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The Competition-Performance Relation: A Meta-Analytic Review and Test of the Opposing Processes Model of Competition and Performance

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What is the relation between competition and performance? The present research addresses this important multidisciplinary question by conducting a meta-analysis of existing empirical work and by proposing a new conceptual model-the opposing processes model of competition and performance. This model was tested by conducting an additional meta-analysis and 3 new empirical studies. The first meta-analysis revealed that there is no noteworthy relation between competition and performance. The second meta-analysis showed, in accord with the opposing processes model, that the absence of a direct effect is the result of inconsistent mediation via achievement goals: Competition prompts performance-approach goals which, in turn, facilitate performance; and competition also prompts performance-avoidance goals which, in turn, undermine performance. These same direct and mediational findings were also observed in the 3 new empirical studies (using 3 different conceptualizations of competition and attending to numerous control variables). Our findings provide both interpretational clarity regarding past research and conceptual guidance regarding future research on the competition-performance relation. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
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The Competition–Performance Relation: A Meta-Analytic Review and Test
of the Opposing Processes Model of Competition and Performance
Kou Murayama
University of Munich Andrew J. Elliot
University of Rochester
What is the relation between competition and performance? The present research addresses this important
multidisciplinary question by conducting a meta-analysis of existing empirical work and by proposing a
new conceptual model—the opposing processes model of competition and performance. This model was
tested by conducting an additional meta-analysis and 3 new empirical studies. The first meta-analysis
revealed that there is no noteworthy relation between competition and performance. The second
meta-analysis showed, in accord with the opposing processes model, that the absence of a direct effect
is the result of inconsistent mediation via achievement goals: Competition prompts performance-
approach goals which, in turn, facilitate performance; and competition also prompts performance-
avoidance goals which, in turn, undermine performance. These same direct and mediational findings
were also observed in the 3 new empirical studies (using 3 different conceptualizations of competition
and attending to numerous control variables). Our findings provide both interpretational clarity regarding
past research and conceptual guidance regarding future research on the competition–performance
relation.
Keywords: rivalry, attainment, productivity, goal structure, reward structure
Competition is highly prevalent in human societies across the
globe (Eibl-Eibesfelt, 1989; D. W. Johnson & Johnson, 1989;
McClelland, 1961; cf. Bonta, 1997). In their vocational and avo-
cational activities alike, individuals compete with one another in
myriad ways. The present research addresses a basic and important
question regarding competition, namely: What is the relation be-
tween competition and performance?
Not surprisingly, theorists have long been interested in whether
competition helps or hinders performance. Surprisingly, little con-
sensus has been reached on this issue over the years. Many
theorists, such as Scottish philosopher and economist Adam Smith
(1776/1937), have contended that competition enhances motiva-
tion and is beneficial for performance, thereby broadly embracing
the Roman poet Ovid’s dictum, “A horse never runs so fast as
when he has other horses to catch up and outpace” (Ovid, The Art
of Love: Book III, p. 173; Abra, 1993; Festinger, 1954; Locke,
1968; McClelland, Atkinson, Clark, & Lowell, 1953; Michaels,
1977; Parker, 1998; Schumpeter, 1934; Sherif, 1978; Shields &
Bredemier, 2009; Smith, 1776/1937; Spencer, 1860/1969). Many
other theorists, however, such as English philosopher and political
theorist Thomas Hobbes (1651/1994), have espoused the opposite
view, arguing that competition undermines motivation and is det-
rimental to performance; these theorists would be more likely to
concur with the Hungarian composer Bella Bartok’s quip, “Com-
petitions are for horses, not artists” (Covington, 1992; Deci &
Ryan, 1985; Deutsch, 1949; Forsyth, 1999; Frank & Cook, 1995;
Johnson & Johnson, 2003; Kohn, 1986; Maehr & Midgley, 1991;
Mead, 1937; Montagu, 1952; Ulrich, 2008). Both of these con-
trasting positions on the competition–performance relation con-
tinue to be espoused within broad and diverse areas of the con-
temporary psychological literature, including educational
psychology, industrial–organizational psychology, social–
personality psychology, and sport and exercise psychology (for
reviews, see Sambolec, Kerr, & Messe´, 2007; Tauer & Harackie-
wicz, 2004; Tjosvold, Johnson, Johnson, & Sun, 2006).
The present work has four foci. First, we conduct a meta-
analysis of the existing empirical work on the competition–perfor-
mance relation. Second, we propose a motivationally based model
of competition and performance that is consistent with the extant
research and that accommodates both of the contrasting positions
on the competition–performance relation. Third, we conduct an
additional meta-analysis (using meta-analytic structural equation
modeling) that tests the central tenets of the proposed model.
Fourth, we present three new empirical studies designed to further
test the proposed model.
Existing Research on the Competition–Performance
Relation: A Meta-Analysis
Competition may be conceptualized in three distinct ways
(Brown, Cron, & Slocum, 1998): As a characteristic of the person
(trait competitiveness), as a characteristic of the perceived situa-
tion (perceived environmental competitiveness), and as a charac-
teristic of the actual situation (structural competition). All of these
conceptualizations focus on interpersonal competition—that is,
Kou Murayama, Department of Psychology, University of Munich,
Munich, Germany; Andrew J. Elliot, Department of Psychology, Univer-
sity of Rochester.
This study was supported by an Alexander von Humboldt Foundation
fellowship to Kou Murayama.
Correspondence concerning this article should be addressed to Kou
Murayama, Department of Psychology, University of Munich, Leopold-
strasse 13 (PF 67), Munich, Germany, 80802. E-mail: murakou@
orion.ocn.ne.jp
Psychological Bulletin © 2012 American Psychological Association
2012, Vol. 138, No. 6, 1035–1070 0033-2909/12/$12.00 DOI: 10.1037/a0028324
1035
competition between individuals. Competition may involve other
aspects, such as intrapersonal competition (i.e., competition with
oneself) and intergroup competition (i.e., competition between
groups). We limit our focus to interpersonal competition herein,
because this aspect of competition has received the vast majority
of the conceptual and empirical attention, especially with regard to
the competition–performance relation. Furthermore, the other as-
pects of competition are quite distinct from interpersonal compe-
tition, emphasizing different types and levels of psychological
processes (Albert, 1977; Elliot, Murayama, & Pekrun, 2011;
Mehta, Wuehrmann, & Josephs, 2009; Tajfel & Turner, 1979), and
researchers have compellingly argued that the different aspects of
competition should be studied separately (see Tauer & Harackie-
wicz, 2004). In the following, we define each of the three concep-
tualizations of competition and describe the state of the literature
for each with regard to systematic empirical reviews.
Trait competitiveness represents a dispositional preference to
compete with others in achievement situations (Spence & Helm-
reich, 1983). Research on competitiveness as a personality trait has
several different conceptual roots (e.g., Helmreich & Spence,
1978; Jenkins, Zyzanski, & Rosenman, 1979; Ryckman, Hammer,
Kaczor, & Gold, 1990), and trait competitiveness has been an
important personality construct in several different subdisciplines
of psychology, especially educational psychology (e.g., Wigfield
& Guthrie, 1997) and industrial–organizational psychology (e.g.,
Fletcher, Major, & Davis, 2008). The existing research has typi-
cally used the competitiveness subscale of the Work and Family
Orientation (WOFO) scale (Helmreich & Spence, 1978) to assess
trait competitiveness in a brief, face valid manner (sample item: “I
feel that winning is important in both work and games”). Although
research on trait competitiveness and performance has been con-
ducted for over 30 years, not a single systematic empirical review
(i.e., meta-analysis) has been published.
Perceived environmental competitiveness represents an individ-
ual’s cognitive construal of the competitive nature of the achieve-
ment setting. Deutsch (1949) and others (e.g., Kristof, 1996) have
argued that participants’ subjective perceptions of the competitive-
ness of the achievement environment are critical to understanding
competition effects. Perceived environmental competitiveness has
been considered a particularly important construct in educational
settings (Astin, 1968; Maehr & Midgley, 1996). However, most of
the studies that have been conducted in the education domain have
focused on perceived environmental competitiveness as a group-
level variable (i.e., classroom or school), rather than an individual-
level variable (i.e., student; e.g., Fraser & Fisher, 1982; Moos,
1979; Walberg & Anderson, 1972). This type of design allows
researchers to investigate group-level effects of competition (“Do
competitive groups do better than noncompetitive groups?”) but
cannot address the focal question herein, which is “Do individual’s
perceptions of the competitiveness of the environment influence
their individual outcomes?” (see Robinson, 1950). A systematic
empirical review of the link between perceived environmental
competitiveness and performance has yet to be conducted. One
article that appears to be relevant to this question at first glance
(Haertel, Walberg, & Haertel, 1981) is not pertinent upon closer
investigation, as the only studies that were examined with regard
to perceived environmental competitiveness focus on group-level
effects and composite, omnibus outcome variables that include
motivation, self-concept, and attendance in addition to perfor-
mance.
Structural competition represents an actual situation in which
two or more people vie for a mutually exclusive achievement
outcome (Johnson & Johnson, 1989).
1
Traditionally, research on
competition and performance has conceptualized competition in
this manner. Unlike the aforementioned research on trait compet-
itiveness and perceived environmental competition, several sys-
tematic empirical reviews have been conducted over the years on
structural competition and performance. However, most of these
reviews have been constrained in one of several ways as a function
of the precise research question under consideration. Qin, Johnson,
and Johnson (1995) and Stanne, Johnson, & Johnson (1999) com-
pared the influence of competitive structures to cooperative struc-
tures on performance. This comparison is clearly of theoretical and
practical importance, but it does not address structural competition
per se. To test whether structural competition per se is beneficial
or deleterious for performance, it is necessary to compare com-
petitive structures to neutral controls (sometimes labeled “individ-
ualistic structures”). In addition, some meta-analyses have re-
stricted their focus to a specific type of performance (e.g., motor
performance; Stanne et al., 1999) or a specific age group (e.g.,
12–15 years; Roseth, Johnson, & Johnson, 2008). The only peer
reviewed meta-analysis that compares the influence of competitive
structures to neutral controls on all types of performance across
age groups was conducted by Johnson, Maruyama, Johnson, Nel-
son, and Skon (1981).
2
These researchers found no significant
difference between competitive structures and neutral controls on
performance attainment. Given that 30 years have passed since this
research was published, an update of this important work is clearly
overdue.
In sum, despite long-term and widespread interest in the
competition–performance relation, systematic evaluation of the
existing empirical yield has been lacking. This is particularly
the case with regard to trait competitiveness and perceived envi-
ronmental competitiveness, although an updating of meta-analytic
work on structural competitiveness is also clearly needed. In the
following, we provide a meta-analytic review that focuses on the
relation between each of the three conceptualizations of competi-
1
Perceived environmental competitiveness and structural competition
are related with regard to their influence on performance; in both instances,
it is one’s perception of the situation that (ultimately) guides behavior
(Ames & Archer, 1988; Deutsch, 1949; Lewin, 1935). Nevertheless, dis-
tinguishing between these two conceptualizations of competition has prac-
tical value, because researchers have investigated them with very different
methodologies (i.e., research on perceived environmental competitiveness
uses self-report questionnaires, whereas research on structural competition
relies on experimental manipulation).
2
In a book chapter, Johnson and Johnson (1989) also reported meta-
analytic data that compared the influence of competitive structures to
neutral controls on all types of performance across age groups. The results
showed a performance increment for competitive structures in initial anal-
yses, but this finding became null when the analysis was restricted to high
quality studies. It should also be noted that the Stanne et al. (1999)
meta-analysis contains an error in Table 2; it is clear from the narrative text
that “competition vs. individualistic” should read “cooperation vs. individ-
ualistic.” Stanne et al. (1999) did not include a comparison of competitive
structures and neutral controls.
1036 MURAYAMA AND ELLIOT
tion and performance. No restrictions are made with regard to type
of performance or age group, and the structural competition anal-
yses focus on competition per se (i.e., competitive structures vs.
neutral controls).
Sample of Studies
The studies included in our meta-analysis were identified via a
thorough search of the literature for studies written in English and
published by April 2011 that investigated the relation between
competition (trait competitiveness, perceived environmental com-
petitiveness, or structural competition) and performance with hu-
man participants. First, we searched PsycINFO and ERIC using
pairs of keywords, one representing competition and the other
representing performance. The search terms representing compe-
tition included competition,competitive,competitiveness,hyper-
competition,hypercompetitive,reward structure,goal structure,
and motivational climate. The search terms representing perfor-
mance included performance,achievement,attainment,accom-
plishment, and productivity. More than 7,000 references were
retrieved. Second, we checked to ensure that all studies used in the
prior published meta-analyses on structural competition and per-
formance (e.g., Johnson et al., 1981; Roseth et al., 2008) were
retrieved. Third, we searched for additional studies citing any of
the major scales used to assess trait competitiveness or perceived
environmental competitiveness (e.g., Midgley et al., 1998; Smither
& Houston, 1992). Fourth, we searched for additional studies by
major contributors to the literature on the competition–perfor-
mance relation (e.g., David Johnson, Roger Johnson, Robert Helm-
reich). Finally, we searched the reference sections of all of the
relevant retrieved studies for additional relevant studies. We re-
viewed the abstracts of these retrieved studies and eliminated those
that were clearly not relevant to the competition–performance
relation.
