Intercollegiate athletics and institutional fundraising: a meta-analysis.
Martinez, J. Michael ; Stinson, Jeffrey L. ; Kang, Minsoo 等
Introduction
Since the late 1970s, numerous academic studies have purported to
examine the effects of intercollegiate athletics on fundraising. Still,
nearly 30 years later, disparate research designs and conflicting
results have left researchers lacking the ability to confidently comment
on how athletic programs influence donors to higher education. The goals
of this meta-analysis are to clarify the common knowledge developed
through previous research and to provide direction for continued
research of how sports programs affect fundraising at colleges and
universities.
Many of the weaknesses of this research stream lie in the various
research designs employed. While most studies use fundraising, in one
way or another, as the dependent variable, the calculation of
fundraising varies dramatically. Some studies use aggregated
institutional giving as the dependent variable (e.g., Gaski & Etzel,
1984; McCormick & Tinsley, 1990; Humphreys & Mondello, 2007;
Stinson & Howard, 2007), while other studies examine individual
donor behavior (e.g., Stinson & Howard 2004). Some studies include
only alumni donors (e.g., Baade & Sundberg, 1996; Grimes &
Chressanthis, 1994), while other studies include both alumni and
non-alumni donors (e.g., Stinson & Howard, 2004; Humphreys &
Mondello, 2007). Further, several studies have focused only on
fundraising for intercollegiate athletics programs (e.g., Mahony,
Gladden, & Funk, 2003; Gladden, Mahony, & Apostolopoulou, 2005;
McEvoy, 2005), while other studies have included academic fundraising or
general institutional support (e.g., Cunningham & ConchiFicano,
2002; Grimes & Chressanthis, 1994). Some studies have focused
entirely on private schools (e.g., Shulman & Bowen, 2001; Turner,
Meserve, & Bowen, 2001), other studies have examined only public
schools (e.g., Grimes & Chressanthis, 1994; Stinson & Howard
2004), while yet other studies have included both public and private
schools in the sample (e.g., Rhoads & Gerking, 2000; Humphreys &
Mondello, 2007). Finally, many studies have essentially been case
studies of a single institution (e.g., McCormick & Tinsley, 1990;
Grimes & Chressanthis, 1994; Stinson & Howard 2004), while other
studies have examined panel data for multiple institutions (e.g., Baade
& Sundberg, 1996; Tucker, 2004; Stinson & Howard, 2007;
Humphreys & Mondello, 2007). The end result of the inconsistency in
research design is a set of confusing, often conflicting results.
The conclusions of these previous studies can essentially be
classified into three categories: studies concluding there is little or
no relationship between athletics and fundraising, studies concluding
that intercollegiate athletics programs have a positive influence on
fundraising (either for athletics and/or institutional support), and
studies concluding that athletics programs have a negative effect on
institutional fundraising (i.e., crowding-out effects). Several early
studies concluded that intercollegiate athletics programs have little or
no influence on fundraising. Notably, Gaski and Etzel (1984) constructed
over 100 regressions on giving at multiple institutions and concluded
that athletics programs had little influence on giving. More recently,
Shulman and Bowen (2001) asserted in their study of academically elite,
private schools that there was not a strong relationship between
intercollegiate athletics and fundraising. In a literature review, Frank
(2004) also concluded that the lack of consistent results across the
research stream was suggestive of the lack of a strong relationship
between athletics and giving.
Equally as many studies have concluded that there is a positive
relationship between intercollegiate athletics and institutional
fundraising. Sigelman and Carter (1979) were among the first authors to
identify a positive effect of intercollegiate athletics on alumni
giving. McEvoy (2005) also linked athletic performance positively to
athletic fundraising. McCormick and Tinsley (1990) not only concluded
that athletics had a positive relationship with athletic fundraising,
but also with academic support. These authors noted that at Clemson
University, a ten percent increase in athletic support was associated
with a five percent increase in academic support. Similarly, Stinson and
Howard (2008) concluded that athletic success enhanced both athletic and
academic giving for NCAA Division I-AA and I-AAA institutions. Daughtry
and Stotlar (2000) identified a positive effect of a NCAA Division II
football national championship on institutional fundraising. Other
authors have found that when included with other institutional variables
and factors, intercollegiate athletics has a significant positive
influence on fundraising, though other institutional factors, such as
measures of academic quality may be more important determinants of
giving (i.e., Rhoads & Gerking 2000, Cunningham & Conchi-Ficano
2002).
The third category of findings centers on potential crowding-out
effects, where athletics programs may have a negative effect on
institutional support. Crowding out effects in this context would
typically be caused by donors increasing their giving to athletic
programs and simultaneously decreasing their support of academic
programs. Sperber (1990, 2000) asserted that crowding-out effects are
responsible for a lack of academic support at some institutions, though
he did not offer any empirical support. A case study at the University
of Oregon (Stinson & Howard, 2004) concluded that crowding-out
effects were possibly occurring amongst donors making annual gifts of
over $1,000. A 2007 multi-institutional study extended these results,
concluding that at most schools athletics fundraising was growing more
quickly than academic fundraising and that crowding-out effects were
most likely to occur at schools falling outside the top tier of
academically ranked schools (Stinson & Howard, 2007).
