Measurement
Journal of Sport Management, 2006, 20, 260-279
© 2006 Human Kinetics, Inc.
Development of a Scale to Measure Team
Brand Associations in Professional Sport
Stephen D. Ross
University of Minnesota
Jeffrey D. James
Florida State University
Patrick Vargas
University of Illinois
The Team Brand Association Scale (TBAS), which is intended to measure
professional sport team brand associations, was developed through the use of a
free-thought listing technique in combination with a confirmatory factor analysis
procedure. Information was provided by individuals regarding their favorite sports
team, and 11 dimensions underlying professional sport team brand associations
were identified: nonplayer personnel, team success, team history, stadium community, team play characteristics, brand mark, commitment, organizational attributes,
concessions, social interaction, and rivalry. Review of the TBAS psychometric
properties indicated that eight dimensions had acceptable reliabilities (Cronbach’s
alpha scores ranging from .76-.90), as well as content validity (verified by a 3member expert panel review), discriminant validity (based on correlations among
latent constructs and their standard errors), concurrent validity (significant correlations with an external measure), and construct validity.
Given the steady escalation in professional sport team franchise values, a
long-term focus on the brand equity of a franchise will increasingly dictate the
actions of team sport managers (Gladden, Irwin, & Sutton, 2001). David Aaker
(1996) and Kevin Keller (1993) proposed perhaps the most notable theories of
brand equity. Aaker conceptualized brand equity as an aggregate variable of the
four categories, or dimensions, of brand assets: brand awareness, brand loyalty,
perceived quality, and brand associations. Though he did not suggest a specific
measure of brand equity, he proposed that the four components could directly
Ross is with the University of Minnesota, 218 Cooke Hall, 1900 University Ave. S.E., Minneapolis,
MN 55455; James is with Florida State University, Dept. of Sport Management, Recreation Management,
& Physical Education, 110 Tully Gym, Tallahassee, FL 32306-4280; Vargas is with the University of
Illinois, 103 Gregory Hall, MC 462, 810 S. Wright Street, Urbana, IL 61801.
260
Brand Association Scale Development 261
create brand equity. Within Aaker’s framework brand associations are anything
linked in memory to the brand, perceived quality is a consumer’s judgment of a
product’s overall excellence relative to its intended purpose, and brand loyalty is
thought of as the capability of attracting and retaining customers. Before these
three components are manifest, however, the fourth component, brand awareness,
must be present.
In response to the lack of a specific framework for understanding brand equity,
Keller (1993) proposed the multidimensional construct of brand knowledge as a
determinant of consumer-based brand equity. Keller’s notion of consumer-based
brand equity and Aaker’s framework have two key features in common. Keller’s
proposal included brand awareness and brand associations, two of Aaker’s four
dimensions. Berry (2000) adopted a different approach with his research into service
brand equity. He analyzed the strategies of 14 mature high-performance service
companies to produce a service-branding model of brand equity. He claimed that
in packaged goods the product is the primary brand, whereas for services, including sports teams, the organization is the primary brand. The locus of brand differs
for services because they lack the tangibility that allows packaging, labeling, and
displaying. Even more important is the source of customer value creation. Brand
impact shifts from product to organization as service plays a greater role in determining customer value (Berry & Parasuraman, 1991). The distinction provided by
Berry is similar to that of corporate branding. Specifically, an organization engages
in corporate branding when it markets the organization itself as the brand (Argenti
& Druckenmiller, 2004).
Up until the mid-1990s managers interpreted corporate branding as the strategic
process of leveraging the equity in the corporate name across an expanding array of
products (de Chernatony, 2002). Around the mid-1990s, researchers began to talk
about managers becoming more sophisticated and interpreting corporate brands at a
higher level of abstraction (e.g., Aaker, 1996). Managers began to regard corporate
brands as a dynamic interface between an organization’s actions and customers’
perceptions (Schultz & de Chernatony, 2002). As Berry (2000) maintained in his
discussion of branding a company, a strong brand is a blend of what the organization says the brand is, what others say, and how the organization performs the
service—all from the customer’s point of view.
The theories by Aaker, Keller, and Berry have added considerably to our
knowledge of brand equity; there has been little application of their ideas to
sport, however, and few pieces in the branding literature approach brand equity
from a sport perspective. Among the work that has been done, recent propositions concerning brand equity and sport have attempted to provide an explanation of the concept relative to the unique aspects of sport (Boone, Kochunny,
& Wilkins, 1995; Gladden, Milne, & Sutton, 1998; Gladden & Milne, 1999;
Gladden et al., 2001). Although these conceptual frameworks have advanced our
understanding of the antecedents and consequences of sport brand equity, work
is still needed to examine the components of brand equity. The next step in the
study of brand equity should focus on developing a thorough understanding of
the specific elements contributing to the construct. One element, and possibly
the most important, that should be examined is brand associations (Aaker, 1991,
1996; Keller, 1993).
262 Ross, James, and Vargas
Brand Associations
Brand associations are the thoughts and ideas that an individual holds in his
or her memory for a particular good or service (Aaker, 1991; Keller, 1993). These
associations can take on a variety of forms, including tangible, functional associations, and intangible, experiential associations (Shocker, Srivastava, & Ruekert,
1994). Keller (1993) proposed that brand associations can be classified as attributes,
benefits, or attitudes.
Attributes are categorized as product-related or non-product-related. Productrelated attributes are defined as the ingredients necessary for performing the product
function sought by consumers. Non-product-related attributes are defined as external
aspects of a good or service that relate to its purchase or consumption. Benefits
represent the meaning and value consumers attach to the product (Keller, 1993)
and can be further distinguished into three categories according to the underlying
motivations to which they relate (Park, Jaworski, & MacInnis, 1986): functional,
experiential, and symbolic. Finally, attitudes are defined in terms of a consumer’s
overall evaluation of a brand and often depend upon the strength and favorability
of the attributes and benefits provided by the brand (Keller, 1993). Although Keller
did not suggest what specific associations consumers might possess, he did propose
that the associations would fit within the three broad categories.
