335

Journal of Sport Management, 2012, 26, 335-349 © 2012 Human Kinetics, Inc.

Wishart is with the Dept. of Marketing, University of Queensland, Brisbane, Queensland, Australia. Lee is with the Dept. of Sport Management, University of Michigan, Ann Arbor, MI. Cornwell is with the Dept. of Marketing, University of Oregon, Eugene, OR.

Exploring the Relationship Between Sponsorship Characteristics and Sponsorship Asking Price

Taryn WishartUniversity of Queensland

Seung Pil LeeUniversity of Michigan

T. Bettina CornwellUniversity of Oregon

Price setting in the sponsorship of sport, charity, arts and entertainment is usually negotiated, and private, so we know little about what determines price. With a sample of publicly available sponsorship proposals, the relationship between sponsorship characteristics and price set by the property is examined. Media coverage and attendance levels are hypothesized to have a positive impact on property price, as are a host of on-site communications. Overall the most influential variable explaining the property’s asking price is media cover-age. In contrast, on-site communications are not important in price setting. Interestingly, access to property offerings such as celebrities and venues has a significant positive impact on property price. While the empirical investigation is limited to the relationship between communication characteristics and asking price, the price negotiation process and property-based characteristics that lead to the final price are also discussed.

Of all the facets of corporate sponsorship that have been examined in the past few decades, pricing of spon-sorship investments has received very little attention. This is for good reason. Pricing decisions are usually negotiated in private. Even in studies of the financial impact of sport sponsorships on corporate share price, price-setting aspects of the sponsorship must be inferred (see for example, Pruitt, Cornwell & Clark, 2004, p. 294). Nonetheless, the prominence of sponsorship in some promotional budgets has increased the need for justification and explanation of price decision-making. Both property and sponsorship managers need to justify price-setting agreements. With this in mind, identifying characteristics of sponsorship that drive pricing is an issue requiring investigation. Thus, this study examines the relationships between sponsorship characteristics and the price offered by the property to potential sponsors. Also explored, but not examined empirically, are the factors that may enter into the negotiation process that ultimately leads to the final price.

Sponsorship Value and Price

The value of sponsorship is largely found in its ability, as a marketing tool, to accrue a wide variety of ben-efits to the sponsoring organization. Benefits identified within the literature may be broken into three types; consumer, employee and corporate benefits (Cliffe & Motion, 2005; Cornwell, 1995). Consumer impact is the most widely studied outcome in the literature (Cliffe & Motion, 2005; Cornwell & Maignan, 1998; Cornwell, Roy, & Steinard, 2001) and the one that properties may most readily address in their sponsorship proposals. When successfully implemented, sponsorship associa-tions have the potential to build brand awareness, and increase affective and behavioral outcomes toward the brand (Cliffe & Motion, 2005; Cornwell, Roy, & Stein-hard, 2001; Cornwell, Weeks, & Roy, 2005; Quester, 1997). Affective outcomes include consumer liking or preference toward the brand or the creation of favorable thoughts toward the brand whereas behavioral outcomes are a consumer’s intention to purchase or actual purchas-ing behavior (Cornwell et al., 2005). These benefits are widely discussed as the objectives of sponsorship and thus may influence price.

Sponsorship has two main corporate outlays (International Events Group, 2005): the rights fee for an event and leverage or money spent to communicate about the sponsorship. An investment is made by the

336 Wishart, Lee, and Cornwell

firm in exchange for the right to associate with the event (Cornwell & Maignan, 1998). This is recognized as the rights fee: the sponsor may use this “right in pursuit of any objective as well as leverage it through any activ-ity” (Polonsky & Speed, 2001, p. 1364). The purchased right may include access to such items as audience and event image or logo. The level of rights fee investment typically determines the nature of sponsor exposure or association for the event.

To communicate the partnership between the brand and the property, a sponsoring firm may leverage a sponsorship by using collateral communications, such as television commercials, to advertise the partner-ship. Leveraging is a fundamental underpinning of sponsorship-linked marketing strategies and Cornwell et al. (2001) found higher levels of leverage result in a perception of differentiation and adding financial value to the brand. Industry reports suggest, on average, orga-nizations invest a dollar on leverage for every dollar spent on sponsorship rights fees (International Events Group, 2005). Activation, an aspect of leverage that focuses on consumer or audience involvement depends on on-site or media platforms that engage participation and interaction (Weeks, Cornwell, & Drennan, 2008). What is spent outside the proposal package is still termed leverage and is not part of sponsorship price setting and as such is not considered directly within the scope of this research. It is, however, the case that sponsorship characteristics may allow for particular leverage and/or activation plans and may be valued for these. The following section discusses these and other characteristics and hypothesizes regarding their influence on price setting by the property.

Conceptual Model and Hypotheses Development

Properties seeking sponsors create and communicate characteristics that they believe represent value to a poten-tial sponsor. A publicly available sponsor solicitation (as is examined here) is therefore an interesting composite picture of what properties expect sponsors will value.

Early research on sponsorship conducted in Australia found a number of hoped-for outcomes of sponsorship engagement including media coverage, improved com-pany and product awareness, client relationships via hospitality, and opportunities for promotional extension that complement public relations and advertising (Scott & Suchard, 1992). An early survey of 70 marketing professionals in Ireland that considered the various audi-ences for sponsorship reported the following ranking of communication opportunities: media coverage, event title designation, entertain guests, exposure to attendees, perimeter advertising, heart of action identification, expo-sure to participants, advertising theme values (Crowley, 1991). This listing of sponsorship characteristics has largely stood the test of time. Naturally, properties in response to market demands, have come to offer what

managers seek for the corporate and brand communica-tions. In putting forward a bundle of offerings, how then does the property manager envision the price?

In a 2001 study of the ways in which sponsorship contributes to brand equity, Cornwell et al. found that managers ranked corporate image, brand image and brand awareness as the top three brand elements developed by sponsorship. While all aspects of sponsorship can develop the elements of image and awareness, they are strongly influenced by media coverage. Especially, for consumer sector companies, media coverage is by far the most important promotional instrument for exploitation purposes (Crowley, 1991, p.18).

In contrast to the “it is all about media coverage” hypothesis, Grohs, Wagner and Vsetecka (2004) argue that mere exposure via media coverage has lost its appeal as more brand managers seek measureable aspects of con-sumer behavior (p. 119). While central goals of sponsor-ship are still seen as awareness and image development, on-site aspects of sponsorship should have an increasingly important role if these aspects are strategically devel-oped. Thus, a fuller conceptualization of how properties see their value and subsequently set sponsorship price should include a measure of those attending and the on-site communications they expect their property to offer. Naturally, on-site communications and media exposure should be related to attendance. Expected or historical figures on attendance is at best a surrogate indicator of the value the sponsor may see in the property but still it is a somewhat concrete number that the property can communicate in a proposal. This thinking is reflected in the conceptual model of Figure 1, where the three major communication-based characteristics of asking price are media coverage, on-site communications and attendance at the event.

