Does your sponsor affect my perception of the event? the role of event sponsors as signals.

Walker, Matthew ; Hall, Todd ; Todd, Samuel Y. 等

Does Your Sponsor Affect My Perception of the Event? The Role of Event Sponsors as Signals

For the sponsor, the ability to leverage its connection to an event, in addition to accessing specific demographic groups, is exchanged for a financial or in-kind investment used to underwrite the costs of the event (Cliffe & Motion, 2005; Farrelly & Quester, 2003; Howard & Crompton, 2004). This seemingly simple exchange may also result in some unintended effects that to date, have yet to garner the attention of sport marketing researchers. For example, while companies carefully consider how associating with specific events will reflect on their image, little consideration has been given to how sponsors may impact the event's image. If such an issue has been considered, the discussion has been restricted to whether the event should sell sponsorships to the so called "sin industries" of alcohol and tobacco.

In their detailed review of the extant sponsorship research, Cornwell and Maignan (1998) concluded that scholars need to more completely understand how sponsorship communication (i.e., whether intended or unintended) can impact event perceptions. Following this recommendation, Pracejus (2004) summarized seven psychological mechanisms through which sponsorship can impact various desirable marketing objectives. In his discussion, the author offered evidence that implied size, the cognitive processing that "... this must be a big company to sponsor this event" (p. 183), has received both anecdotal and empirical support. He also stated that this function may operate in the opposite direction, wherein the quality of the sponsor may impact the quality (or equity) of the event. Little research, however, has investigated this effect. This statement points to the need to clarify under what conditions a sponsor can influence (i.e., signal) perceptions of event quality. For example, the company is large enough to be title sponsor of a major event or conversely, the event is large enough to retain such a high profile sponsor. The primary objective of this study was to investigate how potential spectators judge the quality of an event based on the sponsor of the event (see Figure 1).

[FIGURE 1 OMITTED]

To ground this purpose, signaling theory is used to examine how consumers process the perceptual connection between the event and the sponsoring firm. "Signaling theory revolves around the judicious use of signals which are consistent with the attainment of a particular and valued attribute that, in the absence of the signal, would be very difficult to unambiguously convey" (Clark, Corwell, & Pruitt, 2009, p. 173). Based on this definition, two important sponsor characteristics are considered to be signals of event quality which could assist organizers when promoting relatively small or obscure events.

Despite the magnitude and expansion of sponsorship spending (see IEG, 2010), not enough is understood about the salient objectives that might affect the overall image of an event prior to experiential consumption. This comes as somewhat of a surprise given the substantive nature of sponsorships as a communication tool in many firms' promotional and marketing budgets (Pope, Voges, & Brown, 2009). This article makes a specific contribution to the sport marketing literature by providing a more complete understanding of the role sponsors play in the perceived image of the event and potential attendance of spectators. The results are of particular importance for event marketers in their selection of corporate partners.

Theoretical Background

Signaling Theory

Since its introduction, signaling theory (Ross, 1977; see also Spence, 1974) has been commonly employed to assess consumer perceptions of quality (Kelley, 1988; Kirmani, 1990; Kirmani & Wright, 1989; Zeithaml, 1988). The theory stipulates that tangible information is provided to consumers through cues which allow them to more easily construct evaluations for relatively unobservable factors (Grau & Folse, 2007), and have emerged when buyers and sellers possess asymmetric information in reference to product quality (Boulding & Kirmani, 1993; Spence, 1974). Most often, sellers possess complete information about the quality of the product, while buyers have incomplete information regarding product quality as they have yet to consume it. Buyers are therefore forced to interpret a variety of messages, most of which are presented as persuasive advertisements.

Most consumers might simply rely on their previous experiences with the seller to gauge product quality, which may not exactly correspond to event management and sponsorships. In the case of some widely recognized and recurring sponsored events, consumers have previously been exposed to the "seller" either in the form of general publicity or perhaps previous event attendance. In these cases, the majority of potential consumers should have a bank of information on which they would rely when forming perceptions about an event. For example, sport events that occur annually in the same city like NASCAR races, Professional Golf Association Tour (PGA TOUR) events, and annual road races (i.e., marathons, triathlons, etc.) are generally attended by spectators who possess an appreciable amount of exposure to messages that presumably send signals of event quality. However, because some events continually change host locations, their respective images may be relatively obscure in the minds of potential consumers. In instances such as these, potential spectators will look for other cues in order to form their impressions of the event.