The Importance of Understanding Sport Brand Associations
Although sport managers have begun to realize the importance of investing in
brands and the creation of favorable associations in regard to attracting consumers,
the process by which brand associations are identified and measured is still in the
developmental stage. From an organizational perspective, relevant and accurate
research on brand associations is imperative for brand managers seeking to effectively manage a brand (Kapferer, 1997; Keller, 1998). From the sport team perspective, sport managers need to understand the components of brand equity so that it
might be effectively manipulated (Gladden & Funk, 2002). Literature relevant to
relationship between brand association and brand image suggests that associations
aid in the creation (and transformation) of image (Faircloth, Capella, & Alford,
2001). That is, when consumers perceive a brand in a specific way, an image of the
brand is created. Cobb-Walgren, Ruble, and Donthu (1995) maintain that from the
perspective of the individual consumer, a hierarchical-effects framework helps to
explain the relationship between brand associations and brand image. Consumers
form perceptions about the tangible and intangible associations of a brand through
various information sources such as advertising and personal experience. These
perceptions, in turn, contribute to the meaning of the brand for consumers.
Given the importance of this relationship, a more complete understanding of
brand associations can contribute to enhancing the image, awareness, and revenues
of a team and its programs. More specifically, if the sport marketer understands
what association(s) spectators and fans hold, then marketing activities could be
controlled more efficiently to create favorable brand images and to reinforce
the positive brand associations that already exist. For example, various forms of
advertising that promote specific attributes of the sport product might influence an
individual’s support of a favorite sport or team (Cobb-Walgren et al., 1995).
Brand Association Scale Development 263
Stemming from the importance of brand associations to management, the
consequences of managers failing to grasp the full breadth and depth of associations people have for brands can be quite serious. For example, when managers’
understandings of customer brand perceptions and the way brands are positioned
relative to competitors in the mind of customers are biased, opportunities for
new or improved marketing strategies might be missed. In addition, communication strategies might be less effective and managers might fail to discover a
negative development in the positioning of the brand. For example, out-of-date
advertising programs might lead a consumer to believe something that is actually
false about an organization. In addition, when managers are not aware of the
favorable associations relevant to brands in other product categories, the opportunities for important brand extensions and brand alliances might be missed.
Given the importance of identifying and understanding the brand associations
that consumers hold for a sport team, it is essential that brand associations be
accurately measured.
Brand Association Measurement
Only a small number of empirical research studies have examined brand
associations (Aaker, 1991, 1996; Heath, 1999; del Rio, Vazquez, & Iglesias, 2001;
Lederer & Hill, 2001), and very few have focused on brand associations in the context of sport. Gladden and Funk (2002) provided the most thorough examination of
brand associations in sport through the development of the Team Association Model
(TAM), an initial effort to assess dimensions of brand associations. Sixteen dimensions were identified as potential constructs believed to underlie brand associations
in sport. These 16 dimensions were derived based on the three categories proposed
by Keller: attributes, benefits, and attitudes. Gladden and Funk’s framework contributes to the literature regarding sport brand associations and sport brand equity
as a whole; some limitations of the Team Association Model, however, emphasize
the need for further study of the sport brand associations.
One concern with the TAM is the wording of items used to measure sport
brand associations. A review of the item wording indicates that many of the items
deemed brand associations were derived from research assessing factors influencing
attendance (Branvold, Pan, & Gabert, 1997; Fisher & Wakefield, 1998; Wakefield
& Sloan, 1995) and research on sport consumer motives (Branscombe & Wann,
1991; Wakefield, 1995; Wann, 1995) not necessarily team brand associations. For
example, one item assessing a stadium association is worded, “My favorite team’s
stadium enhances the enjoyment of attending games.” Although future research
might examine the relationships among these variables, there is no existing research
supporting the idea that factors influencing attendance and sport consumer motives
are indeed specific team brand associations.
A second limitation with the TAM pertains to the focus groups conducted in
order to clarify the conceptual framework of team associations. Gladden and Funk
(2002) sought open-ended feedback from focus-group participants about why they
followed particular teams and why team brands were strong. The rationales for why
individuals follow specific teams are consistent with the work on sport consumer
motivation and might be related to brand associations, but such ideas are not necessarily specific brand associations.
264 Ross, James, and Vargas
In addition to the TAM, other instruments are purported to measure brand associations (see Table 1). There are, however, several problems regarding the validity
of these scales. First, there is the issue of external validity. Many of the scales were
developed from a manufactured goods perspective, and it is not yet known whether
these scales are applicable to the sport service sector (Cobb-Walgren et al., 1995;
Lederer & Hill, 2001). Second, the need for psychometrically sound instruments
is a necessary condition for developing and testing theories. Although the tools
developed to assess brand associations have been innovative and valuable for an
understanding of the concepts, there are questions regarding their validity. Neither
the psychometric properties nor the applicability of the scales to sport services have
been carefully tested. This absence of testing has led to something of a “blind faith”
mentality regarding brand association measurement.
The most important and fundamental limitation of existing research is the fact
that many of the developed brand association measures have relied upon categories
identified by the researchers themselves (Lederer & Hill, 2001; Gladden & Funk,
2002). Given that brand associations are the consumers’ thoughts when thinking of a
Table 1 Summary of Previous Research on Brand Associations
Author(s)
Setting
Psychometric
Testing?
Limitations
Cobb-Walgren,
Ruble, and
Donthu (1995)
Consumer goods
No
Examined frequency of associations rather than specific
categories. Lack of scale development.
Heath (1999)
Unknown
No
Unclear as to what the scale
items were and how they were
developed. Reliability and
validity not established.
Lederer and Hill
(2001)
Consumer goods
No
Associations generated from
source other than consumers.
Employees of the organization
provided associations. Validity
questionable.
O’Cass and Lim
(2001)
Consumer Goods
No
Used previously developed
scales from other research settings. Appropriateness of the
scale validity questionable.
del Rio, Vazquez, Consumer Goods
and Iglesias
(2001)
Yes
Used previously developed
scales from other research settings.Validity is questionable.
Gladden and
Funk (2002)
Yes
Associations generated from
source other than consumers. The researchers identified
associations through literature
review. Validity is questionable.
Sport Service
Brand Association Scale Development 265
brand (Aaker, 1996), it is therefore the consumer’s thoughts that are being targeted.
Hence, constructs and items assessing brand associations developed by the researcher
might not accurately represent the thoughts of sport consumers. Such measures
would assess a consumer’s evaluation of what the researcher believes are team brand
associations. In response to problems associated with researcher supplied groupings,
Miller, Wattenberg, and Malanchuk (1986) suggest that rather than imposing ad hoc
typologies, respondents themselves be responsible for providing the categories.
