Points of attachment and sponsorship outcomes in an individual sport.
Reams, Lamar ; Eddy, Terry ; Cork, B. Colin 等
Introduction
According to IEG, North American sport sponsorship spending is
anticipated to escalate to $15 billion in 2015 (IEG, 2015). Because of
the capitalistic significance to sport properties and corporate
sponsors, managers expect favorable returns on these investments
(Abratt, Clayton, & Pitt, 1987; Crompton, 2004; Meenaghan, 1991;
Stotlar, 2004). Driven by conceptual inquiries and managerial
expectations, many industry practitioners and academic researchers have
embarked on the arduous task of measuring the effectiveness of sport
sponsorships (Bennett, Henson, & Zhang, 2002; Maestas, 2009). As a
result, sponsorship effectiveness has been examined extensively within
the sport marketing literature. Common measures of sponsorship
effectiveness include: brand awareness (Gwinner, 1997; Gwinner &
Bennett, 2008), enhancement of brand image (Dees, Bennett, &
Ferreira, 2010; Gwinner & Eaton, 1999), sponsor recognition,
attitudes toward the sponsor, sponsor patronage, and satisfaction with
the sponsor (Alexandris & Tsiotsou, 2012; Gwinner & Swanson,
2003; Tsiotsou & Alexandris, 2009). An important characteristic of
the existing literature to note is that the majority of studies have
been devoted to team sports (Alexandris & Tsiotsou, 2012; Biscaia,
Correia, & Rosado, 2013; Madrigal, 2001; Meenaghan, 2001; Tsiotsou
& Alexandris, 2009; Zhang, Won, & Pastore, 2005), with less
coverage provided to individual sports where athletes exist
independently (without associations to "team" brands) and
serve as recognizable points of attachment for consumers (Robinson &
Trail, 2005).
Headquartered in Las Vegas with offices across the globe (e.g.,
South America, China, United Kingdom), and a current lineup of
approximately 500 fighters, the professional mixed martial arts (MMA)
league Ultimate Fighting Championship (UFC) is at the forefront of
combat sports (Tainsky, Salaga, & Santos, 2012). Representative of
the sport's rise, in 2011, Fox Sports paid the UFC an estimated
$100 million to broadcast its events (Fowlkes, 2014), not including the
annual lineup of marquee pay-per-view (PPV) events that contribute to
the league's $500 million in annual revenues (Miller, 2012).
Corporate sponsors have taken note as well, with Bud Light, Harley
Davidson, Dodge Motor Vehicles, Electronics Arts (EA) Sports, Metro PCS,
and a plethora of combat sport industry sponsors signed to league and
individual fighter sponsorship agreements (Cruz, 2012), varying in
length from a single fight to multiple years. A quick glance at a UFC
combatant shows the extent of the sport's reach, as branding covers
his/her in-fight shorts and pre- and post-fight gear (Marrocco, 2013).
Although there has been some investigation of individual
athlete/sport sponsorships in past research (Cianfrone & Zhang,
2006; Cornwell, Roy, & Steinard, 2001; Dees et al., 2010; Martin,
1996), the existing inquiries are mostly unable to capture the
theoretical and practical setting of the current study, as structural
differences can cause different individual sports to appeal to different
groups of spectators and/or participants based on their demographic and
psychological characteristics (i.e., the solitary nature of golf versus
the direct competition in tennis) (Nicholls, Roslow, & Dublish,
1999). Further, from a theoretical standpoint attachment has either been
examined as a unidimensional construct (Filo, Funk, & O'Brien,
2010), or as an emotional link between athlete/league and fan, typically
operationalized as team identification (Dees et al., 2010). What has
resulted is a partial theoretical and pragmatic gap pertaining to
attachment as a multidimensional concept, and the effectiveness of
individual and league sponsorships within an individual sport structure.
