{"id":248,"date":"2006-09-01T10:21:51","date_gmt":"2006-09-01T15:21:51","guid":{"rendered":""},"modified":"2015-03-27T13:30:32","modified_gmt":"2015-03-27T18:30:32","slug":"a-model-of-the-factors-contributing-to-fan-support-at-small-college-athletic-events","status":"publish","type":"post","link":"https:\/\/thesportjournal.org\/article\/a-model-of-the-factors-contributing-to-fan-support-at-small-college-athletic-events\/","title":{"rendered":"A Model of the Factors Contributing to Fan Support at Small-College Athletic Events"},"content":{"rendered":"
Submitted by: Alan Brokaw , Dr. George W. Stone & Michael A. Jones<\/div>\n

Introduction<\/strong><\/p>\n

A great deal has been written in both academic and popular periodicals
\nabout the value of college athletic programs. While some argue that the
\nnet outcome of college athletic programs is favorable in terms of benefits
\nto the institution, detractors often view these programs as financially
\ndebilitating to the welfare of the institution (Weeth, 1994). An issue
\nof controversy for many institutions is the value of the benefits versus
\nthe cost associated with operating intercollegiate athletic programs (Lehnus
\nand Miller, 1996). The dilemma for administrators is often more pressing
\nat the small-college level because funding is usually limited and the
\nprograms themselves generally prove to be unprofitable (Helitzer, 1996).
\nOne of the more pressing problems for many small-college athletic programs
\nis the lack of fan attendance, because attendance can influence support
\nfrom alumni and the administration of the school. The present study examines
\nwhat factors are key in explaining attendance at small-college sporting
\nevents.<\/p>\n

<\/p>\n

Factors Affecting Attendance<\/strong><\/p>\n

Much research effort has been dedicated to the study of fan attendance
\nin an attempt to assess fan motivation and other related factors predicting
\nfan attendance (Wakefield, 1995; Mawson and Coan, 1994; Baade and Tiehen,
\n1990; Noll, 1974). A number of conceptual and empirical studies have been
\ndirected in the area of sports-fan identity with the team as a future
\npredictor of attendance (Fisher and Wakefield, 1998; Wann and Schrader,
\n1997: Zhang, Smith, and Pease, 1996; Pol and Pak, 1994; Yeagin, 1986).
\nThese investigations build upon earlier consumer research in such areas
\nas group involvement and group identification. Additional streams of sports
\nmarketing research address sports promotion (Helitzer, 1996; Graham, Goldblatt,
\nand Delpy, 1995; and Wilkenson, 1993) as part of the attendance model.
\nNone of these articles, however, specifically address the promotion of
\nattendance at small-college athletic programs. Wells et al. (2000) is
\none of the few studies that address attendance at small-college sporting
\nevents. They studied small-college football attendance using nine determinants
\nfrom DeSchriver\u2019s (1996) model as well as fourteen additional determinants
\nfrom a literature review of fan attendance to develop their model. The
\nsignificant variables in their analysis were time and season of the game,
\nwinning percentage of the team, promotional effort, prices, whether or
\nnot the school had a sport marketing position, student enrollment, and
\nthe existence of booster clubs.<\/p>\n

Data Collection and Analysis<\/strong><\/p>\n

Data were collected at intercollegiate basketball games involving three
\nsmall schools in the South and Midwest at approximately the same time
\nof the season. The questionnaire that was used incorporated much of what
\nis known or understood to be the salient factors affecting attendance
\nwhile including additional factors that were derived from a series of
\nfocus group studies with fans of various sports teams from several small
\ncolleges. It included thirty-nine Likert scale questions (See Exhibit
\nI for a list of the Likert questions). 492 questionnaires were completed.
\nMissing data reduced the number of usable questionnaires to 404.<\/p>\n

The thirty-nine Likert scale statements (1 = strongly disagree to 5 =
\nstrongly agree) were analyzed using factor analysis to determine their
\nbasic, underlying structure. As described by Hair et al. (1995), eight
\nof the variables were excluded from the factor analysis because of low
\ncorrelations with the other variables. Six factors were extracted, based
\non the criterion of having eigenvalues greater than one. The six factors
\nrepresented slightly over 55% of the variability in the data. The factor
\nloadings, after varimax rotation, for the remaining thirty-one variables
\non the six factors are shown in Exhibit I; the eight variables not included
\nin the factor analysis are also described.<\/p>\n