We then screened the resulting pool of studies on the following
inclusion criteria. With regard to trait competitiveness and per-
ceived environmental competitiveness, studies were included if (a)
the study dealt specifically with the relation between self-reports
of competitiveness (trait or perceived environmental) and perfor-
mance and (b) the study contained sample sizes and at least one
zero-order correlation for the variables of interest. Studies in which
only path coefficients (from multiple regression or structural equa-
tion modeling) or partial correlations were reported without ac-
companying zero-order correlations were not included, because
these values do not provide a comparative metric across studies
(Lipsey & Wilson, 2001). With regard to structural competition,
studies were included if (a) the study dealt specifically with the
experimental effect of competition on performance, (b) the study
compared a competition condition with a neutral control condition
(as opposed to a cooperation condition), and (c) the study con-
tained information to calculate an effect size for the dependent
variable or variables (see the Calculating and Integrating Effect
Sizes section, below).
For all three conceptualizations of competition, competition was
operationally defined as normative comparison between individu-
als, and we included all studies in which this definitional aspect of
competition was salient (e.g., the trait competitiveness measure
included items focused on normative comparison, or the structural
competition manipulation focused on interpersonal comparison).
Performance was operationally defined as a score obtained on a
task, with measures including graded performance (e.g., exam
scores, grade point averages), quality and quantity of job produc-
tivity (e.g., sales performance, professors’ scholastic achieve-
ments), sport performance, quality of and accuracy on cognitive/
motor/sensory tasks, time to obtain solutions to problems, level of
cognitive reasoning and critical thinking, creativity, recall, and
retention. Studies using only self-perceived performance measures
were not included. As delineated earlier, the focus of the present
research is on the relation between competition and performance at
the individual level of analysis; as such, studies on intergroup
competition or using groups rather than individuals as the focal
unit of data analysis were not included. If a relevant study did not
report information to compute an effect size and was published
since 2000, we attempted to contact the author(s) to obtain the
pertinent data.
In all, our search produced the following number of studies for
meta-analytic review. For trait competitiveness, 56 articles were
identified, yielding a final sample of 65 studies using 14,721
participants. For perceived environmental competitiveness, 33 ar-
ticles were identified, yielding a final sample of 33 studies using
11,439 participants. For structural competition, 59 articles were
identified, yielding a final sample of 81 studies using 5,887 par-
ticipants. The studies included in the meta-analysis are listed in the
Appendix.
Coding Study Characteristics
The variables coded in the meta-analysis for each conceptual-
ization of competition were as follows: (a) outlier status (outlier or
not); (b) gender composition (female dominant, if female ratio is
more than 75%; male dominant, if male ratio is more than 75%; or
mixed); (c) age group (nonadult [18] or adult; we also coded
mean age for further analysis); (d) nationality (U.S. or non-U.S.);
and (e) year of publication (1980s and before, 1990s, or 2000 and
after). For trait competitiveness and perceived environmental com-
petitiveness, the type of performance domain was coded (school,
work, or sport), while for structural competition, the type of
performance task was coded (cognitive or motor/perceptual/
sensory).
Calculating and Integrating Effect Sizes
The studies on trait competitiveness and perceived environmen-
tal competitiveness provide correlation coefficients, whereas those
on structural competition provide mean differences. Given this
inconsistency, we used different computation methods (described
below) to compute effect sizes for each type of data. All data
analyses were conducted using Comprehensive Meta-Analysis
(Version 2.2.; Borenstein, Hedges, Higgins, & Rothstein, 2008; for
technical details, see Borenstein, Hedges, Higgins, & Rothstein,
2009).
Trait competitiveness and perceived environmental compet-
itiveness. As recommended in the literature (Hedges & Vevea,
1998; see also Hafdahl & Williams, 2009), we converted all
correlations to Fisher’s zusing the following formula:
zj1
2log1rj
1rj, (1)
1037
THE COMPETITION–PERFORMANCE RELATION
where r
j
, and z
j
denote the sample correlation and Fisher’s zof
study j, respectively. We computed v
j
, the variance of z
j
,as
follows:
vj1
nj3, (2)
where n
j
is the sample size of study j. A few studies used dichot-
omous dependent variables. In such cases we computed the stan-
dardized mean difference between the groups and used it as an
estimate of z
j
. All results are presented using correlation coeffi-
cients to facilitate ease of interpretation of the findings. Effect size
estimates were reconverted to correlations by the inverse of the
Fisher transformation.
Structural competition. Standardized mean differences be-
tween the experimental and control conditions were calculated. We
computed effect sizes using Hedges and Olkin’s (1985) unbiased
estimator g
j
, given by
gj
Y
j
EY
j
C
Sj
13
4nj
Enj
C9
, (3)
where Y
j
E,Y
j
C,nj
E,nj
Care the experimental and control group sam-
ple means and sample sizes for the jth study, and S
j
is the pooled
standard deviation of the two groups. As can be seen, the effect
sizes were calculated so that a positive effect size indicated a
favorable outcome for the experimental (i.e., competition) group.
We computed v
j
, the variance of g
j
, as follows:
vj
nj
Enj
C
nj
Enj
C1
2nj
Enj
C
Y
j
EY
j
C
Sj
2
13
4nj
Enj
C9
2
.
(4)
In the structural competition studies, not all investigations re-
ported the information in Equations 3 and 4. When two groups
were compared and only tvalues were reported, it is straightfor-
ward to transform the tvalues to effect sizes g(see Lipsey &
Wilson, 2001). In some studies, a one-way analysis of variance
with more than two groups or a factorial analysis of variance was
conducted and only the means and sample sizes of each condition
and omnibus Fvalues were reported. In such cases, we used the
available information to estimate the mean-square error of
the analysis of variance, computed the square-root of this estimate,
and then inserted this value for S
j
. A few studies conducted
analysis of covariance but did not report the correlation between
the covariate and the outcome variable; a few other studies did not
report the sample size of each condition but reported the overall
sample size. In such cases, precise estimation of effect sizes is not
possible, so we estimated the effect size by assuming that (a) the
correlation between the covariate and the outcome variable was
0.5, or (b) the sample sizes were equal across the groups.
Integration of the effect sizes. For each conceptualization
of competition, we adopted a random-effects framework to
integrate the computed effect sizes (Hedges & Vevea, 1998). In
this approach, the overall point estimate of the effect sizes is
obtained by computing the weighted average of the effect sizes
(i.e., z
j
for trait competitiveness or perceived environmental
competitiveness and g
j
for structural competition) with the
weight of jth study w
j
given by
wj1
vj2, (5)
where 2is the between-studies variance (the variance of the effect
size parameters across the population of studies), estimated by the
method of moments method. The standard error of the averaged
effect sizes Vis estimated as follows:
V1
i1
Kwi
,
where Kis the total number of studies. This value is used to
construct a 95% confidence interval (CI) of the average effect size.
When a study included multiple effect sizes, the average effect
size within the study was computed and used in the meta-analysis.
This allowed us to avoid nonindependence of the data.
Meta-Analytic Results
Trait competitiveness. Table 1 reports the meta-analytic
results for trait competitiveness. Overall, the average effect size is
r.05 (95% CI [.02, .08]). Although this effect is statistically
significant (as indicated by the 95% CI that does not include 0), it
is clearly of extremely small magnitude. Indeed, the .05 value falls
considerably below a small effect size (r.10; see Cohen, 1988).
Next, we conducted additional analyses to investigate the ro-
bustness of this finding (see Table 1). First, we excluded studies
that had statistically significant standardized residuals (i.e., poten-
tial outlier studies; see Hedges & Olkin, 1985). The average effect
size remained very small with these studies omitted (r.03; 95%
CI [.02, .05]). We then examined whether the effect size was
moderated by the study characteristics that we coded. Specifically,
we computed the effect size separately for each of the following
categories: gender composition, age group, nationality, year of
publication, and type of performance domain. As indicated in
Table 1, none of the study characteristics may be seen as strongly
moderating the relation between trait competitiveness and perfor-
mance. The average effect size remained small to nonexistent
(ranging from r.00 to .11) within each category. We also
conducted a meta-regression analysis (Borenstein et al., 2008)
using the random-effects model (method of moments) to further
test the linear or quadratic effects of age in the relationship
between trait competitiveness and performance. The results
showed no significant effects (ps.61).
Perceived environmental competitiveness. Table 2 reports
the meta-analytic results for perceived environmental competitive-
ness. Overall, the average effect size is extremely small and not
statistically significant (r–.01; 95% CI [–.06, .04]). Thus,
perceived environmental competitiveness has no discernible influ-
ence on performance, and even if the observed effect were signif-
icant, it would be considered very small relative to a small effect
size of r.10.
As with trait competitiveness, we next conducted additional
analyses to investigate the robustness of this finding (see Table 2).
First, we excluded potential outlier studies (on the basis of statis-
tically significant standardized residuals). The average effect size
did not change as a function of these omissions (r–.02; 95% CI
[–.07, .03]). We then examined whether the effect size was mod-
erated by the study characteristics that we coded. Again, as with
1038 MURAYAMA AND ELLIOT
trait competitiveness, we computed the effect sizes separately for
each of the different categories, namely, gender composition, age
group, nationality, year of publication, and type of performance
domain. As indicated in Table 2, none of the study character-
istics may be seen as strongly moderating the link between
perceived environmental competitiveness and performance. The
average effect size remained small to nonexistent (ranging from
r–.10 to .11) within each category. We also conducted a
meta-regression analysis to further test the linear or quadratic
effects of age in the relationship between perceived environ-
mental competitiveness and performance. The results showed
no significant effects (ps.28).
Structural competition. Table 3 reports the meta-analytic
results for structural competition. Note that the effect size in this
analysis is represented by g, a standardized mean difference.
Overall, the average effect size is extremely small and not statis-
tically significant (g.04; 95% CI [.08, .16]). Thus, structural
competition has no discernible influence on performance, and even
Table 1
Meta-Analysis on Trait Competitiveness
Analysis k(total N)
Mean
weighted r95% CI
2
Overall effect size 65 (14,721) .05 [.02, .08] .01
ⴱⴱ
Overall effect sizes excluding outliers 52 (12,246) .03 [.02, .05] .00
Effect sized based on gender composition
Female dominant (male ratio is .25) 8 (1,255) .09 [.01, .20] .01
Male dominant (male ratio is .75) 13 (1,959) .10 [.03, .17] .01
Mixed (male ratio is between .25 and .75) 40 (10,956) .02 [.01, .06] .01
Effect sizes for different age groups
Non-adults (18 years old or younger) 10 (4,064) .00 [.05, .05] .00
Adults (older than 18 years) 55 (10,657) .06 [.03, .10] .01
ⴱⴱ
Effect sizes inside and outside the U.S.
U.S. 51 (10,665) .05 [.02, .09] .01
ⴱⴱ
Non-U.S. 9 (3,511) .07 [.01, .14] .01
Effect sizes based on year of publication
1980s and before 13 (3,044) .04 [.01, .09] .00
1990s 21 (4,851) .08 [.02, .15] .01
2000s and after 31 (6,826) .04 [.00, .08] .01
Effect sizes for type of performance domain
School 28 (8,879) .03 [.01, .06] .00
Work 23 (3,958) .10 [.04, .16] .01
Sports 3 (382) .11 [.09, .30] .02
p.05.
ⴱⴱ
p.01.
Table 2
Meta-Analysis on Perceived Environmental Competitiveness
Analysis k(total N)
Mean
weighted r95% CI
2
Overall effect size 33 (11,439) .01 [.06, .04] .02
ⴱⴱ
Overall effect sizes excluding outliers 30 (10,646) .02 [.07, .03] .01
ⴱⴱ
Effect sized based on gender composition
Female dominant (male ratio is .25) 1 (508) .06 [.23, .11] n/a
Male dominant (male ratio is .75) 1 (262) .10 [.22, .02] n/a
Mixed (male ratio is between .25 and .75) 27 (10,081) .01 [.06, .05] .02
ⴱⴱ
Effect sizes for age groups
Non-adults (18 years old or younger) 23 (8,558) .04 [.10, .02] .02
Adults (older than 18 years) 10 (2,881) .05 [.02, .13] .01
Effect sizes inside and outside the U.S.
U.S. 24 (9,271) .04 [.10, .03] .02
ⴱⴱ
Non-U.S. 9 (2,168) .06 [.02, .14] .01
Effect sizes based on year of publication
1980s and before 5 (1,469) .07 [.01, .15] .00
1990s 9 (4,452) .07 [.17, .03] .02
2000s and after 19 (5,518) .00 [.07, .07] .02
Effect sizes for type of performance domain
School 20 (8,545) .06 [.12, .01] .02
Work 6 (1,374) .05 [.07, .16] .02
Sports 6 (1,225) .11 [.02, .23] .02
p.05.