Literature Review
Sport Sponsorship
Sport sponsorship is receiving an increasing amount of attention in
the academic literature. A variety of cognitive, affective, and
behavioral outcomes have been examined under the banner term of
sponsorship effectiveness, including brand awareness, brand
recall/recognition, brand image, and purchase intentions (Meenaghan
& O'Sullivan, 2013; Walraven, Koning, & van Bottenburg,
2012). Important antecedents to these desirable sponsorship outcomes
include fit between the sponsor and sport property (Simmons &
Becker-Olsen, 2006), attitudes toward sponsorship (Alexandris &
Tsiotsou, 2012; Zhang, Won, & Pastore, 2005) and exposure to the
sponsorship through involvement (Ko, Kim, Claussen, & Kim, 2008).
Relative to team sport sponsorship, team attachment and team
identification have generally been found to have significant, positive
relationships with a variety of sponsorship outcomes, such as sponsor
purchase intentions and brand loyalty (Alexandris & Tsiotsou, 2012;
Meenaghan, 2001; Tsiotsou & Alexandris, 2009).
It should be noted here that while there is generally agreement in
the literature as to the pairwise relationships found between the most
salient constructs, the models used to examine these constructs are
diverse. For example, attitude toward sponsors has been used both as an
outcome (Dees et al, 2010) and a mediator with behavioral intentions
(Alexandris & Tsiotsou, 2010). Similarly, the direct effects of
involvement have been examined on both awareness and conative processing
(Walraven et al., 2012), but other studies suggest involvement is an
antecedent to team attachment with no direct effects on attitudinal and
conative processing (Alexandris & Tsiotsou, 2012). When we also
consider the vast number of contexts used to examine sponsorship
agreements (i.e., hypothetical versus actual sponsorships, individual
versus team sports), it becomes apparent that although the academic work
in sponsorship is becoming robust, there is still a need for researchers
to continue to broaden the contextual and theoretical bases in studies
of sponsorship.
Sponsorship in individual sports. Sponsorship of individual sports
has also received some, albeit less, attention in the literature. Much
of the recent work that is most theoretically relevant to the current
study has been focused on participants in marathons and other running
races (Eagleman & Krohn, 2012; Filo et al., 2010; Fransen, van
Rompay, & Muntinga, 2013). In particular, Filo et al. (2010) is one
of the few examples in the literature where event attachment and
motivations, relative to sponsor-related outcomes, were examined as
multidimensional constructs. In that study, the authors examined a
number of motives related to charity and recreation for half-marathon
participants, finding that charity motives and attachment to the event
played a significant role in sponsor image creation for those
participants, which then guided product purchase intentions (Filo et
al., 2010). Other studies on running participants have focused primarily
on sponsor purchase intentions in the context of activity/event
identification, with particular emphasis on both attitudes toward
sponsorship (Eagleman & Krohn, 2012) and recall/recognition (Fransen
et al., 2013; Lough, Pharr, & Owen, 2014). In general, these studies
have found that highly identified participants will be able to recognize
and recall more sponsors of the event, hold more positive attitudes
toward those sponsors, and suggest a greater willingness to purchase
sponsors' products.
When shifting the focus to individual sports with greater spectator
involvement, much of the work involving sponsorship has come in the
contexts of golf, tennis, action sports, and NASCAR (Gwinner &
Bennett, 2008; Herrmann, Corneille, Derbaix, Kacha, & Walliser,
2014; Jensen, 2012; Levin, Cobbs, Beasely, & Manolis, 2013).
Within the UFC space, two notable studies have been conducted on
UFC-specific sponsorship (Devlin, Brown, Billings, & Bishop, 2013;
Reese & Bennett, 2011). Devin et al. (2013) examined identification
with regard to brand congruence and sponsor purchase intentions,
predictably finding that more highly identified fans had higher
recognition of brand congruence and indicated stronger intent to
purchase sponsors' products. Similarly, Reese and Bennett (2011)
found highly identified UFC viewers more likely to purchase sponsor
products if they perceived greater event/sponsor congruency and
displayed an ability to recognize event sponsors. The authors also
determined that UFC viewers were more likely recognize a victorious
fighter's apparel sponsor more frequently than a losing
fighter's.
