A Model of the Factors Contributing to Fan Support at Small-College Athletic Events

Introduction

A great deal has been written in both academic and popular periodicals
about the value of college athletic programs. While some argue that the
net outcome of college athletic programs is favorable in terms of benefits
to the institution, detractors often view these programs as financially
debilitating to the welfare of the institution (Weeth, 1994). An issue
of controversy for many institutions is the value of the benefits versus
the cost associated with operating intercollegiate athletic programs (Lehnus
and Miller, 1996). The dilemma for administrators is often more pressing
at the small-college level because funding is usually limited and the
programs themselves generally prove to be unprofitable (Helitzer, 1996).
One of the more pressing problems for many small-college athletic programs
is the lack of fan attendance, because attendance can influence support
from alumni and the administration of the school. The present study examines
what factors are key in explaining attendance at small-college sporting
events.

Factors Affecting Attendance

Much research effort has been dedicated to the study of fan attendance
in an attempt to assess fan motivation and other related factors predicting
fan attendance (Wakefield, 1995; Mawson and Coan, 1994; Baade and Tiehen,
1990; Noll, 1974). A number of conceptual and empirical studies have been
directed in the area of sports-fan identity with the team as a future
predictor of attendance (Fisher and Wakefield, 1998; Wann and Schrader,
1997: Zhang, Smith, and Pease, 1996; Pol and Pak, 1994; Yeagin, 1986).
These investigations build upon earlier consumer research in such areas
as group involvement and group identification. Additional streams of sports
marketing research address sports promotion (Helitzer, 1996; Graham, Goldblatt,
and Delpy, 1995; and Wilkenson, 1993) as part of the attendance model.
None of these articles, however, specifically address the promotion of
attendance at small-college athletic programs. Wells et al. (2000) is
one of the few studies that address attendance at small-college sporting
events. They studied small-college football attendance using nine determinants
from DeSchriver’s (1996) model as well as fourteen additional determinants
from a literature review of fan attendance to develop their model. The
significant variables in their analysis were time and season of the game,
winning percentage of the team, promotional effort, prices, whether or
not the school had a sport marketing position, student enrollment, and
the existence of booster clubs.

Data Collection and Analysis

Data were collected at intercollegiate basketball games involving three
small schools in the South and Midwest at approximately the same time
of the season. The questionnaire that was used incorporated much of what
is known or understood to be the salient factors affecting attendance
while including additional factors that were derived from a series of
focus group studies with fans of various sports teams from several small
colleges. It included thirty-nine Likert scale questions (See Exhibit
I for a list of the Likert questions). 492 questionnaires were completed.
Missing data reduced the number of usable questionnaires to 404.

The thirty-nine Likert scale statements (1 = strongly disagree to 5 =
strongly agree) were analyzed using factor analysis to determine their
basic, underlying structure. As described by Hair et al. (1995), eight
of the variables were excluded from the factor analysis because of low
correlations with the other variables. Six factors were extracted, based
on the criterion of having eigenvalues greater than one. The six factors
represented slightly over 55% of the variability in the data. The factor
loadings, after varimax rotation, for the remaining thirty-one variables
on the six factors are shown in Exhibit I; the eight variables not included
in the factor analysis are also described.

Based on the pattern of factor loadings, Factor 1 is labeled “College
Affiliation.” Factor 2 is labeled “Entertainment.” Factor
3 measures the “Affiliation with the Sport.” Factor 4 is “Time
Constraints.” Factor 5 is a measure “Team Familiarity.”
Finally, Factor 6 is “Lack of Awareness.”

The purpose of the factor analysis was to use the results in a regression
model to explain attendance. As described by Hair et al. (1995) surrogate
variables, summated scales, or factor scores might be used for this purpose.
For this study, factor scores were used. The independent variables in
the model were therefore the six factors described above, using the corresponding
factor scores, and a number of dummy variables: GENDER (the gender of
the respondent; 0 = male, 1 = female), MARITAL (marital status; 0 = single,
1 = married), and CHILDREN (whether the respondent has children; 0 = no,
1 = yes). Finally, the eight Likert scale variables that were eliminated
from the factor analysis were included.

The dependent variable, which is the number of home games attended (GAMES),
is a series of discrete values from 1 to 5 (1 = first home game, 2 = 2
home games, 3 = 3 or 4 home games, 4 = 5 to 7 home games, inclusive, and
5 = 8 or more home games). The distribution of GAMES is shown below.