Based on the pattern of factor loadings, Factor 1 is labeled \u201cCollege
\nAffiliation.\u201d Factor 2 is labeled \u201cEntertainment.\u201d Factor
\n3 measures the \u201cAffiliation with the Sport.\u201d Factor 4 is \u201cTime
\nConstraints.\u201d Factor 5 is a measure \u201cTeam Familiarity.\u201d
\nFinally, Factor 6 is \u201cLack of Awareness.\u201d<\/p>\n

The purpose of the factor analysis was to use the results in a regression
\nmodel to explain attendance. As described by Hair et al. (1995) surrogate
\nvariables, summated scales, or factor scores might be used for this purpose.
\nFor this study, factor scores were used. The independent variables in
\nthe model were therefore the six factors described above, using the corresponding
\nfactor scores, and a number of dummy variables: GENDER (the gender of
\nthe respondent; 0 = male, 1 = female), MARITAL (marital status; 0 = single,
\n1 = married), and CHILDREN (whether the respondent has children; 0 = no,
\n1 = yes). Finally, the eight Likert scale variables that were eliminated
\nfrom the factor analysis were included.<\/p>\n

The dependent variable, which is the number of home games attended (GAMES),
\nis a series of discrete values from 1 to 5 (1 = first home game, 2 = 2
\nhome games, 3 = 3 or 4 home games, 4 = 5 to 7 home games, inclusive, and
\n5 = 8 or more home games). The distribution of GAMES is shown below.<\/p>\n\n\n\n\n\n\n\n\n
GAMES<\/td>\nFrequency<\/td>\n<\/tr>\n
1 = 1st game<\/td>\n65<\/td>\n<\/tr>\n
2 = 2nd game<\/td>\n50<\/td>\n<\/tr>\n
3 = 3rd or 4th game<\/td>\n61<\/td>\n<\/tr>\n
4 = 4 to 7 games<\/td>\n77<\/td>\n<\/tr>\n
5 = 8 or more games<\/td>\n151<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

An appropriate regression procedure when the dependent variable is ordinally
\nscaled is ordered probit. Therefore, in order to examine the effects of
\nthe independent variables on attendance, Minitab\u2019s? ordered probit
\nprocedure was used with GAMES as the dependent variable and with the factor
\nscores for the six factors and the other independent variables as described
\nabove. The results were that only the six factors were statistically significant.
\nTherefore, another ordered probit model was created using only the six
\nfactors; the results are shown below. The model is statistically significant
\nbased on the G statistic, which follows a ?2 distribution with the degrees
\nof freedom equal to the number of independent variables (Hosmer and Lemeshow,
\n1989).<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Predictor<\/td>\nCoefficient<\/td>\nP-Value<\/td>\n<\/tr>\n
Const(1)<\/td>\n-1.42704<\/td>\n0.000<\/td>\n<\/tr>\n
Const(2)<\/td>\n-0.81649<\/td>\n0.000<\/td>\n<\/tr>\n
Const(3)<\/td>\n-0.20946<\/td>\n0.004<\/td>\n<\/tr>\n
Const(4)<\/td>\n0.50139<\/td>\n0.000<\/td>\n<\/tr>\n
factor1<\/td>\n-0.56369<\/td>\n0.000<\/td>\n<\/tr>\n
factor2<\/td>\n0.22179<\/td>\n0.000<\/td>\n<\/tr>\n
factor3<\/td>\n-0.30048<\/td>\n0.000<\/td>\n<\/tr>\n
factor4<\/td>\n0.26738<\/td>\n0.000<\/td>\n<\/tr>\n
factor5<\/td>\n-0.61468<\/td>\n0.000<\/td>\n<\/tr>\n
factor6<\/td>\n0.29300<\/td>\n0.000<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Log-likelihood = -495.180
\nTest that all slopes are zero: G = 239.220, DF = 6, P-Value = 0.000<\/p>\n

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

In linear regression, the estimated coefficients can be interpreted as
\nmarginal effects. In ordered probit, the marginal effects must be calculated
\nusing the coefficients, and are reported as probabilities. The marginal
\neffects were calculated and resulted in importance ranking of the factors
\nthat were the same as the absolute value of each factor\u2019s coefficient.
\nTherefore, the importance ranking of the six factors, from most to least,
\nis Factor 5 (Team Familiarity), Factor 1 (College Affiliation), Factor
\n3 (Affiliation with the Sport), Factor 6 (Lack of Awareness), Factor 4
\n(Time Constraints), and Factor 2 (Entertainment).<\/p>\n

