Runner identity and sponsorship: evaluating the Rock 'n' Roll Marathon.

Lough, Nancy L. ; Pharr, Jennifer R. ; Owen, Jason O. 等

Introduction

The economic value of US participation based sport has been reported to eclipse spectator sport by between two to four times each year (Kim, Smith, & James, 2010). With over half of the US population reporting regular sport participation each year (Humphreys & Ruseski, 2009), scholars have acknowledged the lack of research on this important sport market segment (Eagleman & Krohn, 2012; Kim et al., 2010). One sport demonstrating significant growth in recent years, despite difficult economic conditions, is the sport of competitive running. In particular, marathon and half-marathon distance running events have reported one of the largest increases. The number of runners who completed a half-marathon between 2009 and 2010 increased 24% creating a phenomenon Running USA (2011) labeled half marathon "hyper-mania" (p. 4). Similarly, the number of marathoners, or runners who completed a full marathon increased 8.5% during the same time frame. As a result, the running industry has experienced unprecedented and sustained growth (Running USA, 2013) led largely by a growing sophistication among race organizers and funding by sponsors. As the economic value of this participation based sport has continued to increase, research is warranted to understand the relationship between participants and sport sponsors to better inform race organizers.

The Running Industry

Just as the sport industry has continued to grow, the market segment referred to as the running industry has continued to show impressive growth in virtually every sector measured according to Running USA (2013). With overall running numbers up significantly and related apparel sales extending over the billion dollar mark, what has been referred to as the "second running boom" has emerged. Growth of the sector includes record or sold-out race fields, billions of dollars in shoe sales and running apparel, as well as innovative products to satisfy consumer needs, such as personalized devices to track individual workouts (Running USA, 2013).

The Sporting Goods Manufacturers Association forecast the running industry in the US to continue showing consistent annual growth, as total participation increased 57% from 1998 to 2008 (Sporting Goods Manufacturers Association, 2008). Running/jogging shoe sales totaled $2.32 billion in 2010 and sales were projected to continue to grow an additional 1% to approximately $2.33 billion in 2011 (National Sporting Goods Association, 2011). The NSGA also reported a 23% increase since 2009, in running apparel purchases in the US totaling $1.1 billion in 2010. This increase was higher than any other sport category listed in their report on athletic/sport clothing, and apparel in this category was forecast to continue to grow at a rate of 14% by 2011 (National Sporting Goods Association, 2011). These numbers substantiate a trend that started in 1994 and has continued as the number of US runners finishing a race has increased every year with the exception of 2003 (Running USA, 2013). All this growth has resulted in what has been deemed the second running boom with an estimated all-time high of 13 million race finishers nationwide and the largest percent increase (10%) in road race finishers that had ever been reported for two consecutive years (Running USA, 2011).

Yet, little is known about the sport participant as a consumer, in particular runners as consumers. Of note, when considering participant demographics, females now account for a record number of the nearly 6.9 million annual race finishers in the US. Plus, women on average represent 53% of runners in any event field. In comparison, in 1990 women were only 25% of the average field. By 2010, men also set a new high for race participation with more than 6.1 million US finishers. Interesting, nearly all of the reported increase in participation has evolved from two race categories, marathons (26.2 miles) and half marathons (13.1 miles).

According to Running USA "marathon mania" was reported initially in 2009 with a 9.9% participation increase. Then despite the lingering US recession, another year of record growth occurred in 2010 resulting in an estimated 507,000 marathon finishers. The 8.6% leap over 2009 represented the second largest increase in participation in 25 years. Still as yet another indicator of sustainable growth, most large US marathons reported sold-out or record fields, with several of the 2011 races having sold-out in record time (Running USA, 2011). Sustained growth is a selling point for race sponsors.

Despite the impressive growth of the marathon, America's favorite road race distance is clearly the half-marathon with a phenomenal growth rate of 24% reported for 2009. The trend continued with another reported increase from approximately 1.1 million half-marathon finishers in 2009 to 1.4 million finishers in 2010 (Running USA, 2011). Again, the women's segment, in addition to the Competitor Group's Rock 'n' Roll race series were identified as fueling the change, with a record 24 US half-marathons reporting 10,000 or more finishers (Running USA, 2013).

Since 2000 the number of half-marathon finishers in the US has nearly tripled (482,000 to 1,385,000), with growth since 2003 eclipsing 10% or more each year. The upward trajectory of half marathon races has resulted in the fastest growing road race distance for five consecutive years. With such unprecedented numbers, no other race distance has even come close to this level of participation. Experts believe the popularity of half marathons has been fueled mainly by easily accessible training programs, destination-based events/series, women's participation, and runners moving (up or down) from the marathon distance (Hamilton, 2012). Each of these explanations can be used to attract sponsors, whether through partnering with a destination city such as Las Vegas, using a training program as a point of activation or appealing to a specific segment such as the women's market. To date, no race organization has been as successful at hosting quality marathon and half-marathon events across the US and around the world as the Competitor Group.

Rock 'n' Roll Series

The Competitor Group's Rock 'n' Roll Series of events has continuously attracted more race participants each year. By adding new courses, promising fun destination-style events, live entertainment along the scenic courses as well as post-race concerts, the Competitor Group has created a brand name synonymous with quality races. In 2010, the Rock 'n' Roll series included seven of the top 10 US half-marathons, in addition to three inaugural half-marathons, each with more than 9,200 finishers. During this same year 15% of all US half-marathon finishers participated in one of the 14 Rock 'n' Roll half-marathons (Competitor Group, 2012).

Of the 255,000 runners who actually crossed the finish line in 2010, 62% were female, and 37% were running their first marathon or half-marathon, reflecting the broad appeal of these events to participants, race organizers and sponsors. Specifically related to this study, the inaugural Zappos.com Rock 'n' Roll Las Vegas half-marathon ranked ninth in the world with 19,217 participants. With 5,180 marathon participants in this same race, the potential for over 24,000 runners to associate a top quality event with the Zappos.com brand name was apparent. Perhaps even more intriguing is the potential to make the brand name synonymous with the Las Vegas based event. With a precedent set by the PF Chang's Rock "n" Roll Arizona Marathon, the inaugural sponsorship by Zappos.com may prove to hold this potential. Among marathon runners, the "PF Chang's" brand has become synonymous with the marathon organized by the Competitor Group in Arizona.