ⴱⴱ
p.01.
1039
THE COMPETITION–PERFORMANCE RELATION
if the observed effect were significant, it would be considered very
small (falling considerably below a small effect size of g.20;
see also Lipsey & Wilson, 2001). To establish comparability of the
results across competition conceptualizations, we also transformed
the effect size ginto r(Hedges & Olkin, 1985) and integrated the
results with a random effects model. This yielded a very small
average effect size of r.02 (95% CI [.04, .08]).
As with trait competitiveness and perceived environmental com-
petitiveness, we next conducted additional analyses to investigate
the robustness of this finding (see Table 3). First, we excluded
potential outlier studies (on the basis of statistically significant
standardized residuals). The average effect size did not change as
a function of these omissions (g.08; 95% CI [.02, .18]). We
then examined whether the effect size was moderated by the study
characteristics that we coded. Again, as with the preceding con-
ceptualizations of competition, we computed the effect sizes sep-
arately for the categories gender composition, age group, nation-
ality, and year of publication. We also investigated possible
moderation by type of performance task. As indicated in Table 3,
none of the study characteristics may be seen as strongly moder-
ating the effect of structural competition on performance. The
average effect size remained small to nonexistent (ranging from
g⫽⫺.10 to .13) within each category. We also conducted a meta
regression analysis to further test the linear or quadratic effects of
age in the relationship between structural competition and perfor-
mance. The results showed no significant effects (ps.63).
Summary and integration. In sum, the meta-analytic results
indicate that there is no discernible relation or, at very most, an
extremely weak relation between competition and performance.
Two of the three overall analyses exhibited a nonsignificant effect,
and the one significant effect (for trait competitiveness) was so
small as to be of trivial importance. This null or extremely small
relation was also observed in the ancillary analyses omitting out-
lier studies, as well as the ancillary analyses focused on coded
study characteristics.
In a final analysis, we combined all of the studies together,
regardless of conceptualization of competition, to examine the
omnibus competition–performance relation.
Specifically, we converted all of the geffect sizes into the r
metric and applied a random effects model; care must be taken in
interpreting the result from such an analysis, given the combining
of different effect size metrics. The analysis (k174) revealed
that the omnibus average effect size is extremely small and not
statistically significant (r.03; 95% CI [–.00, .06]). In short, the
existing data lead to the conclusion that competition has no note-
worthy relation with performance.
The Opposing Processes Model of Competition and
Performance
As noted at the beginning of this article, there is a widespread
belief among scholars that competition influences performance,
with some theorists contending that the influence is positive and
others contending that it is negative. Both sides of this argument
are espoused vigorously, and this has been the case not just for
decades but for centuries. In this context, our meta-analytic results
are quite sobering, as they seem to suggest that neither side is
correct; instead, they indicate that competition has no noteworthy
relation with performance.
Although this finding may come as a surprise to some, it will
likely resonate with others, such as those who have tried to review
research on the competition–performance relation in narrative
fashion. Surveying the literature in this way, one is struck by the
preponderance of null results, coupled with occasional (often
weak) findings in a positive or negative direction. Narrative re-
viewers have struggled with how to characterize the literature
accordingly; for example, Chertkoff and Mesch (1997) stated the
following: “Given the mixed research results, drawing conclusions
about this literature has presented a difficult challenge” (p. 2; see
also Hinsz, 2005; Lewis & Cooney, 1987). Our meta-analysis
Table 3
Meta-Analysis on Structural Competition
Analysis k(total N)
Mean
weighted g95% CI
2
Overall effect size 81 (5,887) .04 [.08, .16] .22
ⴱⴱ
Overall effect sizes excluding outliers 69 (4,885) .08 [.02, .18] .08
ⴱⴱ
Effect sized based on gender composition
Female dominant (male ratio is .25) 20 (844) .03 [.19, .25] .10
Male dominant (male ratio is .75) 20 (826) .01 [.25, .22] .16
Mixed (male ratio is between .25 and .75) 29 (2,391) .07 [.32, .17] .38
Effect sizes for age groups
Non-adults (18 years old or younger) 41 (2,930) .00 [.20, .20] .34
Adults (older than 18 years) 40 (2,957) .09 [.05, .22] .12
Effect sizes inside and outside the U.S.
U.S. 61 (3,529) .05 [.07, .16] .10
ⴱⴱ
Non-U.S. 20 (2,358) .05 [.25, .34] .38
Effect sizes based on year of publication
1980s and before 52 (3,680) .05 [.13, .22] .29
ⴱⴱ
1990s 17 (1,294) .01 [.20, .19] .09
2000s and after 12 (913) .11 [.14, .36] .13
Effect sizes for type of performance task
Motor/perceptual/sensory 33 (1,406) .10 [.32, .11] .27
ⴱⴱ
Cognitive 48 (4,481) .13 [.01, .27] .17
ⴱⴱ
p.05.
ⴱⴱ
p.01.
1040 MURAYAMA AND ELLIOT
provides an empirical basis for addressing this challenge, and our
findings lead to the firm conclusion that there is no noteworthy
relation between competition and performance.
Inconsistent Mediation
One possible response to our meta-analytic results is to declare
that both sides of the argument regarding the competition–perfor-
mance relation are wrong. An alternative response, however, is to
recognize that our meta-analysis focuses on just one type of
relation between competence and performance—the direct effect.
It is possible to move beyond a focus on this direct effect to a
consideration of the psychological processes evoked by competi-
tion that influence performance attainment. At present, there is a
decided absence of theoretical and empirical work on mediational
processes in this area of inquiry, and we believe that attending to
such mediational processes will help illuminate the nature of the
competition–performance relation. Indeed, we believe that a care-
ful examination of mediation will reveal that both sides of the
ongoing argument are not wrong, as the meta-analytic results
might seem to suggest, but rather that both sides of the argument
are actually right.
The lack of clarity to date regarding the direct effect between
competition and performance is undoubtedly responsible for the
absence of attention to mediational processes. The conventional
wisdom on mediation in the psychological literature has long been
that a direct effect between an independent and dependent variable
must be documented before a mediational process can be consid-
ered (Baron & Kenny, 1986; Judd & Kenny, 1981; see also
Hyman, 1955). In the past several years, however, this conven-
tional wisdom has been refuted by methodologists who have
identified a number of cases in which mediational analysis is valid
in the absence of a direct effect (e.g., inconsistent mediation, distal
mediation; Collins, Graham, & Flaherty, 1998; Kenny, Kashy, &
Bolger, 1998; MacKinnon, Krull, & Lockwood, 2000; Shrout &
Bolger, 2002). The emerging consensus in the literature is that the
analysis of indirect effects can bear considerable fruit, regardless
of the presence or absence of a direct effect (Judd & Kenny, 2010;
MacKinnon, 2008; Preacher & Hayes, 2008b; Zhao, Lynch, &
Chen, 2010).
In the present research, we argue that inconsistent mediation is
operative in the competition–performance relation and that attend-
ing to this form of mediation will explain, both conceptually and
empirically, the absence of a direct effect between competition and
performance. Inconsistent mediation occurs “in multiple mediator
models where mediated effects have different signs”; in such
instances, “the overall relation . . . may actually be zero, yet there
are two opposing mediational processes” (MacKinnon, Fairchild,
& Fritz, 2007, p. 602). That is, in inconsistent mediation, a null
direct effect masks the operation of two different mediational
processes: one that has a positive influence on the dependent
variable and another that has a negative influence on the dependent
variable. Here we propose that competition evokes two distinct
mediational processes, one that facilitates performance and one
that undermines performance. Specifically, we posit performance-
approach and performance-avoidance achievement goals as joint
mediators of the competition–performance relation.
Performance-Approach and Performance-Avoidance
Achievement Goals
In achievement settings, general appetitive or aversive concerns
are evoked by dispositional tendencies and situational construals/
affordances. These desires or fears are presumed to energize be-
havior but do not provide specific guidelines for how one may
accomplish or address the desire or fear that has been activated
(Elliot, 1999). Individuals commonly adopt more concrete aims or
goals that help them guide and direct their behavior with regard to
more specific competence-relevant possibilities (Elliot & Church,
1997). These achievement goals function as concrete tools that
individuals use to strategically regulate their general desires and
fears about success and failure. In prior work, we have conceptu-
alized achievement goals as proximal predictors of achievement-
relevant outcomes (Elliot & Church, 1997); here we take the
additional step of casting them as mediator variables that explain
the indirect influence of dispositional tendencies and situational
construals/affordances on achievement-relevant outcomes.
Achievement goals vary with regard to two basic aspects of
competence—definition and valence (Elliot & McGregor, 2001).
Competence is defined by its standard of evaluation, and three
standards may be identified: a task-based standard (how one is
doing compared to what the task demands), a self-based standard
(how one is doing compared to one’s own intrapersonal trajectory),
and an other-based standard (how one is doing compared to
others). Competence is valenced by its positive focus on success or
its negative focus on failure. The two achievement goals most
pertinent to the present research, performance-approach goals and
performance-avoidance goals, are both grounded in an other-based
standard and focus on a positive or negative normative possibility,
respectively. That is, performance-approach goals represent trying
to do well relative to others, and performance-avoidance goals
represent trying to avoid doing poorly compared to others.
In the present research, we conceptualize performance-approach
and performance-avoidance goals as mediator variables in an ex-
planatory account of the competition–performance relation that we
call the opposing processes model of competition and performance
(see Figure 1b). Research indicates that competition activates
social comparison processes and shifts attention to normative
standards of evaluation (Ames & Ames, 1984; Mussweiler, 2003;
Tesser, 1988). In addition, there are hints in the literature that
competition is associated with both appetitive and aversive pro-
cesses such as excitement and anxiety (Ames, Ames, & Felker,
1977; Fletcher & Nusbaum, 2008; Heggestad & Kanfer, 2000;
Ross, Rausch, & Canada, 2003). Accordingly, we posit that com-
petition positively predicts the adoption of both performance-
approach and performance-avoidance goals (Paths 1 and 3 in
Figure 1b). That is, individuals are posited to regulate their com-
petitive concerns—whether evoked by dispositional tendencies,
situational construals, or structural features of the achievement
environment—by adopting and pursuing specific aims focused on
outperforming or not being outperformed by their peers.
Performance-approach goals have been shown to be associated
with challenge-based affect, cognition, and behavior (e.g., eager-
ness, task-absorption, persistence) that tend to facilitate perfor-
mance, whereas performance-avoidance goals have been linked
with threat-based affect, cognition, and behavior (e.g., worry, task
distraction, self-handicapping) that tend to undermine performance
1041
THE COMPETITION–PERFORMANCE RELATION
(Brodish & Devine, 2009; Darnon, Butera, Mugny, Quiamzade, &
Hulleman, 2009; Elliot, McGregor, & Gable, 1999; Sideridis,
2005; Urdan & Midgley, 2001; Vallerand et al., 2007). As such, it
is not surprising that a considerable amount of research has doc-
umented performance-approach goals as a positive predictor of
performance outcomes and performance-avoidance goals as a neg-
ative predictor (for reviews, see Elliot, 2005; Hulleman, Schrager,
Bodmann, & Harackiewicz, 2010; Kaplan & Maehr, 2007). In
accord with this research, in the proposed model we posit perfor-
mance-approach and performance-avoidance goals as positive and
negative predictors of performance, respectively (Paths 2 and 4 of
Figure 1b). Furthermore, we posit that these two achievement
goals jointly mediate the relation between competition and perfor-
mance and that these joint processes explain the absence of a direct
effect revealed in our meta-analytic review (Figure 1a). Thus,
competition is viewed as facilitating performance to the extent that
it prompts performance-approach goal pursuit and is viewed as
undermining performance to the extent that it prompts perfor-
mance-avoidance goal pursuit; the combination of these mutually
opposing processes is posited to mask the fact that competition
actually has an important impact on performance outcomes. Note
that this model is not only consistent with the extant research
revealing no overall, direct influence of competition on perfor-
mance but also accommodates both of the contrasting positions on
the competition–performance relation described at the outset of
this article. In the following, we present an additional meta-
analysis (using meta-analytic structural equation modeling) and
three new empirical studies that are designed to test the opposing
processes model of competition and performance.