Discussion<\/strong><\/p>\n

Factor 1: College Affiliation<\/em><\/p>\n

Research within the social science discipline indicates that peer group
\naffiliation creates a sense of belonging and identity (Parsons, 1993).
\nWhile secondary group affiliation plays a smaller role in the individual\u2019s
\nidentity and affiliation in terms of group dynamics, individual membership
\nand a sense of belonging are important to the formation of organizational
\ncultures. Larger organizational groupings do tend to play a major role
\nin the development of the type of organizational culture thought to exist
\non many college campuses. Secondary group membership has been closely
\nlinked with both organizational culture and the development of esprit
\nde corps within the organizational structure (Hunt, Wood, and Chonko,
\n1989; Tajfel, 1981). As Wakefield (1995) has indicated, attending a sporting
\nevent is a highly social event, and thus the effects of reference group
\nacceptance may be considered a determining factor in patronage intentions.
\nMurrell and Dietz (1992) have also indicated that fans who maintain a
\nstrong identity with a university as their relevant institution, will
\nmanifest that identification in greater support for the school\u2019s
\nsports teams. In the present study, Factor 1 (College Affiliation) was
\nthe second most important factor influencing attendance, suggesting that
\nindividual association with a school has a powerful effect on attendance
\nat school sponsored sporting events.<\/p>\n

Factor 2: Entertainment<\/em><\/p>\n

The Entertainment factor was the least important influence on attendance.
\nEntertainment included special events, prizes, and sales promotions designed
\nto increase excitement and attendance. Research on the actual effect of
\npromotional activities on sport attendance is varied even though promotion
\nof sporting events is considered an essential element of success for any
\nsport franchise. Promotional activities, however, have been demonstrated
\nto produce mixed results. While some teams experience increased sport
\nattendance figures throughout the season as a result of the team\u2019s
\npromotional activities, other teams have discovered that much of what
\nconstitutes an \u201cincrease\u201d is in fact temporal. The net effect
\nof season long stimulation for the purpose of increasing patronage is
\nthat that a marketing barrage only affects those people who attend solely
\nfor the purpose of receiving the sort of novelty item being offered at
\na \u201cspecial event\u201d (Pitts and Stotlar, 1996). Hence, there
\nis a fine line between drawing attention to the team (or to the sporting
\nevent) and interrupting the normal attendance schedule through promotional
\nactivities. Promotions can either be considered an effective method of
\ndemonstrating appreciation to the everyday sport consumer, or they can
\nmask serious deficiencies in actual fan support.<\/p>\n

Factor 3: Affiliation with the Sport<\/em><\/p>\n

One of the more obvious reasons why individuals would choose to attend
\na sporting event is because they enjoy the sport itself. People who are
\nfans of a sport have developed a fondness for the intricacies of the game
\nand are more likely to choose to further their own participation in the
\nsport by becoming fans. Krohn and Clarke (1998) indicate that people who
\nattend sporting events can be characterized either as spectators or fans.
\nWhile spectators fulfill their enjoyment by casually viewing the sport
\nand not getting caught up in the logistics of the event, most true fans
\nattend sporting events because of some deep involvement in what the authors
\ndescribe as \u201cthe almost religious rituals\u201d one sometimes associates
\nwith the sporting event itself. While there are many ways of developing
\nan interest in a sport, one of the principal methods of developing deep
\nknowledge of a sport is through participation, either as a player or as
\na spectator.<\/p>\n

Factor 4: Time Constraints<\/em><\/p>\n

This was the fifth most important factor in the model. In order for sporting
\nevents to become attractive enough so that they become an integral part
\nof the fan\u2019s schedule, the scheduling of the events should coincide
\nwith the lifestyle and schedule of the primary attendees. The timing of
\na sporting event is important in that if it is not conducive to the time
\nconstraints and scheduling conflicts of the primary fan base, then the
\nevent will not be well attended. However, it could be argued that time
\nconflicts are an excuse for not attending. A true fan would find how to
\nattend in spite of conflicts.<\/p>\n