More broadly, most of the findings regarding identification within
specific individual sports are consistent with what is mentioned above
(Gwinner & Bennett, 2008; Levin et al., 2013), and similar results
have been found when exposure has been used as an antecedent (Herrmann
et al., 2014; Jensen, 2012). Where differences begin to arise is between
individual sports. For example, Nicholls et al. (1999) found differences
between the sponsorship recall of golf and tennis fans (tennis fans
displayed greater recall and preferences in 67% of the cases), while the
fans that appear to be most positively affected by sponsorship (in
general) are those of NASCAR (Clark, Cornwell, & Pruitt, 2009; Dees
et al., 2010; Levin et al., 2013). This variation in findings lends
support to the continued examination of sponsorship in many different
individual sport settings.
While the body of work in this area includes studies that examine
both single- and multiple-sport contexts, generally only one type of
sponsor has been examined (i.e., league, team, or individual). For
example, Gwinner and Bennett (2008) found that stronger perceived
event-sponsor fit led to greater consumer purchase intentions, but the
relationship was mediated by attitude toward the sponsor. What was not
examined in that study, however, was the impact that the individual
athletes may have on sponsorship outcomes. Dees et al. (2010), on the
other hand, examined NASCAR drivers in terms of brand personality and
personality fit with their individual sponsoring brands, and found these
constructs had a positive relationship with attitudes toward the
sponsorship and consumer purchase intentions, but did not include other
sponsors of NASCAR more generally. As such, there is a gap in this
literature in that both athlete and league sponsors have not been
examined together in the same study.
Theoretical Framework
Attachment Theory. Attachment theory posits that individuals
develop favorable mental associations of significant others, and of
their relationships with others (Bowlby, 1979; Mikulincer & Shaver,
2007). Research since Bowlby's seminal work suggests that
meaningful attachments can be extended to personal relationships with
places, personal possessions, and brands (Vlachos, Theotokis, Pramatari,
& Vrechopoulos, 2010). Brand attachment, an extension of attachment
theory in marketing, asserts that consumers develop similar connections
to brands (Kwon & Armstrong, 2004; Thomson, Maclnnis, & Park,
2005). In the general marketplace, consumers have displayed brand
attachments to celebrities, gifts, pets, sport teams, and other special
items (Adams-Price & Greene, 1990; Ball & Tasaki, 1992; Funk
& James, 2006; Hirschman, 1994; Mick & DeMoss, 1990). In a
similar fashion, sport consumers develop favorable attachments to
various aspects of the sport consumptive experience (Kwon et al., 2005).
Points of attachment. Team identification, at times used
interchangeably with team attachment (cf., Cialdini et al., 1976; Sloan,
1989; Wann & Branscombe, 1993), is a unidimensional measure of a
sport fan's bond with a team (Kwon et al., 2005). The point of
attachment index (PAI; Robinson & Trail, 2005) is an expanded,
multidimensional measure of attachment to the team coach, team, the
community in which the team competes, the level of play (e.g.,
professional as opposed to amateur), an individual player, or a specific
sport (Robinson & Trail, 2005; Trail, Fink, & Anderson, 2000).
Points of attachment can differ depending upon the context of the
analysis (e.g., player, league, fantasy sports, etc.) (Dwyer, 2013; Karg
& McDonald, 2011; Shapiro, Drayer, & Dwyer, 2011), and have been
found to have an influence on a sport fan's consumptive behavior
(Kwon et al., 2005; Kwon, Trail, & Anderson, 2006).
Consistent with previous research (cf., Robinson & Trail, 2005;
Trail et al., 2000), we propose that consumers could be attached to
various aspects of the UFC consumption experience; specifically, the UFC
organization as a league, individual fighters who compete in the UFC,
the sport of MMA, and professional level MMA competition. Further
support for these points of attachment were derived from previous works
in this area that found women more identified with specific fighters
than men, men more attached to the sport of MMA than women (Brown,
Devlin, & Billings, 2013), interest in the organization as a
potential motive for MMA consumption (Kim, Andrew, & Greenwell,
2009), and differences in motivation to consume by level of competition
(i.e., professional as opposed to amateur) (Andrew, Kim, O'Neal,
& James, 2009).
