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FLORIDA STATE UNIVERSITY
COLLEGE OF EDUCATION
AN INTEGRATED MODEL OF VALUE EQUITY IN SPECTATOR SPORTS:
CONCEPTUAL FRAMEWORK AND EMPIRICAL RESULTS
DANIEL ROBERT SWEENEY
A Dissertation submitted to the Department of Sport Management,
Recreation Management, and Physical Education in partial fulfillment of the
requirements for the degree of Doctor of Philosophy
The members of the committee approved the Dissertation of Daniel Robert Sweeney
defended on March 6, 2008.
________________________ Jeffrey D. James
Professor Directing Dissertation ________________________ J. Joseph Cronin, Jr.
Outside Committee Member
________________________
R. Aubrey Kent Committee Member
________________________
Steven McClung Committee Member
Approved: _________________________________________________________________ Cheryl Beeler, Chair, Department of Sport Management, Recreation Management, and Physical Education The Office of Graduate Studies has verified and approved the above named committee members.
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To my remarkable wife Jamie –
for her infinite patience, understanding, and love. She has made significant sacrifices over the last five years
to see me pursue my dreams and accomplish my goals.
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ACKNOWLEDGEMENTS
I am especially indebted to Dr. Jeffrey James, my committee chair and program
advisor, for his guidance throughout the research process as well as the last four years.
His continued support through difficult times made all the difference.
I also thank my committee members: Dr. Aubrey Kent, Dr. Joe Cronin, and my
pinch hitter Dr. Steven McClung, who stepped in midway through the process when
asked. The committee members provided valuable insight and I appreciate their time
and effort. I would also like to thank Dr. Harry Kwon for his early involvement in the
project. His comments and critiques during the proposal stage of this project were very
helpful.
My PhD colleagues, past and present, were an inspiration and a source of
support to me. I also thank everyone past and present in the SMRMPE office, including
Cynthia Bailey, Kerry Behnke, Harriet Kasper, and Shannon Barksdale for their help.
The little things really meant a lot to me.
This research would not have been possible without the cooperation of Ben
Zierden, Director of Ticket Operations for the Florida State University Department of
Athletics and Kirk Goodman, former General Manager of the Jacksonville Suns. I thank
them for providing me access to their facilities, and more importantly to their valued
customers.
I would be remiss if I did not acknowledge and thank Jamie, Carly, Derek, Justin,
Birgit, Masa, Young, Yuko, Katie, and Sean for giving up their time to help distribute
surveys.
My family was very much a part of this success. I thank my mother and
father who instilled in me from a young age the value of an education. My sister Carly
deserves considerable praise for unknowingly pushing me to stay one-step ahead of
her;). Thanks to my gramma Eleanor, for the unshakeable confidence she has that her
grandson Dani can do no wrong (except for wet towels left in a pile on the floor of her
apartment of course!). I also want to thank the Metz’s and Crumley’s, my new family,
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for supporting me throughout this process as I continue to drag their daughter across
the country.
Finally, I wish that my grandmother Reva and grandfathers Bernie and Matthew
were here to see this moment. I know they would have enjoyed it and somewhere up
there, I know they are proud of me and happy for me.
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TABLE OF CONTENTS
List of Tables................................................................................................................... x List of Figures.................................................................................................................xii Abstract ......................................................................................................................... xiii
Components of Customer Equity .................................................................. 21 Value Equity ....................................................................................... 22 Brand Equity....................................................................................... 45 Relationship Equity............................................................................. 58
Scale Development ....................................................................................... 67 Initial Data Collection.......................................................................... 72 Purification of the Measure................................................................. 72
3. METHODOLOGY & PILOT STUDY ......................................................................... 80
Research Objectives ..................................................................................... 80
Research Design........................................................................................... 81
Steps 1 and 2: The Specification of the Domains of Construct and Generation of Sample Items ............................................................. 81
Entertainment Value........................................................................... 82 Social Value ....................................................................................... 83 Service Quality ................................................................................... 87 Perceived Price .................................................................................. 87 Epistemic Value.................................................................................. 91
Step 3 – First Data Collection: Pilot Study .................................................... 92 Introduction......................................................................................... 92 Population and Sample ...................................................................... 92 Data Collection ................................................................................... 93 Instrument Development .................................................................... 93