The need for an instrument developed from respondents’ perceptions is evident based upon the conceptual definition of brand associations. Because brand
associations have been defined as anything linked in memory to a brand (Aaker,
1991), measures developed through literature reviews and researchers’ brainstorming sessions seem incomplete as tools to measure the thoughts of consumers. The
current base of literature includes these types of measures; by using these measures
the potential for misinterpretation by researchers allowed to make inferences about
the thoughts and emotions of consumers is greater. Therefore, the purpose of this
research endeavor was to develop a reliable and valid measure of professional sport
team brand associations.
Method
Using Churchill’s (1979) suggested procedure the current study implemented
a four-stage research design to develop a scale to measure professional sport team
brand associations. In the first stage a group of respondents completed a thoughtlisting procedure in order to identify the specific associations that are held by
individuals relative to a favorite professional sports team and, ultimately, to formulate initial items for the scale. Given the problems with previous research, this
exploratory technique was particularly important in order to identify the associations truly held by individuals and help establish the validity of the measure. The
second stage involved performing exploratory factor analysis on the initial instrument items in order to identify groupings of items representing brand association
dimensions. In the third stage, a panel of expert reviewers assessed the face and
content validity of the items and proposed scale. In the fourth stage a confirmatory
factor analysis procedure was used to validate the structure established with the
exploratory factor analysis.
Free-Thought Listings
The choice to use a free-thought listing technique was based on the goal to
discover the specific sport team associations that individuals hold regarding their
favorite sports team. In addition, free-thought listing increased the likelihood that
only those responses elicited by the stimulus (i.e., favorite professional sport team)
and those associations that were readily accessible were measured (Cacioppo &
Petty, 1981). Thought-listing forms were administered to 40 undergraduate students
at a large Midwestern university. The use of students was considered appropriate
given that the use of students is common in product and brand choice research
(Biswas & Sherrell, 1993), and they are a captive, easily accessible audience. Just
as important though, students are also significant consumers and users of sport.
266 Ross, James, and Vargas
The participants were given a form and instructed to list their favorite professional
sport team at the top of the form and then to write down the first thoughts that
occurred to them in regards to that team. Individual boxes were provided for each
one of the thought listings.
Of the 40 forms administered, 37 were completed and considered usable for
analysis (92.5% effective response rate). Three of the surveys administered were
not completed by the respondents and were deemed unusable. Griffin and Hauser
(1992) suggest that between 20 and 30 respondents are needed to capture 90–95%
of consumer responses. Considering the exploratory nature of the first stage, the
37 completed forms were deemed sufficient for analysis.
Nearly one-half (44.4%) of the respondents were 22 years of age, whereas onethird of the respondents (33.3%) were between the ages of 19 and 21. The remaining
one-quarter (22.3%) of the respondents were between the ages of 23 and 25. Over
three-quarters (80.6%) of the respondents were White/Caucasian, and 13.9% were
African American. The gender distribution of the respondents was 41.7% female
and 58.3% male. Nearly one-third (29.8%) of the respondents listed between 2
and 5 individual thoughts, one-third (35.1%) listed 6 individual thoughts, and the
remaining 35.1% of the respondents listed between 7 and 10 individual thoughts.
Of the teams listed as favorites, 17 were football teams, 13 were baseball teams,
11 were basketball teams, 3 were soccer teams, and 2 were hockey teams. The list
included professional teams from the United States, as well as two professional
teams from other countries.
The researchers and two coders conducted a content analysis on the individual
thoughts provided in order to identify the initial items for the Team Brand Association Scale (TBAS) by identifying broad categories in which the data were believed to
fit. Each coder analyzed the thought-listing data to ascertain whether the individual
thoughts characterized a specific concept or idea for brand associations, and each
response was labeled to reflect that concept or idea. The individual thoughts were
further examined in order to develop the initial items of the TBAS Scale.
Exploratory Factor Analysis
A questionnaire was constructed using the items identified through analysis
of the thoughts listed by respondents. The questionnaire was administered to a
convenience sample of 395 students from a large Midwestern university, of which
367 were completed and deemed usable for an effective response rate of 92.9%.
Two different versions of the instrument presenting the items in random order were
used to prevent order and fatigue biases. The respondents were instructed to rate the
extent to which they thought of a specific association when thinking of their favorite
professional sport team. All items in the instrument were measured on seven-point
Likert-type scales with response categories anchored by Never (1) and Always (7).
In addition, respondents were asked how long they had been a fan of their favorite
team in order to assess the viability of the sample as sport consumers.
Nearly two-thirds (58.1%) of the respondents were between 18 and 20 years
of age, whereas 37.8% of the respondents were between the ages of 21 and 22.
The remaining 15.8% of the respondents were between the ages of 23 and 29. The
majority of the respondents (87.1%) were White/Caucasian; 4.4% were African
American, and 4.1% were Hispanic. The gender distribution of respondents was
Brand Association Scale Development 267
46.0% female and 54.0% male. The number of years being a fan of the favorite
team ranged from 1 to 25 (M = 13.25), indicating that the respondents were an
appropriate sample of sport consumers.
The scale data were submitted to exploratory factor analysis using the Comprehensive Exploratory Factor Analysis (CEFA) program (Browne, Cudeck, Tateneni,
& Mels, 1999). The factor analysis method used maximum likelihood extraction
with oblique direct quartimin rotation (Iacobucci, 2001). Given that there were no
a priori hypotheses regarding the number of factors that should emerge, a variety of
criteria were used to decide on an appropriate number of factors to retain (Comrey,
1978; Fabrigar, Wegener, MacCallum, & Strahan, 1999; Stevens, 2002): the Kaiser
criterion (Kaiser, 1970), the scree test (Zwick & Velicer, 1982), examination of
the root mean square error of approximation (RMSEA; Browne & Cudeck, 1993;
Stieger, 1989, 1998), parallel analysis (Zwick & Velicer), and extent of interpretability (Fabrigar et al.).
Expert Review
Three judges, individuals with expertise in the branding of sport, were asked to
review and edit the items and resulting factor structure for face and content validity.
