Determinants of Consumers' Attitudes Toward a Sport Sponsorship: A ...

Journal of Nonprofit & Public Sector Marketing, 26:185–207, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 1049-5142 print/1540-6997 online DOI: 10.1080/10495142.2014.899811

Determinants of Consumers’ Attitudes Toward a Sport Sponsorship: A Tale from College Athletics YONG JAE KO Department of Tourism, Recreation, and Sport Management, University of Florida, Gainesville, Florida, USA

YU KYOUM KIM Department of Physical Education, Seoul National University, Seoul, South Korea

Although sponsorship is considered one of the most important revenue sources, there have been surprisingly few attempts to explain how sponsorship works in the mind of a consumer in the nonprofit business segment. The purpose of this study was to identify factors that determine consumers’ attitudes toward sponsorship in college athletics. A conceptual model includes factors related to the sports property/event/team and sponsors. This study also examined the role of a perceived congruence between the sponsor and the sponsored property. A structural equation model test using a convenience sample of 460 students enrolled in a division I-A university suggested that specific characteristics of both the sponsor and the sponsored event are significant determinants of attitudes toward a college athletic sponsorship, and the perceived congruence plays an important part as moderator of a sponsorship perception–attitude link. KEYWORDS sponsorship, consumer attitude, image congruence, college athletics

Corporate sponsorship is increasingly recognized as an effective form of corporate communication and therefore a lucrative commercial investment (Walliser, 2003). Worldwide spending on such sponsorships had reached Address correspondence to Yong Jae Ko, PhD, Associate Professor, Department of Tourism, Recreation, and Sport Management, University of Florida, P.O. Box 118208, Gainesville, FL 32611-8208. E-mail: [email protected] 185

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US$53.3 billion in 2013 and was projected to continue to increase in subsequent years, despite severe economic downturns in many business sectors (IEG Sponsorship Report, 2013). Although the range of sponsored activities has increased steadily, sport sponsorship remains the most popular, with approximately 70% of sponsorship investment being directed to sports (IEG, 2009). Sponsorship is an important source of revenue for college sport in the United States, particularly for highly competitive varsity sport programs. As financial pressures mount, for example, the National Collegiate Athletic Association (NCAA) is trying to diversify its revenue sources after their 11year, $6.1 billion CBS deal expires in 2012 (Wolverton, 2007). Currently, the bulk of universities and their athletic programs require multimillion dollar budgets. They share the burden of ever-increasing athletics expenditures with significantly declining federal and state funding. According to a recent NCAA study, only 14 of the 120 Football Bowl Subdivision schools reported that their cash flows are greater than expenses (Fulks, 2010). As such, they are heavily reliant on corporate sponsorship and private support from boosters (Gutierrez-Nieto & Serrano-Cinca, 2010; Urriolagoitia & Vernis, 2011). By associating with varsity sport programs, corporate sponsors expect image enhancement and sales opportunities through increased awareness and consumer loyalty among target customers (Cornwell & Coote, 2005; Madrigal, 2000). In exchange for these tangible and intangible benefits, the sports property expects financial and/or in-kind benefits. Corporate sponsors and sports events/teams thus have a mutual interest in optimizing sponsorship effectiveness in terms of the positive attitudes and purchase behavior of consumers (McDaniel, 1999). As sponsorship has become an increasingly common marketing and communication phenomenon, so has the amount of research devoted to analysis of sponsorship effectiveness (Copeland, Frisby, & McCarville, 1996; Cornwell & Maignan, 1998; Ko, Kim, Claussen, & Kim, 2008; Meenaghan, 2001). The marketing and advertising literature reported that well-designed sponsorship positively influences (a) consumer recall/awareness (Cornwell, Weeks, & Roy, 2005; Javalgi, Traylor, Gorss, & Lampman, 1994; Lardinoit & Derbaix, 2001); (b) the image of sponsors and their products (Gwinner & Eaton, 1999; Javalgi et al., 1994); and (c) attitudes toward the sponsor (Nicholls, Roslow, & Laskey, 1994; Ruth & Simonin, 2003; Speed & Thompson, 2000). According to Walliser (2003), most of this research has focused on the impact of sponsorship on increased awareness among target consumers and image transfer between sponsors and properties. However, there has been no consensus regarding which variables and outcomes should be measured (Cornwell, 1995; Cornwell et al., 2005; Speed & Thompson, 2000; Walliser, 2003), and few studies have proposed a coherent theoretical framework of the relationships among the salient variables of sponsorship

Sponsorship Attitude

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effectiveness. This is particularly true in the not-for-profit business context. This myopic view has hindered research progression because scholars have yet to provide a comprehensive explanation of sponsorship perceptions that guide evaluation of sponsorship effectiveness from customers’ perspectives. Against this background, the purposes of the present study were to: (a) identify the determinants of consumers’ attitude toward sponsors and their perceptions of (and responses to) sports sponsorship; and (b) examine how the moderator role of perceived congruence between the sponsor and the sponsored property (event/team) influences consumers’ attitudes toward a sponsorship. The study pursues these objectives by adapting and extending Speed and Thompson’s (2000) conceptual model of sports sponsorship. The proposed model includes: (a) consumers’ perceptions associated with the sponsored sports property/event/team (service quality, trust, commitment, and prestige); (b) consumers’ perceptions associated with the sponsor (prominence, sincerity, and ubiquity); and (c) consumers’ perceptions of congruence between the sponsor and the sponsored sports property (which is postulated in the model as playing a moderator role in the relationship between sponsorship perceptions and attitude formation). Although several studies have examined the determinants of consumers’ sponsorship perceptions and attitudes, relatively few studies (Simmons & Becker-Olsen, 2006; Stipp & Schiavone, 1996) have empirically investigated the moderator role of sponsorship congruence in the context of sports sponsorship. The present study thus makes a significant theoretical and practical contribution to understanding of the determinants of sponsorship response in general and the role of sponsor–property congruence in particular. Given that corporate sponsorship represents one of the main ways that university athletic departments offset budget shortfalls, make capital improvements, and run their day-to-day operations, the current research has great potential to strengthen our understanding of sponsorship in a nonprofit business segment.