Gwinner (1997) identified three cues that are used to interpret an event: (1) event type, (2) event characteristics, and (3) individual factors (which he proposed result from the spectators' image or perception of the event). Armed with this knowledge, event organizers may attempt to influence the perceptions of those individuals comprising the desired target market by altering event characteristics such as the venue, the use of professional and/or amateur athletes, the type and size of the event, or the type and size of the sponsors associated with the event. In such instances, organizers employ signaling theory as a "push" method of communication, or a way to communicate intangible benefits that might be gained through the materialist notions of experiential consumption or event attendance (Bird & Smith, 2005). In doing so, event organizers are attempting to make their event more appealing to the desired audience by pushing messages as quality signals to salient consumer groups. Thus, applying signaling theory to a sponsorship provides a way to illustrate that intangible benefits can serve as signals of the event or the sponsoring entity. In addition, by paying attention to credibility when individuals make interdependent decisions based on incomplete information (e.g., about products, services, and/or organizations), signaling theory might clarify the boundaries of such decisions, thereby serving as an indicator of event quality.

Regardless of this alleged pushing effect in the psychological processing strategy of signaling theory, the current study integrated this idea to gain a better understanding of the sponsor's impact on the potential spectators' formation of image perceptions and intent to attend an event. Therefore in the current sponsorship context, a targeted presentation might signal other meanings that would improve processing fluency among the consumers.

Image and Sponsorship

Howard and Crompton (2004) noted that image enhancement is one of five broad benefits desired by corporate sponsors. In the sponsorship exchange relationship, the sponsor typically seeks to leverage its connection to an event in exchange for a financial or in-kind investment (Cliffe & Motion, 2005; Farrelly & Quester, 2003; Howard & Crompton, 2004). Even though only two parties (i.e., the corporate sponsor and the sport property) might actually be involved in such a relationship (although several others may exist), there are nevertheless multiple brand identities or images to consider. Defined as "... the perceptions about a brand as reflected by the brand associations held in consumer memory," Keller (1993, p. 3) suggested that uniqueness, favorability, and strength of the consumer association are vital to building a strong brand image. These consumer associations are formed through several sources including actual product usage or event attendance, as well as through informational sources such as advertising, word-of-mouth, and association with other brands. In sponsorship terms, this association with other brands is especially relevant in serving as signals to a targeted audience, as well as to achieve a balanced partnership. For example, Coca-Cola actively sponsors several global sporting events such as the Olympics, FIFA World Cup, and the Rugby World Cup. By linking their brand with these high profile events, Coca-Cola is signaling to consumers that they are indeed a global brand.

Gwinner's (1997) model underpins this idea by arguing that an event's image is formed from a number of internal and external characteristics. This overall event image then is purported to transfer to the related corporate sponsor because of the emotional attachment the spectator has attributed to a given event. In other words, because corporations often seek to enhance their image by engaging in partnerships with properties that have a similar or better image (Howard & Crompton, 2004; Pracejus, 2004), it is generally accepted that image transfer flows from event to sponsoring brand. This transfer of image idea prompted our interest in the current study (albeit inversely) to consider the relationship of the sponsorship exchange. If corporate sponsors can use the sponsorship platform to signal various messages to a targeted audience, we argue that signaling theory can be employed to send messages about the quality of a product, or in the current study, the quality of an event.

Relatedness of Sponsor and Event

When deciding on what sponsorship opportunities best fit the organization's goals, firms employ many criteria (IEG, 1999). Howard and Crompton (2004) suggested that brand image and target market similarities are two areas requiring special attention when considering property alternatives. As discussed, sponsoring brands attempt to enhance their image by affiliating with specific sport properties. Studies of sponsorship, branding, and endorsements have bolstered the notion of image fit, where high levels of congruence may enhance consumer attitudes toward the sponsors (e.g., Becker-Olsen & Hill, 2006; Keller & Aaker, 1992; Speed & Thompson, 2000). Gwinner (1997) described two types of congruency (i.e., relatedness) between the sponsor and the event. A functional similarity occurs when the sponsoring company's brand is used directly in the event. For example, if a golf equipment manufacturer (e.g., Taylor Made) sponsored a PGA TOUR event, this would be considered a direct functional based similarity. On the other hand, if a watch company (e.g., Rolex) sponsored that same event, this would be considered an image related similarity, based on the prestigious or luxurious image of both the brand and the event.