GAMES Frequency
1 = 1st game 65
2 = 2nd game 50
3 = 3rd or 4th game 61
4 = 4 to 7 games 77
5 = 8 or more games 151

An appropriate regression procedure when the dependent variable is ordinally
scaled is ordered probit. Therefore, in order to examine the effects of
the independent variables on attendance, Minitab’s? ordered probit
procedure was used with GAMES as the dependent variable and with the factor
scores for the six factors and the other independent variables as described
above. The results were that only the six factors were statistically significant.
Therefore, another ordered probit model was created using only the six
factors; the results are shown below. The model is statistically significant
based on the G statistic, which follows a ?2 distribution with the degrees
of freedom equal to the number of independent variables (Hosmer and Lemeshow,
1989).

Predictor Coefficient P-Value
Const(1) -1.42704 0.000
Const(2) -0.81649 0.000
Const(3) -0.20946 0.004
Const(4) 0.50139 0.000
factor1 -0.56369 0.000
factor2 0.22179 0.000
factor3 -0.30048 0.000
factor4 0.26738 0.000
factor5 -0.61468 0.000
factor6 0.29300 0.000

Log-likelihood = -495.180
Test that all slopes are zero: G = 239.220, DF = 6, P-Value = 0.000

Factors 1 through 6 are all significant using a 5% alpha value. Because
of the way Minitab? calculates the coefficients in ordered probit analysis,
the reported negative coefficients indicate that an increase in the independent
variable tends to be associated with a greater attendance. The pattern
of coefficients is as one would expect.

In linear regression, the estimated coefficients can be interpreted as
marginal effects. In ordered probit, the marginal effects must be calculated
using the coefficients, and are reported as probabilities. The marginal
effects were calculated and resulted in importance ranking of the factors
that were the same as the absolute value of each factor’s coefficient.
Therefore, the importance ranking of the six factors, from most to least,
is Factor 5 (Team Familiarity), Factor 1 (College Affiliation), Factor
3 (Affiliation with the Sport), Factor 6 (Lack of Awareness), Factor 4
(Time Constraints), and Factor 2 (Entertainment).

Discussion

Factor 1: College Affiliation

Research within the social science discipline indicates that peer group
affiliation creates a sense of belonging and identity (Parsons, 1993).
While secondary group affiliation plays a smaller role in the individual’s
identity and affiliation in terms of group dynamics, individual membership
and a sense of belonging are important to the formation of organizational
cultures. Larger organizational groupings do tend to play a major role
in the development of the type of organizational culture thought to exist
on many college campuses. Secondary group membership has been closely
linked with both organizational culture and the development of esprit
de corps within the organizational structure (Hunt, Wood, and Chonko,
1989; Tajfel, 1981). As Wakefield (1995) has indicated, attending a sporting
event is a highly social event, and thus the effects of reference group
acceptance may be considered a determining factor in patronage intentions.
Murrell and Dietz (1992) have also indicated that fans who maintain a
strong identity with a university as their relevant institution, will
manifest that identification in greater support for the school’s
sports teams. In the present study, Factor 1 (College Affiliation) was
the second most important factor influencing attendance, suggesting that
individual association with a school has a powerful effect on attendance
at school sponsored sporting events.

Factor 2: Entertainment

The Entertainment factor was the least important influence on attendance.
Entertainment included special events, prizes, and sales promotions designed
to increase excitement and attendance. Research on the actual effect of
promotional activities on sport attendance is varied even though promotion
of sporting events is considered an essential element of success for any
sport franchise. Promotional activities, however, have been demonstrated
to produce mixed results. While some teams experience increased sport
attendance figures throughout the season as a result of the team’s
promotional activities, other teams have discovered that much of what
constitutes an “increase” is in fact temporal. The net effect
of season long stimulation for the purpose of increasing patronage is
that that a marketing barrage only affects those people who attend solely
for the purpose of receiving the sort of novelty item being offered at
a “special event” (Pitts and Stotlar, 1996). Hence, there
is a fine line between drawing attention to the team (or to the sporting
event) and interrupting the normal attendance schedule through promotional
activities. Promotions can either be considered an effective method of
demonstrating appreciation to the everyday sport consumer, or they can
mask serious deficiencies in actual fan support.

Factor 3: Affiliation with the Sport

One of the more obvious reasons why individuals would choose to attend
a sporting event is because they enjoy the sport itself. People who are
fans of a sport have developed a fondness for the intricacies of the game
and are more likely to choose to further their own participation in the
sport by becoming fans. Krohn and Clarke (1998) indicate that people who
attend sporting events can be characterized either as spectators or fans.
While spectators fulfill their enjoyment by casually viewing the sport
and not getting caught up in the logistics of the event, most true fans
attend sporting events because of some deep involvement in what the authors
describe as “the almost religious rituals” one sometimes associates
with the sporting event itself. While there are many ways of developing
an interest in a sport, one of the principal methods of developing deep
knowledge of a sport is through participation, either as a player or as
a spectator.