Sponsorship and Running Events

One recent study focused specifically on runners as sport participants, utilizing a road race series with varying distances to measure sponsorship awareness through recognition and recall rates, along with purchase intentions and attitudes toward race sponsors (Eagleman & Krohn, 2012). In addition to a sponsor recognition rate of 80.7% for two race sponsors, Eagleman and Krohn (2012) found participants who were highly identified with the road race series visited the race website more often, thus providing more potential opportunities for sponsors to communicate with consumers and for sponsorship activation. The authors found no significant differences based on demographic characteristics, but several key differences were found related to the respondent's reported level of identification with the race series. Those with higher levels of identification with the event were able to correctly identify more sponsors, and indicated a greater intent to purchase from race sponsors. As a result, Eaglemen and Krohn (2012) suggested a race organizer's goal should be to increase the level of identification participants have with the event, due to high rates of recognition, recall and purchase intention reported by runners who took part in the race series. Importantly, this study focused on identification with the event, in contrast to identification as a runner.

Several researchers have reported various aspects of identity tied to sport sponsorship effectiveness measures, with most scholars employing rates of sponsor recognition, recall and purchase intention (Bennett, Henson, & Zhang, 2002; Bennett, Cunningham, & Dees, 2006; Pitts & Slattery, 2004) and one study included the dimension of team identity. Maxwell and Lough (2009) compared sponsorship recognition among spectators in college basketball arenas with signage, versus arenas without signage, and reported rates were only 1.69% percent higher in arenas laden with signage. The researchers explained this surprising finding: "Spectators identification levels significantly contributed to correct sponsor recognition" (p. 195).

In a frequently cited study on marketing grassroots sporting events, Miloch and Lambrecht (2006) indicated "participants and supporters of these events may be different from the average sport consumer" (p. 148), suggesting sport participants may be more likely to purchase sponsor products. In their study rates of recognition and recall were comparable to other studies, although a bit lower. Similarly, respondents with greater interest in the grass-roots event indicated a higher likelihood to purchase sponsor products.

With regard to participant based sponsorship evaluation, Filo, Funk, and Obrien (2010) found the degree of a participant's attachment to the event influenced both their intention to purchase sponsor products as well as participate in a charity sporting event. However, the participant's perception of the sponsor's image did not influence their intent to participate in the event. In a related participant based study, Kim et al. (2010) reported non-elite triathletes with a higher level of gratitude towards triathlon race sponsors indicated a higher intention to purchase race sponsor products. As we see from these studies, when examining sponsorship effectiveness through recognition, recall and purchase intention, scholars have used a variety of identification measures including identification with the race series, team identity at spectator based sporting events, participant attachment to the event and participant's gratitude toward event sponsors, yet to date no study has focused specifically on the participant's identity as an athlete, or in this case runner identity.

With this small but growing body of literature focused on sport participant's impressions of event sponsors, we can conclude that identification with the event, attachment to the event and gratitude toward the event sponsors are all related to increased rates of sponsorship recognition, recall and purchase intention. Yet, what remains to be examined is the participant's identification with the sport at the center of the event and therefore the sponsorship relationship. In particular, can a participant's athletic identity, and in this case runner identity, be used to predict rates of recognition, recall and purchase intention, commonly used for sponsorship evaluation? If so, how can race organizers use participant's athletic identity measures when soliciting sponsors in the selection and/or evaluation process? Therefore, the goal of this study is to better understand the relationship between runner identity and race sponsor effectiveness. The following section will detail the theoretical underpinnings of athletic identity used to frame this study.

Athletic Identity

Sport marketing researchers have focused heavily on sport consumer aspects such as team identity, but rarely on sport participant identity. To initiate the conversation on athletic identity, research from sport psychology was reviewed. In 1993, Brewer, Van Raalte, and Linder established athletic identity as a measurable construct. They defined athletic identity as "the degree to which an individual identifies with the athlete role" (p. 237). Their Athletic Identity Measurement Scale (AIMS) was shown to be a valid and reliable measure, and as such has been utilized repeatedly in scholarly work (Horton & Mack, 2000; Martin, Eklund, & Mushett, 1997; Tasiemski, Kennedy, Gardner, & Blaikley, 2004; Visek, Hurst, Maxwell, & Watson, 2008). Harter (1990) was one of the first to describe a person's self-concept as a multi-dimensional entity with self-evaluation in the physical and athletic domains prevalent across the life span. This conceptualization was extended by sport psychologists who explained "individuals with strong athletic identity ascribe great importance to involvement in sport/exercise" (Brewer et al., 1993, p. 237).

Athletic identity also maintains a social aspect as found among individuals who report making a social statement about themselves by choosing to participate in a particular sport or exercise activity (Sadalla et al., 1988). Sport participation, such as running events, provides key opportunities to develop a sense of self, along with athletic prowess while engaging in social interaction. Runners are known for carrying on conversations during long runs, sometimes using their training time to bond with fellow runners. Given that "high levels of commitment commonly accompany participation in sport and exercise activities" (Brewer et al, 1993, p. 237), runners training for endurance length races or events share a commitment non-runners may not fully understand. From a marketing standpoint, these unique aspects of the sport participant represent opportunities to develop consumer based communication reflecting their consumer orientation and as a result may be facilitated among the running community by word of mouth (Godes & Mayzlin, 2004).

Brewer et al. (1993) found athletic identity is in fact a distinct form of identity. These authors also suggested athletic identity is likely to be stronger when one is in the presence of athletes or in a sport environment. With regards to the current focus, one study was found that specifically examined runner identity, as an application of the athletic identity scale to marathon runners. Horton and Mack (2000) used the AIMS to assess marathon runner's levels of athletic identity. Their key finding was "high AI was associated with better athletic performance, more commitment to running and an expanded social network" (Horton & Mack, 2000, p. 101).