Also found in Figure 1 is a short list of items that might be considered in the negotiation process, and could be expected to influence the final negotiated price. At any point in time a unique set of properties and a unique set of sponsors are available to form a relationship. For example, in 2010, after 21 years of naming rights, Fed-eral Express dropped sponsorship of the Orange Bowl. This property was then acquired by Discover Financial Services and will again be unavailable for the four years of the new contract. Aspects of available properties will be more or less attractive to particular sponsors and will influence the final negotiated price. These elements will be discussed in more detail following discussion of the sponsorship proposal characteristics that hypothesized to influence the asking price.

Lastly, it should be noted that Figure 1 includes antecedent variables to asking price. All the character-istics that make up a sponsorship property are naturally antecedent to the asking price for the property. The nature of the offering, the image of the particular property, eco-nomic climate as well as the season of play are just a few characteristics that influence price. If a particular target sponsor were known and a proposal written for them, it

Sponsorship Characteristics and Sponsorship Asking Price 337

Figure 1 — Conceptual Model of Sponsorship Pricing: Determinants of Sponsorship Asking Price Showing Original Relation-ships (Bold Arrows) and Revised Relationships (Dashed Arrows), also shown are Negotiation Process and Final Negotiated Price.

is only logical that some of the variables listed as part of the negotiation process might influence the asking price as well. The empirical investigation presented here is limited to those sponsorship characteristics communicated in a publicly available proposal without a particular targeted sponsor nominated and thus values determined by the relationship between the property and the sponsor are depicted as subsequent to the asking price communicated.

Sponsorship Proposal Characteristics

Media Coverage. Media is defined as “the channels of communication that carry the ad message to target audiences” (Wells, Moriarty & Burnett, 2005, p. 564). This covers such broadcast mediums as television, radio and Internet as well as print media such as newspapers or magazine coverage. Media coverage of an event has been recognized as the primary objective of sponsorship and a key evaluation criterion for sponsorship selection (Tripodi, Hirons, Bednall, & Sutherland, 2003). While media equivalence measures, where brand exposure time in sponsorship was equated with advertising, were

dismissed (Cornwell, 1995; Crompton, 2004) they none-theless became the benchmark measure of sponsorship in many sports. Recently, interest in the social media aspects of sponsorship has come to the fore. The communications opportunities for social media as values to the sponsor come from the sponsor’s subsequent communications if given permission to make contact with the audience. While the property might make communications with their audience on behalf of their sponsors, these kinds of arrangements are not described as such in proposals. Thus, in the current study, media coverage is limited to traditional forms such as TV and radio. Those that generate high reach and frequency such as nation or international coverage maybe more sought after thus affecting the sponsorship rights fee price through demand and supply. In addition, discrepancies exist surrounding the importance of media coverage across sponsorship categories. For instance media communication has been more highly rated in the sports category than the arts cat-egory by managerial decision makers (Crowley, 1991). It, however, was positively rated in both categories as such it is expected to have a positive influence on property price.

338 Wishart, Lee, and Cornwell

H1: Media Coverage Will Have a Positive Impact on Sponsorship Property Price.

On-Site Communication Elements. As sponsorship has become market driven, events of all types have become opportunities for customer engagement. The multifaceted sponsorship proposal offered by the to-be-sponsored property often includes various elements designed to reach different target audiences. A discussion of these site related elements follows.

Hospitality. One of the major determinants of sponsor-ship selection is whether facilities are made available during the sponsorship event to entertain guests (Crow-ley, 1991). Such entertainment facilities could include access to physical facilities during the event, free tickets or admission or the access to celebrities for corporate functions. These aspects have been noted to play an important role within organizations influencing the business community and may be more prominent within sponsorships seeking community awareness rather than mass public exposure (Meenaghan & Shipley, 1999) and are decidedly important to cultural sponsorships (Sylves-tre & Moutinho, 2007). While the presence of corporate hospitality is not expected to be as influential as media exposure in influencing property price, it is still expected to have a positive impact as it is most likely used in a different promotional role to media exposure.

Logo Placement, Branding on People and Heart of Action Identification. One of the primary determi-nants of sponsorship selection is the access to perimeter advertising (Crowley, 1991). Perimeter advertising refers to the amount of logo or branding opportunities offered within the property price contractual agreement. Logo placement and branding of items around the event have the potential to create audience awareness, ultimately influencing affective and behavioral attitudes of these potential consumers (Cornwell et al., 2005). Thus, the more branding opportunities offered to a sponsor, the more likely it is to create positive feelings toward the brand and consumer purchasing intentions.

In addition to communicating about sponsoring brands on the physical space of the sponsored event, it has become commonplace to put sponsor names on volunteer, attendee and participant apparel. Yet another particular aspect of this strategy is heart of action iden-tification. Phrased “heart of action” by Crowley (1991), the concept has been identified as centrality to the event plot in television (Russel & Stern, 2005) and centrality to action within interactive media research (Gupta & Lord, 1998; Schneider & Cornwell, 2005). The overarching idea is to identify the association between the event and the sponsoring brand within a highly visible location such as on the participant’s equipment; thus making the logo highly visible during event action, increasing the chance of audience exposure to the brand. This form of identification, however, is controversial particularly within the sporting category as it has the potential to be seen by the consumer as an overexploitation of the

association between event and sponsor (Meenaghan, 2001). Since it may still be expected to positively influ-ence the level of exposure for sponsors, heart of action logos are hypothesized to have a positive influence on sponsorship property price.

Handout Materials and Customer Interactions. As Ghros et al. (2004) note, events are now being cultivated as places where consumers are able to interact with spon-sors. Although the Internet is replete with companies keen to help sponsors and event organizers develop their materials and customer interactions, there is far little in terms of empirical work that seeks to assess the value of these interactions. While on-site promotion and sampling is evident in collegiate athletic sponsorship objectives (Tomasini, Frye, & Stotlar, 2004) and official programs with sponsor identification are standard in many arts, entertainment, and charity sponsorships, we know little about their potential influence on asking price but can presume that it would be positive.

