understanding domains and roles of fit in sport …
TRANSCRIPT
UNDERSTANDING DOMAINS AND ROLES OF FIT IN SPORT EVENT SPONSORSHIP
By
ARI KIM
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2017
© 2017 Ari Kim
To my father
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ACKNOWLEDGMENTS
First and foremost, I would like to acknowledge the guidance and patience of my
advisor, Dr. Heather Gibson. During times of self-doubt and wandering, her leadership
helped me to remind of my abilities to accomplish my goals and move forward. Next, I
would like thank Drs. Yong Jae Ko, Dan Connaughton, and Chris Janiszewski who
provided me valuable suggestions and guidance along the way. I am also indebted to
Dr. Kiki Kaplanidou who gave me an opportunity in the academic field of sport
management in the first place. In addition, I would like to say “special thanks” to sport
marketing scholars and colleagues who served as my panel of experts.
I am very grateful that I have worked with the best colleagues at the College of
Health and Human Performance, especially the FLG 206 crew including my officemates
Mona and Akiko. Also, I would like to thank all my friends in Gainesville. I especially
owe a great debt to Ara and Yoojung for always being there for me and Ben. Without
their support and favor, I would not have been able to complete this dissertation.
Finally, I want to thank my family. To my mother and brother Zeemo for their
support and encouragement. To aunts and uncles Drs. Hangu and Yoosook Kim and
Drs. Mann and Yoohee Yoon for inspiring me to pursue my academic career. And I
would finally like to mention my husband Moonhoon Choi and our son Benjamin.
Moonhoon could not have been more helpful and generous with his time taking care of
family despite being suffering to pursue his own Ph.D. Ben was born independent and
knows how to be self-entertained, which makes my last phase of dissertation work
much easier. Though the process has taken longer than they have ever imagined, all
my family never lost their faith in my ability to get this done. Their endless love, trust,
and sacrifice made this all possible.
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TABLE OF CONTENTS page
ACKNOWLEDGMENTS ............................................................................................ 4
LIST OF TABLES ...................................................................................................... 8
LIST OF FIGURES .................................................................................................. 10
ABSTRACT ............................................................................................................. 11
CHAPTER
1 INTRODUCTION .............................................................................................. 13
Statement of Problem ....................................................................................... 16 Conceptual Framework ..................................................................................... 17
Purpose of the Study ........................................................................................ 20
2 LITERATURE REVIEW .................................................................................... 24
Sport Sponsorship ............................................................................................ 24 Sport Event Sponsorship ............................................................................ 25 Sponsorship Outcomes .............................................................................. 27
How Sponsorship Works: Schema Congruity Theory ....................................... 29 Sponsor–Event Fit ............................................................................................ 30
General Definition of Fit .............................................................................. 31
Dimensions of Fit ........................................................................................ 32
Issues of Measuring Fit .............................................................................. 35 Multifaceted Measurements of Fit .............................................................. 36
Fit as a Predictor of Sponsorship Outcomes ..................................................... 37
Cognitive Outcomes ................................................................................... 38 Affective Outcomes .................................................................................... 39
Behavioral Outcomes ................................................................................. 39 Moderating Role of Involvement ....................................................................... 41 Summary .......................................................................................................... 41
3 METHODS ........................................................................................................ 44
Methods: Qualitative Phase .............................................................................. 44
Data Collection ........................................................................................... 45 Participants ................................................................................................. 48
Data Analysis ............................................................................................. 48 Methods: Quantitative Phase ............................................................................ 49
Instrumentation ........................................................................................... 49 Data Collection ........................................................................................... 57 Participants ................................................................................................. 58 Data Analysis ............................................................................................. 59
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4 RESULTS ......................................................................................................... 67
Results: Qualitative Phase ................................................................................ 67 Image-Based Fit ......................................................................................... 67
Functional-Based Fit .................................................................................. 74 Brand Characteristics ................................................................................. 80 Sponsorship Outcomes .............................................................................. 85
Results: Quantitative Phase .............................................................................. 89 Descriptive Statistics .................................................................................. 89
Data Screening and Test of Assumptions for SEM .................................... 90 Measurement Models ................................................................................. 91 Structural Model ......................................................................................... 95 Moderating Effect ....................................................................................... 97
5 DISCUSSION ................................................................................................. 117
Grounded Theory Model of Sponsor–event Fit ............................................... 117
Confirmation of the Structure of Sponsor–event Fit ........................................ 122 Sponsor–Event Fit as a Predictor of Sponsorship Outcomes ......................... 126
Moderating Effect of Event Involvement ......................................................... 129 Practical Implications ...................................................................................... 130 Limitations and Delimitations .......................................................................... 131
Limitations ................................................................................................ 132 Delimitation ............................................................................................... 133
Future Research ............................................................................................. 134 Conclusion ...................................................................................................... 134
APPENDIX
A QUALITATIVE STUDY RECRUITMENT MATERIALS ................................... 136
B QUALITAIVE STUDY INSTITITUIONAL REVIEW BOARD APPROVAL ........ 138
C ONLINE QUESTIONNAIRE FOR QUALITATIVE STUDY PARTICIPANTS RECRUITMENT .............................................................................................. 139
D FOCUS GROUP DISCUSSION GUIDE .......................................................... 142
E PILOT STUDY INSTITITUIONAL REVIEW BOARD APPROVAL .................. 143
F PILOT STUDY QUESTIONNAIRE .................................................................. 144
G EXPERT REVIEW MATERIALS ..................................................................... 147
H QUANTITATIVE STUDY QUESTIONNAIRE .................................................. 152
I QUANTITATIVE STUDY INSTITITUIONAL REVIEW BOARD APPROVAL ... 160
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LIST OF REFERENCES ....................................................................................... 161
BIOGRAPHICAL SKETCH .................................................................................... 170
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LIST OF TABLES
Table page 2-1 Definition of congruence in the sponsorship literature .................................. 43
3-1 Qualitative study participant pseudonyms and demographic information ..... 61
3-2 Sponsoring brand awareness and perceived sponsor–event fit from pilot study ............................................................................................................. 62
3-3 Initial list of measurement items for expert review ........................................ 63
3-4 Quantitative sample descriptive characteristics ............................................ 65
3-5 Purchase experience of sponsoring brand among main quantitative study participants ................................................................................................... 66
4-1 Image-based fit item descriptives ................................................................. 98
4-2 Functional-based fit item descriptives ........................................................... 99
4-3 Brand Characteristics sponsor–event fit item descriptives ......................... 100
4-4 Sponsorship outcome item descriptives ..................................................... 101
4-5 Involvement item descriptives..................................................................... 102
4-6 Image-based fit confirmatory factor analysis results ................................... 103
4-7 Functional-based fit confirmatory factor analysis results ............................ 104
4-8 Brand Characteristics sponsor–event fit confirmatory factor analysis results ......................................................................................................... 105
4-9 Correlation among sponsor–event fit constructs......................................... 106
4-10 Rotated component matrix after exploratory factor analysis ....................... 107
4-11 Sponsor–event fit confirmatory factor analysis results (5 factor model) ...... 108
4-12 Goodness of fit indices for the hypothesized and alternative model ........... 109
4-13 Sponsorship outcomes confirmatory factor analysis results ....................... 110
4-14 Correlation among sponsorship outcome constructs .................................. 111
4-15 Involvement confirmatory factor analysis results ........................................ 112
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4-16 Invariance tests of structural model to test moderating effect ..................... 113
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LIST OF FIGURES
Figure page 1-1 Grounded theory model of the Sponsor–Sport Event Fit (SSEF model)
developed from the qualitative study ............................................................ 23
4-1 Revised third-order hierarchical model for sponsor–event fit ...................... 114
4-2 Alternative independent factor model for sponsor–event fit ........................ 115
4-3 Structural model for sponsor–event fit and sponsorship outcomes ............ 116
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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
UNDERSTANDING DOMAINS AND ROLES OF FIT IN SPORT EVENT
SPONSORSHIP
By
Ari Kim
August 2017
Chair: Heather Gibson Major: Health and Human Performance
The perceived fit between a sport event and a sponsoring brand is a core
antecedent in predicting consumers’ sponsorship response. When the fit is perceived as
good, this results in consumers’ positive responses to sponsorship activity. The purpose
of this dissertation was to explore domains of sponsor–event fit in sport consumers’
minds and to examine the relationship between sponsor–event fit and sponsorship
outcomes.
A complimentary sequential mixed-methods approach was employed combining
qualitative and quantitative methods. The qualitative phase explored individuals’
perceptions of sponsor–event fit in focus group discussions using cognitive mapping
technique. The findings revealed that sponsor–event fit is a multidimensional construct
containing three main themes: image-based fit, functional-based fit, and brand
characteristics. The quantitative phase tested the resulting grounded theory model
(SSEF model) among a larger generalizable sample using online survey method. A
multidimensional measurement scale of sponsor–event fit was developed from the
grounded theory model and the review of literature. The quantitative data showed that
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image-based fit and functional-based fit are two effective domains of sponsor–event fit
where the former positively influences favorability and interest, and the latter influences
intention to use.
By building the grounded theory model and empirically confirming domains and
roles of fit in sport event sponsorship, this study provides a conceptual foundation for
further sport event sponsorship research. From a practical perspective, the author
recommends sponsor–event fit as a key component that can assist brand managers
and sport event organizers in making decisions regarding sponsorship agreements.
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CHAPTER 1 INTRODUCTION
Sponsorship has emerged as a key strategic initiative for marketers in recent
years (Fullerton, 2006). Keller (1993) suggested that nontraditional marketing activities
such as sponsorship help build strong brand equity. When a brand is associated with an
event through sponsorship, some of the event’s images may become linked to the
brand (Gwinner, 1997). Among the different types of sponsorship opportunities, sport
sponsorship is the largest and fastest-growing segment (IEG, 2017). This may have
happened because sports are one of the most effective and efficient ways to
communicate with current and potential target markets (Shank, 2005). Sport
sponsorship can be defined as financial investment in sport entities, athletes, leagues,
teams, or events to support overall organizational objectives, marketing goals, and
promotional strategies (Shank, 2005). According to the International Event Group (IEG),
sport sponsorship spending in the North American market amounted to $15.7 billion in
2016, accounting for 70% of total sponsorship spending. The growth rate from 2015 to
2016 for sport sponsorship outlays in North America was 4.7%, which exceeded the
growth of traditional advertising and marketing spending (IEG, 2017).
Sponsorship of mega sport events such as the Olympic Games or the FIFA
World Cup is one of the most preferable types of sport sponsorship because these
events generate global attention (Ferrand, Chappelet, & Séguin, 2012). Typically,
official sponsors of mega sport events obtain the right to be a sponsor by engaging in a
sponsorship agreement that involves a significant contract fee. For the 2012 Summer
Olympic Games, the International Olympic Committee (IOC) generated $957 million
through the Olympic Partners (TOP) program, which was more than for any previous
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Olympics (IOC, 2012). In 2013, FIFA generated $404 million from 2014 FIFA World Cup
Sponsors. Each major sponsor paid $25–50 million per year, and second-tier partners
paid $10–25 million per year (Smith, 2014). Sponsorship programs provide each
sponsoring company with exclusive global marketing rights and opportunities. Though
mega sport event sponsorship has received the most attention, smaller scale sport
events also attract marketing executives’ interest, given their ability to access live
audiences (Fullerton, 2006).
In general, sponsorship holds a unique position in marketing because it is
effective in building brand awareness, providing differentiated marketing platforms,
facilitating direct business benefits, and providing valuable networking and hospitality
opportunities (Shank, 2005). The possible benefits of sport sponsorship include
increasing awareness, acquiring a competitive edge, reaching new target markets,
building relationships with consumers, and building brand image (Shank, 2005). Many
for-profit companies have differentiated and leveraged their brands through sponsorship
(Crimmins & Horn, 1996). Psychological approaches related to consumer behaviors
focus on the processes through which sport sponsorship is translated into behavioral
intention toward the sponsoring product based on cognitive and affective psychological
mechanisms.
In the case of sport event sponsorship, sponsors try to associate their brand with
the sponsored event in the minds of consumers by activating sponsorship (Gwinner,
2014). Activation can be defined as “the set of strategic efforts that are designed to
support and enhance the sponsorship” (Fullerton, 2006, p. 209). Sponsors can
frequently leverage their sponsorship through on-site sponsorship activation (i.e.,
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providing customers with the opportunity to try out the products) and interaction with
consumers at the sponsored event (Close, Finney, Lacey, & Sneath, 2006; Sneath,
Finney, & Close, 2004). The sponsoring company gains an additional benefit from sport
sponsorship through events as event sponsorship provides opportunities to gauge
customer responses to products immediately at the event venue.
Due to the positive benefits of sport event sponsorship mentioned above, more
companies are trying to find opportunities to support sport events and add sport event
sponsorship to their marketing portfolios. As a result, sponsorship marketing through
sport events is reaching its saturation point (Fullerton, 2006). Therefore, brand
executives need to find ways to maximize sponsorship agreements and activate more
systematic sponsorship programs that make them stand out. Furthermore, to improve
the effectiveness of sport event sponsorship, there is a need to better understand the
relationship between sport events and sponsoring brands (Pracejus & Olsen, 2004).
A perceived fit between sponsors and sponsored entities is important because it
is a key antecedent to predict consumers’ sponsorship response (McDonald, 1991). In
the sponsorship literature, fit is referred to as “relatedness” and “relevance” (Johar &
Pham, 1999) or described in terms of whether the images of the two entities (i.e., the
sponsor and the event) are perceived to be congruent or incongruent with viewer
expectations (Heckler & Childers, 1992). Simmons and Becker-Olsen (2006) defined
congruence as the extent to which the sponsor and the event are perceived as similar,
whether on the basis of functionality, attributes, images, or other key associations.
Some sponsorship researchers have defined fit on the basis of the sponsor’s direct or
indirect relevance to the event (McDonald, 1991). Gwinner (1997) further defined direct
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relevance as functional-based similarity and indirect relevance as image-based
similarity. Empirically, sponsorship studies have revealed that the fit between sponsor
and sponsored event affects outcomes such as sponsorship awareness (Johar & Pham,
1999), attitude toward the sponsor (Becker-Olsen & Simmons, 2002; Speed &
Thompson, 2000), brand image (Gwinner & Eaton, 1999), sponsor credibility (Rifon,
Choi, Trimble, & Li, 2004), intention to purchase or use (Gwinner & Bennett, 2008;
Madrigal, 2001), word of mouth (WOM) (Visentin, Scarpi, & Pizzi, 2016), product
differentiation (Amis, Slack, & Berrett, 1999), and market share (Chandon, Wansink, &
Laurent, 2000).
Statement of Problem
Despite the importance of fit in sponsorship research, the conceptualization of fit
as a construct is not clear. Although there are scales that evaluate level of similarity
(e.g., Gwinner, 1997; Gwinner & Eaton, 1999), relatedness (e.g., Johar & Pham, 1999),
match (e.g., McDaniel, 1999), or fit (e.g., Becker-Olsen & Simmons, 2002; Speed &
Thompson, 2000), it is still unclear what dimensions of fit sport event consumers care
about. Moreover, previous studies that have examined the role of the fit construct on the
effectiveness of sponsorship outcomes have shown some limitations in terms of
measurement (e.g., too broad and comprehensive). Furthermore, the use of
prespecified scale items tends to measure the similarities between the two entities, but
fails to measure what the similarities are about. Several sport marketing researchers
(e.g., Gwinner & Eaton, 1999; Speed & Thompson, 2000) have measured general fit
with semantic differential scales that are anchored with the words “poorly matched” and
“well matched.” The positive effectiveness of fit on consumer response in sponsorship
contexts manipulates sponsorship stimuli based on the preperception of the image of
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the sponsoring brand or cause. In their experimental study, Johar and Pham (1999)
selected congruent and incongruent pairs based on pretest and manipulated them to
test the impact of fit on sponsorship outcomes. However, with this general fit, it is
difficult to understand what domains of fit consumers think about.
Experimental research studies rely heavily on comparing the extreme cases of
good or bad fit. Some studies based on schema congruity theory have compared
different levels of congruity (i.e., extreme congruence, moderate incongruence, extreme
incongruence) and investigated whether the level of fit can affect consumer response.
There have also been attempts to establish subdimensions of fit (e.g., Zdravkovic,
Magnusson, & Stanley, 2010), but these are still too broad for sport marketing
practitioners to use when estimating the relationship between their brand and the sport
event. In summary, the disconnect between the conceptualization and
operationalization of the fit construct needs to be addressed if sport sponsorship
congruity research is to advance.
Conceptual Framework
Among many possible theories that explain the mechanics of sponsorship and
how sponsorship activation can generate positive sponsorship outcomes, schema
congruity theory (Fiske, 1982) has been used mostly to explain consumers’ processing
of sport sponsorships and the role of sponsor–event fit. Fiske (1982) defined a schema
as “an active organization of past experiences, which must always be supposed to be
operating in any well-adapted organic response” (p. 60). In the sponsorship literature,
schema congruity theory has been found to be useful in investigating (a) how
consumers process the image fit of a brand and a sport event brought together through
sponsorship, and (b) how the image fit leads to favorable cognitions, attitude toward the
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sponsoring brand, and behavioral outcomes (Cornwell, Weeks, & Roy, 2005; Jagre,
Watson, & Watson, 2001). As schema congruity literature highlights, it is important to
focus on perceived fit between the sponsor and sponsored event on generating positive
sponsorship outcomes.
The associative network memory model (Keller, 1993) is deemed appropriate to
further describe how individuals infer sponsor–event fit as fit is created with the
association of two entities. The model explains that when a brand becomes associated
with a sponsored event, some of the associations connected to the sponsored event
may become linked in memory to the brand (Keller, 2003). The associations are not
limited to words, concepts, or visual images (Cornwell et al., 2005), and consumers
employ numerous concepts and, information stored in their minds (i.e., nodes) to
understand the relationship between a sponsor and an event, thereby not relying on
only one piece of information. However, what kind of information or associations are
used as cues to link sponsor and sponsored event are yet to be investigated. Therefore,
the current study explored the types of information that sport consumers use when
connecting sponsoring brand and sponsored event.
The grounded theory model of Sponsor and Sport Event Fit (SSEF model) was
developed in the first phase of this research, derived from the qualitative study results in
combination with schema congruity theory and associative network model (Figure 1-1).
The SSEF model integrated three main themes of sponsor–event fit: image-based fit,
functional-based fit, and brand characteristics. Each main theme has three or four
related subthemes as follows:
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Image-based fit: similarity between the event image and the sponsoring brand
image.
Active and healthy image – This theme highlighted the active, energetic, and healthy image that a well-matched sponsoring brand might have. Participants perceived similarity between a sport event and a sponsor when two entities shared such images.
Caring community – Caring community reflected image fit based on the sponsor brand’s goodwill to the community.
Prominence – Prominence captured perceived image similarity based on the reputation of sponsors and events influenced by its awareness, size, market share, and visibility.
Socioeconomic status of consumer – Participants noted overlapping images between event audiences and target consumers of sponsoring brands when an event and a sponsoring brand were well matched.
Functional-based fit: perceived fit occurred when the products or services of
sponsoring brands were directly or indirectly used during the event.
Athlete use during the game – Participants tended to link an event and a sponsoring brand well when they believed that athletes participating in the event used the sponsor’s product.
Operational use – Participants stated that there is a good fit between an event and a brand when the products or services of the sponsoring brand were used by event organizers to manage the event.
Audience consumption during the game – The sponsoring brand’s products do not necessarily need to be used directly by the athletes or the event staffs. Participants perceived a good fit when the audience consumed the sponsor’s product while watching the game.
Brand characteristics: the perceived association between an event and a brand
based on the brand feature itself.
Symbolic feature – Some participants perceived a good fit between an event and a brand when the sponsoring brand’s symbolic features such as brands’ names, logos, and colors are somehow linked to the event in their mind.
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Product coverage – When the product range and types of product categories of a brand were matched with the event, participants well associated the brand and the event.
Geographical characteristics – Most of participants tried to figure out country of origin or target market of a brand, then discussed if those regions were well matched with geographical areas associated with an event (e.g., hosting cities or countries, regions where the event viewership is high).
Length of sponsorship – Participants sometimes associated an event and a brand with no logical explanations other than a long-term partnership as a sponsor and a sponsee.
The grounded theory model also illustrated a relationship between the sponsor–
event fit themes and sponsorship outcomes. Cognitive (e.g., awareness, recall),
affective (e.g., positive attitudes, favorability), and behavioral outcomes (e.g., purchase
intention, word of mouth (WOM)) were revealed as consequences of sponsor–event fit.
In terms of WOM, the qualitative study results suggested a sequential impact of
sponsor–event fit on WOM. Participants argued that sponsor–event fit first resulted in
positive cognitive and affective outcomes, and then generated positive WOM.
During the group discussion, highly involved and less involved sports fans
conveyed different views on various issues. This discrepancy suggested a moderating
role of involvement in the relationship between sponsor–event fit and sponsorship
outcome. This grounded theory model and associated themes are discussed in more
detail in Chapters Four and Five, respectively.
Purpose of the Study
The purpose of this study was to: (a) understand sport consumers’ perceptions of
sponsor–event fit, (b) create a measure to assess multidimensional components of fit,
and (c) confirm the predictive validity of the scale by examining the relationships
between fit and its dependent variables (i.e., cognitive, affective, and behavioral
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outcomes). To achieve these objectives, a multiphase, multi-method study was
designed.
First, a qualitative exploration of a specific sponsor–event fit was conducted to
uncover underlying dimensions and generate a list of possible measurement items. To
explore the domains of sponsor–event fit in consumer’s minds, the following questions
were addressed for the qualitative study:
Research question 1: What are the dominant sponsor–event fit themes?
Research question 2: What are the sponsorship outcomes in sport consumers’ minds?
Research question 3: How does sponsor–event fit link to sponsorship outcomes?
The purpose of phase two, the quantitative study was to: (a) refine measurement
items, (b) confirm the hierarchical structure of the fit model, and (c) examine the
relationship between fit and sponsorship outcomes. Based on the results from the
qualitative study and the aforementioned purpose of the study, the following research
questions and hypotheses were proposed for the quantitative study:
Research question 1: Can the three subdomains of the global sponsor–event fit be empirically verified?
Research question 2: What are the effective domains of sponsor–event fit that positively influence sponsorship outcomes?
Research question 3: Is the influence of sponsor–event fit on WOM sequential?
To examine these research questions, the following hypotheses were formed and
tested:
Hypothesis 1: Fit is one global construct that has a third-order relationship with its subdimensional factors.
Hypothesis 2: Image-based fit has a positive impact on a) cognitive sponsorship outcomes and, b) affective sponsorship outcomes.
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Hypothesis 3: Functional-based fit has a positive impact on behavioral sponsorship outcomes.
Hypothesis 4: Brand characteristics have a positive impact on a) cognitive sponsorship outcomes and, b) affective sponsorship outcomes.
Hypothesis 5: a) cognitive sponsorship outcomes and, b) affective sponsorship outcomes mediate the relationship between sponsor–event fit and WOM.
Hypothesis 6: Event involvement moderates in the relationship between sponsor–event fit and sponsorship outcomes.
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Figure 1-1. Grounded theory model of the Sponsor–Sport Event Fit (SSEF model) developed from the qualitative study
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CHAPTER 2 LITERATURE REVIEW
The following sections provide an overview of sport sponsorship research,
concentrating on the role of fit in sport event sponsorship. The first part of the literature
review provides the definition and significance of sport event sponsorship as well as
general sponsorship outcomes. Subsequently, schema congruity theory (Fiske, 1982) is
described as the theoretical mechanism of sponsorship, followed by discourses
regarding fit in the sport sponsorship context, which include the definition of fit, issues
that arise when measuring fit, the role of fit as a predictor of sponsorship outcome, and
the moderating role of involvement.
Sport Sponsorship
Sponsorship has been defined as “an investment, in cash or in kind, in an
activity, in return for access to the exploitable commercial potential associated with that
activity” (Meenaghan, 1991, p. 36). Cornwell (1995) defined sponsorship-linked
marketing as “orchestration and implementation of marketing activities for the purpose
of building and communicating an association to a sponsorship” (p.15). Sport
sponsorship is a commercial exchange to achieve business goals not only for the
sponsor, but also for the sponsored property (sport team, sport event, athletes, or the
sport itself) through association (Gwinner, 2014). Sport consumers identify a sponsor as
an official supporter of an event. Farrelly and Quester (2005) emphasized the long-term,
relationship-based approach of sport sponsorship to earn the maximum benefit for both
the sponsor and the sport organization. When a sponsorship agreement is made,
sponsors make strategic efforts that are designed to support and enhance the
sponsorship. The key goal of sport sponsorship activation is to link the sponsor and the
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sponsored property in the consumer’s mind (Gwinner, 2014). In the sport sponsorship
setting, the affinity, or positive feelings, toward the team, sport, or event becomes
associated with the sponsoring brand when sponsorship is activated and announced to
sport consumers.
Sponsorship differs from advertising because, unlike sponsorship, which involves
a fee paid in advance for future potential communication values, advertising offers a
more knowable and controlled communication (Meenaghan, 1991). In addition, third-
party (sponsored property) involvement exists (Speed & Thompson, 2000). Unlike
advertising, which is a marketing communication tactic that delivers concrete, direct
messages to its audiences, the sponsorship messages are not directly communicated to
viewers (Fleck & Quester, 2007). In many cases, sponsorship is presented to
audiences, but not actively addressed. Because of the less explicit and more indirect
characteristics of sponsorship, sponsorship executives put effort into generating
associations between the sponsored property and the sponsoring brand to obtain the
greatest outcome (Gwinner, 2014).
Sport Event Sponsorship
Brooks (1994) defined the possible platforms for sponsorship as the team, the
sport, the event, and the athlete. Among these platforms, the event is most commonly
associated with sport marketing (Shank, 2005). Similar to other platforms, the benefits
of sponsoring a sport event are increasing brand awareness and enhancing the
sponsor’s image. Besides these benefits, one unique advantage of being an event
sponsor is the opportunity to communicate with consumers directly at the event site.
Sponsors’ involvement in an event often provides a consumption-like situation in which
consumers can interact with the sponsors’ products and services at the event venue
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(Choi, Stotlar, & Park, 2006). Due to the on-the-spot nature of sport event sponsorship,
an appropriate match of sponsor and sport event is essential in decision making.
Companies can potentially sponsor sport events of different sizes. These can
range from mega events with high tourist demand and high impact to less impactful
medium-size events and smaller local events (Getz, 2008). Shani and Sandler (1996)
introduced the sport event pyramid, which they developed to categorize sponsorship
opportunities with different sizes and levels of events. The sport event pyramid consists
of five event levels: global, international, national, regional, and local.