Many service leaders have embraced this idea and have begun to think more strategically about their sponsoring partners (Becker-Olsen & Hill, 2006). For example, a direct functional similarity creates an environment wherein potential consumers can easily draw an association between the sponsor and the property (Howard & Crompton, 2004). In some cases, however, corporate sponsors do not appear to have either functional or image based similarities with the properties they sponsor. Johar and Pham (1999) noted that relatedness is not simply confined to semantic associations between the event and the sponsor. Rather, additional associations between the event and the sponsor's image and personality should also be considered. These associations (coupled with the sponsor's influence) have the power to predict several possible sponsorship outcomes. With regard to our functionally based similarity proposition, the following hypotheses were generated:

H1a: Sponsor relatedness will significantly and positively influence consumer perceptions of event quality such that a related sponsor will yield higher event quality perceptions.

H1b: Sponsor relatedness will significantly and positively influence consumer perceptions of intentions to attend such that a related sponsor will yield higher intentions to attend.

H1c: Sponsor relatedness will significantly and positively influence consumer perceptions of the sponsor influence such that a related sponsor will yield a higher perceived influence.

H2: The strength of the sponsor's influence will significantly and positively influence perceptions of event quality, attendance intent, advocacy, and community prestige.

Size of the Sponsor

In Gwinner's (1997) model of event image, the size of an event is one of the primary characteristics influencing consumer perceptions of an event. For an event, however, size carries with it various subjective interpretations, which include length/duration, number of participants, amount of physical space required, and the level of media exposure. Likewise, in explaining one of seven psychological mechanisms that consumers may use to process sponsorship relationships, Pracejus (2004, p. 183) put forth the idea of implied size, stating that "... the message of implied size is that 'this company is big." In other words, if a company sponsors a mega-event, such as the Super Bowl or Olympic Games, consumers are likely to interpret such signals to mean that the company is likely very large and successful. While this concept has been implicitly described in the advertising literature (Kirmani, 1990; Kirmani & Wright, 1989), it has yet to be empirically examined in the sponsorship context. In the current study, we operationalized sponsor size as the presence the firm has in the marketplace and argue that this size could impact event perceptions among potential spectators. Consequently, we were more interested in testing the impact of the sponsor's influence on the event rather than the impact of the event on the sponsor. In other words, for consumers, this would mean that "this event is for me" rather than "this company is for me." This idea assisted in the development of the following hypotheses:

H3a: Sponsor size will significantly and positively influence consumer perceptions of event quality such that a national sponsor will yield higher perceptions of event quality.

H3b: Sponsor size will significantly and positively influence consumer intent to attend such that a national sponsor will yield higher intentions to attend.

Method

To test the proposed relationships, a 2 x 2 between-subjects experimental design using multiple analysis of covariance (MANCOVA) was employed. The two manipulated factors (i.e., independent variables) were sponsor size (national vs. local) and sponsor relatedness (functional similarity vs. no similarity). For each significant main effect, we conducted linear contrasts to examine the patterns over the treatment conditions and post hoc regression analyses determined the influence of the manipulated factors on event quality, attendance intentions, advocacy, and perceived community prestige.

The main product was a long-drive competition, a commonly sponsored commodity that was relevant to the participants in the study (i.e., sport management students). The sample (N=167) was drawn from sport management classes at a large research institution and respondents were randomly assigned to one of four treatment conditions. The respondents each received an experimental packet that included marketing materials for the event, a brief description (i.e., scenario) of the event, and information about the title sponsor for the event (see Appendix). After reading the scenario, the respondents were asked to respond to a series of questions. Each group viewed a theme-relevant flyer containing the same event description, with information regarding the event sponsor altered according to the manipulations. Except for the manipulations, the additional aspects of the scenarios were invariant. Cell sizes ranged from 31 to 34 respondents for each of the study manipulations. Additionally, the respondents' previous interest level in golf was entered as a covariate to isolate any effects on the manipulated factors. In terms of demography, 120 (71.4%) of the respondents were male, while 48 (28.6%) were female; and ages ranged from 18 to 33 (M=20.8, SD=2.22).