Factor 5: Team Familiarity<\/em><\/p>\n

This was the most important influence on attendance in the model. Fan
\nidentification with players of a particular sports team is an area in
\nwhich personal commitment and emotional involvement by the fan often occurs.
\nIn rare cases, fans have so closely identified themselves with an organization\u2019s
\nplayers that they begin to define themselves in terms of the attributes
\nof those players (Mael and Ashforth, 1992). Wann and Branscombe (1993)
\nhave found that high fan identification with a team and its players relates
\nto additional involvement with the team, which in turn relates to greater
\nattendance at home games. In general, sport as a whole is thought to differ
\nsignificantly from other forms of entertainment because sports tend to
\nevoke a higher level of emotional attachment and identification from its
\nfans (Sutton, et al., 1997). As Lever (1983) indicates, sport not only
\npromotes communication among people, it tends to involve diverse groups
\nof people by providing common symbols and a collective sense of solidarity
\nfor both the players and the sports organization.<\/p>\n

Factor 6: Lack of Awareness<\/em><\/p>\n

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

Respondents mentioned the general lack of awareness and knowledge of
\nthe time of the sporting event and lack of awareness and knowledge about
\nthe identity of the opponent as possible factors for why fans failed to
\nshow for the game but, as with time conflicts, this may simply be an excuse.
\nReal fans would learn about the schedule.<\/p>\n

Conclusions and Strategy Recommendations<\/strong><\/p>\n

An interesting outcome of this study is the relatively low importance
\nof win\/loss records in explaining attendance. Only one of the Likert questions
\n(Q37: \u201cI would not attend <SCHOOL> basketball games if the
\nteam were not winning) was used in the factor analysis, and it loaded
\n(loading = 0.398) on the Entertainment factor. The three other questions
\nconcerning the records of the teams (Q36: \u201cOne of the main reasons
\nI attend <SCHOOL> basketball games now is because of the team\u2019s
\nrecord,\u201d Q38: \u201cI am attending <SCHOOL> basketball games
\nlately because of the team\u2019s national small college ranking,\u201d
\nand Q39: \u201cThe team\u2019s record does not really affect my attendance
\nlevel\u201d) were not significant in explaining attendance in the original
\nmodel.<\/p>\n

That identification with players (Team Familiarity) resulted in being
\nthe most important factor is not surprising for a smaller college. For
\ncurrent students, the chances of knowing a player are likely to be greater
\nat smaller colleges.<\/p>\n

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

\u2022 Make team members accessible to fellow students and community
\nmembers. Do not have special dormitories, etc. which would separate student
\nathletes from fellow students. Also, encourage other participants in the
\nsporting event (e.g., cheerleaders, members of the pep band, etc.) to
\ninteract with students and the community.
\n\u2022 Encourage identification of the community and students with the
\ncollege.
\n\u2022 Help potential fans understand basketball better in an attempt
\nto convert people to true fans. Sessions with coaches and players in which
\npast games are analyzed and current strategy is discussed might be helpful.
\nThese sessions would help with the previous two bullets as well.
\n\u2022 Ensure awareness of the times and dates of games. Merely printing
\na schedule is not enough. Market segments must be identified in terms
\nof how best to aggressively inform them of the times and dates.
\n\u2022 Schedule college events to avoid conflicts with the sports schedule.
\n\u2022 Use promotions and other activities to improve the excitement
\nand entertainment value of the sporting event, taking care to make sure
\nthat these activities are complementary to the event and do not detract
\nfrom it.<\/p>\n