Global events top the pyramid because they have the widest coverage around
the world. Such global events also generate the greatest interest among sports
consumers. According to Shani and Sandler (1996), there are only two truly global
events: the FIFA World Cup and the Olympic Games. Potential sponsors that want to
position themselves in the global market must pay large sponsorship fees for
involvement in a global event. The next tier, international events, has a relatively high
level of interest, but less than global events. International events, although often global
in scope, may have a lower level of interest in some countries. Examples of
international events include the Wimbledon Championship, the UEFA European
Championship, and the Pan-American Games. When companies want to reach a
narrower and more targeted global market and pay less money compared to the amount
associated with a global event, international events provide a good sponsorship option.
The third level of the sport event pyramid represents national events, which hold
extremely high interest in one or two countries. Examples of national events within the
United States are the World Series, the NCAA Final Four, and the Super Bowl. Regional
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events have a narrower geographic focus and are characterized by high interest levels
within the region where they take place. One example is the regional conference
tournaments associated with NCAA basketball. Local or what are often referred to as
small-scale events attract a small segment of consumers within a city or community.
High school sports and local races are examples of small-scale sport events.
Sponsorship Outcomes
Sponsorship research has focused on the effects or outcomes of sponsorship
activation. Cornwell et al. (2005) classified sponsorship outcomes as cognitive,
affective, and behavioral. Those outcomes depend on the goals of sponsorship
(Gwinner, 2014).
Cognitive outcomes mainly include sponsorship awareness, recall, and
recognition (Cornwell et al., 2005). For example, in Bennett’s (1999) study, unaided
sponsor brand recall, product category-aided sponsor brand recall, and fully aided
sponsor brand recall were measured after exposure to a sponsored soccer game.
Tripodi, Hirons, Bednall, and Sutherland (2003) also measured sponsor brand
awareness in the context of the Olympic Games, but in a more comprehensive way.
They used four different approaches to measure sponsor brand recall and found that
different approaches led to varying results. In an experimental setting, Johar and Pham
(1999) measured sponsors’ recall by presenting several sponsor–sponsored event pairs
and testing whether participants could match the sponsor and the event correctly.
Affective outcomes include consumer preference and attitudes toward
sponsorship and sponsor (Cornwell et al., 2005). Nicholls, Roslow, and Dublish (1999)
examined the brand sponsor preference of golf and tennis tournaments by asking which
brand the spectators preferred after being exposed to the on-site sponsorship. Many
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studies have also investigated attitudes toward the sponsor or attitudes toward the
sponsorship after individuals’ exposure to the sponsorship (e.g., Becker-Olsen & Hill,
2006; Madrigal, 2001). McDaniel (1999) used pretest and posttest studies to track the
changes in attitude toward a brand after watching a sponsorship-related advertisement.
Overall, the results of these studies found that there were positive affective outcomes
toward the sponsorship activation.
Considering that one of the ultimate goals for sponsors involved in sponsorship
agreements is to increase sales volume, the relevant behavioral outcome of the
sponsorship is the sport consumers’ increased intention to purchase the sponsor’s
product or service (Cornwell et al., 2005). Empirical research has investigated purchase
intentions (e.g., Madrigal, 2001; Mason, 2005; Speed & Thompson, 2000) because of
the difficulty in measuring the actual sales volume caused by the sponsorship activation.
Madrigal (2001), for example, measured the likelihood of purchasing a sponsor’s
products in the near future (within a 3-month period after being exposed to the
sponsorship) by asking the amount of effort (e.g., time for information searching)
consumers will put into buying a sponsor’s product. In the cases of affective and
behavioral outcomes, the assumption is that individuals can express their attitudes
toward the sponsors and intentions of future behavior, and their answers reflect the
sponsorship exposure’s effects (Cornwell et al., 2005).
Speed and Thompson (2000) presented sponsorship response as a sponsorship
outcome in their conceptual framework. In their model, sponsorship response consisted
of three different constructs: interest, favorability, and use. Interest is the extent to which
consumers believe sponsorship will affect their attention to the sponsor and its other
29
promotions. Favorability is the extent to which consumers are favorable toward the
sponsor. Use is consumers’ willingness to consider the sponsors’ product for their future
use. The current study adopted Speed and Thompson’s (2000) articulation of
sponsorship outcomes to explain the effect of sponsor–event fit on sponsorship
outcomes.
How Sponsorship Works: Schema Congruity Theory
The primary motivation for developing schema congruity theory was to offer an
alternative explanation for human information processing. Fiske’s (1982) theory of
schema-triggered affect suggests that consumers have preconceived ideas of the
partnerships between brands and their partners, so the theory was extended to explain
consumers’ processing of sport sponsorships. Consumers may use these schemas to
determine how well a brand (sponsor) and a sponsored event go together. The idea of
match or congruence between the sponsor and the event, activity, individual, or sport
has been used in advertising to evaluate the fit between a product and
endorser/celebrity (Till & Busler, 2000). With regard to sport sponsorship, it has been
used to evaluate the functional or image-related similarity between the event and the
sponsoring brand (Gwinner, 1997; Gwinner & Eaton, 1999).
Fit has been most commonly used as a key criterion explaining the success of
brand extensions. Congruity theory suggests that memory retention and information
retrieval are influenced by relatedness or similarity, so that, for example, a running
event sponsored by a running shoe brand seems appropriate and memorable.
Researchers of sponsorship have used schema congruity theory and the idea of
advertising schemas (McDaniel, 1999) to explain match-up effects. While the memory
effects of matching are supported by research, scholars have only considered the
30
effects of incongruity as a lack of fit and have not investigated them further. Congruity is
typically found to be positively related to memory of sponsorship stimuli (i.e.,
sponsorship recall) and other sponsorship outcomes (e.g., attitudes, behavior). The only
potentially negative consequences of congruence suggested by existing research so far
relate to heuristics used in recollection. For small brands, market prominence bias may
operate against them as the truly congruent sponsor when a competitor with a larger
market share is more readily recalled and mistakenly thought to be the sponsor (Johar
& Pham, 1999). In summary, extensive schema congruity literature highlights the
importance of perceived fit between the sponsor and sponsored event. Therefore,
sponsor–event fit is reviewed in the following section.
Sponsor–Event Fit
In the sponsorship context, fit (or congruence) between the sponsor brand and
sport events is the most frequently investigated concept (Cornwell et al., 2005). Many
sponsorship scholars have found that the fit between a sponsor and an event is an
antecedent of individual response to the sponsorship (Meng-Lewis, Thwaites, &
Gopalakrishna Pillai, 2013; Rifon et al., 2004; Roy & Cornwell, 2004; Ruth & Simonin,
2003); therefore, defining fit is key to understanding sport event sponsorship. Olson and
Thjømøe (2009) stated that fit is the most widely used theoretical concept related to the
processing of sponsorship stimuli. The popularity of fit in sport sponsorship research is
due to both the innate appeal of matching similar things together and the strong support
for its validity. Understanding the types and role of fit is also important from a practical
standpoint because it can help companies looking to sponsor events in the process of
selecting from the many events vying for their sponsorship dollars (Gwinner, 2014).
31
General Definition of Fit
The definition of fit tends to evolve from more general marketing literature, which
often focuses on fit between existing brands and new product extensions (Gwinner,
2014). Fit has been used to indicate consumer perceptions of similarity (but with
variations across studies), and applications adopting congruity theories have used a
variety of terminologies interchangeably. Mandler (1982) suggested that congruity is
represented by a match between the attributes of an object/product and a relevant
schema, whereas incongruity involves some mismatch. Park, Milberg, and Lawson
(1991) defined perceived fit as a function of product-similarity judgments in which
consumers compare some aspects of the existing set of products with those of the
extension product. The researchers examined the importance of two different bases that
consumers may use to evaluate an extension’s goodness of fit with the brand category.
The bases were product feature similarity and brand concept consistency. Hoeffler and
Keller (2002) defined brand association as abstract (or image-related) associations
focused on the brand’s image, whereas concrete associations refer to associations
pertaining to product-related attributes.
In the sponsorship literature, the fit or congruence construct has been defined in
numerous ways (e.g., functional-based, image-based, historical-relationship-based;
e.g., Becker-Olsen & Simmons, 2002; Fleck & Quester, 2007; Gwinner, 2014). Fleck
and Quester reviewed definitions of fit or congruence in the sponsorship literature.
Speed and Thompson (2000), Becker-Olsen and Simmons (2002) have all used the
term “fit.” The term “congruence” is mentioned by authors when they try to emphasize
the link between sponsor and sponsored property (d'Astous & Bitz, 1995; Otker &
Hayes, 1988) or a semantic link between the two or relatedness (Johar & Pham, 1999;
32
Lardinoit & Quester, 2010). Johar and Pham (1999) defined “relatedness” as the
semantic relationship that many consumers assume should exist between sport events
and the sponsoring companies. They suggested that “in sponsor identification tasks,
consumers rely on the semantic overlap between features of the event and those of
potential sponsors” (Johar & Pham, 1999, p. 300). The concept of congruence (Jagre et
al., 2001; Speed & Thompson, 2000) and incongruence (d'Astous & Bitz, 1995) have
also been mentioned in relation to sponsorship. McDaniel (1999) referred to the term
“match-up” because his study relied on the match-up hypothesis. Similarity (Gwinner,
1997; Gwinner & Eaton, 1999) and relevancy (McDonald, 1991; Rodgers, 2003) were
also used in some studies. Table 2-1 presents the various terms and definitions used to
introduce the concept of fit or congruence.
Dimensions of Fit
Dimensions of fit were mentioned briefly in the previous section, but this section
will present a more comprehensive review of dimensions of fit—whether it is
unidimensional or multidimensional. In early sponsorship research, fit was considered to
be rather unidimensional, meaning that the link between a sponsor and an event is
either strong or weak (e.g., d′Astous & Bitz, 1995). Speed and Thompson (2000) also
viewed fit as a unidimensional construct portraying the logical connection between a
sponsor and an event. In McDaniel's (1999) research, fit was referred to as the shared
attributes of the event and brand. Heckler and Childers (1992) explained that an
inconsistent fit between a sponsoring company and an event can be operationalized by
the degree to which the individuals perceive the relationship to be incongruent with their
expectations and preexisting knowledge structures associated with the theme.
33
Image-based fit vs. functional-based fit. A number of sponsorship researchers
have viewed fit as a multidimensional construct. For instance, McDonald (1991)
perceived fit as having two dimensions: direct relevancy, which occurs when a
sponsor’s product is used during the event, and indirect relevancy, which occurs when
some aspect of the sponsor is related to the event. Similarly, image-based fit and
functional-based fit have also been used in sponsorship research (Gwinner, 1997;
Gwinner & Eaton, 1999). In those studies, functional-based fit is used when the brand is
utilized during the event, and image-based fit is used when the brand’s image is
consistent with the event’s image (e.g., both brand and event are viewed as
prestigious). Gwinner (1997) clarified direct relevance as “functional-based similarity,”
which occurs when the sponsor’s product is used during the sponsorship event, and
indirect relevance as “image-based similarity,” which is a marriage between the
consumer’s core values and the values the sponsor and the sponsorship event
represent. Jagre et al. (2001) suggested that fit between an event and a sponsor is
expected when an individual’s knowledge of the sponsor’s functional similarity or image-
related similarity with the event is consistent. In their study, the authors perceived fit as
a bidimensional construct that consists of image and functional fit. Alcañiz, Cáceres,
and Pérez (2010) also conceived of fit as a bidimensional construct. They suggested
that functional fit is the affinity between sponsor and sponsored object, and therefore an
evaluation of functional fit involves a comparison between the features and functions of
the product or service being promoted and the characteristics of the sponsored object.
In Alcañiz et al.’s (2010) definition, image fit refers to the fit between brand associations
and the image of specific nonprofit organizations that embody a social cause. Image fit
34
is related to a general evaluation of the compatibility between brand image and social
cause. Compared to functional fit, image fit is a more symbolic, peripheral indicator that
involves a lower degree of cognitive elaboration by consumers.
Recent work has used a broad approach to fit that argues that consumers make
judgments about fit based on a number of dimensions. For example, Simmons and
Becker-Olsen (2006) found that high fit occurs when consumers perceive congruity
between the brand and the sponsored event in the areas of “mission, products, markets,
technologies, attributes, brand concepts, or any other key association” (p. 155). In their
assertion, Simmons and Becker-Olsen (2006) indicated fit’s multidimensionality.
Barone, Norman, and Miyazaki (2007) also suggested that company–cause fit can be
interpreted in multiple ways, including product (i.e., functional) congruence, image
congruence, and target market congruence. Olson and Thjømøe (2011) identified seven
dimensions of fit using a qualitative approach: (a) use of brand’s products during a
game either directly (e.g., athletes’ use of athletic shoes or sports drink) or indirectly
(e.g., spectators drink beer while watching game), (b) size similarity (i.e., the sponsored
object and brand are both prominent or not prominent), (c) audience similarity (i.e., the
sponsored object’s audience is the brand’s target segment), (d) geographic similarity
(e.g., national brand and national team), (e) attitude similarity (i.e., equal liking of both
the brand and the event), (f) image similarity (i.e., similar meaning or image of both the
brand and the sponsored object), and (g) length of the sponsorship relation (e.g.,
“unhealthy” beer brands were seen as fitting well with “healthy” sports because of their
longtime sponsorship link with the sponsored object). They also determined what
dimensions could predict the overall fit between sponsors and sponsored object.
35
Zdravkovic et al.'s (2010) research also posits fit’s multidimensionality. The authors
empirically found that congruence between a sponsor and a sponsee can be
established along numerous dimensions. They analyzed the content of the qualitative
responses and identified ten subdimensions contributing to the perceived overall fit
between a cause and a brand: (a) visibility of the relationship, (b) explicitness of the
relationship, (c) slogan compatibility, (d) mission agreement, (e) color or visual
compatibility, (f) common target market, (g) promotional activities compatibility, (h)
geographic compatibility, (i) local attributes, and (j) active involvement. This finding
stands in contrast to traditional unidimensional fit measures (e.g., d′Astous & Bitz, 1995;
McDaniel, 1999; Speed & Thompson, 2000).
In sum, there are numerous studies examining the dimensions of fit. However,
there is neither a unified explanation of the dimension of fit nor concrete evidence as to
whether a multidimensional understanding of fit explains the association between a
sponsor and an event better than the unidimensional notion of fit does. In addition, the
recent sponsorship studies that take a multidimensional view (e.g., Olson & Thjømøe,
2011; Zdravkovic et al., 2010) do not include the development of a global fit
measurement.
Issues of Measuring Fit
In consumer behavior studies, particularly those that used two or three simple
scales to investigate brand extension, researchers measured fit for the purpose of a
manipulation check. Lee (1995, p.212) measured the effectiveness of the schema
congruity manipulation using nine-point semantic differential scales on three questions:
(a) “How typical are these food items of Brand Name?” (“Very atypical–very typical”); (b)
“How similar are these items to those found in a usual Brand Name menu?” (“Very
36
different–very similar”); and (c) “How likely will you find these items at Brand Name?”
(“Very unlikely–very likely”). Milberg, Sinn, and Goodstein (2010) measured fit with two
seven-point scales. One measured fit: 1 = very low fit, 7 = very high fit; the other
measured sense: 1 = makes little sense, 7 = makes a lot of sense. Similar to brand
extension studies, research measuring fit has typically used nonspecific overall
measures (e.g., “not good fit–good fit”) to allow respondents to answer on whatever fit
basis they desired (Pracejus & Olsen, 2004; Rifon et al., 2004; Speed & Thompson,
2000; Till & Busler, 2000). For example, Pracejus and Olsen employed a general
measure of fit using one seven-point scale (1 = very low fit, 7 = very high fit). Rifon et al.
similarly measured the perceived congruence between a sponsor and website content
with a three-item seven-point semantic differential scale (not compatible–compatible,
not a good fit–a good fit, congruent–not congruent). Speed and Thompson measured fit
by asking direct questions (e.g., Do the sponsor and event fit together well?). Roy and
Cornwell (2003) also studied fit in a holistic way by asking respondents whether several
sets of opposite adjectives described the fit of the sponsored event (e.g., not a good fit–
good fit). Like Roy and Cornwell, Gwinner and Eaton (1999) used global fit measures in
their pretest. They also used sets of several adjectives that had either image-based or
functional-based similarities to capture the image fit between the sponsor and the event.
In some cases, research on fit has not measured the concept of fit at all; instead,
it has relied on “obvious” fitting sponsor–object pairings (e.g., Becker-Olsen & Simmons,
2002; Johar & Pham, 1999).
Multifaceted Measurements of Fit
Gwinner and Eaton (1999) used 11 adjectives taken from the brand personality
literature (Aaker, 1997) and found support for image transfer based on the higher
37
similarity of ratings across the personality adjectives for respondents who were given
sponsorship knowledge versus a control group, but they did not test whether their
personality-based measure predicted overall fit. Fleck and Quester (2007) developed a
five item scale to measure relevancy and expectancy as two dimensions of fit; they
found them to be highly correlated with a measure of “global fit,” but these measures did
not provide a basis for understanding why a particular brand was relevant or expected
as a sponsor. Barone et al. (2007) used three dimensions of fit with a three-item, nine-
point semantic differential scale (1 = very poor; 5 = neutral; 9 = very good) to measure
the fit between (a) the retailer’s core product line and the cause (functional fit), (b) the
images of the retailer and the cause (image fit), and (c) the target markets of the retailer
and the cause (audience fit). As mentioned in Section 2.3.2, Olson and Thjømøe (2011)
used seven dimensions of fit.
As illustrated above, there are previous studies evaluating the level of sponsor–
event fit with multifaceted measurement. Although some studies used an extensive set
of fit dimensions, there is no universal instrument to measure sponsor–event fit.
Therefore, the first step in developing such an instrument should be identifying the
domains of sponsor–event fit in a sport consumer’s mind when evaluating the level of fit.
Fit as a Predictor of Sponsorship Outcomes
There is evidence suggesting that when sponsoring brands fit well with the
sponsored event, the sponsorship activities are more effective in creating positive
sponsorship outcomes (e.g., brand recall, event attitude, and stock price; Gwinner,
2014). Fit has been shown to predict or influence a wide variety of sponsorship
outcomes such as sponsor recall, brand awareness, brand image, sponsor favorability,
positive attitude toward the sponsorship and sponsor, and purchase intentions (Becker-
38
Olsen & Simmons, 2002; Cornwell et al., 2005; Gwinner & Eaton, 1999; Olson &
Thjømøe, 2009, 2011; Rifon et al., 2004; Roy & Cornwell, 2004; Sneath et al., 2004;
Speed & Thompson, 2000). Cornwell, Weeks, and Roy (2005) classified sponsorship
outcomes as cognitive, affective, and behavioral outcomes, where those outcomes
depend on the goal of sponsorship (Gwinner, 2014).
Cognitive Outcomes
Koo, Quarterman, and Flynn (2006) explained the effect of perceived brand/sport
event image fit on consumers’ cognitive responses by applying a match-up hypothesis.
In an experimental setting, Johar and Pham (1999) measured sponsors recall by
presenting numbers of sponsor–sponsored event pairs and testing whether participants
could match sponsor and event correctly. The majority of studies that have investigated
the relationship between fit and brand recall suggested that higher fit is related to higher
sponsor recall or recognition accuracy (Cornwell et al., 2005). However, some research
revealed that relatively modest fit results in accurate recall (e.g., Johar et al., 2006;
Olson & Thjømøe, 2009). For example, Olson and Thjømøe (2009) revealed that mild
incongruence can result in higher sponsor recognition accuracy due to increased
attention or elaboration. To overcome these discrepancy issues in examining the
relationship between fit and the cognitive outcomes, Speed and Thompson (2000)
included interest in their model which can be referred as the extent to which consumers
believe sponsorship will affect their attention to the sponsor and its other promotions.
The goal of the current study is to confirm the predictive validity of sponsor–event fit.
Therefore, cognitive outcome was included in the model but as a way of measuring
participants’ belief in their cognitive response to the sponsorship thereby following the
lead of Speed and Thompson (2000).
39
Affective Outcomes
Affective outcomes include consumer preference or attitudes toward sponsors
and events (Cornwell et al., 2005). Many of these scholars have found a positive
relationship between fit and attitudes toward the sponsorship or sponsor (Becker-Olsen
& Simmons, 2002; Gwinner, 1997; Gwinner & Bennett, 2008; Koo et al., 2006; Olson &
Thjømøe, 2009; Speed & Thompson, 2000). Gwinner (1997) suggested that a good
congruent match between a sponsor’s image and an event image creates a more
positive consumer response than an incongruent match. Individuals assess fit based on
either functional or symbolic dimensions (Gwinner & Bennett, 2008), so the closer the fit
between the event and the brand, the higher the likelihood that these dimensions will be
transferred from the event to the brand (McDaniel, 1999; Olson & Thjømøe, 2011) and
the greater the effects (Olson, 2010). Speed and Thompson (2000) similarly stated that
image congruence between a sporting event and a sponsor brand will contribute to the
consumers’ favorability toward the sponsor. A strong match between event and brand
should positively affect individual attitudes toward the sponsoring brand, reinforcing the
associative link (Mazodier & Merunka, 2012; Till & Nowak, 2000; Wolfsteiner, Grohs, &
Wagner, 2015).
Behavioral Outcomes
Considering sponsorship as a marketing communication tool, the purpose of
which is to stimulate consumers’ behavioral action, the sponsorship literature has
investigated how attitudes toward sponsorship translate into behaviors such as WOM
and intention to purchase (Bennett, Cunningham, & Dees, 2006; Delia & Armstrong,
2015; Simmons & Becker-Olsen, 2006; Tsiotsou & Alexandris, 2009).
40
Behavioral intention in the sponsorship context generally refers to the intention to
purchase a sponsor’s product. Madrigal (2001) examined the positive influence of fit on
the likelihood of purchasing a sponsor’s products. In the relationship between fit and
behavioral intention, attitude toward the sponsor often plays a mediating role. Gwinner
and Bennett (2008) found that fit influenced consumers’ attitudes toward the sponsor,
which eventually had a positive influence on purchase intentions. Koo et al. (2006)
explained the effect of perceived brand/sport event image fit on consumers’ cognitive
and affective responses and the effects of consumers’ cognitive and affective responses
on purchase intentions by applying a match-up hypothesis.
WOM refers to “person-to-person communication between a receiver and
communicator whom the received perceives as noncommercial, regarding a brand, a
product, or a service.” (Arndt, 1967, p.5). Laczniak, DeCarlo, and Ramaswami (2001)
asserted that WOM is more influential on consumers’ brand evaluation than information
obtained from commercial sources (i.e., advertising). In sport consumer research,
Chang, Kang, Ko, and Connaughton (2017) claimed that corporate social responsibility
(CSR) activities can positively enhance sport fans’ WOM. Consumers will talk more
about a brand when the brand is perceived as having a positive impact on society (e.g.,
participating in philanthropic activities such as sport event sponsorship). Therefore,
WOM is considered as an effective sponsorship outcome. Recent studies concluded
that sponsor–event fit ultimately generates more positive conversation between
consumers (i.e., WOM; Delia & Armstrong, 2015; Visentin et al., 2016), because
sponsor–event fit increases customer familiarity towards sponsor brand (Söderlund,
2002). The familiarity caused by sponsor–event fit is positively associated cognitive and
41
affective outcomes of sponsorship (e.g., brand satisfaction), and in turn, WOM
(Söderlund, 2002). Therefore, the positive influence of sponsor–event fit on cognitive
and affective outcomes and WOM was tested in the quantitative study.
Moderating Role of Involvement
Shank and Beasley (1998) described sports fans as a unique group of
individuals because many of them are highly involved and have an emotional
attachment to sport. Along with this view, the role of involvement has been suggested in
the previous sponsorship literature (e.g., Meenaghan, 1991, 2001; Sirgy, Lee, Johar, &
Tidwell, 2008). In the sport marketing literature, fan involvement refers to the extent to
which consumers identify with, and are motivated by, their engagement and affiliation
with particular leisure activities (Meenaghan, 2001, p.106). Sirgy et al., (2008)
empirically tested the moderating role of involvement which impacts the strength of the
positive influence of fit on sponsorship outcomes (i.e., loyalty with the sponsoring brand
in their study). They revealed that the influence of fit was greater when the consumer
was highly involved with the sponsored event than when the consumer was less
involved. When spectators are highly involved with a sport event, the positive feelings
they have towards the event are more likely to transfer to the brand, and may eventually
lead to positive sponsorship outcomes (Gwinner & Eaton, 1999; Madrigal, 2001;
Meenaghan, 1991, Sirgy et al., 2008). The current study therefore, examined the effect
of involvement in moderating the relationship between sponsor–event fit and its
consequences.
Summary
This literature review suggests that sponsor–event fit plays a key role in
generating positive sponsorship outcomes. Therefore, the evaluation and measurement
42
of sponsor–event fit is important in sport sponsorship research. The associative network
memory model helps to understand the sponsor–event link and how associative
information is used in sponsorship-related information processing. However, there is no
clear explanation as to what type of information and association consumers use when
they evaluate sponsor–event fit. Some sponsorship research has attempted to advance
a more complex understanding of sponsor–event fit. Nevertheless, there is no universal
description of sponsor–event fit. Schema congruity theory posits that greater fit
produces better sponsorship outcomes such as cognitive (e.g., brand recall, brand
recognition), attitude (e.g., attitude toward sponsorship, attitude toward sponsor), and
behavioral intention (e.g., purchase intention, WOM). As such, the current study focuses
on developing a global measure of sponsor–event fit and investigating the relationship
between sponsor–event fit and sponsorship outcomes.
43
Table 2-1. Definition of congruence in the sponsorship literature
Source Definition
Otker & Hayes, 1988 Link between sponsor and event on a continuum from very weak to very strong
McDonald, 1991 Direct relevancy when sponsor’s product can be used in the event Indirect relevancy when some aspects of the sponsor relate to the event
d’Astous & Bitz, 1995 Link between sponsor and property
Gwinner, 1997 Similarity based on functional aspect when the brand is used by event participants Similarity based on image when the image of the event is linked to the image of the brand or not
Didellon, 1997 Perceived alignment: Overall positive judgment of the logical connection between sponsor and property
McDaniel, 1999 Match-up between sponsor and event: Perceived similarity between sponsor attributes and event attributes
Johar & Pham, 1999 Relatedness: Existence of a semantic link between sponsor and event
Gwinner & Eaton, 1999
Same as Gwinner (1997)
Speed & Thompson, 2000
Fit or congruence: Attitude toward the sponsor–event pair and degree to which the pair is perceived as well matched
Jagre, Watson & Watson, 2001
Congruity or fit: Same definitions as Heckler & Childers (1992) and Mandler (1982) Fit: Consistency with prior expectations and schemas
Becker-Olsen & Simmons, 2002
Native fit: Degree to which the sponsor and the cause can be deemed to go well together, regardless of any communication Created fit: Fit induced by communication and not intrinsic to the organizations involved
Rodgers, 2003 Relevancy: Natural proximity between the sponsor’s products and the sponsored object
Rifon, Choi, Trimble, & Li, 2004
Same as Gwinner (1997)
Alcañiz, Cáceres, & Pérez, 2010
Image fit: The fit between the brand associations and the image of the specific nonprofit organization that embodies the social cause Functional fit: The attributes and functions of the product category performed by the company and the type of social cause sponsored
44
CHAPTER 3 METHODS
As aforementioned, the purpose of this study was to explore domains of sport
sponsor–event fit and examine the relationship between fit and its dependent variables.