Access to Property Offerings. A final category included here responds to the rising integration among event sponsorship, leveraging, and celebrity endorsement. After reviewing the works of Diericks & Cool (1989), Hall (1992), and Williams (1992), Fahy, Farrelly and Quester (2004) identify intangible assets including trade-marks, patents, brand reputation, networks and databases in development of a conceptual model of sponsorship-based competitive advantage. They also discussed that key intangible assets in the context of sponsorship should focus on how images are derived from various resources including sports stars, sport leagues and visual arts events, and subsequently represented to the customers. Thus, both access for those images, and databases for commu-nication should be considered as valuable components by sponsors. Further, Bal, Quester and Plewa (2009) discuss that sporting events by nature provide “a rich reservoir of communication opportunities in terms of image, content, stories to be seized by sponsors” (p. 373). They suggest that activation in the contexts of sport venue, event and celebrity are opportunities sponsors can take advantage of as collateral marketing activities. Therefore, access to the images of sport celebrity, venue, event and database of customers for collateral communication activities form a basic category of somewhat latent potential that sponsors may consider in sponsorship investment.

As marketers seek to present a more integrated single story that includes advertising, often featuring the venue and participating celebrities, and to communicate with potential or previous event attendees about their sponsor-ship, what is termed here “access to property offerings,” becomes another type of benefit that the property might offer and that the sponsor might value. In summary, taken together, one would expect these on-site elements to come together as a type of value that might add to or even challenge the contribution of media coverage. The values in this category contrast with more straightforward measures like attendance since they must be actualized by the sponsor.

Sponsorship Characteristics and Sponsorship Asking Price 339

H2: On-Site Communication Elements Will Have a Positive Impact on Sponsorship Property Price.

Exposure to Attendees. Event audiences vary greatly depending on the type of event sponsored, and can fluctu-ate depending on the category. For example, sports events may attract thousands of participants where as an arts event may only attract a few hundred. Interestingly, this factor was ranked among the lowest in importance when making sponsorship decisions in 1991 (Crowley, 1991). This ranking by managers perhaps reflects the fact that attendance per se is not important, rather it is the poten-tial audience or more narrowly still the potential target audience for the sponsor that really matters. In addition, given the recently recognized potential of event venues as places to sample, demonstrate, and essentially engage with the brand, a larger number of attendees are expected to positively impact rights fee since this increases the level of reach and frequency of the sponsorship message and may serve as a signal of event success.

H3: The Degree of Exposure to Participants/Attendance Will Have a Positive Impact on Sponsorship Property Price.Property-Based Characteristics Influencing Price. In addition to straightforward communication character-istics that are readily enumerated by the property in a proposal, there may be a suite of property-based char-acteristics that could contribute to the value of an offer. No matter the communications potential of a property in terms of audience or media coverage, the inherent nature of the property limits the sponsors with which it has a natural or functional fit. Thus, the value of the property to a given sponsor may be based in part in the potential fit of the property to the sponsors needs at the time. Another property-based characteristic that may influence price is the potential to customize activation for a sponsor. Properties like basketball, which have a distinctive half time, offer different possible activations than golf where continuous sport coverage is the norm. Similarly opera and theater have intermissions whereas charity festivals are continuous. Yet another characteristic of the property that may be differently valued by sponsors is their tech-nological sophistication and thus their ability to integrate with processes and systems employed by the sponsor.

Other value determining characteristics of the prop-erty may be relationship-based. For example, Farrelly (2010) identified a number of relationship aspects that may be important to sponsorship success. For potential sponsors, sponsorship experience and management capa-bilities of the property may influence perceived value and related price. The willingness and ability of the property to support or manage sponsorship measurement may also influence price.

Clearly this is only an illustrative list that would be more detailed in any particular negotiation. A host of

additional variables such as timing and the desperation of the property as the event date nears, may sway price. Like-wise, strategic understanding of the sponsoring brand’s perspective, adaptability, and simple congeniality on the part of the property might also play a role. It may also be the case that a property has an emotional or regional con-nection to a potential sponsor that could influence the final price paid. For example, the Microsoft Xbox 360 spon-sorship relationship with the Seattle Sounders, a Major League Soccer team in the Pacific Northwest, aligns with the headquarters location of the sponsor. Similarly, a charity or cause sponsorship that engenders goodwill may be more valued by some potential sponsors. While it is easy to see that these elements may be a consideration in what a sponsor is willing to pay for a property, because they are somewhat relational—depending on the potential partners at a particular time and therefore idiosyncratic, they are difficult to measure. Thus, the current research recognizes the importance of property characteristics beyond those oriented to communication in determining final price but does not include them in this undertaking.

Method

Sample

The sample for this study is sponsorship proposals adver-tised on the Internet. A sponsorship proposal is defined for the purpose of this study as a proposal (in this instance advertised by the property website or broker’s website) outlining the property price required by the sponsor and the characteristics and benefits of the property acquired for this fee. These proposals were attractive as sample for several reasons. First, it is convenient to collect these proposals as complete documents. Second, they have been vetted for public distribution (rather than possibly being developed as a response to a survey inquiry). While the type of sponsorship and the percentage of sponsorship opportunities advertised on the Internet may differ from those advertised through other media such as brokers, or through direct contact with potential sponsors, the lack of exposure and impermeable nature surrounding those opportunities passed from company to company through word of mouth and exclusive deals means accessibility for the general public and outside interested parties is difficult. Thus, it is expected that these proposals are not representative of, in particular, the largest sponsorship properties.

Online sponsorship databases as well as the use of search engines such as Google were used to identify pro-posals. Search terms such as “sponsorship opportunity” or “sponsorship proposal” were used within Google to identify proposals advertised on the event’s websites. A sample of 300 sponsorship proposals was collected from the Internet in a six-month period. Proposals were sought until the quota was filled for the category. The purposive sample sought equal groupings for the sport (N = 100), charity (N = 100), and arts/entertainment (N = 100) categories. Any sport related proposal was considered.

340 Wishart, Lee, and Cornwell

Charity was distinguished as involving a nonprofit ben-eficiary but included a range of activities. Arts/entertain-ment included music, visual, and dramatic arts as well as nonsport entertainment activities such as festivals and while combined for analysis, the separate groups of this category are shown in Table 1 for descriptive purposes only. The use of three categories was to ensure the overall analysis is not weighted by one category’s characteristics. Because the search was conducted in English, several English-speaking countries are represented within the sample, namely; Australia, Canada, New Zealand, United Kingdom, and the United States of America. Of particular note is the dominance of the United States within the sample (46.7%).

For analysis a common metric was needed, thus, an average U.S. exchange rate was taken for the period covered within the sample to reduce volatility across exchange rates. The use of such a range will also provide a safer interpretation of exchange rates for subsequent years as the volatility within the use of a sole average yearly exchange rate is reduced. After the sampling period closed, during analysis, three observations from the arts/entertainment category were deleted due to incomplete information.