Manipulations and Measures

Sponsor size (i.e., national vs. local) was represented by two actual firms with national presence (i.e., Chili's and Callaway), and two actual (but local) counterparts of these firms (i.e., a local ethnic restaurant and a local driving range). We defined "national presence" as a firm that competes in multiple markets and has multiple locations, rather than simply restricted to the local area where the study took place. Sponsor relatedness (i.e., functional similarity vs. no similarity) was manipulated through sport-related sponsors and non-related sponsors. For the scenarios, Callaway Golf and Hackers (i.e., a local driving range) were functionally similar, while Chili's and the local restaurant had no functional similarity.

The subjects were asked to respond to a series of single-item measures after reading their assigned scenario. Aaker et al. (2005) maintained that, for decision-making purposes, single items' predictive validity can be equally as valid as multiple-item measures. Rossiter (2002, p. 310-311) argued that single-item measures are sufficient if the construct is such that (in the respondents' mind) it is "concrete singular" and the attribute connected to the construct is "concrete." In other words, if the object can be conceptualized as concrete and singular and the attribute as concrete, it does not require multiple items to represent it in the measure. Based on this information, the study measures were developed in a singular and concrete manner to assuage any concerns regarding the applicability of the single-item measures. Also, since higher level analyses (e.g., structural equation modeling) were not employed, multiple-item measures were not deemed necessary (Bergkvist & Rossiter, 2007).

Event quality perceptions were measured using the item, "what do you think will be the quality of this event?" (1=low quality; 10=high quality). Intent to attend was measured by using the item, "how likely is it that you will attend this event?" (1=not likely to attend; 10=very likely to attend). Sponsor influence was measured using the item, "how did the sponsor of this event influence your answers?" (1=negatively; 10=positively). The relative strength of the sponsor's influence was measured using the item, "how strongly did the sponsor of this event influence your answers?" (1=not at all; 10=very much). As a covariate, the participant's general interest in golf was assessed by asking the respondent to "indicate your general interest level in golf" (1=no interest, 10=much interest). Spectator perceptions of prestige of the event were assessed by asking, "how would you rate this event in terms of prestige for [the city]?" (1=low prestige; 10=high prestige). Finally, advocacy was examined by asking "based on what you know of this event, would you tell your friends about it?" (1=definitely not; 10=definitely).

Results

Manipulation Check

The participants were asked whether the scenario featured either a local or national business to assess the manipulated factor. A significant [chi square] test (p<.001) showed that the participants were able to correctly identify the condition to which they were assigned, demonstrating a successful manipulation of the proximal condition in the analysis (Grau & Folse, 2007). Pre-testing of the manipulations also confirmed that sponsor familiarity and sponsor liking did not influence the results.

Hypothesis Tests

Preliminary data checks were conducted to ensure that there were no violations of normality or linearity, both of which were confirmed. The homogeneity of variances and regression slopes all adequately met this MANCOVA assumption (i.e., Levene's Tests across the three outcomes were greater than .05). As only one covariate was used in the analysis, there was no need to calculate covariate correlations. The equality of covariance matrix revealed no statistical significance (p=.898), thereby supporting the covariate's inclusion in the model. As the results vary across the three dependent measures, the findings for each of these outcomes are reported separately. Individual cell means are presented in Table 1.

Table 2 reports the results from the 2 x 2 between-groups MANCOVA conducted to assess the impact of sponsor relatedness and size on the dependent measures (i.e., event quality, attendance, and sponsor influence). First, an overall test of the model was performed. The MANCOVA revealed significant effects on sponsor relatedness ([F.sub.1, 114] = 4.089; [[eta].sup.2] = .10) and for the covariate interest in golf ([F.sub.1, 114] = 20.108; [[eta].sup.2] = .35), while sponsor size was not a significant factor (i.e., [H3.sub.a,b] were not supported). After determining the overall effects, the univariate analysis of the sponsor relatedness hypotheses were tested. For [H1.sub.a,b,c] differences were found for perceived event quality, attendance intentions, and the nature of the sponsor influence. To more closely examine these differences, pairwise linear contrasts (adjusted for the covariate) were conducted. These contrasts revealed that when compared to sponsors with no similarity, functionally similar sponsors produced a higher commitment to attend ([[bar.[chi square]].sub.related] = 4.91; [[bar.[chi square]].sub.unrelated] = 7.42; a higher perception of overall event quality ([[bar.[chi square]].sub.related] = 7.42; [[bar.[chi square]].sub.unrelated] = 6.61), and a higher perceived sponsor influence ([[bar.[chi square]].sub.related] = 5.23; [[bar.[chi square]].sub.unrelated] = 4.23). The significant results coupled with these contrasts support the related hypotheses. Overall, sponsor relatedness explained 34% of the variance on attendance intent, 9% of the variance on nature of the sponsor influence, and 7% of the variance in assessment of event quality.