A sequential mixed methods approach was employed to synthesize quantitative and
qualitative research methods (Teddlie & Tashakkori, 2003). Creswell and Plano Clark
(2007) describe mixed methods research in the following manner:
It focuses on collecting, analyzing and mixing both quantitative and qualitative data in a single study or series or studies. Its central promise is that the use of quantitative and qualitative approaches, in combination, provides a better understanding of research problems than either approach alone (p. 5).
Mertens (2014) noted that mixed methods sequential data collection forms occur when
one form of data provides a basis for the collection of another form of data. In other
words, mixed methods research attempts to synthesize quantitative and qualitative
research. In this study, the qualitative study provided the theoretical foundation for the
quantitative study, which empirically tested some of the propositions raised in the
qualitative findings and provided researchers with a greater ability to generalize the
results. In the remaining part of this chapter, an overview of the data collection
procedure, participants, instrumentation, and data analysis procedure is presented.
Methods: Qualitative Phase
A qualitative grounded theory approach using focus group discussions was
adopted to answer three research questions. Considering that audiences of sport event
sponsorship are the general public who watch such events in person or via broadcast,
anyone over the age of 18 who had watched at least one recent mega or major sport
event either in person or via broadcast was eligible to participate in the study. The list of
45
events included in the study are presented in the data collection section. In each focus
group, questions were asked in an interactive group setting where participants were free
to talk with other participants. According to Morgan (1998), focus group interviews may
have a comparative advantage to individual interviews by gathering data more
efficiently, especially if there is a synergic group interaction among participants.
Data Collection
After reviewing studies that used focus groups for data collection, it became clear
that there is no concrete rule for a specific number of groups. Calder (1977) suggested
that once the focus group moderator could effectively and accurately anticipate how the
next group was going to respond to the questions, the appropriate number of groups
had been reached. The term for this phenomenon is theoretical saturation (Calder,
1977). As an illustration of this process, Livingstone and Lunt (1994) described the
following: “the number of focus groups was determined by continuing until comments
and patterns began to repeat and little new material was generated” (p. 181).
Another issue to be mindful of when selecting the appropriate number of focus
groups is how the range of views expressed may depend on socio-demographic factors.
On the topic of using focus groups in social research, Kitzinger (1994) suggested a
large number of groups in hopes of collecting as many diverse perspectives as possible.
It is important to note that this issue does not hinder all researchable topics; thus, a
large number of groups is not always necessary. Also, an increased number of groups
breeds greater complexity of analysis. Considering these issues, six groups of
participants were recruited for the current study.
Participants were recruited via flyers posted on the University of Florida’s
campus (e.g., board in front of Library West) during summer 2015. Social media
46
websites, such as “University of Florida (Gators) Easiest Courses” on Facebook, were
also used to post the research invitation (see Appendix A). Preceding data collection,
institutional review board (IRB) approval and informed consent were obtained (see
Appendix B for IRB approval). Potential participants interested in this study were
directed to complete a short online screening questionnaire that asked them about their
prior experiences with three recent mega sport events (the 2012 London Summer
Olympic Games, 2014 Sochi Winter Olympic Games, and 2014 FIFA World Cup), one
major sport event (the 2015 Wimbledon Championship), and demographics (see
Appendix C). Four sport events were preselected as recent mega or major sport events
considering the large amount of global attention paid to these events and their impacts
on the global community (Ferrand et al., 2012). Although the Wimbledon Championship
is smaller in size and possible impact compared to other mega events, it has been
included with a belief that the unique characteristics of the event (i.e., luxurious, high-
end, and regional based) may encourage a richer discussion among participants.
Using purposive sampling to balance the focus groups for prior event experience,
the participant profile generated from the questionnaire data was used to select
potential participants and to invite them to the focus groups. The six mixed-gender
groups consisted of people with a diverse range of sport involvement, which provided a
wide array of perceptions on the topic of sport event sponsorship. To account for a
range of sport involvement in each focus group, the researcher asked sport involvement
questions in the online recruitment questionnaire and constructed the groups to account
for the variability. Shank and Beasley’s (2005) eight semantic differential items were
used to measure sport involvement.
47
A cognitive mapping technique which allows the investigation to go deeper into
an individual’s core perceptions of the object was employed for this study. A cognitive
map is a representation of the relationships among elements of a given situation
(Ahmad & Azman, 2003). Participants in each group were asked to place visual cards
representing three mega sport events (summer and winter Olympic Games and the
FIFA World Cup) and one major sport event (the Wimbledon Championship) and 30
sponsoring brand names on the table to reflect how well (or not) each entity fit together
in a sponsorship context. Then the top ten sponsoring brands of each sport event (Acer,
Adidas, Bridgestone, Budweiser, Castrol Oil, Coca-Cola, Dow, Emirates Airlines, Evian,
GE, Hertz, HSBC, Hyundai-Kia Motors, IBM, Johnson and Johnson, Lavazza, Lanson,
McDonalds, OI, Omega, Panasonic, P&G, Ralph Lauren, Rolex, Samsung, Slanzenger,
Sony, Toyota, VISA, Yingli) were selected considering the size of the sponsorship
agreement (i.e., sponsorship fee). All group members were encouraged to participate in
the decision-making process. To ensure that respondents were not contaminated by
any established concepts of fit, they were not given any definitions or explanations of fit
prior to the exercise beyond the simple instructions to “put the brand and sports pictures
closer and farther apart depending on how well they fit together in a sponsorship
situation, with closer together representing a better fit” (Olson & Thjømøe, 2011). After
completing the cognitive map, participants were asked about the extreme cases on their
perception map (i.e., those that were seen as fitting extremely well and those that fit
extremely poorly). Participants were also asked about the outcomes of sport
sponsorship and the importance of a sponsor–event fit to generate positive sponsorship
48
outcomes, as well as to provide their demographic background (see Appendix D). All
focus group sessions were audio recorded.
Participants
The sample consisted of 17 males and 18 females for a total sample of N = 35
participants in six groups. To protect the identity of the participants, the researcher
assigned pseudonyms to each individual. Table 3-1 presents the list of participants and
their brief demographics. The participants ranged from 21 to 45 years of age with a
mean of 29.4 years. Thirty-four out of 35 participants had watched either the 2012
London Summer Olympic Games or 2014 Sochi Winter Olympic Games, while only six
people had watched the 2015 Wimbledon Championship. Thirty-one people out of 35
had watched the FIFA World Cup. Sport involvement was measured using seven-point-
scale semantic differential items (M = 5.07, SD = 1.33). The participants were
categorized as an individual with a “low,” a “medium,” or a “high” sport involvement
based on the mean score of sport involvement relative to the 33rd percentiles (Sport
Involvement Score = 4.65) and 67th percentiles (Sport Involvement Score = 5.60). Each
focus group was then comprised of two to three participants at each level of sports
involvement (i.e., low, medium, and high involvement).
Data Analysis
Each group interview was transcribed verbatim from the audio recordings and
then analyzed as each phase of data collection was completed using constant
comparison method (Strauss & Corbin, 1990). Prior to data analysis, the researcher
carefully read the interview transcripts. The data were subsequently analyzed using
QSR NVivo 10.0 qualitative data analysis software. Strauss and Corbin’s (1990)
procedure for coding grounded theory data that consists of open, axial, and selective
49
coding was employed. First, open coding was conducted to identify concepts and
related properties within the data. The researcher read through each transcript several
times and then started to create tentative categories based on the meanings that
emerged from the data. Second, through a process of axial coding, the relationships
between categories and relevant subcategories were identified guided by Gwinner’s
(1997) bidimensional view of sponsor–event similarity and Cornwell et al.’s (2005)
sponsorship outcomes model. Lastly, in the selective coding stage, categories were
combined and integrated to suggest a grounded theory of sponsor–event fit.
Methods: Quantitative Phase
The purpose of the quantitative phase was to develop a sponsor–event fit
measurement scale and to confirm the predictive validity of the scale by examining the
relationships between its fit and its dependent variables. The following sections describe
the instrumentation, data collection procedure, participants, and data analysis.
Instrumentation
Instrument development. The questionnaire was designed to allow participants
to answer the questions about sponsor–event fit based on their preexisting perceptions
and knowledge of actual pairs of sport events and sponsoring brands. Hence, a sport
event and its official sponsoring brand (e.g., the Olympic Games and Coca-Cola) were
presented to the participants as the study context at the beginning of the questionnaire.
Participants were asked to answer questions regarding their perceptions of the given
event and brand. The study context of a particular version of the questionnaire had to
be one that allowed participants to easily describe their perceptions of the event and
brand. Therefore, well-established events and brands were considered as foci for this
study. Meanwhile, the study objective was to develop a global measurement of the fit
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between a sponsor and an event that could be utilized regardless of the event size and
characteristics. To achieve this, several versions of the questionnaire were developed—
each version asked about different events and brands of various sizes and
characteristics in an attempt to achieve wider generalizability of the study results. Below
the steps for the study context selection are described.
First, as in the qualitative study, the Olympic Games, the FIFA World Cup, and
the Wimbledon Championship were chosen as events because they are established,
large-scale events (i.e., mega and major events). Additionally, the Daytona 500 and the
New York City (NYC) Marathon were added to the event list because both events are
smaller in scale than the aforementioned large-scale events, but they still retain
international or national interest (Baade & Matheson, 2000; Cobb & Olberding, 2007).
The Daytona 500 is included in the top 30 sport events in 2017, with 11.9 million
viewers watching the event (Paulson, 2017). The NYC Marathon is the world’s largest
marathon, with 51,999 participants and 51,394 finishers in 2017 (NYC Marathon, 2017).
The list of five sport events is adequate to attain generalizability because it covers (a)
multi sports events (i.e., the Olympic Games) and single sport events (i.e., the FIFA
World Cup, the Wimbledon Championship, Daytona 500, NYC Marathon), (b) team
sports (i.e., the FIFA World Cup) and individual sports (i.e., Daytona 500, NYC
Marathon), and (c) luxury sports (i.e., the Wimbledon Championship) and non-luxury
sports (i.e., the FIFA World Cup, NYC Marathon). Sport events with a professional
league (e.g., NFL Super Bowl, NBA Finals, and MLB World Series) were not considered
because the events are associated more with the sponsors of the teams in the league
versus the sponsor of each event which would have been confusing. Second, the top 10
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sponsoring brands of each sport event were selected by the size of the sponsorship
agreement, which is the same procedure used in the qualitative study. A pilot test was
conducted to examine the awareness of the sponsoring brands and the perceived
overall fit between the sponsor and event after obtaining institutional review board
approval and informed consent (Appendix E). The overall fit was measured by Speed
and Thompson’s (2000) seven-point Likert-type scale measurement with five items.
Appendix F presents the pilot study questionnaire. The complete list of the brands,
brand awareness, and the perceived overall fit between the sponsoring brand and the
event can be found in Table 3-2. Among the sponsoring brands that had significant
brand awareness (brand awareness > 80%), one high-fit brand and one low-fit brand for
each event were selected based on the results of the pilot test. The final ten sponsor–
event pairs are as follows: the Olympic Games–VISA, the Olympic Games–Acer, the
FIFA World Cup–Adidas, the FIFA World Cup–Castrol Oil, Wimbledon Championship–
Rolex, and Wimbledon Championship–Häagen-Dazs, Daytona 500–Goodyear, Daytona
500–Microsoft, NYC Marathon–New Balance, and NYC Marathon–Dunkin Donuts.
Sponsor–event fit initial instrument. The main purpose of this study was to
identify domains of fit and develop a scale to measure sponsor–event fit. As such,
measurement items for a new scale can be generated “from [either] the extant literature
or by the scale authors” (Netemeyer, Bearden, & Sharma, 2003, p. 95). Following this
notion, measurement items for three dimensions of sponsor–event fit (image-based fit,
functional-based fit, and brand characteristics) were adopted from existing scales first.
Although previous researchers have examined fit construct as a multidimensional
construct within the general sport sponsorship context (Olson & Thjømøe, 2011) and
52
the context of sponsorship for social causes (Zdravkovic et al., 2010), no previous study
has explored the subdimensions of fit in the sport event sponsorship context. Therefore,
many of the measurement items used in this study were derived from the results of the
qualitative study and added as original items to the questionnaire. All sponsor–event fit
measurement items for the current study were measured on a seven-point Likert-type
scale, with responses ranging from 1 (strongly disagree) to 7 (strongly agree).
To measure the active and healthy image subtheme, adjectives (e.g., “active,”
“healthy,” and “energetic”) were extracted from the qualitative study findings. Gwinner
and Eaton (1999) used similar adjectives (e.g., “leisurely,” “exciting,” “active,” and
“energetic”) to measure the similarity of image transfer from event to brand. They
presented 10 adjectives to describe each sport event first and asked the following
question: “My image of the [sporting event name] is consistent with my image of [brand
name] which was assessed using a seven-point Likert-type scale where 1 = ‘strongly
disagree’ and 7 = ‘strongly agree”. Adopting Gwinner and Eaton (1999)’s findings, five
items were developed to measure the subtheme active and healthy. In regards to the
subtheme of caring community, three items were derived from the qualitative focus
group discussions. To measure the prominence subtheme, this study adopted Olson
and Thjømøe’s (2011) items which were originally operationalized as three semantic
differential scales. In the current study, the researcher changed them to Likert-type
scales. In addition to Olson and Thjømøe’s (2011), one additional item (“(Brand X) has
the financial means to sponsor (event Y).”) was added to measure the prominence
subtheme. The subtheme of socioeconomic status of consumer is a concept similar to
Zdravkovic et al.’s (2010) target market construct which was defined as the extent to
53
which the brand’s and the cause’s target markets overlap. Therefore, three items from
Zdravkovic et al.’s (2010) scale to measure target market were adopted for this study.
Olson and Thjømøe (2011) measured ‘use by participants’ (How likely is it that
the products from [sponsor] are used by the participants in [object]?) and ‘audience use’
(When watching [object] on television, how likely are audience members to be using
[sponsor] products?), which is similar to this study’s functional-based fit construct.
However, no previous study had measured the subdimensions of functional-based fit as
was done in the current study. Therefore, the items for functional-based fit were derived
from the qualitative findings.
Zdravkovic et al.’s (2010) subthemes of fit, such as slogan, and visuals/color, are
similar in concept to this study’s subtheme of symbolic features. Therefore, the current
study adopted Zdravkovic et al.’s item but modified it to better capture the results of the
qualitative findings. The subtheme of product coverage was an original item based on
the qualitative data. Therefore, three items were newly developed. In terms of
geographical characteristics, Zdravkovic et al. measured geographical characteristics as
geographic compatibility using three seven-point Likert scale items, and Olson and
Thjømøe (2011) measured geographical characteristics as geographic similarity using
two seven-point semantic differential scale items. By modifying those items and adding
new items from the qualitative findings, the current study used three seven-point Likert
scale items. Regarding the duration of sponsorship, Olson and Thjømøe (2011)
explained that it is not possible to ask respondents to test variations in sponsorship
duration. However, in the current study, the concept ‘length of sponsorship’ did not aim
to measure the actual length of sponsorship duration, but rather aimed to capture the
54
perceived time duration of sponsorship in the consumers’ minds. Therefore, three
measurement items for long-term relationship as sponsor were developed. Table 3-3
summarizes the initial list of measurement items for the current study.
Expert review. Because the newly added items were included in the sponsor–
event fit scale for the current study, a panel of experts who have expertise in both the
measured and methodological issues associated with survey research (e.g., faculty
members and doctoral students in sport management) reviewed the items to confirm
content validity. Hardesty and Bearden (2004) suggested using a panel of experts for
the initial stage of scale development to reduce an initial item pool and to determine
which items are to be further analyzed (Hardesty & Bearden, 2004). First, the
researcher created a pool of potential items based on the literature review and
qualitative study findings, refined construct definitions, eliminated redundant items, and
shared the list of measurement items with a panel of experts. Rubio, Berg-Weger, Tebb,
Lee, and Rauch (2003) suggested that a sample size of ten experts is the most
appropriate number. However, the researcher initially distributed the questionnaire to 19
sport marketing scholars as a panel of experts satisfying concerns about the response
rate and received answers from nine experts. The expert review is meant to ensure
adequate representation of the proposed construct, reduce item redundancy, and refine
the wording of the items. Specifically, the experts were asked to review survey items to
evaluate the relevance, representativeness, and clarity of each item for measuring the
intended constructs. An email cover letter which briefly explained the purpose of study
and an attached questionnaire was sent out to the panel of experts (See Appendix G).
The panel members were asked to rate questionnaire items on three criteria (i.e.,
55
relevance, representativeness, and clarity) using the five-point scale (1 = unacceptable,
2 = poor, 3 = acceptable, 4 = good, 5 = excellent). Relevance was assessed as
intentions of the need to demonstrate how closely each item was pertinent to the
construct; representativeness was assessed by how much each item represented the
construct; and clarity was assessed by judging how clearly each item was worded. The
experts also contributed any comments concerning suggestions or concerns regarding
the proposed survey items.
After reviewing the experts’ assessment on each measurement item and
suggestions, the following changes were made: First, the product coverage subtheme
which had belonged to brand characteristics was removed. Several experts mentioned
that it was difficult to understand and somewhat overlapped with the ‘operational use’
subtheme. One item (The product or service category of brand X is related to the sport
that is played in the event Y) was moved to the operational use theme. Second, the two
subthemes of image based fit were renamed following the panel of experts’ suggestions
(caring community to goodwill toward sport, and prominence to compatibility). Third, one
of the compatibility items measuring financial capability (i.e., the brand X can afford to
sponsor the event Y) was removed complying with the experts review that “The item
doesn’t capture neither the intended construct nor the concept of ‘fit’.
Pretest. The final questionnaire, revised after the expert review, was pretested
with seven undergraduate and four graduate students in a research methods class
using cognitive interviews. Drennan (2003) described cognitive interviewing as a survey
pretest method that improves face validity of questionnaires by identifying problematic
questions (Drennan, 2003). After the cognitive interview process was complete, final
56
revisions to the questionnaire including correction of typos and minor grammatical
errors were made.
Final Instrument. The final questionnaire contained three main parts: sponsor–
event fit constructs, sponsorship outcomes, and demographics (See Appendix H for
questionnaire).
The final sponsor–event fit instrument contains three subthemes: image-based
fit, functional-based fit, and brand characteristics. A total of 46 observed items of the
sponsor–event fit scale (17 items for image-based fit; 14 items for functional-based fit;
15 items for brand characteristics) were derived from literature review and qualitative
results and refined by aforementioned instrument development steps.
Speed and Thompson (2000) measured sponsorship outcomes with three
constructs: interest (3 items, α = .91), favorability (3 items, α = .95), and use (3 items, α
= .94). The cognitive outcome measurement items in Speed and Thompson’s (2000)
research were not intended to measure actual recall or brand awareness, but
consumer’s belief in their cognitive response to the sponsorship. The current study
utilized Speed and Thompson’s (2000) nine measurement items which represent three
variables measuring sponsorship responses. In addition to Use, WOM was included as
the behavioral outcome of sponsorship. Visentin et al.’s (2016) 3-item measurement (α
= .79), which was adapted from Harrison-Walker (2001), was used to measure WOM.
The detailed items were: “I will mention brand X to others frequently”; “I will tell more
people about brand X than I’ll tell about other brands”; and “I will not miss an opportunity
to tell others about brand X.” To assess these items, a seven-point Likert-type scale
where 1 = “strongly disagree” and 7 = “strongly agree” was used.
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To measure event involvement, Shank and Beasley's (1998) eight-item Sports
Involvement Scale (SIS) was adopted and modified. The SIS was assessed using a
seven-point semantic differential scale
Items measuring demographic characteristics of participants were also included
in the questionnaire. The questions measured gender, age, ethnicity, employment
status, education, marital status, and household income with fixed choice
questionnaires.
Data Collection
Data were collected via a web-based survey using Qualtrics research software
provided by the University of Florida. Because Hair, Anderson, Babin, and Black (2010)
suggested a sample size of 200 or more participants when performing CFA and SEM,
this study aimed to collect a total of 500 responses (10 versions of the questionnaire X
50 participants per version). To ensure confidentiality and anonymity, study participants
were not asked to provide their names, addresses, e-mail addresses, or any other
identifiable information. As such, there was no list connecting participants’ names or e-
mail addresses to their survey responses. A web-based survey was used because it
has several advantages over traditional mail surveys, including the ability to reach a
geographically diverse sample, lower costs, and a shorter data collection period
(Dillman et al., 2009). Participants were compensated one US dollar ($1) upon
completion of the survey. Participants were recruited using Amazon’s Mechanical Turk
(MTurk) tool (more details follow in the participants section). Prior to data collection,
institutional review board approval and informed consent was obtained (Appendix I).
58
Participants
Similar to the focus group participants, in the quantitative phase, the survey
participants consisted of individuals who had recently watched one of the given sport
events in person or via broadcast and who were aware of the brand that was to be
shown to them in the research protocol. As the survey population required a general
population that had been exposed to the particular sport events and sponsorship,
survey participants were recruited using Amazon MTurk. Buhrmester, Kwang, and
Gosling (2011) found that MTurk participants are significantly more diverse than typical
American college samples, and that the data obtained from MTurk are at least as
reliable as data obtained via traditional methods. Another advantage of MTurk is that
participants can be recruited rapidly and inexpensively compared to traditional methods.
The qualifications function of MTurk was used to make sure no respondent participated
in the studies more than once. To qualify for the study, potential respondents were
asked two screening questions (see below). Only those who were over the age of 18,
had watched the selected event, and were aware of the selected brand were chosen to
participate in the survey.
Screening Questions:
1. Have you ever watched the following sport event as a spectator onsite or through any form of media?
2. Do you know [the brand]?
A total of N = 595 usable responses were obtained through the online data
collection procedure. Participants ranged in age from 20 to 76 (M = 36.26, SD = 10.75).
The sample was predominantly male (n = 356), married (n = 268), college educated (n =
411), full-time employed (n = 449), and White/Caucasian (n = 453). The median of the
59
participants’ 2016 annual household income was between $50,000 and $59,999. Of the
sample, 19% reported income less than $30,000 (n = 113), whereas only 4.2% reported
income more than $150,000 (n = 25). The detailed sociodemographic characteristics of
the sample are provided in Table 3-4. The majority of the sample had purchased the
product or service of the sponsoring brand at least once (n = 478) (Table 3-5.)
Data Analysis
Data analysis included several steps and was conducted using STATA 14
statistical modeling software and SPSS 20.0 statistics software. First, descriptive
statistics were calculated for all constructs to gain an overall understanding of the data
and to investigate concerns related to coding errors, outliers, skewness, and kurtosis.
Second, to answer research question 1 (RQ1) and to test hypothesis 1 (H1), the validity
and reliability of the sponsor–event fit scale was assessed. To assess the factor
structure and the discriminant and convergent validity of the constructs within the
sponsor–event scale, CFA was conducted in accordance with Kline’s (2011)
recommendations. Cronbach’s alpha coefficient and the average variance extracted
(AVE) score for each factor was used to assess internal consistency and construct
reliability. The overall fit of the measurement model was evaluated using the following fit
indices (Kline, 2011): chi-square to degree of freedom ratio (χ2/df), root mean square
error of approximation (RMSEA), standardized root mean square residual (SRMR),
comparative fit index (CFI), and the Tucker-Lewis index (TLI). Factor loadings were
further reviewed to ensure the statistical significance of relationships among constructs
and their measurement items. Third, the structural equation model was evaluated to
answer research questions 2 and 3, (RQ2 and RQ3) and to test hypotheses 2, 3, 4, and
5 (H2, H3, H4, H5) using the same model fit indices with the measurement model (i.e.,
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χ2/df, RMSEA, SRMR, CFI, TLI; Kline, 2011). The validation process involves the
examination of the structural relationships between fit and sponsorship outcomes. Last,
a multigroup SEM and invariance tests of structural model were conducted to test
hypothesis 6 (H6), which posited the moderating effect of Involvement.