While self-concept is acknowledged to be a multidimensional structure, "identity salience can be conceptualized as the probability that a given identity will be activated in a given situation" (Stryker, 1978, p. 102). Thus, people strong in AI, such as marathon runners, are likely to surround themselves with other athletes or in this case runners, who encourage a self-definition centered on the sport of running.

High AI participants were found to have an expanded social network related to involvement in running, with AI reported to be positively related to the proportion of good friends identified as runners. Similarly, high AI participants indicated greater commitment to running, greater enjoyment of running, greater investment in running, greater involvement in running opportunities and greater perceived social constraints to continue running, as compared to low AI participants (Horton & Mack, 2000).

"AI was directly related to expanded social network and proportion of friends who were runners" (Horton & Mack, p. 113), suggesting runners with strong AI form new relationships with other runners and thus, expand their overall social network. From a sponsor's perspective, the impression one runner has of an affiliated brand/sponsor will likely be shared among their friends in the running community. With word of mouth shown to maintain significant influence among consumers (Godes & Mayzlin, 2004), it is reasonable to suggest that marathon race sponsors have tremendous potential for positive impressions from a well-organized race, as well as the opposite should the impression be negative.

From a race management standpoint, these attributes along with the following description of race participants as consumers may be instructive: runners with a faster personal best time tend to manifest higher levels of AI. This suggests the motivation and discipline necessary for intense training and success in events such as a marathon will likely be correlated with high AI. This is not to suggest that slower marathon times would indicate low AI. To the contrary, completing a marathon, or successfully running 26.2 miles, would rarely be considered a disappointment. As research on cognitive dissonance has shown, the evaluation of a task is directly related to the degree of effort one must expend to accomplish the task (e.g., Aronson and Mills, 1959). While justification for the fatigue endured and intensive training required to complete a marathon successfully must come from within the athlete, identity salience may be enhanced simply due to the discipline and commitment required. Horton and Mack (2000) suggested "runners develop strong AI to justify the effort that they expend in pursuit of the marathon finish line" (p. 115). Race organizers who can relate promotional materials and sponsorship platforms to connect with this intensive aspect of runner identity have the opportunity to create a deep connection with race participants, and may have the potential for lasting impressions leading to increasing levels of loyalty. The following sections will provide an overview of the current state of research on sponsorship evaluation measures from a consumer perspective.

Sponsor Effectiveness

Sponsorship of a sporting event is a way corporations and other entities have established a link between their product and a leisure activity, such as running events. A consumer, or in this case participant is more receptive during a leisure activity to a sponsor's message because the participant is relaxed and engaged in an activity they enjoy and/or prefer (Mullin, Hardy, & Sutton, 2007). How receptive the participant / consumer is to the message can be determined through measuring the ability of the consumer to identify a specific firm as a sponsor of a specific sporting event (O'Reilly, Nadeau, Seguin, & Harrison, 2007). Although various aspects of consumer identification have become instrumental in measuring sponsorship effectiveness, there appears to be a lack of understanding regarding participant identity or in this case athletic identity measures and the evaluation of sport sponsorship effectiveness. No previous study was found that examined the athletic identity aspect of the research subjects, although researchers have demonstrated that runners tend to maintain a level of athletic identity that can be measured (Horton & Mack, 2000).

Sponsorship Use in Sport

Sport sponsorship seen in the earliest sporting events, such as the Olympic Games, largely came in the form of private donations provided by cities represented in the early Olympic Games (Giannoulakis, Stotlar, Chatziefstathiou, et al., 2008). Following the trend of providing donations to support sporting events, running event sponsors initially provided donations or in kind gifts in exchange for their logo or brand on the race t-shirt. The norm established early on for sponsors of running events was brand placement among a cluttered grouping of other "goodwill" or community based businesses (Lough, 2009). No competitive advantage was likely to be achieved for these race sponsors, although few sponsors had a stated market driven goal for these investments. However, as competition grew and sponsorship decision makers were increasingly held accountable, evaluation of sponsorships changed. Sport sponsorship has since evolved into a relationship where both the corporate sponsor and sport entity seek to benefit from the sponsorship activity (Lough & Irwin, 2001; Polonsky & Speed, 2001). Sport events have grown in popularity as a means of advertising and sculpting the image of various firms and organizations (Cunningham, Cornwell, & Coote, 2009). Sport sponsorship is now viewed as a significant branding medium for corporate sponsors due to its global reach through a variety of platforms (Santomier, Dolles, & Soderman, 2009) and the potential it provides for financial stability in a variety of segments within the sport industry (Bennett et al., 2002).

Sponsorship of Participation Sport Events

The current literature covering sport sponsorship primarily focuses on large, spectator based events and the respective sponsors of those events. The variables identified for a successful sport sponsorship for spectator based events include attendance numbers, venue size and prestige (Kim, Smith, & James, 2010). In contrast, sponsorship of participant based sporting events has been centered around lifestyle marketing (Miloch & Lambrecht, 2006). The primary goal of the sponsor in this case is to align a specific product with the lifestyle behaviors of the consumer through promotional activities at participant based sporting events (Michman, Mazze, & Greco, 2003). Participant based sporting events and lifestyle marketing are appealing to corporate apparel and equipment sponsors due to the extravagant spending habits of an emerging generation of young adults who frequently take part in participant based sport (Bennett & Lachowetz, 2004). For the purposes of this study, runners as sport participants appear to provide an avenue for the development of successful sponsorship relationships through application of lifestyle marketing strategies.