In addition to the effect of the manipulations on the outcomes, H2 was concerned with the predictive power of the strength of sponsors' influence on perceptions of event quality, attendance intentions, advocacy behaviors, and perceived community prestige. While not formally hypothesized, we also analyzed whether the covariate significantly influenced the outcomes. Regression analyses revealed significant and positive effects for the strength of the sponsors' influence on the perceptions of event quality, attendance intent, advocacy, and community prestige (see Table 3). These relationships revealed that the more positive perception the respondent had toward a sponsor, the more likely they were to attend or perceive the event as higher in quality. Additionally, the covariate influence of the respondent's interest in golf had a positive and significant influence on attendance, advocacy, and community prestige, while the respondents' perception of event quality was not significantly affected. In sum, this portion of the analysis revealed that a positive sponsor image increased attendance intentions and impacted the strength of the sponsor's influence.

Discussion

While sponsorship has been theorized primarily from an advertising perspective, one of the main outcomes of this research lies in highlighting the role an event can play as part of a positioning strategy. As the predominant advertising perspective has emphasized awareness and image in the sponsorship medium, this positioning proposition suggests that sponsorship also offers experiential opportunities to create meaning linked to the event itself (Cliffe & Motion, 2005). This idea is particularly salient when considering the goal of retention and the consummate need for synergistic alignment with a sponsoring brand. While companies carefully consider how association with specific events will impact their image, little consideration has been paid to the idea that event sponsors may impact consumers' evaluations of an event's image. Only in the case of the "sin industries" of tobacco and alcohol have researchers explored this positioning strategy and subsequent impact (Siegel, 2001). In the current study however, we examined how consumers of events are affected by the sponsor of an event, or stated differently, what type of signals a sponsor of an event sends to potential consumers. We were primarily interested in the role of (1) sponsor relatedness (i.e., fit) with the event and (2) sponsor size as it pertained to the perceptions formed about the event.

The results of this study give rise to a few interesting discussion points, the first of which goes directly to the main thrust of this investigation. Our results suggest that the subjects were more likely to plan attendance to an event and perceive the event as "high quality" when the event was sponsored by a firm with a related product. In the case of this experiment, a long-drive competition was used as the focal event; thus, a sponsor was "related" when it corresponded to the golf industry in some (perhaps even tangential) way. In our experiment, potential spectators were presented with descriptions of a future long-drive competition to be held in their town. Interestingly, the subjects' perceptions were only influenced by the extent to which a sponsor was related to the event, and not by the extent to which to a sponsor was nationally or locally based. Signaling theory helps to elucidate why this was so. This theory suggests that since potential spectators possess asymmetrical information about the event's quality, they instead rely on familiar elements (i.e., relatedness of event sponsor) to estimate event quality and its relative attractiveness. As mentioned, a long-drive competition was used in an experimental design. We should note that this type of event is generally not the most recognized sporting event, and thus potential spectators would not likely have familiar elements on which to base their views of the event. So in this case, the sponsor of the event was the strongest signal about the event. Specifically, the two national sponsors did not have a local presence in the town where the data were collected. As such, it appears that those firms were not as familiar to subjects as the local firms used in the scenarios.

Future researchers could explore this finding in greater detail using additional experimental designs to consider other conditions to which this idea might hold. One suggestion would be to explore whether a sponsorship signal is (in part) contingent upon the size of the city (i.e., the Metropolitan Statistical Area, MSA) in which the event is held. In the parlance of signaling theory, are the messages that are sent to subjects in smaller towns substantively different than those sent to subjects in larger cities? If this is the case, events in smaller towns might need to target different sponsors to attract the most spectators. One caveat here is that the subjects were located in a relatively small city and as such, the idea of a large sponsor over a smaller sponsor may not be particularly palpable. Conversely, the respondents might also be impressed if a national sponsor were involved with an event over a smaller, more regional entity. Future researchers would be commended in this exploration.

