

Based on the results, managers need to pay attention to the privacy of employees’ performance evaluation results. According to the findings, if the performance results of all employees are publicly known, for poor performers, they may tend to attribute failure or negative feedback to external factors rather than to internal factors. They are more likely to search for excuses for their failure and not think of their own responsibility for negative outcomes. This would be detrimental for employees’ subsequent performance and organizational effectiveness. Moreover, when performance results are made public, employees may become more aware of other employees’ performance, and develop a stronger tendency for comparison and competition.

For good performers, if results are kept public or private, it seems that their explanation for their success remains the same. Whether or not to make employees’ performance or project results publicly known depends on the management’s purpose and organization culture. If the company culture endorses competition, then it may consider publicizing employee’s results; if the organization emphasizes harmony and teamwork, then keeping results private would be more beneficial.

Limitations and future research

There are several limitations to this study: Firstly, the hypotheses were tested in an experimental design and the participants were business college students. Whether the results can be generalized to a work context needs more empirical evidence. In the future, researchers can collect data from employees and supervisors in real work settings. Secondly, the data was only collected in a Chinese cultural context so there was no comparison between Chinese and western approaches to self-serving bias. In the future, a study that includes people from diverse cultural backgrounds may produce more detailed results. Thirdly, this study only tested the effect of particular social contexts (results were public or private) on self-serving bias. In the future, researchers can explore more social contexts that may influence an individual’s self-serving bias, e.g., examining attribution in a public context, in different team contexts, or task characteristics.

Future research can also study the effect of face in the Chinese context (Shi, Ichiro & Jin, 2011 ; Shi, Kuang & Yang, 2017 ) to explain how test publicity affects individuals’ self-serving attributional bias. The relevance of results to an individuals’ performance evaluation can be another important factor that influences the effect of test publicity. Team climate (trust, safety) and perceived leader support may also affect how people interpret their public failures. In entrepreneurship research, scholars can also study how people react to entrepreneurial failures differently when the enterprise is well-known or famous. In a service-related context, how employees attribute their service failure and the related effect on their win-back management may be examined (Tang, Chou & Chen, 2008 ; Tang et al., 2010 ).

To conclude, self-serving bias can be observed in Chinese culture as it has been in western cultures. Individuals tend to blame external factors for their failure when the failure is known by others and the individual is aware of others’ results. Individuals blame themselves for failure when the context is private rather than when it is public.

Abbreviations

Analysis of Variance

Standard Deviation

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Acknowledgements

I would like to thank Prof. Dora C. Lau for the support during data collection. I also appreciate Prof. Jessica Kwong and Prof. Lynda J. Song for their constructive comments for this paper.

This study was supported by a grant from Shenzhen University (Young scholars’ supporting funding, project no. 17QNFC21–85202).(深圳大学人文社会科学青年教师扶持项目:17QNFC21–85202).

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Wen, S. The effect of result publicity on self-serving attributional bias —— a social comparison perspective. Front. Bus. Res. China 12 , 7 (2018). https://doi.org/10.1186/s11782-018-0028-8

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Self-serving bias in fairness perception: Allowing allocators to allocate unfairly

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In resource-allocation situations, the allocators often make advantageous unfair allocations intentionally, which may threaten their moral self. We propose that allocators self-servingly interpret these allocations as less unfair, which potentially lessens threat to their moral self, allowing them allocate unfairly. In a hypothetical dictator game (Experiment 1, 3 and 4), a real dictator game (Experiment 2 and 5) and a hypothetical ultimatum game (Experiment 3), we compared the fairness perceptions of allocators with those of recipients (Experiment 1 and 2) and a control group (Experiment 3 and 4), both before (Experiment 1–4) and after (Experiment 5) the allocations. The studies consistently found that the allocators perceived the possible advantageous unfair allocations as less unfair, and these fairness perceptions further predicted their allocations. We highlight the psychological mechanism, specifically the self-serving bias in fairness perception that may lessen the anticipated threat to the allocators’ moral self, allowing them to allocate unfairly.

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This study was funded by the National Natural Science Foundation of China [72271094] and the Ministry of education of Humanities and Social Science project [22YJA190008].

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Wang, X., Liu, Y. Self-serving bias in fairness perception: Allowing allocators to allocate unfairly. Curr Psychol 43 , 6384–6395 (2024). https://doi.org/10.1007/s12144-023-04819-3

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ORIGINAL RESEARCH article

Self-serving bias in performance goal achievement appraisals: evidence from long-distance runners.

• 1 Department of Business and Economics, Utica College, Utica, NY, United States
• 2 School of Marketing, Entrepreneurship, Sport Management, Hospitality and Tourism, Western Carolina University, Cullowhee, NC, United States
• 3 Department of Tourism, Recreation and Sport Management, University of Florida, Gainesville, FL, United States
• 4 School of Sport, Tourism and Hospitality Management, Temple University, Philadelphia, PA, United States
• 5 Department of Sport Management, Florida State University, Tallahassee, FL, United States
• 6 Department of Health, Exercise Science, and Recreation Management, University of Mississippi, Oxford, MS, United States

While working with a long-distance running event organizer, the authors of this study observed considerable differences between event participants’ official finish time (i.e., bib time) and their self-reported finish time in the post-event survey. Drawing on the notion of self-serving bias, we aim to explore the source of this disparity and how such psychological bias influences participants’ event experience at long-distance running events. Using evidence of 1,320 marathon runners, we demonstrated how people are more likely to be subject to a biased self-assessment contingent upon achieving their best finish time at the event. The study samples were split into record-high-achieved and record-high-missed groups, and the self-serving biases of each group were explored. Results from the t -test comparing record-high-achieved and -missed groups showed that runners in the record-high-missed group were significantly more likely to report a positively biased finish time than runners in the record-high-achieved group ( p < 0.01). Additionally, results from logistic regression showed that as runners missed their best finish time by a wider margin, the probability of reporting a positively biased incorrect finish time increased. Lastly, we conducted an additional t -test and revealed that runners who are subject to self-serving bias showed a lower level of overall event satisfaction. The current study suggests one way to bypass the adverse effects of participant sport event participants’ worse-than-expected athletic performance. We specifically suggest that the event organizers target runners who had worse-than-expected performance and make extra efforts on non-race service attributes (e.g., finish line experience, rest and recovery area, and transportation after the event) because these runners are more likely to be unsatisfied with the event.

Introduction

Competition is often considered a key element of sports ( Anderson-Butcher et al., 2014 ). The outcome of competition in sport contexts can greatly influence fans’ and recreational athletes’ experiences ( Yoshida and James, 2011 ; Du et al., 2015 ). For instance, competition outcomes in a spectator sport services context—who wins and who loses—have been identified as a core element of service quality evaluation ( Greenwell et al., 2002 ; Theodorakis et al., 2013 ). Scholars studying participant sport services have likewise found that athletic performance in participant sport events is a critical antecedent of participants’ evaluations of their overall event experiences ( Du et al., 2015 ; Hyun and Jordan, 2020 ). For instance, failing to achieve a pre-determined athletic performance goal in a long-distance running event results in negative perceptions of the entire event ( Hyun and Jordan, 2020 ). Conversely, runners who achieve their pre-determined goals tend to be more satisfied with the entirety of the event journey even if other service aspects were disappointing ( Du et al., 2015 ).

