Testing models of motives and points of attachment among spectators in college football.
Woo, Boyun ; Trail, Galen T. ; Kwon, Hyungil Harry 等
Testing Models of Motives and Points of Attachment among Spectators
in College Football
Sport spectating is a popular leisure activity in the United
States. In fact, attendance and revenues for spectator sports have
steadily increased for the past decade. According to the U.S. Census
Bureau (2008), in 2005, it was estimated that revenue from spectator
sports was approximately $24 billion, which is 3.5% higher than the
previous year and 26.6% more than in 2000 (U.S. Census Bureau, 2008). It
was also estimated that people spent approximately $15.9 billion in 2005
for admission to professional and amateur athletic events. Attending
college football games is certainly a substantial part of spectating at
amateur athletic events activity as it was estimated that over 48
million people attended college football games in 2007 (NCAA, 2008).
This is a 30% increase from 1990 and a 10% increase compared with 2005.
As the spectator sport market has become large and competition for
consumers has increased, sport marketers' interests in searching
for more effective marketing strategies to increase attendance have also
increased. In general, dividing the market into different segmentations
and applying different strategies for each segment based on their
characteristics and needs is crucial in order to come up with effective
marketing plans. Traditionally, researchers have examined different
demographic factors, such as gender, age, education level, and household
income to determine whether segmenting the market based on these
characteristics is beneficial (e.g., Dietz-Uhler, Harrick, End, &
Jacquemotte, 2002; Fink, Trail, & Anderson, 2002b; Kahle, Kambara,
& Rose, 1996; Robinson, Trail, & Kwon, 2004; Swanson, Gwinner,
Larson, & Janda, 2003; Zhang et al., 2001). However, recently,
researchers have studied other factors, such as social values (Kahle,
Duncan, Vassilis, & Aiken, 2001), motivations (Kahle et al., 1996;
Swanson et al., 2003), and brand associations (Ross, 2007) as ways to
segment markets.
Yet, the areas of spectators' motives and points of attachment
need more attention as potential variables with which to segment
consumers. Some researchers have investigated various motives as
important factors that influence people's decisions to spectate at
sports events (Trail, Anderson, & Fink, 2000; Trail, Fink, &
Anderson, 2003; Trail & James, 2001; Wann, 1996; Won & Kitamura,
2007). Other researchers have suggested that there may be other factors
that influence people's decisions concerning sport consumer
behaviors. Kwon, Trail, and Anderson (2005) suggested that some people
watch sports events because they have a strong social-psychological
connection with a team, coach, player, university, community, level of
sport, and/or type of sport. They call these connections points of
attachment. As the concepts of motives and points of attachment have
become popular, researchers have been examining relationships among
motives and points of attachment (Fink, Trail, & Anderson, 2002a;
Robinson & Trail, 2005; Robinson, Trail, & Kwon, 2004; Trail,
Robinson, Dick, & Gillentine, 2003). These researchers claimed that
certain spectators' motives may lead to strengthening certain
points of attachment.
However, studies on the relationships among different motives and
points of attachment are still limited. Although many researchers use
different motives when examining spectators' consumption behaviors,
most researchers have only focused on team identification when
discussing points of attachment (e.g., James & Ross, 2002; Trail
& James, 2001; Fink et al., 2002a). Also, research that deals with
multiple motives and multiple points of attachments has shown
conflicting results. Therefore, it appears important to extend previous
research that examines the relationships among motives and points of
attachment.
In addition, with exception of Trail, Robinson, et al.'s
(2003) study, most studies do not make distinctions between spectators
and fans. This distinction may be valuable when studying sport consumer
behavior. According to Sloan (1989), two different types of sport
spectators may exist in a game: observers and fans. Those who attend the
games as observers do not have a strong social-psychological attachment
to team entities, such as the team, the player(s), or the coach, while
fans are more likely to be highly attached to one or more of these
potential connections. For our purposes, observers will be referred to
as spectators. According to Trail, Robinson, et al. (2003), spectators
and fans may have different motives, and these motives may lead to
different points of attachment. Thus, the purpose of the current study
was to extend
Trail, Robinson, et al.'s (2003) study on the relationships
among motives and points of attachment while making a distinction
between fan and spectator motives in the context of college football. We
propose four models that examine possible relationships among the
variables in order to find a model that explains the most variance. A
better understanding of why people attend sports events can greatly help
sport marketers develop more effective marketing strategies that can
enhance spectators' and fans' level of satisfaction with the
sport consumer experience. As a result, sport marketers would be able to
increase game attendance, media consumption, and merchandise consumption
as suggested in the previous literature (e.g., Andrew & Todd, 2007;
Fisher & Wakefield, 1998; Swanson et al., 2003; Trail & James,
2001). For example, Fisher and Wakefield (1998) discovered that group
identification, which was motivated by domain involvement, perceived
group performance, and group member attractiveness, was a significant
predictor of attendance and the purchase of licensed products. In
addition, Swanson et al. demonstrated that team identification,
eustress, group affiliation, and self-esteem enhancement were closely
related to game attendance.
Motives
Understanding sport consumer behavior such as event attendance is
important for the financial success of sport. According to Trail et al.
(2000), at least nine different motives may exist among sport
spectators. These individual motives include vicarious achievement,
acquisition of knowledge, aesthetic qualities of the game/sport, social
interaction, drama, escape, family, physical attractiveness, and
appreciation of physical skills. Previous studies have shown that these
motives are highly correlated with each other indicating that they can
be grouped into one category representing the same factor
'motive' (Robinson & Trail, 2005; Trail, Fink, et al.,
2003; Trail & James, 2001).
Other researchers suggested that these motives should be
categorized into different groups (Robinson & Trail, 2005; Trail,
Robinson, et al., 2003). Trail, Robinson, et al. (2003) grouped motives
based on whether an individual is a fan or a spectator as suggested by
Sloan (1989). They suggested that the reasons fans attend games and the
reasons spectators attend games may be quite different, although some of
the motives are applicable to both fans and spectators. They categorized
vicarious achievement as a motive for fans of successful teams, and
physical skill, aesthetic, drama, and knowledge as motives for fans of
unsuccessful teams and for spectators. In addition, social and escape
motives were classified as overarching motives that could be applied to
both groups.
Points of Attachments
Although motives and points of attachment are closely related
constructs, researchers have made a clear distinction between these two
constructs. Motives are thought to be related to basic human
"needs" (McDonald, Milne, & Hong, 2002; Robinson &
Trail, 2005), whereas points of attachment reflect a "psychological
connection" toward a certain entity (Kwon & Armstrong, 2004).