A RESEARCH MODEL AND HYPOTHESES A Proposed Model Various models of sponsorship evaluation have been proposed, most of which have focused on consideration of the characteristics of sponsors and events (Speed & Thompson, 2000; Tripodi, 2001). However, this approach has been criticized because these models fail to provide a theoretical explanation of how sponsorship works in the mind of the consumer (Cornwell et al., 2005). It has therefore been argued that variables reflecting consumer behavior should be included in such models of sponsorship effectiveness; after all, it is the consumers of the sponsored events who are, ultimately, the targets of the corporate sponsors (Meenaghan, 2001).

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The present study adopts and modifies Speed and Thompson’s (2000) framework of sponsorship effectiveness. In its original form, this model included three sequential phases: (a) consumers’ exposure to sponsorship, (b) consumers’ perceptions of sponsorship, and (c) consumers’ sponsorship responses. In this framework, the factors that determine consumers’ perceptions include: (a) event factors (status of event and personal liking for the event); (b) sponsor factors (prominence, sincerity, and ubiquity of sponsor); and (c) sponsor–event congruence (perceptions of whether the sponsored event and the sponsor fit well together). The model proposed for the present study modifies Speed and Thompson’s (2000) model in several ways. First, the study adopts the first two main determinants of consumer perceptions (event and sponsor) but replaces these generic factors with constituent dimensions of each, derived from the research literature. Second, in another modification of the model of Speed and Thompson, the third determinant of consumer perceptions (sponsor–event congruence) is posited as a moderating variable between perceptions and attitudes, renamed “sponsor–property congruence.” The modified model is illustrated in Figure 1. As shown in the diagram, the first factors on the left side relate to perceptions of dimensions of the sponsored event. Because the sponsored sports entity might not only be an event, but also a team, the generic term property is also used in this study to indicate the sponsored event/team/property. The four dimensions of this construct in the model shown in Figure 1 are: (a) trust, (b) commitment, (c) service quality, and (d) prestige. The model also includes three dimensions

Trust .98 Commitment

.70 Perception of event/team/ property

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Prestige Perception of sponsorship Prominence .98

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Ubiquity

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.53 Sincerity

FIGURE 1 A proposed model.

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Attitudes toward sponsor


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of perceptions of the sponsor: (a) market prominence, (b) ubiquity, and (c) sincerity. The model also shows the construct of sponsor–property congruence being posited as a moderating factor between perceptions and attitudes. These constructs, and the hypothesized relationships among them, are discussed in greater detail below.

Constructs and Hypotheses OVERALL

PERCEPTION OF SPONSORSHIP

If consumers have positive perceptions of the sponsored event/team/ property, they are more likely to have positive overall perceptions of the particular sports sponsorship. In the present study, these perceptions of event/team/property are measured by the four factors shown in Figure 1 (trust, commitment, service quality, and prestige). In addition, a consumer’s response to a sponsorship is influenced by the consumer’s level of prior knowledge and strength of opinions regarding the sponsor (Speed & Thompson, 2000). As shown in Figure 1, three variables relating to the sponsor (market prominence, ubiquity, and sincerity) are utilized in the present study to assess perceptions of the sponsor. Taken collectively, these specific constituent variables of both the event/team/property and the sponsor are important determinants of consumers’ overall perceptions of a particular sports sponsorship. The following hypothesis regarding overall perceptions of a sports sponsorship is proposed: H1: Consumers’ overall perceptions of a sponsorship are influenced by their perceptions of the characteristics of both the property (event/team) and the sponsor.

CONSUMERS’

PERCEPTIONS OF A PROPERTY ( EVENT / TEAM )

As noted above, four variables are posited in the model to represent the characteristics of the sponsorship event/team/property: (a) trust, (b) commitment, (c) service quality, and (d) prestige of team. In the marketing literature, trust has been clearly identified as a key factor in establishing a successful relationship between exchange partners, such as customers and providers (Morgan & Hunt, 1994; Palmatier, Dant, Grewal, & Evans, 2006). Morgan and Hunt defined trust as “one party [having] confidence in the exchange partner’s reliability and integrity” (p. 23). Trust in a provider thus develops when consumers believe that their needs will be fulfilled by actions undertaken by the provider (Anderson & Weitz, 1989). Reductions in perceived risk and confidence in the provider’s future behaviors eventually lead to the consumer developing some degree of loyalty to the provider (Mayer, Davis, & Schoorman, 1995; Morgan & Hunt, 1994; Sirdeshmukh, Singh, & Sabol, 2002).