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Table 3-1. Qualitative study participant pseudonyms and demographic information
Participant Pseudonym
Gender Age Sport
Involvementa
Watched 2012
London Olympics
Watched 2014 Sochi
Olympics
Watched 2014 Brazil
World Cup
Watched 2015
Wimbledon Championship
Group 1
Alex M 27 5.5 Yes Yes Yes No
Kate F 30 5 Yes No Yes No
Colin M 39 3.63 Yes Yes Yes No
Chloe F 47 6.13 Yes Yes Yes No
Oliver M 29 4.75 Yes Yes Yes Yes
Susan F 26 7 Yes Yes Yes Yes
Group 2
Amy F 31 5.25 Yes Yes Yes No
Bridget F 29 4.25 Yes Yes No No
Owen M 29 2.75 Yes No No No
Peggy F 32 5.13 Yes Yes Yes No
Robin M 31 4.63 Yes Yes No No
Steve M 28 6 Yes No Yes Yes
Yulia F 27 5.25 Yes Yes Yes No
Group 3
Eddie M 45 4.88 Yes Yes Yes No
Lisa F 25 7 Yes Yes Yes No
Matt M 33 6.5 Yes Yes Yes Yes
Mac M 33 4.13 Yes No Yes No
Sam M 28 7 Yes Yes Yes Yes
Wendy F 27 5.25 Yes Yes Yes No
Group 4
June F 23 6.25 Yes Yes Yes No
Jolly F 27 3 Yes Yes No No
Nancy F 26 3.63 Yes Yes Yes No
Peter M 21 1.38 Yes Yes Yes No
Shawn M 35 4.5 Yes Yes Yes No
Sarah F 30 3 Yes No Yes No
Group 5
Alice F 30 5.5 Yes Yes Yes No
Bailey F 37 4.5 No Yes Yes No
Cameron M 21 5.63 No No Yes Yes
Lee M 21 5.13 Yes No Yes No
Ian M 29 7 Yes Yes Yes No
Group 6
Barbara F 26 6.25 Yes Yes Yes No
Jim M 22 6.5 Yes Yes Yes No
Leo M 31 5.25 Yes No Yes No
May F 26 5.75 Yes Yes Yes No
Rachel F 27 4.13 Yes Yes Yes No
Note. a=Sport involvement was asked using a seven-point-scale semantic differential items (8 items in total) and mean scores were reported in the table
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Table 3-2. Sponsoring brand awareness and perceived sponsor–event fit from pilot study
Brand awarenessa Fit scoreb Sport event Sponsoring brand Frequency Percent (%) M SD Olympic (N = 30)
VISA 30 100.0 4.91 1.46 Samsung 30 100.0 4.31 1.73 Coca-Cola 30 100.0 4.29 1.88 Panasonic 30 100.0 3.66 1.77 Acer 30 100.0 3.50 1.65 GE (General Electric) 29 96.7 3.50 1.73 Bridgestone 26 86.7 3.94 1.53 P&G 19 63.3 3.95 1.59 Omega 18 60.0 5.20 1.00 Dow 14 46.7 3.09 1.62
FIFA (N = 29)
Adidas 29 100.0 5.90 1.10 Sony 29 100.0 4.22 1.82 McDonalds 29 100.0 3.19 1.79 Johnson & Johnson 29 100.0 2.81 1.39 Hyundai-Kia Motors 28 96.6 3.43 1.66 Budweiser 28 96.6 3.26 1.62 Castrol Oil 26 89.7 2.48 1.34 Emirates 23 79.3 4.76 1.53 OI 2 6.9 3.00 0.82 Yingli 1 3.4 5.00 1.02
Wimbledon (N = 30)
Rolex 30 100.0 5.50 1.25 IBM 30 100.0 3.57 1.70 Hertz 29 96.7 3.77 1.48 Ralph Lauren 27 90.0 5.36 1.22 Evian 27 90.0 5.24 1.26 Häagen-Dazs 26 86.7 3.23 1.66 HSBC 22 73.3 4.34 1.56 Slanzenger 12 40.0 5.88 1.21 Lavazza 8 26.7 5.13 1.20 Lanson 5 16.7 4.42 2.10
Daytona500 (N = 28)
Ford 28 100.0 6.20 0.98 Chevrolet 28 100.0 6.15 0.94 Microsoft 28 100.0 3.33 1.64 Monster Energy Drink 27 96.4 5.10 1.32 3M 27 96.4 4.35 1.58 M&M 27 96.4 3.79 1.48 Goodyear 26 92.9 6.42 0.77 Coors Light 26 92.9 5.19 1.21 Sirius XM 25 89.3 4.62 1.58 Camping World 13 46.4 3.52 1.42
NYC Marathon (N = 19)
United Airlines 19 100.0 4.22 1.75 Dunkin Donuts 19 100.0 3.02 1.76 New Balance 18 94.7 5.56 1.49 Airbnb 18 94.7 4.43 1.69 UPS 18 94.7 3.64 1.49 Tiffany &Co. 18 94.7 3.51 1.89 PowerBar 17 89.5 5.40 1.49 Fitbit 16 84.2 5.95 0.88 Michelob Ultra 11 57.9 2.96 1.33 Abbott Laboratories 5 26.3 3.44 1.64
Note. a=Brand awareness is number of those who answered “yes” for the question “do you know Brand A?” b=Fit score was asked using a seven-point Likert scale items (5 items in total) and mean scores were reported in the table
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Table 3-3. Initial list of measurement items for expert review
Variables Sources Items
Image-based Fit
Active and healthy image
Adopted from Gwinner and Eaton (1999) and modified
(Brand X) and (event Y) share an active image. (Brand X) and (event Y) share an energetic image. (Brand X) and (event Y) share a healthy image. (Brand X) and (event Y) share a leisurely image. (Brand X) and (event Y) share a sporty image.
Caring community
Derived from qualitative study
(Brand X) is an organization that helps the community. (Brand X) invests in sports. (Brand X) shares an image with (event Y) because they support young athletes.
Prominence Adopted from Olson and Thjømøe (2011) and modified
The sizes of (brand X) and (event Y) are similar. The role of (brand X) in the community is as important as that of (event Y). (Brand X) and (event Y) have similar reputations. (Brand X) has the financial means to sponsor (event Y).
Socioeconomic status of consumer
Adopted from Zdravkovic et al. (2010) and modified
The characteristics of consumers of (brand X) and spectators of (event Y) are similar. The socioeconomic characteristics of those who use (brand X)’s product or service are also those of (event Y)’s fans. (Brand X)’s target market or users remind me of the people associated with (event Y).
Functional-based Fit
Athlete use during the game
Derived from qualitative study
Athletes in (event Y) often use (brand X)’s product or service during a game. It is common for athletes to use (brand X)’s product while they play in the (event Y). I can see athletes wearing (brand X)’s product in (event Y).
Operational use Derived from qualitative study
The product or service of (brand X) is used to operate (event Y). The product or service of (brand X) is helpful in making (event Y) successful. It is natural that the product or service of (brand X) is used to operate the (event Y). (Event Y)’s organizers need to use (brand X)'s product or service to manage the game.
Audience consumption during the game
Derived from qualitative study
When watching (event Y) on television, viewers are likely to consume the product or service of (brand X). When watching (event Y) on site, spectators are likely to consume the product or service of (brand X). I would think of using (brand X)’s product or service while watching (event Y) on television. I would think of using (brand X)’s product or service while watching (event Y) on the spot.
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Table 3-3. Continued
Variables Sources Items
Brand Characteristics
Symbolic feature
Adopted from Zdravkovic et al. (2010) and modified
(Brand X)’s use of color or visual attributes is similar to the colors/images associated with (event Y). (Brand X)’s slogan is a clever play on words to incorporate themes and values of (event Y). (Brand X)’s logo is well matched to (event Y). (Brand X)’s symbolic features are complementary to (event Y).
Geographical characteristics
Adopted from Olson and Thjømøe (2011) and Zdravkovic et al. (2010) and modified
The geographical origin of (brand X) is similar to the location where (event Y) takes place. The geographical target market of (brand X) is similar to the location(s) associated with (event Y). The locations (either global or local) associated with (brand X) are similar to the locations associated with (event Y).
Product coverage
Derived from qualitative study
The range of products or services that (brand X) covers matches well with (event Y). The product or service category of (brand X) is related to the sport(s) that are played in (event Y). The variety of product service range of (brand X) is similar to those of (event Y).
Length of sponsorship
Derived from qualitative study
(Brand X) has been sponsoring (event Y) for a long period of time. (Brand X) and (event Y) have a long-term relationship, associating them with each other. I have known (brand X) to be a sponsor of (event Y) for a long period of time.
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Table 3-4. Quantitative sample descriptive characteristics
Demographic Variables (N=595) Frequencya Percent (%)
Gender (n=595)
Male 356 59.8
Female 239 40.2
Employment status (n=595) Student 29 4.9
Employed full-time 449 75.5
Employed part-time 44 7.4
Unemployed/Looking for work 21 3.5
Homemaker 31 5.2
Retired 13 2.2
Other 8 1.3
Race/Ethnicity (n=593) American Indian/Native American 2 0.3 Asian 51 8.6 Black/ African American 46 7.8 Hispanic/Latino 33 5.6 White/Caucasian 453 76.4 Other 8 1.3
Education (n=594) Less than high School 3 0.5 High School / GED 50 8.4 Some college 130 21.9 2 year degree 79 13.3 4 year degree 260 43.8 Master’s Degree 59 9.9 Doctoral Degree 13 2.2
Marital status (n=595) Single, never married 248 41.7
Married without children 62 10.4
Married with children 206 34.6
Divorced 21 3.5
Separated 6 1.0
Widowed 7 1.2
Living w/ partner 45 7.6 Note. a=Frequency is number of those who answered “yes” for the question “Have you ever purchased or used the
product or service of (brand X)?
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Table 3-5. Purchase experience of sponsoring brand among main quantitative study participants
Sponsor–event pairs Frequency Percent (%)
Olympic VISA (N=73) 72 98.6
Acer (N=80) 53 66.3
FIFA World Cup Adidas (N=59) 57 96.6
Castrol Oil (N=56) 34 60.7
Wimbledon Rolex (N=60) 13 21.7
Häagen-Dazs (N=59) 55 93.2
Daytona500 Goodyear (N=58) 48 82.8
Microsoft (N=49) 49 100.0
NYC Marathon New Balance (N=55) 53 96.4
Dunkin Donuts (N=46) 44 95.7
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CHAPTER 4 RESULTS
Results: Qualitative Phase
The results revealed that sponsor–event fit can be depicted through three main
themes and related subthemes, all of which were based on the focus group discussions.
The following sections outline each theme of sponsor–event fit. The two main themes
(image-based fit and functional-based fit) are in line with Gwinner’s (1997) bi-
dimensional view of sponsor–event similarity, whereas the third main theme (brand
characteristics) was inductively identified from the data. Sponsorship outcomes in the
sport consumer’s mind were also identified from the data. The sponsorship outcomes
were presented in accordance with Cornwell et al.’s (2005) model: cognitive (brand
recall and image enhancement), affective (liking and preference), and behavioral
(purchase intention).
Image-Based Fit
The first theme, image-based fit, can be defined as the similarity between the
event image and the brand image. Participants described their perceived image of the
given sponsoring brand and target consumers and explained how well or poorly those
perceived images matched their perceptions of the given mega or major sport events. In
most cases, an image-based fit was described with adjectives such as active, energetic,
global, and prestigious. The results revealed that image-based fit can be classified into
four subthemes: active and healthy, caring community, prominence, and socioeconomic
status of the consumer. In line with Becker-Olsen and Simmons’s (2002) view of native
fit and created fit, the results showed that some subthemes were based on intrinsic
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similarity, whereas other subthemes portrayed image-based fit as induced by the
sponsor’s marketing message.
Active and healthy image. Considering the core value of sport, the perceived
images of the mega and major sport events that were asked about during the focus
group were described as active, energetic, and healthy. Therefore, sponsoring brands
that have such images were mentioned as well-matched sport event sponsors. Energy
drink brands are one example that matched with sport events, as Colin, a 39-year-old
man who described himself as a casual skateboarder, explained, “Red Bull Extreme
Sports events for skateboarding comes to mind. It makes sense that those would be
paired together because it’s an extreme drink and skateboarding is an extreme sport.
They both are so active and alive.” Although active and healthy lifestyles are embedded
in the core value of sport, participants also perceived products that are unrelated to
sport as having an active and sporty brand image. Oliver, a 29-year-old who is
moderately involved in sports, stated after Colin, “I notice that Hyundai has something
sporty, so it can be anywhere, any sport game. I can’t name one particular event, but it’s
sporty for me.” When asked to put Coca-Cola on the map, Amy, a 31-year-old Coca-
Cola lover, mentioned, “I think closely, more closely with FIFA than with the Olympics
because Coke is more active, more energetic, and the World Cup has that craziness.”
The term “healthy” was frequently used when participants recalled weird sponsor–brand
pairs. The two most well-known sponsors of the Olympic Games, McDonald’s and
Coca-Cola, were mentioned as mismatched sponsors across all six groups. Bailey, a
37-year-old diehard soccer fan from Poland, explained:
I always think of McDonald’s and the Olympics. That one is always really weird to me. I just feel like it’s very contradictory. Do you really think these
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athletes are eating unhealthy McDonald’s? I don’t know, honestly. Same with Coke. It’s like they have those Cokes spilling over. I’m like, “Are they really drinking Coke before they run 100 meters?”
Steve, whose father used to serve as a coach on the national volleyball team for the
Olympic Games, had a similar sentiment, “It's something very weird. Everyone knows
Coca-Cola and McDonald's in the Olympic Games as main sponsors, but they don't fit
because they are super unhealthy if you go to a sport event, I think.” Similar to the
cases of unhealthy fast-food brands, controversial perceptions of tobacco brands also
emerged. Robin, a 31-year-old nonsmoker, stated, “Cigarettes, they’re known to reduce
your endurance, and, you know, sporting events are all about endurance and how much
you can do.” Amy, who was in the same group, had a counterargument to Robin, “The
Marlboro man is supposed to be the rugged man who can take on every terrain and la-
di-da. He’s like the macho thing around. That can represent a strong sportsman, right?”
In sum, for active and healthy themes, participants appraised the similarity between a
sponsor’s image and an event’s image based on the inherent images of the brand.
Caring community. The second subtheme of image-based fit is caring
community. Companies often seek sponsorship opportunities as a part of their CSR
program activation. Therefore, sport sponsorship can be closely linked to the image of a
caring community. Female participants who were highly involved in sport tended to
perceive a better fit between the sponsor and the event when they were inspired by a
sponsor’s goodwill to the community. One way a sponsoring brand can show its
goodwill to the community is by supporting young amateur athletes. Yulia, a 27-year-old
former Olympian, remembered a sponsor’s campaign during the Olympic Games, “I saw
that during the past Olympic period, Procter & Gamble advertised a lot, like cheer for
the mom who raised the Olympian, something like that. So they support their
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Olympian’s mom.” Similarly, Susan, a 26-year-old diehard soccer fan and a former FIFA
World Cup volunteer, appreciated how McDonald’s cared for youth athletes,
“McDonald’s, they are doing a lot of philanthropic things for children related to soccer,
so I think the company is a really good match with the World Cup.” Rachel, a 27-year-
old student majoring in sport management, also values McDonald’s efforts to encourage
sport participation among the younger generations and linked the brand to both the
FIFA World Cup and the Olympic Games:
FIFA is focused on youth, youth sports, I mean youth soccer, and to develop in a youth sense. That’s what McDonald’s is doing now, focusing on children and kids, to play and be a family. The slogan, you remember? “Inspire a Generation” was the slogan of 2012’s London Olympic Games. That’s why McDonald’s is doing this. It is inspiring a new generation of sport.
Another example related to the caring community mentioned in the focus groups was
Nike’s support for women athletes. Bailey, a 37-year-old woman, said, “What Nike did
with women was brilliant. They just captured this entire, huge market because they
sponsored a lot of events with women’s sports––athletes, there you go, women
athletes.” Those caring community images of the sponsors, however, are usually
created by commercials and related marketing communications. Hence, some of the
participants were unconvinced of the sponsors’ intrinsic motives for sponsorship,
especially when the size of the company and event did not match. While Susan rated
McDonald’s CSR efforts highly, Alex, a 27-year-old who used to play youth baseball,
said:
If the big companies try to mark down or, for example, sponsor a local youth sport, I would be skeptical about it because they are trying to improve their image, and it’s kind of––I don’t like it. I doubt the event and sponsor go well together.
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Recent concerns regarding the ability to make mega sport events environmentally
sustainable were recognized by some participants. They tended to link environmentally
friendly brands with the sports event. Oliver explained:
What I could make sense is if any of these mega events had a big environmental campaign, and they’re going to have––this is going to be our cleanest environmental event ever. So we’re partnering with this clean energy company along with the host of other similar companies. That would make sense if it was packaged correctly.
Environmental issues were also mentioned when Chloe, a 47-year-old public relations
doctoral student, explained the perceived misfit between brand and event, “Every time I
think of Dow Chemicals in the news, it’s because they’ve had like a spill or explosion or
whatever. So they shouldn't be sponsoring any event.”
Prominence. The third subtheme of image-based fit is prominence. It is worth
noting that the main focus of this study is mega sport events, and the term mega is
directly related to the term big as Roberts (2004) stated that “mega-events are out of the
ordinary, international, and simply big” (p. 108). Bridget, a 29-year-old who is
moderately involved in sport, associated the Olympic Games with its sponsor well,
“Coca-Cola is a big brand, and the Olympic Games is a mega event, and then it’s just
very easy to associate it with that.” Similarly, Nancy, a 26-year-old who would rather
watch the Olympic Games than the FIFA World Cup, said, “I always feel that the
overarching brand like Apple or Microsoft would sponsor the Olympics, but not Acer.” In
addition to the sponsor’s size in relation to the event, participants also consider the
sponsor’s presence in the global market when they estimated the similarity of the event
and the sponsor. Susan said, “To be sponsors of those events, I think they must have
some global standards, at an international level, like a nation.” Jim, a 22-year-old highly
active sports fan, also linked a big conglomerate with the Olympic Games, “I’d put GE in
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the Olympics because I think it has the broadest international base.” Mac, a 33-year-old
who was relatively less involved in sport, tried to link brands in unhealthy categories
(e.g., fast food, beer) to the mega sport event by considering their impact in the global
community, “Coca-Cola or McDonald’s or beer companies. These companies have a lot
of money, plus such events make such a great impact on a global scale.” Participants
cited not only the company’s actual size and fame in the market as important, but also
whether it had the funds to spend on a sponsorship. They perceived a low level of fit
when they thought the brand did not have enough money for such a large sponsorship
agreement. Mac explained:
My only concern is if they can afford to sponsor the Olympics because it involves a lot of money. Acer is not big enough to sponsor the Olympics from my perspective. Well.., let’s think of a second-tier event rather than those mega events…I would say the Stanley Cup, which starts tonight. A little less prominent brand might be advertising there.
Shawn, a 35-year-old soccer fan from Turkey, had a slightly different view on
affordability. He tried to understand the given misfit situation with this example, “If I see
a brand I don’t know sponsoring any mega event, I’d be like, ‘They must have money to
be able to advertise in the Olympics.’ Ambitious, maybe.” Interestingly, the prominent
image-based fit was mentioned frequently when participants linked a non-sport related
brand to the events as mentioned above.
Socioeconomic status of consumer. The fourth subtheme of image-based fit is
the socioeconomic status of the consumer. When the group discussion went on to the
reasons or motivations that sponsors might have to support mega sport events,
participants pointed out that an event should have an audience group that overlaps with
the sponsoring brand’s target group, especially in terms of socioeconomic status. The
socioeconomic status of the consumer was the most frequently mentioned subtheme
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among all the image-based fit subthemes. The sponsor–event fit based on the
spectator/consumer profile was explained with terms such as prestigious, luxurious, less
valued, and high-end/low-end class. Wimbledon was mentioned across all groups and
matched with high-end, prestigious brands. Kate, a 30-year-old who is moderately
involved in sports, mentioned:
I think because those who fly that airline [Emirates] are super-rich. It’s not like a British Airways or a Delta or anything like that. This is a really small, super exclusive and they probably watch Wimbledon type of events. I’ve never flown on it, but, in my head, Emirates seems like an elite airline, so I did put it near Wimbledon.
Wendy, a 27-year-old who did not watch the last Wimbledon tournament, also
explained, “I think it [Wimbledon] goes with the luxury brands, and the luxury at the
higher end of Wimbledon means fashion companies like Rolex or Ralph Lauren. That’s
what ties them.” Sarah, a 30-year-old who rarely follows sports news, disassociated
McDonald’s from Wimbledon with this explanation, “I just feel like McDonald’s probably
knows that their audience isn’t really Wimbledon. I just don’t think they [McDonald’s]
would be down near there [between the Olympic Game and the FIFA World Cup].”
Compared to the Wimbledon Championship, the Olympic Games and the FIFA World
Cup are linked to mid to low-end brands. Matt, a 33-year-old highly involved sports fan,
said, “Bridgestone is a fairly quality tire, but it’s not high-end. So just with the Olympics.”
Cameron, a 21-year-old who watched the last FIFA World Cup and Wimbledon
Championship, explained the characteristics of the FIFA World Cup viewer in detail:
The World Cup gives me more of that roughened look, a little bit of being on a couch, drinking a beer, and shouting ‘Goal!’ People from silver-spoon families and it’s very––they [the FIFA World Cup fans] are a little more rough around the edge and not so smooth. I don’t know. That’s just my perception, so beer or soft drinks goes along with FIFA.
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Sometimes participants considered the product category rather than the brand itself. For
example, Owen, a 29-year-old who has never watched the Wimbledon Championship,
linked the banking industry with the Wimbledon Championship, but he did not specify
HSBC’s image when ascertaining the fit between the brand and the event, “Let’s put
HSBC near Wimbledon. Wimbledon has more rich crowds, richer crowds. This is like a
crowd, and banking people will benefit more from the richer crowd. They have like a
high-end image.” Leo, a 31-year-old who also did not watch the last Wimbledon
Championship, perceived Lanson, a French champagne brand, as a good fit for
Wimbledon, “I know that champagne should be positioned obviously higher. I’ve never
heard of the brand, I mean it could be cheap also, but it’s just that Wimbledon is known
for having wealthier clients. I guess champagne has a wealthier image.” Some
sponsoring brands have an image that is considered more “for everyone,” so they were
mentioned to fit well with any event. For example, Lisa, a 25-year-old highly involved
sports fan, said, “Omega is more of an everyman kind of watch, so it can go along with
any brand.”
Functional-Based Fit
The second theme, functional-based fit, pertains to consumers’ beliefs about
sponsors’ helping the event to be successful by offering their products or services
(Gwinner, 1997). In other words, brand usage by various types of event participants
(athletes, event organizers, and spectators) tends to capture the higher functional-
based fit. The results suggested three subthemes for functional-based fit: athlete use
during the game, operational use, and audience consumption during the game.
Athlete use during the game. The first subtheme of functional-based fit is
athlete use during the game. If athletes used the sponsor’s product, especially sporting
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goods, while playing sports, participants linked those sponsoring brands directly with the
sport event. Eddie, a 45-year-old who watched the last FIFA World Cup, gave this
simple, straightforward example, “In the World Cup, soccer players are using an Adidas
football in the game. It’s an official ball of FIFA World Cup. It even has a special name
for the ball. I don’t remember but…” Even non-sport-related brands could be linked to a
sport event if athletes use them during a game. Peggy, a 32-year-old who watched
various Olympic sports, stated, “The Olympics have all kinds of different sports.
Definitely, there are some sports using tires, so I can definitely see this [Bridgestone]
over there [near the Olympic Games]. Maybe Bridgestone could be a cycling sponsor or
a cycling team sponsor in the Olympic Games.” Sam, a highly involved 28-year-old
sports fan, tried to link an oil company to the sports event, “Castrol is an oil company,
right? We should have NASCAR here [on the map]. If we put NASCAR on the map, it
would make sense to me because they will use gasoline there for car racing.”
Participants also mentioned sports players’ outfits when they discussed athletes’
product use in a game. Although sportswear brands are considered to be sponsors of
individual players, participants tended to perceive good functional fit if the players
playing in the sport event wear them. Colin linked Nike to Wimbledon, “I remember that
Andre Agassi wears it. He has Nike as a huge sponsor. So I will put it with Wimbledon.”
Alice, a 30-year-old who regularly plays tennis, also wanted to associate Ralph Lauren
closely with the Wimbledon Championship, “Ralph Lauren is something like a classic
tennis outfit. Imagine the classic white polo t-shirt with the collar thing and tennis players
wearing it.”
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Operational use. The second subtheme of functional-based fit is operational
use. In the preparation stage of mega sport events, event organizers determine the
different categories they need to fill and find sponsors for each category (e.g., official
beverage sponsors, official telecommunication sponsors). When the product or service
of a sponsoring brand is used during the event, not by the athletes but by the event staff
for operational purposes, participants still consider the event and the sponsor to have a
good fit. In terms of operational use, watch brands for timekeeping are frequently
mentioned. As Oliver noted, “With soccer, the timing is very important I think. This is
one being like, we’re the official clock of timing the games! So watch brand can match
with World Cup.” Yulia similarly observed:
Sports like skiing or swimming or track and field, they use a lot of clock brands. For example, Rolex or Omega, they use a lot of sponsors from the clock brands. For example, like in the 2012 London Olympics or the 2008 Beijing Olympics, they used Omega clock brand for the swimming and track and field.
In the same group, Amy added, “I also saw maybe Omega in the Olympics during
swimming or something like that because, ‘The time was sponsored by...’ Let’s put
Omega near Olympic Games then.” Another group also mentioned the timekeeping
features of watch brands, including Lee, a 21-year-old who likes watching track and
field:
Every time I heard something like a new record came up, it was like this. I think it started with a T, but I’m not sure which it is, but it was like a timer. Clocks and sport events are well matched in that sense.
Ian also mentioned the watch brand for tracking ball speeds during a tennis match, “In
the Wimbledon tennis, when a tennis player smashes a ball, we can see the how much
speed he has. So that is a Rolex I will put with Wimbledon.” Participants were
sometimes unable to describe the exact role of a sponsor’s product or service, but they
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still believed that it was being used to manage the game. Cameron, who loved to play
tennis, mentioned, “Actually IBM, I think, is sponsoring Wimbledon with their
scoreboard, something like system. IBM logo is shown on the scoreboard.” Sponsors
could match with an event even if their product is used not during the sport itself but
during an after-event (e.g., a ceremony). As an example, Cameron pointed out:
They do like a lot of champagne stuff with Wimbledon. At the ceremony, they cheer with champagne. Champagne, they do that at the end of—like the winner they go to this lounge area that they have, and they always open a bottle of champagne.
When a sponsor’s product or service is not sport-related or directly used in the game,
participants perceived a low level of fit. Sam from China came up with an example
involving a Chinese solar energy company:
One of the sponsors of the World Cup is from China, it is called Yingli. It’s a solar energy factory, and I don’t know what their relationship with World Cup is. I mean, their business is about solar energy that has nothing to do with soccer. It’s weird.
When participants tried to recall odd sponsor–event pairs in terms of functional fit, they
seemed to think in terms of product category rather than individual brand, as Bailey did,
“I recently saw an ad for something. It was like the official sponsor of English
Champions League—English premier league and I was like, “Really, how?” It was such
an absurd pairing. It was like loans or a banking company.” In group four, Peter, a 21-
year-old who rarely follows sport news, and Jolly, a 27-year-old soccer fan, had an
interesting argument. Like Sam and Bailey, Peter said, “Acer? I have no idea how this
would fit into any of the event, laptop with a sporting event. I’ve never thought about it.”
Jolly replied, “Everyone who watched the game might use a computer for searching live,
up-to-date news about the game they were watching. I do that all the time. It’s possible.”
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This conversation brought up the needs of the next subtheme, audience consumption
during the game.
Audience consumption during the game. Functional-based fit includes not
only direct use by event participants, but also indirect use by the audience. Bailey
doubted that players would consume beer, but she still noted the match between beer
brands and the FIFA World Cup:
With like beer and soccer, it’s absolutely a fan-focus thing. Players can’t drink, they run half marathons twice a day. I mean, there’s no way they’re going to be able to drink a beer, but because beer is consumed by soccer spectators so much, it’s very much associated with World Cup.