Traditionally, many studies have solely focused on team
identification when dealing with social psychological connection rather
than including other points of attachments (Wann, 1996; Wann, Dolan,
McGeorge, & Allison, 1994; Wann & Robinson, 2002). However, many
researchers now suggest that multiple points of attachment, rather than
a unidimensional attachment-to-the-team, may exist (Funk, Mahony,
Nakazawa, & Hirakawa, 2001; Kwon, Trail, & Anderson, 2005, 2006;
Murrell & Dietz, 1992; Robinson et al., 2005; Robinson & Trail,
2005; Trail, Robinson, et al., 2003). For example, Murrell and
Dietz's (1992) research suggested that identification with the
university as an important point of attachment while Funk et al. (2001)
suggested that fans' attachment to the sport and players may also
be of importance. Recognizing the possible existence of different points
of attachment, Robinson and Trail (2005) proposed that an individual
could be attached to a player, coach, community, university, level of
sport, or sport itself, in addition to the team.
[FIGURE 1 OMITTED]
Relationships between Motives and Points of Attachment
Whereas much research has frequently examined the relationships
between different motives and team identification (Fink et al., 2002a;
Fisher & Wakefield, 1998; Trail & James, 2001; Trail, Fink, et
al., 2003; Wann, Royalty, & Rochelle, 2002), several studies have
examined the relationships among multiple motives and multiple points of
attachment (Funk, Mahony, & Ridinger, 2002; Robinson & Trail,
2005; Robinson, Trail, & Kwon, 2004; Trail, Robinson, et al., 2003).
Some of these results suggest that certain motives may be good
indicators of specific points of attachment. For example, Funk, et al.
(2002) showed that, in a women's soccer game, aesthetics (r = .75)
and excitement (r = .78) motives were associated with attachment to the
sport of soccer, while social interaction was correlated with attachment
to the player (r = .29). Trail, Robinson, et al. (2003) showed that
vicarious achievement, a fan motive, was related to identification with
team, player, university, community, and coach while spectator motives
(skill, aesthetics, knowledge, and drama) were associated with
attachment to the type of sport and to the level of sport.
As mentioned earlier, the primary purpose of the current study was
to extend Trail, Robinson, et al.'s (2003) study. Two models that
showed an equal model fit (RMSEA = .061, CI = .059 - .064, ECVI = 4.19)
in the original study are also examined in the current study. In
addition, two alternative models are included. Further, these models
will be examined based on whether an individual is categorized as a fan
or a spectator. The four models included in this study are explained in
the following section.
Model A
Model A (Figure 1) is almost identical with Model C in Trail,
Robinson, et al.'s (2003) original study. Three different sets of
spectator motives are included in the model: vicarious achievement,
spectator motives, and overarching motives. Vicarious achievement is
considered to be a motive for fans, whereas spectator motives refer to
motives for spectators, and include the motives of skill, aesthetics,
drama, and knowledge. Additionally, the second order latent variable
labeled Overarching Motives, which includes escape and social
interaction, refers to motives relevant to both fans and spectators.
Research has shown that vicarious achievement is a motivator for
fans (End, Dietz-Uhler, Harrick, & Jacquemotte, 2002; Fisher &
Wakefield, 1998; Trail, Robinson, et al., 2003). End et al. (2002)
discovered that people tended to identify more with successful teams,
suggesting that fans who are highly identified value winning more
because their motivation to attend the game is to satisfy the need for
achievement through the association with a successful other. The
tendency to want to associate with successful others is called
basking-in-reflected-glory (BIRGing; Wann, & Branscombe, 1990).
Fisher and Wakefield (1998) showed that perceived success of the team
was only important for fans of successful teams for developing a group
identity. For fans of unsuccessful teams, perceived success of the team
was less important because these fans tended to focus on other motives,
such as an athlete's skills, aesthetic aspects of the performance,
drama of the games, and obtaining knowledge about the sport or the
skills. In other words, fans of successful teams appear to be motivated
to associate themselves with successful others, so they may feel
vicarious achievement when a team, player, or coach is successful.
However, highly identified fans of unsuccessful teams may not be as
motivated by vicarious achievement because their team does not win as
much. Instead, their motives might be more similar to motives of
spectators.
In contrast, escape and social motives may be applied to both fans
and spectators. According to Trail, Robinson, et al. (2003) a fan can
escape from daily life and go to the game to feel vicariously
successful, whereas a spectator can escape from daily life and go to the
game to appreciate the aesthetic qualities of the play. The fan might be
motivated by the social interaction experienced with other fans when
their team wins by BIRGing together, whereas a spectator may enjoy the
social interaction experienced with other people at the game through
sharing their knowledge together.
In addition, in this model, it was hypothesized that there is an
intercorrelation among vicarious achievement, spectator motives, and
overarching motives. Previous studies have shown that motives are
correlated to each other although some motives are more closely
correlated with each other than the others (Robinson & Trail, 2005;
Trail & James, 2001; Wann; 1995; Won & Kitamura, 2007).
Points of attachment were classified into two dimensions:
organizational identification and sport identification as suggested by
Trail, Robinson, et al. (2003). Organizational identification included
identification with the team, coach, university, and player whereas
sport identification included level of sport, and sport. Different from
Trail, Robinson, et al.'s original study, identification with the
community was not included because the community where the study was
conducted was considered a university town. Therefore, it was expected
that the identification with university and the identification with
community would be highly correlated. In fact, the previous studies with
students at this university showed a very high correlation between these
two constructs. Thus, the identification with community construct was
eliminated in the current study.
As indicated in Trail, Robinson, et al.'s (2003) study, it was
speculated that a fan motive of vicarious achievement leads to
organizational identification, and spectator motives lead to sport
identification. Individuals who are motivated by vicarious achievement
need a social-psychological connection to an entity which will allow
them to identify with successful others. These points of attachment
could be a team, player, coach, or a university. Studies suggest that
vicarious achievement is highly associated with team identification
(Fink et al., 2002a; Robinson & Trail, 2005; Wann, 1995), player
identification (Robinson et al., 2005), and university identification
(Wann & Robinson, 2002). Furthermore, Trail, Robinson, et al. (2003)
found a relationship ([beta] = .853) between vicarious achievement and
organizational identification. On the other hand, if spectators do not
care about the wins and losses of the team because they are not
identified with the organizational entities, their points of attachment
might be the sport itself or level of sport. Funk, Mahony, and
Ridinger's (2002) research provided some support for this notion.
In their study, motives of drama (r = .46) and aesthetics were highly
related (r = .75) to interest in soccer. Also, Trail, Robinson, et al.
found a path coefficient of .711 between spectator motives and sport
attachment.