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In the context of the present study, it is therefore reasonable to presume that trust is an important variable to be taken into account when measuring a consumer’s perceptions of a property/event/team. The second variable, commitment, has been defined by Dwyer, Schurr, and Oh (1987) as “an implicit or explicit pledge of relational continuity between exchange partners” (p. 19). In the marketing literature, commitment (like trust) has been identified as a key variable of successful relationships between exchange partners (Garbarino & Johnson, 1999; Morgan & Hunt, 1994; Palmatier et al., 2006). Highly committed customers have emotional attachments to brands, stores, or services (Thomson, MacInnis, & Park, 2005) and a tendency to resist change (Pritchard, Havitz, & Howard, 1999). In this regard, Mahony, Madrigal, and Howard (2000) developed an instrument known as the Psychological Commitment to Team (PCT) scale to measure sport fans’ attitudinal commitment to a team, even when that team is performing poorly. In the leisure context, Iwasaki and Havitz (2004) identified the mediating effects of psychological commitment on the relationship between leisure involvement and behavioral loyalty to a recreation agency. In the sponsorship context, Cornwell and Coote (2005) provided empirical evidence for the contention that consumers with high levels of identification with a nonprofit organization (i.e., the sponsorship property) are more likely to purchase the sponsoring firm’s product. The fourth variable, perceived service quality, was defined by Parasuraman, Zeithaml, and Berry (1985) as “a global judgment, or attitude relating to the superiority of a service” (p. 16). Numerous studies have confirmed that service quality is positively associated with customer satisfaction, loyalty, and trust (Cronin & Taylor, 1992; Zeithaml & Bitner, 1996). In the context of the present study, it is therefore reasonable to presume that the level of service quality provided by a sports property/event/team is positively related to spectators’ overall perceptions of the property. Finally, the fourth variable, prestige, refers to consumers’ perceptions of the reputation and respect of a provider organization. Such perceptions are based on the exposure of individual consumers to direct and indirect experiences and information about the provider and its activities (Fombrun & Shanley, 1990; Smidts, Pruyn, & van Riel, 2001; Weigelt & Camerer, 1988; Yoon, Guffey, & Kijewski, 1993). In addition to direct personal exposure to such information and experiences, consumers’ perceptions of prestige might be formed from the opinions of reference groups, word of mouth, and publicity about the performance of the provider. In some instances people feel proud to be associated with a well-respected organization, which leads to the phenomenon of “basking in reflected glory” (Cialdini et al., 1976). Several studies have provided empirical evidence that perceived prestige is positively related to customer satisfaction and enhanced purchase intention (Carmeli, 2005; Cornwell & Coote, 2005). Many people who enter into a contract with an organization base their decision on its reputation (Ganesan, 1994), and


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many are willing to pay a reasonable premium to do so (Anderson & Weitz, 1989; Clark & Montgomery, 1998). In the context of sports sponsorship, official sponsors of high-status events, such as the Olympics, can expect a favorable consumer response (Speed & Thompson, 2000; Stipp & Schiavone, 1996). On the basis of the above discussion, it is reasonable to suppose that consumers’ perceptions of a sports property are influenced by trust, commitment, service quality, and the perceived prestige of the property. The following hypothesis is therefore proposed: H2: Consumers’ perceptions of a sports property are influenced by their perceptions of the trust, commitment, service quality, and prestige of the property.

CONSUMERS’

PERCEPTIONS OF SPONSORS

As noted above, three variables are posited in the model to represent the characteristics of the sponsor: (a) market prominence, (b) ubiquity, and (c) sincerity. The first of these variables, market prominence, refers to “variations in market prominence (reputation) of potential sponsors as a source of information when inferring the identity of event sponsors” (Pham & Johar, 2001, p. 124). Perceptions of market prominence are based on such factors as brand awareness, market share, and visibility. In the sponsorship context, consumers are more likely to identify a prominent sponsor or brand, especially in “cluttered” media environments in which it is difficult for consumers to make associations between particular sponsors and events (Pham & Johar, 2001). The second variable, ubiquity,refers to consumers’ perceptions of the frequency and selectivity of a firm’s sponsorship involvement (Speed & Thompson, 2000). Speed and Thompson (2000) suggested that ubiquity is a critical component of determining how the sponsors are perceived. Regarding the direction of the ubiquity and the consumer perception, the results from previous studies including Speed and Thompson were not conclusive. In addition, there are plausible explanations for both directions. Speed and Thompson argued that respondents do not have a strong response toward sponsorship by firms they perceived to be engaging in a large number of sponsorships simultaneously and hypothesized that perceived ubiquity of the sponsor is negatively associated with the level of sports sponsorship response. However, the consumers might interpret the ubiquity as evidence demonstrating the success and the financial soundness of the firm, which in turn can be translated into positive image of the firms (Shimp, 2013). Therefore, due to the inconclusive empirical evidence and plausible explanations supporting both directions, we do not specify the direction of influence of ubiquity in the hypothesis.

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With regard to the third variable, sincerity,Speed and Thompson (2000) found that a sponsor that is perceived to be a “sincere” partner of a given team or event is more likely to receive more positive responses from consumers in terms of interest and a willingness to consider the sponsor’s brand. In addition, several studies have shown that consumers develop positive attitudes and increased purchase intention if sponsors are perceived to have a philanthropic motivation rather than being motivated by purely commercial considerations (Becker-Olsen & Hill, 2006; D’Astous & Blitz, 1995; Rifon, Choi, Trimble, & Li, 2004). This is particularly true in so-called cause-related sponsorship arrangements (Becker-Olsen & Hill, 2006; Rifon et al., 2004; Stipp & Schiavone, 1996). Taking these three characteristics of sponsors together, the following hypothesis is therefore proposed: H3: Consumers’ perceptions of a sponsor are influenced by their perceptions of the prominence, ubiquity, and sincerity of the sponsor.