Meta-Analytic Structural Equation Modeling
Meta-analysis is commonly used to synthesize prior empirical
research on the relation between two variables (as in the meta-
analysis reported above), but it is also possible to use meta-
analysis to test a new theoretical model (N. Miller & Pollock,
1995). Herein we used meta-analytic structural equation modeling
(MASEM; Cheung & Chan, 2005; Viswesvaran & Ones, 1995) to
test the validity of the opposing processes model of competition
and performance as represented in the extant data on the variables
in the model: competition, performance-approach goals, perfor-
mance-avoidance goals, and performance. In our MASEM analy-
sis, we first meta-analyzed the correlations of all of the possible
pairs of these variables (i.e., competition and performance-
approach goals, competition and performance-avoidance goals,
competition and performance, performance-approach goals and
performance-avoidancegoals, performance-approach goals and per-
formance, performance-avoidance goals and performance) to com-
pute a pooled correlation matrix. Then, we applied a structural
equation model to the obtained pooled correlation matrix to test
our model (Figure 1b). MASEM allows us to not only estimate
path coefficients but also evaluate the fit of the model to the
meta-analytic data. If all of the path coefficients in Figure 1b
(Paths 1–4) were statistically significant and model fit were good,
this would provide supportive evidence that the observed weak
relation between competition and performance in the previous
meta-analysis could be explained by inconsistent mediational pro-
cesses involving performance-approach and performance-
avoidance goals. Note that even if all of the path coefficients were
statistically significant, model fit could be bad (Kline, 2005); this
would indicate that the weak competition–performance relation is
not well accounted for by the proposed inconsistent mediation
(e.g., the magnitude of one indirect effect may be substantially
larger than that of the other indirect effect, making the cancelation
effect incomplete).
Sample of Studies
The studies included in this meta-analysis were identified via a
thorough search of the literature for studies written in English and
published by April 2011 that investigated the relations of at least
two variables of interest in our model (i.e., competition, perfor-
mance-approach goals, performance-avoidance goals, and perfor-
mance) with human participants. Our previous meta-analysis al-
ready sampled the studies on the relation between competition and
performance; accordingly, our literature search focused on the
remaining five relations (i.e., competition and performance-
approach goals, competition and performance-avoidance goals,
performance-approachgoals and performance-avoidance goals, per-
formance-approach goals and performance, performance-
avoidance goals and performance).
The study collection procedure was analogous to that used for
our previous meta-analysis. First, we searched PsycINFO and
ERIC using pairs of keywords, each of which represents the
variables of interest in our model. As in the previous meta-
analysis, the search terms representing competition included com-
petition,competitive,competitiveness,hypercompetition,hyper-
competitive,reward structure,goal structure, and motivational
climate; likewise, the search terms representing performance in-
cluded performance,achievement,attainment,accomplishment,
and productivity. The search terms representing achievement goals
were those used in Hulleman et al.’s (2010) recent meta-analysis
on achievement goals and performance: performance-approach,
performance approach, performance-avoidance, performance
avoidance, performance, and achievement goals. Second, there is
a
b
Figure 1. A schematic of our hypothesized model linking competition
and performance. Competition does not have a direct effect on performance
(a), but this is due to the positive indirect effect of performance-approach
goals and the negative indirect effect of performance-avoidance goals (b;
the opposing processes model of competition and performance). The
dashed line represents a null (or weak) effect; the solid lines represent a
positive () or negative (–) effect.
1042 MURAYAMA AND ELLIOT
no prior comprehensive meta-analysis on competition and perfor-
mance-approach goals or competition and performance-avoidance
goals, so all studies for these relations were retrieved anew. For the
relations between performance-approach goals, performance-
avoidance goals, and performance, we ensured that all published
studies used in the most recent comprehensive meta-analysis on
achievement goals and performance (Hulleman et al., 2010) were
retrieved. Indeed, we were able to acquire the actual database from
this meta-analysis to use as a foundation for our study collection;
3
this database stopped at 2006, so we continued the study collection
process to add all applicable studies published in 2007 and there-
after in accord with the search criteria delineated above. As noted
above, the database for the competition and performance relation
was the same as that used in our prior meta-analysis. Third, we
searched for additional studies citing any of the major scales used
to assess trait competitiveness, perceived environmental competi-
tiveness, or achievement goals (e.g., Elliot & McGregor, 2001;
Midgley et al., 1998; Smither & Houston, 1992). Fourth, we
searched for additional studies by major contributors to the liter-
atures on the relations under consideration (e.g., Andrew Elliot,
Judith Harakiewicz, Robert Helmreich, David Johnson, Roger
Johnson, Carol Midgley). Finally, we searched the reference sec-
tions of the relevant retrieved studies for additional relevant stud-
ies. We reviewed the abstracts of these retrieved studies and
eliminated those that were clearly not relevant to the relations
under consideration.
We then screened the resulting pool of studies on the following
inclusion criteria. Studies were included if (a) the study dealt
specifically with the relation between the variables of interest
(competition, performance-approach goals, performance-
avoidance goals, and performance), and (b) the study contained
sample sizes and at least one zero-order correlation for the vari-
ables of interest at the individual level. There were a few studies
that experimentally manipulated achievement goals with a neutral
control condition; these studies were included after converting the
geffect sizes into the rmetric. The operational definitions of
competition and performance were the same as those used in the
previous meta-analysis. For performance-approach and perfor-
mance-avoidance goals, we included all studies in which authors
explicitly distinguished between these two types of goals (regard-
less of the labels used); studies that focused only on omnibus
performance goals (i.e., studies not separating the approach and
avoidance components of performance goals) were excluded. Fol-
lowing Hulleman et al. (2010), to retain a precise focus on studies
of achievement goals defined as representations of desired or
undesired end states (Austin & Vancouver, 1996; Elliot & Fryer,
2008; Harackiewicz & Sansone, 1991; Kruglanski, 1996), we
excluded studies in which goals were measured with statements of
positive affect rather than goal-relevant language (e.g., “I feel
successful when . . .”; Duda & Nicholls, 1992).
Our search produced the following number of studies for the
MASEM. For the competition and performance-approach goal
relation, 35 articles were identified, yielding a final sample of 36
studies using 17,669 participants. For the competition and perfor-
mance-avoidance goal relation, 31 articles were identified, yield-
ing a final sample of 32 studies using 14,794 participants. For the
performance-approach goal and performance-avoidance goal rela-
tion, 233 articles were identified, yielding a final sample of 287
studies using 103,263 participants. For the performance-approach
goal and performance relation, 113 articles were identified, yield-
ing a final sample of 136 studies using 42,749 participants. For the
performance-avoidance goal and performance relation, 101 articles
were identified, yielding a final sample of 123 studies using 36,622
participants. For the competition and performance relation, the
sample is the same as that in the previous meta-analysis. In all, our
MASEM has a total sample of 474 studies with 139,464 partici-
pants. In the current MASEM, we did not distinguish between the
three conceptualizations of competition (i.e., trait competitiveness,
perceived environmental competitiveness, and structural competi-
tion), because it is not possible to apply this distinction to the
studies that assessed only performance-approach goals, perfor-
mance-avoidance goals, and performance (or any two of these
variables). The studies included in the MASEM are listed in the
Appendix.
MASEM Procedure
MASEM is generally conducted in two steps. First, all correla-
tions are meta-analyzed to compute a pooled correlation matrix.
Second, structural equation modeling (SEM) is applied to this
pooled correlation matrix to test a model. In conducting our
MASEM analysis, we used a recently developed technique called
two-stage structural equation modeling (Cheung & Chan, 2005). In
this approach, the pooled correlation matrix is estimated by mul-
tivariate meta-analysis (see Gleser & Olkin, 2000) within the
framework of SEM (Cheung, in press; see also Cheung, 2008). In
this process, if a study does not have all relevant correlations, these
nonexisting correlations are treated as missing data. Then, the
obtained pooled correlation matrix is placed into an asymptotic
distribution-free SEM to test the model, using an asymptotic
covariance matrix of the pooled correlations as the weight matrix.
This approach has a number of advantages over traditional
MASEM methods (e.g., Viswesvaran & Ones, 1995). For exam-
ple, because this approach simultaneously estimates pooled corre-
lations with a full information maximum likelihood function, pa-
rameter estimates are much less biased than they are with
traditional methods, especially when there are substantial missing
correlations (see Enders, 2006). This is of particular importance in
our context, given that there are only a few studies that included all
of the variables of interest (none of which tested the proposed
model). In addition, because an asymptotic covariance matrix of
the pooled correlations is used as the weight matrix, we are able to
estimate standard errors precisely. Traditional methods simply use
the point estimate of the pooled correlation matrix and the sample
size is determined by an arbitrary criterion (Cheung & Chan,
2005); as such, variations of the estimated correlations are ignored.
All data analyses were conducted using metaSEM (Cheung,
2011) and OpenMx (Boker et al., 2011) packages in R. A random
effects model was used. When a study included multiple effect
sizes, the average effect size within the study was computed and
used in the meta-analysis.
MASEM Results
The pooled correlation matrix obtained from multivariate meta-
analysis is reported in Table 4. Consistent with the previous
3
We thank Christopher Hulleman for allowing us access to the database.
1043
THE COMPETITION–PERFORMANCE RELATION
(univariate) meta-analysis, the correlation between competition
and performance is very weak and not statistically significant (r
.03; 95% CI [.00, .06]). Note that the values are slightly different
from the previous meta-analysis, because multivariate meta-
analysis takes into account the covariation with the other correla-
tions (see Gleser & Olkin, 2000). The other correlations are all
statistically significant.
Of central importance, MASEM supported our hypothesized
model (Figure 1b). As predicted, competition was positively asso-
ciated with performance-approach goals (␤⫽.41; 95% CI [.36,
.47]) and performance-avoidance goals (␤⫽.29; 95% CI [.24,
.34]). In addition, performance-approach goals were positively
associated with performance (␤⫽.15; 95% CI [.12, .17]), whereas
performance-avoidance goals were negatively associated with per-
formance (␤⫽⫺.17; 95% CI [.19, .15]). Importantly, the
model provided a good fit to the data:
2
(1) 1.03, p.31,
CFI 1.00, TLI 1.00, RMSEA 0.000. This suggests that the
weak relationship between competition and performance is ex-
plained by an inconsistent mediational process involving perfor-
mance-approach and performance-avoidance goals.
Next, we used a (parametric) bootstrapping approach to test the
significance of the indirect effects (see MacKinnon, Lockwood,
Hoffman, West, & Sheets, 2002). The analyses showed that both
the positive indirect effect (competition 3performance-approach
goals 3performance) and the negative indirect effect (competi-
tion 3performance-avoidance goals 3performance) were sig-
nificant (estimates .06 and –.05, respectively, ps.01). Table
5 summarizes the obtained results.
Summary
The MASEM results indicated that competition is not directly
related to performance but is indirectly related via achievement
goals. Performance-approach and performance-avoidance goals
were validated as mutually opposing mediators of the
competition–performance relation, and it is these opposing pro-
cesses that produced the weak direct relation between competition
and performance observed in the previous meta-analysis.
New Empirical Studies
MASEM is a flexible and powerful data analytic tool, and our
use of MASEM herein yielded clear support for the validity of our
hypothesized opposing processes model of competition and per-
formance. Our original meta-analytic results were included within
the MASEM analysis; thus, the MASEM results effectively doc-
umented that the weak competition–performance relation observed
in our original meta-analysis can be explained by the opposing
processes model. However, the MASEM approach to testing our
model is post hoc and indirect, and there are some inherent
limitations to using this approach to test the specific research
questions under consideration.
First, as noted earlier, it is not possible to distinguish between
the three conceptualizations of competition (i.e., trait competitive-
ness, perceived environmental competitiveness, and structural
competition) in our MASEM analysis, because this distinction
cannot be applied to the many studies that assessed only perfor-
Table 4
Multivariate Meta-Analysis Results on the Correlations Between Competition, Performance-
Approach Goals, Performance-Avoidance Goals, and Performance
Variable 1 2 3 4
1. Competition
2. Performance-approach goals .41 [.36, .46]
3. Performance-avoidance goals .30 [.25, .35] .41 [.38, .43]
4. Performance .03 [.00, .06] .10 [.08, .12] .12 [.14, .10] —
Note. k 472 (N139,388). Numbers in square brackets represent 95% confidence intervals.
Table 5
Path Coefficients and Indirect Effects in MASEM and Studies 1–3
Direct effect model
(Figure 1a)
Opposing processes model of competition and performance (Figure 1b)
Effect via performance-approach goals Effect via performance-avoidance goals
(0) Competition to
performance
(1) Competition to
Pap goals
(2) Pap goals to
performance
Indirect
effect
(3) Competition to
Pav goals
(4) Pav goals to
performance
Indirect
effect
MASEM 0.03 0.41
ⴱⴱ
0.15
ⴱⴱ
0.06
ⴱⴱ
0.29
ⴱⴱ
0.17
ⴱⴱ
0.05
ⴱⴱ
Study 1 0.03 0.50
ⴱⴱ
0.42
ⴱⴱ
0.21
ⴱⴱ
0.33
ⴱⴱ
0.46
ⴱⴱ
0.15
ⴱⴱ
Study 2 0.09 0.35
ⴱⴱ
0.44
ⴱⴱ
0.15
0.25
ⴱⴱ
0.45
ⴱⴱ
0.11
ⴱⴱ
Study 3 0.13 0.39
ⴱⴱ
0.44
0.17
0.46
ⴱⴱ
0.45
0.20
Note. Numbers in parentheses correspond to those in Figure 1. MASEM meta-analytic structural equation modeling; Pap performance-approach;
Pav performance-avoidance.
p.05.
ⴱⴱ
p.01.