[FIGURE 2 OMITTED]
Model B
Model B (Figure 2) also comes from Trail, Robinson, et al.'s
(2003) study. It is almost identical to Model A in the present study,
with one exception. Instead of assuming no relationship exists between
organizational identification and sport identification, we hypothesize
that there are some instances in which organizational identification
will lead to sport identification, and there are some cases in which
sport identification will lead to organizational identification (i.e., a
reciprocal relationship). For example, if an individual is highly
identified with college football, it might be impossible not to have a
favorite team or player. Similarly, one who is highly identified with a
specific team cannot just like the team without liking the sport itself.
Therefore, a reciprocal relationship may exist between organizational
identification and sport identification.
[FIGURE 3 OMITTED]
Model C
Model C (Figure 3) is quite similar to Model A, but the difference
exists in overarching motives and fan motives. Model C depicts a second
order latent variable labeled Fan Motives consisting of vicarious
achievement and social interaction. The notion is that the social
interaction motive would be stronger in highly identified fans than mere
spectators. In other words, fans may socially interact with each other
more than spectators because they consider themselves as an
"in-group" which has a clear shared goal (winning) and show
favoritism towards their in-group members (Branscombe & Wann, 1994).
For example, when their team wins, the fans who cheer for the same team
may feel a social bond because their goal was the same (i.e., their team
winning), and it was achieved. In a game between rivals, we see this
phenomenon more frequently. During and after the game, strangers may
interact more freely because they share the same feelings and have the
same sense of belonging (Anderson & Stone, 1981; Stone, 1981). After
a win, they may be engaged in BIRGing behavior together, or after a loss
they may be engaged in BLASTing behavior (blaming external sources for
the loss) together (Bernache-Assollant, Lacassagne, & Braddock,
2007; Branscombe & Wann, 1994; Snyder, Lassegard, & Ford, 1986;
Wann & Branscombe, 1990). This activity may be an important part of
their spectating experience. Although no studies have proposed this
categorization previously, indirect support exists. For example, Mahony,
Howard, and Madrigal (2000) argued that self-esteem responses have
social implications.
Model D
The only difference between Model C and Model D (Figure 4) is the
reciprocal paths between organizational identification and sport
identification. The reason for the inclusion of these paths is explained
in the section on Model B.
Method
Sample and Procedure
The participants were a convenience sample of 501 college students
who were enrolled in the Department of Health and Human Performance at a
large Midwestern university, whose football team competed in the Big 12
conference. The student population of the university was approximately
26,000, and the average attendance at the home football game at the year
the data were collected was estimated to be 56,362. A wide range of
classes from introductory classes to advanced classes were included in
the study. The survey was distributed to the students in class at the
beginning of the fall semester, before games for that collegiate
football season had started. Football, as a sport, was chosen because
the researchers anticipated that responses to questions about the
university's football team would elicit a more normal distribution
than any other sport. Among the participants, 46.7% (n = 234) were male
and 53.1% (n = 266) were female. In addition, 96% (n = 481) were single
and 3.4% (n = 17) were married. The majority of the participants were
Caucasian (92.8%, n = 462). The age of the participants ranged from 17
to 49, but 89% (n = 445) fell in between the age of 18 and 22 years.
[FIGURE 4 OMITTED]
Instruments
Two scales were used in this study: the Motivation Scale for Sport
Consumption (MSSC) and the Points of Attachment Index (PAI). The MSSC as
originally developed (Trail & James, 2001) had nine motives, but the
current study only included seven: vicarious achievement, escape, social
interaction, appreciation of physical skills of the athletes,
aesthetics, drama, and knowledge. The motive of physical attraction was
removed due to the request of the athletic department where the survey
was conducted because they did not want to acknowledge that people might
be motivated to attend games because of the attractiveness of the
athletes. The motive of family was not included because studies have
shown that family may not be a motive (Fink et al., 2002a; Robinson
& Trail, 2005) having low correlations with other motives. In
addition, it may not be applicable to college students because this
dimension focuses on the ability to spend time with family and/or
spouse. Each motive had three items, except the motive of drama (four
items), for a total of 22 items. Previous studies have shown that the
MSSC possessed good construct reliability, discriminant validity,
criterion validity, and internal consistency (Fink et al., 2002a;
Robinson & Trail, 2005; Robinson et al., 2004; Trail & James,
2001). For example, Robinson et al.'s (2004) study showed good
construct reliability (AVE .67-.79) and good internal consistency
([alpha] = .86-.92) for the seven motives, and Robinson and Trail (2005)
also showed good construct reliability (AVE .51-.76) and good internal
consistency ([alpha] .75-.90) for the seven motives. In addition, Trail
and James (2001) demonstrated that the MSSC showed good discriminant
validity (the AVE values for each construct were all greater than
squared correlation) and criterion validity (the motives were
significantly correlated with team identification, general fanship, and
attendance, which were used as criterion variables).
The Points of Attachment Index (PAI) was used to measure connection
to various aspects relating to the team and including the team (Robinson
& Trail, 2005). Six points of attachment were included in this
study: team, coach, player, university, sport, and level of sport. The
PAI consisted of 18 items including three items per point of attachment.
Kwon et al. (2005) showed that the subscales of the PAI showed good
construct reliability (AVEs = .635-.725) and internal consistency
([alpha] = .83-.87). In addition, Robinson and Trail (2005) also showed
adequate to good construct reliability (AVEs = .48-.68) and internal
consistency ([alpha] = .69-.85).
Therefore, there were a total 40 items (22 motive items and 18
points of attachment items) in addition to demographic items (gender,
age, marital status, and ethnicity). All preface statements for the MSSC
and PAI items focused on the university's football team and the
response format for MSSC and PAI items in the questionnaire was a
7-point scale ranging from 1 (Strongly Disagree) to 7 (Strongly Agree).
Data Analysis
The RAMONA Structural Equation Modeling (SEM) technique, available
in the SYSTAT 7.0 (1997) statistical package, was used to examine the
factor loadings of the items on the specified factors (a confirmatory
factor analysis, CFA). In addition, alpha coefficients were calculated
for each scale or subscale as internal consistency measures to determine
how well the items in a specific scale were correlated to each other.
According to Nunnally and Bernstein (1994), values greater than .70 are
assumed to be adequate. Average Variance Extracted (AVE) values were
used as construct reliability measures to indicate the amount each item
contributes to explaining variance in the specified construct. AVE
values greater than .50 are assumed to have good construct reliability
(Fornell & Larcker, 1981).