CONSUMERS’

ATTITUDES TOWARD SPONSORS

Attitude was defined by Fishbein and Ajzen (1975) as “a learned predisposition to respond in a consistently favourable manner with respect to a given object” (p. 6). According to Hull’s (1943) theory of learning, attitudes are formed through a learning process in which a given response becomes associated with a given stimulus. Once formed, attitudes then produce a consistent response to a given stimulus object, which implies that attitudes influence behaviors (Ajzen, 2001; MacKenzie & Lutz, 1989; MacKenzie, Lutz, & Belch, 1989; Shimp, 1981). Within the context of sponsorship, one of the sponsor’s primary goals is to create positive consumer attitudes toward the sponsor (Cornwell & Maignan, 1998). The attitude of consumers toward a sponsor or its brand has thus been a common dependent variable in studies of advertising in general and sponsorship in particular (Javalgi et al., 1994; Lee, Sandler, & Shani, 1997; Speed & Thompson, 2000). The following hypothesis is therefore proposed: H4: Consumers’ overall perceptions of a sponsorship have a positive relationship with their attitude toward the sponsor.

SPONSOR–PROPERTY

CONGRUENCE

In the sponsorship literature, the term congruence refers to relatedness, relevance, or fit (Becker-Olsen & Hill, 2006; Bhat & Reddy, 1998; Johar & Pham, 1999; Rifon et al., 2004; Rodgers, 2004). Numerous studies have provided empirical evidence of the importance of congruence between the image of the sponsor and the image of the sponsored property (Bhat & Reddy, 2001; Cornwell, Humphreys, Maguire, Weeks, & Tellegen, 2006; Gwinner & Eaton, 1999; Johar & Pham, 1999; Rifon et al., 2004; Simmons & Becker-Olsen, 2006; Stipp & Schiavone, 1996).


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Such congruence might refer to credibility and cause (Rifon et al., 2004), or it might refer simply to a semantic relationship between an event (e.g., the Super Bowl) and the sponsoring company (e.g., an automobile company; Johar & Pham, 1999). Sponsor recall has been shown to increase when consumers perceive a relationship between the image of the event and that of the sponsoring brand (Gwinner & Eaton, 1999). So-called image transfer (Gwinner & Eaton, 1999) can also occur; for example, Stipp and Schiavone (1996) found that consumers who could recall Olympic sponsors also perceived a strong relationship between the sponsoring brand and the Olympics. This transfer process is enhanced when there is some perceived match between the image or function of the event and that of the sponsor. The phenomenon of celebrity endorsement in advertising is another example of image transfer, in which the consumer’s response to the promotional message is influenced by a perceived match between the endorser’s image attributes and the brand’s image attributes (McDaniel, 1999). On the basis of this discussion, the following hypothesis is proposed: H5: Sponsor–property congruence plays a moderating role in the relationship between consumers’ overall perceptions of a sponsorship and their attitude toward the sponsors.

EMPIRICAL STUDIES To examine the proposed hypotheses, two studies were conducted in the context of sponsorship of collegiate sports in the United States. Sponsorship of teams in the National Collegiate Athletic Association (NCAA) has experienced significant growth in the past two decades (Masteralexis, Barr, & Hums, 2009).

STUDY 1 Purpose The purpose of Study 1 was to develop a parsimonious instrument to test the conceptual model of Figure 1 by generating and testing the psychometric properties of a set of items with which to measure the constructs in the model.

Participants and Procedures College students in an NCAA Division I-A university in the United States were selected as respondents for the study because students represent a large proportion of the consumers of collegiate sports events (Sabri et al.,

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2008). In this study (as well as in Study 2, see below), the sponsors were actual sponsors from 10 industries (automobile, Internet, sports diet supplements, apparel, restaurants, groceries, broadcasting, insurance, banking, and wireless carriers), all of which provided products and services appropriate for purchase by students. Face-to-face self-administered questionnaires were utilized in the survey. Potential participants, who were informed that participation in the study was entirely voluntary and unpaid, were given an explanation of the purpose of the research and brief instruction on how to complete the questionnaire. On average, it took 10 minutes to complete each questionnaire. A total of 319 college students enrolled in sport, health, and fitnessrelated classes at a major southeastern university in the United States participated in the study. Of these, 34 completed questionnaires were deemed unusable due to invalid responses. These were discarded, leaving 285 usable surveys. The average age of the participants was approximately 22 years. A majority (61%) were female. Most of the participants were Caucasian (50%), followed by Hispanic (31%), Asian (8%), African American (8%), and other (3%).

Instrumentation Measures that had previously been shown to have good psychometric properties were selected from the relevant literature. Some items were modified to suit the context of the current study. All items were then reviewed by a five-member panel of scholars with relevant expertise in the conceptual and methodological issues of the present study, following which problematic items were refined or excluded. As a result, a total of 35 items were retained, as follows: ● ● ● ● ●

● ● ● ●

Trust: four items (Morgan & Hunt, 1994); Commitment: four items (Morgan & Hunt, 1994); Ubiquity: three items (adapted from Speed & Thompson, 2000); Sincerity: four items (adapted from Speed & Thompson, 2000); Sponsor–property congruence: five items (adapted from Speed & Thompson, 2000); Service quality: four items (Dabholkar, Shepherd, & Thorpe, 2000); Prestige: three items (Mael & Ashforth, 1992); Prominence: four items (adapted from Johar, Pham, & Wakefield, 2006); Attitude: four items (Lee & Cho, 2009).