As this brief review of research indicates, it is quite difficult
to confidently draw any generalizable conclusions as to the effect
intercollegiate athletics programs have on institutional giving. Given
the number of studies conducted, and the over 30 years of research
available, a meta-analysis is appropriate. There are four primary
advantages to pursuing a meta-analytical approach in summarizing this
research stream (Wilson, 2001): meta-analysis is a structured research
technique that allows formal review of previous empirical work;
meta-analysis is more sophisticated than traditional qualitative review
studies; effect sizes across the studies may identify relationships that
would otherwise be missed; and meta-analysis allows for the coordination
and management of the various findings from each of the included
studies. Successful meta-analysis will be useful in identifying the
common effects across the research stream and for providing strong
direction for future research.
The purpose of this study is to perform a meta-analytic review of
the available scholarly research on the relationship between
intercollegiate athletic success and institutional giving.
Methodology
Data Sources
The initial search for studies relevant to this meta-analytic
review was conducted utilizing a selection of available Internet-based
research databases including: ABI/INFORM Complete, Academic Search
Premier, Dissertations and Theses Full-text from Proquest, EBSCO Electronic Journal Service, ERIC (Educational Resource Information
Center), General OneFile, JSTOR, Management & Organization Studies:
A SAGE Full-Text Collection, OmniFile Full-text Mega Edition, Social
Sciences Full-text, and Web of Science. Among the key search terms
included were combinations of athletic success, philanthropy,
fundraising, institutional giving, and development. Articles published
from 1975 through 2008 were included in this selection process.
According to the literature, 1976 was the first year a peer-reviewed
publication featured an article quantitatively investigating the
relationship between intercollegiate athletic success and philanthropic giving (Budig, 1976). Additionally, manual ancestor searches and
electronic descendent searches were conducted to compile additional
studies, including relevant unpublished doctoral dissertations. This
initial search resulted in more than 75 publications in the initial pool
of studies. While the initial pool included more than 75 possible
studies, a narrowing process was applied to determine a more targeted
list of eligible studies for inclusion in the meta-analysis (i.e.,
quantitative exploration, comparable variables, etc.). The narrowing
process focused on compiling a list of studies that met the criteria to
conduct what DeCoster (2004) suggests is a "reasonable target for
synthesis" (p. 6). For example, initial searches may include a
study that highlights the relationship between athletic success and the
benefits to a university. However, after further evaluation of that
study, the relationship may make a mention of increases in institutional
giving as a possible benefit, although no actual quantitative
examination took place for that specific relationship. Following this
process, a total of 26 publications remained from which the final
dataset was taken. Although more than 65 percent of the initial pool was
delimited, this is not uncommon in meta-analytic reviews (DeCoster,
2004). Further classification of the remaining 26 studies was completed
as well, and that process is outlined in the following study selection
process.
Study Selections
The collection of 26 studies was narrowed further based on whether
or not the following criteria were included in the study: 1) measures of
athletic success (win percentage, postseason appearances, and rankings);
2) a related outcome measure of philanthropic giving; 3) and
designations of school type (public/private), sports of interest
(football, basketball, etc.), level of athletic competition (NCAA
divisions), pertinent giving targets (university, athletics, or
academics), and giving bases (all donors or alumni donors only). Studies
without appropriate statistical measures (i.e., regression weights)
reported were excluded, as were studies that lacked the applicable data
of interest. For example, a study which focused on the selected
variables of interest may have been removed for only reporting the
significant p-values of the relationship and not for including
corresponding regression weights or correlations. Thus, the final sample
consisted of 14 studies published between 1979 and 2008. A brief summary
of included studies appears in Table 1.
Data Extraction
In concordance with the meta-analysis procedures outlined by
DeCoster (2004), studies were then coded with pertinent study
identifiers and select moderator variables extracted from the overall
pool. Moderating variables included: 1) school type (public, private, or
other); 2) giving targets (university, athletics, or academics); 3)
giving base (all donors or alumni donors only); 4) NCAA classification
(Division I, Division IAA, or other); and 5) sports of interest
(football, basketball, or other)
Data Analysis
As previously mentioned, meta-analytic techniques for research
synthesis are made stronger because of the added statistical evaluation
used to aggregate the results of the included studies. Research
indicates that the strength of any meta-analysis is the concept of
effect size (DeCoster, 2004; Lipsey & Wilson, 2001). Effect size is
the measure by which we can compare the varying degrees of relationships
or "effects" between variables as reported in different
studies. In the case of the current inquiry, the relationship explored
in each study is essentially based on the effect of athletic success on
fundraising. Although the included studies each operationalize athletic
success in different ways (i.e., winning percentage, bowl appearances,
etc.), evaluation of the overall relationship between athletic success
and fundraising can be achieved using the meta-analytic techniques,
which standardize the reported effects into one succinct metric of
evaluation, effect size (Lipsey & Wilson, 2001).
Effect Size
For each of the selected studies, effect sizes were determined
utilizing the product-moment correlation effect size (ESr) as outlined
by Lipsey and Wilson (2001). Included studies reported relationships in
three different ways: correlations (e.g., Sigelman & Carter 1979),
t-ratios (e.g., Grimes & Chressanthis, 1994), and F-ratios (e.g.,
Daughtrey & Stotlar, 2000). Therefore, studies reporting values as
either t-ratios or F-ratios were converted to correlations using the
following formulas suggested by Lipsey and Wilson (2001, p. 201).