Sponsorship of Running Events

Limited research has been conducted on the sponsorship of running events, however the research that has been conducted has shown similar benefits of sponsoring a running event as other participation based sporting events (McKelvey, Sandler, & Snyder, 2012). An important benefit to sponsoring a running event is the ability of a corporate sponsor to develop brand equity through name awareness and brand loyalty. Corporate sponsors have found a niche market in running events when seeking to align with an event that has the specific qualities of distinct name awareness and brand loyalty in events such as the Flying Pig Marathon (Olberding & Jisha, 2005). Olberding and Jisha (2005) explain that corporate sponsors have gravitated towards such events due to the unique nature of the running event and the intense loyalty to the marathon. These authors also described how the branding that occurs through the unique gifts given to marathon participants has created a distinct awareness, and has attracted large national sponsors, as well as regional sponsors. Other researchers have found that corporate sponsors are finding the sponsorship of large running events very beneficial to their product because of the positive image that participating in a health-promoting event, such as a marathon, represents (Eagleman & Krohn, 2012; Firica, 2008). Similar studies have found that corporate sponsors of running events are realizing a significant amount of value by sponsoring non-profit, cause-related running events because of the positive image transfer of the race to the associated sponsor (Cornwell & Coote, 2005). Cornwell and Coote (2005) reported the association of the corporate sponsor with the cause-related race increased the purchase intentions of race sponsor products amongst race participants. However, no study was found that included an examination of the athletic identity aspect of the research subjects as related to measures of sponsorship effectiveness, although research has demonstrated that runners tend to maintain a level of athletic identity that can be measured (Horton & Mack, 2000).

Given this growing body of literature, along with the rapidly developing running industry, we can conclude that a study examining participants' athletic identity is warranted. Previous research on aspects of identity such as attachment to the event and gratitude toward the event sponsors have fallen short of a more psychologically-based measure characterizing an aspect of the consumer's self-concept that is most directly related to the sponsored event. Thus, what remains to be examined is the participant's identification with the sport at the center of the event and thereby the sponsorship relationship. In particular, can a participant's athletic identity, and in this case runner identity, be used to predict rates of recognition, recall and purchase intention, referred to here as sponsor effectiveness? If so, how can race organizers use participant's athletic identity measures when seeking sport sponsors?

Methods

Email surveys were sent to all registered participants in the Las Vegas Rock 'n' Roll Marathon held on December 5, 2010 (Wooldridge, 2009). In total, 24,338 runners completed the race. The survey was distributed via email by the Competitor Group, Inc. the official race organizer, to all registered runners after the completion of the race and 1,388 completed the survey. Descriptive statistics were calculated for the participants and included gender, age, income, relationship status and education.

The survey was constructed utilizing the ten questions comprising the Runner Identity Scale validated by Horton and Mack (2000). The author's sought to assess the relationship between athletic identity and various social, behavioral and psychological aspects of running by utilizing the ten item AIMS to assess the degree to which a sport participant identifies him or herself as an athlete. To evaluate marathon runners, the authors modified the items to achieve a more direct application. For example, "I consider myself an athlete" was altered to "I consider myself a runner." Using a seven point Likert scale, participants indicated their extent of agreement with each item, with a 7 representing "strongly agree" and 1 representing "strongly disagree". High scores demonstrated stronger identification as a runner. Upon modification of the instrument to measure runner identity, Horton and Mack reported an acceptable internal consistency score (a=.86), which was similar to the original version (a=.93) reported by Brewer et. al (1993). They also asserted that, because the AIMS had already been validated by Brewer et. al (1993) and because AI of marathon runners was not inherently different from other sports, the scale had external validity. One example of validity provided by Brewer et. al (1993) was that the mean AIMS score increased as the level of athletic involvement increased (p<.005) among participants in their study. Interestingly, Horton and Mack (2000) found a significant, positive relationship (p<.001) between commitment to running, investment in running, enjoyment of running and involvement in opportunities to run and their participants' AIMS score, illustrating that their modified AIM scale measured what they set out to measure and providing evidence of validity.

For their sample of 236 marathon runners a 40.92 (SD=9.27) mean score was acquired based upon the modified AIMS. Extreme groups were established based upon cut-points at the 33rd and 67th percentiles. Participants below the 33rd percentile were labeled low AI (M=30.97, SD=4.77, n=79), while those above the 67th percentile were considered high AI (M=51.09, SD=5.28, n=79). The AIMS scores were determined to be significantly different from one another, F(1,156)=630.76, p<.001. This same approach to attain runner identity levels was utilized in the current study. The highest possible runner ID score was 70 and the lowest was 7.

Demographic data were collected for participants. Multiple linear regression was utilized to determine if demographic characteristics of runners were significantly associated with runner identity. Total runner identity score was the dependent variable and demographic characteristics were the independent variables which included gender, age, income, education, and relationship status.

In addition to the runner identity questions, recall questions were included to assess whether participants could recall the title sponsor of the race, the official bottled water sponsor and the official energy supplement sponsor of the race. Recognition questions were also posed that listed three official sponsors (Zappos.com, Brooks, and GU) and seven non-sponsors (dummy sponsors) representing competing brands in common sponsor categories (Shoes.com, Prudential, Progressive, Geico, PF Changs, Benihana, Piperlime, Asics, Powerbar, and ING). Participants were asked to identify the brands they believed represented official sponsors of the race (Robinson, Pons, Stotlar, & Bradish, 2008). Proportions were calculated for those who recalled Zappos.com as the title sponsor and identified Zappos.com as the title sponsor (recognition). Multiple logistic regression analysis was utilized to determine which factors predicted the likelihood of respondents: 1) recalling Zappos.com as the title sponsor and 2) recognizing Zappos.com, GU, and Brooks official sponsors. The predictive (independent) variables included the total runner identification score, gender, age, income, education, and relationship status.

Multiple linear regression was utilized to determine which characteristics of the runners (total runner ID score, age, income, gender, ethnicity, education, or relationship status) would predict purchase intention variables. The purchase intention questions were measured on a seven-point Likert scale and coded as continuous variables. The purchase intention items included: How likely are you to visit the website of the title sponsor because of their involvement with the event? How likely are you to consider products of the title sponsor over non-sponsors? Does their involvement in the Las Vegas Rock 'n' Roll marathon make you more likely to use the title sponsors products/services? Does their involvement in the Las Vegas Rock 'n' Roll marathon make you more likely to use official sponsor products/services?