As Bailey observed, participants closely associated beverage brands with the sport
event when they thought of spectators in the stadium. Barbara, a 26-year-old, highly
involved sports fan, said, “Coke could just be an official sponsor to provide soft drinks,
but for spectators. They sell their product at the concession in the stadium.” Susan
similarly linked Coca-Cola with the FIFA World Cup, “People drink Coke a lot when they
are watching games, especially soccer maybe. In the stadium, literally everybody drinks
Coke.” Susan also brought up an interesting idea about how spectators could use
mobile devices during the event, “Samsung produces mobile devices. People always
take pictures at the sports event. For me, it makes sense they sponsor the Olympics.”
Participants also considered rental car brands relevant because they are used by onsite
event spectators. June, a 23-year-old enthusiastic soccer fan, explained the need for
car rental to get between the FIFA World Cup host cities, “Not like the Olympics or
Wimbledon, the World Cup has different host cities in the host country. You need to
travel. So with that affordable rental car, you can travel within Brazil with Hertz.” Jolly
then added, “In the Olympics, they also have Rent-a-Car on the side of the stadium.
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They bring a lot of tourists there. Tourists, you need cars. So, Hertz, go for it.” Focus
group participants in this study mentioned not only direct use during sport, but also
indirect use by offsite viewers during an event when discussing the theme of functional
based fit. They also mentioned beverage brands frequently in this regard, as Robin
remarked:
Beer commercials go pretty good with sports especially in America, because like you say, consumers, they are in that mode. They are using it already. So if you give them a sponsor, like if you’d show them the banners on TV and everything during the sport event, they can kind of relate to it like, “Oh, let’s try that. Let’s try that beer.” I mean they already have a beer in their hand so it’s very, very close to—it’s on their mind.
Similarly, Bailey stated, “Yes, these people watching the Olympics on TV actually use
water because they have to drink it.” Participants further associated electronic brands
that produced televisions closely with major events because viewers worldwide watch
such events. Barbara explained this well, “Some of these tech companies—they’re not
necessarily directly related to the sports. Maybe indirectly, like, Samsung makes TVs
which most . . . people want a bigger screen to watch sports on.” May, a 26-year-old
sport management major student, added, “Actually, before the Olympics, a lot of places
reported Samsung has been selling a lot of TVs right before the Olympics. Just so
people can watch.” Colin had a similar point of view and linked GE with all three given
events, “GE produces TV and the three major events also have broadcasting rights. So
that’s why . . . people watch those games with GE products.” Rachel, an Olympics fan,
had nostalgic thoughts of the Olympics and Panasonic, “My childhood was with
Panasonic. I remember the brand since I was a child, but I mean back then, I watched
the Olympics with a Panasonic TV.” Participants’ remarks reveal flexible explanations
regarding indirect functional image fit as compared with a direct functional based fit.
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They had creative conversations in which they tried to link a given sponsor and an
event. For instance, when someone did not perceive a fit between a brand and an
event, others came up with alternative justifications. For example, Peggy remarked:
What comes to my mind are all the car brands for weird sponsors of sport games. They have various car brands as sponsors for any different kind of events, even from like college football, whatever event, or even all the way to the large sport event like Olympics. They are everywhere. Somehow, I’m always wondering like, “Why?” [Laughter] I don’t know how effective actually that can convince people saying, “Hey, try our car” when sponsoring sport events. I don’t know.
To which Robin replied:
That’s how they get to the stadium to watch the game. They drove their cars to the stadium and then went to watch the game. No, I mean, if we want to find the reason, we can find the reason, but that probably won’t be the reason why the companies will sponsor an event. If we sit here and try to find a reason why car companies would sponsor an event, we will find a reason.
In another discussion in the same group, Robin perceived a low fit between a coffee
brand and summertime sport events, “I'm sitting in a stadium, hot. [Laughter.] It's very
difficult that you're going to crave coffee if you're sweating like crazy. You’re like, ‘No
way.’” However, Alex linked coffee with the Winter Olympic Games, “Maybe if there is a
Winter Olympics, maybe the coffee company goes as well. People might drink hot
drinks while watching it.”
Brand Characteristics
The third theme, brand characteristics, explains sponsor–brand association
based on the sponsoring brand’s features rather than the brand’s perceived image. Four
subthemes were identified in brand characteristics: symbolic features, product
coverage, geographical characteristics, and long-term relationship as a sponsor.
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Symbolic features. The first subtheme of brand characteristics was driven by
some participants who linked sponsoring brands’ names, logos, and colors with certain
sport events. If those various types of symbolic features remind participants of a
particular event, they perceived a good fit between the sponsor and the event. For
example, Matt linked a brand name with a sport event, “Regardless of what their
business, what their brand is doing that’s just the name Acer, Acer’s serving ace in
tennis. So it’s kind of related to tennis.” For Kate, the Evian logo is positively associated
with the Olympic Games, “The logo is the French Alps. So when I see the mountains, I
think of the Winter Olympics. Evian fits well with the Olympic Games for that reason.”
The symbolic features of a product can also be associated with the logo of an event, as
Owen mentioned, “I see circles, and I think tires. I mean, instead of Olympic rings, I can
put in Bridgestone tires.” A sponsoring brand is sometimes linked to a specific color,
providing an example of perceived similarity. Bridget mentioned, “Coca-Cola, they use
the color red. They are so red. And it gives it a very warm feeling, and FIFA soccer is
crazy. For me, red is for craziness.” Lee also described the colorful features of Swatch
products, “I’d put Swatch more like towards the Olympic Games because they have the
whole color thing going on, which is variety and diversity like the Olympic Games. It
reminds me of the Olympic Games.” Leo guessed what kind of brand Castrol is based
on its logo. He explained, “Castrol, to me, comes across, like the colors come across as
Italian or like the high-end formula race cars. So, I think I’m putting those with
Wimbledon.”
Product coverage. Whether a brand produced a wide range of products or niche
products, participants often mentioned the product coverage of the sponsoring brand,
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which is the third subtheme of brand characteristics. For example, Peggy described
Acer as a general electronics brand and perceived it as matching well with the Olympic
Games, “Acer not only have computers but they also have a lot of these types of
products. They also have televisions, everything. So it goes along with the Olympics.
The Olympics are broader in general. It's an everything game.” About Toyota, she
added, “Toyota has a wider diversity of cars. That's why I would like to say Toyota will
be more like for everything than like focused. Let's put it with the Olympics.” Procter &
Gamble was frequently mentioned in regard to its broad product range. As Mac noted,
“It is so big like every product we are using we might not find out but it’s really from
them like the shampoo, the soap.” Cameron linked Procter & Gamble with the Olympic
Games for the same reason, “If you go home right now and pick out any chemical you
have in your home, they probably made 92% of it. And I would definitely see that type of
company in the Olympics, yes, so general and broad.” GE shared a similar perception
with Procter & Gamble. As Nancy stated, “GE is definitely in the middle to me. I feel that
they’re sponsoring everything. Even their name is General Electric.” There was also an
interesting comment regarding the broadness of FIFA by Shawn in group four:
You know what? We didn’t put many sponsoring brands near the FIFA World Cup. Why is that? Maybe the World Cup is too broad. I mean everybody in the world is watching it. It’s for everyone. So not many brands are associated with it. It’s just too broad to be linked to a specific brand.
In regard to sporting goods, participants frequently discussed whether a brand was
produced for a specific sport. Participants were wondering whether the brand was
specialized for a particular sport. Cameron pointed out what Adidas is famous for, “They
[Adidas] are a big soccer brand. They were the first ones to patent soccer shoes. So it
can be linked with the World Cup.” Susan wanted to know more about Slazenger:
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Do they do shoes? Do they do a specific sport? Do they do apparel? I don’t know. For those sports goods company I’d better know what they’re for and then . . . if they are famous for soccer shoes, I’ll put in FIFA.
Geographical characteristics. Olson and Thjømøe (2009) saw geographical
similarity as a subcategory of the fit construct. Similar to Olson and Thjømøe, this study
revealed that geographical characteristics affect some participants’ perceptions in
evaluating the degree of sponsor–event fit. Therefore, geographical characteristics were
comprised as the second subtheme of brand characteristics. Country of origin was
frequently mentioned across all groups. Bridget described the importance of the country
of origin, “It will make more sense when the brand is from the hosting country.” But
when it comes to the case of a global brand, participants did not care much about the
sponsor’s location, as Robin stated, “I think Hertz will go with anything which has more
widespread, global appeal. Okay. It doesn’t matter where the brand comes from.”
Participants tended to mention the country of origin when they knew the brand was
recognized in the specific region they came from, as Yulia did:
Evian comes from a European country. That’s why it goes to Wimbledon. Maybe people who watch it in Wimbledon, they all tend to have a lot of people in Europe so maybe they are more familiar with the Evian brand than Coca-Cola.
Cameron also linked a brand and an event based on the country of origin, “Oi? If it’s a
Brazilian telecommunication company, you go Oi with the FIFA World Cup because it's
from Brazil. It's like soccer.” Participants asked each other where the brand originated
when they thought the brand was not global enough or they were not sure where it
came from, suggesting that the country of origin is important. Lisa asked the group:
Is it an Italian coffee brand? England is tea. So I don’t think the coffee would be good for Wimbledon. But if it's Italian, hmm . . . Or maybe they’re closer with the World Cup because soccer is big in Italy.
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Similarly, Wendy doubted, “I don’t know that they would sponsor tennis. I don’t know if
it’s a big thing in England or a big brand in London.” The brand’s target audience as well
as the location of the brand’s sponsor mattered to the participants. Matt stated, “It may
be international but it’s typical, I think the brand is more known to people in the United
States and so, think about where we might have more American viewers or individual
spectators.”
Robin also considered where the event audience is located:
World Cup, where is it watched? It's watched in the Middle East a lot. Now given that the World Cup has a good presence in the Middle East, Fly Emirates and World Cup matches. Emirates Airlines I think they could very well sponsor this as well, but I think they’re going to get more bang for their buck doing the World Cup for their particular realm.
Jim made a similar observation regarding Emirates Airlines, “Emirates Airlines goes with
the World Cup because it flies a lot between Europe and the Emirates, where a lot of
football fans are.” But again, some participants perceived that the target region did not
seem to matter for global brands; for example, as June described Visa, “Whether you’re
American or you’re European, everybody uses Visa. It’s just international. So Visa is
more for any event.”
Length of sponsorship. In many cases, participants put two entities together,
but they could not explain why. They associated one sponsoring brand with an event
without any particular reason. The connection was probably based on the longevity of
the relationship between specific sponsors and events. Therefore, the fourth subtheme
of brand characteristics was termed length of sponsorship. Wendy this subtheme well,
“For some reason I think GE would just be like the Olympics, and I don’t know if it’s just
like default that I just associate those two out of the three.” Nancy made a similar
statement about the Olympic Games and Coca-Cola, “I feel like the Olympics and Coca-
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Cola go together. I don’t know why but it’s one thing that comes in my mind. They were
together forever from the start.”
When participants were aware that there had been a long-term relationship
between the sponsor and the sport event, they tended to perceive a better fit between
those two entities and put the items close to each other on the map. Chloe, a 47-year-
old Olympic fan, called on her memory to explain the IBM–Olympic Games association,
“I think IBM has had a longstanding relationship with the Olympics. I don't know if they
still do, but I know they were definitely in the ‘90s. Since then, IBM has always been
connected with the Olympics in my mind.” Susan had previous knowledge about the
relationship between Samsung and the Olympic Games, “I know that Samsung has a
pretty strong relationship with the Olympic Games. They have been always top sponsor
of all the big games.” Susan also linked Emirates Airlines with the FIFA World Cup,
based on her previous experience, “I also do recall seeing people wear soccer jerseys.
Arsenal’s sponsor is Emirates, and they sponsor some other soccer teams I know. So
that’s why you are more affiliated with FIFA.” Matt gave more specific examples of long-
term sponsor–event relationships:
I specifically remember the Barcelona Olympics. Wow it’s back in the 90s. Visa had their ads, something like if you’re going to the Olympics don’t forget to pack all this stuff and don’t bring American Express because the Olympics don’t accept it.
Sponsorship Outcomes
After the main activity, which involved mapping the sponsoring brands and large-
scale sport events based on their similarity, each group held brief discussions about
possible sponsorship outcomes. The results of these discussions will be presented
through three subthemes: cognitive, affective, and behavioral outcomes.
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Cognitive. Sponsorship’s cognitive outcome is normally focused on brand
awareness or recall (Cornwell et al., 2005). Participant discussions mentioned these
cognitive outcomes. Amy thought the benefit of sponsoring a sport event is that it can
be a reminder to consumers to recognize the brand:
I get the pistachio company and Mars and Snickers: they were buying expensive —even Budweiser was buying expensive spots just to be like, “Hey, we’re still around,” as a reminder. Same with Coke. Coke never needs to advertise for any reason because everybody and their grandparents knows Coke, but it’s just like a reminder to say, “Hello, we’re still in the game and we still have big money.”
In terms of brand awareness and recognition, Lee stated, “If Coke doesn’t sponsor and
it doesn’t get that spot in the commercial, then Pepsi’s going to get it. To be well
remembered, the brands have no choice but to keep being involved in sponsorship.” In
group three, there was a controversial view on the effect of fit on recall. Eddie first
pointed out that he knew the consumer electronics brand Haier from the 2008 Beijing
Summer Olympic Games and he had included it in the consideration list of electronics
goods brands in his mind ever since. On the contrary, Wendy was skeptical about brand
recall, especially in the case of a global brand that was already renowned, stating that
“Maybe yes for Haier or those small companies. But what about Coke? Everybody
knows Coke. Everybody even knows that they are sponsoring the Olympics forever.
What’s the virtue of sponsoring the Olympics? It’s a waste of money.” Another aspect of
sponsorship’s cognitive outcome is transferring the positive image of a sport event
toward a sponsoring brand. June noted, “I think sponsors want to get the energetic and
positive image from sporting events. And many of them succeeded.” June also
mentioned image reinforcement:
Somebody who lives in a small house in South Africa is watching the World Cup, so they have seen that Rolex. Are they going to be able to buy
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it? No, but it reinforces that that’s a status symbol of the wealthy. That reinforces that for those people who can afford it, this is something that you get to make sure that people know you’re wealthy.
The groups also discussed the possibilities of changing a negative image to a positive
one through sponsorship. Ian briefly stated, “The door is wide open to change a brand
image or fix the brand image.” Using a risk management example, June explained this
idea in more detail:
Image is, I think, a big part. Like some of these companies have scandals. For example, I think I remember Johnson & Johnson having a scandal for using some shampoo or whatever on pets or whatever. Then they come out with a commercial that’s telling some enlightening story about some Olympic player and you think, “They’re not so bad after all.”
Affective. Affective outcomes of sponsorship can be referred to as likes,
preferences, and positive attitudes (Becker-Olsen & Simmons, 2002; Speed &
Thompson, 2000). Bailey aptly explained possible affective outcomes:
You sit in front of the TV, you cry, you yell, you are super happy. The emotional involvement of people who watch this [sports] is so much higher, and you can positively associate the brand with the emotional involvement of the event. You want someone who’s yelling and is super happy to see the logo of your brand. If they link the image of these two, I mean the event and the brand, they will like the sponsoring brand.
The findings showed that affective outcome might vary depending on what type of
sponsor–event fit they have perceived. Matt suggested that image-based fit is more
important than functional-based outcome in terms of generating affective outcomes:
I understand Omega is in use during the Olympic Games, or FIFA World Cup. It’s good to see they [Omega] do their job there. They match well each other. But if I’d love Omega more than before just because they sponsor the game? Well... not sure. I want more emotional touch. I want more creative link between two.
Behavioral. Behavioral outcomes of sponsorship are frequently measured by
WOM and purchase intention (e.g., Delia & Armstrong, 2015; Simmons & Becker-Olsen,
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2006). Amy clearly described the direct impact of functional-based fit on purchase
intention, “Every time I go Adidas, I always go check if there is new Stella Mccartney
tennis dresses. Williams sisters wear them in Wimbledon and I think it’s so awesome.”
However, the lack of control for capturing purchase intention made participants doubtful
about the behavioral outcome. In other words, there are many other variables that can
affect purchase intention. As Mac described:
If I am rich or you are rich and you’re watching Wimbledon, you would see all of these brands being advertised during the event. But will you buy a Rolex watch after the event? You may not. Now, would you necessarily become more hesitant to buy Sony products because they’re not advertising in Wimbledon? You may not.
Additionally, June explained purchase intention from a brand manager’s perspective:
I don’t even think it’s necessarily as important to sell their product because I think if they have enough money to sponsor one of these events, they don’t really have a problem selling it. I feel like with Coke and with McDonald’s, they are trying to build a brand name, but not promote the actual sales.
During the discussions, participants suggested that sponsor–event fit positively impacts
affective outcomes first, then positive affective outcomes generate positive WOM.
Susan, a huge soccer fan, described well this sequential relationship. She said, “If I see,
for example, Adidas sponsors FIFA World Cup, it makes sense. Adidas for soccer? It’s
so right. Isn’t it? I like it. I will like Adidas more and talk about it.”
Figure 1-1 portrayed the results of the qualitative study and the SEFF model
explaining the multidimensional structure of sponsor–event fit and the effect of fit on
sponsorship outcomes.
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Results: Quantitative Phase
The results of the quantitative study are presented in the following order:
descriptive statistics, data screening and test of assumptions, measurement models,
structural models, and moderating effects.
Descriptive Statistics
Sponsor–event fit variable. Descriptive statistics for sponsor–event fit variables
are presented in Tables 4-1, 4-2, and 4-3. The means of the sponsor–event fit ranged
from 4.00 to 4.91 on a seven-point Likert scale. The standard deviations ranged from
1.33 to 1.99. The highest rated Sponsor–event fit item was “It makes sense to me that
(brand X) sponsors (event Y) because (brand X)’s target consumers would watch (event
Y)” (M = 4.91, SD = 1.52), whereas the lowest-rated Sponsor-event fit item was “The
role of (brand X) in the world is as important as that of (event Y)” (M = 4.00, SD = 1.73).
In terms of Image-based fit, Active and healthy image items showed relatively high
mean scores ranged from 4.62 to 4.85 compared to items related to other subthemes.
Among Functional-based fit items, “The product or service of (brand X) is used during
the operation of (event Y)” showed the highest mean score (M = 4.71, SD = 1.66).
Sponsorship outcome variable. Table 4-4 displays the descriptive statistics for
sponsorship outcomes. The means of Interest items were relatively high and ranged
from 4.35 to 4.63, whereas the means of WOM items were lower and ranged from 3.40
to 3.83. The item “This sponsorship would make me more likely to remember brand X’s
promotion” had the highest mean (M = 4.63, SD = 1.67), followed by the item “This
sponsorship would make me more likely to notice brand X’s name on other occasions”.
The item “This sponsorship makes me not miss an opportunity to tell others about brand
X” had the lowest mean (M = 3.40, SD = 1.68).
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Involvement variable. Table 4-5 shows the descriptive statistics for
Involvement. The means of the Involvement was skewed towards high values ranged
from M = 4.57 to M = 5.78 on the seven-point Semantic Differential scale, and the
standard deviations ranged from SD = 1.19 to SD = 1.51. Because the data were
skewed towards the highly involved event fans, it was not appropriate to compare high
involvement group and low involvement group. Alternatively, researcher divided the
quantitative study samples into two groups–the high involvement group and the
moderate involvement group–using median split for further performing multigroup SEM.
McGehee, Yoon, and Cardenas (2003) has similarly divided study samples into high
involvement group and medium involvement group in their research investigating
involvements of runners.
Data Screening and Test of Assumptions for SEM
Prior to the main analyses, all the variables were examined to check the
accuracy of data entry and outliers. The critical assumptions of SEM (i.e., univariate and
multivariate normality assumptions, linearity assumption) were also tested.
First, to check for univariate outliers and missing data, standardized scores were
calculated for observed items of all scales and reviewed to see if they satisfied the cut-
off standard. The suggested cut-off values for potential outliers were above 3.29 and
below -3.29 (Tabachnick & Fidell, 2007). No standardized score for any variable was
above 3.29, and no standardized score for any variable was below -3.29, suggesting
there were no outliers. Second, to test the univariate normality assumption, histogram,
summary descriptive statistics, and Shapiro–Wilk test of all scales were performed. The
test results suggested that none of the observed variables were significantly skewed, at
p < .01. However, Mardia’s (1985) multivariate skewness and kurtosis coefficients and
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normalized estimates of the coefficients of both skewness and kurtosis were significant
at p < .01. This served as evidence that multivariate normality assumptions for observed
variables were violated. To deal with the nonnormality issue, the Satorra-Bentler scaling
method (SB χ2), which adjusts model fit indices based on SB χ2, was used for the
current study. In terms of the linearity assumption, all randomly selected pairs of
variables appeared to be linearly related.
Measurement Models
In the current study, research question one and hypothesis one were related to
the measurement model of sponsor–event fit constructs. Therefore, a series of
confirmatory factor analyses (CFA) was performed to test and refine the measurement
model of sponsor–event fit. Then two additional confirmatory factor analyses were
separately conducted to evaluate the measurement models for the dependent variables
(i.e., Interest, Favorability, Use, and WOM) and the moderating variable (i.e., Event
involvement).
Measurement model of sponsor–event fit.
Research question one and hypothesis one are related to the structure of
Sponsor–event fit construct. To answer RQ1 and confirm H1, measurement model of
Sponsor-event fit was tested.
RQ 1: Can the three subdomains of the global sponsor–event fit be
empirically verified? First, an initial confirmatory factor analysis was performed for the
46 observed items of sponsor–event fit scale with 10 latent factors. A post hoc model
modification of the initial model (46 items) was performed using the modification index
and expected parameter change statistics as recommended by Kaplan (1990, 1991). A
final decision regarding which items to retain and which to eliminate was made,
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considering factor loadings, theoretical relevance, and the parsimoniousness of the
model, collectively. As a result, four items (one Active and healthy image item, one
Audience consumption during the game item, and two Geographical characteristics
items) were removed.
The revised sponsor–event fit 10-factor measurement model (42 items) showed
an acceptable fit to the data (χ2/df = 1910.49/774 = 2.47, SRMR = 0.05, RMSEA = 0.05,
CFI = 0.93, TLI = 0.92). Tables 4-6, 4-7, and 4-8 display the factor loadings, Cronbach’s
alpha coefficients, and AVE values for the CFA of the remaining 42 items. The revised
sponsor–event fit measurement model demonstrated strong reliability values in terms of
Cronbach’s alpha (α = .840 to .927). Eight out of 10 factors exceeded the required
thresholds for an AVE of .5 and above, as recommended by Hair et al. (2010): Active
and healthy image (AVE = .697), Goodwill toward sport (AVE = .563), Socioeconomic
status of consumer (AVE = .646), Athlete use during the event (AVE = .719),
Operational use (AVE = .502), Audience consumption during the event (AVE = .514),
Symbolic features (AVE = .565), and Length of sponsorship (AVE = .596). However, the
Compatibility (AVE = .459) and Geographical characteristics (AVE = .465) factors did
not meet the required AVE thresholds (Hair et al., 2010), which raises concerns about
the validity of these factors. Moreover, correlations between some pairs of factors were
above .85, and squared correlations between some pairs of factors were greater than
the AVE scores of either factor (Table 4-9). These results indicated that people could
not distinguish some factors (e.g., Compatibility and Socioeconomic status of consumer,
Athlete use during the event and Operational use) and even though these factors were
theoretically different.
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To solve this discriminant validity issue, exploratory factor analysis was
conducted for 42 items using a promax rotation (i.e., uncorrelated or oblique factor
assumption) and with eigenvalues set to 1. Principal axis factoring was chosen as the
extraction method because it can be used when the assumption of normality has been
violated (Fabrigar, Wegener, MacCallum, & Strahan, 1999). The exploratory factor
analysis for sponsor–event fit indicated that a five factor solution best fit the data, as
depicted in Table 4-10. The results from the factor analysis concurred with the
qualitative data analysis, which suggested a multidimensional sponsor–event fit scale.
In terms of designating item factor loadings for inclusion in the model, Hair et al. (2010)
suggested a required threshold of .4 and above when the sample size was larger than
350. However, Tabachnick and Fidell (2007) used more stringent cut-offs suggesting
.45 is fair and .55 is good. In the current study, items with a factor loading of .5 and
above were considered with a view to achieving a parsimonious model. Theoretical
relevance and item cross-loadings were also reviewed for the item selection. The
revised five factor model consisted of 27 items: Sporty image (8 items), Audience-
consumer image (4 items), Direct use (5 items), Indirect use (6 items), and Long-term
relationship (4 items). The first two factors corresponded with the Image-based fit
dimension because all items were originally included in the Image-based fit dimensions.
The third and fourth factors corresponded with the Functional-based fit dimension
because all included items were initially classified as part of the Functional-based fit
dimension. The last factor was the only factor remaining among the three original
factors of the Brand characteristics dimension. The revised hierarchical model of
sponsor–event fit can be found in Figure 4-1. Factor loadings, Cronbach’s alpha
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coefficients, and AVE values from the confirmatory factor analysis of the five factor
model are located in Table 4-11. All five factors met or exceeded the required threshold
for Cronbach’s alpha (α = .894 to .938) and AVE (AVE = .515 to .689), indicating
sufficient convergent validity and reliability for the latent variables.
H1. Fit is one global construct that has a third-order relationship with its
subdimensional factors. The revised measurement model achieved good fit for the
data (χ2/df = 953.13/315 = 3.03, SRMR = 0.05, RMSEA = 0.06, CFI = 0.94, TLI = 0.93)
indicating that hypothesis 1 is supported. To confirm the third-order hierarchical model,
the alternative independent factor model (Figure 4-2) was compared with the proposed
model. The alternative independent factor model fit the data well (χ2/df = 941.68/312 =
3.02, SRMR = 0.05, RMSEA = 0.06, CFI = 0.94, TLI = 0.93) (Table 4-12). Although the
fit indices suggested that both the proposed model and alternative model fit the data
well, the chi-square difference test (Δ χ2 = 11.45, df = 3, p < .01) demonstrated that the
independent factor model performed slightly better than the third-order hierarchical
model.
Measurement Model of Sponsorship Outcomes. This model demonstrated
good fit (χ2/df = 92.39/48 = 1.92, SRMR = 0.02, RMSEA = 0.04, CFI = 0.99, TLI = 0.99).
Table 4-13 displays the factor loadings, Cronbach’s alpha coefficients, and AVE values
for the Sponsorship outcomes: Interest, Favorability, (intention to) Use, and WOM. The
subscales of Interest (α = .906 and AVE = .661), Favorability (α = .942 and AVE = .773),
Use (α = .950 and AVE = .803), and WOM (α = .930 and AVE = .734) showed strong
internal consistency and construct reliability. The pairwise χ2 difference test showed that
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correlations among factors were significantly different from 1.0. The correlation matrix
among other factors is located in Table 4-14.