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
Furthermore, Lipsey and Wilson (2001) suggest that each of the
calculated effect sizes be standardized using Fisher's
[Z.sub.r]-transform (p. 63) in order to be able to generate proper
standard error for each effect size, which is a key component for
determining inverse variance weight. While the effect size statistic is
the building block in any meta-analysis, the concept of inverse variance
weight (w) also is important. The inverse variance weight allows
researchers to more accurately compare effect sizes coming from varying
sample sizes. Thus, an effect size with a sample size of 10 can easily
be compared to an effect size calculated from a sample size of 100 by
comparing the inverse weight variance. Accordingly, each effect size for
the study was determined using the following equation:
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Once each of the necessary effect sizes and inverse variance
weights were calculated, a test of homogeneity (Q) was conducted through
SPSS for overall effect size. The test of homogeneity is an important
step in the meta-analysis process as it allows researchers to
"determine if a grouping of effect sizes from different studies
shows more variation than would be expected from sampling error
alone" (Lipsey & Wilson, 2001, p. 8). Once the effect sizes are
determined to be homogeneous or not, meta-analytic researchers must then
determine whether a fixed-effects model or a random-effects model would
be evaluated. According to Lipsey and Wilson, when the distribution of
effect sizes is homogeneous (i.e., a non-significant Q value), the
effect sizes differ from the population only because of subject-level
sampling error (p. 119), prompting the use of the fixed-effects model.
However, when the distribution is found to be heterogeneous (i.e., a
significant Q-value), then a random effects model is evaluated, taking
into account not only the differing effect size due to sampling error
but also because of some other variables, operationalized as moderators.
In the latter case, the moderator analyses were to be followed. Using
the methods described by Lipsey and Wilson (2001), the effect of each
moderator variable was examined. This final statistical procedure was
calculated through SPSS version 17.0.
Results
Studies Selected
The initial search for applicable studies resulted in 26 empirical
studies that focused on the relationship of athletic success and
institutional giving in NCAA institutions. Among the 26 articles, 24
were from peer-reviewed journals, while two were unpublished
dissertations. Following the inclusion and exclusion process, a final
count of 14 studies were found, from which 75 different effect sizes
could be calculated (Table 2).
Tests of Homogeneity
Homogeneity analysis (Q = 932.3, df = 74) was significant (p <
.001). As a result, the random effects model was selected. The
relationship between athletic success and giving resulted in a weighted
mean effect size of 0.12 and a 95-percent confidence interval of 0.08
and 0.16. A minimum effect size (ESr) was -0.027 and a maximum effect
size was 1.472, with a weighted standard deviation of 0.169. Athletic
success, across the included studies, has a statistically significant,
positive effect on giving.
Because of the heterogeneity of effect size distribution, follow-up moderator analysis was conducted.
Moderator Analysis
Moderator analysis for philanthropic giving (see Table 3) was
tabulated on five moderators: institution type, giving target, giving
base, NCAA classification, and sport of interest. Within meta-analytic
studies, the aforementioned Q-statistic is necessary for comparison.
While the overall Q-statistic allows researchers to establish the
homogeneity of the data, evaluation of the [Q.sub.between] statistic
allows researchers to determine how much of the variance can be
explained by the moderating variables (DeCoster, 2004). The results
indicate that only institution type did not significantly influence the
strength of the relationships between athletic success and giving. For
giving target, [Q.sub.between] showed a value of 20.91 (df = 2) and was
significant (p < .001). While the effect sizes for all three groups
are small (<.1), the results indicate that athletic success has a
stronger influence on total institutional giving than either athletic or
academic giving independently.
The [Q.sub.between] for giving base was 15.10 (df = 1) and was
significant (p < .001). The effect size for alumni giving was twice
the effect size for all donors (.08 vs. .04). Alumni donors appear to be
more strongly influenced by athletic success than the general
population.
[Q.sub.between] for NCAA classification had a value of 45.05 (df =
2) and was significant (p < .001). As shown in Table 3, the effect
size for giving at Division I institutions was substantially higher than
I-AA and other levels of NCAA membership. The effect of athletic success
on giving is significantly higher at NCAA I-A schools.
Sport of interest had a [Q.sub.between] value of 26.57 (df= 2) and
was significant (p < .001). Consistent with previous research
documenting the power of football, football success had an effect size
more than twice as large as the effect size for basketball (.09 vs.
.04). The strongest effect on giving, at least at schools that compete
in football, appears to be the success of the football program.
Institution type was the only non-significant (p=.072) moderator in
the study with a [Q.sub.between] value of 5.26 (df = 2). The results of
this meta-analysis suggest that donors at both public and private
schools are influenced similarly by the success of athletic programs at
those institutions.
Discussion
The primary objective of this study was to provide some conclusion
to the seemingly disparate research results reported over the last 30
years regarding the influence intercollegiate athletics programs have on
institutional fundraising. Using the differing ranges of correlation
effect size (small [ES.sub.r] [less than or equal] .10; medium
[ES.sub.r] = .25; large [ES.sub.r] [greather than or equal] .40) as
cited by Lipsey and Wilson (2001), the overall results suggest that
athletic success ([ES.sub.r] = .121) has a small but significant
relationship with institutional giving (p < .001). In the aggregate,
the 30 years of studies included in this meta-analysis indicate that
intercollegiate athletics are an important influence on donors. However,
the small overall effect sizes are indicative of the varying degrees of
influence athletics has had in the reported studies. Both institutional
heterogeneity and unmeasured influences on giving limit the ability to
generalize results across institutions. Thus, further analysis was
undertaken to better understand the influence of several potentially
important moderating variables. (See Table 4 for a Summary of Results
and Implications.)