Finally, an analysis of variance (ANOVA) and an analysis of covariance (ANCOVA) were utilized to determine if runner ID influenced purchase intentions (PI). Runners were divided into three groups based on their total runner identity score. The groups were based upon the previously mentioned study by Horton and Mack (2000). Following the example, highly identified runners were those in the top 67th percentile and participants with low runner identity were those in the bottom 33rd percentile (Horton & Mack, 2000). Participants whose total runner identity fell between the 33rd and 67th percentile were considered to be moderately identified runners. A Tukey post hoc test was utilized when overall ANOVA or ANCOVA results were significant for group differences. Gender, age, income, education, ethnicity and relationship status were used as covariates in the ANCOVA. SPSS 22.0 statistical software was utilized for all statistical analyses.

Results

Descriptive statistics for the participants' are included in Table 1. Primary participant attributes of note included the participants' mean age was 40 years, and the mean household income was $124,295.60. Other attributes of note included gender count, where participants were primarily female (60.3%) compared to males (39.4%). The gender makeup of this event was similar to other Rock 'n' Roll events which have 60% female and 40% male participation. Most participants (61.2%) had no children under the age of 18. Over half of the participants were married, and participants were highly educated with degrees reported as bachelor's (43.7%), master's (19.7%), doctoral (4.6%), or another type of professional degree (5.1%). Most of the participants indicated their ethnicity as Caucasian (76.51%). The mean runner ID score for the group was 36.08 (Standard Deviation 12.81). Multiple linear regression was utilized to determine if demographic variables were associated with total runner ID scores. The model was not significant (p=0.29) showing gender, age, income, education and relationship status were not significantly related to total runner ID score.

Participants in this study had exceptionally high recall rates (unaided recall) of Zappos.com as the title sponsor (96.97%) relative to other sponsors and non-sponsors (see Table 2). Using multiple logistic regression, only total runner ID score (p<.001) was a significant variable for correct identification of Zappos.com as the title sponsor. Gender (p=0.15), age (p=0.89), income (p=0.35), education (p=0.67) and relationship status (p=0.85) were not significant for title sponsor recall.

The recognition (aided-recall) rates showed that official sponsors received higher recognition rates compared to non-sponsors (see Table 3). The participants also recognized official sponsors at an elevated rate relative to the dummy sponsors. Participants recognized the official sponsors including Zappos.com, GU, and Brooks at rates of 97.48%, 73.63%, and 80.62%, respectively. Multiple logistic regression was used to determine if total runner ID score or other demographic variables were significant for predicting recognition of official sponsors. Again, only the total runner ID score (p<.01) was a significant variable for recognizing Zappos.com, GU, and Brooks as official sponsors. Gender, age, income, education, and relationship status were not significant for recognizing official sponsors of the event.

Multiple linear regression was utilized to determine which characteristics of the runners predicted purchase intention variables. Independent variables included runner ID, age, income, educational attainment, and relationship status. Of the independent variables, runner ID and gender were significant predictors of each of the purchase intention variables including: how likely are you to visit the website of the title sponsor because of their involvement with the event (F=2.91, model p<0.01, runner ID p<0.01, gender p=0.06); how likely are you to consider products of the title sponsor over non-sponsors (F=2.69, model p<0.01, runner ID p<0.01, gender p=0.01); does their involvement in the Las Vegas Rock 'n' Roll marathon make you more likely to use the title sponsors products/services (F=2.77, model p<0.01, runner ID p<0.01, gender p<0.01); and does their involvement in the Las Vegas Rock 'n' Roll marathon make you more likely to use office sponsor products/services (F=1.88, model p=0.02, runner ID p<0.01, gender p<0.01). The beta coefficient for gender was positive with male gender having a positive relationship with purchase intention in each analysis.

As previously mentioned, runners were grouped into three categories based on their summed runner identity score. Group 1 included runners with a summed runner ID score below the 33rd percentile (summed runner ID score below 31), and this group was considered to have a low runner identity (mean summed identity score=22.07, N=445, SD=5.8). Group 2 included runners with a summed runner ID score between the 33rd percentile and the 67th percentile (summed runner ID scores between 31 and 42), and this group was considered to have a moderate runner identity (mean summed identity score =36.48, N=483, SD=3.5). Group 3 included runners with a summed runner ID score above the 67th percentile (summed runner ID score above 42) and this group was considered to have a high runner identity (mean summed identity score=50.32, N=450, SD=5.8). Table 4 shows the distribution of runner identity scores.

The ANOVA test showed there were significant differences between groups (p<0.01) in regards to their respective purchase intention variables. Mean purchase intention scores with 95% confidence intervals are shown in Table 5. A Tukey Post Hoc test showed that the most highly identified group, Group 3, was more likely (p=0.04) to purchase products from the title sponsor because of their involvement in the event compared to Group 1 the lowest identified group. Tukey post hoc tests also revealed that the highly identified group would be more likely to visit the website of the title sponsor because of their involvement in the event (p<0.01), consider title sponsor products over non-sponsor products (p<0.01) and purchase the products of race sponsors in general (p<0.01), relative to the group with the lowest level of runner identity.

Lastly, ANCOVA was utilized to understand the influence of runner ID on purchase intention using gender, age, income, education and relationship status as covariates. Interaction terms were created for runner ID and each of the covariates. None of the interaction terms were significant. Gender (p<0.01) was the only significant covariate for each of the purchase intention analyses. Purchase intention means with gender as a covariate increased and are provided in Table 5.

In summation, the results of this study have revealed high levels of recognition and recall of the title sponsor and other official sponsors of the inaugural Zappos.com Las Vegas Rock 'n' Roll Marathon with total runner identity score predicting their ability to recall and recognize the official title sponsor. Gender was the only other significant independent variable. A positive correlation was also discovered between the total runner identity score and the purchase intentions of a participant in regard to the title sponsor's product. In the following section, the key findings will be discussed along with implications for sport marketers.

Discussion

The initial purpose of this study was to examine the relationship between runner identity and sponsorship effectiveness, as measured by recognition, recall, and intent to purchase sponsor's products. No previous study was found that examined the athletic identity aspect of the research subjects, although researchers have demonstrated that runners tend to maintain a level of athletic identity that can be measured (Horton & Mack, 2000). As a result, the most interesting finding was that the total runner identity score influences many aspects of a runner as a consumer, including the ability to recall and recognize a sponsor, as well as predict purchase intentions. Perhaps most surprising, the beta coefficient for gender was positive with male gender having a positive relationship with purchase intention.