Exhibit I<\/p>\n

Likert Scale Variables and Highest Factor Loadings
\n(1 = Strongly Disagree, 5 = Strongly Agree)<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Variable<\/td>\n<\/td>\nFactor<\/td>\nLoading<\/td>\n<\/tr>\n
Q1:<\/td>\nOne of the main reasons I go to basketball games here is because
\nI want to support the <school> basketball program.<\/td>\n		1<\/td>\n0.735<\/td>\n<\/tr>\n
Q2:<\/td>\nI am a fan of <SCHOOL> basketball.<\/td>\n1<\/td>\n0.729<\/td>\n<\/tr>\n
Q3:<\/td>\nI do not care whether the <SCHOOL> team wins the game.<\/td>\n1<\/td>\n-0.521<\/td>\n<\/tr>\n
Q4:<\/td>\nIt is important for me to support the <SCHOOL> basketball
\nteams.<\/td>\n		1<\/td>\n0.778<\/td>\n<\/tr>\n
Q5:<\/td>\nIf I could attend the similar sporting events elsewhere I would
\nstill choose to support <SCHOOL> sports.<\/td>\n		1<\/td>\n0.759<\/td>\n<\/tr>\n
Q6:<\/td>\nI attend sporting events here primarily because I love to watch
\nbasketball.<\/td>\n		3<\/td>\n0.713<\/td>\n<\/tr>\n
Q7:<\/td>\nThe primary reason I attend basketball games here at <SCHOOL>
\nis because I love to watch the sport itself.<\/td>\n		3<\/td>\n0.803<\/td>\n<\/tr>\n
Q8:<\/td>\nThe basketball game itself is the most important reason I attend
\ngames here at <SCHOOL>.<\/td>\n		3<\/td>\n0.829<\/td>\n<\/tr>\n
Q9:<\/td>\nThe basketball game itself is not the main reason I attend games
\nat <SCHOOL>.<\/td>\n		3<\/td>\n-0.658<\/td>\n<\/tr>\n
Q10:<\/td>\nThe special events (e.g., games at which cash or prizes are given)
\nare main reasons I attend <SCHOOL> basketball games.<\/td>\n		2<\/td>\n0.734<\/td>\n<\/tr>\n
Q11:<\/td>\nI would attend <SCHOOL> basketball games even if there were
\nno prizes given out during the games.<\/td>\n		Not factored<\/td>\n<\/tr>\n
Q12:<\/td>\nThe prizes given out at <SCHOOL> basketball games are more
\nimportant to me than attending for the sport itself.<\/td>\n		2<\/td>\n0.783<\/td>\n<\/tr>\n
Q13:<\/td>\nThe prizes given out during the game are more important to me than
\nsupporting the <SCHOOL> basketball team.<\/td>\n		2<\/td>\n0.811<\/td>\n<\/tr>\n
Q14:<\/td>\nI attend basketball sporting events at <SCHOOL> primarily
\nbecause they are very inexpensive.<\/td>\n		Not factored<\/td>\n<\/tr>\n
Q15:<\/td>\nI usually have scheduling conflicts at the same time that the games
\nare being played.<\/td>\n		4<\/td>\n0.752<\/td>\n<\/tr>\n
Q16:<\/td>\nI would rather watch basketball on television than attend the games
\nat <SCHOOL>.<\/td>\n		1<\/td>\n-0.586<\/td>\n<\/tr>\n
Q17:<\/td>\nFraternity and sorority functions often interfere with my attendance
\nat games.<\/td>\n		2<\/td>\n0.475<\/td>\n<\/tr>\n
Q18:<\/td>\nI would rather spend my time engaged in attending religious activities
\nthan attending <SCHOOL> basketball games.<\/td>\n		Not factored<\/td>\n<\/tr>\n
Q19:<\/td>\nI would rather play basketball than watch the game being played.<\/td>\n1<\/td>\n-0.485<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Factor Labels:
\nFactor 1 = College Affiliation, Factor 2 = Entertainment, Factor 3 = Affiliation
\nwith the Sport
\nFactor 4 = Time Constraints, Factor 5 = Team Familiarity, Factor 6 = Lack
\nof Awareness<\/p>\n