To better understand effective managerial responses to long-distance running event participants’ behavior, one would be remiss to simply conclude that undesirable competition outcomes will lead to lower levels of satisfaction (e.g., if sport participants cannot achieve their athletic goals in a participant sport event, whey will not be satisfied with the event). If this were the case, there would be little investment that managers can make to change the experience of participants. However, when people encounter negative outcomes, they do not remain unsatisfied but instead seek to alleviate negative emotions—or mitigate the experiences tied to negative outcomes—by using various coping strategies ( Snyder et al., 1986 ; Poczwardowski and Conroy, 2002 ). In better understanding how to identify these strategies, managers may better be able to understand how to interpret and act upon event feedback from participants.

Per attribution theory ( Kelley, 1973 ), self-serving bias is one of the effective coping strategies that can protect one’s self-esteem and alleviate negative emotions from undesirable outcomes ( Kashima and Triandis, 1986 ; Zhang et al., 2018 ). People tend to take credit for positive outcomes while attributing negative outcomes to external factors; therefore, people are less likely to be satisfied with external factors when the outcome is negative or less than their expectations. For instance, collegiate Division 1 wrestlers tend to attribute their win to more internally caused and internally controlled factors (e.g., one’s own athletic ability) compared to losers ( De Michele et al., 1998 ). Self-serving bias is also observed in long-distance running event settings: Runners tend to over-credit their ability in a rosy manner after the event even if they fail to meet their preset time goal ( Lemm and Wirtz, 2013 ). In addition, runners who are not satisfied with their athletic performance are also likely to be unsatisfied with the overall event ( Du et al., 2015 ; Hyun and Jordan, 2020 ).

The purpose of this study is to understand how long-distance running event participants appraise their own athletic performance after the event and how runners with undesirable athletic performance cope with dissatisfaction with their performance. In particular, while working with a long-distance running event organizer for their participant experience analysis, the authors observed considerable differences between runners’ official finish time (i.e., bib time) and their self-reported finish time in the post-event survey. Therefore, in the current study, drawing on the concept of self-serving bias, we seek to answer the following research question: what drives the difference between official finish time and self-reported finish time of long-distance running event participants, and what implications do this long-distance runners’ behavior have for participant sport event organizations?

The survey utilized in this study was distributed to the potential respondents with a clear note that the research team was collaborating with the marathon event organization to understand event participants’ behavior. As such, the respondents were very likely to know that the survey administrators have information about their official finish time (i.e., bib time), while many previous studies in the similar contexts were based on surveys that respondents answered survey questions with being unsure whether the survey administrators had the objective measure of the questions in the surveys (e.g., Gil and Mora, 2011 ; Markle et al., 2018 ; Flegal et al., 2019 ). It would be a strength of the current study that this is a clear test of self-serving bias because it examines whether runners misreport their finish time (i.e., self-serving bias) although they might know that the survey administrators could have information about their official time performance. As such, it would be a novel and effective approach to test self-serving bias in the context of participant sport events where the athletic performance (i.e., marathon finish time) is very important to participants, but there are no prominent rewards of successful performance.

Performance Appraisal in Participant Sport Events and Coping Behavior

Irrespective of spectator or participant sport contexts, competition appraisals, often in the forms of athletic performance assessment, are contingent upon an individual’s ability to set realistic and rational expectations. In particular, a marathon is a highly goal-directed sport event for amateur runners ( Lemm and Wirtz, 2013 ). For instance, runners participating in a long-distance running event often cite goal achievement as a motivation; they try to run faster and beat a specific time goal, and improve their record-high finish time ( Funk et al., 2011 ; Lemm and Wirtz, 2013 ). As such, in a long-distance running event, participants often appraise their athletic performance using a certain finish time as a reference point ( Markle et al., 2018 ). The achievement of this referenced finish time has a great effect on a runner’s experience with an event. Many sport management studies in the domain of participant sport have discussed the appraisal of athletic performance goal achievement and its ramifications for contestants’ experience at participant sport events (e.g., perceived service quality, event satisfaction, and re-participation intention; Lemm and Wirtz, 2013 ; Du et al., 2015 ; Markle et al., 2018 ; Hyun and Jordan, 2020 ).

In particular, a marathon is a race against the clock for amateur runners participating in a long-distance running event. Amateur runners care little about their ranking among participants; rather, they pay special attention to their best finish time (i.e., personal improvement referred in the concept of mastery goal; Adie et al., 2008 ). In other words, a runner’s best finish time is very likely to be a strong self-referential criterion (i.e., reference point) of their athletic performance appraisal in a long-distance running event. Interestingly, prospect theory suggests that the marginal utility of fulfilling the reference point as opposed to performance failure might not follow a linear continuum ( Kahneman and Tversky, 1979 ). That is, the evaluation of goal achievement is characterized by a reference-dependent S-shaped value function where there is a huge non-linear gap in utility between people whose performance is just below a referenced finish time (i.e., goal missed) and people whose performance is just above a reference point (i.e., goal achieved; Allen et al., 2016 ).

Effects of Athletic Performance in Long-Distance Running Events

According to Du et al. (2015) , achieving an athletic performance goal (i.e., breaking a referenced finish time) in participant sport events are sometimes strong enough to compensate for negative experiences involving service provider–generated factors; people with a high level of goal achievement maintained high overall event satisfaction regardless of other factors. For instance, service quality, which is often suggested as one of the most important predictors of consumers’ satisfaction with service products, became powerless in predicting event satisfaction for runners who achieved their athletic performance goals. By contrast, service quality and overall event satisfaction had a strong linear relationship for runners who missed their pre-determined athletic goals: as service quality evaluations increased, so did overall event satisfaction ( Du et al., 2015 ). This finding offers critical insight into the role of athletic goal achievement in participant sport event contexts: athletic goal achievement is such a pivotal aspect of the participant sport event experience that it exerts a strong impact on runners’ overall experience with a participant sport event and may determine runners’ post-event evaluation of the event and behavior.

Self-Serving Bias in Coping With Performance Failure

Self-serving bias.