Consequently, in this study we assessed these four points of
attachment in terms of salience and prediction of two relevant sponsor
outcomes (i.e., attitudes and purchase intentions) from the perspective
of both the UFC as a league, as well as the individual competitors.
Noting the literature and theoretical framework, this study utilized a
correlational research design to address the following research
questions:
RQ1: Which points of attachment will predict consumers'
attitudes toward UFC sponsors?
RQ2: Which points of attachment will predict consumers'
attitudes toward fighter sponsors?
RQ3: Which points of attachment will predict consumers'
purchase intentions for UFC sponsor products?
RQ4: Which points of attachment will predict consumers'
purchase intentions for fighter sponsor products?
Specifically, attachment to the UFC, individual fighters, the sport
of MMA, and professional level MMA competition were regressed on
attitudes and purchase intentions of UFC and favorite fighter sponsors.
Since consumer points of attachment and sponsor outcomes have received
little attention within the UFC space, and points of attachment have not
been examined as predictors of sponsor outcomes in any context,
theoretical and pragmatic implications will result. The following
section contains a description of the data collection and analyses
performed in the study.
Methods
Sample
A purposive, non-probability online sample of adult UFC consumers
(aged 18 and over) derived from several popular MMA news websites (i.e.,
sherdog.com, mixedmartialarts.com) was obtained. The survey was hosted
by Qualtrics, and posted with the permission of the message board
administrators for two weeks in September 2014. Message board
administrators labeled the "UFC study" thread as a sticky to
encourage member participation. A total of 216 surveys were collected;
39 were incomplete, yielding 177 surveys that were considered usable for
analysis.
The respondents were almost exclusively male (90.9%), mostly
between the ages of 18 and 35 (73.6%), and primarily Caucasian/white
(74.6%). Others identified themselves as Hispanic (6.8%), Asian/Pacific
Islander (3.4%), black/African American (1.1%), multiracial (4.5%), and
other (4.5%). Five percent of the participants did not respond to the
question. Fifty percent of the participants were single, and 46.3% had
earned a bachelor's degree or higher. In terms of household income,
33.3% earned less than $50,000 per year, while 16.9% earned more than
$100,000 per year. Forty-four percent of the participants had attended
at least one UFC fight live in their lifetime, 60.5% had purchased UFC
merchandise in the last 12 months, and the respondents spent 14.87 hours
(SD = 24.05) following UFC online per week, on average. All respondents
self-identified as fans of the UFC (M = 11.02 years, SD = 5.78).
Instrument
After agreeing to participate and indicating they were 18 years of
age or older, respondents were asked to identify their favorite UFC
fighter. Each respondent's selection was then piped into the items
of the instrument that pertained to the selected fighter. The remaining
survey instrument was comprised of 36 items. An adapted PAI (Robinson
& Trail, 2005), consisting of 12 items, was included on the
instrument. Previous works support using a reduced PAI (Kwon, Trail
& Anderson, 2005) and have found the index to display good internal
consistency and validity (Robinson, Trail, & Kwon, 2004). The
adapted scales of the PAI were sport attachment, university attachment,
player attachment, and level of attachment. The subscales were slightly
modified to reflect MMA attachment (MMAPAI), UFC attachment (UFCPAI),
fighter attachment (FFPAI), and professional MMA attachment (PROPAI)
(see Table 1).
For the remainder of the instrument, 12 items were devoted to the
attitudes toward fighter sponsors (FFATT) and attitudes toward UFC
sponsors (UFCATT; Dees et al., 2010), as well as fighter sponsor
behavioral intentions (FFSPI) and league sponsor behavioral intentions
measures (UFCSPI; Alexandris & Tsiotsou, 2012). All factors on the
instrument were measured on a 7-point Likert-type scale, and
Cronbach's alpha values (see Table 1) were above the generally
accepted lower bound of 0.7 (Tabachnick & Fidell, 2007), except for
MMAPAI ([alpha] = .631) (Nunnally & Bernstein, 1994). The remaining
12 items consisted of six demographic items (i.e., gender, age,
race/ethnicity, marital status, education, and annual household income),
four UFC consumption items (i.e., length of fandom, number of attended
fights, merchandise purchased, and hours spent online following UFC),
and two optional items (i.e., name for gift card raffle and email
address for future research).