Exhibit I (continued)<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Variable<\/td>\n<\/td>\nFactor<\/td>\nLoading<\/td>\n<\/tr>\n
Q20:<\/td>\nI would rather watch movies or television than attend <SCHOOL>
\nbasketball games.<\/td>\n		1<\/td>\n-0.575<\/td>\n<\/tr>\n
Q21:<\/td>\nI would rather spend my time doing homework or studying than attending
\n<SCHOOL> basketball games.<\/td>\n		2<\/td>\n0.400<\/td>\n<\/tr>\n
Q22:<\/td>\nI am familiar with many of the players on the <SCHOOL> basketball
\nteams.<\/td>\n		5<\/td>\n0.677<\/td>\n<\/tr>\n
Q23:<\/td>\nI attend basketball games at <SCHOOL> because I like many
\nof the players.<\/td>\n		5<\/td>\n0.709<\/td>\n<\/tr>\n
Q24:<\/td>\nI don\u2019t attend many basketball games at <SCHOOL> because
\nI am not familiar with any of the players.<\/td>\n		2<\/td>\n0.406<\/td>\n<\/tr>\n
Q25:<\/td>\n<SCHOOL> basketball players don\u2019t interest me in the
\nleast.<\/td>\n		2<\/td>\n0.310<\/td>\n<\/tr>\n
Q26:<\/td>\nI\u2019ve become familiar with many of the players on the <SCHOOL>
\nbasketball team through my attendance.<\/td>\n		5<\/td>\n0.503<\/td>\n<\/tr>\n
Q27:<\/td>\nI attend basketball games at <SCHOOL> because I like the cheerleaders.<\/td>\nNot factored<\/td>\n<\/tr>\n
Q28:<\/td>\nThe cheerleaders, the pep band, and the dance team greatly influence
\nmy attendance at <SCHOOL> basketball games.<\/td>\n		Not factored<\/td>\n<\/tr>\n
Q29:<\/td>\nI would go to a <SCHOOL> basketball games just to watch the
\ncheerleaders and dance team.<\/td>\n		2<\/td>\n0.483<\/td>\n<\/tr>\n
Q30:<\/td>\nIf the games were held at a different time I would attend more <SCHOOL>
\nbasketball games.<\/td>\n		4<\/td>\n0.779<\/td>\n<\/tr>\n
Q31:<\/td>\nI generally have too many other time conflicts on the days that
\n<SCHOOL> basketball games are played.<\/td>\n		4<\/td>\n0.782<\/td>\n<\/tr>\n
Q32:<\/td>\nIf the games were played earlier I would attend more <SCHOOL>
\nbasketball games.<\/td>\n		4<\/td>\n0.622<\/td>\n<\/tr>\n
Q33:<\/td>\nI\u2019d attend more basketball games if I knew when they were
\nbeing played.<\/td>\n		6<\/td>\n0.641<\/td>\n<\/tr>\n
Q34:<\/td>\nI\u2019m not always aware of when the games are being played.<\/td>\n6<\/td>\n0.684<\/td>\n<\/tr>\n
Q35:<\/td>\nI generally know about the basketball games in advance.<\/td>\n6<\/td>\n-0.509<\/td>\n<\/tr>\n
Q36:<\/td>\nOne of the main reasons I attend <SCHOOL> basketball games
\nnow is because of the team\u2019s record.<\/td>\n		Not factored<\/td>\n<\/tr>\n
Q37:<\/td>\nI would not attend <SCHOOL> basketball games if the team was
\nnot winning.<\/td>\n		2<\/td>\n0.398<\/td>\n<\/tr>\n
Q38:<\/td>\nI am attending <SCHOOL> basketball games lately because of
\nthe team\u2019s national small college ranking.<\/td>\n		Not factored<\/td>\n<\/tr>\n
Q39:<\/td>\nThe team\u2019s record does not really affect my attendance level.<\/td>\nNot factored<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Factor Labels:
\nFactor 1 = College Affiliation, Factor 2 = Entertainment, Factor 3 = Affiliation
\nwith the Sport
\nFactor 4 = Time Constraints, Factor 5 = Team Familiarity, Factor 6 = Lack
\nof Awareness<\/p>\n

References<\/strong><\/p>\n

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    Submitted by: Alan Brokaw , Dr. George W. Stone & Michael A. Jones<\/div>\n

