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  • 标题:Points of attachment and sponsorship outcomes in an individual sport.
  • 作者:Reams, Lamar ; Eddy, Terry ; Cork, B. Colin
  • 期刊名称:Sport Marketing Quarterly
  • 印刷版ISSN:1061-6934
  • 出版年度:2015
  • 期号:September
  • 语种:English
  • 出版社:Fitness Information Technology Inc.
  • 摘要: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).
  • 关键词:Market research;Marketing research;Sports spectators;Sports sponsorship

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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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
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