The analysis of moderating variables provides clarification of the
circumstances in which intercollegiate athletics are most likely to have
the strongest influence on institutional giving. Specifically, this
study identified four important moderators: giving target, alumni status
of donor, NCAA classification, and focal sport of interest.
This study found that the effects of athletic success on giving
were strongest when total institutional giving was considered, as
opposed to athletic or academic giving specifically. Intuitively this
finding makes sense. Studies examining aggregated institutional giving
will pick up the positive effects of giving to both athletic and
academic programs. This result, and the overall effect size of .121, is
consistent with the findings of broader institutional studies that have
concluded athletics has a small but positive relationship with
institutional fundraising efforts (Rhoads & Gerking, 2000;
Cunningham & Conchi-Ficano, 2002). Specific analysis on the
differential impacts of athletic success on athletic versus academic
giving reveals that athletic giving is only slightly more impacted by
athletic success than academic giving. This finding, perhaps more than
anything, underscores the potential value of athletics programs to
assist in the growth of academic and institutional fundraising. While
the effect sizes are small, it is clear that athletic success has a
significant influence on all types of institutional fundraising. Similar
to McCormick and Tinsley's (1990) study at Clemson University, it
appears that successful athletic teams potentially benefit more than
just athletic programs by spurring growth in fundraising across the
campus.
Another significant moderator identified in the meta-analysis was
the alumni status of the donor. Studies focusing solely on alumni giving
resulted in an effect size nearly double that of studies based on giving
from all institutional donors. This finding, while counter to many
assertions made in the popular press (e.g., Sperber, 2000), is an
important finding that may bear directly on whether athletics help or
hurt institutional fundraising. Athletic performance, most notably
football success, has been linked to increased numbers of alumni donors
making gifts (Daughtrey & Stotlar, 2000; Stinson & Howard,
2008). Increased numbers of donors is indicative of the positive
influence athletics can have on institutional fundraising. However,
other studies have suggested that these alumni donors may alter their
institutional giving patterns, both to athletic and academic programs
based on athletic performance. In the extreme, alumni donors may
cannibalize their academic giving to support athletics in times of
success, potentially harming the institutional fundraising effort
(Stinson & Howard, 2004; Stinson & Howard, 2007). Further work
should concentrate specifically on the effect of athletics on
pro-institutional alumni behaviors, including fundraising.
Not surprisingly, NCAA classification was also identified as an
important moderator in the meta-analysis. Institutions competing at the
NCAA I-A level of competition were more strongly influenced by the
success of their respective athletic programs that institutions
competing at lower levels. Several plausible explanations exist for this
finding, though precise understanding awaits future research. NCAA I-A
schools receive significantly more media attention, particularly for
athletics, than other institutions. The high profile, focused more
heavily on athletics, may prompt larger groups of donors (alums and
non-alums) to identify specifically with the athletic teams at the
institution. Non-alumni in particular may make gifts to the institution
that would not be made in the absence of athletic success. This could
potentially explain the larger effects at NCAA I-A schools. Also, the
fact that the vast majority of studies examining athletic success and
giving have been conducted at the NCAA I-A level provides a more
thorough examination of giving at that level. Still, it is important to
note that the effect sizes are significant and positive at all levels of
NCAA competition. Stinson and Howard (2008) suggested that, in fact,
athletic success at lower levels of competition (IAAA) was more
important to increases in academic support than athletic success at the
I-A level. Future research should continue to extend beyond high profile
Division I-A schools.
Finally, this study identified a moderating role for the primary
sport of interest. Football success displayed a much stronger influence
on giving (by nearly 60 percent) than basketball or other sports.
Previous studies have certainly documented the strong influence of
various measures of football performance on giving (i.e., winning
percentage, bowl appearances), so this finding is not necessarily
surprising (Baade & Sundberg, 1996; Goff, 2000; Humphreys &
Mondello, 2007; McCormick & Tinsley, 1990; Rhoads & Gerking,
2000; Stinson & Howard, 2007). Nevertheless, this result is
important in that it continues to support the dominant role of football
in athletic and institutional fundraising efforts. While not directly
tested here, it seems possible that the ability of many football stadia
to attract and seat more fans than basketball arenas heavily favors
football in its influence. This is particularly true in cases where a
university is able to "require" a donation for many or all
season tickets in the respective arenas. Even though basketball teams
typically play many more games in a season, they are more constrained than football in the number of season tickets that can be sold. This in
turn constrains the required giving that can be generated through
basketball programs. Thus, efforts to increase seating capacity and
donor clubs that are associated with football programs appear to be
paying off (Howard & Crompton, 2004). This finding is also
consistent with research concluding that when football is not present
(NCAA IAAA institutions), basketball as the focal sport is the primary
influence on giving (Stinson & Howard, 2008). The conclusion of this
meta-analysis is that the performance of the focal revenue-generating
sport on a given campus is a significant influence on institutional
fundraising. Researchers, and universities, should continue their
efforts to understand how to use these athletic programs to best benefit
the entire institutional fundraising effort.