Measurement Model of Involvement. The measurement model for Involvement
was a saturated single factor model, and thus the model perfectly fit the data (χ2/df =
0.00/0 = 0.00, SRMR = 0.00, RMSEA = 0.00, CFI = 1.00, TLI = 1.00). Table 4-15
outlines the factor loadings, Cronbach’s alpha coefficients, and AVE values for the
Involvement measurement. The subscales had strong internal consistency and
construct reliability with a Cronbach’s alpha of .926 and AVE value of .565.
Structural Model
Although both the third-order hierarchical model and the independent factor
model showed good fit indices, the independent five factor model was chosen to answer
the remaining research questions and to test the remaining hypotheses because the
independent factor model allows the effect of the subdomains of Sponsor–event fit to be
compared. The structural model and the standardized path coefficient are depicted in
Figure 4-3. All goodness-of-fit indices on the proposed structural model supported a
reasonable fit to the data (χ2/df = 2296.66/678 = 3.38, SRMR = 0.10, RMSEA = 0.06,
CFI = 0.91, TLI = 0.90).
RQ 2: What are the effective domains of sponsor–event fit that positively
influence sponsorship outcomes? Overall, all five factors of Sponsor–event fit
showed significant effects on Sponsorship outcomes. However, the consequences of
each Sponsor–event fit factor were different as portrayed in developing the hypotheses.
Detailed results regarding each hypothesis are described below.
H2. Image-based fit has a positive impact on a) cognitive sponsorship
outcomes and, b) affective sponsorship outcomes. The second hypothesis was
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supported by the data; both Sporty image and Audience-consumer image were
revealed as significant predictors of the cognitive and affective outcome domains.
Sporty image had a significant impact on Interest (β = 0.42, p < .05) and Favorability (β
= 0.46, p < .05). Audience-consumer image also showed a significant impact on Interest
(β = 0.46, p < .05) and Favorability (β = 0.35, p < .05).
H3. Functional-based fit has a positive impact on behavioral sponsorship
outcomes. The third hypothesis was supported by the data. Both Direct use (β = 0.12,
p < .05) and Indirect use (β = 0.49, p < .05) positively influenced Intention to use the
sponsoring brand.
H4. Brand characteristics has a positive impact on a) cognitive
sponsorship outcomes and, b) affective sponsorship outcomes. The fourth
hypothesis was not supported by the data. Length of sponsorship negatively influenced
Interest (β = -0.14, p < .05), whereas, the effect of Length of sponsorship on Favorability
was not significant (β = -0.08, p > .05).
RQ3. Is the influence of sponsor–event fit on WOM sequential? The effect of
Interest (β = 0.49, p < .05) and Favorability (β = 0.77, p < .17) on WOM were significant,
which suggests a possible indirect effect of Sponsor–event fit on WOM.
H5. a) Cognitive sponsorship outcomes and b) affective sponsorship
outcomes mediate the relationship between sponsor–event fit and WOM. The fifth
hypothesis was supported by the data. The results of an indirect path analysis indicated
the mediating role of Interest and Favorability in establishing the relationship between
Fit and WOM. The indirect effect of Sporty image on WOM (β = 0.49, p < .05) and
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Audience-consumer on WOM (β = 0.43, p < .05) were positively significant. The indirect
effect of Length of sponsorship on WOM was negatively significant (β = -0.12, p < .05).
Moderating Effect
H6: Event involvement moderates in the relationship between sponsor–
event fit and sponsorship outcome. A multigroup SEM was conducted to examine
the moderating effect of Involvement on the relationship between Sponsor–event fit and
Sponsorship outcome. Table 4-16 presents the results of a series of invariance tests for
evaluating χ2 difference. The invariance test between the unconstrained model and
equal factor loadings model was significant, suggesting there exists a significant
difference between the high involvement group and the moderate involvement group.
Because the moderating effect of Involvement was suggested by the model invariance
test, the group invariance tests of significant parameters were performed to explore
which direct paths were affected by the moderator. Models constraining one direct path
(M2–M10) were compared with the model, freely estimating all the paths across groups
(M1). As a result, the path from Audience-consumer image to Interest (M3-M1: Δ χ2 =
9.94(1) p < .05) and the path from Audience-consumer image to Favorability (M6-M1: Δ
χ2 = 13.70(1) p < .05) demonstrated significant differences across involvement groups.
The higher the level of event involvement, the more powerful was the impact of
Audience-consumer image on Interest and Favorability, from which it can be concluded
that H6 is partially supported.
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Table 4-1. Image-based fit item descriptives
Factors and items Variable Name M SD
Active and healthy image (Brand X) and (event Y) share an active image ah1 4.62 1.58
(Brand X) and (event Y)share an energetic image ah2 4.82 1.58
(Brand X) and (event Y) share a lively image ah4 4.85 1.51
(Brand X) and (event Y) share a sporty image ah5 4.53 1.83
Goodwill toward sport
(Brand X) shares an image with (event Y) because (brand X) invests in sports
gw1 4.71 1.61
(Brand X) shares an image with (event Y) because (brand X) supports young athletes
gw2 4.59 1.51
(Brand X)’s philanthropic effort for the sports industry makes me associate (brand X) with (event Y)
gw3 4.09 1.63
(Brand X) shares an image with (event Y) because (brand X) has the best interests of the sport at heart
gw4 4.24 1.60
Compatibility
To me, the market sizes of (brand X) and (event Y) are similar
cp1 4.22 1.67
The role of (brand X) in the world is as important as that of (event Y)
cp2 4.00 1.73
(Brand X) and (event Y) have similar reputations cp3 4.29 1.62
It makes sense to me that (brand X) sponsors (event Y) because both (brand X) and (event Y) are highly regarded in their respective industries
cp4 4.83 1.53
Socioeconomic status of consumer
Consumers of (brand X) and spectators of (event Y) share similar characteristics
user1 4.59 1.50
The socioeconomic characteristics such as income, education level, and occupation of those who use (brand X)’s product or service are similar to those of (event Y)’s fans
user2 4.58 1.50
It makes sense to me that (brand X) sponsors (event Y) because (brand X)’s target consumers would watch (event Y)
user3 4.91 1.52
When I think of the people who use or buy (brand X), they are similar to the people who are interested in (event Y)
user4 4.65 1.48
Note. All items measured from strongly disagree (1) to strongly agree (7).
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Table 4-2. Functional-based fit item descriptives
Factors and items Variable Name M SD
Athlete use during the event Athletes in (event Y) use (brand X)’s product or service during the event
au1 4.20 1.95
It is common for athletes to use (brand X)’s product or service while they play/participate in (event Y)
au2 4.13 1.98
I expect that (brand X)’s product or service is used by athletes during (event Y)
au3 4.31 1.96
I believe (brand X) helps (event Y) because their product or service is used by the athletes during (event Y)
au4 4.27 1.85
Operational use
The product or service of (brand X) is used during the operation of (event Y)
ou1 4.71 1.66
The product or service of (brand X) is helpful in making (event Y) well managed
ou2 4.31 1.64
It makes sense that the product or service of (brand X) is used in (event Y)
ou3 4.70 1.75
(Event Y)’s organizers need to use (brand X)’s product or service to manage the event
ou4 4.03 1.70
I believe (brand X) helps (event Y) because its product or service is used by event organizers
ou5 4.63 1.58
The product or service category of (brand X) is related to the sport that is played in (event Y)
ou6 4.07 1.99
Audience consumption during the event
When watching (event Y) on television or live at the event, viewers are likely to consume the product or service of (brand X)
cu1 4.30 1.67
I would think of using (brand X)’s product or service while I am watching (event Y) on television or live at the event
cu2 4.07 1.77
It makes sense to me that (brand X) sponsors (event Y) because (brand X)’s product or service would be used by (event Y)’s spectators during the event
cu3 4.64 1.66
The product or service of (brand X) will help (event Y)’s audience have a better experience during the event
cu4 4.12 1.63
Note. All items measured from strongly disagree (1) to strongly agree (7).
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Table 4-3. Brand Characteristics sponsor–event fit item descriptives
Factors and items Variable Name M SD
Symbolic features
The colors and graphics of (brand X) are similar to the colors and graphics of (event Y)
sb1 4.19 1.47
(Brand X)’s slogan works well with (event Y) sb2 4.62 1.44
(Brand X)’s logo is well matched with (event Y) sb3 4.46 1.59
The visual presentations of (brand X) and (event Y) overlap with each other
sb4 4.27 1.54
(Brand X)’s symbolic features are complementary with (event Y).
sb5 4.47 1.53
Geographical characteristics
The geographical origin of (brand X) is close to the location in which (event Y) takes place
geo1 4.11 1.40
(Brand X)’s country of origin is somehow related to (event Y)
geo2 4.26 1.49
The geographical target market of (brand X) is similar to the location(s) associated with (event Y)
geo3 4.69 1.36
(Event Y) is popular in the region where (brand X) is highly regarded
geo4 4.81 1.34
(Brand X) has its businesses in the locations associated with (event Y)
geo5 4.71 1.33
It makes sense to me that (brand X) sponsors (event Y) because the viewership of (event Y) is high in the target region of (brand X)
geo6 4.79 1.54
Length of sponsorship
I believe (brand X) has been sponsoring (event Y) for a long time
long1 4.56 1.48
I think (brand X) and (event Y) have a long-term relationship associating them with one another
long2 4.72 1.50
I have known (brand X) as a sponsor of (event Y) for a long time.
long3 4.06 1.73
It is natural to link (brand X) and (event Y) together because of their long-term partnership
long4 4.44 1.65
Note. All items measured from strongly disagree (1) to strongly agree (7).
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Table 4-4. Sponsorship outcome item descriptives
Factors and items Variable Name M SD
Interest
This sponsorship would make me more likely to notice brand X’s name on other occasions.
int1 4.55 1.69
This sponsorship would make me more likely to pay attention to brand X’s advertising.
int2 4.35 1.74
This sponsorship would make me more likely to remember brand X’s promotion.
int3 4.63 1.67
Favorability This sponsorship makes me feel more favorable towards brand X
fav1 4.34 1.67
This sponsorship would improve my perception of brand X
fav2 4.31 1.66
This sponsorship would make me like brand X more.
fav3 4.17 1.73
Use
This sponsorship would make me more likely to use brand X’s product.
use1 4.05 1.72
This sponsorship would make me more likely to consider brand X’s product the next time I buy.
use2 4.20 1.77
I would be more likely to buy from brand X because of this sponsorship.
use3 3.96 1.71
WOM
This sponsorship would make me more likely to mention brand X to others in the future.
wom1 3.83 1.75
This sponsorship makes me tell more people about brand X than about other brands.
wom2 3.72 1.75
This sponsorship makes me not miss an opportunity to tell others about brand X
wom3 3.40 1.68
Note. All items measured from strongly disagree (1) to strongly agree (7).
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Table 4-5. Involvement item descriptives
Items Variable Name M SD
Boring-Exciting iv1 5.74 1.25
Uninteresting-Interesting iv2 5.78 1.22
Worthless-Valuable iv3 5.19 1.24
Unappealing-Appealing iv4 5.71 1.19
Useless-Useful iv5 4.92 1.34
Not needed-Needed iv6 4.57 1.51
Irrelevant-Relevant iv7 5.28 1.34
Unimportant-Important iv8 4.95 1.45
Note. All items measured using seven-point Semantic differential scale
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Table 4-6. Image-based fit confirmatory factor analysis results
Factors and items λ α AVE
Active and healthy image .927 .697 ah1 .843 ah2 .875 ah4 .824 ah5 .795
Goodwill toward sport .885 .563 gw1 .721 gw2 .774 gw3 .743 gw4 .763
Compatibility .840 .459
cp1 .641 cp2 .652 cp3 .761 cp4 .648
Socioeconomic status of consumer .914 .646 user1 .795 user2 .779 user3 .805 user4 .834
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Table 4-7. Functional-based fit confirmatory factor analysis results
Factors and items λ α AVE
Athlete use during the event .925 .719 au1 .851 au2 .867 au4 .826
Operational use .889 .502 ou1 .725 ou2 .739 ou3 .734 ou4 .677 ou5 .708 ou6 .667
Audience consumption during the event .866 .514 cu1 .744 cu2 .717 cu3 .706 cu4 .700
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Table 4-8. Brand Characteristics sponsor–event fit confirmatory factor analysis results
Factors and items λ α AVE
Symbolic features .899 .565 sb1 .666 sb2 .743 sb3 .799 sb4 .775 sb5 .767
Geographical characteristics .843 .465 geo3 .706 geo4 .718 geo5 .621 geo6 .677
Length of sponsorship .896 .596 long1 .790 long2 .765 long3 .759 long4 .776
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Table 4-9. Correlation among sponsor–event fit constructs
1 2 3 4 5 6 7 8 9 10
1. Active and healthy image 1.00
2. Goodwill toward sport 0.86 1.00
3. Compatibility 0.77 0.86 1.00
4. Socioeconomic status of consumer 0.76 0.77 0.88 1.00
5. Athlete use during the event 0.65 0.69 0.63 0.57 1.00
6. Operational use 0.71 0.78 0.74 0.66 0.91 1.00
7. Audience consumption during the event 0.60 0.66 0.68 0.64 0.67 0.87 1.00
8. Symbolic features 0.84 0.83 0.84 0.79 0.65 0.77 0.66 1.00
9. Geographical characteristics 0.74 0.74 0.78 0.82 0.58 0.66 0.64 0.85 1.00
10. Length of sponsorship 0.77 0.77 0.75 0.74 0.67 0.72 0.59 0.86 0.84 1.00
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Table 4-10. Rotated component matrix after exploratory factor analysis Items Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
ah2. energetic image .92 -.07 -.01 .02 -.03
ah5. sporty image .85 -.22 .07 -.08 .23
ah4. lively image .81 -.05 -.04 .15 -.03
ah1. active image .74 -.11 .07 .06 .14
gw2. supports young athletes .72 .09 -.10 .08 .00
gw1. invests in sports .64 -.13 .09 .05 .15
gw4. best interests of the sport at heart .63 .21 -.12 .06 .06
gw3. philanthropic effort for sports .60 .20 .04 .03 -.08
cu4. help audience to have better experience .02 .89 -.13 .02 -.07
ou4. event organizers’ use to manage event -.10 .84 .09 -.17 .08
ou2. helpful in making event well managed .08 .79 .02 -.15 .07
cu1. viewers consume sponsors’ product -.16 .74 .05 .10 .01
ou5. help event by being used by organizers -.02 .65 -.02 .03 .16
cu2. I will use sponsor product while watching .16 .58 -.03 .06 .07
cu3. spectators’ consume sponsors’ product -.07 .50 .01 .32 .09
cp2. important in the world .32 .36 .01 .12 -.06
long1. sponsoring for a long time -.11 -.06 .98 -.01 -.03
long3. known sponsor for a long time .01 -.03 .80 -.10 .10
long2. long-term relationship .01 -.04 .71 .11 .08
long4. long-term partnership .08 -.07 .68 .00 .23
geo3. geographical target market -.05 .00 .51 .36 -.12
sb3. logo well matched .33 .06 .50 .03 -.07
geo4. popular in region -.18 .00 .47 .47 -.01
geo5. business in associated location -.03 .10 .46 .20 -.07
sb4. visual presentation .36 .09 .45 -.01 -.02
sb5. symbolic features .28 .03 .42 .15 .03
sb2. slogan .30 .10 .41 .06 -.02
sb1. colors and graphics .39 .22 .40 -.15 -.19
user4. similar each other -.01 -.12 -.02 .91 .10
user3. target consumers and viewers matched .03 -.12 -.04 .86 .13
user2. similar socioeconomic characteristics .00 .06 -.01 .86 -.11
user1. share similar consumer characteristics .19 -.04 .02 .70 .02
cp3. similar reputations .27 .14 .00 .47 -.07
geo6. high viewership in the target region .00 -.02 .36 .47 .04
cp4. both highly regarded .28 .09 .06 .46 -.08
cp1. similar market sizes .17 .10 .17 .39 -.07
au2. athletes’ use while playing/participating .04 -.01 -.03 -.02 .92
au1. athletes’ use during event -.03 .07 -.04 .02 .89
au4. help event by being used by athletes .00 .17 .05 .01 .71
ou6. product category is related .26 .03 .01 -.05 .65
ou3. product used in event .04 .16 .06 .15 .55
ou1. product used for operation -.07 .39 .04 -.03 .51
Variance explained (%) 51.16 6.68 4.04 3.30 2.87
Cronbach’s α .938 .906 .902 .914 .935
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Table 4-11. Sponsor–event fit confirmatory factor analysis results (5 factor model)
Factors and items λ α AVE
Sporty image .938 .613
ah1 .816
ah2 .822
ah4 .804
ah5 .811
gw1 .769
gw2 .758
gw3 .724
gw4 .751 Audience-consumer image .914 .646
us1 .795
us2 .779 us3 .805 us4 .834
Direct use .936 .689
au1 .857
au2 .867
au4 .837
ou3 .778 ou6 .808
Indirect use .894 .515
ou2 .754
ou4 .729
ou5 .687
cu1 .702
cu2 .691 cu4 .739
Length of sponsorship .896 .596
long1 .790 long2 .765 long3 .759 long4 .776
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Table 4-12. Goodness of fit indices for the hypothesized and alternative model
Model χ2/df SRMR RMSEA CFI TLI
Proposed model 953.13/315 = 3.03 0.05 0.06 0.94 0.93
Alternative model 941.68/312 = 3.02 0.05 0.06 0.94 0.93
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Table 4-13. Sponsorship outcomes confirmatory factor analysis results
Factors and items λ α AVE
Interest .906 .661
inter1 .799
inter2 .811
inter3 .829
Favorability .942 .773
favor1 .879
favor2 .884
favor3 .875
Use .950 .803
use1 .910
use2 .888
use3 .889
WOM .930 .734
wom1 .866 wom2 .868 wom3 .836
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Table 4-14. Correlation among sponsorship outcome constructs
1 2 3 4
1. Interest 1.00
2. Favorability 0.82 1.00
3. Use 0.81 0.86 1.00
4. WOM 0.71 0.77 0.81 1.00
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Table 4-15. Involvement confirmatory factor analysis results
Factor and items λ α AVE
Involvement .926 .565
iv1 .721
iv2 .681
iv3 .800
iv4 .759
iv5 .746
iv6 .704
iv7 .786 iv8 .808
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Table 4-16. Invariance tests of structural model to test moderating effect
Model Test of invariance
M0: Unconstrained
M1: Equal factor loadings M1-M0: Δ χ2 = 54.10(30) p > .05
M2: Equal factor loadings and equal path from sporty image to interest M2-M1: Δ χ2 = 0.01(1) p > .05 M3: Equal factor loadings and equal path from audience-consumer image to interest M3-M1: Δ χ2 = 9.94(1) p < .05
M4: Equal factor loadings and equal path from length of sponsorship to interest M4-M1: Δ χ2 = 3.51(1) p > .05
M5: Equal factor loadings and equal path from sporty image to favorability M5-M1: Δ χ2 = 1.65(1) p > .05 M6: Equal factor loadings and equal path from audience-consumer image to favorability M6-M1: Δ χ2 = 13.70(1) p < .05
M7: Equal factor loadings and equal path from direct use to intention use M7-M1: Δ χ2 = 0.61(1) p > .05
M8: Equal factor loadings and equal path from indirect use to intention use M8-M1: Δ χ2 = 0.14(1) p > .05
M9: Equal factor loadings and equal path from favorability to WOM M9-M1: Δ χ2 = 0.40(1) p > .05
M10: Equal factor loadings and equal path from interest to WOM M10-M1: Δ χ2 = 0.65(1) p > .05
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Figure 4-1. Revised third-order hierarchical model for sponsor–event fit
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Figure 4-2. Alternative independent factor model for sponsor–event fit
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Figure 4-3. Structural model for sponsor–event fit and sponsorship outcomes
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CHAPTER 5 DISCUSSION
This study has shown that sponsor–event fit is a multidimensional construct
containing three main domains: image-based fit, functional-based fit, and brand
characteristics. The study results posit a view similar to that of more recent work that
has considered fit as a multidimensional construct (e.g., Becker-Olsen & Simmons,
2002; Jagre et al., 2001; Olson & Thjømøe, 2011). In addition to the sponsor–event fit
construct, this study revealed sponsorship outcomes to be cognitive, affective, and
behavioral. The SEFF model was suggested in the current study explaining the
multidimensional concept of sponsor–event fit and its impact on sponsorship outcomes.
Each domain of sponsor–event fit was found to influence sponsorship outcomes
differently, and event involvement partially moderated the relationship between the
sponsor–event fit and sponsorship outcomes. The following sections describe detailed
discussions regarding the grounded theory model, research questions, and hypotheses.
Grounded Theory Model of Sponsor–event Fit
The qualitative phase of the study identified the domains of sponsor–event fit and
provided concepts that were operationalized in the initial questionnaire purporting to
measure the fit construct. The grounded theory model (SSEF model, Figure 1-1)
created through the qualitative phase of this study portrays the multidimensional nature
of sponsor–event fit and consists of three subdimensions: image-based fit, functional-
based fit, and brand characteristics. Among these three subdimensions of sponsor–
event fit, the first two, frequently mentioned in the previous sponsorship literature (e.g.,
Gwinner, 1997; Gwinner & Eaton, 1999; Jagre et al., 2001), suggest fit as a
bidimensional construct. However, the proposed grounded theory model is inconsistent
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with bidimensional views of sponsor–event fit because the model contains one
additional subdimension: brand characteristics. Recently, sport sponsorship researchers
(e.g., Olson & Thjømøe, 2011) have investigated additional factors that could be
included in a global fit construct, but the scholarly work on the multidimensional
structure of fit is limited. Therefore, the current study is significant because it is one of
the initial pieces suggesting a tridimensional concept of sponsor–event fit.
The first theme, image-based fit, is closely related to Gwinner and Eaton’s (1999)
work on building brand image through event sponsorship. The focus group participants
used adjectives such as “active” and “healthy” to describe core sport event–related
images. In addition, they also used the more generic images such as “caring
community” or “prominent” to assess the extent of fit between the sponsoring brand and
the event. Johar and Pham’s (1999) study also supported this idea of prominence. In
their study, Johar and Pham argued that consumers use the market prominence of
potential sponsors as a source of information when associating the image of the
sponsoring brand with the image of the sport event. Perceived market prominence may
derive from factors such as brand awareness, market share, visibility, and share of
voice. Furthermore, the socioeconomic status of the consumer subtheme, which
suggests a similarity between the event audience and the sponsoring brand’s target
segment, confirms the notion of audience fit found in previous studies (e.g., Barone,
Norman, & Miyazaki, 2007; Olson & Thjømøe, 2011).
In terms of functional similarity, the findings confirmed Gwinner’s (1997) idea that
functional-based similarity occurs when the sponsor’s product is used during the
sponsored event. In fact, the current study’s findings have expanded the scope of
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Gwinner’s functional-based fit by including pre-event and post-event product use in
addition to use during the sporting performances. The findings also suggest that
consumers consider a wide range of information when assessing functional fit. The
focus group participants discussed the use of a sponsor’s product or services by
different types of event participants (i.e., athletes, event organizers, spectators) to
evaluate the functional-based fit. This finding, especially with regard to the operational
use subtheme, also confirms Alcañiz et al.’s (2010) result that functional-based fit
involves a higher degree of cognitive elaboration by consumers in comparison with
image-based fit. When preparing to stage a mega or major sport event, event
organizers typically determine the various product or service categories needed for
sponsorship before finding official sponsors for each category (e.g., official beverage
sponsors, official telecommunication sponsors); sometimes, however, the product or
service categories of the official sponsors are not naturally linked to the image of the
sport event. In this study, focus group participants tried to justify such cases and
evaluate the rationale for perceived similarity between the event and the sponsor by
suggesting operational usages.
The third and last theme of sponsor–event fit, brand characteristics, follows
Keller’s (1993) associative network memory model. In this model, brand image refers to
“the set of associations linked to the brand that consumers hold in memory” (Keller,
1993, p. 2). Adopting the associative network memory model in the sponsorship
context, the sponsoring brand and the event are linked by multiple available information
nodes, which are the brand characteristics. Indeed, the current study’s findings about
brand characteristics supported Olson and Thjømøe’s (2011) findings, as they included
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geographic similarity as a subcategory of their fit dimension. In terms of geographic
similarity, Olson and Thjømøe (2011) focused on country of origin, examining whether
the sponsor and the sponsored object are global or local. However, the current study
has offered a broader explanation of geographic similarity by including the concept of
target market, focusing on whether the sponsoring brand’s regional target market
associates well with the event. The fit between the sponsor and the event might be
perceived, even though there is no logical connection between those two entities. Olson
and Thjømøe included time duration as a subcategory, assuming that longtime
sponsorship association has a positive effect on overall fit. Similar to Olson and
Thjømøe’s (2011) findings, the current study also revealed that a longtime sponsor–
sponsee partnership results in higher perceived fit.
The multidimensional view of sponsor–event fit is based on the associative
memory view of sponsorship, which holds that the perceived fit is composed of all of the
associations that consumers link with the brand and the event (Gwinner, 2014). These
associations come from a variety of sources stored in consumers’ minds and are utilized
when consumers evaluate the fit between the sponsor and the event.
In addition to the sponsor–event fit-related themes, the qualitative study revealed
the cognitive, affective, and behavioral outcomes of sponsorship, which are consistent
with previous literature (Becker-Olsen & Simmons, 2002; Cornwell et al., 2005; Gwinner
& Bennett, 2008; Gwinner & Eaton, 1999; Johar & Pham, 1999; Koo et al., 2006; Lee &
Cho, 2009; Speed & Thompson, 2000). While focus group participants discussed
sponsorship outcomes, they identified the possible influence of sponsor–event fit on
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those outcomes, confirming the notion of schema congruity theory (Fiske, 1982),
thereby proffering an explanation of the theoretical mechanics of sponsorship.
First, the qualitative findings suggested the cognitive outcomes as the dependent
variables of sponsor–event fit. This finding is also consistent with previous literature that
posited that prominent sponsors that have a strong association with the event are more
easily recalled than those that do not (Gwinner, 2014). The majority of research that has
investigated the relationship between fit and brand recall has found that higher fit is
related to higher sponsor recall or recognition accuracy (Cornwell et al., 2005).
Nonetheless, there is a controversial view regarding the relationship between fit and
brand recall. Focus group participants in this study showed more optimistic views of the
cognitive outcome of sponsorship than were shown in previous research. They believed
that the sponsorship activity would help audiences recognize a sponsoring brand;
however, the focus group participants did not clearly mention the impact of sponsor–
event fit on brand awareness or recall.
