A Quantitative Analysis – The Sport Journal

Authors: Kyle J. Brannigan, University of Northern Colorado & Dr. Alan L. Morse, University of Northern Colorado

Corresponding Author:
Kyle J. Brannigan
4750 W29th Street APT 1210
Greeley CO, 80634
[email protected]
845-216-0965

Second Author:
Dr. Alan L. Morse
Butler-Hancock 261A University of Northern Colorado Sports & Exercise Science
Campus Box 118
Greeley, CO 80639
[email protected]

An
Empirical Investigation of the Variables Influencing Contributions in NCAA
Division I Athletics: A Quantitative Analysis

ABSTRACT

The
purpose of this study was to identify variables that influence contributions to
help athletic departments become more efficient with their fundraising efforts.
In addition, this study was expected to provide a better understanding of the
effect each explanatory variable has on contributions. The researchers conducted
a multiple linear regression, using the data, which spanned over three years
(2015, 2016, and 2017), to investigate what factors influence contributions to
Division I, public schools, in the Power Five conferences. A regression was
conducted to clarify further the studies significance. The researchers tested
for assumptions, collinearity, correlations, normality, and variance. The
significant variables in the study were 1) Average announced attendance for
football 2) Enrollment, 3) Football winning percentage 4) Population of Metropolitan
Statistical Area or MSA, 5) Fundraising years of experience. In addition, every
conference was significant with the Southeastern Conference having the largest
part correlation, which demonstrated influence for each variable. Other interesting
findings in this study were overall ticket sales were almost significant and Texas
A&M is an influential observation because its contributions are much higher
than other institutions. The results of this study may aid athletic departments
in determining focus to maximize donations. As enrollment was a significant
factor, the results further strengthen the case that athletic departments
should be using their alumni bases even more to solicit donations. Another
implication is that getting into a Power 5 conference can help your
contribution levels. In addition, it is crucial for athletic departments to focus
on hiring experienced directors of fundraising to guide the staff in maximizing
donations. Lastly, athletic departments may want to continue using ticket sales
to solicit donations. If athletic departments take into consideration variables
that affect donations the most and focus on these variables, they may be able
to increase overall athletic donations.

Keywords: Contributions, donations, tickets, revenue, NCAA

INTRODUCTION

Donor
contributions are the largest revenue generator in the National Collegiate Athletic
Association (NCAA) for division one athletics (Fulks, 2017). Previous research
has been conducted on factors that influence donor contributions (Coughlin
& Erekson, 1984; Daughtrey & Stotlar, 2000; Wells et al. 2005). The
importance of funding through contributions is most visible through the
construction of enhanced facilities; however, the increase in funds also helps
to draw more national attention, increase application rates, and increase
academic donations (Sigelman & Bookheimer, 1983). From 2008, fundraising
surpassed ticket sales as the single largest source of revenue for Division I
athletic departments (Fulks, 2008). With contributions being a vital part of
revenue generation today, it is becoming more important to examine further the
factors that influence contributions. Findings from previous studies indicated
donor motivation to be associated with perks, such as priority seating,
parking, and power in decision making, social and philanthropic purposes, and
to contribute to the academic success of student-athletes (Gladden, 2005; Mahoney,
2003; Shapiro et al. 2010). Other scholars have found winning percentages in
football and basketball, national championships, ticket prices, conference
affiliation, number of living alumni, size of fundraising staff, and county
income to be reasons for donor contributions (Daughtrey & Stotlar, 2000;
Stinson & Howard, 2007; Wells et al. 2005). One inconsistent finding across
studies is that winning has a positive impact on donor contributions. This
specific variable is both significant (Anderson, 2012; Reynolds et al., 2017;
Stinson & Howard 2008), and insignificant (Cohen et al.; 2010; Turner et
al. 2001; Wells et al. 2005), depending on the study. The purpose of the
current study is to identify variables that influence contributions to help
athletic departments be more efficient in fundraising efforts and to provide a
better understanding of the effect each explanatory variable has on
contributions.