In order to compare the four models suggested in the study and
select the best fitting model, the RAMONA SEM technique was used. When
comparing the models, root mean square error of approximation (RMSEA),
the expected cross-validation index (ECVI), and chi-square difference
test were used. According to Browne and Cudeck (1992), RMSEA is the best
way to check for the fit of the model because chi-square value based fit
indices are influenced largely by the sample size and the number of
parameters in the model. RMSEA values less than .06 indicate a close fit
of the model to the data (Hu & Bentler, 1999). However, according to
Browne and Cudeck (1992), values less than .08 are also acceptable
indicating a reasonable fit. On the other hand, values greater than .10
should not be considered (Browne & Cudeck, 1992). A chi-square
difference test was only used when comparing between model A and B, and
between model C and D. Models A, B and Models C, D could not be compared
using chi-square difference test because they were not nested models.
In order to examine discriminant validity of the constructs,
correlations among the constructs were examined. According to Kline
(1985), constructs lack discriminant validity if they are too highly
correlated (.85 or above).
In addition, the paths were determined to have practical
significance if the variance explained was greater than 6%. According to
Cohen (1992), a minimum of 6% of variance is required to have a
practical significance.
Results
Results of the confirmatory factor analysis on the MSSC showed a
reasonable fit (RMSEA = .079; CI = .074-.085; pclose = 0.0, [chi
square]/df = 776/188 = 4.13). The alpha coefficients ranged from .81 to
.99, and the AVE values were all greater than .50, ranging from .60 to
.83 for the seven motive subscales indicating good construct reliability
(Table 1). The PAI showed an adequate fit (RMSEA = .083; CI = .076-.090;
[p.sub.close] = 0.0, [chi square]/df = 528/127 = 4.40). The alpha
coefficients ranged from .79 to .88, and the AVE values were all greater
than .50, ranging from .57 to .69 for the six points of attachment
subscales indicating good construct reliability (Table 2).
Model Comparison
The goodness-of-fit statistics indicated that Model A (RMSEA =
.072; CI = .069-.075; [p.sub.close] = 0.0, [chi square]/df = 2575/723 =
3.56, ECVI = 5.62), Model B (RMSEA = .072; CI = .069-.075; [p.sub.close]
= 0.0, [chi square]/df = 2542/721 = 3.52, ECVI = 5.56), Model C (RMSEA =
.072; CI = .069-.075; [p.sub.close] = 0.0, [chi sqaure]/df = 2584/723 =
3.57, ECVI = 5.63), and Model D (RMSEA = .072; CI = .069-.075;
[p.sub.close] = 0.0, [chi square]/df = 2566/721 = 3.56, ECVI = 5.61) all
performed equally well, showing reasonable fit. The chi-square
difference test showed that the difference between Model A and B and the
difference between Model C and D were significant. However, chi square
values are easily inflated by sample size. Due to the inflation of these
values, a more accurate way to compare the models is using RMSEA values
and their confidence intervals. Yet, there were no differences in the
RMSEA values across the four models. While the ECVI values were slightly
different among the four models (Model A = 5.62, Model B = 5.58, Model C
= 5.63, Model D = 5.61), the confidence intervals all overlapped
indicating no practical significant differences among the models.
The difference between Models A, B and Models C, D is solely due to
the location of the Social Interaction motive. In Models A and B, the
Social Interaction motive was included in Overarching Motives while it
was included in Fan Motives in Models C and D. The results indicated
that whereas the Social motive loaded slightly higher on Overarching
Motives (Model A, [beta] = .61; Model B, [beta] = .61) than on Fan
Motives (Model C, [beta] = .57; Model D, [beta] = .57), the confidence
interval values overlapped, indicating the Social motive loaded equally
well on either Overarching Motives or Fan Motives.
The correlations between the second-order construct of Overarching
Motives and Spectator Motives, and the first order construct of the
Vicarious Achievement in Model A and Model B showed that these three
constructs were highly correlated (Model A ranging from .81 to.91, Model
B ranging from .77 to .93). The correlations between the second-order
constructs of Fan Motives and Spectator Motives and the first order
construct of Escape in Model C and Model D also showed that these three
constructs were highly correlated (Model C ranging from .70-.84, Model D
ranging from .68 to .82). Correlations greater than .85 raise an issue
of discriminant validity. In Models A and B, the correlations between
Vicarious Achievement and Overarching Motives (Model A, [beta] = .91,
Model B, [beta] = .89) and the correlations between Overarching Motives
and Spectator Motives (Model A, [beta] = .93, Model B, [beta] = .93)
exceeded .85, indicating these constructs were not distinct from each
other, whereas no correlation coefficients in Models C and D exceeded
.85. Therefore, Models A and B were eliminated.
In addition, the difference between Models A/C and Models B/D is
the inclusion of the paths between Organizational Identification and
Sport Identification in Models B and D. Model D indicated that the path
from Sport Identification to Organizational Identification was not
significant ([beta] = .05) while the path from the Organizational
Identification to the Sport Identification was both statistically
([beta] = .26) and practically significant explaining approximately 6.8%
of the variance. This indicates that the addition of the path was
correct (contrary to Model C); therefore, we chose Model D for further
evaluation.
In Model D, most of the first order factors well represented their
second order factors (Table 3), ranging from [beta] = .57 to [beta] =
.95 for the motive subscales and [beta] = .52 to [beta] = .83 for the
Points of Attachment subscales. There were three exceptions:
Identification with Sport, Identification with Team, and Identification
with Players. Identification with Sport loaded perfectly ([beta] = 1.00)
on Sport Identification. Although Identification with Team did not load
perfectly on Organizational Identification, the factor loading was .99,
and the confidence interval ranged from .96 to 1.02, indicating a
possible perfect loading. The former indicates a boundary parameter
violation for this data set and the latter indicates a fallacy. On the
other hand, Identification with Player did not load highly on the second
order construct of Organizational Identification ([beta] = .26). This
indicates that Identification with Player does not share much
commonality with the other first order constructs in Organizational
Identification for this data set.
All of the relationships among the latent variables were
significant and explained a fair amount of variance except one, the path
from Sport Identification to Organizational Identification. The Escape
motive was significantly correlated with both Fan Motives ([beta] = .75)
and Spectator Motives ([beta] = .68), and Fan Motives and Spectator
Motives were also highly correlated ([beta] = .82). Fan Motives
explained 77% of the variance in Organizational Identification.
Spectator Motives explained 31% of the variance in Sport Identification.
In addition, Organizational Identification explained 7% of variance in
Sport Identification. However, Sport Identification was not
significantly related to Organizational Identification (Table 3).
Discussion
The purpose of the current study was to test different models that
explain the relationships among motives and points of attachment and
find a model that explains the greatest amount of variance in the
referent variables. In particular, the motives were divided into
different sets of categories based on whether an individual is a fan or
a spectator, and it was assumed that fan motives and spectator motives
would be related to different points of attachment. The results
indicated that in fact, the motives for fans and spectators were
different, and these different sets of motives led to different sets of
points of attachment for this group of college football fans and
spectators.