Step 4 – Reliability and Validity Assessment of First Data Collection ........... 94 Data Analysis ..................................................................................... 94 Results ............................................................................................... 96
Pilot Study Discussion................................................................................. 124
Step 6 – First Data Collection of the Main Study......................................... 135 Target Population and Sample Design............................................. 135
Step 7 – Assessment of Reliability and Validity........................................... 137 Data Analysis Procedures ................................................................ 137
Step 8 – Development of Norms ................................................................. 146
Discussion of the Results ............................................................................ 185 Entertainment Value......................................................................... 185 Perceived Service Quality ................................................................ 196 Perceived Price ................................................................................ 198 Knowledge as Value......................................................................... 199 Satisfaction as and Outcome of Value.............................................. 202
Research Implications................................................................................. 202
Limitations and Future Research ................................................................ 206
Table 2.01. Literature on the Antecedents of Customer Equity .................................... 18
Table 3.01. Dimensions and Items of Entertainment Value.......................................... 84
Table 3.02. Dimensions and Items of Social Value. ..................................................... 86
Table 3.03. Dimensions and Items of Service Quality .................................................. 88
Table 3.04. Dimensions and Items of Perceived Price................................................. 90
Table 3.05. Dimensions and Items of Epistemic Value ................................................ 91
Table 3.06. Dimensions and Items of Satisfaction ....................................................... 92
Table 3.07. Demographic Characteristics of the Pilot Sample ..................................... 97
Table 3.08. Reliability Estimates of Entertainment Value Factors. ............................... 98
Table 3.09. Reliability Estimates of Social Value Factors............................................. 99
Table 3.10. Reliability Estimates of Service Quality Factors ...................................... 100
Table 3.11. Reliability Estimates of Perceived Price ...……………………………….…101
Table 3.12. Reliability Estimates of Epistemic Value ....………………………………..101
Table 3.13. Reliability Estimates of Satisfaction......................................................... 101
Table 3.14. Descriptive Statistics for Entertainment Value Items. .............................. 104
Table 3.15. Eigenvalues for Entertainment Value Factors ......................................... 105
Table 3.16. Rotated Pattern Matrix for Entertainment Value ...................................... 107
Table 3.17. Factor Correlation Matrix for Entertainment Value .................................. 108
Table 3.18. Descriptive Statistics for Social Value Items............................................ 108
Table 3.19. Eigenvalues for Social Value Factors...................................................... 109
Table 3.20. Rotated Pattern Matrix for Social Value .................................................. 111
Table 3.21. Factor Correlation Matrix for Social Value............................................... 111
Table 3.22. Descriptive Statistics for Service Quality Items ....................................... 112
Table 3.23. Eigenvalues for Service Quality Factors.................................................. 113
Table 3.24. Model Fit Results for Varying Number of Service Quality Factors........... 115
Table 3.25. Rotated Pattern Matrix for Two-Factor Model of Service Quality............. 116
Table 3.26. Rotated Pattern Matrix for Three-Factor Model of Service Quality .......... 117
Table 3.27. Factor Correlation Matrix for Two-Factor Model of Service Quality ......... 118
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Table 3.28. Descriptive Statistics for Perceived Price Items ...................................... 118
Table 3.29. Eigenvalues for Perceived Price Factors................................................. 119
Table 3.30. Rotated Pattern Matrix for Perceived Price ............................................. 121
Table 3.31. Factor Correlation Matrix for Perceived Price.......................................... 121
Table 3.32. Descriptive Statistics for Epistemic Value Variables................................ 122
Table 3.33. Eigenvalues for Epistemic Value ............................................................. 123
Table 3.34. Factor Matrix for Epistemic Value............................................................ 124
Table 5.01. Demographic Characteristics of the Confirmatory Sample...................... 148
Table 5.02. CFA for the Value Equity Factors and Items ........................................... 152
Table 5.03. Fit Indices for the 16-Factor Model with 74 Indicators ............................. 155
Table 5.04. Factor Correlations for First Data Collection............................................ 156
Table 5.05. Discriminant Validity Analysis for Model AVE’s ....................................... 157
Table 5.06. X2 difference test for One- and Two-Factor Models of Service Quality.... 157
Table 5.07. CFA for the RESPECIFIED Value Equity Factors and Items................... 166
Table 5.08. Factor Correlations for Respecified Model .............................................. 168
Table 5.09. Fit Statistics for Respecified Model ......................................................... 169
Table 5.10. Demographic Characteristics of the Validation Sample........................... 174
Table 5.11. Chi Square Analysis – Relationship between length of time following consumption and manifest variable mean scores. ................................. 175
Table 5.12. CFA Validation Sample ........................................................................... 176
Table 5.13. Factor Correlations for Third Data Collection .......................................... 177