1044 MURAYAMA AND ELLIOT
mance-approach goals, performance-avoidance goals, and perfor-
mance (or two of these variables). Second, some of the relations in
the MASEM model may be seen as susceptible to confounding
variables that could inflate the observed relation. For example,
prior research has shown that perceptions of competence are
positively associated with both performance-approach goals and
performance (e.g., Elliot & Church, 1997; Marsh & Craven, 2006);
as such, the observed link between performance-approach goals
and performance in the MASEM analyses could be inflated or
even spurious. MASEM focuses on simple zero-order correlations
and cannot address this possibility. Third, in many, if not most, of
the studies contributing to the MASEM analysis, the data were
collected in a single session, which can also lead to covariate
inflation. The temporal separation of construct assessments is
recommended to address this problem (Podsakoff, MacKenzie,
Lee, & Podsakoff, 2003). Fourth, there is considerable variation in
the achievement goal assessments included in our MASEM anal-
ysis, and some measures include content unrelated to the perfor-
mance-approach and performance-avoidance goal constructs (e.g.,
self-presentation concerns, self-worth concerns; Elliot & Mu-
rayama, 2008; Elliot et al., 2011). Hulleman et al. (2010) have
shown that these nuisance factors in achievement goal measures
artificially depress relations between achievement goals and per-
formance.
In light of these limitations, we deemed it important to supple-
ment our MASEM findings with new empirical studies designed to
put the opposing processes model to direct empirical test while
also attending to the aforementioned issues. In the following, we
present three such studies, each of which tested the model using a
different conceptualization of competition—trait competitiveness
(Study 1), perceived environmental competitiveness (Study 2), and
structural competition (Study 3). In each of the studies, we in-
cluded measures of perceived or prior competence and other
possible confounding variables to examine the robustness of the
focal relations. Furthermore, we designed Studies 1 and 2 to
include considerable temporal separation between the competition,
achievement goal, and performance assessments to minimize the
likelihood of covariation inflation. Finally, we used recently de-
veloped achievement goal assessments that were explicitly de-
signed to eliminate construct contamination. Supportive data from
these new studies would nicely complement our MASEM results,
and the two sets of findings together would represent a particularly
powerful validation of the opposing processes model of competi-
tion and performance. Table 6 lists the primary variables focused
on in each of the three studies and provides descriptive statistics
for these variables.
Study 1
In Study 1, we tested the hypothesized model in the context of
a college classroom using trait competitiveness as the independent
variable, exam performance as the dependent variable, and class-
room achievement goals as mediator variables. We expected a null
relation between trait competitiveness and exam performance but
anticipated that this null effect would be explained by the opposing
influences of performance-approach goals (positive) and perfor-
mance-avoidance goals (negative). We examined the focal rela-
tions controlling for possible confounding variables to ensure that
any observed findings were not mere artifacts of these other
variables. Control variables included participants’ general ability
(SAT scores), perceived ability (general perceived competence and
specific competence expectancies), and response bias (impression
management and self-deceptive enhancement).
Method
Participants. A total of 301 (110 male, 191 female) students
at a U.S. university participated in return for extra course credit. In
this and all subsequent studies, participation was restricted to
native English speakers. Participants were enrolled in an
introductory-level psychology course where evaluation was based
on a normative grading structure. The mean age of participants was
19.60; ethnicity was as follows: 216 Caucasian, 26 African Amer-
ican, 28 Asian, 17 Hispanic, and 14 unspecified.
Procedure. Participants reported their demographic informa-
tion and their verbal SAT score in a large group session during the
first week of the semester. Later that same week, they completed
measures of trait competitiveness and general perceived compe-
tence in a take-home questionnaire packet. The following week,
they completed a measure of response bias in another take-home
Table 6
Descriptive Statistics and Internal Consistencies of the Main Variables in Studies 1–3
Variable MSDObserved range Cronbach’s
Study 1
Trait competitiveness 3.39 0.82 1.00–5.00 .77
Performance-approach goals 4.71 1.51 1.00–7.00 .93
Performance-avoidance goals 4.57 1.47 1.00–7.00 .89
Exam performance 77.4 13.0 31–100
Study 2
Perceived class competitiveness 2.59 1.05 1.00–5.00 .91
Performance-approach goals 3.72 1.08 1.00–5.00 .94
Performance-avoidance goals 3.40 1.20 1.00–5.00 .94
Exam performance 83.6 11.1 44–100
Study 3
Performance-approach goals 6.43 1.80 2.33–9.00 .92
Performance-avoidance goals 6.22 1.90 1.33–9.00 .86
Baseline anagram performance 5.16 2.96 0–15
Postmanipulation anagram performance 6.02 3.14 0–14
1045
THE COMPETITION–PERFORMANCE RELATION
questionnaire packet. Participants reported their performance-
approach and performance-avoidance goals for the class, as well as
their competence expectancy for the class, in a large group session
approximately 3 weeks later (1 week prior to their first exam).
Exam performance data (possible range 0–100) were acquired
from the course instructor. For all assessments, participants were
assured that their responses would remain confidential and would
in no way influence their course grade.
Measures. Spence and Helmreich’s (1983) five-item compet-
itiveness measure from the WOFO scale was used to assess trait
competitiveness (e.g., “I feel that winning is important in both
work and games”). Participants responded ona1(strongly dis-
agree)to5(strongly agree) scale (␣⫽.77). Elliot et al.’s (2011)
achievement goal measure was used to assess participants’ perfor-
mance-approach goals (three items, e.g., “[My goal is] to do better
than my classmates on the exams in this class”) and performance-
avoidance goals (three items, e.g., “[My goal is] to avoid doing
worse than other students on the exams in this class”). Participants
responded ona1(strongly disagree)to7(strongly agree) scale
(s.93 and .89, respectively).
Several measures were used to assess control variables (in
addition to participants’ verbal SAT score). Law, Elliot, and Mu-
rayama’s (2012) four-item General Perceived Competence mea-
sure was used to assess broad perceptions of ability (e.g., “I do
well at most things I try”). Participants responded ona1(strongly
disagree)to5(strongly agree) scale (␣⫽.82). Elliot and Church’s
(1997) two-item measure was used to assess competence expec-
tancies for the class (e.g., “I expect to do well in this class”).
Participants responded ona1(strongly disagree)to7(strongly
agree) scale (␣⫽.85). Response bias was assessed with two
20-item subscales from Paulhus’s (1991) Balanced Inventory of
Desirable Responding. The subscales include impression manage-
ment (IM) and self-deceptive enhancement (SDE). Participants
responded ona1(not true)to7(very true) scale; half of the items
for each subscale represent desirable statements (IM, e.g., “I
always obey laws, even if I’m unlikely to get caught”; SDE, e.g.,
“I always know why I like things”), and half represent undesirable
statements (IM, e.g., “When I was young I sometimes stole
things”; SDE, e.g., “I have not always been honest with myself”).
Participants received one point for each extreme response (s
.68 and .72 for IM and SDE, respectively).
Results and Discussion
In this and all subsequent studies, the full information maximum
likelihood method was used to avoid loss of information due to
missing data (Enders, 2006; Schafer & Graham, 2002).
Trait competitiveness as a direct predictor of exam perfor-
mance. First, we examined trait competitiveness as a direct
predictor of exam performance (see Figure 1a). We used a latent
variable model to prevent false negative (i.e., null) effects due
to attenuation caused by measurement error (Bollen, 1989).
Trait competitiveness was represented as a latent variable (with
individual items as indicators), whereas exam performance was
represented as an observed variable. As expected, trait compet-
itiveness was not a significant predictor of exam performance
(␤⫽.03, p.63).
The mediational model. We then investigated the hypothe-
sized opposing processes model in which performance-approach
and performance-avoidance goals serve as joint mediators of the
indirect relation between trait competitiveness and exam perfor-
mance (see Figure 1b). Trait competitiveness, performance-
approach goals, and performance-avoidance goals were modeled
as latent variables (with individual items as indicators), whereas
exam performance was represented as an observed variable. In this
and all subsequent studies, we allowed for correlated errors of the
performance-approach and performance-avoidance goal variable,
as recommended in multiple mediator models (Preacher & Hayes,
2008a).
As predicted, trait competitiveness was a positive predictor of
both performance-approach goals (␤⫽.50, p.01) and perfor-
mance-avoidance goals (␤⫽.33, p.01). In addition, perfor-
mance-approach goals were a positive predictor of exam
performance (␤⫽.42, p.01), whereas performance-avoidance
goals were a negative predictor (␤⫽–.46, p.01). The model
provided a good fit to the data:
2
(50) 114.23, p.01, CFI
.95, TLI .93, RMSEA .065, indicating that the weak direct
effect can be explained by the opposing effects of performance-
approach and performance-avoidance goals. We used a bootstrap-
ping approach to test the significance of the indirect effects
(MacKinnon et al., 2002). The analyses showed that both the
positive indirect effect (trait competitiveness 3performance-
approach goals 3exam performance) and the negative indirect
effect (trait competitiveness 3performance-avoidance goals 3
exam performance) were significant (standardized estimates .21
and –.15, respectively, ps.01). Table 5 summarizes the obtained
results.
Control variable analyses. Next, we repeated each of the
above analyses controlling for variables that could influence the
focal relations. Specifically, we (independently) controlled for
SAT score, general perceived competence, competence expectan-
cies for the class, and IM and SDE response biases. As may be
seen in Table 7, each of the nonsignificant (direct effect) and
significant (indirect effect) findings from the primary analyses
remained the same in these analyses.
In sum, the results indicate that trait competitiveness is not a
direct predictor of exam performance but is an indirect predictor
via achievement goals. Performance-approach and performance-
avoidance goals were validated as mutually opposing mediators of
the trait competitiveness-performance relation, and it is these op-
posing processes that produced the null direct relation between
trait competitiveness and performance. The obtained results were
not a function of participants’ general ability (SAT score), per-
ceived ability (general perceived competence and specific compe-
tence expectancies), or response bias (impression management and
self-deceptive enhancement).
Study 2
Study 2 sought to conceptually replicate Study 1 using percep-
tions of class competitiveness, rather than trait competitiveness, as
the independent variable. Again we examined the focal relations
controlling for the possible confounding variables used in Study 1.
Method
Participants. A total of 240 (75 male, 165 female) students at
a U.S. university participated in return for extra course credit.
1046 MURAYAMA AND ELLIOT
Participants were enrolled in an introductory-level psychology
course where evaluation was based on a normative grading struc-
ture. The mean age of participants was 19.15; ethnicity was as
follows: 176 Caucasian, 10 African American, 32 Asian, 11 His-
panic, and 11 unspecified.
Procedure. As in Study 1, participants reported their demo-
graphic information and their verbal SAT score in a large group
session at the beginning of the first week of the semester. At the
end of the first week, they completed a measure of general per-
ceived competence in a take-home questionnaire packet. During
the second week of the semester, participants completed a per-
ceived class competitiveness measure and a response bias measure
in another take-home questionnaire packet. Participants reported
their performance-approach and performance-avoidance goals for
their midterm exam, as well as their competence expectancy for
the exam, in a large group session approximately 2 months later (1
week prior to the exam). Exam performance data were acquired
from the course professor (possible range 0–100). For all
assessments, participants were assured that their responses would
remain confidential and would in no way influence their course
grade.
Measures. To assess perceived class competitiveness, we
created a five-item face valid measure for this study (e.g., “In this
class, it seems that students are competing with each other”).
Participants responded ona1(strongly disagree)to5(strongly
agree) scale (␣⫽.91). Elliot and Murayama’s (2008) achievement
goal measure was used to assess participants’ performance-
approach goals (three items, e.g., “My goal is to perform better
than the other students on the exam”) and performance-avoidance
goals (three items, e.g., “My goal is to avoid performing poorly
compared to others on the exam”). Participants responded on a 1
(strongly disagree)to5(strongly agree) scale (s.94 and .84,
respectively).
For control variables, in addition to participants’ verbal SAT
score, we assessed their general perceived competence (␣⫽.82)
and response bias (IM and SDE; s.67 and .70) with the same
measures used in Study 1. Competence expectancies were assessed
with the same measure used in Study 1 (␣⫽.87) but focused on
the exam, not the class.
Results and Discussion
Perceived class competitiveness as a direct predictor of exam
performance. Analogous to Study 1, we first examined per-
ceived class competitiveness as a direct predictor of exam perfor-
mance. We used a latent variable model; perceived class compet-
itiveness was represented as a latent variable (with individual
items as indicators), whereas exam performance was represented
as an observed variable. As expected, perceived class competitive-
ness was not a significant predictor of exam performance (␤⫽.09,
p.15).
The mediational model. We then investigated the hypothe-
sized opposing processes model in which performance-approach
and performance-avoidance goals serve as joint mediators of the
indirect relation between perceived class competitiveness and
exam performance. Perceived class competitiveness, as well as
performance-approach and performance-avoidance goals, were
modeled as latent variables with individual items as indicators,
whereas exam performance was represented as an observed vari-
able.