Self-serving bias is derived from a large body of evidence from behavioral economics and cognitive psychology ( Gilovich et al., 2002 ), which refers to humans’ tendency to attribute positive outcomes to their own abilities but ascribe negative outcomes to external factors ( Campbell and Sedikides, 1999 ). This psychological assessment can be triggered by the notion of cognitive dissonance in which individuals subconsciously and inadvertently suppress noise that conflicts with pre-determined expectations of athletic performance ( Kelley, 1973 ; Campbell and Sedikides, 1999 ; Gilovich et al., 2002 ). Self-serving bias is often observed in the context where an individual’s self-esteem is being threatened by negative outcomes of one’s effort ( Blaine and Crocker, 1993 ), and this is what usually happens in a marathon event when a runner’s finish time is worse than their expectations. For example, in the context of a marathon event, it has been shown that runners’ worse-than-expected finish time led to many negative consequences, such as a decreased level of event satisfaction, re-participation intention, and future exercise intention ( Lemm and Wirtz, 2013 ; Du et al., 2015 ; Hyun and Jordan, 2020 ). As achieving a good time performance is one of the critical factors affecting runners’ post-event perception and behavior, runners whose finish time is worse than their best time are likely to be affected by self-serving bias.

Self-serving bias can be exhibited in many different forms of behavior, and one of which is conscious or unconscious dishonest behavior ( Mazar and Ariely, 2006 ). As per the theory of self-deception ( Trivers, 2000 ), self-serving bias (i.e., a strong desire to improve or maintain self-esteem) could lead to dishonest behavior even when there are no external benefits of being dishonest; self-deception represents “a biased, self-serving information flow within an individual—that is, an active but unconscious misrepresentation of reality to the conscious mind” ( Mazar and Ariely, 2006 , p. 122). Self-deception allows individuals to maintain a positive sense of self in the wake of moments of confusion, frustration, dissatisfaction, or other emotions that arise from negative outcomes. As noted above, participants of long-distance running events would feel a deep frustration when their athletic performance is worse than their expectations. To avoid or alleviate this frustration and maintain their self-esteem, they would have self-serving bias (i.e., ascribing their failure to external factors), which would lead them to have a biased, self-serving information about their athletic performance. As such, we hypothesize that long-distance runners whose finish time is worse than their best time performance will be likely to report a positively biased finish time (i.e., self-reported finish time that is faster than official finish time)—even in a situation with no apparent benefits of being dishonest, such as an anonymized survey.

H 1 : Long-distance runners whose official finish time is slower than their best finish time will exhibit a stronger self-serving bias compared to runners whose official finish time is faster than their best finish time.

H 1 a : The former will more frequently exhibit a self-serving bias than the latter.

H 1 b : The former will more strongly exhibit a self-serving bias than the latter.

H 2 : As the extent to which a long-distance running event participant’s time performance falls short of their best finish time increases, the probability of them reporting a positively biased finish time will increase.

At the same time, long-distance runners who are subject to self-serving bias will be less likely to be satisfied with the overall event because they tend to blame the external factors and event environment for their failure. This tendency would be particularly salient among runners who reported a positively biased self-reported finish time because self-deception is evidence that they were actively utilizing self-serving bias as a coping strategy to avoid any negative emotion from the failure. Runners who are subject to self-serving bias would believe that the event environment was the cause of their poor athletic performance; for example, they might think that the course was too difficult, weather was not supportive, water station was inconvenient, time markers were hard to read, there were too many participants, or shoes were uncomfortable. As such, we hypothesize that athletes who report positively biased incorrect time performance in a post-event anonymous survey (i.e., those who actively used a coping strategy to protect their self-esteem due to self-serving bias) will have a low level of overall event satisfaction compared to runners who did not use a coping strategy (i.e., those who reported a correct finish time in a post-event anonymous survey).

H 3 : Long-distance runners whose self-reported finish time is positively biased (i.e., better than their official finish time) will have a significantly lower level of overall event satisfaction compared to runners who correctly reported their finish time in the post-event anonymous survey.

Materials and Methods

Study participants.

To test the proposed hypotheses, we conducted a series of statistical analyses based on the official time performance database and post-event survey from a long-distance running event held in the southern United States in 2016. The event included 23,001 participants among full marathon, half marathon, and 5K runners. Among them, 1,320 participated in the current study. Demographically, 44.17% of the current sample were women, 46.82% were Hispanic, 44.24% were Caucasian, 84.24% held at least a 4-year college degree, and 53.41% earned an annual household income greater than $80,000. Athletes’ average age was 40.39 ( SD = 10.88), with a median age of 40. We also compared survey respondents’ age and gender to those of all registered runners. The average age of all event participants was 39.52 ( SD = 10.78) with a median age of 39; 49.30% were women. Therefore, survey respondents represented the entire sample well in terms of age and gender, despite a response rate of 15.56%. Sample characteristics are summarized in Table 1 .

Table 1. Sample characteristics.

The data were collected from three sources. First, when registering for the event, participants were required to provide their best finish time with the purpose of assigning an appropriate starting corral. Second, every participant’s official finish time was measured by a digitalized system (i.e., bib time) by the event organizer. Third, a post-event survey was emailed to all participants a week after the event using their email addresses in the event organizer’s race registration database. The post-event survey was designed to measure long-distance running event participants’ athletic performance appraisals and event satisfaction; therefore, the survey included questions about their race finish time, event satisfaction, and a group of control variables (i.e., running involvement, past running experience, intensity and frequency of daily exercise, and demographics; see Table 2 ).

Table 2. Post-event survey measurement items.

Among the 23,001 participants, 3,579 completed the survey (response rate: 15.56%). After the survey data were collected, respondents’ best finish time and official finish time were added to the dataset. 5K runners were excluded from the dataset because shorter distance runners are likely to be inexperienced runners and have a lower commitment to running compared to half and full marathon participants ( Funk et al., 2011 ), resulting in being less likely to care about their finish time. In addition, seasoned runners who are participating in half or full marathon often participate in 5K as a rehearsal (5K is usually held a day before half/full marathon). In this event, approximately 53.8% of 5K runners also participated in half/full marathon. Also, runners who reported that finish time is not of their interest (i.e., no finish time goal) were excluded from the dataset. Ultimately, 1,320 survey responses were matched based on valid best finish time in the race registration, a self-reported finish time in the survey responses, and an official finish time in the performance database. The data collected from the same event but in a different year were used by the research team in an already published study. In the current study, we investigated whether there were any repeat participants from our prior dataset. We found that 9.9% of respondents in this study were also included in our previous data. These respondents were retained in the present dataset because the purpose of this study is distinct from our earlier work ( Fine and Kurdek, 1994 ).

Experimental Parameters

Self-reported finish time was measured in the post-event survey by asking “What was your actual time for the event?” Overall event satisfaction was assessed using a 3-item construct adapted from Oliver (1980) , scored on a 7-point Likert scale; for instance, “I was satisfied with my decision to participate in this event” (1 = strongly disagree , 7 = strongly agree ). Then, the average score on the three items was calculated to analyze the data. Athletic performance was measured by comparing participants’ referenced finish time (i.e., the best finish time in the past races) and official finish time recorded by the digitalized system ( Du et al., 2015 ; Markle et al., 2018 ). The difference between the two finish times was calculated by subtracting each participant’s official finish time from their best finish time. Self-serving bias was evaluated by the discrepancy between the self-reported ability of oneself or achievement and objectively measured performance in a certain task ( Alicke et al., 1995 ; Trivers, 2000 ; Mazar and Ariely, 2006 ). Specifically, in the current study, participants’ self-reported finish time and official finish time (i.e., bib time) were compared, and the magnitude of self-serving bias was calculated by subtracting each participant’s self-reported finish time from their official finish time. For example, if a runner’s official finish time was 1 h 50 min and their self-reported finish time was 1 h 40 min, then the magnitude of self-serving bias was 10 min.