The recognition of runner identity as a measurable variable, and one that predicts sponsorship effectiveness measures, serves as a key contribution to current theory. Participants with high runner identity had significantly higher scores on purchase intention than participants with lower levels of runner identity. This is important because identity can fluctuate, meaning a runner's identity can grow with increasing involvement in the sport, and can be influenced by social groups engaged in the activity (Taifel, 1982; Turner, 1982). Similarly, knowing higher levels of identity translate to higher rates of purchase intention, race organizers can utilize this variable to enhance sponsorship proposals and activation opportunities.

Based on their study findings, Eaglemen and Krohn (2012) suggested a race organizer's goal should be to increase the level of identification participants have with the event. Our findings support this suggestion, as well as demonstrate the value of an aspect of sport consumer identity not previously considered. With regard to the specific race utilized for this study, sponsorship effectiveness measures were remarkably high. Perhaps a partial explanation is the fact that the Zappos.com Las Vegas Rock 'n' Roll marathon was recognized as the largest half marathon field in the US in 2011, in the same year that the half marathon was rated as the favorite race among runners (Hamilton, 2012). After the inaugural success of the 2010 event, word of mouth among runners regarding the race experience led to a reputation as a "must do" race among highly identified runners. Because of the interpersonal influence perpetuated by word of mouth, it has been shown to be a strong predictor of behavior towards a brand (Godes & Mayzlin, 2004; Gershoff & Johar, 2006; Cheema & Kaikati, 2010). Thus, there appears to be a capacity for runner identity to influence positive word of mouth regarding race event brands, such as the Rock 'n' Roll, as well as race sponsors.

Measuring runner identity is a concept that emerged from the Athletic Identity Measurement Scale (AIMS), which measures the psychological attachment and commitment of an individual to their respective sport. The level to which an individual identifies with his/her sport is contingent upon how much significance an athlete attributes to his/her participation in the sport, as well as his/her social standing within the domain of the respective sport (Brewer et al., 1993). The participation of an individual will lead to different levels of success, relative to the self-concept of the athlete, which will ultimately determine the strength of the athletic identity of the individual (Turner, 1982). The defining factor attributed to the social self-concept of the individual within the domain of sport is relative to the sport-specific influences perpetuated by the individual's surrounding social network (Styrker & Serpe, 1994; Taifel, 1982; Turner, 1982; Horton & Mack, 2000). The idea of self-concept, in terms of identity salience, relates to runner identity, and ultimately to the purchase intentions of a runner, due to the concept that identity salience can predict the choices of an individual based upon their perceived social role (Stryker & Serpe, 1994). As we demonstrated, of the predictive variables, only total runner identification score was a significant predictor for identifying Zappos.com as a sponsor (p<.001, = .043). Thus, to facilitate a relationship between sponsor effectiveness measures and sport participants, attention should be paid to levels of sport specific athletic identity, such as runner identity.

With regard to significance when considering the results, the differences between runners with high identity and runners with lower levels of identity may not immediately appear meaningful. The difference between mean scores was statistically significant, however when considering the mean scores individually, one might question the practical significance (i.e., is a mean score of 4.10 practically different from a mean score of 3.71 for intent to visit the website of the title sponsor because of their involvement with the event? (Table 5). Yet, this difference points to the value offered by studying identity as a variable. With the number of races increasing each year, and growing competition for sponsorship resources in finite categories such as running shoe companies, small differences in key consumer variables may have more meaning when considering aspects of market share. For example, the running shoe company Brooks, would find far greater value investing in a race in which the participants are known to have high levels of runner identity in contrast to event identity.

Relatedly, we found that male gender increased the purchase intention responses. One explanation may be that women are not more likely to visit Zappos' website or purchase their product because of their involvement with the event. Women are a key target market for this online retailer that started by selling shoes. Women in the study may already visit Zappos' website and purchase their products on a regular basis. In a marathon sponsorship Zappos' goal was not to make loyal customers more loyal, so much as to generate awareness and new business. It appears this finding shows an increase in interest among men who might not be loyal customers but who Zappos would want to influence to become customers through their sponsorship of the event. With so much focus on the preponderance of women in running events, this finding points to the value of male runners as a target market. Therefore, race organizers who demonstrate an awareness of key analytic variables such as levels of identity and gender can create more targeted sponsorship proposals, with greater likelihood for effectiveness. Similarly, runner identity has been shown to have the capacity to develop, which may influence identification with running events and sponsors over time leading to enhanced loyalty.

Implications for Race Organizers

The current study includes information as to how runner identity is tied to measures that can be used by race organizers to attract or retain sponsors. From a lifestyle marketing perspective, those committed to the training required to complete a marathon or half-marathon distance race represent a distinct lifestyle (Bennett & Lachowetz, 2004; Horton & Mack, 2000). The primary implications for race organizers, such as the Competitor Group, appear to be threefold. First, maintain a focus on women given women drive the numbers in the half marathon, with 950,000 female finishers in 2011, representing 59% of all finishers (Hamilton, 2012). Additionally, women are likely to bring friends along to run as it typically represents a social experience for them, and social identity is likely to be enhanced in this environment. Second, continue to offer a half-marathon race option. "Today half marathoners outnumber marathoners on average 4 to 1 in all but one of the Competitor Groups 26 events" (Hamilton, 2012, p. 76). The Las Vegas marathon attracted 4,000 runners in 2011, while in comparison 33,000 ran the half marathon distance. This trend has continued for years as Hamilton (2012) reported the half over took the marathon as the marquee event in 2004.

According to the over 8,000 respondents to the runnersworld.com survey, 37% rated the half-marathon as their favorite distance, with the marathon coming in a distant fourth on the list at 13%. Meanwhile 50% indicated they had not run a full marathon, and the highest percentage (39%) had completed between one and five full marathons. From a runner identity perspective, it seems race organizers would be wise to focus on repeat runners/consumers for the favored distance. Similarly, marathons appear more likely to be a check on a list of races to complete, rather than an event to repeat year after year.