As predicted, perceived class competitiveness was a positive
predictor of both performance-approach goals (␤⫽.35, p.01)
and performance-avoidance goals (␤⫽.25, p.01). In addition,
performance-approach goals were a positive predictor of exam
performance (␤⫽.44, p.01), whereas performance-avoidance
goals were a negative predictor (␤⫽–.45, p.01). Again, the
model provided a good fit to the data:
2
(50) 110.95, p.01,
CFI .96, TLI .95, RMSEA .071, indicating that the weak
direct effect can be explained by the opposing effects of perfor-
mance-approach and performance-avoidance goals. Testing the
significance of the indirect effects (as in Study 1) showed that both
the positive indirect effect (perceived class competitiveness 3
performance-approach goals 3exam performance) and the neg-
ative indirect effect (perceived class competitiveness 3perfor-
Table 7
Path Coefficients and Indirect Effects With Controlling Variables in Studies 1 and 2
Direct effect
model
(Figure 1a)
Opposing processes model of competition and performance (Figure 1b)
Effect via performance-
approach goals
Effect via performance-
avoidance goals
(0) Competition to
performance
(1) Competition to
Pap goals
(2) Pap goals to
performance Indirect effect
(3) Competition to
Pav goals
(4) Pav goals to
performance Indirect effect
Study 1 0.03/0.02 0.50
ⴱⴱ
/0.51
ⴱⴱ
0.42
ⴱⴱ
/0.35
ⴱⴱ
0.21
ⴱⴱ
/0.18
ⴱⴱ
0.33
ⴱⴱ
/0.36
ⴱⴱ
0.46
ⴱⴱ
/0.36
ⴱⴱ
0.15
ⴱⴱ
/0.13
ⴱⴱ
0.04/0.01 0.50
ⴱⴱ
/0.48
ⴱⴱ
0.42
ⴱⴱ
/0.35
ⴱⴱ
0.21
ⴱⴱ
/0.17
ⴱⴱ
0.35
ⴱⴱ
/0.33
ⴱⴱ
0.46
ⴱⴱ
/0.41
ⴱⴱ
0.17
ⴱⴱ
/0.14
ⴱⴱ
0.05/0.05 0.50
ⴱⴱ
/0.50
ⴱⴱ
0.42
ⴱⴱ
/0.41
ⴱⴱ
0.21
ⴱⴱ
/0.20
ⴱⴱ
0.32
ⴱⴱ
/0.34
ⴱⴱ
0.44
ⴱⴱ
/0.45
ⴱⴱ
0.14
ⴱⴱ
/0.15
ⴱⴱ
Study 2 0.09/0.11 0.35
ⴱⴱ
/0.34
ⴱⴱ
0.44
/0.45
ⴱⴱ
0.15
ⴱⴱ
/0.15
ⴱⴱ
0.25
ⴱⴱ
/0.24
ⴱⴱ
0.45
ⴱⴱ
/0.44
ⴱⴱ
0.11
ⴱⴱ
/0.10
ⴱⴱ
0.08/0.06 0.35
ⴱⴱ
/0.32
ⴱⴱ
0.43
ⴱⴱ
/0.32
ⴱⴱ
0.15
ⴱⴱ
/0.10
0.25
ⴱⴱ
/0.25
ⴱⴱ
0.44
ⴱⴱ
/0.36
ⴱⴱ
0.11
ⴱⴱ
/0.09
0.09/0.08 0.35
ⴱⴱ
/0.36
ⴱⴱ
0.45
ⴱⴱ
/0.50
ⴱⴱ
0.16
ⴱⴱ
/0.18
ⴱⴱ
0.24
ⴱⴱ
/0.24
ⴱⴱ
0.46
ⴱⴱ
/0.52
ⴱⴱ
0.11
ⴱⴱ
/0.12
ⴱⴱ
Note. Numbers in parentheses correspond to those in Figure 1. For each column and variable, the first value is from the initial analysis, the second value
is from the analysis controlling for SAT score, the third value is from the analysis controlling for general perceived competence, the fourth value is from
the analysis controlling for competence expectancies for the class, the fifth value is from the analysis controlling for impression management, and the sixth
value is from the analysis controlling for self-deceptive enhancement. Pap performance-approach; Pav performance-avoidance.
p.05.
ⴱⴱ
p.01.
1047
THE COMPETITION–PERFORMANCE RELATION
mance-avoidance goals 3exam performance) were significant
(standardized estimates .15 and –.11, respectively, ps.01).
The results are summarized in Table 5.
Control variable analyses. Again, we repeated each of the
above analyses controlling for variables that could influence the
focal relations. Specifically, we (independently) controlled for
SAT score, general perceived competence, competence expectan-
cies for the exam, and IM and SDE response biases. As may be
seen in Table 7, each of the nonsignificant (direct effect) and
significant (indirect effect) findings from the primary analyses
remained the same in these analyses.
In sum, the results indicate that perceived class competitiveness
is not a direct predictor of exam performance but is an indirect
predictor via achievement goals. Performance-approach and per-
formance-avoidance goals were validated as mutually opposing
mediators of the perceived class competitiveness-performance re-
lation, and it is these opposing processes that produced the null
direct relation. The obtained results were not a function of partic-
ipants’ general ability (SAT score), perceived ability (general
perceived competence and specific competence expectancies), or
response bias (impression management and self-deceptive en-
hancement).
Study 3
In Study 3, we sought to conceptually replicate Studies 1 and 2
using structural competition, rather than trait competitiveness or
perceptions of competitiveness, as the independent variable, and
anagram performance as the dependent variable. That is, we ma-
nipulated competition in the lab and examined the effect of this
manipulation on anagram performance both directly and via task-
specific performance-approach and performance-avoidance goals.
We included a baseline performance measure to ensure that any
observed relations with task performance would not be a mere
artifact of preexisting differences in ability.
Method
Participants and experimental design. Fifty-six (14 male,
42 female) students at a U.S. university participated in return for
extra course credit. The mean age of participants was 19.83, and
ethnicity was as follows: 43 Caucasian, 11 Asian, 1 Hispanic, and
1 unspecified. Participants were randomly assigned to either a
competition condition or a control condition.
Procedure and materials. The experiment was run with two
participants at a time; the participants were placed in adjoining lab
rooms but never saw or interacted with each other in any way.
Once both participants arrived, the experimenter opened the doors
to the individual lab rooms and stood between the rooms to
provide instructions to the two participants simultaneously.
First, participants were instructed to complete the practice (base-
line) anagram task for 5 min. Then, participants in the competition
condition were informed that they would complete another version
of the 5-min anagram task but that this time they would do so in
competition with the person in the other room. They were asked to
try their best in competing against the other person and were told
that they would receive information regarding their score and
whether they had won, lost, or tied after completion of the task.
Participants in the control condition were simply informed that
they would complete another version of the 5-min anagram task.
They were asked to try their best in solving the anagrams and were
told that they would receive information regarding their score after
completion of the task (see Tauer & Harackiewicz, 1999, for a
similar manipulation). Immediately following the manipulation,
participants reported their performance-approach and perfor-
mance-avoidance goals for the upcoming anagram task using
Elliot and Murayama’s (2008) achievement goal measure on a 1
(strongly disagree)to9(strongly agree) scale (s.92 and .86,
respectively). Then participants completed the (postmanipulation)
anagram task.
We used anagrams for the experimental task, because previous
research has shown that anagrams are sensitive to motivational
manipulations (e.g., Elliot, Maier, Moller, Friedman, & Meinhardt,
2007; A. Miller & Hom, 1990). We developed two different sets of
anagram tasks (one for baseline and one for postmanipulation),
both of which involved solving 16 five-letter, single-solution ana-
grams over a 5-min period. The anagram sets were derived from a
published list (Mayzner & Tresselt, 1966), and the anagram items
were selected on the basis of average solution time to ensure that
each set would represent a moderate level of difficulty.
Results and Discussion
Competition manipulation as a direct predictor of anagram
performance. First, we examined the direct effect of the com-
petition manipulation on postmanipulation anagram performance
controlling for baseline anagram performance (to increase the
statistical power to detect the direct effect). We used structural
equation modeling; the competition manipulation (competition
1, control 0), baseline anagram performance, and postmanipu-
lation anagram performance were all represented as observed
variables. Baseline anagram performance was a positive predic-
tor of postmanipulation anagram performance (␤⫽.61, p
.01); as expected, the competition manipulation did not have a
significant effect on postmanipulation anagram performance
(␤⫽–.13, p.32).
The mediational model. We then investigated the hypothe-
sized opposing processes model in which performance-approach
and performance-avoidance goals serve as joint mediators of the
indirect relation between the competition manipulation and post-
manipulation anagram performance (controlling for baseline ana-
gram performance). Given the modest sample size in the experi-
ment, performance-approach and performance-avoidance goals, as
well as the competition manipulation, baseline anagram perfor-
mance, and postmanipulation anagram performance, were repre-
sented as observed variables.
As predicted, the competition manipulation had a positive in-
fluence on both performance-approach goals (␤⫽.39, p.01)
and performance-avoidance goals (␤⫽.46, p.01). Baseline
anagram performance was a positive predictor of postmanipulation
anagram performance (␤⫽.58, p.01) and, more important,
performance-approach goals were a positive predictor of postma-
nipulation anagram performance (␤⫽.44, p.05), whereas
performance-avoidance goals were a negative predictor (␤⫽–.45,
p.05). The model provided a good fit to the data:
2
(1, N
56) 0.00, p.95, CFI 1.00, TLI 1.08, RMSEA .00,
indicating that the weak direct effect can be explained by the
opposing effects of performance-approach and performance-
1048 MURAYAMA AND ELLIOT
avoidance goals. Testing the significance of the indirect effects (as
in the prior studies) showed that both the positive indirect effect
(competition manipulation 3performance-approach goals 3ana-
gram performance) and the negative indirect effect (competition
manipulation 3performance-avoidance goals 3anagram perfor-
mance) were significant (standardized estimates .17 and –.20,
respectively, ps.05). The results are summarized in Table 5.
In sum, the results indicate that structural competition is not a
direct predictor of anagram performance but is an indirect predic-
tor via achievement goals. Performance-approach and perfor-
mance-avoidance goals were validated as mutually opposing me-
diators of the structural competition–performance relation, and it is
these opposing processes that produced the null direct relation. The
obtained results were not a function of preexisting differences in
ability.
Sex Effects in Studies 1–3
We conducted multigroup analyses for each study to test for
possible sex differences in our data. Specifically, we used a log-
likelihood ratio test to examine if the effects observed in the
preceding analyses were invariant across males and females (Bol-
len, 1989). The analyses indicated that for Studies 1, 2, and 3 the
path coefficients were not significantly different across sex for
both the direct effect and mediational models (ps.10). Each of
the nonsignificant (direct effect) and significant (indirect effect)
findings from the primary analyses remained the same in these
analyses.
General Discussion
The relation between competition and performance is an impor-
tant topic of inquiry, integral to conceptual and practical issues in
many different psychological disciplines. Despite considerable
research activity addressing this relation, little clarity or agreement
has been reached to date, and polarizing debate is the norm in this
literature. It is in this context that we carried out the present work,
designed to systematically review prior empirical research and to
propose and test a new model of the competition–performance
relation.
Overview of Results
We commenced our research with a meta-analysis that focused
on each of the three basic conceptualizations of competition—trait
competitiveness, perceived environmental competitiveness, and
structural competition. For trait competitiveness and perceived
environmental competitiveness, the meta-analysis represents the
first of its kind; for structural competition, it represents a much
needed updating of the last comprehensive meta-analysis con-
ducted 30 years ago. In two of the three instances (i.e., perceived
environmental competitiveness and structural competition), the
meta-analysis revealed a nonsignificant relation, and in the other
(i.e., trait competitiveness), the significant relation was so small
(r.05) as to be of trivial importance. These results held across
ancillary analyses focused on omitting outliers and attending to
various study characteristics. An omnibus meta-analysis collapsing
across the three conceptualizations also yielded a nonsignificant
relation. Given the prevalence of competition in daily life and the
multitude of theorists positing the existence of a competition-per-
formance relation (be it negative or positive), these results may
seem disappointing, if not disconcerting. A straightforward inter-
pretation of these results would lead to the conclusion that com-
petition has no noteworthy influence on performance. We refute
this straightforward interpretation herein, providing, in its stead, a
conceptual model that explains the reason for the null relation.
Our model, the opposing processes model of competition and
performance, posits that the observed null relation is actually the
result of antagonistic appetitive and aversive processes that cancel
each other out (Figure 1b). We conducted an additional meta-analysis
to put this model to test, and the results yielded clear support for the
model. The MASEM analysis revealed that opposing indirect effects
involving performance-approach and performance-avoidance
achievement goals explained the null competition–performance link
observed in the original meta-analysis. Furthermore, we also con-
ducted three new empirical studies to directly test our model and
address the limitations inherent in the MASEM analysis. The
results consistently yielded clear support for the opposing pro-
cesses model. These studies revealed no effect for the direct
relation between competition and performance (consistent with our
initial meta-analytic results) but revealed inconsistent mediation
via performance-approach and performance-avoidance achieve-
ment goals (consistent with our MASEM results). Importantly, our
findings supported the proposed model for each of the three
different conceptualizations of competition, across participants’
sex and a variety of different control variables (general perceived
competence, specific competence expectancies, impression man-
agement, self-deceptive enhancement, SAT score, and baseline
performance), and with achievement goal assessments that exclude
theoretically extraneous components. Taken together, the findings
from our MASEM analysis and our three new studies provide
extremely strong evidence for the validity of the opposing pro-
cesses model of competition and performance.