The choice of Model D showed that Social Interaction and Vicarious
Achievement were more likely to be motives for fans of teams, whereas
Skills, Aesthetics, Drama, and Knowledge were more likely to be the
motives for fans of sport, meaning spectators. In addition, Escape was a
motive that seemed to be connected to both groups. For example, both
fans and spectators may attend games to escape from daily
responsibilities. These results are in contrast to Trail, Robinson, et
al.'s (2003) findings, which provided support for the Social
Interaction motive as well as the Escape motive for being overarching
motives that apply to both fans and spectators. This might be due to the
fact that more social interaction opportunities may make themselves
available when winning is valued. Winning is an objective outcome that
may enhance sentiments of belonging. For example, fans might cheer
together when their team scores and BIRG together after the team wins.
When the team loses, the fans might engage in BLASTing together. On the
other hand, these opportunities may be somewhat limited to spectators
because the evaluations of physical skills of the athletes and
appreciating the aesthetic nature of the performance is more subjective
and oriented to the specific individual, meaning that one skill that is
appreciated by an individual is not necessarily a skill that is
appealing to others.
Regarding the relationships among motives and points of attachment,
the Fan Motives variable was correlated with the Organization
Identification variable, whereas the Spectator Motives variable was
associated with Sport Identification. This finding supports the notion
that different motives are related to different points of attachment and
is consistent with previous findings (Trail, Robinson et al., 2003;
Robinson et al., 2004; Robinson & Trail, 2005).
However, different from our expectations that Sport Identification
would lead to Organizational Identification, and Organizational
Identification would lead to Sport Identification, the path from Sport
Identification to Organizational Identification was not significant.
This result is understandable because liking a type of sport or a level
of sport does not always mean that an individual would like the
particular team salient to the survey.
In addition, different from our expectations, Identification with
Player did not load on the second order construct of Organizational
Identification as highly as the other factors. This may be due to the
fact that fans and spectators acknowledge the fact that the college
players are with the team only for a short period of time until they
graduate. As a result, the fans and spectators do not necessarily view
the players as a part of the organization. However, although player
identification did not have a high factor loading on Organizational
Identification, the magnitude (mean score) of player identification was
as high as the other points of attachment. This indicates that player
identification may be a separate point of attachment that does not
belong to either Organizational Identification or Sport Identification,
but still is an important point of attachment for fans. Therefore,
utilizing players in marketing plan should not be ignored.
In the current study, the motive of physical attractiveness was not
included because of the requirement by the athletic department. However,
it is possible that the motive of physical attractiveness would load on
both fan motives and spectator motives if it were to be included in the
model. It may load on fan motives because the physical attractiveness of
the players may influence why people become fans. Or, it may load on
spectator motives because it is possible that people just come to the
games to see attractive players without being fans of the players. More
studies are needed in this matter to expand our model.
The findings of the current study have important practical
implications for marketers. First of all, it suggests that motives that
explain why people want to be, or feel that they are, attached to the
organization (including the team, coach, players, etc.) may be somewhat
different than motives that explain why people are fans of the sport or
level of sport. This seems to indicate that there are, in fact, two
different market segments, fans of the team and fans of the sport. The
latter, who may have limited or no attachment to the marketer's
team, would be considered spectators. This is consistent with
Sloan's (1989) and Trail, Robinson, et al.'s (2003) claims.
Therefore, marketers need to identify the target markets and should
develop separate marketing strategies based on their target markets. If
their focus is to attract more fans, the plan should include features
that emphasize vicarious achievement and social interaction. On the
other hand, if they would like to increase spectator attendance, then
marketers should come up with strategies that focus more on the aspects
of aesthetics, player skills, drama, and/or knowledge acquisition. For
example, marketers can plan a social event where fans can get together
after the games and interact with each other. In order to promote drama
for spectators, marketers can schedule games with teams that have
similar winning records or are more likely to provide other conditions
conducive to a heightened level of drama.
In addition, marketers should recognize what aspect the fans and/or
spectators are attached to and incorporate the information into the
marketing plans. For example, the results showed that fans of teams are
attached to the team, player, coach, and university. Therefore, in order
to attract more fans to the games, the marketers can plan an event where
fans can take pictures with the players and the coaches after the game.
Conversely, for the spectators who are attached to the sport, marketers
can set up a booth in the stadium where they provide interesting
information about the specific sport, if there are a sufficient number
of sport fans in the audience. In order to attract both fans and
spectators, marketers can use a strategy that satisfies both groups. For
instance, a free lesson where skills are taught by the players should be
able to attract both fans who are attached to the players and spectators
who are attached to the sport. Moreover, the idea of points of
attachment can be expanded to marketing merchandise as well. For
example, rather than selling products that only have team logos, they
can expand the idea and produce products that are associated with
players, coaches, and the sport itself.
There are some limitations in this study. Although the sample size
was relatively large, whether the sample well-represents the population
is debatable because it was a convenience sample. It is possible that if
another sample is drawn using a different sampling method, the results
might be significantly different from the current study. In addition,
the sample consisted of only college students; therefore, it cannot be
generalized to other populations other than college students. Also, the
results cannot be generalized to other sports other than college
football because the items only focused on a specific college football
team. Further, the football team in the study was a Division I-A
(Football Bowl Division) team; therefore, the findings may not be
applied to other divisions. For these reasons, generalizability of the
study is limited.
The current study contributes to the body of sport management
literature, in particular spectator sport consumer motives. The findings
support the notion that fans and spectators should be studied and
marketed differently, therefore, providing evidence to researchers that
these two segments should be studied separately as well as evidence to
marketers that their marketing plans should be developed differently for
fans and spectators. For example, Kim, Greenwell, Andrew, Lee, and
Mahony (2008) found that a fan motive of vicarious achievement was
significantly related to media consumption for an individual combat
sport. In addition, Trail and James (2001) demonstrated that vicarious
achievement, aesthetics, physical attraction, physical skill, and social
interaction motives were significantly related to merchandise
purchasing, whereas vicarious achievement, aesthetics, escape, physical
skill, and social interaction motives were significantly associated with
media consumption. Further, the authors found that acquisition of
knowledge, aesthetics, and physical skill were significantly correlated
with game attendance.
In order to provide more guidelines to researchers and
practitioners, many more studies on the relationships among motives and
points of attachment are needed. Future studies should examine the
applicability of the model in different settings, such as different
national cultures, types of sport, and levels of sport. In addition,
studies should be conducted regarding gender differences to discover if
the model is applicable to both males and females. Alternatively, a new
model that considers the identification with player as a separate point
of attachment not belonging to either organizational identification or
sport identification should be tested to see if it better explains the
relationships between motives and points of attachment.