The expert panel was comprised of three different faculty members with PhD’s,
from three different universities, and all with expertise in sport brand management
research. Members of the expert panel were mailed a package containing a cover
letter explaining the procedure and expectations, a detailed description of the
researcher’s interpretation of the factors, and a complete list of the items retained
from the exploratory factor analysis. The experts provided feedback regarding the
potential omission of items, conceptual definitions of the identified factors, and
items assessing each factor. Feedback from the reviewers prompted the removal
of several items, the renaming of one factor, and the division of one factor into
two distinct factors.
Confirmatory Factor Analysis
Questionnaires with the final set of items were administered to a different
convenience sample of 467 students from the same large, Midwestern university,
of which 447 were completed and deemed usable for an effective response rate of
95.7%. Two different versions of the instrument presenting the items in random order
were used to prevent order and fatigue biases. The respondents were instructed to
list their favorite professional team and to rate the extent to which they thought of
an association when thinking of the particular team listed. All items in the instrument were measured on seven-point Likert-type scales with response categories
anchored by Never (1) and Always (7). Respondents were also asked how long they
had been a fan of their favorite team in order to assess the viability of the sample
as sport consumers.
One-third (33.9%) of the respondents were between 18 and 20 years of age,
whereas two-thirds of the respondents (62.0%) were between the ages of 21 and 22.
The remaining 4.1% of the respondents were between the ages of 23 and 40. Threequarters (75.0%) of the respondents were White/Caucasian, 8.0% were African
American, and 8.0% were Asian or Pacific Islander. The percentage of respondents
268 Ross, James, and Vargas
by gender was 40.6% female and 59.4% male. The number of years being a fan of
their favorite team ranged from 1 to 36 (M = 12.75), indicating that the respondents
in the confirmatory stage were an appropriate sample of sport consumers. Of the
professional teams listed as favorites, 34.4% were football teams, 43.8% were
baseball teams, 16.1% were basketball teams, 2.2% were hockey teams, and 3.6%
were teams from a variety of other sports (e.g., rugby, soccer). The list included
professional teams from the United States, as well as six professional teams from
nations other than the United States.
In addition, 24 items assessing similar categories of associations from Gladden & Funk’s (2002) Team Association Model were included in order to assess
concurrent validity of the scale. Although there is some question as to whether all
the factors from Gladden and Funk’s proposed scale do assess consumer-based
brand associations specifically, eight of the proposed categories do indeed reflect
similar theoretical constructs to seven of the factors suggested in the current study.
Given the conceptual similarity between these association categories, we determined
that criterion validity of the instrument could be assessed through the correlations
among these factors.
The validation of the instrument involved submitting the data gathered in the
second data collection procedure to a confirmatory factor analysis using Jöreskog
and Sörbom’s (1999) Linear Structural Relations (LISREL) 8.54 to estimate the
model for the scale items and constructs. In addition, convergent, discriminant,
and criterion validity were evaluated in order to validate the instrument through
an assessment of construct validity.
Results and Discussion
Free-Thought Listings
The respondents provided a total of 218 individual thoughts regarding their
favorite professional sport teams. Two of the coders identified 14 categories, whereas
the other coder identified 15 categories. Initial analysis by the coders produced a
coefficient of agreement (Cohen, 1960) of 81.7%. Discrepancies in coding were
resolved through discussion among the primary researchers and the two coders. The
final analysis resulted in 15 broad categories in which all 218 individual thoughts
were included.
The 218 individual thoughts were further examined, and 70 items were developed to reflect the constructs discovered in the content-analysis phase of the study.
The specific wording of the scale items were based upon the language provided
by the respondents in the free-thought listing task. The large discrepancy between
the number of thought listings provided and the number of initially developed
items was a result of multiple listings of the same thought. For example, multiple
respondents listed the specific term “tradition.”
Exploratory Factor Analysis
The Kaiser criterion (Kaiser, 1970), assessing the number of factors with
eigenvalues greater than 1.0, suggested 13 factors. The scree test (Zwick & Velicer,
1982) revealed a substantial drop in eigenvalues after three factors, suggesting three
Brand Association Scale Development 269
factors should be retained. Examination of the RMSEA (Browne & Cudeck, 1993;
Stieger, 1989, 1998) indicated that 4 or more factors showed values demonstrating
a reasonable fit (i.e., RMSEA < .08). Parallel analysis (Zwick & Velicer) suggested
retaining seven factors, although the interpretability (Fabrigar et al., 1999) of
factor loadings suggested retention of 10 factors. In contexts in which procedures
produce different numbers of factors, the researchers should examine the subset
of models that these procedures suggest are most plausible (Ford, McCallum, &
Tait, 1986). The rotated solutions for these models can be examined to see which
model produces the most readily interpretable and theoretically sensible pattern of
results (Comrey, 1978). As such, the factor structures suggested by the criteria (3-,
7-, 10-, and 13-factor models) were examined for interpretability. We reasoned that
by examining the diverse representation of suggested factor structures, additional
information regarding the interpretability of varied models would be accumulated.
This additional information pertaining to the interpretability of the suggested models
gave support to the decision of how many factors to retain.
The 3-, 7-, 10-, and 13-factor models were examined to determine which provided the best fit. The item loadings for each model were assessed to ensure that the
items loaded significantly on the respective factors. Particular attention was paid to
the number of significant items loading on the respective factors to avoid retaining
factors with only one item or too many items that could be reasonably interpreted
(Fabrigar et al., 1999; Fava & Velicer, 1992). Interpretability of respective factors
was also an important criterion in selecting the number of factors to retain. The
results indicated that the 10-factor solution provided the most sensible and explicable structure, suggesting a good fit to the data. Given the potential hazards of
overfactoring and underfactoring, in addition to the extent to which the solutions
were interpretable, the 10-factor solution was accepted.
After accepting the 10-factor solution, the RMSEA estimates of goodness-offit were examined. The RMSEA point estimate for the 10-factor solution was .061
(90% CI: .058, .063). Given that the RMSEA value fell within the acceptable range
of values suggested by Stieger (1989), the 10-factor model was deemed to have
a reasonable fit. The 10-factor solution accounted for 64.7% of the total variance
explained by the model. Of the initial 70 items included in the instrument, 50 were
retained for the interpretation of the factors. The retained factors and interpretations
of their conceptual definitions are presented in Table 2.