Factor 4: Time Constraints

This was the fifth most important factor in the model. In order for sporting
events to become attractive enough so that they become an integral part
of the fan’s schedule, the scheduling of the events should coincide
with the lifestyle and schedule of the primary attendees. The timing of
a sporting event is important in that if it is not conducive to the time
constraints and scheduling conflicts of the primary fan base, then the
event will not be well attended. However, it could be argued that time
conflicts are an excuse for not attending. A true fan would find how to
attend in spite of conflicts.

Factor 5: Team Familiarity

This was the most important influence on attendance in the model. Fan
identification with players of a particular sports team is an area in
which personal commitment and emotional involvement by the fan often occurs.
In rare cases, fans have so closely identified themselves with an organization’s
players that they begin to define themselves in terms of the attributes
of those players (Mael and Ashforth, 1992). Wann and Branscombe (1993)
have found that high fan identification with a team and its players relates
to additional involvement with the team, which in turn relates to greater
attendance at home games. In general, sport as a whole is thought to differ
significantly from other forms of entertainment because sports tend to
evoke a higher level of emotional attachment and identification from its
fans (Sutton, et al., 1997). As Lever (1983) indicates, sport not only
promotes communication among people, it tends to involve diverse groups
of people by providing common symbols and a collective sense of solidarity
for both the players and the sports organization.

Factor 6: Lack of Awareness

College athletic departments share the common need of promoting their
own product, in this case, the sporting event itself. Ironically, advertising
the event and promoting the general awareness of the scheduled time of
play and the opponent during the contest is not listed as the top perceived
priority of athletic department marketing personnel. Instead, college
athletic department marketing personnel list the job of selling corporate
sponsorships as their top priority. The second most important job responsibility
(as identified by 52% of athletic directors) is the planning and implementation
of individual game promotions, followed closely (at 48%) by planning and
directing season-ticket campaigns (Lehnus and Miller, 1996).

Respondents mentioned the general lack of awareness and knowledge of
the time of the sporting event and lack of awareness and knowledge about
the identity of the opponent as possible factors for why fans failed to
show for the game but, as with time conflicts, this may simply be an excuse.
Real fans would learn about the schedule.

Conclusions and Strategy Recommendations

An interesting outcome of this study is the relatively low importance
of win/loss records in explaining attendance. Only one of the Likert questions
(Q37: “I would not attend <SCHOOL> basketball games if the
team were not winning) was used in the factor analysis, and it loaded
(loading = 0.398) on the Entertainment factor. The three other questions
concerning the records of the teams (Q36: “One of the main reasons
I attend <SCHOOL> basketball games now is because of the team’s
record,” Q38: “I am attending <SCHOOL> basketball games
lately because of the team’s national small college ranking,”
and Q39: “The team’s record does not really affect my attendance
level”) were not significant in explaining attendance in the original
model.

That identification with players (Team Familiarity) resulted in being
the most important factor is not surprising for a smaller college. For
current students, the chances of knowing a player are likely to be greater
at smaller colleges.

Based on this sample, encouraging connections to players (Factor 5: Team
Familiarity) and the college (College Affiliation), in that order, will
have the greatest impact on encouraging heavy use. The results suggest
the following guidelines, roughly in order of importance, for encouraging
heavy users in small college basketball. These suggestions should be viewed
as complementary to the findings of Wells et al. (2000). Although their
study involved small-college football and our study basketball, we suspect
the same would be true for other sports.

• Make team members accessible to fellow students and community
members. Do not have special dormitories, etc. which would separate student
athletes from fellow students. Also, encourage other participants in the
sporting event (e.g., cheerleaders, members of the pep band, etc.) to
interact with students and the community.
• Encourage identification of the community and students with the
college.
• Help potential fans understand basketball better in an attempt
to convert people to true fans. Sessions with coaches and players in which
past games are analyzed and current strategy is discussed might be helpful.
These sessions would help with the previous two bullets as well.
• Ensure awareness of the times and dates of games. Merely printing
a schedule is not enough. Market segments must be identified in terms
of how best to aggressively inform them of the times and dates.
• Schedule college events to avoid conflicts with the sports schedule.
• Use promotions and other activities to improve the excitement
and entertainment value of the sporting event, taking care to make sure
that these activities are complementary to the event and do not detract
from it.