The response format for all items (except those for attitude) was a 7point Likert-type scale (1 = strongly disagree; 7 = strongly agree). The items for attitude were measured by 7-point semantic differential scale items (1 =


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bad, 7 = good; 1 = unfavorable, 7 = favorable; 1 = negative, 7 = positive; 1 = dislikable, 7 = likable). Items measuring demographic characteristics of participants were also included in the questionnaire. To avoid response bias from order effect, the items were randomly placed in the questionnaire.

Results and Discussion The positive sign of the determinant of the input matrix, which was obtained by factor analysis using SPSS 16.0 (SPSS, 2007), demonstrated that there was no severe multicollinearity or singularity in the data. In addition, the linearity of the variables was confirmed when randomly selected pairs of variables were examined. However, the univariate distribution of 34 of 35 observed variables were significantly skewed (ranging from –2.79 to –0.23; (p < 0.01), and the univariate distribution of 19 observed variables showed significant kurtosis (ranging from –0.66 to 9.56). The normalized Mardia (1985) coefficients of skewness and kurtosis, which were obtained through PRELIS 2.80 (Jöreskog & Sörbom, 2006), were 64.43 and 23.12, respectively. These results indicated violations of the assumption of normality (both univariate and multivariate). The Satorra-Bentler (1994) scaling method was therefore employed to address the non-normality of the data, with the S-B χ 2 being adjusted in accordance with Satorra and Bentler’s (2001) recommendations when conducting χ 2 difference tests. The data were subjected to further scale purification by confirmatory factor analysis (CFA) using Mplus 5.2 (Muthén & Muthén, 2008). Bentler’s (1990) comparative fit index (CFI), standardized root mean square residual (SRMR), Steiger’s (1990) root mean square error of approximation (RMSEA) and χ 2 /df were used to evaluate the goodness of fit of the model to the data (MacCallum & Austin, 2000; Weston & Gore, 2006). The initial measurement model fitted the data adequately (S-B χ 2 /df = 951.67/524 = 1.82; RMSEA = 0.05; CFI = 0.92; SRMR = 0.05). Factor loadings, average variance extracted (AVE) values, and reliability coefficients were used to evaluate convergent validity of the measures (Hair, Black, Babin, Anderson, & Tatham, 2005). All factor loadings were significantly larger than zero. AVE values ranged from 0.38 (for sincerity) to 0.78 (for commitment). Because Cronbach’s alpha coefficient has been shown to be somewhat unreliable when a measurement model is not essentially τ -equivalent (Cronbach, 1951; Novick & Lewis, 1967; Osburn, 2000; Raykov, 1997), Raykov’s (1997, 2001) structural equation modeling (SEM) method was used instead of Cronbach’s alpha for estimating scale reliability (Graham, 2006). Reliability coefficients ranged from 0.76 (for sincerity) to 0.95 (for commitment). After this initial CFA, four items (modification index > 10) were excluded, based on Lagrange multipliers. In addition, to develop a more

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parsimonious scale, the number of items per subscales was further reduced on the basis of their pertinence and psychometric properties. The final measurement model included 27 items, arranged as follows: (a) trust (three items), (b) commitment (three items), (c) service quality (three items), (d) prestige (three items), (e) prominence (three items), (f) ubiquity (three items), (g) sincerity (three items), (h) congruence (three items), and (i) attitude (three items). The revised measurement model achieved good fit for data (S-B X 2 /df = 462.35/288 = 1.60; RMSEA = 0.05; CFI = 0.96; SRMR = 0.04). All factor loadings were significantly larger than zero. AVE values ranged from 0.48 (for sincerity) to 0.85 (for commitment). Reliability coefficients ranged from 0.72 (for sincerity) to 0.93 (for commitment). Taken together, the results provided evidence for convergent validity of the measurement scales (Hair et al., 2005). The S-B χ 2 statistic of the unconstrained model was significantly less (p < 0.05) than that of the constrained model for all pairs of latent factors, providing support for discriminant validity (Anderson & Gerbing, 1988).

STUDY 2 Purpose The purposes of Study 2 were: (a) to validate the measurement scales obtained in Study 1; and (b) to use the scales to evaluate the hypothesized relationships in the proposed model of Figure 1.

Participants and Procedures The data-collection procedures and sponsors utilized in Study 1 were again employed in Study 2. A total of 510 individuals recruited from the same university participated in the study. Fifty completed questionnaires were disqualified due to invalid responses. This resulted in 460 usable questionnaires. The majority (62%) of the respondents were male. They ranged in age from 18 years to 47 years (mean = 21.24; SD = 2.72). Most of the respondents (60%) were Caucasian, followed by Hispanic (26%), Asian (5 %), African American (8%), and other (1%).

Results and Discussion In general, data-analysis techniques in Study 2 were the same as those for Study 1. The paths in the hypothesised model were examined by a simultaneous equations analysis using Mplus 5.2 (Muthén & Muthén, 2008). The latent moderated structural equations (LMS) method (Klein & Moosbrugger, 2000) available in Mplus 5.2 was used to test the moderating effect of “sponsor-property congruence.”