Expert Panel Review
In order to minimize the subjectivity of the labeling process and establish
content validity (Ford et al., 1986), three expert judges were selected to refine and
edit the initial 50 items for face and content validity. The feedback from the panel
members resulted in the removal of several items, the renaming of one factor, and
the division of one factor into two distinct factors. The Characteristics of Sport
factor was renamed Rivalry (labeled RIVAL in subsequent analyses) in order to
better reflect the conceptual makeup of the items representing the factor. The Consumption Experience factor was separated into two factors called Social Interaction
(labeled SOCIAL in subsequent analyses) and Concessions (labeled FOOD in
subsequent analyses) in order to more accurately measure the two distinct theoretical concepts. The resulting structure of the instrument included 41 items assessing
270 Ross, James, and Vargas
Table 2 Team Brand Association Scale Factor Names and Factor
Descriptions
Factor Name
Factor Description
Nonplayer personnel
Thoughts such individuals as coaches of the team, the
team management, and the owners of the team.
Team successab
Thoughts such as a team’s success in competition, the perceived quality of the players, and the perceived quality of
the team itself.
Team historyab
Historical thoughts regarding the team, the history of success, and the history of the team’s personnel.
Stadium communityab
Thoughts of the stadium in which their favorite professional team calls “home”; community and area surrounding the stadium or arena in which the team plays its games.
ab
Team play characteristicsab Thoughts regarding specific characteristics that a team
displays upon the field of play; how the team goes about
scoring, and specific characteristics that may be ascribed
to the team’s play.
Brand markab
Thoughts regarding the identifying mark such as the logo,
symbol, and the colors.
Consumption experiencebc
The concessionary aspects and social interaction related to
a particular team – eating specific foods, consuming beverages, going to games with friends, etc.
Characteristics of sporta
Characteristics of sport being played by the professional
teams; the specific sport, and competition with rivals.
Commitmentab
Thoughts regarding individual’s enduring affiliation to a
particular professional sport team; regarding the length,
continued regularity, and general notion of affiliation.
Organizational attributesab
Thoughts regarding specific attributes that characterize
the sport organization as a whole; organization’s loyalty to
fans, management actions, and brand personality.
Social interactionb
The idea of associating with others is reflected in social
interaction with friends and other fans of a particular professional team.
Concessionsb
Thoughts regarding eating and consuming beverages at
the stadium of the favorite team; actual concessions at the
facility, and the act of consuming concessions at the facility.
Rivalrybc
Thoughts regarding the competitive nature of sport; pertains to the competition among teams that are known to be
historically significant competitors.
Factor included in the initial 10-factor structure; b Factor included in the 11-factor structure; cFactor
included in the initial 10-factor structure but renamed in the 11-factor structure.
a
Brand Association Scale Development 271
11 identified factors: nonplayer personnel (5 items), team success (5 items), team
history (5 items), stadium community (7 items), team play characteristics (2 items),
brand mark (3 items), concessions (4 items), social interaction (2 items), rivalry (3
items), commitment (2 items), and organizational attributes (3 items). The factors
and interpretations of their conceptual definitions are listed in Table 2.
Confirmatory Factor Analysis and Reliability
Goodness-of-fit indices are reported in Table 3. As reported, each fit index
reached an acceptable or good fit to the data. Therefore, the confirmatory factor
analysis computed with data from the 447 respondents indicated a reasonable fit.
The reliability estimates for the validation model are presented in Table 4. The
Cronbach alphas range from .56 to .90. Although Cronbach’s alpha coefficient
represents a measure of internal consistency, it does not measure the amount of
variance explained by the construct relative to the amount of variance that might
be attributed to measurement error (Fornell & Larcker, 1981); average variance
extracted (AVE), however, is such a measure. The AVE values for eight of the eleven
factors’ values exceeded the recommended 0.50 cutoff (Fornell & Larcker), as can
be seen in Table 4. Analysis of the data suggested that the overall reliability of the
TBAS was acceptable.
Convergent Validity
A fundamental aspect of construct validity is the determination of whether a
scale’s items each contribute to its underlying theoretical construct. Specifically,
convergent validity is evidenced if each indicator’s loading on its posited underlying construct is greater than twice its standard error (Anderson & Gerbing, 1988).
Each of the items did load significantly on its specified factor (t-values ranged from
11.03 to 24.30), suggesting that convergent validity was achieved (see Table 4).
One additional measure of the internal quality of a construct’s indicators is
provided by an inspection of the residual matrix (Bagozzi & Yi, 1988). The pattern of residuals is often most useful for locating the source of misspecification
(Anderson & Gerbing, 1988). MacDonald and Ho (2002) suggest that residual
values lower than .10 are good, values ranging from .11 to .15 are acceptable,
Table 3 Fit Indices for Team Brand Association Scale Confirmation
Model
Index
Value
Indication of fit
χ2
2318.66
Acceptable
RMSEA
.074 (90% CI = .070, 077)
Acceptable
ECVI
6.19 (90% CI = 5.86, 6.54)
Acceptable
TLI
.93
Good
CFI
.95
Good
Note. RMSEA = Root mean square error of approximation; ECVI = expected cross-validation index,
TLI = Tucker-Lewis index, CFI = comparative fit index.
272 Ross, James, and Vargas
Table 4 Factor Reliabilities (α), Average Variance Extracted (AVE),
Factor Loadings, Standard Errors, and t Values for the Team Brand
Association Scale.