Another suggestion for future research would be to manipulate the event's prestige (i.e., status) and test the impact of the sponsor's signals. Some have suggested that prestige can be a vital and active agent in sport, as it is there that its effects are most noticeable compared to other industries (e.g., Andrew et al., 2006; Todd & Kent, 2009). We suggest that the prestige of the event may also send a signal to potential consumers apart from that of the sponsor. In this sense, the results presented in this study may likely only apply to events that are unrecognized by potential spectators; events where the sponsor is positioned to be the best signal of event quality which will drive attendance. Future researchers could then experimentally pit the two signals against one another in an effort to determine which is more effective in yielding positive consumer related outcomes of event quality perceptions, event advocacy, and likelihood of attendance.

Implications

In this study we see that the subjects were more likely to attend, advocate for the event, and report a higher event quality based on a strong sponsor influence. In terms of practical implications, the findings have some fairly straightforward implications for marketers and event managers. For example, the results suggest that the strength of the sponsor's influence can positively impact spectator outcomes. Therefore, event organizers could capitalize on the relative strength of the sponsor through marketing communications geared towards relatedness and size. Similarly to previous work, we show that relatedness should be a key consideration when developing and securing sponsorship deals--especially for lesser known or relatively obscure events. While sponsorships assist in influencing brand and product equity (i.e., for the sponsor and sponsee), the effect on consumer attitudes can be difficult to ascertain. Although high relatedness could (and should) reinforce the overall positioning of the event, it may be only one of the inputs necessary to yield positive consumer reactions to the sponsorship. This carries implications for how persuasion can be exploited, because event consumers could be persuaded differentially based upon our "strength" proposition. Additionally, the results support the anecdotal evidence provided by Parker (1991) and conceptualized by Pracejus (2004) that size of the sponsor may indeed signal strength or equity of a sporting event.

The idea of persuasion has been examined from multiple perspectives (i.e., theoretically and contextually) but Friestad and Wright (1994) were among the first to acknowledge that everyday persuasion knowledge is important in determining how people cope with persuasion attempts. Their model was conceptualized with regards to the tasks required for both the target and the agent. In terms of the target, tasks assist when coping with a persuasion attempt; for the agent, such tasks assist with effectively executing the persuasion attempt (Friestad & Wright, 1994). To offer the proper conceptual perspective, the authors analyzed these tasks in terms of the type of knowledge they required, using the Persuasion Knowledge Model (PKM). This model posits that consumers develop knowledge about persuasion and use this knowledge to "cope" with persuasion episodes (Friestad & Wright, 1994). Kirmani and Campbell (2004) noted that while the targets of persuasion are resourceful participants who have the ability to select response tactics on their own, the extant research has a fairly passive view of the target. This means that individuals may develop context-specific persuasion knowledge because such knowledge applies to situations they infrequently encountered (Friestad & Wright, 1994).

Alternatively, there are persuasion tasks that the population does often encounter (e.g., buying, selling, advertising, and shopping) but a large portion of the research has examined personal relationships (e.g., family and friends) rather than marketplace relationships (e.g., salesperson, company, and consumer; Kirmani & Campbell, 2004). To understand the connections between the domains and the messages directed at these specific domains, it is necessary to take a receiver oriented view of the links among the event, and people's attitudes and behaviors about the message being transmitted. In line with this reasoning, marketers should examine how their event can be used as agents of persuasion to gain further insight into this seemingly complex, but still burgeoning, idea. Such information can be pushed to consumers from various message sources to build impressions of the event or overcome situations of misfit or inappropriateness of the sponsor match. If a receiver oriented perspective is adopted, marketers will be able to more effectively target their messages. This point is particularly germane for the current study because of the potentially biased sample, and constitutes one specific limitation. For example, because most sport management students have more knowledge of sponsorship as a marketing practice, the "persuasion" attempt may have varied somewhat among the participants. As such, the participants may have provided responses that might vary slightly from a general population sample. This limitation nonetheless provides another angle for future research.