After data cleaning, two dummy variables were created: (1) record-high-achieved and record-high-missed groups and (2) biased and unbiased groups. First, based on the athletic performance measure, study participants were classified into either the record-high-achieved or record-high-missed group. Specifically, if the measure of athletic performance was positive (i.e., the official finish time was faster than the best finish time), then a runner was included in the record-high-achieved group. Conversely, if the gap between best finish time and official finish time (i.e., athletic performance measure) was negative (i.e., the official finish time was slower than the best finish time), runners were categorized into the record-high-missed group. Ultimately, 635 runners fell into the record-high-achieved group, and 685 fell into the record-high-missed group.

Second, respondents were classified into either the biased or unbiased group based on the self-serving bias measure (i.e., the gap between self-reported time performance and official time performance). If the self-serving bias measure was greater than 59 s (i.e., self-reported time was faster than official finish time by more than 59 s), a runner was deemed as having misreported their time performance and was placed in the biased group. A difference of less than 1 min was not considered deception because self-reported finish time was collected in only hour(s) and minute(s), whereas official finish times included second(s), and marathon event participants largely tended to ignore seconds when discussing their time performance (i.e., rounding down). All other runners whose self-serving bias measure was less than 1 min (i.e., the discrepancy between self-reported time performance and official time performance was less than 1 min) were included in the unbiased group. Consequently, 161 runners were placed in the biased group while 1,159 were placed in the unbiased group.

Control Variables

Several variables that might influence runners’ self-serving bias were included as control variables. In this study, we hypothesized that self-serving bias would be used as a coping strategy in stressful situations where an athlete’s positive self-image as a runner is threatened ( Taylor and Armor, 1996 ). Therefore, variables that could represent runners’ involvement in the sport were included because they were likely to be strongly associated with study participants’ self-image as a runner. First, among three sub-dimensions of the running involvement construct (i.e., sign , centrality , and pleasure ), sign was included because it represents the self-expression value, or symbolism, of an activity (running, in our case, such as indicated by the statement “Running says a lot about who I am”; Beaton et al., 2011 ). Centrality and pleasure were not included because they reflect the importance of running and the extent to which people enjoy running in daily life rather than one’s self-image as a runner. Second, participants’ behavioral representations of involvement in running were included as control variables: past experience (the number of events in which they had participated), intensity of running as a form of exercise (“In general, how many miles per week do you run as a part of your physical activity?”), and frequency of running as a form of exercise (“In general, how many days per week do you spend on running as a part of your physical activity?”). Summary statistics appear in Table 3 .

Table 3. Descriptive statistics of focal and control variables.

Data Analysis

All statistical analyses were performed in R 3.6.2 and SPSS 27. First, to test Hypothesis 1, a chi-square analysis and an independent sample t -test with the assumption of unequal variances were conducted. In these tests, the magnitude of self-serving bias between the record-high-achieved and record-high-missed groups was statistically compared to determine whether runners in the record-high-missed group reported a positively biased time performance more frequently and strongly than those in the record-high-achieved group. Second, logistic regression analysis was used to test Hypothesis 2; we tested whether the magnitude of missed record-high finish time (i.e., the difference between one’s best finish time and official finish time) affected the probability of runners reporting a positively biased self-reported finish time. Last, to test Hypothesis 3, another independent sample t -test was conducted with the assumption of unequal variances. In this test, the overall event satisfaction between the biased and unbiased groups was statistically compared to examine whether runners in the biased group reported a lower level of overall event satisfaction than those in the unbiased group. A 5% significance level was used in all the statistical tests. The data analysis process is depicted in Figure 1 .

Figure 1. Flow chart for the testing process and measured parameters.

Frequency and Magnitude of Self-Serving Bias

As shown in Table 4 , the chi-square analysis indicated that the frequency of reporting a positively biased finish time in a post-event survey varies significantly based on whether runners achieved their record-high or not [ x 2 (1) = 48.69, p < 0.01]. Specifically, for the record-high missed group, the number of runners who reported a positively biased finish time was significantly more than expected ( p < 0.01); 125 out of 685 runners (18.2%) reported a positively biased finish time. On the contrary, the number of runners who reported a positively biased finish time was significantly fewer than expected in the record-high achieved group ( p < 0.01); only 36 out of 635 runners (5.7%) reported a positively biased finish time. These results supported Hypothesis 1a.

Table 4. Results of chi-square test.

In the independent sample t -test, the level of self-serving bias (i.e., the difference between one’s official time performance and self-reported time performance) was compared between the record-high-achieved and record-high-missed groups. We observed a significant difference in the level of self-serving bias between the two groups. The record-high-achieved group’s average extent of self-serving bias was 0.81 min ( SD = 2.42, n = 635), equal to roughly 49 s. For example, if a runner self-reported her/his finish time as 1 h 50 min, then the official finish time was 1 h 50 min 49 s, on average. Essentially, the record-high-achieved group rarely reported their time incorrectly except for a rounding pattern that ignored seconds. On the contrary, the average level of self-serving bias in the record-high-missed group was 2.08 min ( SD = 6.60, n = 685), which is about 2 min 5 s; that is, the record-high-missed group consciously or unconsciously reported time performance incorrectly by an average of 2 min 5 s. The t -test results, summarized in Table 5 , revealed that this mean difference was statistically significant ( t = −4.69, df = 877.49, p < 0.05), supporting Hypothesis 1b.

Table 5. Results of independent sample t -test with unequal variance assumption.

Probability of Misreporting Finish Time

Logistic regression analysis was used to test Hypothesis 2. A dummy variable was created using a self-serving bias measure (0 = biased, 1 = unbiased) and was regressed on the level of athletic performance (i.e., record-high – official finish time); a group of control variables was also included in the model (i.e., frequency of physical activity, intensity of physical activity, past event experience, and running involvement). Because the athletic performance was coded based on best finish time minus official finish time, the level of athletic performance increased as a runner’s official finish time was faster than her/his best finish time by a wider margin. According to the results in Table 6 , a significant association appeared between one’s level of athletic performance and self-serving bias, indicating that failure to beat one’s best finish time led to a higher probability of being categorized into the biased group [β = 0.701, exp(β) = 2.015, p < 0.05]. Thus, Hypothesis 2 was supported. The pseudo R 2 (i.e., Nagelkerke R 2 ) of the model was 0.09. Based on the logistic regression results, each runner’s probability of reporting a positively biased self-reported finish time was estimated given the level of athletic performance, as shown in Figure 2 .