Results
Based on the mean scores for each of the PAI constructs (see Table
1), the participants indicated being more attached to MMA in general (M
= 5.52, SD = 1.33) and professional-level MMA (M = 5.69, SD = 1.34) than
they were attached specifically to the UFC (M = 4.74, SD, 1.37) or their
favorite fighters (M = 4.18, SD = 1.73). In terms of the sponsor
outcomes, based on a neutral score of 4, the respondents held generally
positive attitudes toward both UFC (M = 4.77, SD = 1.48) and
fighter-specific (M = 5.26, SD = 1.35) sponsors. On the other hand,
purchase intentions for both UFC (M = 2.73, SD = 1.13) and fighter (M =
3.08, SD = 1.19) sponsors were somewhat negative based on the same
neutral score of 4. Pairwise relationships between the PAI variables
were examined using Pearson correlation coefficients (see Table 2).
In order to answer the four research questions, four multiple
linear regression models were tested using UFCATT, FFATT, UFCSPI, and
FFSPI as the dependent variables, and the four PAI factors were the
independent variables in each model. Prior to examining the regression
equations, assumptions of normality, independence of observations,
linearity, and homoscedasticity were assessed via normal probability
plots, scree plots, etc., with no gross violations observed (Osborne
& Waters, 2002). When checking for multicollinearity, all variance
inflation factors (VIF) were well below the common threshold value of 5,
but MMAPAI was somewhat strongly correlated with PROPAI (r = .644) and
UFCPAI (r = .417). When MMAPAI was included in the initial regression
models it was not significant, but the significance and direction of
other independent variables were in some conflict with the correlation
table. This problem was fixed when MMAPAI was removed, so it appeared
that MMAPAI was the cause of some moderate multicollinearity.
Given that the Cronbach's alpha value for MMAPAI was also
slightly below .7, MMAPAI was dropped from the models presented here.
Finally, since four regression analyses were being performed on the same
set of independent variables, a Bonferroni adjusted significance level
of .05/4 = .0125 was used (Huck, 2008).
All four models were significant overall, with [R.sup.2] values
ranging from .164 to .306 (beta coefficients, p-values, F statistics,
and [R.sup.2] values for each research question can be found in Tables
3-6). In the UFC sponsor-focused models, UFCPAI and PROPAI were both
significant predictors of UFCATT, but only UFC PAI was a significant
predictor of UFCSPI. FFPAI was not significant in either UFC
sponsor-focused model. For the fighter sponsor-focused models, UFCPAI
was once again a significant predictor in both cases, but this time
FFPAI was a significant predictor of both FFATT and FFSPI. PROPAI was
not significant in either fighter sponsor-focused model.
Discussion
Based upon attachment theory and previous research, the study was
approached by examining specific points of attachment (Kwon et al.,
2005; Robinson & Trail, 2005) and sponsorship effectiveness outcomes
in a league-structured, individual sport. These findings have
implications for both sport marketing practice and future research,
specifically whether consumers' salient points of attachment to a
sport product have an impact on sponsorship outcomes--an issue that has
received no direct investigation in the literature. Results of the study
display differences in sponsorship outcomes depending on which points of
attachment are most salient among fans. In addition, based on the
discrepancy between outcomes for UFC sponsors and fighter sponsors, it
would appear as if this work has provided an impetus for further
exploration of this topic.
In terms of the research questions, fan attachment the UFC was a
significant predictor of the four sponsorship effectiveness measures
that were examined (i.e., UFCATT, UFCSPI, FFATT, and FFSPI).