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The univariate distribution of 24 of 27 observed variables were significantly (p < 0.01) skewed (ranging from –1.89 to 0.02), and the univariate distribution of all observed variables revealed significant kurtosis (ranging from –0.98 to 3.16). The normalized Mardia’s coefficients of skewness and kurtosis were 44.79 and 24.71, respectively. Therefore, the Satorra-Bentler (1994) scaling method was utilized to obtain model χ 2 . The correlation matrix for the measurement model is presented in Table 1. The model fitted the data very well (S-B χ 2 /df = 472.52/288 = 1.64; RMSEA = 0.04, CFI = 0.97, SRMR = 0.04). The factor loadings, AVEs, and reliability coefficients of the final measurement model are shown in Table 2. All factor loadings were significant in the predicted direction (p < 0.05); all AVE values were greater than 0.50, ranging from 0.53 (for sincerity) to 0.84 (for commitment) and all reliability coefficients were greater than 0.70, ranging from 0.77 (for sincerity) to 0.94 (for commitment). These results provide support for the convergent validity of the measurement scales (Hair et al., 2005). In addition, all χ 2 -difference tests between two nested models for each pair of latent factors were significant. These results indicate that correlations for all pairs of latent factors were significantly different from 1.0, thus providing support for discriminant validity (Anderson & Gerbing, 1988). The simultaneous equation model achieved good fit for the data (S-B χ 2 /df = 462.15/242 = 1.91; RMSEA = 0.04, CFI = 0.96, SRMR = 0.08). As can be seen from Figure 1, all loadings were significant. The loadings for the four dimensions of the construct of “perception of event/team/property” ranged from 0.70 (for commitment) to 0.98 (for trust). The loadings for the three dimensions of the construct of “perception of sponsor” ranged from 0.53 (for sincerity) to 0.88 (for prominence). The loadings for the secondorder constructs of “perception of event/team/property” and “perception of sponsor” on the third-order construct of “perception of sponsorship” were 0.47 and 0.98, respectively. The construct of “sponsorship perception” had a significant influence on “attitudes toward sponsor” (standardized γ = 0.80, S.E. = 0.05, z = 17.58). “Perception of sponsorship” explained 64% of the variance in “attitudes toward sponsor.” The LMS results showed a significant negative moderating effect of “sponsors–property congruence” (γ = –0.16, S.E. = 0.05, z = – 3.11) on the relationship between “perception of sponsorship” and “attitudes toward sponsor.”

GENERAL DISCUSSION Research Implications Although nonprofit organizations are under increasing pressure to secure funding from nongovernment sources, they face a high level of competition in the corporate sponsorship market. As such, they should develop

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Trust1 1.00 Trust2 .44 1.00 Trust3 .59 .63 1.00 Commitment1 .42 .46 .47 1.00 Commitment2 .44 .45 .52 .80 1.00 Commitment3 .47 .48 .53 .84 .88 1.00 SQ1 .43 .57 .60 .42 .39 .40 1.00 SQ2 .40 .47 .54 .46 .40 .42 .53 1.00 SQ3 .37 .54 .59 .43 .45 .46 .62 .56 1.00 Prestige1 .44 .54 .57 .38 .41 .45 .51 .43 .44 1.00 Prestige2 .40 .55 .62 .49 .51 .51 .52 .43 .51 .64 1.00 Prestige3 .42 .51 .58 .49 .47 .46 .46 .52 .51 .58 .63 1.00 Prominence1 .22 .22 .22 .05 .01 .03 .26 .29 .27 15 .16 .15 1.00 Prominence2 .22 .21 .24 .10 .06 .08 .32 .33 .30 .16 .18 .17 .68 1.00 Prominence3 .17 .15 .22 .13 .09 .13 .26 .30 .22 .15 .19 .16 .59 .72 1.00 Ubiquity1 .21 .19 .24 .20 .17 .21 .31 .42 .23 .18 .21 .18 .42 .51 .49 1.00 Ubiquity2 .29 .21 .27 .18 .20 .22 .36 .34 .25 .20 .19 .16 .43 .53 .53 .60 1.00 Ubiquity3 .20 .19 .26 .15 .14 .17 .31 .40 .30 .17 .19 .17 .45 .53 .55 .66 .79 1.00 Sincerity1 .33 .36 .34 .34 .30 .31 .33 .32 .30 .24 .29 .35 .23 .29 .27 .26 .32 .29 1.00 Sincerity2 .39 .32 .34 .33 .34 .35 .29 .26 .28 .19 .27 .27 .21 .25 .25 .21 .33 .27 .58 1.00 Sincerity3 .26 .22 .27 .26 .28 .28 .24 .20 .22 .15 .25 .21 .08 .18 .17 .19 .24 .22 .45 .52 1.00 Attitude1 .19 .22 .25 .09 .09 .07 .29 .28 .26 .16 .18 .20 .49 .54 .47 .36 .38 .37 .23 .26 .27 1.00 Attitude2 .23 .30 .31 .14 .11 .12 .33 .36 .29 .21 .21 .24 .52 .58 .54 .42 .47 .45 .32 .28 .28 .72 1.00 Attitude3 .25 .31 .29 .14 .13 .14 .30 .36 .30 .19 .20 .25 .51 .57 .50 .39 .43 .44 .29 .32 .26 .72 .85 1.00 Fit1 .28 .23 .28 .24 .22 .26 .28 .43 .24 .22 .25 .23 .33 .39 .41 .60 .53 .58 .36 .40 .28 .34 .39 .41 1.00 Fit2 .27 .24 .30 .31 .32 .32 .33 .35 .32 .22 .23 .19 .23 .29 .32 .38 .47 .45 .41 .54 .37 .26 .30 .33 .58 1.00 Fit3 .25 .27 .32 .20 .19 .24 .33 .37 .30 .21 .26 .20 .35 .46 .44 .52 .58 .59 .38 .44 .32 .36 .45 .44 .66 .56 1.00 Mean 4.6 4.7 4.3 3.8 3.6 3.6 5.7 5.0 4.7 4.2 4.2 4.2 6.2 5.8 5.6 5.4 5.41 5.4 4.5 4.4 4.3 5.8 5.8 5.8 5.0 4.4 5.1 SD 1.32 1.31 1.15 1.76 1.75 1.78 1.32 1.41 1.42 1.25 1.12 1.28 1.33 1.41 1.42 1.43 1.51 1.48 1.47 1.52 1.55 1.37 1.38 1.36 1.45 1.50 1.54