Content Analysis

Based on the literature review, the units were placed in mutually exclusive and collectively exhaustive commu-nication instrument groupings. Characteristics identified within sponsorship offerings included: media coverage, logo placement, logo heart of action, branding on people, handouts, customer interactions, hospitality, and access to property offerings. Items were coded for analysis based on the presence or absence of a characteristic, or the frequency of a characteristics offering (see coding variables in Table 2). Coding reliability was tested using two business postgraduate students. A 90% agreement across coders was established and remaining items were

classified following discussion. Other items collected from the analysis of text but not requiring coding included the property price and the number of people attending the event. It should also be noted that some additional variables were initially gathered but then dropped from further analysis. For example, property website presence was originally coded but was essentially ubiquitous and thus offered no variance.

The lack of large property proposals communicated through the Internet impacted the property price range within the sample. While sponsorship property prices may reach $100’s of millions, the highest property price found through our search was less than $1.5 million, suggesting a large discrepancy may exist between these advertised sponsorship proposals and the more elusive sponsorship proposals such as those for the Olympics, the Rugby World Cup, the FIFA World Cup or the PGA Masters. Thus, given that even the quarter of the sample that fell into the top category, “$100,000 and over” was still predominantly between $200,000 and $500,000, the sample represents small and medium sized sponsorship proposals. The attendance ranges also declare the small to medium size nature of this sample. Over half the spon-sorship proposals claimed attendance levels under 5,000 (54.5%), more than a quarter of the sample was medium in size (27%, 5,000–50,000) and the final grouping was over 50,000 attendees (17.8%).

Structural Equation Modeling

Structural equation modeling (SEM) is used to determine the relationship between sponsorship communication-based characteristics and asking price. Key assump-tions of MLE are large sample and multivariate normal distribution in indicator variables and latent variables. One variable ‘sponsorship asking price’ was found to be strongly skewed and kurtotic (skew 5.080, kurtosis 40.142). Therefore, a natural log was taken to trans-form the variable, ‘property price’ and ensure it was

Table 1 Sample Characteristics

Country of Origin Arts Entertainment Sport Charity Total

United States 9 39 27 65 140

Australia 15 9 32 16 72

United Kingdom 16 9 30 11 66

Canada 3 4 9 16

New Zealand 0 0 6 0 6

Total 100 100 100 300

Sponsorship Size Arts Entertainment Sport Charity Total

Under $20,000 6 24 21 47 98

$20,000—$99,999 18 26 44 40 128

$100,000 Plus 16 10 35 13 74

Total 100 100 100 300

Sponsorship Characteristics and Sponsorship Asking Price 341

appropriate for the analysis. After log-transformation, skew and kurtosis reduced to -.255 and -.431 respectively. This approach for handling skewed variables is as identi-fied by Hair, Anderson, Tatham, & William (1998). Table 3 shows the means, standard deviations, and normality of the variables.

Results

Measurement Model of On-site Communication

To measure the latent variable, on-site communication, which is conceptualized to affect the sponsorship asking

price, the dependent variable, we conducted a confirma-tory factor analysis based on the correlation matrix of antecedent variables in Table 4. Table 5 shows the result of the confirmatory factor analysis. As shown in Table 5, six of seven indicators including logo heart of action, branding on people, logo placement, handouts, customer interactions and hospitality consistently load on one common factor.

On the other hand, the confirmatory factor analysis shows that only ‘access to property offerings’ loads on an independent factor. Reviewing this variable, it has charac-teristics (e.g., access to celebrities and images that may be included in advertising) that place it chronologically ante-cedent to media coverage. In addition, direct marketing

Table 2 Coding of Variables

Category Coding Scale Type

Sponsorship Asking Price

Dollar value of rights fee price Metric

Attendance at Event Dummy variable coding for number of people attending, low (below 5,000), medium (5,000–50,000), high attendance (more than 50,000).

Ordinal

Media Coverage Dummy variable coding for type of media exposure, no coverage, local, national or international coverage.

Ordinal

Logo Placement Sum of logo placements offered throughout the event excluding heart of action. Any number.

Metric

Logo Heart of Action Sum of logo placements offered within heart of action. Any number Metric

Branding on People Presence or absence of branding offered on volunteer and give away apparel, total out of two.

Metric

Handouts Sum of different handout types offered. Metric

Customer Interactions Presence or absence of booth, sampling opportunity, sampling within bag. Summed to possible total of 3.

Metric

Hospitality Presence or absence of tickets, discounts, corporate hospitality, catering total, apparel, networking opportunity, employee benefits. Sum out of 7

Metric

Access to Property Offerings

Presence or absence of accessibility to celebrities, venue, event image for advertising, database of customers. Sum out of 4.

Metric

Table 3 Assessment of Normality and the Means and Standard Deviations of the Variables

Variable Min Max Skew C.R. Kurtosis C.R.

Access to Property Offerings .000 2.000 .883 6.214 -.215 -.758

Attendance at Event 1.000 3.000 .732 5.151 -.938 -3.301

Media Coverage .000 3.000 .699 4.917 .269 .945

Logo Heart of Action .000 7.000 2.384 16.775 8.743 30.756

Branding on People .000 2.000 1.385 9.742 .873 3.072

Logo Placement .000 11.000 1.470 10.343 3.297 11.599

Handouts .000 7.000 2.062 14.506 5.461 19.212

Customer Interactions .000 3.000 .428 3.014 -.897 -3.154

Hospitality .000 7.000 .455 3.202 -.388 -1.363

Sponsorship Asking Price 6.551 14.177 -.255 -1.794 -.431 -1.515

Multivariate 21.359 11.880

342 Wishart, Lee, and Cornwell

made possible by access to database of potential custom-ers makes it a possible direct and different contributor to sponsorship property price. Given the exploratory nature of this first study of pricing, we revised our model to include this rogue variable rather than dropping it from further analysis. Thus, in the revised model access to property offerings is an independent variable proposed to affect media coverage and sponsorship property price in the structural equation model. To test the measure-ment model of ‘on-site communication’ including those six variables identified as loading together, a composite confirmatory factor analysis was used. The following fit indices were considered: the chi-square per degree of freedom ratio (χ2/df = 8.506/9 = .945), Comparative Fit Index (CFI)=1.000, Incremental Fit Index (IFI)=1.011, Turker-Lewis Index (TLI)=1.020, and Root Mean Square Error of Approximation (RMSEA)= .000. These indices indicated a good model fit of measurement model of on-site communication.

Structural Equation Model: Overall Model

Figure 2 shows the overall structural equation model including all the three categories of sponsorship: sport, charity, and arts/entertainment. It explains the sponsor-ship asking price based on media coverage, attendance, and communication-based characteristics. The following fit indices including the chi-square per degree of free-dom ratio (χ2/df = 43.208/34 = 1.271), the Root Mean Square Error of Approximation (RMSEA = 0.030), and the Comparative Fit Index (CFI= .930), Incremental Fit Index(IFI= .935) an, Turker-Lewis Index (TLI= .907) were used to examine model fit. A chi-square per degree of freedom ratio (χ2/df) in the range of 2–3 indicates acceptable fit (Carmines & McIver, 1981). A ratio less than 2 of χ2/df ratio represents a good fit (Byrne, 1989). RMSEA values less than .05 indicate that a model has good fit (Steiger, 1990) and RMSEA values of 0.8 or less indicate acceptable fit. CFI close to 1 indicates a good fit (Bentler, 1990) and CFI of .930 indicates that 93% of the covariation in the data can be reproduced by the given model. Based on examination of these criteria, we conclude that this model fits the data.