Exhibit I

Likert Scale Variables and Highest Factor Loadings
(1 = Strongly Disagree, 5 = Strongly Agree)

Variable Factor Loading
Q1: One of the main reasons I go to basketball games here is because
I want to support the <school> basketball program.
1 0.735
Q2: I am a fan of <SCHOOL> basketball. 1 0.729
Q3: I do not care whether the <SCHOOL> team wins the game. 1 -0.521
Q4: It is important for me to support the <SCHOOL> basketball
teams.
1 0.778
Q5: If I could attend the similar sporting events elsewhere I would
still choose to support <SCHOOL> sports.
1 0.759
Q6: I attend sporting events here primarily because I love to watch
basketball.
3 0.713
Q7: The primary reason I attend basketball games here at <SCHOOL>
is because I love to watch the sport itself.
3 0.803
Q8: The basketball game itself is the most important reason I attend
games here at <SCHOOL>.
3 0.829
Q9: The basketball game itself is not the main reason I attend games
at <SCHOOL>.
3 -0.658
Q10: The special events (e.g., games at which cash or prizes are given)
are main reasons I attend <SCHOOL> basketball games.
2 0.734
Q11: I would attend <SCHOOL> basketball games even if there were
no prizes given out during the games.
Not factored
Q12: The prizes given out at <SCHOOL> basketball games are more
important to me than attending for the sport itself.
2 0.783
Q13: The prizes given out during the game are more important to me than
supporting the <SCHOOL> basketball team.
2 0.811
Q14: I attend basketball sporting events at <SCHOOL> primarily
because they are very inexpensive.
Not factored
Q15: I usually have scheduling conflicts at the same time that the games
are being played.
4 0.752
Q16: I would rather watch basketball on television than attend the games
at <SCHOOL>.
1 -0.586
Q17: Fraternity and sorority functions often interfere with my attendance
at games.
2 0.475
Q18: I would rather spend my time engaged in attending religious activities
than attending <SCHOOL> basketball games.
Not factored
Q19: I would rather play basketball than watch the game being played. 1 -0.485

Factor Labels:
Factor 1 = College Affiliation, Factor 2 = Entertainment, Factor 3 = Affiliation
with the Sport
Factor 4 = Time Constraints, Factor 5 = Team Familiarity, Factor 6 = Lack
of Awareness

Exhibit I (continued)

Variable Factor Loading
Q20: I would rather watch movies or television than attend <SCHOOL>
basketball games.
1 -0.575
Q21: I would rather spend my time doing homework or studying than attending
<SCHOOL> basketball games.
2 0.400
Q22: I am familiar with many of the players on the <SCHOOL> basketball
teams.
5 0.677
Q23: I attend basketball games at <SCHOOL> because I like many
of the players.
5 0.709
Q24: I don’t attend many basketball games at <SCHOOL> because
I am not familiar with any of the players.
2 0.406
Q25: <SCHOOL> basketball players don’t interest me in the
least.
2 0.310
Q26: I’ve become familiar with many of the players on the <SCHOOL>
basketball team through my attendance.
5 0.503
Q27: I attend basketball games at <SCHOOL> because I like the cheerleaders. Not factored
Q28: The cheerleaders, the pep band, and the dance team greatly influence
my attendance at <SCHOOL> basketball games.
Not factored
Q29: I would go to a <SCHOOL> basketball games just to watch the
cheerleaders and dance team.
2 0.483
Q30: If the games were held at a different time I would attend more <SCHOOL>
basketball games.
4 0.779
Q31: I generally have too many other time conflicts on the days that
<SCHOOL> basketball games are played.
4 0.782
Q32: If the games were played earlier I would attend more <SCHOOL>
basketball games.
4 0.622
Q33: I’d attend more basketball games if I knew when they were
being played.
6 0.641
Q34: I’m not always aware of when the games are being played. 6 0.684
Q35: I generally know about the basketball games in advance. 6 -0.509
Q36: One of the main reasons I attend <SCHOOL> basketball games
now is because of the team’s record.
Not factored
Q37: I would not attend <SCHOOL> basketball games if the team was
not winning.
2 0.398
Q38: I am attending <SCHOOL> basketball games lately because of
the team’s national small college ranking.
Not factored
Q39: The team’s record does not really affect my attendance level. Not factored

Factor Labels:
Factor 1 = College Affiliation, Factor 2 = Entertainment, Factor 3 = Affiliation
with the Sport
Factor 4 = Time Constraints, Factor 5 = Team Familiarity, Factor 6 = Lack
of Awareness

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