1

TABLE 1 Correlation Matrix

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Sponsorship Attitude TABLE 2 Confirmatory Factor Analysis Factors and items Trust I can count on team X Team X has integrity Team X is reliable Commitment I am devoted to team X I am dedicated to team X I am committed to team X Service Quality Team X offers high standards of service Team X provides excellent overall service Team X provides service of very high quality Prestige People in my community think highly of team X It is considered prestigious in my community to be a fan of team X Team X has a good reputation in my community Prominence Firm A is well known Firm A is highly regarded in the industry Firm A is one of the most capable firms in the industry Ubiquity Firm A sponsors many different sports I expect firm A to sponsor major sport events It is very common to see firm A sponsoring sport events Sincerity The main reason firm A would sponsor team X is because the firm believes team X deserves support Firm A would be likely to have the best interest of team X at heart Firm A would probably support team X even if it had a much lower profile Attitude Overall, my attitude toward firm A sponsoring team X is Negative (1), Positive (7) Overall, my attitude toward firm A sponsoring team X is Bad (1), Good (7) Overall, my attitude toward firm A sponsoring team X is Dislikable (1), Likable (7) Fit Firm A and team X fit together well The image of team X and the image of firm A are similar It makes sense to me that firm A sponsors team X

λ

S.E.

.64 .75 .85

.04 .03 .02

.87 .92 .96

.02 .01 .01

.76 .82 .77

.03 .02 .03

.78 .67 .77

.03 .03 .03

.76 .89 .81

.03 .02 .03

.74 .86 .90

.03 .02 .02

.72

.03

.82 .63

.03 .04

.79

.03

.92

.02

.92

.02

.80 .72 .81

.02 .03 .02

ρ

AVE

.78

.57

.94

.84

.80

.61

.78

.55

.86

.68

.87

.70

.77

.53

.91

.77

.82

.60

Note. AVE = average variance extracted.

a strategic partnership with highly selected corporate patrons (MacMillan, 1983). It is important to develop a comprehensive understanding of how sponsorship works in consumers’ mind to develop mutually beneficial relationships and maximize sponsorship effectiveness. The research model developed in this study consolidates various constructs related to sponsors and events/teams/properties into a single comprehensive framework, thus providing an integrated view of the factors that determine consumers’

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perceptions of a sponsorship and their attitudes toward a sponsor. The empirical studies have shown that the psychometric properties of the proposed measurement scales are sound, and the testing of the hypotheses has provided new insights into perceptions and attitudes toward sports sponsorships. There was empirical support for H1, which had proposed that consumers’ overall perceptions of a sponsorship are influenced by their perceptions of both the property and the sponsor. In general, sports consumers who had a positive perception of the event/team/property and the sponsor were more likely to develop positive perceptions of the sponsorship. More specifically, sponsor-related dimensions made a more significant contribution to the development of consumers’ perceptions of a sponsorship than did property-related factors. This finding is in accordance with previous research (MacKenzie & Lutz, 1989; Rifon et al., 2004; Speed & Thompson, 2000). In this regard, it is interesting that a consumer’s positive relationship with a particular sports team does not necessarily lead to the development of a positive attitude toward the team’s sponsors; rather, this relationship was found to be mediated by the perceived sincerity of the sponsor. There was also empirical support for H2, which had proposed that consumers’ perceptions of a sports property are influenced by their perceptions of the trust, commitment, service quality, and prestige of the property. In particular, the consumer’s belief (trust) in the event/team/property was identified as the most significant determinant of the consumer–property relationship. H3, which had proposed that consumers’ perceptions of a sponsor are influenced by their perceptions of the prominence, ubiquity, and sincerity of the sponsor, also received empirical support. Although all of these dimensions were found to be significant, prominence was identified as the most important determinant of the development of perceptions of sponsors. This finding is consistent with a previous study, which found that consumers were more likely to identify prominent sponsors. This prominence bias is likely to be of importance in the highly “cluttered” U.S. college sports context, in which identification of event–sponsor associations is often difficult (Johar & Pham, 1999; Pham & Johar, 2001). In terms of ubiquity, there are two schools of thought on the direction of ubiquity’s impact. One possible impact is that ubiquity has negative impact on perceptions of the sponsor because consumers are more likely to view the sponsors’ motive as self-interested and profit-oriented. However, the positive impact of ubiquity can be also justified based on signaling theory, which states that the consumer will consider the ubiquity of the sponsor as the signal indicating the firms are financially strong to make substantial sponsorship investment. Therefore, we used a two-tailed hypothesis rather than a one tailed-hypothesis. Our results have shown the positive relationship between ubiquity and perception of sponsor supporting the signal theory. We do not claim our results provide a definite answer