Hypotheses Testing

The structural equation model (Figure 2) shows the structural relationship between various communication characteristics and sponsorship asking price. In Table 6, measurement equations with standard errors and test statistics show that media coverage has the largest impact on property price (standardized regression path coefficient = .269, critical ratio = 5.973, p < .001). This model supports H1 that media coverage has a positive impact on sponsorship property price. Interestingly, however, the latent variable, on-site communication, measured by six indicator variables does not have a significant relationship with property price (standard-ized regression path coefficient = .079, critical ratio= .947, p = .344). Thus, H2 is not supported. On the other

Table 4 Correlation Matrix of Variables

Variables 1 2 3 4 5 6 7 8 9 10

1. Sponsorship Asking Price -

2. Attendance at Event .184** -

3. Logo Placement .075 .076 -

4. Logo Heart of Action -.04 -.04 .181** -

5. Branding on People .006 -.03 .117* .167** -

6. Handouts .044 -.06 .058 .157** 0.09 -

7. Access to Property Offerings .260** .079 .063 .066 0 .09 -

8. Media Coverage .328** .061 -.06 -.08 .05 -.03 .328** -

9. Hospitality .075 .021 .129* .089 .135* .11 .179** .115* -

10.Customer Interactions .115* .099 .129* .017 .163** .08 .03 .075 .08 -

Note. * p<.10, ** p<.05,

Table 5 Confirmatory Factor Analysis for On-site Communication

Component Matrix

Component

1 2

Logo Heart of Action .535 -.063

Branding on People .530 -.438

Customer Interactions .407 -.408

Logo Placement .528 -.167

Handouts .456 .158

Access to Property Offerings .344 .721

Hospitality .534 .375

a. Extraction Method: Principal Component Analysis.

b. 2 components extracted.

343

Figure 2 — Overall Structural Equation Model of the Relationships Between Sponsorship Communication-based Characteristics and Sponsorship Asking Price Covering all the Categories of Sponsorships. N = 297, c2 =43.208, degree of freedom = 34, c2/df = 1.271, p = 1.134, CFI= .930, IFI= .935, TLI= .907, RMSEA= .030, R-square for DV= .16. Solid lines represent, respectively, statistically significant (p < .05) and dashed line represents nonsignificant at the significance level of a= .05.

hand, access to property offerings has significant posi-tive impact on sponsorship asking price (standardized regression coefficient = .154, critical ratio = 2.716, p = .007). In addition to this direct effect, we investigate a mediated relationship between access to property offer-ings and asking price.

This partial mediation effect is calculated by multi-plication of two standardized coefficients; .328 on path from ‘access to property offerings’ to ‘media coverage’ and .269 on path from ‘media coverage’ to ‘investment.’ We conducted the Sobel Test to test significance of this mediation effect by the formula (z-value = a*b/sqrt(b2*Sa

2

344 Wishart, Lee, and Cornwell

+ a2*Sb2) drawn from Mackinnon and Dwyer (1993) and

from Mackinnon, Warsi and Dwyer (1995). This media-tion effect is statistically significant (standardized regres-sion coefficient =.088, critical ratio = 3.716, p < .001). That is, due to the mediation effect via media coverage, when access to property offerings goes up by 1 standard deviation, asking property price goes up by .088. This is in addition to any direct effect that access to property offerings has on asking property price.

Lastly, we can see that event attendance has a statistically significant positive impact on asking price (standardized regression coefficient = .155, critical ratio = 2.9, p = .004), as shown in Table 6. This supports H3 that the degree of exposure to participants/attendance will increase the rights fee price. Admittedly, the R-square for the dependent variable, sponsorship asking price is relatively low with only 16% of variance explained. There are several possible reasons why explanatory power is not better. Firstly, properties, especially small and medium ones, may view goodwill or community relations derived from the sponsorship as a central value. Another possibility is that properties anticipate a round of negotiations as outlined in the conceptual model and thus mark the price up so to have room for bargaining. Yet another explanation for the relatively low explanatory power of the empirical model is that properties tend to make an ambit claim that is in part wishful thinking. It is also possible that some additional variables important in setting the property price could be missing in the current structural model. This is discussed further in the section of limitations and suggestions for future research.

In summary, we can see that media coverage has the largest impact on sponsorship property price compared with attendance and on-site exposure (including: logo heart of action, branding on people, logo placement, handouts, customer interactions, and hospitality) across the areas of sponsorship. Second, on-site exposure as measured by the six indicators does not have statistically

significant impact on sponsorship property price. Third, and very interesting in terms of new and unexpected findings is that access to property offering separate from the measure of on-site exposure has significant direct and indirect (via media coverage) influence on property price. Naturally, a question not answered by this overall model is if the characteristics influencing property price differ across sponsorship categories.

Exploring Category DifferencesThe three sponsorship categories, sports, arts/entertain-ment, and charity differ in terms of price. Sport spon-sorships were higher in property price than charity and arts/entertainment sponsorship (Chi-square (4, N = 297) =18.176, p = .001). In addition, the arts/entertainment category is significantly different from charity in terms of higher price (Chi-square (2, N = 197) =6.872, p = .032). For this reason and for economy of presentation, we con-sider a multigroup comparison by sponsorship category. Analyses of these models follow the same procedure as with the overall model and the results are shown in Figure 3 and Table 7. Given the small sample sizes of the subcategories and the exploratory nature of the study, results at the .10 level are discussed as significant.

Model for the Sport Sponsorship Category. Breifly, the sport model is similar to the overall model (Figure 2), except for the different composition of on-site communi-cation. Only three indicators: branding on people, logo placement and hospitality load on on-site communication for sport. In the sport model shown in Figure 3, the impact of attendance increased sport model. Again in this model, on-site communications do not significantly impact price. Yet, access to property offerings, as in the overall model, has significant impact on property price and this relation-ship is significantly mediated by media coverage. Further, we find the R-square for the dependent variable increased from .16 in the overall model to .22 in the sport model.