Table 6. Estimates from logistic regression for self-serving bias.

Figure 2. Probability of being unbiased based on the level of athletic performance. *A positive number of athletic performance indicates that a runner broke her/his record-high at the event. The solid blue line shows predicted effects of Athletic Performance, the gray area shows 95% CI, and the black dots represent the actual data values.

Effects of Self-Serving Bias on Event Satisfaction

To test Hypothesis 3, an independent sample t -test was performed. According to the results, the level of overall event satisfaction was significantly different between the biased group and the unbiased group. The biased group’s average overall event satisfaction was 6.31 ( SD = 0.83, n = 161), while the unbiased group’s average overall event satisfaction was 6.46 ( SD = 0.69, n = 1,159). The t -test results, summarized in Table 7 , indicated that the mean difference between the two groups was statistically significant ( t = −2.13, df = 192.02, p < 0.05), supporting Hypothesis 3.

Table 7. Results of independent sample t -test with unequal variance assumption.

This study enriches understanding of recreational athletes’ behavior in a participant sport services context by examining how these runners sought to cope with less-than-expected athletic performance. In response to our research question, self-serving bias was hypothesized as a coping strategy among runners who missed their best finish time at a long-distance running event. The hypotheses were developed based on the concept of self-serving bias, which posits that people tend to have positively biased perception toward oneself by ascribing failures to external factors to overcome dissatisfaction with one’s capability to complete a certain task ( Gilovich et al., 2002 ). Above all, our findings aligned with the notion of self-serving bias; runners whose finish time fell short of their best finish time were more likely to report positively biased incorrect finish time than those whose time performance was better than their best finish time, despite the lack of external reward for doing so. As suggested by studies regarding self-serving bias, such behavior could be interpreted as a means of coping with potential dissatisfaction or discomfort with one’s less-than-expected athletic performance at the event; participants might have deceived themselves in an effort to protect their positive self-image as a runner ( Campbell and Sedikides, 1999 ; Trivers, 2000 ; Mazar and Ariely, 2006 ).

Specifically, a significant positive relationship was found between athletic performance and the probability of self-reporting a positively biased finish time: As long-distance running event participants failed to break their best finish time by a wider margin, the probability of reporting positively biased incorrect finish time increased (see Figure 2 ). As illustrated, if a runner missed their goal by approximately 20 min, the probability of deception (i.e., self-reporting positively biased incorrect time performance) was roughly 20.00%. Comparatively, if a runner achieved their goal by approximately 20 min, the likelihood of misreporting their finish time was only 8.12%; there was an 11.88 percent points increase in the probability of misreporting between the two. This result might be surprising to event organizers because runners had no explicit reason to misreport their finish time: they would receive no external benefits or rewards for reporting better time performance in an anonymous survey.

Many researchers have found similar biases in several different contexts; people tend to have positive views of themselves with the purpose of maintaining their self-image ( Taylor and Armor, 1996 ; Trivers, 2000 ; Mazar and Ariely, 2006 ). For instance, people tend to have a positively biased perception toward their physical self-image (i.e., body image). Flegal et al. (2019) showed that, regardless of gender, self-reported height was significantly higher than measured height based on the National Health and Nutrition Examination Survey collected in the United States. Gil and Mora (2011) also identified similar bias in reporting height and weight using Health Examination Surveys conducted in Spain; as individuals’ satisfaction with their own body image increases, the probability of misreporting their weight decreases. Furthermore, people frequently overestimate their own qualities and abilities and believe that they are better than their average peer (i.e., better-than-average effect; Alicke et al., 1995 ; Alicke and Govorun, 2005 ).

The underlying reasons on why people exhibit these biases in various contexts could be largely explained by self-determination theory ( Ryan and Deci, 2019 ). Self-determination theory is comprised of six “mini-theories,” and one of which is basic psychological needs theory ( Ryan and Deci, 2019 ). According to basic psychological needs theory, people have three fundamental psychological needs, namely autonomy (feeling a sense of choice about one’s behavior), competence (being able to bring about positive changes in desired outcomes), and relatedness (feeling accepted by one’s social milieu; Ntoumanis et al., 2021 ). The frustrations (and satisfactions) of these needs would impact one’s wellness and optimal functioning ( Ryan and Deci, 2019 ), resulting in amotivation, depression, and unhealthy behavior when frustrated ( Ng et al., 2013 ; Ntoumanis et al., 2021 ) and lower amotivation and adaptive behavior when satisfied ( Vansteenkiste et al., 2018 ; Ntoumanis et al., 2021 ; Pope et al., 2021 ). In the current study, runners who experienced performance failure were likely to encounter frustration in their self-determined motivations, such as competence and relatedness, because they failed to achieve their goals despite the significant amount of time and effort they put into the preparation for the event. To protect their self-image and prevent any negative emotion resulting from such frustration, runners would be inclined to cope with their less-than-expected athletic performance by self-serving bias ( Campbell and Sedikides, 1999 ).

Our findings also imply that self-serving bias affects event participants’ overall perceived event experience. Specifically, a significant difference in overall event satisfaction between the biased and unbiased groups was found in this study. Per prior research regarding self-serving bias ( Campbell and Sedikides, 1999 ), people who experienced a failure in a certain task tend to ascribe their failure to external factors. As such, they are less likely to be satisfied with the surrounding environment. In the context of long-distance running events, runners whose athletic performance is worse than their expectation would blame the event environment, rather than their own ability, for their worse-than-expected athletic performance. As suggested in self-serving bias literature ( De Michele et al., 1998 ), this would lead them to believe that the event environment prevents them from achieving their record-high finish time. Conceptually, reporting a positively biased incorrect finish time in an anonymous survey shows that a runner is subject to self-serving bias. Therefore, as shown in this study, they are less satisfied with the overall event compared to runners who are not subject to self-serving bias; runners exhibiting self-serving bias are very likely to think that their worse-than-expected finish time was due, in part, to the event environment.

Theoretically, this study underlines self-serving bias as one way recreational athletes handle disappointing competition outcomes in a participant sport services context. Unlike spectator sport, scholars cannot and do not consider “reflected” glory or “reflected” failure (i.e., BIRGing and CORFing; Cialdini et al., 1976 ; Campbell et al., 2004 ) in participant sport services because competitions are completed by athletes themselves. That is, both glory and failure in competitions at participant sport events are tied to athletes’ own outcomes. This nature of participant sport thus requires a unique approach to understanding participant sport consumers’ strategies for coping with disappointing competition outcomes. The current study thus offers a new theoretical perspective on participant sport consumers’ coping behavior in a participant sport events context. Specifically, we propose self-serving bias as a potential coping strategy for personal failure in achieving athletic performance goals in a long-distance running event; by engaging in self-serving bias, runners are cutting off performance failure (COPFing).