Institution type was not statistically significant as a moderator
across the studies included in this meta-analysis. In fact, the effect
sizes for public and private schools were virtually identical,
suggesting a similar influence of athletic success on giving at both
types of institutions. This finding is somewhat surprising in relation
to previous research. Many recent studies that have concluded that there
is no relationship between intercollegiate athletics and fundraising
have included data primarily drawn from academically elite private
institutions (i.e., Shulman & Bowen 2001, Turner, Meserve, &
Bowen, 2001). On the other hand, many of the recent studies concluding
there are significant effects of athletics on giving include strong or
sole representation of public institutions (i.e., Grimes &
Chressanthis, 1994; McCormick & Tinsley, 1990; Rhoads & Gerking,
2000; Stinson & Howard, 2004). Possible explanations for this
pattern of results may be indicative of other institutional factors as
more powerful moderators than public/private status. For example, the
level of investment in athletics programs may determine the extent of
effects. Or, as Stinson and Howard (2008) reported, academic rankings
may be a primary determinant of the influence of athletics on giving.
Further research should continue to focus on these potential moderating
factors.
Despite a thorough review and inclusion of the available research
on the relationship of athletic success and institutional giving, this
study is not without certain limitations. Foremost, there is a
relatively small amount of quantitative-based research in the field of
intercollegiate athletic relationship and giving, including a smaller
percentage of studies that examine this relationship in terms of sports
other than football and basketball and across differing NCAA
classification levels. This fact may very well have led to the
insignificant effect sizes for the institution type moderator. Still,
the significant meta-analytic findings identified here are critical to
understanding the influence of athletics programs on fundraising. The
significant effects noted here represent a strong set of findings based
on over 30 years of research in this area. As a result, we can be quite
confident that intercollegiate athletic programs do have a significant
influence on institutional fundraising, though the strength of that
relationship is moderated by four important variables: the target of the
giving, the alumni status of the donor, the institution's level of
NCAA competition, and the primary sport of interest. Thus, these
findings begin to set the conditions for when athletic performance is
most likely to influence giving. Future research should continue to seek
understanding of the underlying mechanisms causing these relationships,
as well as extending itself to a consideration of other variables that
may be important in the athletic performance-fundraising relationship.
Further, research should be broadened to include other important
variables subject to the influence of athletic programs, including
institutional image, college choice and/or matriculation (Chressanthis
& Grimes, 1993; Mixon, Trevino, & Minto, 2004), and academic
quality (Goidel & Hamilton, 2006; McCormick & Tinsley, 1987;
Mixon & Trevino, 2005).
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contributions, academic quality and athletic success. Contemporary
Economic Policy, 18(2), 248-258.
Shulman, J. L., & Bowen, W. G. (2001), The fame of life,
Princeton, NJ: Princeton University Press.
* Sigelman, L., & Bookheimer, S. (1983). Is it whether you win
or lose? Monetary contributions to big-time college athletic programs.
Social Science Quarterly, 64(2), 347-359.
* Sigelman, L., & Carter, R. (1979). Win one for the giver?
Alumni giving and big-time college sports. Social Science Quarterly,
60(2), 284-294. Sperber, M. (1990). College sports inc. New York: Henry
Holt.
Sperber, M. (2000). Beer and circus: The impact of big-time college
sports on undergraduate education. New York: Henry Holt.
Stinson, J. L., & Howard, D. R. (2004). Scoreboards vs.
mortarboards: Major donor behavior and intercollegiate athletics. Sport
Marketing Quarterly, 13, 73-81.
* Stinson, J. L., & Howard, D. R. (2007). Athletic success and
private giving to athletic and academic programs at NCAA institutions.
Journal of Sport Management, 21(2), 237-266.
* Stinson, J. L., & Howard, D. R. (2008). Winning does matter:
Patterns in private giving to athletic and academic programs at NCAA
Division IAA and I-AAA institutions. Sport Management Review 11(1),
1-20.
* Tucker, I. B. (2004). A reexamination of the effect of big-time
football and basketball success on graduation rates and alumni giving
rates. Economics of Education Review, 23(6), 655-661.
* Turner, S. E., Meserve, L. A., & Bowen, W. G. (2001). Winning
and giving: Football results and alumni giving at selective private
colleges and universities. Social Science Quarterly, 82(4), 812-826.
* References marked with an asterisk indicate studies included in
meta-analysis.
J. Michael Martinez, PhD, is an assistant professor in the
Department of Kinesiology and Health Promotion at Troy University. His
research interests include charitable giving, intercollegiate athletics,
internal branding, and media consumption.
Jeffrey L. Stinson, PhD, is an assistant professor of marketing at
Central Washington University. His research interests include charitable
giving, intercollegiate athletics, and education institution branding.
Minsoo Kang, PhD, is an associate professor in the Department of
Health & Human Performance at Middle Tennessee State University. As
a measurement specialist, he has contributed to the manuscript by
analysis and interpretation of meta- analysis data, and drafting and
revising the manuscript.
Colby B. Jubenville, PhD, is an associate professor of sport
management at Middle Tennessee State University. His research interests
include branding, sport sponsorship, sport marketing, systems thinking,
and sport policy.
Table 1.
Summary of Included Studies
Study Independent Dependent Findings
Variables Variables
Baade & Records for Alumni giving Bowl appearances,
Sundberg men's football NCAA BB tournament
(1996) and basketball appearances
teams, associated with
post-season significant
appearances increases in alumni
giving at doctorate
institutions.