Table 6 Overall Model Measurement Equations with Standard Errors and Test Statistics

PathUnstandardized

EstimateStandardized

Estimate S.E. C.R. p-value

Media Coverage ← Access to Property Offerings .455 .328 .08 5.97 <.001

Sponsorship Asking Price ← Media Coverage .493 .269 .10 4.75 <.001

Sponsorship Asking price ← Access to Property Offerings .391 .154 .14 2.72 .01

Sponsorship Asking price ← Attendance at Event .301 .155 .10 2.9 <.001

Hospitality ← On-site Communication .314

Customer Interactions ← On-site Communication .525 .279 .23 2.32 .02

Handouts ← On-site Communication .621 .283 .27 2.34 .02

Logo Placement ← On-site Communication 1.497 .379 .57 2.62 .01

Branding on People ← On-site Communication .494 .401 .19 2.66 .01

Logo Heart of Action ← On-site Communication .724 .375 .28 2.61 .01

Sponsorship Property Price ← On-site Communication .246 .079 .26 .95 .34

Sponsorship Characteristics and Sponsorship Asking Price 345

Model for the Charity. Following a similar approach, Figure 3 also shows the structural equation model for the charity category. Notably, the significant composite indicators of on-site communication for the charity cat-egory are relatively inclusive with logo heart of action, branding on people, logo placement, handouts, customer actions and hospitality. Despite charities having a mul-tifaceted on-site composition, this variable still does not

influence price setting. Access to property offerings has a significant impact on both media coverage and sponsor-ship property price. Interestingly, attendance at event is not significant factor determining sponsorship property price in the charity category. The R-square for this model drops to .11 from .16 in the overall model. Clearly, we do not explain as much about what determines price for charity as we do about sport.

Figure 3 — Structural Equation Model of Multi-Group Analysis by Sponsorship Category (Sport, N = 100; Charity, N = 100; Arts/entertainment, N = 97). c2 =131.42, degree of freedom = 102, c2/df = 1.288, CFI= .813, IFI= .845, TLI= .917, RMSEA= .031. Top coefficients are for sport category, middle for charity category and bottom for arts/entertainment category. Bold font represents statistical significance at the a= .10 level (p < .10).

346

Table 7 Multi-Group Comparison by Category (Chi-square/DF = 131.427/102 = 1.288, CFI=.813, IFI=.845, RMSEA=.031)

Sport category (N = 100) R-square =22% Estimate S.E. C.R. P Std. Estimate

Media Coverage ← Access to Property Offerings .470 .146 3.223 .001 .308

Sponsorship Asking Price ← Media Coverage .427 .133 3.222 .001 .302

Sponsorship Asking Price ← Access to Property Offerings .347 .202 1.716 .086 .161

Sponsorship Asking Price ← Attendance at Event .486 .166 2.919 .004 .260

Hospitality ← On-site Communication 1.000 .541

Customer Interactions ← On-site Communication .128 .154 .830 .407 .116

Handouts ← On-site Communication .008 .123 .067 .947 .009

Logo Placement ← On-site Communication 1.160 .486 2.388 .017 .519

Branding on People ← On-site Communication .380 .159 2.391 .017 .513

Logo Heart of Action ← On-site Communication .282 .197 1.428 .153 .212

Sponsorship Price ← On-site Communication -.060 .207 -.289 .773 -.035

Charity (N = 100) R-square =11% Estimate S.E. C.R. P Std. Estimate

Media Coverage ← Access to Property Offerings .310 .094 3.295 .001 .314

Sponsorship Asking Price ← Media Coverage .589 .312 1.888 .059 .189

Sponsorship Asking Price ← Access to Property Offerings .601 .307 1.953 .051 .195

Sponsorship Asking Price ← Attendance at Event -.159 .207 -.770 .441 -.073

Hospitality ← On-site Communication 1.000 .381

Customer Interactions ← On-site Communication .443 .237 1.867 .062 .286

Handouts ← On-site Communication 1.503 .575 2.617 .009 .661

Logo Placement ← On-site Communication 1.061 .439 2.414 .016 .454

Branding on People ← On-site Communication .503 .204 2.460 .014 .476

Logo Heart of Action ← On-site Communication .567 .258 2.198 .028 .374

Sponsorship Asking Price ← On-site Communication .209 .321 .651 .515 .079

Arts and Entertainment (N = 97) R-square =10% Estimate S.E. C.R. P Std. Estimate

Media Coverage ← Access to Property Offerings .176 .092 1.902 .057 .191

Sponsorship Asking Price ← Media Coverage .812 .271 2.992 .003 .293

Sponsorship Asking Price ← Access to Property Offerings .031 .250 .123 .902 .012

Sport category (N = 100) R-square =22% Estimate S.E. C.R. P Std. Estimate

Sponsorship Asking Price ← Attendance at Event .176 .167 1.054 .292 .101

Hospitality ← On-site Communication 1.000 .032

Customer Interactions ← On-site Communication .300 1.007 .298 .766 .017

Handouts ← On-site Communication 3.581 5.695 .629 .530 .169

Logo Placement ← On-site Communication 4.380 7.227 .606 .544 .094

Branding on People ← On-site Communication 1.537 2.449 .628 .530 .160

Logo Heart of Action ← On-site Communication 27.754 82.595 .336 .737 1.890

Sponsorship Asking Price ← On-site Communication -1.788 3.088 -.579 .563 -.065

Sponsorship Characteristics and Sponsorship Asking Price 347

Arts and Entertainment Category. Following the same approach, Figure 3 also shows the structural equation model for the arts/entertainment category. Very interest-ingly, there is no significant composite indicator of on-site communication for the arts/entertainment category. In addition, access to property offerings does not have a significant impact on sponsorship property price directly in the arts/entertainment category and this is different from both the sport and charity categories. Access to property offerings does have a significant impact on sponsorship property price but only via media coverage. The R-square for this model drops to .10 from .16 for the overall model. Of the three, this category comes the closest to being in keeping with the “it’s all about media coverage” hypothesis previously mentioned.

Discussion and ImplicationsAn important contribution of this study is to demonstrate empirically that media coverage is an important factor in setting sponsorship property price even in these small and medium sized sponsorship proposals. In fact, the received wisdom and manifest practices by sponsors has always been that media coverage was important part in the purchase of sponsorship rights. This is, however, the first study to attempt to explore this relationship empirically. Since the empirical work only captures asking price, it is possible that the negotiated price would place even more emphasis on media coverage.

A second serendipitous contribution of this research is to offer empirical support for the importance of access to property offerings such as celebrities and star play-ers and potential customer databases when considering sponsorship right fees. Properties appear to expect that accessibility to celebrities, access to the venue, event images, and customer databases offer value to potential sponsors. When one thinks, for example, of social media marketing that may be launched via property customer contact, or of the communications potential of celebrities and images, it is easy to see how access to these assets influences asking price. While there has been research to suggest that the use of celebrities generates publicity and attention from the public in advertising (Ohanian, 1991) the antecedent nature of this relationship to media coverage deserves more exploration.