Factors and Items
Brand mark (BRAND)
1. the symbol of the team
2. the team’s logo
3. the team colors
Rivalry (RIVAL)
1. beating the team’s main rival
2. the team’s biggest opponent
3. the team’s conference
Concessions (FOOD)
1. eating a specific food at the stadium/arena
2. eating at the stadium/arena
3. concessions at the stadium/arena
4. consuming beverages at the stadium/arena
Social interaction (SOCIAL)
1. other fans of the team
2. going to games with my friends
Team history (HISTORY)
1. a specific era in the team’s history
2. game winning plays in the team’s history
3. championships the team has won
4. the most recent championship the team won
5. the success of the team in the past
Commitment (COMMIT)
1. being a fan of the team since childhood
2. regularly following the team
Organizational attributes (ORGANIZ)
1. an organization committed to its fans
2. a team loyal to its fans
3. the team giving back to the community
Nonplayer personnel (PERSON)
1. the head coach
2. a current coach on the team
3. excellent coaches
4. the team’s management
5. owners of the team
Stadium community (STADCOM)
1. the area surrounding the stadium/arena
2. the community surrounding the stadium/
arena
3. the location of the stadium/arena
4. the city that the team is from
α
.85
.79
.90
.56
.84
.62
.76
.86
.88
Factor
AVE loading
.67
.859
.902
.691
.58
.809
.780
.690
.72
.905
.900
.859
.710
.40
.596
.665
.53
.510
.616
.884
.839
.714
.46
.591
.760
.55
.794
.860
.542
.57
.833
.826
.733
.723
.656
.53
.749
.722
.797
.534
SE
t
.040
.039
.043
21.29
22.84
15.93
.042
.042
.044
19.23
18.28
15.55
.037
.037
.038
.042
24.30
24.09
22.32
16.88
.048
.048
12.29
13.66
.046
.044
.038
.040
.042
11.03
13.82
22.84
21.10
16.73
.048
.049
12.18
15.39
.042
.041
.046
18.62
20.69
11.54
.039
.039
.042
.043
.041
20.97
20.70
17.37
17.07
14.98
.041
.042
17.99
17.11
.040
.045
19.69
11.68
(continued)
Brand Association Scale Development 273
Table 4 (continued)
Factors and Items
5. what stadium/arena the team plays its home
games in
6. the team’s home stadium/arena
7. unique characteristics of the team’s stadium/
arena
Team success (SUCCESS)
1. a winning team
2. the performance of the team
3. quality players
4. the quality of the team
5. a great team
Team play (TEAMPLY)
1. how the team scores its points
2. specific team characteristics (e.g., lucky,
exciting)
α
.87
.56
Factor
AVE loading SE
.769
.041
t
18.70
.808
.702
.040
.042
20.09
16.45
.761
.739
.809
.825
.721
.041
.041
.040
.039
.042
18.34
17.60
20.09
20.67
17.01
.661
.602
.048
.048
13.61
12.34
.60
.40
whereas those values greater than .15 indicate a problem. Examining the residual
matrix, 8.1% of the residuals were found to be greater than .15. Items with the
highest values were associated with the social interaction and commitment factors. Two items specifically accounted for 29.4% of the high residuals (the first
item assessing both social interaction and commitment); no other item accounted
for more than 4% of the total number of high residuals. In sum, evidence of convergent validity based on the t values, the values of the factor loadings, and the
residuals revealed that the 11-factor model adequately accounts for the variance
in the instrument.
Discriminant Validity
In the current study two tests of discriminant validity were used. According
to Anderson and Gerbing (1988), discriminant validity can be assessed by determining whether the confidence interval around the correlation estimate between
any two factors includes 1.0. The correlations among latent constructs and their
standard errors are shown in Table 5. Although the correlations between some
of the constructs were high, no relationship failed this initial test of discriminant
validity.
A more rigorous test of discriminant validity was applied in which the AVE
for each construct was evaluated. Fornell and Larker (1981) suggested that the
AVE for each construct should be greater than the squared correlation between that
construct and any other. Failing this test indicates that the variance accounted for
by a construct explains less variance than that explained by that construct’s correlation with another, thus denoting a lack of discrimination. Results of the AVE
test of discriminant validity are shown in Table 5. The TEAMPLY and COMMIT
subscales comprised the majority of the nondiscrimination problems, and might
be able to be improved through future scale purification.
.146 (.052)
.825* (.044) .889* (.041) .698* (.049) .232 (.063)
.261 (.050)
.082 (.052)
.288 (.063)
.679 (.034)
.672 (.044)
.426 (.046)
STADCOM
TEAMPLY
BRAND
FOOD
SOCIAL
RIVAL
COMMIT
ORGANIZ
.190 (.051)
.509 (.040)
–.041 (.052) 1.000
1.000
.270 (.051)
.456 (.053)
.48 (.044)
.022 (.066)
.129 (.064)
.288 (.063)
1.000
—
TEAMPLY
.543 (.041)
.401 (.055)
.260 (.052)
—
FOOD
—
SOCIAL
.770* (.048) .498 (.046)
.352 (.049) .449 (.044)
.611 (.055)
—
COMMIT
—
ORGANIZ
.588 (.050) 1.000
.770* (.043) 1.000
.565 (.064)
1.000
—
RIVAL
.812* (.059) .411 (.055) .215 (.058)
.476 (.061)
.474 (.057) .775* (.044) 1.000
.246 (.049) 1.000
1.000
—
BRAND
.835* (.046) .275 (.052) .159 (.053)
.856* (.042) .439 (.076)
*Correlations that failed the AVE evaluation discriminant validity test.
.398 (.047)
.604 (.048)
.641 (.037)
.210 (.064)
–.106 (.051) –.137 (.051) .567 (.036)
.290 (.049)
.521 (.053)
.630 (.034)
1.000
—
.693 (.031)
HISTORY
—
.693 (.031)
SUCCESS
—
STADCOM
1.000
HISTORY
PERSON
SUCCESS
PERSON
Factors
Table 5 Correlations Between Factors and Standard Errors (in parentheses) for the Team Brand Association
Scale Confirmation Model
274 Ross, James, and Vargas
Brand Association Scale Development 275
Criterion Validity
Criterion validity must be assessed in the validation of an instrument. Criterion validity can take two forms, concurrent and predictive validity. Predictive
validity refers to those instances when data are collected on the criterion variable
at a point in time after data are collected on the scale (Malhotra, 1999). Concurrent validity is assessed when the criterion variable is measured at the same
time as the scale that is being evaluated. Tests can be validated against others
that are somewhat similar, and correlations of about 0.3 should be expected
(Kline, 1998), though they are not necessary. The current study examined criterion validity using concurrent validity. Seven factors identified in the current
study were correlated with eight factors from Gladden and Funk’s (2002) Team
Association Model. While the TAM overall is not convincing in terms of construct validity, eight factors from the TAM were found to be valid associations
held by sport consumers in the current study, and the use of these particular
factors in the assessment of concurrent validity was deemed appropriate. The
factors from the instrument to be correlated with factors from the TAM were
chosen based on their conceptual similarity (e.g., Organizational Attributes and
Management; Success and Quality). Factors from the TBAS for which there
was no conceptually similar structure in the TAM were not included in this test
(e.g., Concessions, Rivalry).