Finally, the third consideration for race organizers should be an incentive program similar to the one developed by the Competitor Group (2012). Their "Heavy Medal" theme aligning with the Rock 'n' Roll brand is built on the notion of a runner becoming a "Rock Star". This approach rewards runners who complete between two and twelve events in one calendar year, with a specific medal (referred to as bling in the running community) to designate the accomplishment. This incentive program may be a key component toward increasing runner identity, as the medals are based on each runner's accomplishment. For example, two races will lead to the "Rock Encore" medal; followed by the "Triple Crown" for three races; "Home Run" for four races; and the coveted status of "Rock Star" for completing five Rock 'n' Roll races in one calendar year. Still, the awards continue on up to twelve races, and also include two special medals for the "Desert Double-Down" series including Las Vegas and Phoenix; and the "Pacific Peaks" for completing both the Portland and Seattle races (Competitor Group, 2012). By incentivizing runners to complete multiple races, the race organizers are improving the potential for runner identity to be sustained at a high level or actually increase. From a sponsor effectiveness perspective, high levels of identity along with the repeated opportunities for brand development provide significant assets for race organizers to work with in seeking sponsorships. As this study demonstrated, the highly identified group would be significantly more likely to visit the website of the title sponsor, consider title sponsor products over non-sponsor products and purchase the products of race sponsors in general.

Implications for Sponsors

Inaugural events or initial affiliation as a title sponsor can lead to branding of the event with the sponsor's brand name (Cornwell &

Coote, 2005). For example, consider the PF Chang's Arizona Rock 'n Roll marathon. Among runners, the race is referred to as the "PF Chang's", and it has one of the highest sustained participation rates among the series (Competitor Group, 2012). Just as the Kleenex brand became synonymous with the product of facial tissue, the potential for a race sponsor to become synonymous with the running event may be realized. Zappos.com achieved multiple objectives through their association with the Las Vegas marathon, but much of the success in this partnership can be attributed directly to the Competitor Group. Prior to becoming a stop on the series, the Las Vegas marathon had struggled, with inconsistent attendance and reputation. Perhaps the fit between the Rock 'n' Roll brand and the destination city of Las Vegas enhanced the relationship, but in addition linking a Las Vegas based brand with a unique name and mission also appeared to create a synergy that has resulted in beneficial outcomes for all three entities. As Cornwell (2012) has shown, there is considerable challenge in re-branding for new sponsors after an initial impression has been established. For Zappos.com, sponsorship of the Las Vegas marathon may result in a lasting impression that would be hard for any future sponsor to overcome.

When one considers the length of time required for a runner to prepare for a marathon, along with the identity/commitment level of these runners, the potential exists for improved brand awareness and equity. The title sponsor (PF Chang's or Zappos.com) will likely have their brand name repeated by runners, media, volunteers and other community members for months leading up to the event. As we have seen from the current study, word of mouth may have been influential in the record number of runners recorded in the 2011 Las Vegas event. However word of mouth can also create negative associations (Godes & Mayzlin, 2004). At a price of $175 ($130 for early registrants) the Zappos.com Rock 'n' Roll Las Vegas Half Marathon was the most expensive in the US (Hamilton, 2012). From the sponsor perspective, changing this event to be run at night under the lights of the famous Las Vegas strip, seemed to be a good idea, and it gained considerable status as the largest event of this kind in the world. Thus, generating additional publicity and thereby brand awareness for the title sponsor. However, multiple problems occurred during and after the night time event leading several runners to post complaints on Facebook which may have resulted in negative impressions of the event. The Zappos.com brand did not directly receive negative publicity however race sponsors should be cautious in their decision making with regards to both the race organizer's ability to host a well-run event, as well as considering changes to the event that will directly impact runners/consumers. As use of social media increases, highly identified consumers/runners may be influential in building or compromising the reputation of races and/or sponsors.

Conclusion

As this study has shown, there is measurable value associated with highly identified sport participants. One question specific to the running industry that warrants future study is what makes a race one that highly identified runners want to repeat? We have seen from this study, as well as others, that various aspects of identity can be measured, and can add value for sponsors as well as sport organizers and marketers. However, one component of runner identity and identification with an event to consider is whether identity is related to loyalty, and whether that loyalty can enhance sponsor effectiveness. Further research is warranted to determine if there is a cumulative effect when runners complete multiple races. Specifically, does completion of more races result in higher levels of runner identity and resultantly, higher levels of sponsorship effectiveness or allegiance?

With regards to the current study, does the Rock 'n' Roll incentive program build loyalty for the Rock 'n' Roll brand alone, or does it also add value and potential loyalty for title sponsors of their events? Similarly, do loyalty programs have the capacity to increase levels of runner identity? Lastly, a dearth of research exists on pricing sponsorships (Cornwell & Coote, 2005). As future research begins to expand in this area, consideration should be given to the gender of highly identified runners (or other sport participants) and the opportunity to attract sponsors based upon these unique market segments.

Limitations

The focus of the current study was limited to runner identity and therefore no other aspect of identity was considered. As a result, generalization of the current findings to other sports or participation-based events (i.e., triathlon, cycling, golf, etc.) would not be appropriate. Runners, and in particular those who train for and complete marathon distances, represent both a unique set of consumers and a unique lifestyle. Similarly, the data represent a US-based event. Runner identity may vary based on country of origin, and patterns of sport participation may also vary.

As we have seen from previous studies, when examining sponsorship effectiveness through recognition, recall, and purchase intention, scholars have used a variety of identification measures including identification with the race series, team identity at spectator based sporting events, participant attachment to the event, and participant's gratitude toward event sponsors, yet to date this is the first study to focus specifically on the participant's identity as an athlete, or in this case runner identity. The most compelling aspect of this study was the determination that athletic identity, or in this case, a runner's level of identity, influences their ability to recall and recognize a sponsor, as well as predict purchase intentions. Runner identity has also been shown to have the capacity to develop, which may influence identification with running events and sponsors over time leading to enhanced loyalty. By knowing higher levels of identity translate to higher rates of purchase intention, race organizers can utilize this variable to enhance sponsorship proposals and activation opportunities.