Furthermore, researchers have recently started viewing team
identification as a multi-dimensional construct (e.g., Dimmock, Grove,
& Eklund, 2005; Heere & James, 2007). Therefore, including each
dimension of team identification as separate points of attachment and
studying the model would be beneficial. As discussed earlier, testing
the model with inclusion of physical attractiveness motive is also
necessary to improve the model.
References
Anderson, D. F., & Stone, G. P. (1981). Sport: A search for
community. In S. L. Greendorfer & A. Yiannakis (Eds.), Sociology of
sport: Diverse perspectives (pp. 164-172). West Point, NY: Leisure
Press.
Andrew, D. P. S., & Todd, S. Y. (2007). Segmenting collegiate
football fans by team identification: The relationship between motives
and merchandise consumption. In J. James (Ed.), Sport marketing across
the spectrum: Selected research from emerging, developing, and
established scholars (pp. 115-126). Morgantown, WV: Fitness Information
Technology.
Bernache-Assollant, I., Lacassagne, M., & Braddock, J. H.
(2007). Basking in reflected glory and blasting differences in
identity-management strategies between two groups of highly identified
soccer fans. Journal of Language and Social Psychology, 26, 381-388.
Branscombe, N. R., & Wann, D. L. (1994). Collective self-esteem
consequences of outgroup derogation when a valued social identity is on
trial. European Journal of Social Psychology, 24, 641-657.
Browne, M. W., & Cudeck, R. (1992). Alternative ways of
assessing model fit. Sociological Methods and Research, 21, 230-258.
Cohen, J. (1992). Statistical power analysis for the behavioral sciences
(2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
Dietz-Uhler, B., Harrick, E. A., End, C., & Jacquemotte, L.
(2002). Sex differences in sport fan behavior and reasons for being a
sport fan. Journal of Sport Behavior, 23, 219-231.
Dimmock, J. A., Grove, J. R., & Eklund, R. C. (2005).
Reconceptualizing team identification: New dimensions and their
relationship to intergroup bias. Group Dynamics: Theory, Research and
Practice, 9(2), 75-86.
End, C. M., Dietz-Uhler, B., Harrick, E. A., & Jacquemotte, L.
(2002). Identifying with winners: A reexamination of sport fans tendency
to BIRG. Journal of Applied Social Psychology, 32, 1017-1030.
Fink, J. S., Trail, G. T., & Anderson, D. F. (2002a). An
examination of team identification: Which motives are most salient to
its existence? International Sports Journal, 6, 195-207.
Fink, J. S., Trail, G. T., & Anderson, D. F. (2002b).
Environment factors associated with spectator attendance and sport
consumption behavior: Gender and team differences. Sport Marketing
Quarterly, 11, 8-19.
Fisher, R. J., & Wakefield, K. (1998). Factors leading to group
identification: A field study of winners and losers. Psychology and
Marketing, 15, 23-40.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural
equation models with unobservable variables and measurement error.
Journal of Marketing Research, 18, 39-50.
Funk, D. C., Mahoney, D. F., Nakazawa, M., & Hirakawa, S.
(2001). Development of the Sport Interest Inventory (SII): Implications
for measuring unique consumer motives at team sporting events.
International Journal of Sports Marketing and Sponsorship, 3, 291-316.
Funk, D. C., Mahony, D. F., & Ridinger, L. L. (2002).
Characterizing consumer motivation as individual difference factors:
Augmenting the sport interest inventory (SII) to explain level of sport.
Sport Marketing Quarterly, 11, 33-43.
Hansen, H., & Gauthier, R. (1989). Factors affecting attendance
at professional sport events. Journal of Sport Management, 3, 15-32.
Heere, B., & James, J. D. (2007). Stepping outside the lines:
Developing a multi-dimensional team identity scale based on social
identity theory. Sport Management Review, 10, 65-91.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit
indexes in covariance structure analysis: Conventional criteria versus
new alternatives. Structural Equation Modeling, 6, 1-55.
James, J. D., & Ross, S. D. (2002). The motives of sport
consumers: A comparison of major and minor league baseball.
International Journal of Sport Management, 3, 180-198.
Kahle, L., Duncan, M., Vassilis, D., & Aiken, D. (2001). The
social value of fans for men's versus women's university
basketball. Sport Marketing Quarterly, 10, 156-162.
Kahle, L. R., Kambara, K. M., & Rose, G. M. (1996). A
functional model of fan attendance motivations for college football.
Sport Marketing Quarterly, 5, 51-60.
Kim, S., Greenwell, C., Andrew, D. P. S., Lee, J., & Mahony, D.
F. (2008). An analysis of spectator motives in an individual combat
sport: A study of mixed martial arts fans. Sport Marketing Quarterly,
17, 109-119.
Kline, R.B. (2005). Principles and practice of structural equation
modeling (2nd ed.). New York: Guilford Press.
Kwon, H. H., & Armstrong, K. L. (2004). An exploration of the
construct of psychological attachment to a sport team among college
students: A multidimensional approach. Sport Marketing Quarterly, 13,
94-103.
Kwon, H. H., & Trail, G. T. (2001). Sport fan motivation: A
comparison of American students and international students. Sport
Marketing Quarterly, 10, 147-155.
Kwon, H. H., Trail, G. T., & Anderson, D. F. (2005). Are
multiple points of attachment necessary to predict cognitive, affective,
conative, or behavioral loyalty? Sport Management Review, 8, 255-270.
Kwon, H. H., Trail, G. T., & Anderson, D. F. (2006). Points of
attachment (identification) and licensed merchandise consumption: A case
study. International Journal of Sport Management, 7, 347-360.
Mahony, D. F., Howard, D. R., & Madrigal, R. (2000). BIRGing
and CORFing behaviors by sport spectators: High self-monitors versus low
self-monitors. International Sports Journal, 4, 87-106.
McDonald, M. A., Milne, G. R., & Hong, J. (2002). Motivational
factors for evaluating sport spectator and participant markets. Sport
Marketing Quarterly, 11, 100-113.
Murrell, A. J., & Dietz, B. (1992). Fan support of sport teams:
the effect of a common group identity. Journal of Sport and Exercise
Psychology, 14, 28-39.
NCAA (2008). 2007 National college football attendance. Retrieved
October 9, 2008, from
http://www.ncaa.org/wps/wcm/connect/resources/file/
eb04d809ac57460/2007FBattendance.pdf?MOD=AJPERES
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric
theory. New York: McGraw-Hill.