Pragmatically for the UFC, individual fighters, and corporate sponsors,
the league brand should be leveraged in contractual agreements and
marketing activities should target those fans who identify as strong
supporters of the league. In order to provide more value to league
sponsors (and consequently increase sponsorship revenue), the UFC should
also consider marketing initiatives that would strengthen fan attachment
with the league itself, given that the participants in this study were
quite heavily involved with following the UFC online (approximately 15
hours per week), but were only somewhat positively attached to the UFC
brand (M = 4.74, SD = 1.37). This practical application might also hold
true in stock car racing (i.e., NASCAR) considering their fan base
displays high levels of sponsor brand loyalty and identification with
specific drivers (Levin, Beasley, & Gamble, 2004).
Not surprisingly, fan attachment to a favorite fighter had a
significant, positive relationship with both attitudes towards the
fighter sponsor and fighter sponsor purchase intentions. However,
fighter attachment displayed no relationship with the more general UFC
sponsorship effectiveness outcomes, which perhaps indicates that fans
who are highly attached to a particular fighter see that athlete as
their own independent brand, rather than simply an athlete from the UFC.
In addition, although the model fit for fighter sponsor outcomes (see
Tables 5 and 6) was substantially weaker than the model fit for UFC
sponsor outcomes (see Table 3 and 4), the overall mean scores for FFATT
and FFSPI were more positive than those for the corresponding UFC
sponsor variables. The weaker prediction could be a function of the
larger variation in specific sponsors (and types of sponsors) between
fighters, since the UFC sponsors (Burger King, etc.) are a relatively
small group in comparison. Further, the importance of event/sponsor
congruence should not be overlooked, as previous research has found that
more highly identified UFC fans will display greater intentions to
purchase a sponsor's products if the fit between event and sponsor
is perceived as congruent (Devin et al., 2013; Reese & Bennett,
2011). It is also possible that many UFC fans do not participate in
martial arts, so they may not perceive a need to purchase the combat
sport-related products that are frequently displayed on individual
fighters' gear. Subsequent research should also explore why MMA
fans appear to have favorable attitudes towards sponsors yet express
weaker intentions to purchase their products (despite strong
correlations between the two), and whether or not participation in
martial arts is a moderating factor.
It should be noted that the [R.sup.2] values in this study are
comparable with other studies in this area. For example, the [R.sup.2]
values reported by Dees et al. (2010) in their study of NASCAR
sponsorship were between .30 and .41 for models that examined fan
identification, as well as product involvement, brand attitudes, and
personality traits of drivers. Given that NASCAR fans are considered to
be extremely brand loyal (Dees et al., 2010; Levin et al., 2004), and
other significant antecedents to sponsor outcomes were not part of this
study (i.e., sponsor image, brand attitudes, sponsor fit; Walraven et
al., 2012), the prediction of the models in this study, particularly
those involving attitudes toward sponsors, could be considered somewhat
strong.
The findings in this study are also particularly timely, as Reebok
was announced as the official uniform provider for the UFC (commencing
in the latter half of 2015), ultimately ending the presence of
individual fighter sponsors inside the cage or during other UFC-hosted
events (Al-Shatti, 2014). Under the new sponsorship revenue sharing
agreement, all fighters will be paid based on a tiered system according
to their tenure with the league (i.e., 1-5 fights, champions, etc.),
with marquee fighters receiving dedicated product lines. Many fighters
are particularly concerned, as new and existing fighters alike displayed
branding on their shorts under the previous model that paid them more
than the latest program will ($2,500-$40,000) (Simon, 2015). Some lesser
known fighters are particularly concerned, as many of them displayed
branding on their shorts under the previous model to supplement their
salaries. Equally alarmed are MMA sponsors, as they will essentially
lose their presence inside the octagon (Kidd, 2013). However, it appears
as though Reebok may be able to capitalize on the exclusivity inherent
in its agreement through both the positive relationship between UFCPAI
and all sponsor outcomes examined in this study (since it will
technically be a league sponsor), as well as the fact that FFATT and
FFSPI had higher mean scores than for UFC sponsors (since its brand will
become linked with all fighters participating in the UFC). Although the
data for this study were collected before the Reebok agreement was
signed, meaning direct comparisons could not be drawn, it appears that
the findings still provide indirect support for this decision.