Practical Implications

With regard to athletic performance and self-deception as a coping strategy, the current study has some important practical takeaways. Although the current study suggests that runners whose athletic performance is worse than their best finish time are likely to report a positively biased finish time, such bias neither harms anybody nor has undeserved external benefits. People merely try to protect their self-esteem from their own failure in sport competitions (e.g., failing to break record-high performance). However, participant sport event organizers should understand this process of how event participants cope with their worse-than-expected athletic performance. In other words, they must be careful in how they internalize event feedback. Researchers in spectator sport have cautioned about the differences in event experience feedback after a win versus a loss ( Matsuoka et al., 2003 ). In participant sport events, there are always going to be those who are satisfied with their personal performance and those who are dissatisfied. When participants fail to achieve their goal, they blame the event environment for their failure, and these people may have significantly lower event satisfaction; we showed in this study that people who had self-serving bias (i.e., reporting a positively biased finish time) showed a significantly lower level of overall event satisfaction. Identifying the participants subject to self-serving bias allows event managers to understand event feedback more specifically (i.e., those engaging in self-serving bias will be more likely to rate their event experience lower).

In addition, event organizers must make extra efforts for runners who perform worse than expected at the event because they are susceptible to engaging in self-serving bias, which leads them to be less satisfied with the event. For instance, participants’ non-race experience (e.g., supportive staffs, entertainment on the course, cheer zone, food and beverage, rest and recovery area, and content of goody bag) is also an important component of overall event satisfaction and could offset the negative effect of worse-than-expected athletic performance on event satisfaction ( Du et al., 2015 ); it has been shown that there is a high positive association between service quality and event satisfaction among runners who are not satisfied with their athletic performance while runners who are satisfied with their athletic performance are also satisfied with the overall event regardless of their level of service quality perception ( Du et al., 2015 ). Providing participants with the best non-race experience would be one way to bypass the adverse effects of runners’ self-serving bias derived from worse-than-expected athletic performance, which is otherwise largely out of the control of organizers.

Limitations and Future Research

The current study has some significant limitations. First, rounding errors may have tempered the reliability of our results. Most sample participants rounded down seconds from their time performance; for instance, if a runner’s finish time was 1 h 40 min 50 s, they often reported their finish time as 1 h 40 min. Mathematically speaking, however, their finish time was closer to 1 h 41 min. We did not consider rounding down to be deception in this study because the rounding phenomenon was observed across all participants regardless of their level of goal achievement. In future work, people’s behavioral patterns regarding rounding down and the psychological rationale behind it could reveal intriguing insight.

Second, according to Mazar et al. (2008) , self-deception has a short-term effect; while people can maintain their self-esteem through self-serving bias and self-deception, these conciliatory effects only persist for a short time. In the long term, self-deception may backfire due to overestimated self-evaluation. Therefore, we strongly recommend that scholars investigate the potential negative long-term effects of self-deception in a participant sport services context. It would be especially interesting to explore whether athletes who engage in self-deception can maintain a positive self-image for an extended period by tracing temporal changes in their self-image as a runner. In so doing, researchers could develop a more thorough understanding of the effectiveness of self-deception as a coping strategy for worse-than-expected athletic performance in participant sport events.

Last, an important limitation related to identifying self-deception is that a third party cannot identify whether people are intentionally lying or are merely reporting an incorrect time due to inaccurate recall. Because it was impossible to determine respondents’ intentionality in the current study, we cannot affirmatively say whether athletes who missed their time goals were engaging in unconscious self-deception or overt deception. However, the results of this study revealed that the likelihood of reporting an incorrect finish time was statistically significantly higher for runners who missed their best finish time than for those who achieved their best finish time despite a lack of reward for misreporting. Subsequent research should examine runners’ consciousness in their deception more closely, ideally within an experimental setting, to provide additional support and boundary conditions for our findings.

Marathon running provided a unique environment to examine runners’ self-serving bias through tapping into individual conscious/unconscious yet harmless self-serving coping mechanisms. Through our analysis, we found that runners whose finish time fell short of their best finish time were more likely to self-report positively biased incorrect finish time than those whose time performance was better than their best finish time. Furthermore, we found that runners who reported positively biased finish time (i.e., those who were subject to self-serving bias) showed significantly lower event satisfaction. In conclusion, participant sport event organizers should understand this psychological process of how event participants cope with their worse-than-expected athletic performance and are encouraged to make extra efforts for runners who performed worse than their expectations because they are susceptible to engage in self-serving bias, which will lead them to be less satisfied with the event.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Author Contributions

MH and JJ contributed to the conception and design of the study. WJ, CW, JD, and TO contributed and wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords : self-serving bias, athletic performance, goal achievement, event satisfaction, participant sport events

Citation: Hyun M, Jee WF, Wegner C, Jordan JS, Du J and Oh T (2022) Self-Serving Bias in Performance Goal Achievement Appraisals: Evidence From Long-Distance Runners. Front. Psychol. 13:762436. doi: 10.3389/fpsyg.2022.762436

Received: 24 August 2021; Accepted: 04 January 2022; Published: 10 February 2022.

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Copyright © 2022 Hyun, Jee, Wegner, Jordan, Du and Oh. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Moonsup Hyun, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Self-Serving Bias in Psychology

Charlotte Ruhl

Research Assistant & Psychology Graduate

BA (Hons) Psychology, Harvard University

Charlotte Ruhl, a psychology graduate from Harvard College, boasts over six years of research experience in clinical and social psychology. During her tenure at Harvard, she contributed to the Decision Science Lab, administering numerous studies in behavioral economics and social psychology.

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Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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The self-serving bias is a cognitive bias where individuals attribute their successes to internal factors like talent or effort, while blaming external factors like luck or other people for their failures. This bias serves to maintain self-esteem and protect one’s ego.

Take-home Messages

• The self-serving bias suggests that no one wants to admit to being incompetent and is likely to blame failures on something external to ourselves. This protects our self-esteem. However, we are happy to take credit for our success.
• We rely on this bias to protect and boost our self-esteem. Our minds don’t want to take responsibility for negative or failed outcomes for fear of hurting our confidence.
• Although this bias is incredibly common in many areas of our lives, from the classroom to sports to the workplace, we can work to overcome it by recognizing its existence and practicing self-compassion.

Picture yourself sitting in a classroom, anxiously awaiting the results of your most recent math exam. When the teacher finally hands you your graded test, you turn it over only to see a giant C minus written in thick red ink.

While still in disbelief, your mind immediately begins to think of all possible explanations for this outcome. The exam questions were too hard, the teacher didn’t teach the topics well enough, the answers were graded unfairly, and the list goes on…

Imagine that when you turned over that graded test, a giant A plus was written instead. This time, with a huge grin, you praise yourself for how hard you studied, for your strong understanding of the material, for your smartness, and the list goes on…

This is an example of what is called the self-serving bias in psychology.