LITERATURE
REVIEW

Multiple
studies have investigated factors that affect contributions (Coughlin &
Erekson, 1984; Reynolds et al., 2017; Shapiro et al., 2010; Stinson &
Howard, 2007; Wells et al., 2005). Coughlin and Erekson (1984) used a
regression model with eight independent variables to estimate the influences on
athletic contributions. Independent variables used in the study were athletic
success, conference affiliation, and population variables. Coughlin and Erekson
(1984) found basketball winning percentages, conference affiliation, football
attendance, state population, and ticket sales as significant determinates of
donor contributions. More recent studies confirm these findings (Baade &
Sunberg, 1996; Cohen et al., 2010; Wells et al. 2005). However, Coughlin and
Erekson (1984) overlooked other variables that scholars showed to influence
contributions. They omitted variables involving enrollment, alumni size, along
with fundraising staff size and experience (Reynolds et al., 2017; Wells et
al., 2005). Significant variables not overlooked were, bowl appearances,
basketball success, conference affiliation, and attendance (Cohen et al., 2010;
Coughlin and Erikson, 1984; Martinez et al., 2010; Wells et al., 2005). One
constant that exists is the contradiction between basketball and football
winning percentages and the influence of the success of the sports has on donor
contributions (Brooker & Klastorin, 1981; Ko et al., 2013; Reynolds et al.,
2017; Sigelman & Bookheimer, 1983; Wells et al., 2005). In addition, other
contradictions exist in significant variables, which include state income and
the number of living alumni (Stinson & Howard, 2010; Wells et al., 2005).
Findings have differed as to whether these variables have a positive impact on
donor contributions. No study has expanded on these contradictions nor compared
all variables to see what influences contributions the most.

Previous
researchers acknowledge that contributions are the most valuable source of
revenue for college athletic departments (Coughlin & Erikson, 1984; Stinson
& Howard, 2010). Moreover, 18% of NCAA division I-A schools’ revenue
stemmed from contributions (Stinson & Howard, 2010). Researchers continue
to find that institutions are doing a better job at soliciting and creating
lifelong connections with donors thus creating donor retention (Coughlin &
Erikson, 1984; Sargeant & Woodliffe, 2007; Stinson & Howard, 2010).
This builds on Wells, et al, (2005) showing the size and experience of your
fundraising staff plays a significant factor in the success of generating donor
contributions. Past researchers have been able to show that contributions are a
main revenue source for Division 1 institutions as well as demonstrating the
significance of having a good fundraising staff. With contributions being more
relevant now than ever, this may create opportunities for researchers to figure
out what factors are most important to donor contributions. In order to add to
the existing literature and aid athletic departments in gaining the most
revenue out of donor contributions, the current study uses a quantitative
analysis to investigate the variables that most influence donor contributions.

This
study will add to the existing literature and provide clarification regarding
donor contributions. Past researchers have not examined all these factors using
a quantitative approach. Researchers have found a variety of factors proven to
influence donations. However, these studies limited themselves to certain
variable groups. The current study aimed to find the most influential variables
in relation to donor contributions. Based on previous literature, researchers
have found conference affiliation, and winning variables had the most
significant impact on donor contributions (Anderson, 2012; Daughtrey &
Stotlar, 2000; Sigelman & Bookheimer, 1983; Stinson & Howard, 2008;
Wells et al., 2005). The researchers hypothesized that enrollment, conference
affiliation, overall ticket sales, and rights and licensing, will be
significant. Enrollment speaks for the size of the school as well as its
possible alumni base, with larger enrollment numbers schools may have more
people to solicit for donations. Overall ticket sales typically include the
opportunity to donate and join the organization’s database, which make
purchasers available for donor solicitations. Both conference affiliation and
rights, and licensing variables allow for exposure, which could influence more
donations.