Moving forward, in addition to the suggestion above that
strengthening fan attachment to the league is important, it might also
behoove the UFC to strengthen links with individual fighters as brand
associations of the UFC itself. Since FFPAI was not a significant
predictor of UFCATT or UFCPAI, it does not appear that UFC sponsors are
receiving significant benefits from consumer attachment to the fighters
themselves under the current sponsorship tax model. The Reebok deal may
actually help facilitate these improved brand associations, since the
fighters may potentially be seen as a tighter knit group of UFC athletes
wearing a standardized uniform, as opposed to a group of independent
brands. As such, further adjustments to the sponsorship model, mirroring
the approach of Reebok, that expand the use of fighters in leveraging
UFC sponsorships (which was uncommon in the current model) might be
beneficial for both the UFC and its other sponsors.
In contrast to what was found with UFCPAI and FFPAI, PROPAI was
only a significant predictor of UFCATT (and not UFCSPI). This was
unique, as when significance was found in the other cases above, the
same result was found for both attitudes and purchase intentions. It
could be the case that the participants do not consume amateur MMA
events, which could cause them to see professional MMA as equivalent to
UFC (a correlation of .273 between UFCPAI and PROPAI lends some support
to this argument), potentially explaining the effect on UFC sponsors but
not fighter sponsors. However, this still does not explain the
significant result for UFCATT and not UFCPAI, so more research would be
necessary in order to determine this difference in findings.
There are several limitations of this work. For example, the sample
was quite homogeneous with respect to the high percentages of male and
Caucasian respondents. While these appear to be dominant demographic
groups among MMA fans based on other research in the area (Cheever,
2009; MacIntosh & Crow, 2011), other demographic groups still appear
to be somewhat underrepresented in this study, as females have been
increasingly targeted by the league in light of the recent addition of
female divisions (Armstrong, 2014). This could perhaps be a function of
where the data were collected, namely online message boards that are
located in the United States and are administered in English language
only, in that females and other demographic groups may be UFC fans, but
may not use these online services.
In terms of the data itself, one of the original points of
attachment (MMAPAI) had to be removed due to some multicollinearity
issues and low factor reliability, as mentioned in the results section.
Specifically, MMAPAI appeared to be multicollinear with PROPAI (and
UFCPAI, to a lesser degree), which could suggest that the participants
view MMA as a primarily professional sport, and subsequently equate UFC
with MMA. As such, it may be beneficial for future research in the MMA
space to focus on other professional and amateur MMA organizations,
whereas the primary research focus to this point has been on the UFC.
In addition, given the large number of UFC sponsors, and even
larger number of fighter-specific sponsors, it was not feasible to
include sponsor names on the survey. While this helps to decrease bias
based on respondents' individual attitudes to particular brands,
this approach could also minimize respondents' feelings about these
topics, causing possible significant relationships to go unobserved
based on the presentation of the items. Lastly, only one individual
sport was examined here, so no statistical comparisons could be drawn to
other individual sports. The results here, however, support further
examination of the points of attachment that are relevant to each sport,
as well as using multidimensional approaches to attachment in future
sponsorship research.
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Lamar Reams, PhD, is an assistant professor of sport management in
the Department of Human Movement Sciences at Old Dominion University.
His research interests include sport marketing and sport consumer
behavior.
Terry Eddy, PhD, is an assistant professor of recreation and sport
management in the Department of Health, Human Performance and Recreation
at the University of Arkansas. His research interests include sport
sponsorship and consumer behavior.
B. Colin Cork, MS, is a doctoral student in the Department of
Health, Human Performance and Recreation at the University of Arkansas.
His research interests include sport marketing and college athletic
donor behavior.
Table 1 Means, Standard Deviations and Cronbach
Alphas for PAI and Sponsorship Outcomes
Variable Mean SD [alpha]
Attachment to MMA (MMAPAI) 5.52 1.33 .631
First and foremost, I consider
myself to be an MMA fan.
MMA is my favorite sport.
I am a MMA fan at all levels
(e.g, professional, amateur).
Attachment to UFC (UFCPAI) 4.74 1.37 .726
I identify with numerous aspects of the
UFC rather than with just one fighter.