Pease, D. G., & Zhang, J. J. (2001). Socio-motivational factors
affecting spectator attendance at professional basketball games.
International Journal of Sport Management, 2, 31-59.
Robinson, M. J., & Trail, G. T. (2005). Relationships among
spectator gender, motives, points of attachment, and sport preference.
Journal of Sport Management, 19, 58-80.
Robinson, M. J., Trail, G. T., & Kwon, H. (2004). Motives and
points of attachment of professional golf spectators. Sport Management
Review, 7, 167-192.
Ross, S. D. (2007). Segmenting sport fans using brand associations:
A cluster analysis. Sport Marketing Quarterly, 16, 15-24.
Snyder, C. R., Lassegard, M. A., & Ford, C. E. (1986).
Distancing after group success and failure: Basking in reflected glory
and cutting off reflected failure. Journal of Personality and Social
Psychology, 51, 382-388.
Sloan, L. R. (1989). The motives of sports fans. In J. H. Goldstein
(Ed.), Sports, games, and play: Social and psychological viewpoints (2nd
ed., pp. 175-240). Hillsdale, NJ: Lawrence Erlbaum Associates.
Stone, G. P. (1981) Sport as a community representation. In G. R.
F. Luschen & G.H. Sage (Eds.), Handbook of social science of sport,
(pp. 214-245). Champaign, IL: Stipes Pub.
Swanson, S., Gwinner, K., Larson, B., & Janda, S. (2003).
Motivations of college student game attendance and word-of-mouth
behavior: The impact of gender differences. Sport Marketing Quarterly,
12, 151-162.
Trail, G. T., Anderson, D. F., & Fink, J. (2000). A theoretical
model of sport spectator consumption behavior. International Journal of
Sport Management, 1, 154-180.
Trail, G. T., Anderson, D. F., & Fink, J. (2002). A theoretical
model of sport spectator consumption behavior. International Journal of
Sport Management, 1, 154-180.
Trail, G. T., Fink, J., & Anderson, D. F. (2003). Sport
spectator consumption behavior. Sport Marketing Quarterly, 12, 8-17.
Trail, G. T., & James, J. D. (2001). The motivation scale for
sport consumption: Assessment of the scale's psychometric
properties. Journal of Sport Behavior, 24, 108-125.
Trail, G. T., Robinson, M. J., Dick, R. J., & Gillentine, A. J.
(2003). Motives and points of attachment: Fans versus spectators in
intercollegiate athletics. Sport Marketing Quarterly, 12, 217-227.
U.S. Census Bureau. The 2008 statistical abstract: 2008 edition.
Retrieved February 10, 2008, from
http://www.census.gov/compendia/statab/2008edition.html
Wann, D. L. (1995). Preliminary validation of the sport fan
motivation scale. Journal of Sport and Social Issues, 19, 377-396.
Wann, D. L. (1996). Seasonal changes in spectators'
identification and involvement with and evaluations of college
basketball and football teams. Psychological Record, 46, 201-215.
Wann, D. L., & Branscombe, N. R. (1990). Die-hard and
fair-weather fans: Effects of identification on BIRGing and CORFing
tendencies. Journal of Sport and Social Issues, 14, 103-117.
Wann, D. L., Dolan, T. J., McGeorge, K. K., & Allison, J. A.
(1994). Relationship between spectator identification and
spectators' perceptions of influence, spectators' emotions,
and competition outcome. Journal of Sport and Exercise Psychology, 16,
347-364.
Wann, D. L., & Robinson III, T.N. (2002). The relationship
between sport team identification and integration into and perceptions
of a university. International Sports Journal, 6, 36-44.
Wann, D. L., Royalty, J. L., & Rochelle, A. R. (2002). Using
motivation and team identification to predict sport fans' emotional
responses to team performance. Journal of Sport Behavior, 25, 207-216.
Won, J., & Kitamura, K. (2007). Comparative analysis of sport
consumer motivations between South Korea and Japan. Sport Marketing
Quarterly, 16, 93-105.
Zhang, J. J., Pease, D. G., Lam, E. T. C., Bellerive, L. M., Pham,
U. L., Williamson, D. P., et al. (2001). Sociomotivational factors
affecting spectator attendance at minor league hockey games. Sport
Marketing Quarterly, 10, 43-54.
Boyun Woo, Galen T. Trail, Hyungil Harry Kwon, and Dean Anderson
Boyun Woo is a PhD candidate in sport management at Ohio State
University. Research interests include organizational behavior and
consumer behavior.
Galen, T. Trail, PhD, is an associate professor and the coordinator
of the Master's of Sport Administration and Leadership program at
Seattle University. His research focuses on sport consumer behavior.
Hyungil Harry Kwon, PhD, is an assistant professor in the
Department of Physical Education at Chung-Ang University, Korea. His
research interests include sport team licensed merchandise sales and
sport consumers' psychological constructs such as team
identification and sport fan commitment.
Dean Anderson, PhD, is a professor in the Department of Kinesiology
at Iowa State University. His research focuses on sociology of sport.
Table 1.
Factor Loadings (b), Confidence Intervals (CI), Standard Errors (SE),
t-values, and Average Variance Explained (AVE) Values for the
Motivation Scale for Sport Consumption
Factor and Item [beta] CI SE t
Vicarious Achievement
I feel a personal sense of .82 .79-.85 .019 44.29
achievement when the team
does well.
I feel like I have won when the .84 .81-.87 .017 48.70
team wins.
I feel proud when the team .83 .80-.81 .018 46.31
plays well.
Aesthetics
I appreciate the beauty .88 .86-.90 .013 69.29
inherent in the sport.
I enjoy the natural beauty in .89 .88-.91 .012 74.96
the sport.
I enjoy the gracefulness .86 .84-.89 .014 62.24
associated with the sport.
Drama
I enjoy the drama of close .84 .84-.89 .014 60.00
games.
I prefer watching a close .70 .70-.78 .023 32.19
game rather than a
one-sided game.
I enjoy it when the outcome of .83 .80-.86 .017 49.29
the game is not decided until
the very end.
I enjoy the uncertainty of .85 .83-.88 .015 55.08
close football games.
Escape
The game provides an escape .87 .84-.90 .019 46.78
from my day-to-day routine.
The game provides a distraction .64 .59-.69 .030 20.86
from my everyday activities.
The game provides a diversion .80 .76-.84 .022 36.74
from "life's little problems"
for me.
Knowledge
I can increase my knowledge .85 .83-.87 .016 53.24
about the sport.
I can increase my understanding .91 .89-.93 .013 72.28
of the sport's strategy by
watching the game.