METHODS

Similar
to the method used by McEvoy and Morse (2007), and Coughlin and Erekson (1984),
the researchers used a multiple linear regression analyses to discover what
variables affected donor contributions to Division 1 public schools in Power 5
conferences, what of all influencing factors affect contributions, and the
differences in affect each factor has. A three year span (2015-2017) of data
was collected from these schools because they are the highest revenue and
contribution gaining institutions in division one athletics (NCAA.com, 2018).
Data was not available for private institutions, and thus they were excluded
from the study. Attendance and winning variables were recorded for football as
well as men’s and women’s basketball as these sports were the most attended,
most broadcasted, and most revenue generating sports in college athletics
(NCAA.com, 2018). Additionally, to the researcher’s knowledge, no study has
combined these factors along with others to test which are most significant. Enrollment,
student fees, and incoming funding variables were included based on previous
literature. The average attendance for each team based on home attendance were
used.

The
researchers conducted a multiple linear regression, using the data, which
spanned three years (2015, 2016, and 2017), to investigate what factors influence
contributions to Division I public schools in the Power 5 conferences. A
regression was conducted to clarify further the studies significance.
Researchers tested for assumptions, collinearity, correlations, normality, and
variance.

Variables

The
purpose of this study was to investigate what factors most influence donor
contributions in Division 1 athletics. A multiple regression analyses model was
created to explain more clearly the relationship between contributions and
division one athletic programs. In addition, the study controlled the potential
astounding variables to best isolate the relationship. The other variables were
chosen based on previous literature. 

Dependent Variable

Contributions
is the dependent variable for the study. The contributions variable is defined
as the amount of money donated to an athletic institution. This variable was
analyzed in each institution included in the sample.

Explanatory Variables

The
explanatory variables studied were rights/licensing, student fees, school
funds, average announced attendance for football, average announced attendance
for men’s basketball (MBB), average announced attendance for women’s basketball
(WBB), overall ticket sales, football home winning percentage, MBB winning
percentage, WBB winning percentage, national championships, conference
championships, march madness appearances, bowl appearance, enrollment,
population of metro statistical area (MSA), median household income, fundraising
staff experience conference affiliation. Fundraising experience was based on
the years of experience for the director of fundraising in the athletic
department. For conference affiliation, a dummy variable was used to better
distinguish each conference. These variables were chosen based on past research,
which found them to be significant in influencing donor contributions, as well
as factors the researchers feel most influence contributions.

Procedures

The
data for annual contributions were collected from usatoday.com (2017). Student
fees, school funds, and rights and licensing fees were also derived from the
USA today database. The researchers used the NCAA website, university websites,
and phone calls to gather all sports attendance data, average ticketing
pricing, winning percentages, national championships, conference championships,
March Madness appearances, conference affiliation, and bowl appearances. University
websites and common data sets were used to gather university enrollment.
Lastly, the U.S. Census Bureau was used to collect income per capita for the
county as well as the population of the Metropolitan Statistical Area (MSA).

Statistical design

Correlations
were also accounted for while the variance inflation factor was used to assess
correlations. These tests allowed the researchers to discover different levels of
significance in all factors. A multiple linear regression was used to test the
significance of the variables.

RESULTS

Table 1: Variable outcomes

Coefficients^a

a. Dependent Variable: Contributions

Table
1 displays descriptive data for all 28 variables included in the study. The
results show that average announced attendance for football, football-winning percentage;
fundraising staff years of experience, population of metropolitan statistical
area, and enrollment for every Power 5 conference school were significant
variables. Overall tickets sales were very close to being significant at .062.
This may be important to note because in studies with this variable, typically
ticket sales is significant. The overall regression model showed statistical significance
yielding a p-value less than .001. This implies at least one or more
independent variables influences contributions. The overall model showed an R-squared
value of .652, more importantly the adjusted R-squared value is .578. Thus,
approximately 58% of the variance in contributions are explained by the
independent variables.                        