The correlations between the seven factors of the proposed instrument and the
eight factors from the TAM included in this study are shown in Table 6. Evidence
of concurrent validity was strong, with each of the seven factors significantly correlating with at least five of the factors proposed by Gladden and Funk (2002). In
fact, five factors correlated significantly with all eight factors, and one significantly
correlated with seven of the factors. Although there is no single criterion-related
validity coefficient (Carmines & Zeller, 1979), based on the abundance of proposed
factors correlating with conceptually similar established factors, the criterion validity of the scale was deemed acceptable (Kline, 1998).
Conclusion and Future Directions
It is clear that a number of brand associations can be involved with a consumer’s
perception of a good or service. The Team Brand Association Scale (TBAS) in
the current study was developed by asking for associations that individuals hold
regarding their favorite sports team. By collecting sport team brand associations
from consumers, the process by which sport marketers can measure, create, and
manage these associations in a sport setting can be improved. This improvement
comes from the point that the associations being scrutinized are the thoughts held
by the consumer; they are not just researcher-generated opinions.
Much of the energy of scale validation was focused on what Kerlinger (1999)
refers to as the preeminent form of validity: construct validity. The scale’s construct
validity was verified through a thorough process of scale development and confirmatory factor analysis. Results of the CFA do suggest areas, however, in which the
measures could be improved through future research. The validity and reliability
of the TBAS might be enhanced by improving three of the factors in particular,
Team Play, Commitment, and Social Interaction.
0.354*
0.506*
0.251*
0.396*
0.145*
Person
Organiz
History
* p < .05 level.
Brand
0.026
0.036
Stadcom
0.384*
0.108*
0.567*
0.114*
0.535*
Success
0.221*
0.449*
Stadium
Teamplay
Quality
0.155*
0.490*
0.259*
0.500*
0.005
0.515*
0.373*
Tradition
0.552*
0.172*
0.303*
0.236*
0.310*
0.376*
0.340*
Logo
0.117*
0.244*
0.346*
0.343*
0.082
0.450*
0.329*
Management
0.371*
0.325*
0.440*
0.364*
0.369*
0.403*
0.449*
Nostalgia
0.314*
0.127*
0.546*
0.238*
0.510*
0.318*
0.317*
Pride in place
0.274*
0.200*
0.371*
0.295*
0.251*
0.499*
0.421*
Product delivery
Table 6 Correlations Among Team Brand Association Scale and Team Association Model Factors to
Assess Concurrent Validity.
276 Ross, James, and Vargas
Brand Association Scale Development 277
The three factors are currently measured using only two items; additional
items should be developed that are similar to existing items in order to improve the
reliability of the respective factors. In order to maintain the content validity of the
scale, additional items developed to represent the three factors should be based on
the thoughts and ideas of sport consumers. Focus groups or interviews with sport
consumers could be used to talk about specific associations based on this research
as part of a process to develop additional items. In a related vein, it is also possible
that consumers hold other associations regarding sports teams. Future research
should explore the existence of other associations and should also consider other
sample groups, for example, individuals attending sporting events or individuals
whose primary consumption is via media. It is possible that different consumer
segments hold different team brand associations.
In addition to the number of items used to assess the Team Play and Commitment factors, attention should be given to the wording of items to more clearly
discriminate between constructs. For example, one item assessing Team Play (how
the team scores its points) might actually be related to the success of the team. One
suggestion for future research is to modify the wording of the item to more clearly
differentiate it from the conceptual underpinnings of the Success factor.
The items assessing the Commitment factor might also be conceptually
connected with factors from which it fails to discriminate. Both items assessing
Commitment involve some aspect of the past, and therefore might be conceptually associated with the History factor. Similarly, it has been found that team success has an effect upon commitment to a team (Murrell & Dietz, 1992; Wann &
Branscombe, 1993) and, therefore, could be conceptually related to the Success
factor. Future scale refinement could modify the items assessing the Commitment
factor to more directly discriminate it from the conceptual basis of the History
and Success factor.
The TBAS can aid sport management professionals in managing their brands
in a variety of ways in order to assist in the creation of favorable associations to
attract or retain consumers. Economically, profit-generating organizations need to
attract people in order to produce revenue and stay in business. From the professional sport team perspective, sport managers need to understand the components
of brand equity because they might allow for managerial manipulation of brand
equity (Gladden & Funk, 2002). The current study presents an important step in
better understanding brand equity, its formation, and how managers might foster
brand equity through associations.
Reference
Aaker, D. (1991). Managing brand equity. New York: Free Press.
Aaker, D. (1996). Building strong brands. New York: Free Press.
Anderson, J., & Gerbing, D. (1988). Structural equation modeling in practice: A review and
recommended two-step approach. Psychological Bulletin, 103, 411-423.
Argenti, P., & Druckenmiller, B. (2004). Reputation and the corporate brand. Corporate
Reputation Review, 6, 368-374.
Bagozzi, R., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of
the Academy of Marketing Science, 16, 74-94.
278 Ross, James, and Vargas
Berry, L. (2000). Cultivating service brand equity. Journal of the Academy of Marketing
Science, 28, 128-137.
Berry, L., & Parasuraman, A. (1991). Marketing services: Competing through quality. New
York: Free Press.
Biswas, A., & Sherrell, D. (1993). The influence of product knowledge and brand name on
internal price standards and confidence. Psychology and Marketing, 46, 31-46.
Boone, L., Kochunny, C., & Wilkins, D. (1995). Applying the brand equity concept to Major
League Baseball. Sport Marketing Quarterly, 4(3), 33-42.
Branscombe, N., & Wann, D. (1991). The positive social and self-concept consequences of
sports team identification. Journal of Sport and Social Issues, 15, 115-127.
Branvold, S., Pan, D., & Gabert, T. (1997). Effects of winning percentage and market size
on attendance in minor league baseball. Sport Marketing Quarterly, 6, 35-42.
Browne, M., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. Bollen & J.
Long (Eds.), Testing structural equation models (pp.136-162). Beverly Hills: Sage.
Browne, M., Cudeck, R., Tateneni, K., & Mels, G. (1999). CEFA: Comprehensive exploratory
factor analysis, Version 1.03 (Computer Software). Columbus, OH.