The self-serving bias refers to the tendency to attribute internal, personal factors to positive outcomes but external, situational factors to negative outcomes.

As you may know, our minds are biased to act, judge, and see the world in such a way. These cognitive biases are the product of human nature, the people we interact with, and an attempt to simplify the millions of bits of information the brain receives each second.

These factors also often cause specific errors in thinking that influence our decisions and judgments. This type of bias is called cognitive bias and occurs without us even realizing it (Kahneman & Tversky, 1972).

These biases arise out of problems with memory, attention, and other mental mistakes, and while they can often be dangerous, cognitive biases help you make sense of the world, reach decisions, and make judgments with relatively quick speed.

The Fundamental Attribution Error and the Actor-Observer Bias

A common phenomenon in psychology is the fundamental attribution error , also referred to as the correspondence bias.

The fundamental attribution error is the tendency of people to overemphasize personal characteristics and ignore situational factors when judging others’ behavior (Ross, 1977).

For example, if an individual cuts in front of you on the street, you might think they did this because they are a bad person and not consider external alternatives such as being late to work and in a rush.

But what happens if you are the actor?

In other words, what if you were the one who cut in front of the pedestrian? Would you then make the same argument that you are a bad person?

According to the actor-observer bias, we tend to explain other people’s behavior in terms of internal factors while explaining our own behavior on the basis of external factors (Jones & Nisbett, 1971).

Because we know ourselves better than anyone else, we can judge when our actions are the result of something external to who we are, but our minds default to assuming another person’s actions are a result of who they are.

But that still isn’t the complete picture. While it is true that we often attribute personal or dispositional characteristics to explain other people’s behavior while attributing situational factors when making sense of our own behavior, this isn’t always the case.

Whether or not the specific outcome of our behavior is good or bad will actually determine whether we make an internal or external attribution. This is the self-serving bias (Heider, 1982).

As illustrated in the example above, a failed or negative outcome (such as performing poorly on a test) causes us to make external attributions, whereas a successful or positive outcome (such as acing a test) will result in us making internal attributions.

Over the past few decades, several empirical studies have illuminated the sectors, populations, cultures, and levels of organization in which self-serving bias is more or less common.

Self-serving bias is particularly prevalent in sports. If you’ve ever played or watched a sport, you’ve probably blamed the referee’s bad call or the other team cheating when you lost a game but praised your sheer talent and mental toughness when you won.

In sports, an individual’s performance (both your own and your opponent’s) is so clearly linked to a specific outcome that it is easy for the self-serving bias to seep in.

And because the outcome and players are so apparent, self-serving bias is especially common in individual sports, where the sole winner is even more defined.

Dating back to 1987, a study conducted by Stephen Zaccaro and colleagues collected 549 statements from athletes who played both individual (e.g., tennis and golf) and team sports (e.g., baseball, football, and basketball) and found that individual sports athletes were significantly more likely to make self-serving attributions about their performance (Zaccaro et al., 1987).

In conjunction with the self-esteem theory for this form of bias, the researchers concluded that individual sports athletes’ performance had a more significant impact on their self-esteem, so they relied more on the self-serving bias to increase their confidence.

Another empirical analysis that investigated the self-serving bias in Division I wrestlers further supports the prevalence of this bias among athletes (De Michele et al., 1998). The wrestlers were asked to self-report on their performance during preseason matches and supplied the results of these matches.

The researchers found that wrestlers who won were more likely to attribute their success to internal factors than those who lost.

And in 2020, a comprehensive meta-analysis that looked at 69 studies and 10,515 total athletes demonstrated that those who play sports have a tendency to attribute success to dispositional factors and failure to external factors (Allen et al., 2020).

From the hiring phase to the firing phase to everything in between, self-serving bias is just as common in the workplace as it is in the sports sector.

People who are hired for a position often attribute this decision to personal factors, such as an exceptional resume or other strong qualifications, but are quick to point to external factors, such as a short-sighted hiring manager, when they are not given the position.

And in the office setting itself, self-serving bias can run rampant in the event of any workplace incident: the victim is likely to blame external factors, while the coworkers and management are more likely to see the accident as a result of the victim’s actions.

In situations like these, the self-serving bias proves to be an obstacle to productivity by blocking the ability to evaluate a situation fairly and take responsibility for any shortcomings.

This can also hurt professional relationships as a result. And when these relationships are tarnished, self-serving bias increases. Specifically, a 2007 study conducted by Joseph Walther and Natalya Bazarova found that the more distant the relationship between employees and their colleagues was, the more easily co-workers blamed each other for workplace failures.

But this form of bias can also occur when workplace successes arise, whether it be a promotion or a presentation that went well. The employee is likely to take full responsibility for these outcomes and neglect the people and circumstances that helped them earn their success.

Self-serving bias is even visible when an employee is terminated: people are quick to attribute external factors to the decision to lay them off (Furnham, 1982). Regardless of the job application stage, type of work, or an individual’s title, self-serving bias is incredibly pervasive in the workplace.

Depression, Culture, and International Effects

Sports and the workplace are just two areas where we can identify this form of bias. Consumer decisions, interpersonal relationships, and other areas of life are also affected by self-serving bias, and certain populations are affected more than others.

For example, research has shown that individuals with depression experience self-serving bias to a much lesser degree. A 2004 meta-analysis analyzed 266 studies that surveyed people from different age groups, diverse regions, and various forms of psychopathology (Mezulis et al., 2004).

The researchers found that the presence of the bias was smallest among those who were clinically diagnosed with depression. They posited that this effect might be due to the fact that these individuals already have lower-than-average levels of self-esteem, so they are more likely to attribute negative events to something they did.

Relating back to the hypothesis that the self-serving bias is tied to how closely an outcome aligns with our expectations, a person with depression might also expect more negative outcomes, and so when those do occur, they take responsibility for them.

The same study also revealed that Asian samples displayed significantly smaller biases than U.S. or Western samples. This finding highlights the cross-cultural differences of the self-serving bias – it is much more prominent in individualistic than collectivist cultures .

This may be because, in individualistic societies, there is a larger focus on individual goals and identity, which increases the need for people to protect themselves and increase their personal self-esteem levels.

Finally, research has also indicated that self-serving bias occurs on a national scale. That is, instead of an individual attributing personal factors to their own successes and external factors to their failures, groups often attribute factors unique to their country when successes arise and factors related to other countries when they run into failures.

A common example of this nationalistic self-serving bias is climate change. A 2011 study conducted out of Carnegie Mellon University and the University of Zurich investigated citizens’ perceptions on which country should lower its greenhouse gas emissions (Kriss et al., 2011).

The team administered surveys to college students in both the U.S. and China and found that they all held nationalistic self-serving biases regarding the economic burdens that result from reducing these emissions, demonstrating the challenges of making international agreements.

The researchers note that with proper intervention, these biases can be mitigated to stimulate environmental policy legislation worldwide.