Based on the literature review, it was conceptualized that on-site exposure, measured by logo placement, logo heart of action, branding on people, handouts, customer interactions, hospitality, and access to property offerings would have a positive influence on the rights fee price. The result, however, suggest that in this database of small and medium sponsorships, on-site communication does not have any significant impact on price setting. This discrepancy reflects that while most on-site communica-tions might play a role as basic or required event activities for attendees in sponsorship events, they do not drive

sponsorship rights fee directly. Thus, this suggests that event organizers may have an opportunity to enhance the roles and values of on-site communication components to corporate sponsors, particularly if they relate in some way to the nature and extent of media coverage. Finally, this study suggests that sports sponsorship differs from charity and arts/entertainment sponsorships in terms of the role of attendance at event as well as the components of on-site exposure. For example, attendance is not a significant factor to determine the sponsorship asking price in the charity and arts/entertainment categories.

Limitations and Suggestions for Future Research

The main limitation of this research is in the generaliz-ability of findings. The sample was exclusively comprised of sponsorship proposals advertised on the Internet. Therefore, the results may only be generalized to this sub-section of the overall sponsorship proposal population. Large-scale sponsorship such as the Olympics and the World Cup soccer games may have different price drivers. A corollary shortcoming of the research is the fact that only the property’s preferred value for the opportunity is used as the dependent variable. As mentioned previously, the negotiated price that sponsors actually pay for proper-ties will likely be very different. In negotiation, elements might be added or dropped and the price might change to better reflect valued communication components. In addition, barter, or the supply of goods and services by the sponsor to the property might influence the negoti-ated value.

Another area for possible critique is the coding deci-sions and the grouping of sets of characteristics. A larger study might be able to break some of these categories apart and learn more about which particular communica-tions items are valued. We also are guilty of being led in part by the data rather than theory but to explore this topic and better understand unexpected relationships was the overriding goal. In sum, this study offers a first step in the study of sponsorship pricing, with many more in need.

The research might also be criticized for the relatively low R-square of 16% for the sponsorship property price with limited number of antecedents mainly focused on media coverage, attendance at event and on-site com-munication elements. While the model explained more about relationships in the sport category, the fact that several of the relationships, such as media coverage and access to property offerings held across categories was compelling. Admittedly, some “soft” variables that might explain the variance of the sponsorship asking price are not included. As mentioned, goodwill, community relations or emotional connection to the event may be attractive to sponsors who seek to build emotional rela-tionship for affective attitude and purchase behavior from

348 Wishart, Lee, and Cornwell

consumers (Meenahan, 2005); but are naturally difficult to measure. Our source for what the property offered was their proposal and while we could have added a dummy variable coded for the promise of an emotional connec-tion we would not know the nature of what was delivered. Moreover, the variable would have lacked variance since almost all properties, charity or not, claim some sense of emotion, passion, or community. Not being able to capture the emotional value of a property might have reduced the R-square. This is an area for future research and might be addressed with a qualitative study that utilizes interviews.

Another obvious future research direction is the study of a representative sample sponsorship proposals, or better yet, sponsorship contracts. This might be cross-sectional or it might start with the analysis of sponsorship proposals accepted by a single organization over time. This would provide a more specific outline to managerial decision makers of the characteristics of proposals within the consideration set as well as feedback concerning their decisions.

Clearly, the topic of access to property offerings is an area of unexpected future potential. The fact that this variable was significant in all models means that it may be of interest across sponsorship categories. Given that we measured the construct by summing the four differ-ent elements (e.g., access to celebrities, access to the venue, use of event image for advertising, and access to customer database), we do not examine the unique impact of each element. Different elements appeared across sponsorships and in differing combinations. These strategic combinations were too varied to examine with the current data. Future research might investigate how the specific individual element of the construct can influence the property price. For example, in terms of celebrity endorsement it opens new questions regarding celebrity value to an integrated marketing platform. It also opens new research questions regarding the value of shared databases. Also in need of future research is the role that on-site communications play. While they do not appear to drive asking price, this does not mean that they are not important or even an essential basic compo-nent. If an element becomes expected then it may not be something that sets a property apart but it also may not be something that can be cut from the proposal. Finally, it seems that there is reason to investigate the differences between sport and other areas of sponsorship and perhaps between different sports to determine the best mix of communication components for the property to offer. Is it the nature of the events that drives the difference or is it tradition and habit? This begs the question of best practice in the proposal and implementation of communications surrounding sponsored events.

Research on pricing is at a fledgling stage, nonethe-less, managers making or reviewing proposals should find these results interesting, as should property managers when they are setting asking price. The conceptual model of sponsorship pricing is a useful starting point for under-standing both the communication-based characteristics of price and the property-based characteristics.

ReferencesBal, C., Quester, P., & Plewa, C. (2009). Event-related emotions:

A key metric to assess sponsorship effectiveness. Journal of Sponsorship, 2(4), 367–378.

Bentler, P.M. (1990). Comparative fit indices in struc-tural models. Psychological Bulletin, 107, 238–246 10.1037/0033-2909.107.2.238. doi:10.1037/0033-2909.107.2.238

Byrne, B.M. (1989). A primer of LISREL: Basic applications and program for confirmatory factor analytic models. New York: Springer-Verlag.

Cliffe, S.M., & Motion, J. (2005). Building contemporary brands: A sponsorship-based strategy. Journal of Business Research, 58, 1068–1077 10.1016/j.jbusres.2004.03.004. doi:10.1016/j.jbusres.2004.03.004

Carmines, E.G., & McIver, J.P. (1981). Analyzing models with unobserved variables: Analysis of covariance structures. In G.W. Bohrnstedt & E.F. Borgatta (Eds.), Social measure-ment: Current issues (pp. 65–115). Beverly Hills, CA: Sage Publications.

Cornwell, T.B. (1995). Sponsorship–linked marketing develop-ment. Sport Marketing Quarterly, 4(4), 13–24.

Cornwell, T.B., & Maignan, I. (1998). An international review of sponsorship research. Journal of Advertising, 27(1), 1–21 Retrieved from http://www.jstor.org/stable/4189056.

Cornwell, T.B., Roy, D.P., & Steinhard, E.A. (2001). Explor-ing managers’ perceptions of the impact of sponsorship on brand equity. Journal of Advertising, 30(20), 41–51 Retrieved from http://www.jstor.org/stable/4189177.

Cornwell, T.B., Weeks, C.S., & Roy, D.P. (2005). Sponsorship-linked marketing: Opening the black box. Journal of Advertising, 34(2), 21–42 Retrieved from http://proquest.umi.com.proxy.lib.umich.edu/pqdweb?did=864975461&Fmt=7&clientId=17822&RQT=309&VName=PQD.