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Nancy L. Lough, EdD, is a professor in the Department of Educational Psychology and Higher Education at the University of Las Vegas at Nevada. Her research interests include the intersection of sponsorship, women and sport.

Jennifer R. Pharr, PhD, MBA, is an assistant professor of public health in the Environmental and Occupational Health Department at the University of Las Vegas at Nevada. Her research interests include the intersection of sport, physical activity and health.

Jason O. Owen is a doctoral student in business management at the University of Mississippi. His research interests include leader identity, franchising, and political skill. Table 1 Descriptive Statistics of the Participants Standard Deviation Variable Mean / N (SD) / % Female 837 60.3% Male 551 39.7% Age 40.41 9.49 Income in dollars 124,296 76,947 Children (n; %) No children 850 61.24% 1 child 161 11.60% 2 children 237 17.07% Other 140 10.09% Relationship Status (n; %) Married 816 58.79% Single 467 33.65% Domestic Partner 49 3.53% Other 56 4.03% Education (n; %) High school diploma 181 13.04% Associate's degree 154 11.10% Bachelor's degree 607 43.73% Master's degree 273 19.67% Doctorate 68 4.90% Other 105 7.56% Race/Ethnicity (n; %) White 1062 76.51% Hispanic 94 6.77% Black 23 1.66% Asian 64 4.61% Other 145 10.45% Table 2 Recall of Title Sponsors Company N ** % Zappos.com * 1346 96.97% Brooks ([dagger]) 25 1.8% PF Changs ([dagger]) 9 .65% ING ([dagger]) 2 .14% * Correct title sponsor ([dagger]) Incorrect title sponsor ** N represents the number of participants who recalled either the correct title sponsor (Zappos.com) or incorrect title sponsors (Brooks, PF Changs or INC) Table 3 Recognition of Official Sponsors Company N ** % Zappos.com * 1353 97.48% Brooks * 1119 80.62% GU * 1022 73.63% Powerbar ([dagger]) 281 20.24% ING ([dagger]) 196 14.12% Asics ([dagger]) 117 8.43% PF Changs ([dagger]) 31 2.23% Geico ([dagger]) 29 2.09% Shoes.com ([dagger]) 18 1.3% Progressive ([dagger]) 18 1.3% * Official Sponsors ([dagger]) Dummy Sponsors ** N represents the number of participants who either correctly recognized official sponsors (*) or incorrectly identified a dummy sponsor ([dagger]) as an Table 4 Summed Runner ID Scores with Frequency and Cumulative Percent Summed Runner Frequency Cumulative ID Score Percent 9.00 2 .1 10.00 18 1.5 11.00 8 2.0 12.00 4 2.3 13.00 11 3.1 14.00 13 4.1 15.00 15 5.2 16.00 17 6.4 17.00 12 7.3 18.00 24 9.0 19.00 18 10.3 20.00 32 12.6 21.00 21 14.2 22.00 22 15.7 23.00 18 17.1 24.00 28 19.1 25.00 26 21.0 26.00 30 23.1 27.00 24 24.9 28.00 31 27.1 29.00 40 30.0 30.00 31 32.3 31.00 42 35.3 32.00 49 38.9 33.00 43 42.0 34.00 34 44.5 35.00 31 46.7 36.00 39 49.6 37.00 41 52.5 38.00 40 55.4 39.00 33 57.8 40.00 50 61.5 41.00 38 64.2 42.00 43 67.3 43.00 31 69.6 44.00 36 72.2 45.00 37 74.9 46.00 35 77.4 47.00 36 80.0 48.00 41 83.0 49.00 20 84.5 50.00 38 87.2 51.00 23 88.9 52.00 25 90.7 53.00 20 92.2 54.00 9 92.8 55.00 8 93.4 56.00 10 94.1 57.00 14 95.1 58.00 15 96.2 59.00 7 96.7 60.00 12 97.6 61.00 9 98.3 62.00 7 98.8 63.00 4 99.1 64.00 6 99.5 65.00 2 99.6 66.00 1 99.7 67.00 1 99.8 68.00 1 99.9 70.00 2 100.0 Table 5 Mean Scores and 95% Confidence Intervals for Purchase Intention Variables On a scale of 1 to 7, how N Mean ANOVA 95% likely are you to: Score Confidence ANOVA Interval Visit the website of the 1.00 * 444 3.71 3.54 title sponsor because of 2.00 * 481 4.07 3.90 their involvement with the 3.00 * 448 4.10 3.93 event? Total 1373 3.96 3.87 Consider products of the 1.00 * 441 3.99 3.82 title sponsor over 2.00 * 482 4.15 4.00 non-sponsors? 3.00 * 448 4.35 4.19 Total 1371 4.16 4.07 Purchase products from 1.00 * 439 4.08 3.91 the title sponsor because 2.00 * 482 4.24 4.08 of their involvement 3.00 * 448 4.36 4.20 in the event? Total 1369 4.23 4.13 Purchase products of 1.00 * 438 4.18 4.03 the race sponsors? 2.00 * 481 4.42 4.28 3.00 * 446 4.50 4.34 Total 1365 4.37 4.28 On a scale of 1 to 7, how ANOVA 95% Mean likely are you to: Confidence Score Interval ANCOVA Visit the website of the 3.87 3.74 title sponsor because of 4.23 4.12 their involvement with the 4.27 4.14 event? 4.06 4.01 Consider products of the 4.15 4.05 title sponsor over 4.30 4.20 non-sponsors? 4.51 4.39 4.26 4.22 Purchase products from 4.24 4.12 the title sponsor because 4.40 4.29 of their involvement 4.52 4.39 in the event? 4.32 4.27 Purchase products of 4.34 4.24 the race sponsors? 4.57 4.47 4.66 4.52 4.46 4.41 * 1=Group 1 - lowest runner ID; 2=Group 2 - moderate runner ID; 3=Group 3- highest runner ID