Budig (1976) Football and Alumni giving No relationship
men's at 79 public between team records
basketball institutions and giving.
records
Coughlin & Football and Contributions Football success
Erekson men's to the (record and bowl
(1984) basketball athletic appearance) and
records, department basketball winning
post-season percentage
appearances significantly
related to athletic
department
contributions.
Daughtrey & Football Alumni Positive impact of
Stotlar championships donation championship season
(2000) in NCAA I-AA, amount and on athletic
II and III number of department donations
alumni donors and number of
athletic donors at
DII and III
institutions. Also,
significant
increases in
institutional
contributions at
DIII schools, and
increase in number
of total donors at
I-AA institutions.
Grimes & Winning Alumni Overall winning
Chressanthis percentage, contributions percentage of all
(1994) television to the three sports
appearances, Mississippi positively
and post-season State associated with
appearances by University alumni
football, men's Foundation contributions.
basketball, and
baseball teams
Litan, Athletic Alumni giving No relationship
Orzag, & operating between football
Orzag (2005) expenditures, success and alumni
football giving.
winning
percentages
Rhoads & Post-season Total and Alumni contributions
Gerking success of alumni giving increase with bowl
(2000) football and from 87 NCAA win; decrease if
men's Division I team placed on
basketball institutions probation.
teams, athletic
probation,
athletic
tradition
Sigelman & Football Institutional Winning football
Bookheimer records giving teams correlate with
(1983) increased athletic,
but not
institutional,
donations.
Sigelman & Football and Change in Neither record nor
Carter men's alumni giving change in record of
(1979) basketball football or men's
records, change basketball teams
in football and significant
men's predictors of
basketball changes in alumni
records giving.
Stinson & Football Academic and Total giving to
Howard records, athletic giving top-ranked academic
(2007) post-season to NCAA I-A institutions less
appearance, institutions susceptible to
post-season influence of
success, athletic success.
tradition Increasing
percentage of
donations at all
schools allocated
toward athletics.
Stinson & Men's Academic and Successful
Howard basketball athletic giving basketball teams
(2008) records, to NCAA positively influence
post-season I-AA/AAA the number of donors
appearance, institutions making gifts and the
post-season average size of
success, those gifts, both
tradition for academic and
athletic programs.
Tucker Football and Alumni giving Football success
(2004) men's positively
basketball influences alumni
records giving; basketball
success is not a
statistically
significant
influence on alumni
giving.
Turner, Football Individual Football won-loss
Meserve, & won-loss donor giving records not
Bowen records data from significantly
(2001) College and related to either
Beyond dataset athletic or general
giving
rates/amounts.
Table 2.
Summary of Effect Sizes
Study Year School Type Ath./Univ. Alumni
Budig 1976 Combination University Alumni
Budig 1976 Combination University Alumni
Budig 1976 Combination University Alumni
Budig 1976 Combination University Total
Budig 1976 Combination University Total
Sigelman & Carter 1979 Combination University Alumni
Sigelman & Carter 1979 Combination University Alumni
Sigelman & Carter 1979 Combination University Alumni
Brooker & Klastorin 1981 Public University Total
Sigelman & Bookheimer 1983 Combination Athletics Alumni
Sigelman & Bookheimer 1983 Combination Athletics Alumni
Coughlin & Erekson 1984 Combination Athletics Total
Coughlin & Erekson 1984 Combination Athletics Total
Grimes & Chressanthis 1994 Public University Alumni
Grimes & Chressanthis 1994 Public University Alumni
Grimes & Chressanthis 1994 Public University Alumni
Grimes & Chressanthis 1994 Public University Alumni
Grimes & Chressanthis 1994 Public University Alumni
Grimes & Chressanthis 1994 Public University Alumni
Grimes & Chressanthis 1994 Public University Alumni
Grimes & Chressanthis 1994 Public University Alumni
Baade & Sundberg 1996 Private University Alumni
Baade & Sundberg 1996 Private University Alumni
Baade & Sundberg 1996 Public University Alumni
Baade & Sundberg 1996 Public University Alumni
Baade & Sundberg 1996 Liberal Arts University Alumni
Baade & Sundberg 1996 Liberal Arts University Alumni
Daughtrey & Stotlar 2000 Combination University Alumni
Daughtrey & Stotlar 2000 Combination Athletics Alumni
Rhoads & Gerking 2000 Combination University Total
Rhoads & Gerking 2000 Combination University Total
Rhoads & Gerking 2000 Combination University Alumni
Rhoads & Gerking 2000 Combination University Alumni
Turner, Meserve, & Bowen 2001 Private University Alumni
Turner, Meserve, & Bowen 2001 Private Athletics Alumni
Litan, Orzag, & Orzag 2003 Combination University Alumni
Tucker 2004 Combination University Alumni
Tucker 2004 Combination University Alumni
Tucker 2004 Combination University Alumni
Tucker 2004 Combination University Alumni
Tucker 2004 Combination University Alumni
Tucker 2004 Combination University Alumni
Stinson & Howard 2007 Combination University Total
Stinson & Howard 2007 Combination University Alumni
Stinson & Howard 2007 Combination Athletics Total
Stinson & Howard 2007 Combination Academic Total
Stinson & Howard 2007 Combination University Total
Stinson & Howard 2007 Combination University Alumni
Stinson & Howard 2007 Combination Athletics Total
Stinson & Howard 2008 Combination University Total
Stinson & Howard 2008 Combination University Alumni
Stinson & Howard 2008 Combination Athletics Total
Stinson & Howard 2008 Combination Athletics Alumni
Stinson & Howard 2008 Combination Academic Total
Stinson & Howard 2008 Combination Academic Alumni
Stinson & Howard 2008 Combination University Total
Stinson & Howard 2008 Combination University Total
Stinson & Howard 2008 Combination Athletics Total
Stinson & Howard 2008 Combination Athletics Total
Stinson & Howard 2008 Combination Academic Total
Stinson & Howard 2008 Combination Academic Total
Stinson & Howard 2008 Combination University Total
Stinson & Howard 2008 Combination University Total
Stinson & Howard 2008 Combination University Alumni
Stinson & Howard 2008 Combination University Alumni
Stinson & Howard 2008 Combination University Alumni
Stinson & Howard 2008 Combination Athletics Total
Stinson & Howard 2008 Combination Athletics Total
Stinson & Howard 2008 Combination Athletics Alumni
Stinson & Howard 2008 Combination Athletics Alumni
Stinson & Howard 2008 Combination Athletics Alumni
Stinson & Howard 2008 Combination Academic Total
Stinson & Howard 2008 Combination Academic Total
Stinson & Howard 2008 Combination Academic Alumni
Stinson & Howard 2008 Combination Academic Alumni
Stinson & Howard 2008 Combination Academic Alumni
Study NCAA Class Sport Success
Budig Combo w/DI FB Win Pct.