Final Thoughts

For years, scholars have examined how elements of sponsorship help the sponsor achieve business objectives of increased sales, brand awareness, new product introduction, and media exposure. There has been limited attention given to the signal a sponsor sends about the event. As such, we present this study as a first step toward understanding the unexplored territory of what the sponsor says to consumers about the quality of the event and how that sponsor sends signals to consumers urging them to attend. The findings of this study present another consideration to event directors who routinely solicit title sponsorships; namely, that not every sponsor will have the same impact on the potential consumers of that event.

Appendix

Sample Stimulus Provided for the Experimental Manipulations

[ILLUSTRATION OMITTED]

[National Sponsor]

"A large national golf organization has decided to host a championship event in [ insert city name]. It will be the National Finals Long Drive Competition taking place on an April weekend in 2010. More than 100 athletes from around the country will travel to compete in this event. This event will be held at a local country club. Callaway Golf has been announced as the official presenting sponsor of this event."

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Matthew Walker, PhD, is an assistant professor in the Department of Tourism, Recreation, and Sport Management at the University of Florida. His research focuses on business strategy with particular emphasis on business ethics and corporate social responsibility.

Todd Hall, PhD, is an assistant professor of sport management in the Department of Hospitality, Tourism, and Family & Consumer Sciences at Georgia Southern University. His research interests cover a variety of research methods and subjects pertaining to sport marketing, most notably regarding employee and consumer perceptions of corporate sponsorship activities as well as sporting event image and personality.

Samuel Y. Todd, PhD, is an associate professor of sport management in the Department of Hospitality, Tourism, and Family & Consumer Sciences at Georgia Southern University. His research interests generally involve people and their work (i.e., their views of work, skills used in the job, attraction to certain jobs, personalities that produce sales, etc.).

Aubrey Kent, PhD, is an associate professor in the School of Tourism and Hospitality Management at Temple University. His research interests include consumer and employee attitudes in sport.

Table 1.
Cell Means for Sponsorship Stimuli

 National Sponsor Local Sponsor

 Unrelated Related Unrelated Related

Cell -1- -2- -3- -4-

Dependent Measures (a)
 Intent to Attend (b) 3.51 4.59 3.70 5.24
 Event Quality (c) 6.75 7.28 6.47 7.56
 Strength of Influence 4.02 5.65 4.49 4.80
 (d)

Note. (a) All measures were on ten-point scales

(b) A higher score indicates more likely to attend

(c) Higher number indicates a higher perception of event quality

(d) Higher number indicates stronger influence from the sponsor

Table 2.
Multivariate Analysis of Covariance
(MANCOVA) Results of Sponsorship Stimuli

 Univariate Results

 MANCOVA Results Event Quality

Variables Wilks' F F Sig.

Sponsor Relatedness .903 4.089 * 5.851 .017 *
Sponsor Size .992 .343 ns ns
Interest in .654 20.11 *** ns ns
 [Golf.sub.covariate]

 Univariate Results

 Sponsor Influence Intent to Attend

Variables F Sig. F Sig.

Sponsor Relatedness 6.841 .017 * 8.942 .003 *
Sponsor Size ns ns ns ns
Interest in 4.905 .029 * 58.06 .000 ***
 [Golf.sub.covariate]

Note. * p<.05; *** p<.001

Table 3.
Regression Coefficients

 Dependent Variables

 Perceived
Independent Variables Attendance Event
 Intentions Quality

Strength of Sponsor Influence .370 *** .196 *
 [R.sup.2] .14 .04
 Adjusted [R.sup.2] .10 .03
 p-value .00 .01
Interest in Golf covariate .511 *** .131
 [R.sup.2] 2 .26 .01
 Adjusted [R.sup.2] .20 .00
 p-value .00 .09

 Dependent Variables

Independent Variables Advocacy Community
 Behavior Prestige

Strength of Sponsor Influence .321 *** .212 **
 [R.sup.2] .10 .05
 Adjusted [R.sup.2] .08 .04
 p-value .00 .00
Interest in Golf covariate .462 *** .188 *
 [R.sup.2] 2 .21 .04
 Adjusted [R.sup.2] .19 .03
 p-value .00 .01

Note. Values are standardized [beta]'s:
* p<.05; ** p<.01; *** p<.001