I can learn about the technical .85 .82-.88 .016 54.19
aspects of the sport by
watching the game.
Physical Skills
The athletic skills of the .83 .81-.86 .017 49.41
players are something I
appreciate.
I enjoy watching a well- .81 .78-.84 .018 44.86
executed athletic
performance.
I enjoy a skillful performance .81 .78-.84 .018 44.90
by the team.
Social
I enjoy interacting with other .89 .87-.91 .011 79.91
people when I go to a game.
I enjoy talking with other .94 .94-.99 .008 114.80
people when I go to a game.
I enjoy socializing with other .9 .88-.92 .011 84.51
people when I go to a game.
Factor and Item [alpha] AVE
Vicarious Achievement .81 .70
I feel a personal sense of
achievement when the team
does well.
I feel like I have won when the
team wins.
I feel proud when the team
plays well.
Aesthetics .99 .77
I appreciate the beauty
inherent in the sport.
I enjoy the natural beauty in
the sport.
I enjoy the gracefulness
associated with the sport.
Drama .89 .68
I enjoy the drama of close
games.
I prefer watching a close
game rather than a
one-sided game.
I enjoy it when the outcome of
the game is not decided until
the very end.
I enjoy the uncertainty of
close football games.
Escape .81 .68
The game provides an escape
from my day-to-day routine.
The game provides a distraction
from my everyday activities.
The game provides a diversion
from "life's little problems"
for me.
Knowledge .90 .76
I can increase my knowledge
about the sport.
I can increase my understanding
of the sport's strategy by
watching the game.
I can learn about the technical
aspects of the sport by
watching the game.
Physical Skills .86 .67
The athletic skills of the
players are something I
appreciate.
I enjoy watching a well-
executed athletic
performance.
I enjoy a skillful performance
by the team.
Social .94 .83
I enjoy interacting with other
people when I go to a game.
I enjoy talking with other
people when I go to a game.
I enjoy socializing with other
people when I go to a game.
Table 2.
Factor Loadings (b), Confidence Intervals (CI), Standard Errors (SE),
t-values, and Average Variance Explained (AVE) Values for the Points of
Attachment Index (PAI)
Factor and Item [beta] CI SE
Identification with the players
I identify more with an individual .68 .64-.73 .029
player(s) on the team than with
the team.
I am a big fan of specific player(s) .86 .83-.90 .022
more than I am a fan of the team.
I consider myself a fan of certain .83 .79-.87 .023
players rather than a fan of the
team.
Identification with the team
I consider myself to be a "real" .85 .82-.88 .017
fan of the team.
I would experience a loss if I had .8 .76-.83 .020
to stop being a fan of the team.
Being a fan of the team is very .88 .85-.90 .015
important to me.
Identification with the coach
I am a big fan of Coach X. .65 .61-.70 .028
I follow the football team because .90 .87-.92 .016
I like Coach X.
I am a fan of the football team .92 .89-.94 .015
because they are coached by X.
Identification with the university
I identify with numerous aspects .76 .72-.81 .026
of the university rather than just
its team.
I feel a part of the university .83 .79-.86 .024
community not just its teams.
I support the university as a .74 .70-.79 .027
whole not just its athletic teams.
Identification with sport
First and foremost I consider .79 .75-.82 .022
myself a football fan.
Football is my favorite sport. .70 .66-.74 .027
I am a football fan of all levels .81 .77-.84 .021
(e.g., high school, college,
professional).
Identification with level of sport
I am a fan of collegiate football .82 .78-.85 .022
regardless of who is playing.
I don't identify with one specific .59 .54-.65 .033
college football team, but
collegiate football in general.
I consider myself a fan of .83 .80-.87 .021
collegiate football, and not just
one specific team.
Factor and Item t [alpha] AVE
Identification with the players .83 .63
I identify more with an individual 23.80
player(s) on the team than with
the team.
I am a big fan of specific player(s) 39.95
more than I am a fan of the team.
I consider myself a fan of certain 35.92
players rather than a fan of the
team.
Identification with the team .88 .69
I consider myself to be a "real" 51.02
fan of the team.
I would experience a loss if I had 40.29
to stop being a fan of the team.
Being a fan of the team is very 58.6
important to me.
Identification with the coach .85 .69
I am a big fan of Coach X. 23.3
I follow the football team because 57.08
I like Coach X.
I am a fan of the football team 60.71
because they are coached by X.
Identification with the university .82 .60
I identify with numerous aspects 29.18
of the university rather than just
its team.
I feel a part of the university 34.59
community not just its teams.
I support the university as a 27.53
whole not just its athletic teams.
Identification with sport .81 .59
First and foremost I consider 36.18
myself a football fan.
Football is my favorite sport. 26.07
I am a football fan of all levels 39.21
(e.g., high school, college,
professional).
Identification with level of sport .77 .57
I am a fan of collegiate football 37.60
regardless of who is playing.
I don't identify with one specific 17.72
college football team, but
collegiate football in general.
I consider myself a fan of 39.60
collegiate football, and not just
one specific team.
Table 3.
Maximum Likelihood Point Estimates (b), Confidence Intervals (CI),
Standard Errors (SE), t-values (t) for Sport
Spectator Consumption Behavior Model D.
1st Order Factors on [beta] CI SE t
2nd Order Factors
Vicarious Achievement <- .95 .92-.98 .017 57.44
Fan Motives
Social <-Fan Motives .57 .51-.63 .035 16.46
Skill <-Spectator Motives .92 .89-.94 .016 56.65
Aesthetics <-Spectator Motives .9 .88-.93 .015 59.57
Drama <-Spectator Motives .75 .71-.79 .025 29.52
Knowledge <-Spectator Motives .66 .61-.71 .031 21.40
ID Team <-Organizational .99 .96-.1.02 .020 49.05
Identification
ID Player <-Organizational .26 .18-.33 .048 5.29
Identification
ID University <-Organizational .53 .47-.60 .04 13.31
Identification
ID Coach <-Organizational .52 .46-.58 .038 13.76
Identification
ID Sport <-Sport 1.00 1.00-1.00 -- --
Identification
ID Level of Sport <-Sport .83 .08-.87 .024 34.76
Identification
Fan Motives <-> Escape .75 .70-.79 .028 26.61
Fan Motives <-> Spectator .82 .77-.85 .023 34.92
Motives
Escape <-> Spectator Motives .68 .63-.73 .032 21.62
Organizational Identification .88 .79-.97 .055 15.88
<- Fan Motives
Sport Identification <- .56 .43-.69 .079 7.08
Spectator Motives
Organizational Identification .05 -.24 .072 .72
<- Sport Identification
Sport Identification <- .26 .11-.41 .089 2.90
Organizational Identification