Connection to Existing Theoretical Work
Given the conceptual and practical importance of the competition–
performance relation and its relevance across multiple disciplines, it is
not surprising that many scholars over the years have offered theories
or approaches that either directly address or are clearly relevant to this
topic. In the following, we give an overview of the most prominent of
these theories and approaches, with an eye toward delineating how
they explain the competition–performance relation and how their
account is similar to or different from that offered by the opposing
processes model.
Social facilitation theories. In a famous social–
psychological experiment, Triplett (1898; see also Fe´re´, 1887)
demonstrated that children do better on a simple fishing reel task
when they perform alongside another child. This research spawned
a voluminous and still active literature on social facilitation (for
reviews, see Aiello & Douthitt, 2001; Bond & Titus, 1983; Guerin,
1993). Although the initial experiment indicated that performance
was enhanced in the presence of others, subsequent research
showed that performance could be impaired in such instances as
well; both performance enhancement and impairment in the pres-
ence of others now fall under the rubric of social facilitation. A
basic premise of social facilitation research is that performance is
enhanced on simple tasks but is impaired on complex tasks (Za-
1049
THE COMPETITION–PERFORMANCE RELATION
jonc, 1965). Many explanations have been offered for this task
difficulty moderation, none of which have risen to the level of
consensus (Aiello & Douthitt, 2001).
Although the initial impetus for social facilitation research was
a desire to understand the competition–performance relation (see
Triplett, 1898), researchers soon separated competition from social
presence per se and explicitly focused on the latter (Allport, 1920).
As such, social facilitation theories are not directly relevant to the
opposing processes model. Nevertheless, a few observations may
be offered in comparative fashion. First, we think the opposing
processes model can be straightforwardly extended to apply to
social facilitation effects and, more specifically, to account for task
difficulty moderation. The presence of others should enhance
competence valuation, the degree to which individuals care about
doing well or poorly (Harackiewicz, Manderlink, & Sansone,
1984), thereby enhancing goal commitment (Elliot & McGregor,
2001). Facing a simple or well-learned task under such circum-
stances should promote challenge appraisals and a focus on suc-
cess, which are known to foster performance-approach goals
(McGregor & Elliot, 2002), whereas facing a complex or difficult
task should prompt threat appraisals and a focus on failure, which
are known to evoke performance-avoidance goals (Chalabaev,
Major, Cury, & Sarrazin, 2009). Performance-approach and per-
formance-avoidance goals, in turn, have beneficial and detrimental
effects on performance, respectively (as documented in our
MASEM analysis and new empirical studies; for a compatible
account within the social facilitation literature focused on cardio-
vascular responses to stressors, see Blascovich, Mendes, Hunter, &
Salomon, 1999).
Second, meta-analytic research has implicated approach and
avoidance relevant personality constructs as moderators of social
facilitation effects, independent of any influence of task difficulty.
Specifically, Uziel (2007) has shown that social presence facili-
tates the performance of individuals with a “positive orientation”
(i.e., extraverts and those high in self-esteem), but debilitates the
performance of individuals with a “negative orientation” (i.e.,
those who are highly anxious and have low self-esteem); these
patterns held across levels of task difficulty. Again, an extended
opposing processes model can straightforwardly account for such
findings. The positive dispositions in question have been shown to
be strongly associated with performance-approach goals, whereas
the negative dispositions have been shown to be strongly associ-
ated with performance-avoidance goals (Elliot & Thrash, 2002;
Heimpel, Elliot, & Wood, 2006). It is likely that these dispositions
prompt their corresponding goals in achievement situations,
which, in turn, influence performance outcomes as specified in our
MASEM analysis. To reiterate, the social facilitation literature
does not focus on the competition–performance relation per se, but
the opposing processes model seems easy to apply to the effects
documented in this literature.
Social interdependence theory. From Deutsch’s (1949,
1962) original formulation to the present, social interdependence
theory has played an important role in explaining the effects of
competition and cooperation on various outcomes, including per-
formance (Deutsch, 1949; Johnson & Johnson, 1989, 2005). In
social interdependence theory, competition is defined as the exis-
tence of negative interdependence, where individuals perceive that
they can obtain their objectives only if the other individuals with
whom they are competitively linked fail to obtain their objectives.
Cooperation, on the other hand, is defined as the existence of
positive interdependence, where individuals perceive that they can
reach their objectives only if the other individuals with whom they
are cooperatively linked also reach their objectives. A third cate-
gory of interdependence, labeled individualistic, is said to exist
when individuals perceive that they can reach their objectives
regardless of whether others reach their objectives (Deutsch,
1962). In the main, competitive relations among individuals are
posited to reduce effective behavior, increase negative emotional
attachment to others, and undermine task performance (Johnson &
Johnson, 1989, 2005).
Importantly, both conceptually and empirically, the primary
focus of social interdependence theory is on cooperation among
individuals and its beneficial effects on psychological functioning
(including performance); competitive and individualistic relations
between individuals get relatively little attention and are essen-
tially used as comparisons for the central focus, cooperation (John-
son & Johnson, 2005). Meta-analytic research on performance
outcomes clearly supports the central premise of social interde-
pendence theory—that cooperative relations lead to more positive
outcomes than competitive and individualistic relations (Johnson
et al., 1981; Qin et al., 1995; Roseth et al., 2008; Stanne et al.,
1999). However, a close reading of the published meta-analytic
results reveals that the competitive versus individualistic contrast
is null for performance outcomes, not favoring individualistic
relations as one might anticipate on the basis of the theory.
Researchers in this tradition have begun to allocate attention to the
possibility (initially suggested as early as 1987 by Johnson and
Johnson), that some types of competition may lead to positive
performance outcomes (Stanne et al., 1999; Tjosvold et al., 2006).
Specifically, competition may be beneficial when individuals are
explicitly assured that everyone has a chance to win (i.e., construc-
tive competition). Preliminary supportive data for this premise
have been reported (Stanne et al., 1999; Tjosvold et al., 2006), but
little research has been conducted to date.
Interdependence theory proposes that the way independence is
structured determines how individuals interact with each other
which, in turn, influences performance outcomes (Deutsch, 1962;
Johnson, 2003). Thus, with regard to mediation, interpersonal
rather than intrapersonal, constructs are the main focus. Occasional
reference is made to achievement goals—mastery and perfor-
mance goals—but only as approach-based “desired outcomes”
(Roseth et al., 2008, p. 224). Furthermore, these goals are either
construed as analogous to forms of interdependence (with coop-
eration and competition mapping onto mastery and performance
goals, respectively; Roseth et al., 2008) or cast as broad motives
that dictate the degree to which individuals compete in a construc-
tive manner (Tjosvold et al., 2006). Thus, the foci of social
interdependence theory and the opposing processes model are
clearly very different. In contrast to social interdependence theory,
the opposing processes model focuses on competition per se, posits
that the overall effect of competition on performance is null,
proposes two mutually canceling approach and avoidance pro-
cesses that account for this null relation, and uses performance-
approach and performance-avoidance goals as situation-specific
mediators of competition effects. The two models do not contradict
or conflict with one another, but rather have different emphases
and may be viewed as complementary analyses of competition–
performance relation. Social interdependence theory is broader in
1050 MURAYAMA AND ELLIOT
focus and attends to cooperation as well as competition, while the
opposing processes model delves more deeply into competition per
se and delineates the intrapersonal processes through which com-
petition has beneficial or detrimental effects.
Cognitive evaluation theory. Cognitive evaluation theory
(Deci & Ryan, 1985) specifies how social and environmental
factors, including competitive structures, help or hinder human
motivation. From the perspective of this framework, competition
typically engenders a controlling rather than an autonomy support-
ive environment, and this shifts the perceived locus of causality
from internal to external, resulting in decreased intrinsic motiva-
tion (Deci & Ryan, 1985). A number of studies have provided data
consistent with this perspective, although competitive outcome
(i.e., win vs. lose) has been identified as a critical moderator
variable (Deci, Betley, Kahle, Abrams, & Porac, 1981; Reeve &
Deci, 1996; Vallerand & Reid, 1984; Vansteenkiste & Deci, 2003).
With regard to competition, this theory focuses primarily on
intrinsic motivation and makes no explicit predictions regarding
the competition–performance relation. Intrinsic motivation is pre-
sumed to be an important energizer of behavior that facilitates
optimal functioning; intrinsic motivation and task performance are
thought to be related in some instances but not others (Deci,
Koestner, & Ryan, 1999; Deci & Ryan, 1985). Cognitive evalua-
tion theory explains competition effects at the level of needs and
motives, rather than goals. Competition is posited to undermine
intrinsic motivation (in most instances) because it interferes with
one’s basic need to feel autonomous (Deci & Ryan, 1985).
Although the opposing processes model does not address the
competition-intrinsic motivation relation, it seems straightforward
to extend the model to account for this link. Research on the
competition-intrinsic motivation relation has yielded somewhat
inconsistent results, with some studies showing negative effects,
but others showing null or even positive effects (see Reeve & Deci,
1996; Tauer & Harackiewicz, 2004); we suspect that a meta-
analysis of the literature would reveal a small negative effect. Our
MASEM analysis clearly showed that competition is a positive
predictor of both performance-approach and performance-
avoidance goals, so the first component of the extended model is
already in place. Achievement goal research indicates that perfor-
mance-avoidance goals are a clear negative predictor of intrinsic
motivation, whereas performance-approach goals tend to be unre-
lated or show a positive relation (Elliot & Moller, 2003; Finney,
Pieper, & Barron, 2004; Harackiewicz, Barron, Pintrich, Elliot, &
Thrash, 2002; Lopez, 1999; Van Yperen, 2006). Thus, the nature
of the direct competition-intrinsic motivation relation seen in the
literature may be a function of the opposing influences of perfor-
mance-approach and performance-avoidance goals, with the some-
what negative overall relation being a function of the somewhat
stronger negative influence of performance-avoidance goals.
Given that performance and intrinsic motivation are widely re-
garded as two of the most important outcomes in competition
settings, we have already commenced meta-analytic work on the
competition-intrinsic motivation relation to test these possibilities.
Motivational traits approach. Kanfer and Heggestad (1997;
see also Kanfer & Ackerman, 2000) proposed a taxonomic frame-
work of motivational traits and skills in an attempt to organize
theory and research on work motivation. They identify two super-
ordinate, integrative motivational traits—achievement and anxi-
ety—as well as two lower level motivational skills—emotion
control and motivation control—as important variables in work
motivation contexts. Achievement is conceptualized as an appet-
itive construct that encompasses competitive excellence and mas-
tery, whereas anxiety is conceptualized as an aversive construct
that encompasses fear of failure and test anxiety. Achievement and
anxiety are posited to influence the development of emotional and
motivational skills, with those high in achievement selecting them-
selves into challenging situations that facilitate skill development
and those high in anxiety avoiding challenging situations, which
leads to poor skill development (Kanfer & Heggestad, 1997). In
general, motivational skills are posited to have a proximal influ-
ence on behavior and motivational traits are posited to have a distal
influence on behavior; no specific predictions with regard to
performance are proffered.
The opposing processes model shares some surface similarities
with the motivational traits approach, in that both focus (in part) on
trait competitiveness, both use the approach-avoidance distinction,
and both posit two levels of constructs that have differential effects
(proximal and distal) on behavior. Aside from these general com-
monalities, however, the two perspectives are very different. First,
the purpose of the motivational traits approach is to provide an
integrative taxonomy of individual differences in work motivation,
whereas the purpose of the opposing processes model is to provide
a motivational account of the competition–performance relation.
Second, the motivational traits approach conceptualizes competi-
tion entirely in dispositional terms, whereas the opposing pro-
cesses model incorporates other, nondispositional, aspects of com-
petition as well. Third, the motivational traits approach does not
incorporate a situation-specific goal construct, whereas such goals
are at the centerpiece of the opposing processes model. Fourth, the
motivational traits approach identifies constructs that may be in-
volved in the competition–performance relation but does not de-
lineate any specific hypothesis about this relation, whereas the
opposing processes model both identifies the relevant constructs
and proposes specific hypotheses about how they work in concert
to predict and explain performance outcomes.
Goal-setting theory. Locke and Latham’s (1990, 2002) goal
setting theory is a well-established framework that focuses on the
goal-performance relation. The basic premise of the theory is that
commitment to specific, challenging goals enhances task perfor-
mance (Locke & Latham, 1990). Although competition is not a
central aspect of goal-setting theory, Locke and Latham (Locke,
1968; Locke & Latham, 1990) have offered a clear, specific
prediction regarding the competition–performance relation. Spe-
cifically, they posit that competition is an incentive that facilitates
performance attainment; competition is thought to foster positive
goal-setting processes (e.g., enhanced goal commitment, adoption
of more challenging goals) which, in turn, are beneficial for
performance.