Cacioppo, J., & Petty, R. (1981). Social psychological procedures for cognitive response
assessment: The thought-listing technique. In T. Merluzzi, C. Glass, & M. Genest (Eds.),
Cognitive assessment (pp. 309-342). New York: Guilford Press.
Carmines, E., & Zeller, R. (1979). Reliability and validity assessment. Beverly Hills: Sage.
Churchill, G. (1979). A paradigm for developing better measures of marketing constructs.
Journal of Marketing Research, 16(1), 64-73.
Cobb-Walgren, C., Ruble, C., & Donthu, N. (1995). Brand equity, brand preference, and
purchase intent. Journal of Advertising, 24(3), 25-40.
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational & Psychological Measurement, 20, 37-46.
Comrey, A. (1978). Common methodological problems in factor analytic studies. Journal
of Consulting and Clinical Psychology, 46, 648-659.
de Chernatony, L. (2002). Would a brand smell any sweeter by a corporate name? Corporate
Reputation Review, 5, 114-132.
del Rio, A., Vazquez, R., & Iglesias, V. (2001). The effects of brand associations on consumer
response. Journal of Consumer Marketing, 18, 410-425.
Fabrigar, L., Wegener, D., MacCallum, R., & Strahan, E. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272-299.
Faircloth, J., Capella, L., & Alford, B. (2001). The effect of brand attitude and brand image
on brand equity. Journal of Marketing Theory and Practice, 9(3), 61-75.
Fava, J., & Velicer, W. (1992). The effects of overextraction on factor and component analysis.
Multivariate Behavioral Research, 27, 387-415.
Fisher, R., & Wakefield, K. (1998). Factors leading to group identification: A field study of
winners and losers. Psychology and Marketing, 15, 23-40.
Ford, J., McCallum, R., & Tait, M. (1986). The application of exploratory factor analysis
in applied psychology: A critical review and analysis. Personnel Psychology, 39,
291-314.
Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable
variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gladden, J., & Funk, D. (2002). Developing an understanding of brand associations in team
sport: Empirical evidence from consumers of professional sport. Journal of Sport
Management, 16, 54-81.
Gladden, J., Irwin, R., & Sutton, W. (2001). Managing North American major professional
sport teams in the new millennium: A focus on building brand equity. Journal of Sport
Management, 15, 297-317.
Gladden, J., & Milne, G. (1999). Examining the importance of brand equity in professional
sports. Sport Marketing Quarterly, 8, 21-29.
Brand Association Scale Development 279
Gladden, J., Milne, G., & Sutton, W. (1998). A conceptual framework for evaluating brand
equity in Division I college athletics. Journal of Sport Management, 12, 1-19.
Griffin, A., & Hauser, J. (1992). The voice of the customer (report number 92–106). Cambridge, MA: Marketing Science Institute.
Heath, R. (1999). Just popping down to the shops for a packet of image statements: A new
theory of how consumers perceive brands. Journal of the Market Research Society,
41, 153-169.
Iacobucci, D. (2001) Methodological and statistical concerns of the experimental behavioral
researcher. Journal of Consumer Psychology, 10, 1-121.
Jöreskog, K., & Sörbom, D. (1999). LISREL VIII. Chicago: Scientific Software International.
Kaiser, H. (1970). A second generation little jiffy. Psychometrika, 35, 401-415
Kapferer, J. (1997). Strategic brand management (3rd ed.). London: Kogan Page.
Keller, K. (1993). Conceptualizing, measuring, and managing customer-based brand equity.
Journal of Marketing, 57(1). 1-22.
Keller, K. (1998). Strategic brand management. Upper Saddle River. NJ: Prentice Hall.
Kerlinger, F. (1999). Foundations of behavioral research (4th ed.). Belmont, CA: Wadsworth.
Kline, P. (1998). The new psychometrics: Science, psychology and measurement. London:
Routledge.
Lederer, C., & Hill, S. (2001). See your brand through your customers’ eyes. Harvard Business Review, 79(6), 125-133.
MacDonald, R., & Ho, M. (2002). Principles and practices in reporting structural equation
analyses. Psychological Methods, 7, 64-82.
Malhotra, N. (1999). Marketing research: An applied orientation (3rd ed.). Upper Saddle
River, NJ: Prentice Hall.
Miller, A., Wattenberg, M., & Malanchuk, O. (1986). Schematic assessments of presidential
candidates. American Political Science Review, 80, 521-540.
Murrell, A., & Dietz, B. (1992). Fans support of sport teams: The effect of a common group
identity. Journal of Sport and Exercise Psychology, 14, 28-39.
Park, C., Jaworski, B., & MacInnis, D. (1986). Strategic brand concept image management.
Journal of Marketing, 50, 621-635.
Schultz, M., & de Chernatony, L. (2002). Introduction: the challenges of corporate branding.
Corporate Reputation Review, 5, 105-112.
Shocker, A., Srivastava, R., & Ruekert, R. (1994). Challenges and opportunities facing brand
management: An introduction to the special issue. Journal of Marketing Research,
31(2), 149-157.
Steiger, J. (1989). EZPATH: A supplementary module for SYSTAT and SYGRAPH. Evanston, IL: SYSTAT.
Steiger, J. (1998). A note on multiple sample extensions of the RMSEA fit index. Structural
Equation Modeling, 5, 411-419.
Stevens, J. (2002). Applied multivariate statistics for social sciences (4th ed.). Mahwah,
NJ: Lawrence Erlbuam.
Wakefield, K. (1995). The pervasive effects of social influence on sporting event attendance.
Journal of Sport & Social Issues, 19, 335-351.
Wakefield, K., & Sloan, H. (1995). The effects of team loyalty and selected stadium factors
on spectator attendance. Journal of Sport Management, 9, 153-172.
Wann, D. (1995). Preliminary validation of the sport fan motivation scale. Journal of Sport
and Social Issues, 19, 377-396.
Wann, D., & Branscombe, N. (1993). Sports fans: Measuring degree of identification with
their team. International Journal of Sport Psychology, 24, 1-17.
Zwick, W., & Velicer, W. (1982). Factors influencing four rules for determining the number
of components to retain. Multivariate Behavioral Research, 17, 253-269.