VIF
is a measurement that determines whether two variables may be explaining the
same thing; therefore, VIF should show how much multi-collinearity is in the
model (displayr.com, 2018). In Table 1, variance inflation factor (VIF) values
appeared to be acceptable, despite some collinearity issues. Average football
attendance and overall ticket sales appear to be similar and have some
collinearity issues; however, the VIF values are not alarmingly high. Going
further, the partial correlation plots showed the linearity assumptions were
met.

The
study also tested for normality and variance. Normality does not appear to be
violated from the histogram (Figure 1) although the normal PP plot (Figure 2)
does show that normality may be violated. This could mean that results may not
be trustworthy. However, according to the scatter plot (Figure 3) the constant
variance assumption does not appear to be violated. In addition, the overall
regression model had high significance levels. Thus, proving the overall study
is significant.

Table 2: Regression table

ANOVA^a

a. Dependent Variable: Contributions
b. Predictors: (Constant), SEC, FundraisingstaffexpYears, FootballConferenceChampionships, MBballNationalChampionships, FootballWinning, Wbballconfchamps, Enrollment, Mbballconfchamps, PopulationofMSA, Big12, WBballNationalChampionships, SchoolFunds, MBBWinning, BowlAppearances, WMarchMadnessAppearances, StudentFees, MedianHouseholdIncome, MMarchMadnessAppearances, FBNationalChamps, Pac12, WBBWinning, RightsLicensing, AnnouncedAttendanceforWBB, Overallticketsales, ACC, AnnouncedAttendanceforMBB, AVGAnnouncedAttendanceforFootball

Table 3: R-Squared table

Model Summary^b

a. Predictors: (Constant), SEC, FundraisingstaffexpYears, FootballConferenceChampionships, MBballNationalChampionships, FootballWinning, Wbballconfchamps, Enrollment, Mbballconfchamps, PopulationofMSA, Big12, WBballNationalChampionships, SchoolFunds, MBBWinning, BowlAppearances, WMarchMadnessAppearances, StudentFees, MedianHouseholdIncome, MMarchMadnessAppearances, FBNationalChamps, Pac12, WBBWinning, RightsLicensing, AnnouncedAttendanceforWBB, Overallticketsales, ACC, AnnouncedAttendanceforMBB, AVGAnnouncedAttendanceforFootball
b. Dependent Variable: Contributions

The
regression model in Table 2 allows us to see the overall regression model
showed significance at 8.799 yielding a p-value less than .001. Again, this indicates
that at least one or more of independent variables does have an influence on
contributions. The overall model (Table 3) showed an adjusted R-squared value
of .578; this explains that approximately 58% of the variance in contributions
are explained by the independent variables. The significant variables are 1) Average
announced attendance for football, 2) Enrollment, 3) Football winning
percentage, 4) Population of MSA, and 5) Fundraising years of experience. In addition,
every conference was significant with the SEC having the largest part
correlation and thus has the most influence on donor contributions of all the Power
5 conferences.

The
enrollment variable had a part correlation of .341
and a p-value of less than .001. This variable had the highest part correlation
of all variables in the study other than the SEC conference. With the exception
of other conferences, enrollment was followed by average announced attendance
for football, which had a part correlation of .222 followed by football winning
percentage. The data demonstrated a gap between the two leading variables that affect
contributions. Other variables that have been shown to affect donor
contributions are fundraising staff experience with a part correlation of -.113 and population of MSA with a part correlation
of -.122.

The
findings of this study supported the initial hypothesis. However, some
variables found to be significant were not hypothesized in this study. It was hypothesized
that enrollment, conference affiliation, ticket sales, winning variables and
rights and licensing fees would have the most impact on donor contributions. However,
rights and licensing fees were not deemed significant. In addition, it was not hypothesized
that fundraising staff experience would have the impact it did. However, the researchers
did correctly hypothesize that conference affiliation; enrollment and winning
would be significant. It should also be noted that overall ticket sales were
very close to being significant, and basketball winning was close as well.