Compared to cognitive outcomes, the relationship between sponsor–event fit and
the affective outcomes was portrayed more positively among the group during
discussion. The focus group discussion results indicated that perceived fit can influence
affective sponsorship outcomes (e.g., attitude toward sponsor brand), reflecting notions
discussed in previous literature (e.g., Gwinner & Bennett, 2008; Koo et al., 2006; Speed
& Thompson, 2000). The qualitative study findings also suggest that image-based fit
might be more prominent than functional-based fit in generating attitudes toward the
sponsoring brand. Some group participants expressed doubts about the effect of
functional-based fit on cognitive and affective outcomes.
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Behavioral outcomes such as intention to use and WOM were deemed as
consequences of sponsor–event fit in the qualitative study. This is the first study to
examine the relationship between functional-based fit and intention to use. Although the
qualitative study’s results showed little evidence of a positive relationship between
functional-based fit and attitudes toward the sponsoring brand, such as favorability and
interest, the findings suggest a possible path from functional-based fit to intention to
use. Moreover, the qualitative study results implied the sequential influence of sponsor–
event fit on WOM through affective outcomes.
In sum, the grounded theory theorizes the relationship between sponsor–event fit
and sponsorship outcomes, built on the results of qualitative research and schema
congruity theory (Fiske, 1982).
Confirmation of the Structure of Sponsor–event Fit
The quantitative phase of the study validated the domains and measurement
scales of the sponsor–event fit. The results of the qualitative study provided evidence
that fit is a global construct that has a third-order relationship with its three
subdimensional factors (i.e., image-based fit, functional-based fit, and brand
characteristics), which confirms H1. The final measurement scale has adequate
psychometric properties. Content validity was established by the literature review,
expert review, and tests of content validity. Internal consistency was established as the
Cronbach’s alpha for all constructs exceeded the accepted cutoff criterion of .7
(Nunnally & Bernstein, 1994). Construct reliability (or convergent validity) was
evidenced by adequate AVE values for all constructs. AVE values above .50 indicate
that the composite reliability of the construct is adequate (Fornell & Larcker, 1981).
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Discriminant validity was confirmed by reviewing correlations among pairs of final
constructs (Kline, 2011).
The third-order hierarchical model of sponsor–event fit has not been suggested
in the sponsorship literature. None of the previous research that claimed either the
bidimensional concept of fit (e.g., Alcañiz et al., 2010; Gwinner, 1997; Jagre et al., 2001;
McDonald, 1991) or the multidimensional concept of fit (e.g., Barone et al., 2007; Olson
& Thjømøe, 2011; Simmons & Becker-Olsen, 2006; Zdravkovic et al., 2010) developed
the third-order hierarchical model. The third-order hierarchical model developed in the
current study, therefore, will help researchers better understand the underlying concepts
of fit.
However, the results of the quantitative phase were inconsistent with the
grounded theory model, which postulates an 11-factor sponsor–event fit model. The
empirical data analysis from the quantitative phase suggested that there are only five
first-order factors: sporty image, audience-consumer image, direct use, indirect use, and
long-term relationship. The first two factors corresponded with image-based fit. Sporty
images combined “active and healthy” and “caring community” (renamed goodwill
toward sport after the expert review) subdimensions. Active and healthy image and
caring community were initially regarded as distinct dimensions of sponsor–event fit, but
the results indicated that the two factors lacked discriminant validity. Therefore, the
sporty image items contained questions originally measuring the active and healthy and
the caring community dimensions. Audience-consumer image was originally named
socioeconomic status of consumer in the grounded theory model, but it was renamed
during the expert panel review for greater clarity.
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The three subdomains of functional-based fit were restructured into two domains:
direct use and indirect use. Direct use contained all athletes use items and two of the
operational use items to capture the extent to which, in consumers’ minds, the
sponsors’ products or services are being directly used during the games. Indirect use
consisted of all of the audience consumption during the event items and some of the
operational use items to capture the extent to which, in consumers’ minds, the
sponsors’ products or services are being indirectly used during the games. Among the
original four brand characteristics factors, long-term relationship was the only factor that
remained in the model because all of the other factors had suffered from a cross-
loading issue with the image-based fit subdimensions. The results suggested a lack of
discriminant validity between the original image-based fit dimension and the brand
characteristics dimension.
One possible explanation for the lack of discriminant validity among some of the
domains identified in the grounded theory may lie in differences between the nature of
the focus group discussion and the online survey. In the focus group discussion,
participants were asked to think about the subject in depth (Vaughn, Schumm, &
Sinagub, 1996), so the discourse from the focus group discussion was rich in breadth
and depth (Milliken, 2010). In contrast, online survey participants might not have put
forth sufficient effort in the evaluation process to differentiate items measuring distinct
concepts. Additionally, the inductive approach to analyzing qualitative data might result
in researchers overestimating the semantic or theoretical distinctions between themes,
which may generate redundant concepts. The law of parsimony (i.e., Occam’s razor)
argues for the parsimony virtue in developing theory (Blumer, Ehrenfeucht, Haussler, &
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Warmuth, 1987), which keeps theories from becoming too complex and
incomprehensible (Wacker, 1998). According to the virtue of parsimony, researchers
should accept the simplest possible theoretical explanation for existing data. The
revised five-factor model is appropriate to explain the data for the current quantitative
study. However, more empirical studies replicating the current study’s model are
needed to confirm the grounded theory model of sponsor–event fit.
The process of comparing the third-order hierarchical model and the independent
factor model using the model comparison test succeeded in distinguishing between the
two models. Although the independent factor model showed a slightly better fit than the
third-order hierarchical model, both models fit the data well, showing similar fit statistics.
The results implied that the two models (i.e., third-order hierarchical model and
independent factor model) are complementary rather than competitive. The independent
factor model could be considered a basic model for evaluating how well the individual
sponsor–event subdimensions are measured by observed variables (Kline, 2005) and
could be used to explore how each of the constructs relates with the dependent
variables (e.g., sponsorship outcomes in this study). The third-order hierarchical model
also corresponded more closely with existing research (Alcañiz et al., 2010; Gwinner,
1997; Gwinner & Eaton, 1999; Jagre et al., 2001; Olson & Thjømøe, 2011; Simmons &
Becker-Olsen, 2006), which posits that fit is a global concept that contains subthemes
that explain aspects of fit. The third-order hierarchical model could be used to explain
the effect of overall fit in relation to the dependent variables. Either model could be
chosen, depending on future study objectives.
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Sponsor–Event Fit as a Predictor of Sponsorship Outcomes
H2, H3, H4, and H5 hypothesized a relationship among sponsor–event fit and
sponsorship outcomes.
First, the influences of image-based fit on cognitive outcome (i.e., interest) and
affective outcome (i.e., favorability) suggested by H2 were examined in the quantitative
phase. The quantitative results confirmed the existence of a positive influence of image-
based fit on cognitive and affective outcomes, which is consistent with qualitative
results. Associative network memory model has been utilized to understand what
happens in consumers’ minds with regard to sponsorship, applying marketing
literature’s view on brand knowledge (Cornwell, 2008). A well-matched relationship
between sponsors and the event can reinforce the associative link in consumers’
memories (Mazodier & Merunka, 2012; Till & Nowak, 2000). Cornwell et al. (2005)
presented an example of paired-associative paradigm in sponsorship contexts. In the
paired-associative paradigm, two entities of sponsorship (sponsoring brand and
sponsored event) are presented, and then individuals are asked to recall one given the
other. For example, if you ask individuals, “Is brand X a sponsor of sport event Y?” the
associates of brand X as well as the associates of sport event Y are activated in
memory. This activation of associates might allow an implicit mediator to naturally arise
and influence memory. Although the cognitive outcome in this study did not cover the
direct brand recall but was measured by asking about participants’ belief in their
cognitive response (i.e., interest), the positive relationship between fit and interest can
still be explained by associative network memory model. In terms of affective outcomes,
Rifon et al.’s (2004) findings may explain the positive relationship between the sponsor–
event fit and the affective outcomes. Rifon et al. suggested that perceived good fit helps
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consumers believe in sponsors’ altruistic motivations, and in turn, they might have
positive attitudes toward the sponsoring brand. The effect of image-based fit on
intention to use was not tested because the qualitative study results suggested that
there was no direct relationship between image-based fit and intention to use.
H3 hypothesized the positive impact of functional-based fit on behavioral
sponsorship outcomes (i.e., intention to use). The quantitative results confirmed the
qualitative results, which explain the relationship between fit and intention to use in both
direct use and indirect use subdimensions. Event spectators or viewers might be willing
to use the sponsoring brand’s product in the future if they believe the product is in use
either directly or indirectly during the event. However, this is inconsistent with the
previous literature, which posits that fit influences attitude, and attitude in turn influences
purchase intention (Visentin et al., 2016). The majority of the sponsorship literature has
investigated how fit generates positive attitudes toward sponsorship and how those
attitudes are then translated into behaviors such as intention to use or purchase
(Bennett, Cunningham, & Dees, 2006; Delia & Armstrong, 2015; Simmons & Becker-
Olsen, 2006; Tsiotsou & Alexandris, 2009; Visentin et al., 2016). For example, Visentin
et al.’s (2016) three-stage model of sponsorship suggested progression through
different phases: (a) assessing the fit of the sponsor with the event, (b) elaborating their
attitude toward the brand based on the level of fit assessment, and (c) translating the
attitudes into intentions and behaviors that individuals display in response to
sponsorship activities. However, in previous research, fit was conceptualized as a
global domain, and image-based fit and functional-based fit were not distinguished. The
current study classified subthemes of fit and was thus able to investigate the direct
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influence of functional-based fit on intention to use. The effect of functional-based fit on
cognitive and affective outcomes was not included in the model developed from the
qualitative study results.
H4 posited that the perceived long-term relationship between the event and the
sponsoring brand would have a positive influence on interest and favorability. In
contrast to the proposition, the quantitative results showed that the long-term
relationship did not have a significant influence on favorability. Moreover, the results
showed a negative relationship between the long-term relationship and interest.
Considering that both advertising and sponsorship are marketing stimuli with similar
objectives of enhancing awareness, branding image, and making sales (Walliser, 2003),
the negative effect of long-term sponsorship relationship on interest may be explained
by the wear-out phenomenon in advertising effectiveness research (e.g., Dahlén, 2001;
Pechmann & Stewart, 1988). Research on the wear-out phenomenon has shown that
consumers may become bored, uninterested, or even irritated as the amount of
repetition of advertising increased, and such wear-out results in diminishing advertising
effect (Dahlén, Lange, & Smith, 2010). In sum, the long-term partnership as a sponsor
might make consumers less interested in the sponsoring brand. For example,
McDonald’s and the IOC recently announced plans to end their long-running
partnership, which began in 1976 (BBC News, 2017). McDonald’s proclaimed that they
reconsidered all aspects of their business to arrest a decline in sales, and they decided
to focus on priorities other than sponsorship. This might be an example indicating that
long-term sponsorship deal might cause consumer fatigue and would no longer be an
effective marketing communication tool. The effect of long-term relationship on use was
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not tested in the current study because there was no evidence in the previous literature
to explain the link between the long-term relationship and use.
Similar to Visentin et al. (2016), the qualitative findings suggested that perceived
sponsor–event fit first influences consumers’ positive cognitive and affective responses
and consequently influences WOM in turn. Therefore, H5 was developed to test the
mediating role of cognitive (i.e., interest) and affective outcomes (i.e., favorability) in the
relationship between fit and WOM. The quantitative study confirmed the sequential
effect of image-based fit on WOM through cognitive and affective outcomes. The
findings of this research seemed to suggest a sequential path from fit to cognitive and
affective outcomes and then to WOM; fit positively influences interest and favorability; in
turn, interest and favorability positively influence WOM.
Moderating Effect of Event Involvement
In the sponsorship research, event involvement has often been considered as a
moderating variable to vary the influence of the antecedents of sponsorship outcomes
(Meenaghan, 2001). The role of involvement was also evidenced during the focus group
discussion. The highly involved sports fans and participants who were less involved in
sports sometimes have different points of view on the given relationship of the sponsor
and the event. Therefore, H6 posited event involvement as a moderator in the
relationship between sponsor–event fit and sponsorship outcome. The quantitative
study results showed that the effect of audience-consumer image on attitude toward the
event varied with the proposed moderator: event involvement. If spectators or viewers
of an event are highly involved in the event (event involvement=high), they may
perceive their self-image in line with the image of the event audience (Sirgy et al.,
2008). If this audience image and the image of people associated with the sponsoring
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brand matches, it helps consumers build more positive attitudes toward the brand that
supports the sport event (Gwinner & Eaten, 1999). Compared to the highly involved
event fans, the general event spectators or viewers (event involvement=med to low)
may care less about the audience–consumer image fit, which may result in the strength
of the associations being less prominent.
Practical Implications
Recently, marketers engaged in corporate social responsibility and the sport
event sponsorship not only seek appropriate sport event sponsorship opportunities, but
also try to maximize the effect of sponsorship activation (Cornwell, 2008). This study
revealed the importance of managing the fit between their brand and the sport event
they are sponsoring. Sport marketers can be more confident about fitting the image of
their brand in line with the sporting event by utilizing the measurement developed in the
current study. The findings of this study also may help brand executives better
understand the multidimensional structure of fit and provide guidance as to which types
of fit should be pursued to generate a positive sponsorship outcome.
Marketers—those who execute the sponsorship activation—want to appraise the
post-sponsorship effectiveness. To answer the call of marketers who need a well-
established sponsor–event measurement, the current research developed an original
sponsor–event fit measurement that confirmed good reliability and validity. The newly
developed measurement scale may benefit sport marketers by providing a useful
instrument to assess the effectiveness of the subdomains of sponsor–event fit. Sport
marketers will be able to evaluate their existing partnership with the sport event they are
sponsoring by using the Sponsor–event Fit Scale developed in the current study.
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The discourses regarding the long-term relationship between a sponsor and an
event may give additional managerial information to sport marketers. First, long-term
partnerships tend to allow consumers to link the sponsoring brand and the sport event
to each other, regardless of brand and event characteristics. This linkage generated
from the long-term relationship can help brands with negative images enhance their
images. If a brand with a negative image is connected with a sport event with a positive
image, the event’s positive image will be transferred to the sponsoring brand from the
event through the associations that are built (Gwinner, 1997). However, the quantitative
results suggest that a long-term relationship with an event as a sponsor does not
always work well. If the duration of the sponsorship is too long, the effect of sponsorship
activation could be none to negative. Thoughtful management of the sponsorship
agreement, especially in terms of the length of sponsorship agreement contract, is
required.
On the event mangers’ side, the current study gives basic ideas of how to
promote events to potential sponsors to increase brand managers’ interests in
sponsoring a particular event. For sponsorship executives in event-organizing
committees, marketing executives in companies are potential customers who evaluate
the direct and indirect values of sponsorship. Event managers may refer to the results of
this study to encourage brand managers whose brand fits well with the event to be their
sponsor.
Limitations and Delimitations
Although this study has the potential to provide a better understanding of
sponsor–event fit and related variables, limitations and delimitations must be
acknowledged.
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Limitations
First, the study’s context is a limitation of the current study. This study focused on
well-known sport events rather than small-scale sport events because the study
adopted the associative network model, which is more applicable to well-renowned,
better-known entities. In this study, survey participants were asked about the actual,
existing pairs of sponsoring brands and sport events because this study was designed
to ask consumers’ preexisting perceptions of those entities in the empirical research
setting. If participants do not have enough information regarding the research objects
(i.e., the sport event or sponsoring brand), then they are less likely to determine whether
the entities correlate. As a result, the sponsor–event fit scale developed in the current
study measures fit between a sport event and the existing sponsor rather than fit
between a sport event and a new sponsor seeking a new sponsorship opportunity.
Moreover, the subdimensions of sponsor–event fit may differ in some other study
context. In a smaller, local event setting, individuals might use different information to
assess the fit between the event and the sponsors.
Another limitation of the current study is the questionnaire’s readability. The
expert review and pretest using cognitive interviewing successfully assessed the face
and content validity of the measurement items and excluded irrelevant items from the
questionnaire. However, the length of some remaining items may have been too long.
The extensive wordiness of each measurement item may have caused fatigue for
participants. Refining the final wording to make each measurement item more concise
might be needed for future use of the questionnaire.
Finally, the quantitative phase of this dissertation did not examine the relationship
between fit and the actual brand (sponsor) recall or recognition. Following findings of
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the qualitative study, which suggested that the perceived sponsor–event fit determines
the extent to which individuals are able to correctly identify sponsoring brands, the
relationship between the fit and cognitive sponsorship outcomes should be further
examined.
Delimitation
The quantitative study sample is skewed toward the highly involved event fans
and is one delimitation of the current study. In the qualitative focus group discussion,
each group was purposely recruited to have a mix of people: those less involved in the
sport, moderately involved people, and highly involved sports fans. Thus, the qualitative
study participants had different backgrounds and had different ideas because of their
different levels of knowledge about events and brands. However, for the quantitative
study, the level of involvement in sport events was asked but not included as a
recruiting criterion. As a result, the quantitative study sample was skewed toward highly
involved event fans. Hence, generalizing the research findings should be considered
cautiously, especially regarding research participants’ characteristics, such as regional
backgrounds, preexisting attitudes toward the sponsoring brand, and involvement as a
sports fan.
The skew of the study sample toward highly involved sports fans may be the
result of a bias caused by the self-selection of participants (self-selection bias) in the
use of MTurk recruitment. Self-selection means that individuals select themselves to
take part in the survey. With MTurk, the survey questionnaire is simply published on the
Amazon MTurk site, and the researcher is not in control of the selection process. MTurk
Workers decide to participate in surveys that deal with topics they are interested in. As a
result, individuals highly involved in the study subject tend to participate in the survey. In
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the future, it is recommended that a more diverse sample with different levels of
involvement in sports be recruited by using methods that allow the researcher to control
the selection process.
Future Research
Aforementioned limitations and delimitations of the study offer room for future
research. Among all issues addressed in the limitation and delimitation section, the
refinement of the questionnaire and measurement item of sponsor–event fit has top
priority because it is the cornerstone of potential future research. Once the
questionnaire gets better readability, future research should replicate the study across
different contexts, for example with smaller events to see whether the model works in
different event contexts. Another direction of the future research is to confirm the
comprehensive grounded theory of sponsor–event fit. In this future research, cognitive
sponsorship outcomes, such as recall or recognition, may be included after more
extensive literature review. The sponsor–event fit themes excluded from the quantitative
phase may be revisited and revalidated. Variables that represent individual
characteristics or demographics and brand-specific variables (e.g., preexisting attitudes
toward the brand, brand familiarity, and product category of the brand) may be included
in the model after a literature review regarding those variables.
Conclusion
The major contribution of this study stems from exploring the underlying
information and associations in consumers’ minds when they evaluate the sponsor–
event fit. Numerous sponsorship studies (e.g., Gwinner & Bennett, 2008; Koo et al.,
2006; Speed & Thompson, 2000) found that fit can influence consumers’ attitudes
toward a sponsoring brand. However, there is no well-established model that shows
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which aspects of fit influence each type of sponsorship outcome. The grounded theory
model confirms the multidimensional structure of the fit and the consequence of
sponsor–event fit. The results of the quantitative study, together with the grounded
theory model, provide a better understanding of the fit concept by presenting five first-
order factors (sporty image, audience-consumer image, direct use, indirect use, and
long-term relationship), two second-order factors (image-based fit and functional-based
fit), and the relationship of fit and sponsorship outcomes. Moreover, despite the fact that
researchers have examined the fit construct as being multidimensional within the
general sport sponsorship context (Olson & Thjømøe, 2011) and the context of
sponsorship for social causes (Zdravkovic et al., 2010), no previous study has explored
the subdimensions of fit in the sport event sponsorship context. To fill this gap in
existing sponsor–event fit research, the current study explored the domains of sponsor–
event fit and provided basic knowledge and understanding of the sponsor–event fit
construct. In sum, the current study is significant in providing a holistic measurement of
fit that is essential for sport event sponsorship research.
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APPENDIX A QUALITATIVE STUDY RECRUITMENT MATERIALS
SOCIAL NETWORK WEBSITE INVITATION Hello, I am a doctoral student in the Department of Tourism, Recreation, and Sport Management who is conducting research for my PhD dissertation. If you are over 18, and have attended any of the 2012 London Summer Olympics, 2014 Sochi Winter Olympics, 2014 World Cup, or 2015 Wimbledon Championships or watched them through any form of media, I am looking for your help! The purpose of this study is to understand sports fans’ perceptions of sport event sponsorship. Participation in the study requires completion of a brief 2-3 minute online questionnaire containing general demographic information and your interest in sport events. HERE IS THE LINK OF SURVEY: XXXXX At the end of the online questionnaire you may be asked to participate in a 60-90 minute focus group about your perceptions of sport events and official sponsors of sport events. The focus group will take place in a conference room in the Florida Gym with 5-7 other people on a time and a day convenient to you between June 1 – September 10. You will get $10 Starbucks gift card for participating in the group interview. There will be also light snacks served during the group interview. If you have any questions or comments, please contact me by email at [email protected]. Thank you. Sincerely, Ari Kim, MS Department of Tourism Recreation and Sport Management Heather Gibson (Faculty Supervisor), PhD Department of Tourism Recreation and Sport Management
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ON CAMPUS FLYERS
Research Volunteers Needed!
If you are over 18, and have attended any games of the 2012 London Summer Olympics, 2014 Sochi Winter Olympics, 2014 World Cup, or 2015 Wimbledon Championships or watched them through any forms of media, we need your help!
The purpose of this study is to understand sports fans’ perceptions of sport event sponsorship.
Participation in the study requires completion of a brief 2-3 minute online questionnaire. Then you may be asked to participate in a 60-90 minute focus group on campus.
Please contact Ari Kim at [email protected], 352-672-3227
If you are interested in participating the study!
A $10 gift card and light snack will be provided during the group interview!
Olympic Games Wimbledon Championships World Cup
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APPENDIX B QUALITAIVE STUDY INSTITITUIONAL REVIEW BOARD APPROVAL
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APPENDIX C ONLINE QUESTIONNAIRE FOR QUALITATIVE STUDY PARTICIPANTS
RECRUITMENT
Thank you for your participation! The study is being conducted by Ari Kim, a doctoral student from the Department of Tourism, Recreation and Sport Management at the University of Florida. Please read this consent document carefully before you decide to participate in this study. This study is designed to understand sports fans’ perceptions of sponsor–event fit and identify domains of sponsor–event fit in sports fans’ minds. You will be asked to participate in a 2-3 minute online questionnaire. At the end of the online questionnaire you may be asked to participate in a 60-90 minute focus group about your perceptions of sport events and official sponsors of sport events on a time and a day convenient to you between May 25 and September 10. With your permission, I will audiotape the interview. The audio recording will be accessible only to the research team. At the end of the study, the tape will be erased. All names will be replaced with pseudonyms to ensure confidentiality and anonymity. Your IP address information will not be collected or stored for any purpose. Your identity will be kept confidential to the extent provided by law. The results will only be reported in the form of general population data. Participation is completely voluntary, and you may withdraw your consent to participate without penalty. You have the right not to answer any question/s. You have the right to ask that information revealed in the course of the interview not be used in the analysis. There are no known risks to you as a participant. There will be light snacks served during the group interview, but no monetary compensation is offered for participation. If you have any questions about this research protocol, please contact: Ari Kim, MS / PhD student, Department of Tourism, Recreation and Sport Management, Room 300, Florida Gym, PO Box 118208, Gainesville, FL 32611-8208 Phone: (352) 672-3227; e-mail: [email protected] Heather J. Gibson, PhD / Professor, Department of Tourism, Recreation and Sport Management, Room 304, Florida Gym, PO Box 118208, Gainesville, FL 32611-8208 Phone: (352) 294-1649, Ext. 1249; e-mail: [email protected] Questions or concerns about your rights as a research participant may be directed to the IRB02 Office, University of Florida, Box 112250, Gainesville, FL 32611, (352) 392-0433. Q1. I have read and understood the above consent form and agree to participate in this study
Yes, I agree to participate.
No, I do not want to participate in the study.
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Q2. Have you attended as a spectator at the following sport event?
2012 London Summer Olympic
Games
2014 Sochi Winter Olympic
Games
2014 Brazil World Cup
2015 Wimbledon Championship
Yes
No
Q3. Have you ever watched the following sport event through media?
2012 London Summer Olympic
Games
2014 Sochi Winter Olympic
Games
2014 Brazil World Cup
2015 Wimbledon Championship
Yes
No
Q4. To me, watching sport events is
Extreme
ly Quite Slightly Neither Slightly Quite
Extremely
boring 1 2 3 4 5 6 7 exciting
uninteresting 1 2 3 4 5 6 7 interesting
worthless 1 2 3 4 5 6 7 valuable
unappealing 1 2 3 4 5 6 7 appealing
useless 1 2 3 4 5 6 7 useful
not needed 1 2 3 4 5 6 7 needed
irrelevant 1 2 3 4 5 6 7 relevant
unimportant 1 2 3 4 5 6 7 important
Q5. Are you
Male
Female
Q6. What year were you born? ___________
Q7. Which of the following describes your current employment status? (Choose all that apply) Student
Employed full time
Employed part time
Unemployed/Looking for work
Homemaker
Retired
Other ____________________
Q8. Would you describe yourself as
American Indian/Native American
Asian
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Black/African American
Hispanic/Latino
White/Caucasian
Pacific Islander
Other ____________________
Q9. What is the highest level of education you have completed?
Less than high school
High school/GED
Some college
Two-year college degree
Four-year college degree
Master’s degree
Doctoral degree
Q10. (Instruction for online survey: ask only for those who answer Q7 “some college” or
above) What is your college major? ________________ Q11. What was your 2014 combined annual household income?
Less than 30,000
30,000 – 39,999
40,000 – 49,999
50,000 – 59,999
60,000 – 69,999
70,000 – 79,999
80,000 – 89,999
90,000 – 99,999
100,000 or more
Q12. In order to contact you if you are selected to participate in this study, please provide the following contact information. Your contact information will not be used for any purpose outside of this study.
First Name: Last Name: E-mail Address: Confirm E-mail Address: Phone Number:
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APPENDIX D FOCUS GROUP DISCUSSION GUIDE
Thank you for participating in this study. Today, we will talk about your perceptions of sport
events and sponsors of sport events. I am going to record our talk so I can remember all of the
details. Do you mind if I record this interview? This is a group discussion, and all of you are free
to say whatever you think during the session. There are no right or wrong answers. There also
will be some group activities during the session.
1. Before we start talking about the topic, can you briefly tell about yourselves?
2. Today, we are talking about sport events and sport event sponsorship. Can you think of any sport event and sponsor pairs? a. Why do you think that event–sponsor pair came to mind? What makes this
sponsorship so well remembered? b. Can you think of any strange/odd event–sponsor pairs? Why do you think it was
strange/odd?