Crompton, J.L. (2004). Conceputalization of alternate operationalizations of the measurement of spon-sorship effectiveness in sport. Leisure Studies, 23(3), 267–281 10.1080/0261436042000183695. doi:10.1080/0261436042000183695

Crowley, M.G. (1991). Prioritising the sponsorship audience. European Journal of Marketing, 25(11), 11–21 10.1108/EUM0000000000628. doi:10.1108/EUM0000000000628

Diericks, I., & Cool, K. (1989). Asset stock accumulation and sustainability of competitive Advantage. Management Science, 35, 1504–1511. doi:10.1287/mnsc.35.12.1504

Fahy, J., Farrelly, F., & Quester, P. (2004). Competitive advantage through sponsorship: A conceptual model and research propositions. European Journal of Marketing, 38(8), 1013–1030. doi:10.1108/03090560410539140

Farrelly, F. (2010). Not playing the game: Why sport sponsor-ship relationships break down. Journal of Sport Manage-ment, 24, 319–337.

Grohs, R., Wagner, U., & Vsetecka, S. (2004). Assessing the effectiveness of sport sponsorships- an empirical examina-tion. Schmalenbach Business Review, 56, 119-138. Retrieved from http://public.univie.ac.at/fileadmin/user_upload/private_seiten/srnkak6/Dokumente/SBR2004Grohsetal.pdf

Gupta, P.B., & Lord, K.R. (1998). Product placement in movies: The effect of prominence and mode on audience recall. Journal of Current Issues and Research in Advertising, 20(1), 47–59. doi:10.1080/10641734.1998.10505076

Hair, J.F., Anderson, R.E., Tatham, R.L., & William, C. (1998). Multivariate data analysis (5th ed.). New Jersey: Prentice-Hall.

Sponsorship Characteristics and Sponsorship Asking Price 349

Hall, R. (1992). The strategic analysis of intangible resources. Strategic Management Journal, 13, 135–144. doi:10.1002/smj.4250130205

International Events Group. (2005). 06 Outlook: Sponsorship growth back to double digits. IEG Sponsorship Report, 24(24), 4–5.

MacKinnon, D.P., & Dwyer, J.H. (1993). Estimating medi-ated effects in prevention studies. Evaluation Review, 17, 144–158 Retrieved from http://www.public.asu.edu/~davidpm/classes/publications/1993EvaluationReview.pdf. doi:10.1177/0193841X9301700202

MacKinnon, D.P., Warsi, G., & Dwyer, J.H. (1995). A simulation study of mediated effect measures. Multivariate Behavioral Research, 30(1), 41–62 10.1207/s15327906mbr3001_3. doi:10.1207/s15327906mbr3001_3

Meenaghan, T. (2005). Evaluating sponsorship effects. In T.B. Cornwell & J. Amis (Eds.), Global Sports Sponsorship (pp. 243–264). Oxford, UK: Berg Publishers.

Meenaghan , T. (2001) . Unders tand ing sponsor-ship effects. Psychology and Marketing, 18(2), 95–122 10.1002/1520-6793(200102)18:2<95:AID-M A R 1 0 0 1 > 3 . 0 . C O ; 2 - H . d o i : 1 0 . 1 0 0 2 / 1 5 2 0 -6793(200102)18:2<95::AID-MAR1001>3.0.CO;2-H

Meenaghan, T., & Shipley, D. (1999). Media effect in com-mercial sponsorship. European Journal of Market-ing, 33(3/4), 323–347 10.1108/03090569910253170. doi:10.1108/03090569910253170

Ohanian, R. (1991). The impact of celebrity spokespersons’ perceived image on consumers’ intention to purchase. Journal of Advertising Research, 31(1), 46–53.

Polonsky, M.J., & Speed, R. (2001). Linking sponsorship and cause related marketing: Complementarities and conflicts. European Journal of Marketing, 35(11/12), 1361–1385 10.1108/EUM0000000006484. doi:10.1108/EUM0000000006484

Pruitt, S.W., Cornwell, T.B., & Clark, J.M. (2004). The NASCAR phenomenon: Auto racing sponsorships and shareholder wealth. Journal of Advertising Research, 44(3), 281–296 10.1017/S0021849904040279. doi:10.1017/S0021849904040279

Quester, P. (1997). Awareness as a measure of sponsorship effec-tiveness: the Adelaide Formula One Grand Prix and evi-dence of incidental ambush effects. Journal of Marketing

Communications, 3(1), 1–20 10.1080/135272697346014. doi:10.1080/135272697346014

Russel, C.A., & Stern, B.B. (2005). Product placement effects: Product character associations (PCA’s) in sitcoms. Advances in Consumer Research. Association for Con-sumer Research (U. S.), 32(1), 233–235.

Schneider, L.P., & Cornwell, T.B. (2005). Cashing in on crashes via brand placement in computer games. International Journal of Advertising, 24(3), 321–343.

Scott, D.R., & Suchard, H.T. (1992). Motivations for Australian expenditure on sponsorship-an analysis. International Journal of Advertising, 11, 325–332.

Steiger, J.H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research, 25(2), 173–180 10.1207/s15327906mbr2502_4. doi:10.1207/s15327906mbr2502_4

Sylvestre, C.M., & Moutinho, L. (2007). Leveraging associations: The promotion of cultural sponsor-ships. Journal of Promotion Management, 13(3-4 ) , 2 8 1 – 3 0 3 1 0 . 1 0 8 0 / 1 0 4 9 6 4 9 0 8 0 2 3 0 8 4 9 7 . doi:10.1080/10496490802308497

Tomasini, N., Frye, C., & Stotlar, D. (2004). National collegiate athletic association corporate sponsor objectives: Are there difference between divisions I-A, I-AA, and I-AAA? Sport Marketing Quarterly, 13, 216-226. Retrieved from http://www.fitinfotech.com/smqEletricVersion/SMQpdf/TomasiniWeb1304-370.pdf

Tripodi, J.A., Hirons, M., Bednall, D., & Sutherland, M. (2003). Cognitive evaluation: Prompts used to measure sponsor-ship awareness. International Journal of Market Research, 45(4), 435–455 Retrieved from http://www.premiership.com.au/pdf/Cognitive%20Evaluation %20Sponsor-ship%20-%20IJMR.pdf.

Weeks, C.S., Cornwel, T.B., & Drennan, J.C. (2008). Lever-aging sponsorships on the Internet: Activation, congru-ence, and articulation. Psychology and Marketing, 25(7), 637–654 10.1002/mar.20229. doi:10.1002/mar.20229

Wells, W., Moriarty, S., & Burnett, T. (2005). Advertising: Principles and practice. Upper Saddle River, NJ: Pearson Prentice Hall.

Williams, J.R. (1992). How sustainable is your competitive advantage? California Management Review, 34, 29–51.