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for the question about the direction of ubiquity’s influence. Nevertheless, we hope our empirical results shed light on the role of ubiquity in sponsorship effect. H4 had proposed that consumers’ overall perceptions of a sponsorship have a positive relationship with their attitude toward the sponsor. This hypothesis was also supported, with overall perceptions of a sponsorship explaining 64% of the variance in predicting attitude toward the sponsor. This finding is in accordance with previous studies of sponsorship outcomes and consumers’ behavioral intentions (Ajzen, 2001; MacKenzie & Lutz, 1989; MacKenzie et al., 1989; Rifon et al., 2004; Shimp, 1981; Speed & Thompson, 2000). There was also empirical support for Hypothesis H5, which had proposed that sponsor–property congruence has a moderating role in the relationship between a consumer’s overall perceptions of a sponsorship and his or her attitude toward the sponsor; that is, the strength of the relationship between “perception of sponsorship” and “attitudes toward sponsor” decreases as the fit between sponsor and team is perceived to increase. This result is in general accordance with previous studies that have emphasized the importance of image congruence between the sponsor and the event in predicting consumers’ responses to a sponsorship (Johar & Pham, 1999; Rifon et al., 2004; Rodgers, 2004). However, the present findings extend knowledge in this area by going beyond the findings of previous studies that have identified a relationship between image congruence and awareness (Gwinner & Eaton, 1999) or between image congruence and attitude (Simmons & Becker-Olsen, 2006) by clarifying the theoretical relationships that exist among: (a) image congruence, (b) consumers’ perceptions of sponsorships, and (c) their attitudes toward sponsors. Specifically, the present findings demonstrate that positive perceptions of a sponsorship can induce a positive attitude toward a sponsor, even if the consumer perceives that there is little congruence between the sponsor and the event; however, the impact of the consumer’s perceptions of the sponsorship in predicting the consumer’s attitudes toward the sponsor is less important when there is a high level of congruence between the sponsor and the team/event/property. This phenomenon is in general accordance with the findings of Cornwell et al. (2006), who reported that congruent sponsors have a natural advantage in terms of consumers’ memory recall, but that such recall can be improved in the case of incongruent sponsor–event images if active steps are taken to articulate and communicate the positive aspects of the sponsorship. In summary, the empirical findings of the present study confirm that: (a) the constructs in the proposed model are significant predictors of sponsorship effectiveness; and (b) sponsor–property congruence plays a significant moderating role in the formation of consumer attitudes toward a sponsor.

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Managerial Implications The results of the study have several important managerial implications for sponsors and for the college athletics that are being sponsored. First, the study shows that consumers’ perceptions of sponsorships are influenced by the characteristics of both the sponsor and the property (event/team) being sponsored. Potential sponsors should note that they are likely to maximize their benefits if they sponsor sports programs that are positively perceived by consumers in terms of service quality, prestige, trust, and commitment. Moreover, for sports programs that are seeking sponsorship, the findings show that consumers’ positive perceptions toward a sponsorship are important because they encourage sport spectators’ purchase of the sponsor’s products. It is thus apparent that both sponsors and sports properties (events/teams) should carefully and continuously monitor the perceptions of consumers with regard to the sports property being sponsored. Second, the study shows that consumers’ overall perceptions of the sponsorship are very important in determining their attitudes toward sponsors, especially when consumers perceive that there is a lack of congruence between the sponsor and the property (event/team). However, their overall perception of the sponsorship plays a less important role in determining their attitudes toward sponsors if they perceive high congruence between the sponsor and the property. These findings reinforce the importance of careful selection of partners for both the sports property and sponsor. Image congruence is obviously desirable, especially for low-profile sports properties and potential sponsors. However, if there is little congruence between the sponsor and the property, potential partners should demonstrate that they have sincere motives for becoming involved in the sponsorship, and they should show genuine concern for the event or team (and its fans). Corporate partners also benefit by establishing and maintaining market prominence. Finally, sport properties should actively communicate the benefits of the partnership created for both the property and its fans. The goodwill generated by such communication is likely to reduce consumer resistance to the marketing communications involved in the sponsorship. As previously noted, effective marketing communication can overcome the disadvantages of a poor fit between the sponsor and the chosen cause or property (Cornwell et al., 2006; Simmons & Becker-Olsen, 2006).

Limitations and Future Research The cross-sectional research design of the present study could be improved by a longitudinal investigation to provide more convincing evidence of the causal relationships in the model. Second, the study was confined to one segment of nonprofit business, which included U.S. college students and two college sport programs. Replicating the study with a broader sampling frame in other sports and nonprofit business contexts would increase the


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generalizability of the present findings. Finally, the variance in sponsorship effectiveness cannot be explained entirely by the selected dimensions identified in this study. In future studies it will be necessary to explore a variety of strategic dimensions that contribute to clear understanding of sponsorship effectiveness in different nonprofit business contexts. Overall, we believe that the proposed research model will contribute to the body of knowledge in sponsorship research in the nonprofit sector. It may provide management with strategic directions in understanding consumers’ attitudes toward sponsorship, which could help marketers develop strategic planning for long-term business-to-business relationships. As a result, this effort may significantly enhance the financial health and overall success of many not-for-profit organizations, including college athletics.

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