Why Does It Occur?

During the 1960s, when psychologists began to investigate the fundamental attribution error.

An Austrian psychologist named Fritz Heider found that in certain ambiguous situations (situations in which the reason for the outcome is unknown), people tend to make attributions based on their need to maintain a higher self-esteem level (Heider, 1982).

To many psychologists, a need for increased self-esteem is the driving force for the presence of this bias. We default to taking responsibility for positive outcomes to preserve our self-esteem and are quick to divert the blame for negative outcomes to protect ourselves.

Having these high levels of self-esteem allows us to feel confident and secure and have positive relationships with others as a result. Additionally, when you have high self-esteem, you’re more open to learning and feedback. Thus, we subconsciously rely on this self-serving bias as a way of maintaining our self-esteem.

Although the linkage between self-esteem and self-serving bias is a leading theory, psychologists have identified several other reasons for why this bias is so prevalent among individuals.

As this phenomenon was gaining traction in the 60s and 70s, two prominent psychologists, Dale Miller and Michael Ross, pushed back on the self-esteem explanation and argued that self-serving bias is instead tied to how closely reality aligns with an individual’s expectations.

In other words, if the outcome of an event is consistent with a person’s expectation, then they will attribute internal factors to the outcome (Miller & Ross, 1975). But if the outcome is unexpected, then they will make external attributions and blame their surroundings.

Another possible explanation is that self-serving bias is a result of natural optimism (“Self-serving bias – biases & heuristics,” 2021).

This theory holds that because humans are inherently optimistic, negative outcomes come as a surprise, and so when these outcomes do occur, we are more likely to attribute these results to external factors as opposed to internal ones.

This helps further explain Miller and Ross’ theory – because humans are naturally optimistic, we expect positive and successful outcomes, so when they don’t occur, we assume it is a result of situational factors alone.

These leading theories help illustrate why we might regularly fall victim to self-serving bias. And although the root cause is still debated, there is no doubt that this form of bias is incredibly prevalent.

How to Overcome

Just as the researchers in Zurich and at Carnegie Mellon alluded to, overcoming self-serving bias is not futile. And the first step is something you are doing right now: awareness!

Like most cognitive biases, bringing something from the unconscious mind to the conscious mind is the first step to mitigating the bias.

And recognizing that biases grow out of our mind’s tendency to think quickly and make snap judgments and decisions, it is important to try to slow down your thinking – taking all relevant factors into consideration and trying to avoid making rash decisions or statements.

The self-serving bias is unique in that it is closely related to our self-esteem. When we rely on this bias to help elevate our sense of self-worth, it makes self-improvement difficult because we are less likely to learn from our mistakes and accept any negative feedback.

But because knowing how to admit when you are in the wrong or are responsible for a negative outcome is paramount to growth, it’s important to challenge the self-serving bias and learn how to be better at taking criticism.

An important way to do this is by practicing self-compassion – allowing yourself to be imperfect and still treating yourself with unconditional kindness when you fall short of your own expectations (Neff, 2003).

You can practice self-compassion through mindfulness, therapy, and even on your own.

These are just a few ways to help combat self-serving bias. The bottom line is that although this bias is inherent in who we are as humans, we can still work towards overcoming this thinking pattern and, at the end of the day, recognize that it is okay to make mistakes.

Learning Check

Which of the following is an example of a self-serving bias?

• John believes he got lost on his way home because of unclear road signs rather than admitting he is bad at directions.
• Mary credits her failure in the competition to her lack of practice, not external factors.
• Jack believes his success in the stock market is purely due to his market understanding but attributes any losses to market volatility.
• Sally accepts that her delay is due to her poor time management, not the traffic on the road.
• David attributes his promotion to his networking skills, but he blames office politics when he doesn’t get a raise.
• Emily believes her win in chess was due to her skill, but when she loses, she blames the opponent’s luck.
• Tom accepts his failure in the exam was due to his lack of studying, not the difficulty level of the exam. (Answer: Not self-serving bias)
• Lisa thinks her successful painting was due to her talent, but she blames the art market when her next painting doesn’t sell.
• Mike admits that not getting the job was due to his lack of experience, not the interviewer’s bias.
• Sarah believes she won the lottery because of her lucky numbers, but when she doesn’t win, she thinks the lottery is fixed.

Answers : Self-serving bias is seen in examples 1, 3, 5, 6, 8, and 10, where individuals credit their successes to their own abilities or qualities but attribute their failures to external factors. In contrast, examples 2, 4, 7, and 9 are not instances of self-serving bias, as individuals attribute their failures to their own shortcomings rather than blaming external circumstances.

Allen, M. S., Robson, D. A., Martin, L. J., & Laborde, S. (2020). Systematic review and meta-analysis of self-serving attribution biases in the competitive context of organized sport. Personality and Social Psychology Bulletin, 46 (7), 1027-1043.

De Michele, P. E., Gansneder, B., & Solomon, G. B. (1998). Success and failure attributions of wrestlers: Further evidence of the self-serving bias. Journal of Sport Behavior, 21( 3), 242.

John, E. E., & Nisbett, R. E. (1971). The actor and observer: Divergent perception of the causes of behavior: Attribution: Perceiving the causes of behavior.

Furnham, A. (1982). Explanations for unemployment in Britain. European Journal of Social Psychology, 12 (4), 335-352.

Heider, F. (1982). The psychology of interpersonal relations . Psychology Press.

Kahneman, D., & Tversky, A. (1972). Subjective probability: A judgment of representativeness. Cognitive psychology, 3(3), 430-454.

Kriss, P. H., Loewenstein, G., Wang, X., & Weber, R. A. (2011). Behind the veil of ignorance: Self-serving bias in climate change negotiations. Judgment and Decision Making, 6 (7), 602-615.

Mezulis, A. H., Abramson, L. Y., Hyde, J. S., & Hankin, B. L. (2004). Is there a universal positivity bias in attributions? A meta-analytic review of individual, developmental, and cultural differences in the self-serving attributional bias. Psychological Bulletin, 130 (5), 711.

Miller, D. T., & Ross, M. (1975). Self-serving biases in the attribution of causality: Fact or fiction? . Psychological Bulletin, 82 (2), 213.

Neff, K. (2003). Self-compassion: An alternative conceptualization of a healthy attitude toward oneself. Self and Identity, 2 (2), 85-101.

Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. In Advances in experimental social psychology (Vol. 10, pp. 173-220). Academic Press.

Self-serving bias – biases & heuristics. (2021). Retrieved from https://thedecisionlab.com/biases/self-serving-bias/

Walther, J. B., & Bazarova, N. N. (2007). Misattribution in virtual groups: The effects of member distribution on self-serving bias and partner blame. Human Communication Research, 33 (1), 1-26.

Zaccaro, S. J., Peterson, C., & Walker, S. (1987). Self-serving attributions for individual and group performance. Social Psychology Quarterly, 257-263.

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