I feel a part of the UFC, not just
individual fighters.
I support the UFC as a whole, not
just its fighters.
Attachment to favorite fighter (FFPAI) 4.18 1.73 .852
I identify with [piped favorite fighter]
more than with the UFC.
I am a big fan of [piped favorite fighter],
more than I am a fan of the UFC.
I consider myself a fan of [piped
favorite fighter] rather than a
fan of the UFC.
Attachment to professional MMA (PROPAI) 5.69 1.34 .795
I am a fan of professional MMA, regardless
of who is fighting.
I don't identify with one specific
professional MMA organization, but
professional MMA in general.
I consider myself a fan of professional
MMA, and not just the UFC.
Attitudes toward UFC sponsors (UFCATT) 4.77 1.48 .971
When I think of companies that are
major sponsors of the UFC,
I personally see them as:
Bad--Good
Unfavorable--Favorable
Unpleasant--Pleasant
Attitudes toward fighter sponsors (FFATT) 5.26 1.35 .980
When I think of the companies that are
major sponsors of [piped favorite fighter],
I personally see them as:
Bad--Good
Unfavorable--Favorable
Unpleasant--Pleasant
UFC sponsor purchase intent (UFCSPI) 2.73 1.13 .926
I am likely to recommend UFC sponsors'
products to others.
I would consider buying UFC sponsors'
products in the future.
I will buy UFC sponsors' products
in the future.
Fighter sponsor purchase intent (FFSPI) 3.08 1.19 .944
I am likely to recommend products from
[piped favorite fighter] sponsor(s)
to others.
I would consider buying products from
[piped favorite fighter] sponsor(s)
in the future.
I will buy products from [piped favorite
fighter] sponsor(s) in the future.
Table 2 Correlations Between Variables
MMAPAI UFCPAI FFPAI PROPAI
MMAPAI 1 .417 * .266 * .644 *
UFCPAI 1 -.164 * .273 *
FFPAI 1 .210 *
PROPAI 1
UFCATT
FFATT
UFCSPI
FFSPI
UFCATT FFATT UFCSPI FFSPI
MMAPAI .355 * .238 * .235 * .271 *
UFCPAI .512 * .408 * .482 * .311 *
FFPAI -.090 .169 * -.056 .204 *
PROPAI .320 * .181 * .168 * .141
UFCATT 1 .680 * .653 * .486 *
FFATT 1 .492 * .644 *
UFCSPI 1 .755 *
FFSPI 1
Note. * indicates significance at the .05 level
Table 3
RQ1--Multiple Linear Regression Results
(DV = Attitudes toward UFC sponsors
(UFCATT))
Independent Standardized t Sig.
Variable coefficient
([beta])
UFCPAI .444 6.530 .000
FFPAI -.062 -.922 .358
PROPAI .212 3.086 .002
Note. (F(4, 172) = 24.794, p < .001),
[R.sup.2] = .301
Table 4
RQ2--Multiple Linear Regression Results
(DV = Attitudes toward fighter sponsors
(FFATT))
Independent Standardized t Sig.
Variable coefficient
([beta])
UFCPAI .445 6.217 .000
FFPAI .241 3.416 .001
PROPAI .009 .120 .905
Note. (F(4, 172) = 16.659, p < .001),
[R.sup.2] = .224
Table 5
RQ3--Multiple Linear Regression Results
(DV = UFC sponsor purchase intentions
(UFCSPI))
Independent Standardized t Sig.
Variable coefficient
([beta])
UFCPAI .475 6.674 .000
FFPAI .014 .201 .841
PROPAI .035 .490 .625
Note. (F(4, 172) = 17.633, p < .001),
[R.sup.2] = .234
Table 6 RQ4--Multiple Linear Regression Results
(DV = Fighter sponsor purchase intentions (FFSPI))
Independent Standardized t Sig.
Variable coefficient
([beta])
UFCPAI .358 4.810 .000
FFPAI .265 3.627 .000
PROPAI -.012 -.163 .871
Note. (F(4, 172) = 11.284, p < .001),
[R.sup.2] = .164