    Introduction <\/p>\n

    A great deal has been written in both academic and popular periodicals
    \n about the value of college athletic programs. While some argue that the
    \n net outcome of college athletic programs is favorable in terms of benefits
    \n to the institution, detractors often view these programs as financially
    \n debilitating to the welfare of the institution (Weeth, 1994). An issue
    \n of controversy for many institutions is the value of the benefits versus
    \n the cost associated with operating intercollegiate athletic programs (Lehnus
    \n and Miller, 1996). The dilemma for administrators is often more pressing
    \n at the small-college level because funding is usually limited and the
    \n programs themselves generally prove to be unprofitable (Helitzer, 1996).
    \n One of the more pressing problems for many small-college athletic programs
    \n is the lack of fan attendance, because attendance can influence support
    \n from alumni and the administration of the school. The present study examines
    \n what factors are key in explaining attendance at small-college sporting
    \n events.<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true,"jetpack_social_options":[]},"categories":[290,291,296],"tags":[25,8,70,75],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p4btio-40","jetpack-related-posts":[{"id":202,"url":"https:\/\/thesportjournal.org\/article\/can-academic-progress-help-collegiate-football-teams-win\/","url_meta":{"origin":248,"position":0},"title":"Can Academic Progress Help Collegiate Football Teams Win?","date":"June 3, 2005","format":false,"excerpt":"Submitted by: Jeffrey W. Lucas & Michael J. Lovaglia INTRODUCTION Recently, the National Collegiate Athletic Association (NCAA) released its first Academic Progress Rate (APR) scores for its football and basketball programs. The APR measures how well athletic programs educate student athletes and will be used to sanction programs that do\u2026","rel":"","context":"In "Contemporary Sports Issues"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":185,"url":"https:\/\/thesportjournal.org\/article\/a-look-at-womens-participation-in-sports-in-maryland-two-year-colleges\/","url_meta":{"origin":248,"position":1},"title":"A Look at Women’s Participation in Sports in Maryland Two-Year Colleges","date":"January 10, 2005","format":false,"excerpt":"Submitted by: Vincent E. Mumford Abstract Much research has been conducted on college athletics. The populations studied most often are four-year, NCAA member institutions. In higher education, 40 percent of the institutions in the United States are two-year colleges. These two-year colleges enroll more than ten million students annually (IPEDS,\u2026","rel":"","context":"In "Contemporary Sports Issues"","img":{"alt_text":"Figure One","src":"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2008\/03\/fig1.jpg?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":272,"url":"https:\/\/thesportjournal.org\/article\/non-economic-societal-impacts-of-intercollegiate-athletics\/","url_meta":{"origin":248,"position":2},"title":"Non-Economic Societal Impacts of Intercollegiate Athletics","date":"March 14, 2008","format":false,"excerpt":"Submitted by: David Larimore, Ph.D & George Chitiyo, Ph.D Abstract: Intercollegiate athletics impact society in numerous positive ways. A number of studies have been done seeking to establish the effects of these sports programs on athletes, their institutions, and society at large. This paper is a synthesis of the literature\u2026","rel":"","context":"In "Contemporary Sports Issues"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":189,"url":"https:\/\/thesportjournal.org\/article\/high-visibility-athletic-programs-and-the-prestige-of-public-universities\/","url_meta":{"origin":248,"position":3},"title":"High-Visibility Athletic Programs and the Prestige of Public Universities","date":"January 5, 2005","format":false,"excerpt":"Submitted by: Michael J. Lovaglia & Jeffrey W. Lucas Introduction: Why are athletic programs such a prominent part of higher education in the United States? Lately, educators have been questioning the value of a connection between high-visibility athletic programs and the academic mission of higher education (Sperber 2003). Do high-visibility\u2026","rel":"","context":"In "Contemporary Sports Issues"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":7914,"url":"https:\/\/thesportjournal.org\/article\/college-footballs-bottom-line-impact-exploring-the-relationship-of-football-performance-on-athletic-finances-for-division-i-institutions-today\/","url_meta":{"origin":248,"position":4},"title":"College Football\u2019s Bottom-Line Impact: Exploring the Relationship of Football Performance on Athletic Finances for Division I Institutions Today","date":"July 23, 2021","format":false,"excerpt":"Authors: Spencer D. Wyld1 and David C. Wyld2 1 Walton College of Business, Department of Finance, University of Arkansas, Fayetteville, AR, USA2 Department of Management & Business Administration, Southeastern Louisiana University, Hammond, LA, USA Corresponding Author:David C. Wyld, DBA47042 Scott DriveHammond, LA 70401dwyld@selu.edu985-789-2127 Spencer D. Wyld, M.B.A., is a doctoral\u2026","rel":"","context":"In "Research"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2021\/07\/Figure1.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":361,"url":"https:\/\/thesportjournal.org\/article\/a-comparision-of-athletic-training-program-financial-resources\/","url_meta":{"origin":248,"position":5},"title":"A Comparision of Athletic Training Program Financial Resources","date":"January 8, 2010","format":false,"excerpt":"Robert Bradley, United States Sports Academy Abstract Athletic departments have budgets for each team. Included within the athletic department master budget includes an athletic training budget. However, unlike sports programs, the athletic training budget goes not towards its own needs, but the needs of the sports teams. The size of\u2026","rel":"","context":"In "Sports Facilities"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/posts\/248"}],"collection":[{"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/comments?post=248"}],"version-history":[{"count":4,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/posts\/248\/revisions"}],"predecessor-version":[{"id":2662,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/posts\/248\/revisions\/2662"}],"wp:attachment":[{"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/media?parent=248"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/categories?post=248"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thesportjournal.org\/wp-json\/wp\/v2\/tags?post=248"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}