Some
interesting findings in this study were overall ticket sales was almost
significant. This variable had a part correlation of .98 and a p-value of .062.
This is very close to the significance level and something that may be taken
into consideration. Another interesting finding was that Texas A&M was a
potential outlier. The reason Texas A&M is an influential observation is because
its contributions are much higher than other institutions. This could also be
the reason that the SEC conference has such an influence on donations as well.
For example, Texas, another leading university, had an average contribution of
$44,150,553 over the studies span compared to Texas A&M’s average
contribution level of $71,871,773. Although the difference is vast, Texas
A&M should not be omitted because the recorded values are legitimate. The
results indicate that  it conference, enrollment,
staff experience affect contributions.

CONCLUSIONS

The
purpose of this study was to identify variables that influence contributions to
help athletic departments be more efficient with their fundraising efforts and
to provide a better understanding of the effect each explanatory variable has
on contributions. Previous literature indicated factors that are significant,
but there seemed to be uncertainty in the understanding of significant
explanatory variables. A multiple linear regression was used in this study to
identify these significant variables and provide a better understanding of the
explanatory variables. This study supports that average announced attendance
for football, enrollment, football winning percentage, population of MSA; fundraising
staff years of experience and conference affiliation have a positive
relationship with donor contributions. Some reasons for this may be that
conference affiliation allows for greater exposure. All these conferences have
large amounts of games on national television and often get national exposure
on sports shows, which may explain why being in a Power 5 conference can affect
donations.

Overall
tickets sales were close to being significant and has been significant in past
studies. It is common when purchasing tickets that a donation is required,
which may contribute to this measure (Wells et al., 2005). Thus, ticket sales
have a direct impact on increasing donations. In addition, ticket sale
databases create more donation revenue opportunities.  

Winning
in the past has been found significant as well. Winning may lead to more
exposure, especially since these teams are often on national television. Winning
big games as well as bowl games allow for a great amount of exposure and allow
ticket departments more power when trying to solicit donations. Of course,
athletic departments cannot control winning or losing but they may be able use
winning to help increase attendance and solicit more donations. Larger
populations to solicit in ticket sales yield more donations, which athletic
departments cannot control but can use to its advantage. Having a fundraising
staff that knows how to relate to both the people in your area and your
existing database may be a positive way for athletic departments to garnish
more donations.

An
understanding of these variables and their significance may be important for
athletic departments in order to maximize donor contributions. A focus on
ticket sales and enrollment may aid organizations in creating more donation
revenue, which has been proven vital to the success of modern-day Division I
college athletic programs (Fulks, 2017; Sigelman & Bookheimer, 1983).
Furthermore, athletic departments should employ a director of fundraising with
fundraising experience, as fundraising staff experience was found significant.
A director who knows how to create relationships and motivate staff may allow
athletic departments to be more successful when soliciting athletic
contributions. 

Support for findings in literature

The
literature is mixed on what factors affect donor contributions. Some find
winning percentages to be significant (Anderson, 2012; Reynolds et al., 2017;
Stinson & Howard 2008), others do not (Cohen et al.; 2010; Turner et al.;
2001; Wells et al.; 2005). Similar to Reynolds et al. (2017), the current study
found football winning percentage to have an impact on donor contributions. This
study was also supported by Daughtrey and Stotlar’s (2000) findings that
conference affiliation affects contributions as well.

APPLICATIONS IN SPORT

The
results of this study may aid athletic departments to maximize donations. As
enrollment is a significant factor, athletic departments should be using their
alumni bases and student populations more to solicit donations. Athletic
departments may want to consider continuing using ticket sales to solicit
donations. Tying in donations with tickets and parking may be a way to use
ticket sales to solicit larger amounts of donations and overall revenue. Conference
membership also had an effect on contribution levels. Finally, athletic
departments should hire experienced directors of fundraising as directors of
fundraising drive donor contributions. These considerations may increase
overall athletic donations.

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