Goal-setting theory and the opposing processes model share a
central premise, namely, that goals mediate the relation between
competition and performance. In addition, in both approaches, the
qualitative nature of goals is important in predicting performance
outcomes. However, there are several important differences be-
tween the two frameworks. Unlike the opposing processes model,
goal-setting theory construes competition in exclusively appetitive
terms as a positive incentive that has a direct positive influence on
performance (Hinsz, 2005). Also unlike the opposing processes
model, goal-setting theory conceptualizes goals entirely in appet-
1051
THE COMPETITION–PERFORMANCE RELATION
itive terms; no mention is made of the approach–avoidance dis-
tinction or the possibility that goals may focus on the avoidance of
negative possibilities. A final difference between the two ap-
proaches concerns the performance-mastery distinction: the oppos-
ing processes model makes use of this distinction and focuses on
performance-based goals per se; Lock and Latham (2002) have
made reference to the performance–mastery distinction in some of
their work, but not within the context of competition. Thus, al-
though the opposing processes model and goal-setting theory share
some important features, goal-setting theory is limited in the
context of the competition–performance relation, in that it can
account for neither the null direct effect found in our meta-analysis
nor the undermining of performance via the performance-
avoidance goal process.
Choking under pressure. Baumeister and Showers (1986)
noted that individuals sometimes “choke under pressure,” defined
as performing suboptimally under pressure conditions. They de-
fined pressure as the presence of situational incentives or cues for
optimal or superior performance, with competition identified as
one important form of pressure situation. Competition, whether
explicitly established or implicitly encouraged, is posited to in-
crease the probability that choking will occur. Baumeister and
Showers also identified three types of variables that increase the
likelihood of choking under pressure: task complexity (more chok-
ing is predicted on difficult or complex tasks); efficacy expectan-
cies (more choking is predicted when efficacy expectancies are
low); and individual differences in anxiety (a high level leading to
more choking), self-consciousness (a high level leading to more
choking), and skill level (a low level leading to more choking).
The choking under pressure analysis of competition is compat-
ible with the opposing processes model in that both approaches
predict that competition can undermine performance attainment.
Indeed, it is likely that performance-avoidance goals are at least
one mediator of the choking under pressure effect (for relevant
empirical research, see Brodish & Devine, 2009: Cury, Elliot, Da
Fonseca, & Moller, 2006). However, there are clear and important
differences between the two approaches. Unlike the opposing
processes model, the emphasis in the choking under pressure
analysis is primarily on the aversive implications of competition
and its negative influence on performance. In this respect, it is
essentially the avoidance-based analog of goal-setting theory, as
detailed above. In addition, unlike the opposing processes model,
the choking under pressure analysis does not make use of the goal
construct in accounting for performance in competition settings.
Thus, much like goal-setting theory, the choking under pressure
analysis is limited with regard to the competition–performance
relation, in that it can account for neither the null direct effect
found in our meta-analysis nor the bolstering of performance via
the performance-approach goal process.
In sum, there are several different theories and approaches
available that address or are relevant to the competition–per-
formance relation. What is perhaps most striking about our
overview of these theories and approaches is how few of them
focus directly and specifically on competition per se, much less
on the competition–performance relation. In most, competition
is one of several foci, and even the impressive, well-developed
theories that seem dedicated to explicating competition effects at
first glance prove on closer examination to be more focused on
other phenomena (e.g., social presence for social facilitation the-
ory, cooperation for social interdependence theory). It is also
important to note that none of the existing theories or approaches
contradict or are incompatible with the opposing processes model
in any way. In several instances, independent nonoverlapping
ground is covered (e.g., cognitive evaluation theory). In others,
contradiction may seem apparent (e.g., goal-setting theory’s stance
that competition enhances performance or the prediction from the
choking under pressure analysis that competition undermines per-
formance), but in these instances the existing explanations are best
seen as accurate but incomplete accounts that are entirely compat-
ible with the specific components of the broader, more compre-
hensive opposing processes model. Indeed, the opposing processes
model offers a more comprehensive and precise account of the
competition–performance relation than any of the other existing
theories and approaches.
Model Expansion
The present research demonstrates the validity and utility of the
opposing processes model of competition and performance, and a
logical next step is to consider how the model may be expanded
and further developed in future research. One promising avenue
would be to extend the model to incorporate different types of
competition. At present, competition is considered in terms of its
presence/absence or high/low amount, albeit with regard to three
different conceptualizations (trait, perceived environment, envi-
ronmental structure). It would be helpful to extend the model to
consider the performance implications of different qualitative
types of competition such as zero-sum, face to face, and intergroup
(Deutsch, 1949; Stanne et al., 1999; Tauer & Harackiewicz, 2004).
Another possibility would be to extend the model beyond compe-
tition to include cooperation, following the lead of social interde-
pendence theory. It is likely that the positive influence of cooper-
ation on performance outcomes, so clearly documented by Johnson
and Johnson (1989, 2005) and their colleagues (Roseth et al., 2008;
Stanne et al., 1999; Tjosvold et al., 2006), is mediated by mastery-
approach goals. Unlike performance-based goals, which are rooted
in social comparison, mastery-approach goals focus on attaining
task-based or intrapersonal competence (Dweck, 1986; Nicholls,
1984). These goals have an inconsistent relation with performance,
but theorists have hypothesized that they are beneficial for perfor-
mance outcomes in several instances (Elliot, 2005; Midgley, Ka-
plan, & Middleton, 2001). We think cooperative contexts are one
such instance, as the task–intrapersonal focus of mastery-approach
goals seems highly compatible with the interdependent emphasis
of these settings (Poortvliet, Janssen, Van Yperen, & Van de
Vliert, 2009; Tossman, Kaplan, & Assor, 2008).
Future work on the opposing processes model would also do
well to adopt a more expansive focus with regard to performance
outcomes, and outcomes more generally. In the present empirical
investigations, we examined the influence of competition on two
different performance variables—exam performance and anagram
performance. Achievement tasks vary considerably in terms of the
types of skills and abilities required (e.g., motor, perceptual, cog-
nitive, etc.) and the domain in which the performance takes place
(the classroom, the workplace, the ball field, etc.). Our meta-
analytic data indicated that the competition–performance relation
was the same (null or very weak) in each of these instances,
suggesting that comparable mutually opposing processes were
1052 MURAYAMA AND ELLIOT
operative accordingly. Nevertheless, subsequent work directly ex-
amining this issue would be welcomed. In addition, other out-
comes beyond performance, such as intrinsic motivation (as dis-
cussed earlier), control beliefs, subjective well-being, and
physical health are also worthy of empirical attention. To the
extent that subsequent research yields supportive findings for
outcomes beyond performance, the label of our model should be
broadened accordingly to the opposing processes model of
competition (per se).
Expansion is also possible with regard to the mediator variables
in the model. We focused on achievement goals as mediators in the
present research, because they have been shown to have tremen-
dous explanatory and predictive utility in prior work on achieve-
ment motivation (Dweck, 1999; Elliot, 2005; Nicholls, 1989).
Indeed, we view achievement goals as integral to a motivationally
based conceptualization of competition and have difficultly envi-
sioning a satisfactory account of competition and performance
absent this construct. As such, when considering other mediational
candidates, we view them as complements to rather than replace-
ments for performance-approach and performance-avoidance
goals. Regarding the link between competition and achievement
goals, we think challenge and threat appraisals (or their corre-
sponding cardiovascular activity; Blascovich & Mendes, 2000) are
good candidates for inclusion, as they represent dynamic appetitive
and aversive evaluations of the potential for gain or loss in the
achievement context (Lazarus, 1991; see our earlier discussion on
social facilitation) that have been linked to achievement goal
pursuit in prior work (see Chalabaev et al., 2009; Elliot & Reis,
2003; McGregor & Elliot, 2002). To the extent that competition
evokes challenge appraisals, the pursuit of performance-approach
goals is likely, and to the extent that that competition evokes threat
appraisals, the pursuit of performance-avoidance goals is likely.
Regarding the link between achievement goals and performance,
we think that task absorption and task distraction are good candi-
dates for inclusion, as prior research has shown that these indica-
tors of cognitive immersion carry important information about the
quality and effectiveness of achievement goal pursuit (Cury, Elliot,
Sarrazin, Da Fonseca, & Rufo, 2002; Harackiewicz & Sansone,
1991; Lee, Sheldon, & Turban, 2003). Task absorption likely
mediates the positive influence of performance-approach goals on
performance, whereas task distraction likely mediates the negative
influence of performance-avoidance goals on performance. Exam-
ination of these relations in future research promises to yield a
more detailed and complete understanding of the way in which
performance-approach and performance-avoidance goals them-
selves operate as mediators of the competition–performance rela-
tion (and beyond).
Our model posits that competition evokes both performance-
approach and performance-avoidance goal pursuit and that these
appetitive and aversive processes have a mutually antagonistic
influence on performance. The fact that our meta-analytic and new
empirical results revealed a null effect suggests that these appeti-
tive and aversive processes are usually of similar strength. This
need not always be the case; in instances when one process is
considerably stronger than the other, a positive or negative influ-
ence of competition on performance might be witnessed. That is,
moderator variables undoubtedly exist that affect the relative
weights of appetitive or aversive mediation effects. In fact, our
previous overview of other relevant theoretical perspectives may
be consulted to derive promising moderator variable candidates,
such as task difficulty, evaluative pressure, self-esteem, and self-
consciousness. A systematic investigation of moderation would be
welcomed in future research, as it is relevant to both theory and
practice.
Broader Considerations and Contributions
Competition is a topic of widespread interest across scholarly
disciplines and levels of analysis. Views on competition not only
vary with regard to individual psychological processes, our focus
herein but also with regard to educational and occupational struc-
tures, economic and political systems, and broad metatheoretical
assumptions about human nature and the purpose of life. Given
this intellectual context, we think it is important to highlight that
our analysis of competition and performance is meant to be de-
scriptive and explanatory, not prescriptive. By documenting that
competition, when accompanied by performance-approach goals,
facilitates performance outcomes, we are not advocating for com-
petitive traits or structures or for the use of normatively focused
forms of self-regulation. Likewise, by documenting that competi-
tion, when accompanied by performance-avoidance goals, under-
mines performance outcomes, we are not advocating against com-
petitive traits or structures or against the use of normatively
focused forms of self-regulation. On the basis of the present
conceptual and empirical research, it is possible to state in em-
phatic terms that competition can be both beneficial for and
detrimental to performance. However, formulating a position on
the relative merits or demerits of competition for individuals,
organizations, and societies is a complex and variegated task well
beyond the present scope.
The opposing processes model fits nicely into the rich tradition
of hierarchical models in achievement motivation literature that
integrate both general motivational orientations and more specific
forms of self-regulation, such as strategies, tactics, and goals
(Cattell, 1957; Elliot, 1997; Emmons, 1989; Lewin, 1935; Little,
1989; McClelland, 1951; McDougal, 1908; Murray, 1938; Nuttin,
1984; Rotter, 1954; Sheldon, 2004). In the opposing processes
model, performance-approach and performance-avoidance goals
represent specific forms of self-regulation, and competition (in its
various forms) is presumed to prompt a general motivational
concern about normative competence that is then regulated by the
two goals. A noteworthy strength of this and other hierarchically
based models is that they, unlike many motivation frameworks, are
able to account for both the energization (i.e., initial instigation)
and direction of behavior.
In addition to contributing to the competition literature, and the
achievement motivation literature more generally, the present re-
search also provides a much needed illustration of the importance
of attending to inconsistent mediation in social science research
(MacKinnon, 2008). Despite a clear declaration by contemporary
methodologists that mediation can be present in the absence of a
direct effect (Kenny et al., 1998; MacKinnon et al., 2000), empir-
ical work exhibiting this type of pattern remains rare, suggesting a
continuing reticence to embrace this perspective. This is unfortu-
nate, as inconsistent mediational processes are likely quite com-
monplace (Zhao et al., 2010); if so, failing to explore such pro-
cesses can only retard theoretical and empirical progress.
Accordingly, we hope that the present documentation of a highly
1053
THE COMPETITION–PERFORMANCE RELATION
robust (replicated several different ways), conceptually sensible
form of inconsistent mediation will help coax potentially reticent
researchers to move past the now outdated convention of waiting
for establishment of a direct effect before examining mediation.
Conclusion
Summary statements about the benefits and ills of competition
are often quite strident, and this seems true regardless of whether
they come from the person on the street, the pundit or politician on
television, or the scholar in academia. The take-home message
from the present research is that at the level of individual psycho-
logical processes, competition appears to be neither entirely ben-
eficial nor entirely detrimental to performance. Rather, our work
indicates that the competition–performance relation varies as a
function of the type of achievement goals pursued. Accordingly,
our research highlights the need for a nuanced, integrative ap-
proach to this important area of inquiry.
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