3. Now we will conduct the group activities. Here are 3 sport events and 30 sponsoring brand names and logos. On this space,[a big sheet of white paper will be placed on the table]please place the brands and sport event cards closer or further apart depending on how well you think they fit together in a sponsorship situation. The pairs that are closer together represent better fit. Try to make a map as a group, but you don’t have to complete the map. If you have a different opinion from someone else, feel free to talk about it. (Note: 2” x 6” cardboard with event/sponsoring brand names and logos will be prepared for each event/brand. A total of 33 cardboards (3 events and 30 brands) will be placed on a 30” x 30” white paper). a. Why do you to want to put this event/brand here? b. This event/brand seems too far from that event/brand. Why did you position this
here? What makes you think these two are close/far from each other?
4. In general, why do you think corporations sponsor sport events? a. What are the benefits of sponsoring sport events for brands? b. Is there any perceived risk for brands in sponsoring sport events? If so, describe. c. What should be considered by marketing executives before making a sponsorship
agreement?
5. Now let’s think about sponsorship from the event organizer’s point of view. a. What are the benefits of having corporate sponsors? b. Is there any perceived risk for sport events to have sponsors? If so, what are they? c. What should be considered by an event organizer before making a sponsorship
agreement?
6. Please tell me about your previous experiences with sport events and sport event sponsors.
7. Is there any particular event you are interested in? How much were you involved in that event/in what way were you involved in that event?
8. Is there anything else you would like to add? Thank you so much for your time.
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APPENDIX E PILOT STUDY INSTITITUIONAL REVIEW BOARD APPROVAL
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APPENDIX F PILOT STUDY QUESTIONNAIRE
Dear Participants; The information collected by these questionnaires in this survey will be used to understand sports fans’ perceptions of sponsor–event fit and identify domains of sponsor–event fit in sports fans’ minds. This survey should take no more than 10 minutes of your time. It would be greatly appreciated if you would simply complete the following questionnaires. Your participation is completely voluntary, and your identity will be kept confidential to the extent provided by law. Your IP addresses may be collected, but it will be destroyed right after the completion of data. We guarantee that your responses will not be identified with you personally. The results will only be reported in the form of general population data. There are no known risks to you if you decide to participate in this survey. Your answers and information will not be used for any other purpose but just for the current research. There will be a screening question to check your eligibility at the beginning of the survey and only qualified individuals will proceed to answer the remaining questions. You will be credited 50 cents after completing this survey. You may withdraw your consent at any time without penalty. If you have any questions about this research protocol, please contact: Ari Kim, MS / PhD Candidate, Department of Tourism, Recreation and Sport Management, Room 300, Florida Gym, PO Box 118208, Gainesville, FL 32611-8208 Phone: (352) 672-3227; e-mail: [email protected] Heather J. Gibson, PhD / Professor, Department of Tourism, Recreation and Sport Management, Room 304, Florida Gym, PO Box 118208, Gainesville, FL 32611-8208 Phone: (352) 294-1649, Ext. 1249; e-mail: [email protected] Q1. I have read and understood the above consent form and agree to participate in this study.
Yes, I agree to participate.
No, I do not want to participate in the study.
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*Programming instruction: There will be 3 versions of questionnaire with 3 different sport events (2016 Summer Olympic Games, 2014 FIFA World Cup, and 2016 Wimbledon Championship). Three versions will randomly assigned to each participants. In each version, 10 official sponsor brands of each event will be presented and a participant will answer about the event (Event X) and 10 sponsor brands (Brand A~J). List of Events and Brands:
Version 1 Version 2 Version 3
Event X 2016 Summer Olympic Games
2014 FIFA World Cup 2016 Wimbledon Championship
Brand A Acer Adidas Evian
Brand B Bridgestone Budweiser Häagen-Dazs
Brand C Coca-Cola Castrol Oil Hertz
Brand D Dow Emirates Airlines HSBC
Brand E GE Hyundai-Kia Motors IBM
Brand F Omega Johnson and Johnson Lanson
Brand G Panasonic McDonalds Lavazza
Brand H P&G Sony Ralph Lauren
Brand I Samsung OI Rolex
Brand J VISA Yingli Slanzenger
Q2. Have you ever attended Event X as a spectator or watched Event X through any form of
media? Yes
No
(Programming: If no, terminate.)
Q3. Do you know Brand A? Yes
No
(Programming: If no, skip Q4.)
Q4. Please use the rating scale below to describe how accurately each statement describes
you by checking 1 = strongly disagree or 7 = strongly agree.
Strongly disagree
Strongly
agree
There is a logical connection between Event X and Brand A.
1 2 3 4 5 6 7
The image of Event X and the image of Brand A are similar.
1 2 3 4 5 6 7
Event X and Brand A fit together well. 1 2 3 4 5 6 7
Event X and Brand Y stand for similar things.
1 2 3 4 5 6 7
It makes sense to me that Brand A sponsors Event X.
1 2 3 4 5 6 7
(Programming: Repeat Q3 and Q4 for Brand B~J.)
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Q5. Are you Male
Female
Q6. What year were you born? _______
Q7. Which of the following best describes your current employment status? Student
Employed full-time
Employed part-time
Unemployed/Looking for work
Homemaker
Retired
Other ____________________
Q8. Would you describe yourself as
American Indian/Native American
Asian
Black/ African American
Hispanic/Latino
White/Caucasian
Pacific Islander
Other ____________________
Q9. What is the highest level of education you have completed?
Less than High School
High School / GED
Some College
2-year College Degree
4-year College Degree
Master’s Degree
Doctoral Degree
Q10. What is your 2016 combined annual household income?
Less than 30,000
30,000 – 39,999
40,000 – 49,999
50,000 – 59,999
60,000 – 69,999
70,000 – 79,999
80,000 – 89,999
90,000 – 99,999
100,000 or more
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APPENDIX G EXPERT REVIEW MATERIALS
Content validity of the sponsor–event fit measurement items The purpose of my dissertation is to develop a measurement scale to assess the fit between the sport event and sponsoring brand (sponsor–event fit scale). Sponsor–event fit can be defined as the extent to which the sponsor and the event are perceived as similar, whether on the basis of functionality, attributes, images, or other key associations. And I hypothesize that there are three subdomains of sponsor–event fit: image-based fit, functional-based fit, and brand characteristics. Here is a list of potential items to measure three subdomains of sponsor–event fit. Survey participants for my study will be asked to rate how much they disagree or agree with the following statements using seven-point Likert style scale: Strongly disagree-Strongly agree. Please evaluate the content validity of each item with following criteria (i.e., relevance, representativeness, and clarity) using the 5 point scale (i.e., write down a number from 1 to 5 where 1 = unacceptable, 2 = poor, 3 = acceptable, 4 = good, 5 = excellent). And please write in your comments if there is any concerns or suggestion for changes for each item. Relevance. How closely each item is relevant to the construct Representativeness. How much each item represents the construct Clarity. How clearly each item was worded. 1. Image-based fit. Image-based fit construct is to measure the similarity between the event image and the brand image. The measurement items were developed to measure how well or poorly the perceived images of sponsoring brand match the given sport events. Please evaluate the content validity of each item and write in your comments.
Relevance Representativeness
Clarity Comments/Corrected sentence
Active and Healthy image. The extent to which sponsor and sport event are well matched in terms of core values and images of sports such as active, energetic, and healthy.
The (brand X) and (event Y) share an active image.
The (brand X) and (event Y) share an energetic image.
The (brand X) and (event Y) share a healthy image.
The (brand X) and (event Y) share a leisurely image.
The (brand X) and (event Y) share a sporty image.
The (brand X) and (event Y) share an exciting image.
Caring Community. The extent to which a sponsor has a goodwill to the community.
The (brand X) is an organization that helps the community that are connected to the (event Y).
The (brand X) shares image with (event Y) because they encourages sport participation.
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The (brand X) shares image with (event Y) invests in sports.
The (brand X) shares image with (event Y) because they support youth athletes.
The (brand X) shares image with (event Y) because they cares about environment and sustainability
Compatibility. The extent to which consumers’ perception of sponsors and events compatible.
The sizes of the (brand X) and (event Y) are similar.
The role of (brand X) in the community is as important as that of (event Y).
The (brand X) and (event Y) have similar reputations in the world.
It makes sense to me that (brand X) sponsors (event Y) because (brand X) is well known.
The (brand X) is capable to sponsor the (event Y).
The (brand X) can afford to sponsor the (event Y).
It makes sense to me that (brand X) sponsors (event Y) because (brand X) is highly regarded in the industry.
Socioeconomic Status of Consumer. The extent to which the sport event and sponsoring brand’s target consumers/audiences overlap.
The characteristics of consumers of (brand X) and spectators of (event Y) are similar.
The Socioeconomic characteristics of those who use (brand X)'s product or service are also those of (event Y)’s fans.
It makes sense to me that (brand X) sponsors (event Y) because (brand X)’s target consumers would watch the (event Y).
The (brand X)’s target market or users reminds me of the people associated with (event Y).
Please write in any concerns regarding image-based fit construct or suggestion for any additional item to be included.
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2. Functional-based fit. Functional-based fit construct is to measure consumers’ beliefs about sponsors’ helping the event to be successful by offering their products or services. Here, it will be measured whether the sponsors’ product or service is in use by various types of event participants (athletes, event organizers, and spectators). Please evaluate the content validity of each item and write in your comments.
Relevance Representativeness
Clarity Comments/Corrected sentence
Athlete Use During the Game. The extent to which the athletes use the sponsor’s product or service during the game.
Athletes in the (event Y) use the (brand X)’s product or service during the game.
It is common for athletes to use the (brand X)’s product or service while they play in the (event Y).
The use of product or service of (brand X) is essential to athletes to successfully play in the (event Y).
I expect that the (brand X)’s product or service is in use by athletes during the (event Y).
I believe (brand X) helps (event Y) because their product or service are used by the athletes during the (event Y).
Operational Use. The extent to which the sponsor’s product or service is used during the game for operational purposes.
The product or service of (brand X) is used to operate the (event Y).
The product or service of (brand X) is helpful for making the (event Y) successful.
It is natural that the product or service of (brand X) are in use to operate the (event Y).
(Event Y)'s organizers need to use (brand X)'s product or service to manage the game.
I believe (brand X) helps (event Y) because their product or service are used by event organizers.
Audience Consumption During the Game. The extent to which the event audiences consume the sponsor’s product or service during the game.
When watching (event Y) on television or on the spot, viewers are likely to consume the product or service of the (brand X).
I would think of using (brand X)'s product or service while I am
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watching (event Y) on television or on the spot.
It makes sense to me that (brand X) sponsors (event Y) because (brand X)’s product or service would be used by (event Y)’s spectators during the game.
The product or service of (brand X) will help (event Y)’s audience to have a better experience during the game.
Please write in any concerns regarding functional-based fit construct or suggestion for any additional item to be included.
3. Brand Characeristics. Brand characteristics construct is to measure sponsor–brand association based on the sponsoring brand’s various features. Please evaluate the content validity of each item and write in your comments.
Relevance Representativeness
Clarity Comments/Corrected sentence
Symbolic Feature. The extent to which sponsoring brand’ symbolic features such as brands’ names, logos, and colors link to the event in consumers’ mind.
(Brand X)’s use of color or visual attributes is similar to the colors/images associated with (event Y).
(Brand X)’s slogan is a clever play on words incorporating (event Y).
(Brand X)’s slogan works well with (event Y).
(Brand X)’s logo is well matched with (event Y).
The visual presentation and colors of the (brand X) and the (event Y) overlap with each other.
(Brand X)'s symbolic features are complementary with (event Y).
Relevance Representativeness
Clarity Comments/Corrected sentence
Geographical Characteristics. The extent to which the sponsoring brand and the sport event have ties to the same geographic area.
The geographical origin of (brand X) is similar to the location in which (event Y) takes place.
(Brand X)’s country of origin is somehow related to the (event Y).
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The geographical target market of (brand X) is similar to the location(s) associated with (event Y).
(Event Y) is popular in the region where (brand X) is highly regarded.
The locations (either global or local) associated with (brand X) is similar to the locations associated with (event Y).
It makes sense to me that (brand X) sponsors (event Y) because the viewership of (event Y) is high in the target region of (brand X).
Product Coverage. The extent to which the range of products or service is matched with the event.
The range of product or service that (brand X) covers matches well with the (event Y).
The product or service category of (brand X) is related to the sport(s) that are played in the (event Y).
It makes sense to me that (brand X) sponsors (event Y) because the variety of (brand X)’s product or service is well matched to the characteristics of (event Y).
Length of sponsorship. The perceived time duration of the brand sponsoring the event in consumers’ mind.
The (brand X) has been sponsoring (event Y) for a long time.
The (brand X) and (event Y) have a long-term relationship associating them with one another.
I have known the (brand X) as a sponsor of (event Y) for a long time.
It is natural to link (brand X) and (event Y) together because of their long term sponsorship agreement.
Please write in any concerns regarding brand characteristics construct or suggestion for any additional item to be included.
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APPENDIX H QUANTITATIVE STUDY QUESTIONNAIRE
RECRUITMENT STATEMENT Sports Event Sponsor Survey Give us your opinion about sports events and their corporate sponsors! We are conducting an academic survey about sports events and the official sponsors of those events. We need to understand sports fans’ perceptions of how well the sponsors fit with the sports events. Please select the link below to complete the survey if you have watched or attended in any of these events: the Olympic Games, FIFA World Cup, Wimbledon Championship, NASCAR Daytona 500, or NYC Marathon.
At the end of the survey, you will receive a code to paste into the box below to receive credit for completing our survey. There will be a screening question to check your eligibility at the beginning of the survey and only qualified individuals will proceed to answer the remaining questions.
Thank you!
Keywords: survey, sports, sports event, sponsor, Olympic, FIFA, Wimbledon, NASCAR, NYC Marathon Reward per Assignment: $1.00
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INFORMED CONSENT AND SURVEY QUESTONNAIRE
Dear Participants,
I am conducting research on sports fans’ perceptions of sports events and their sponsors. The
information collected in this survey will be used to understand the fit between mega or major
sports events and their sponsors. The study is being conducted by researchers from the
Department of Tourism, Recreation, and Sport Management at the University of Florida.
This survey should take no more than 15 minutes of your time, and it requires that you complete
the questionnaire below.
There are no anticipated risks associated with participating in this study. We guarantee that your responses will not be identified with you personally. The results will only be reported in aggregated form. Your identity will be unknown to us, and your responses will be anonymous. There is no way to connect your identity to your responses.
There is a minimal risk that security of any online data may be breached, but our survey host (Qualtrics) uses strong encryption and other data security methods to protect your information. Only the researchers will have access to your information on the Qualtrics server. The data file will be kept on the research team members’ secure server and will be deleted once the study is finished. For the Qualtrics Security Statement, please see http://www.qualtrics.com/security-statement.
Your MTurk Worker ID will be used only for awarding compensation and will not be shared with anyone outside the research team. It will not be linked with your survey responses and will be removed from the data set once compensation has been made. (Note that your Worker ID can be linked to your Amazon user’s public profile page, so you may wish to restrict what information you choose to share in your public profile.)
There will be screening questions about your previous experience of watching a sports event
and knowledge of a sponsor at the beginning of the questionnaire. We will check your eligibility
based on your answer, and only qualified individuals will proceed to answer the remaining
questions. If you are not qualified for the study, the survey will terminate after the screening
question, and you will not obtain any credit. If you are qualified to participate in and continue the
survey, you will be credited a US dollar ($1) after completing this survey.
Your participation in this study is completely voluntary, and you have the right to withdraw at any time and/or not to answer any question without consequences. There are no “correct” or “incorrect” answers in this survey. This study has been reviewed and approved by the University of Florida Institutional Review Board for human subject participation.
If you have any questions about this research protocol, please contact:
Ari Kim, MS / PhD Candidate, Department of Tourism, Recreation and Sport Management,
Room 300, Florida Gym, PO Box 118208, Gainesville, FL 32611-8208,
Phone: (352) 672-3227; e-mail: [email protected]
Heather J. Gibson, PhD / Professor, Department of Tourism, Recreation and Sport
Management, Room 304, Florida Gym, PO Box 118208, Gainesville, FL 32611-8208,
Phone: (352) 294-1649; e-mail: [email protected]
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If you have questions about your rights as a participant in this study, please contact the
University of Florida IRB office, P.O. Box 112250, University of Florida, Gainesville, FL32611-
2250, Phone: 352-392-0433; e-mail: [email protected]
I have read and understood the above consent form, and I agree to participate in this study.
1. Yes, I agree to participate in the study. 2. No, I do not want to participate in the study.
Programming instruction: There will be 10 versions of the questionnaire with 5 different sports events (2016 Summer Olympic Games, 2014 FIFA World Cup, 2016 Wimbledon Championship, 2017 Daytona 500, and 2016 Boston Marathon) and 2 official sponsoring brands of each event. Ten versions will randomly and be evenly assigned to each participant.
Event Y Brand X Fit
2016 Summer Olympic Games VISA H
2016 Summer Olympic Games Acer L
2014 FIFA World Cup Adidas H
2014 FIFA World Cup Castrol Oil L
2016 Wimbledon Championship Rolex H
2016 Wimbledon Championship Häagen-Dazs L
2017 Daytona 500 Goodyear H
2017 Daytona 500 Microsoft L
2016 New York City Marathon New Balance H
2016 New York City Marathon Dunkin’ Donuts L
SECTION I: SCREENING QUESTIONS Have you watched (event Y) as a spectator in person or through any form of media?
1. Yes 2. No
(Programming: If no, terminate.)
Have you heard of (brand X)?
1. Yes 2. No
(Programming: If no, terminate.)
Have you ever purchased or used the product or service of (brand X)?
1. Yes 2. No
SECTION II: SPONSOR–EVENT FIT Image-Based Fit Please rate the following items from 1 (strongly disagree) to 7 (strongly agree) based on your perception of (brand X) and (event Y). (Programming: Rotate items that belong to one dimension.)
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Active and Healthy image 1. (Brand X) and (event Y) share an active image. 2. (Brand X) and (event Y) share an energetic image. 3. (Brand X) and (event Y) share an image of health. 4. (Brand X) and (event Y) share a lively image. 5. (Brand X) and (event Y) share a sporty image.
Goodwill toward Sport 6. (Brand X) shares an image with (event Y) because (brand X) invests in sports. 7. (Brand X) shares an image with (event Y) because (brand X) supports young athletes. 8. (Brand X)’s philanthropic effort for the sports industry makes me associate (brand X)
with (event Y). 9. (Brand X) shares an image with (event Y) because (brand X) has the best interests of
the sport at heart. Compatibility
10. To me, the market sizes of (brand X) and (event Y) are similar. 11. The role of (brand X) in the world is as important as that of (event Y). 12. (Brand X) and (event Y) have similar reputations. 13. It makes sense to me that (brand X) sponsors (event Y) because both (brand X) and
(event Y) are highly regarded in their respective industries. Socioeconomic Status of Consumer
14. Consumers of (brand X) and spectators of (event Y) share similar characteristics. 15. The socioeconomic characteristics such as income, education level, and occupation of
those who use (brand X)’s product or service are similar to those of (event Y)’s fans. 16. It makes sense to me that (brand X) sponsors (event Y) because (brand X)’s target
consumers would watch (event Y). 17. When I think of the people who use or buy (brand X), they are similar to the people who
are interested in (event Y).
Functional-Based Fit
Please rate the following items from 1 (strongly disagree) to 7 (strongly agree) regarding your perception of (brand X) and (event Y). (Programming: Rotate items that belong to one dimension.) Athlete Use during the Event
1. Athletes in (event Y) use (brand X)’s product or service during the event. 2. It is common for athletes to use (brand X)’s product or service while they play/participate
in (event Y). 3. I expect that (brand X)’s product or service is used by athletes during (event Y). 4. I believe (brand X) helps (event Y) because their product or service is used by the
athletes during (event Y). Operational Use
5. The product or service of (brand X) is used during the operation of (event Y). 6. The product or service of (brand X) is helpful in making (event Y) well managed. 7. It makes sense that the product or service of (brand X) is used in (event Y). 8. (Event Y)’s organizers need to use (brand X)’s product or service to manage the event. 9. I believe (brand X) helps (event Y) because its product or service is used by event
organizers. 10. The product or service category of (brand X) is related to the sport that is played in
(event Y).
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Audience Consumption during the Event
11. When watching (event Y) on television or live at the event, viewers are likely to consume the product or service of (brand X).
12. I would think of using (brand X)’s product or service while I am watching (event Y) on television or live at the event.
13. It makes sense to me that (brand X) sponsors (event Y) because (brand X)’s product or service would be used by (event Y)’s spectators during the event.
14. The product or service of (brand X) will help (event Y)’s audience have a better experience during the event.
Brand Characteristics
Please rate the following items from 1 (strongly disagree) to 7 (strongly agree) based on your perception of (brand X) and (event Y). (Programming: Rotate items that belong to one dimension.) Symbolic Features
1. The colors and graphics of (brand X) are similar to the colors and graphics of (event Y). 2. (Brand X)’s slogan works well with (event Y). 3. (Brand X)’s logo is well matched with (event Y). 4. The visual presentations of (brand X) and (event Y) overlap with each other. 5. (Brand X)’s symbolic features are complementary with (event Y).
Geographical Characteristics 6. The geographical origin of (brand X) is close to the location in which (event Y) takes
place. 7. (Brand X)’s country of origin is somehow related to (event Y). 8. The geographical target market of (brand X) is similar to the location(s) associated with
(event Y). 9. (Event Y) is popular in the region where (brand X) is highly regarded. 10. (Brand X) has its businesses in the locations associated with (event Y). 11. It makes sense to me that (brand X) sponsors (event Y) because the viewership of
(event Y) is high in the target region of (brand X). Length of sponsorship
12. I believe (brand X) has been sponsoring (event Y) for a long time. 13. I think (brand X) and (event Y) have a long-term relationship associating them with one
another. 14. I have known (brand X) as a sponsor of (event Y) for a long time. 15. It is natural to link (brand X) and (event Y) together because of their long-term
partnership.
Overall Fit
Please rate the following items from 1 (strongly disagree) to 7 (strongly agree) based on your perception of (brand X) and (event Y).
1. There is a logical connection between (event Y) and (brand X). 2. The image of (event Y) and the image of (brand X) are similar. 3. (Event Y) and (brand X) fit together well. 4. (Event Y) and (brand X) stand for similar things. 5. It makes sense to me that (brand X) sponsors (event Y).
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Why do you think (brand X) and (event Y) fit together (or not)? What makes you think (brand X) and (event Y) fit together or don’t fit together? Please explain below.
SECTION III: Event Involvement
How do you feel about the Olympic Games based on the following set of opposite adjectives? To me, watching the Olympic Games is… Extremely Quite Slightly Neither Slightly Quite Extremely
boring 1 2 3 4 5 6 7 exciting
uninteresting 1 2 3 4 5 6 7 interesting
worthless 1 2 3 4 5 6 7 valuable
unappealing 1 2 3 4 5 6 7 appealing
useless 1 2 3 4 5 6 7 useful
not needed 1 2 3 4 5 6 7 needed
irrelevant 1 2 3 4 5 6 7 relevant
unimportant 1 2 3 4 5 6 7 important
SECTION IV: Sponsorship Outcomes
Thinking about (brand X) sponsoring (event Y), how much do you agree or disagree with the following statements? Please rate the following items from 1 (strongly disagree) to 7 (strongly agree). Favorability
1. This sponsorship makes me feel more favorable towards (brand X). 2. This sponsorship would improve my perception of (brand X). 3. This sponsorship would make me like (brand X) more.
Interest
1. This sponsorship would make me more likely to notice (brand X)’s name on other occasions.
2. This sponsorship would make me more likely to pay attention to (brand X)’s advertising. 3. This sponsorship would make me more likely to remember (brand X)’s promotion.
(Intention to) Use
1. This sponsorship would make me more likely to use (brand X)’s product or service. 2. This sponsorship would make me more likely to consider (brand X)’s product or service
the next time I buy. 3. I would be more likely to buy from (brand X) because of this sponsorship.
Word of Mouth
1. This sponsorship would make me more likely to mention (brand X) to others in the future.
2. This sponsorship makes me tell more people about (brand X) than about other brands. 3. This sponsorship makes me not miss an opportunity to tell others about (brand X).
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SECTION V: Demographic Background
1. Are you a. Male b. Female
2. In what year were you born? ___________ 3. Which of the following best describes your current employment status?
a. Student
b. Employed full time
c. Employed part time
d. Unemployed/Looking for work
e. Homemaker
f. Retired
g. Other ____________________
4. Would you describe yourself as
a. American Indian/Native American
b. Asian
c. Black/African American
d. Hispanic/Latino
e. White/Caucasian
f. Pacific Islander
g. Other ____________________
What is the highest level of education you have completed?
a. Less than high school
b. High school/GED
c. Some college
d. Two-year college degree
e. Four-year college degree
f. Master’s degree
g. Doctoral degree
5. What is your current status? a. Single, never married
b. Married without children
c. Married with children
d. Divorced
e. Separated
f. Widowed
g. Living w/ partner
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6. What was your 2016 combined annual household income in USD? a. Less than 30,000
b. 30,000 – 39,999
c. 40,000 – 49,999
d. 50,000 – 59,999
e. 60,000 – 69,999
f. 70,000 – 79,999
g. 80,000 – 89,999
h. 90,000 – 99,999
i. 100,000 – 119,999
j. 120,000 – 149,999
k. 150,000 or more
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APPENDIX I QUANTITATIVE STUDY INSTITITUIONAL REVIEW BOARD APPROVAL
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BIOGRAPHICAL SKETCH
Ari Kim received her Doctor of Philosophy in Health and Human Performance,
majoring in sport management, from the University of Florida in 2017. Prior to this, Ari
earned a Bachelor of Business Administration and a Master of Science in marketing
from the School of Business at Yonsei University, South Korea. Before entering the
doctoral program at UF, she worked at TNS, a leading market research and information
company, as a senior marketing research executive. Her four-year professional
experience in the marketing research field primarily involved examining consumer
response to various marketing stimuli, including sponsorship activations and
advertisements of Olympic Sponsors.
Ari’s research interests include sport marketing, sport consumer behavior, and
sport communication. She primarily focuses on the antecedents of sponsorship
outcomes within the mega sport event context. Ari is also interested in the role of media
and communication strategies in promoting sport events. Ari is a member of several
professional organizations and has presented her research at the North American
Society for Sport Management (NASSM) and the Sport Marketing Association (SMA)
annual conferences.