Budig Combo w/DI BB Win Pct.
Budig Combo w/DI BB Win Pct.
Budig Combo w/DI FB Win Pct.
Budig Combo w/DI BB Win Pct.
Sigelman & Carter Div. I FB Post
Sigelman & Carter Div. I FB Win Pct.
Sigelman & Carter Div. I BB Win Pct.
Brooker & Klastorin Div. I-A FB Post
Sigelman & Bookheimer Div. I FB Win Pct.
Sigelman & Bookheimer Div. I BB Win Pct.
Coughlin & Erekson Div. I FB Post
Coughlin & Erekson Div. I BB Win Pct.
Grimes & Chressanthis Div. I FB Post
Grimes & Chressanthis Div. I BB Post
Grimes & Chressanthis Div. I Other Post
Grimes & Chressanthis Div. I Total Post
Grimes & Chressanthis Div. I FB Win Pct.
Grimes & Chressanthis Div. I BB Win Pct.
Grimes & Chressanthis Div. I Other Win Pct.
Grimes & Chressanthis Div. I Total Win Pct.
Baade & Sundberg Combo w/DI FB Post
Baade & Sundberg Combo w/DI BB Post
Baade & Sundberg Combo w/DI FB Post
Baade & Sundberg Combo w/DI BB Post
Baade & Sundberg Combo w/DI FB Win Pct.
Baade & Sundberg Combo w/DI BB Win Pct.
Daughtrey & Stotlar Combo w/o DI FB Post
Daughtrey & Stotlar Combo w/o DI FB Post
Rhoads & Gerking Div. I FB Post
Rhoads & Gerking Div. I BB Post
Rhoads & Gerking Div. I FB Post
Rhoads & Gerking Div. I BB Post
Turner, Meserve, & Bowen Combo w/DI FB Win Pct.
Turner, Meserve, & Bowen Combo w/DI FB Win Pct.
Litan, Orzag, & Orzag Div. I-A FB Win Pct.
Tucker Div. I-A FB Post
Tucker Div. I-A BB Post
Tucker Div. I-A FB Rank
Tucker Div. I-A BB Rank
Tucker Div. I-A FB Win Pct.
Tucker Div. I-A BB Win Pct.
Stinson & Howard Div. I FB Post
Stinson & Howard Div. I FB Post
Stinson & Howard Div. I FB Post
Stinson & Howard Div. I FB Post
Stinson & Howard Div. I FB Win Pct.
Stinson & Howard Div. I FB Win Pct.
Stinson & Howard Div. I FB Win Pct.
Stinson & Howard Div. I-AA FB Post
Stinson & Howard Div. I-AA FB Post
Stinson & Howard Div. I-AA FB Post
Stinson & Howard Div. I-AA FB Post
Stinson & Howard Div. I-AA FB Post
Stinson & Howard Div. I-AA FB Post
Stinson & Howard Div. I-AA BB Post
Stinson & Howard Combined BB Post
(I-AA, I-AAA)
Stinson & Howard Div. I-AA BB Post
Stinson & Howard Combined BB Post
(I-AA, I-AAA)
Stinson & Howard Div. I-AA BB Post
Stinson & Howard Combined BB Post
(I-AA, I-AAA)
Stinson & Howard Div. I-AA FB Rank
Stinson & Howard Div. I-AA BB Rank
Stinson & Howard Div. I-AA BB Rank
Stinson & Howard Div. I-AA FB Rank
Stinson & Howard Combined BB Rank
(I-AA, I-AAA)
Stinson & Howard Div. I-AA FB Rank
Stinson & Howard Div. I-AA BB Rank
Stinson & Howard Div. I-AA BB Rank
Stinson & Howard Div. I-AA FB Rank
Stinson & Howard Combined BB Rank
(I-AA, I-AAA)
Stinson & Howard Div. I-AA FB Rank
Stinson & Howard Div. I-AA BB Rank
Stinson & Howard Div. I-AA BB Rank
Stinson & Howard Div. I-AA FB Rank
Stinson & Howard Combined (I-AA, I-AAA) BB Rank
Study N [ES.sub.r]
Budig 58 0.696
Budig 62 0.499
Budig 56 0.588
Budig 58 0.336
Budig 58 0.200
Sigelman & Carter 100 0.098
Sigelman & Carter 100 0.131
Sigelman & Carter 100 0.001
Brooker & Klastorin 58 0.173
Sigelman & Bookheimer 57 0.335
Sigelman & Bookheimer 57 0.092
Coughlin & Erekson 56 0.290
Coughlin & Erekson 56 0.202
Grimes & Chressanthis 30 0.021
Grimes & Chressanthis 30 0.128
Grimes & Chressanthis 30 0.028
Grimes & Chressanthis 30 0.157
Grimes & Chressanthis 30 0.022
Grimes & Chressanthis 30 0.246
Grimes & Chressanthis 30 0.022
Grimes & Chressanthis 30 0.172
Baade & Sundberg 575 0.138
Baade & Sundberg 575 -0.027
Baade & Sundberg 1025 0.100
Baade & Sundberg 1025 0.096
Baade & Sundberg 1688 0.040
Baade & Sundberg 1688 -0.016
Daughtrey & Stotlar 33 0.231
Daughtrey & Stotlar 33 0.428
Rhoads & Gerking 821 0.089
Rhoads & Gerking 821 0.097
Rhoads & Gerking 821 0.110
Rhoads & Gerking 821 0.089
Turner, Meserve, & Bowen 125 0.469
Turner, Meserve, & Bowen 125 0.400
Litan, Orzag, & Orzag 371 0.900
Tucker 78 0.228
Tucker 78 0.002
Tucker 78 0.204
Tucker 78 0.006
Tucker 78 0.268
Tucker 78 0.015
Stinson & Howard 747 0.018
Stinson & Howard 795 0.035
Stinson & Howard 629 0.020
Stinson & Howard 707 0.028
Stinson & Howard 773 0.028
Stinson & Howard 856 0.002
Stinson & Howard 657 0.074
Stinson & Howard 232 0.032
Stinson & Howard 232 0.033
Stinson & Howard 631 0.064
Stinson & Howard 631 0.067
Stinson & Howard 233 0.034
Stinson & Howard 233 0.034
Stinson & Howard 428 0.068
Stinson & Howard 967 0.027
Stinson & Howard 579 0.016
Stinson & Howard 1219 0.007
Stinson & Howard 420 0.069
Stinson & Howard 965 0.028
Stinson & Howard 501 0.013
Stinson & Howard 277 0.025
Stinson & Howard 277 0.018
Stinson & Howard 501 0.046
Stinson & Howard 1032 0.008
Stinson & Howard 581 0.019
Stinson & Howard 575 0.002
Stinson & Howard 575 0.008
Stinson & Howard 581 0.004
Stinson & Howard 1286 0.014
Stinson & Howard 499 0.052
Stinson & Howard 278 0.024
Stinson & Howard 278 0.016
Stinson & Howard 499 0.045
Stinson & Howard 1033 0.010
Note: BB = Basketball, FB = Football, Win Pct. = Winning Percentage,
Post = Postseason Appearance, Rank = National Ranking
Table 3.
Moderator Analysis
Institution Type Effect Size Effect Size CI
Public 0.10 0.06-0.14
Private 0.09 0.05-0.14
Combination 0.06 0.05-0.07
Giving Target Effect Size Effect Size CI
University 0.09 0.07-0.10
Athletic 0.04 0.02-0.06
Academic 0.03 0.00-0.06
Giving Base Effect Size Effect Size CI
Total 0.04 0.02-0.06
Alumni Only 0.08 0.07-0.10
NCAA Classification Effect Size Effect Size CI
Division I-A 0.12 0.10-0.15
Division I-AA 0.05 0.03-0.06
Combination 0.04 0.01-0.06
Sport of Interest Effect Size Effect Size CI
Football 0.09 0.08-0.11
Basketball 0.04 0.02-0.05
Other 0.09 -0.09-0.29
Table 4.
Summary of Results and Implications
Key Finding
* Across 30 years of empirical study, intercollegiate athletics has
a small, but significant influence on institutional fundraising.
* Effects of athletic success are strongest when institutional
giving is considered.
* Alumni donors are more influenced by athletic success than
non-alumni donors.
* Football is the primary influence on giving at institutions where
football is played.
* Public institutions and private schools have nearly identical
effect sizes, indicating all schools may be influenced by athletic
performance.
Implications for Practice
* Institutional fundraisers should invest in understanding the role
athletics play in giving and learn to leverage athletic success to
benefit institutional fundraising efforts.
* Athletic success may be a positive influence on both athletic and
academic fundraising. Academic fundraisers should consider the
ability of athletic programs to assist in donor development.
* Contrary to some popular press, alumni should be targeted with
campaigns leveraging the role of athletics in fundraising. In
particular, successful athletics programs appear to bring more
alumni donors to the institution. Care should be taken to
successfully develop and cultivate these new donors.
* Fundraisers should pay particular attention to the football team.
Positive shaping of expectations and perceptions of success may
enhance institutional fundraising.
* Both public and private schools appear influenced, and therefore
may leverage athletic success in fundraising.