Table 5.14. Fit Indices for Validation Sample of 14-Factor Model with 64 Items ........ 179
Table 5.15. Fit Statistics for Validation Sample Second-Order CFA .......................... 181
Table 5.16. Second-Order CFA for the Validation Sample......................................... 181
Figure 2.03. Behavioral and Financial Consequences of Service Quality Model (Zeithaml, Berry, & Parasuraman, 1996) ................................................. 27
Figure 2.04. Service Quality Model (Grönroos, 1984) .................................................. 29
Figure 2.05. Model of Retail Service Quality (Dabholkar, Thorpe, and Rentz, 1996) ... 32
Figure 2.06. Brady and Cronin’s (2001) Hierarchical Model of Service Quality............ 33
Figure 2.07. Framework of Value Equity in Spectator Sports ...................................... 45
Figure 2.08. Crawford’s (2005) integrated model of competence................................. 56
Figure 2.09. Model of Customer-Based Brand Equity for Team Sport Services........... 59
Figure 2.10. Framework of Relationship Equity in Team Sport Services...................... 68
Figure 2.11. Churchill’s (1979) Procedure for Developing Better Measures................. 70
Figure 3.01. Scree Plot for Entertainment Value ........................................................ 106
Figure 3.02. Scree Plot for Social Value..................................................................... 110
Figure 3.03. Scree Plot for Service Quality ................................................................ 114
Figure 3.04. Scree Plot for Perceived Price ............................................................... 120
Figure 3.05. Scree Plot for Epistemic Value............................................................... 123
Figure 3.06. Post Pilot Study Model of Value Equity .................................................. 134
Figure 5.01. Competing models of service quality for the X2 difference test .............. 158
Figure 5.02. Respecified Model of Value Equity......................................................... 164
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ABSTRACT
The current research was undertaken to propose a model of the components of
customer equity in a spectator team sport setting and to identify and empirically test
measures to assess one part of the model, namely: value equity. Value equity refers to
the portion of a firm’s customer equity derived from customers’ perceived value or worth
of that firm’s product offerings. The measurement of customer perceived value is
essential in assessing current services and for the development of further ones,
because customer segments may have different motives to use services and thus
perceive different value in them (Pura, 2005). This study, which is a first attempt to
measure Value Equity within a spectator sport context, presents a conceptualization of
Value Equity derived from a combination of the frameworks proposed by Sheth,
Newman, and Gross (1991), Rust, Zeithaml, and Lemon (2000), and Sweeney and
Soutar (2001), and includes six dimensions: 1) entertainment value; 2) social value; 3)
service quality; 4) perceived price; 5) epistemic value; and 6) Satisfaction.
A pilot study involving a sample (n = 254) of consumers at a NCAA Division I
baseball game was conducted to provide an initial test of the items in the measurement
scales to establish preliminary validity and reliability. Descriptive statistics, internal
consistency reliability, and exploratory factor analysis were utilized in the data analysis.
The first-order factor structure of Value Equity comprised of five dimensions, 16 first-
order latent variables, and 75 indicator variables was tested in five separate exploratory
factor analyses, one for each of the dimensions of Value Equity, to explain the variance
in the observed variables in terms of underlying latent factors. The results of the pilot
study indicated that the data fit the model reasonably well, though room for
improvement remained. Modifications to the model resulted in a first-order model of
Value Equity comprised of 16 dimensions and 75 items, which was tested in the next
phase of the study.
The main phase of the study was comprised of two separate data collections.
The first data collection involved a convenience sample (n = 376) of spectators in
attendance at a ‘Double A’ minor league baseball game. Based on the analysis of the
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results of the pilot study, a 16-factor model was tested using all 75 items, and internal
tests and confirmatory factor analysis (CFA) were performed. The results indicated the
16-factor model of Value Equity in Spectator Sports Scale did not adequately fit the
data. The 16-factor model with 75 indicators needed to be modified to provide the best
fit to the data based on suggestions from the tests of model estimations and fit of the
internal structure. Based on Bollen’s (1989) criteria for model respecification, the model
was modified accordingly. The modifications resulted in the testing of a 14-factor, 64-
item model. The psychometric properties of the respecified measurement model were
acceptable, as were the assessment of the global and internal fit indices. Given the
favorable results, the researcher proceeded to a second data collection, which was
used to validate the results of the respecified model. The second data collection of the
main study comprised a sample (n = 285) of undergraduate and graduate students at a
large Southeastern university. The analysis of the results of the second data collection
served to confirm the revised model from the analysis of the results from the first data
collection. Finally, a second order HCFA was conducted to test the relationship
between the proposed higher order factors on the first order latent variables. While the
results of the first-order CFA provided support for discrimination among the first-order
factors, the results of the HCFA presented in this chapter indicate the predicted higher-
model may not be appropriate for the current population from which the sample was
drawn. The final chapter presents a discussion of the findings and reported results, as
well as content discussing the implications and limitations of the current research
project. Suggestions for future research are also provided.
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CHAPTER ONE
INTRODUCTION
“In the brutal competition for American leisure time, sports franchises have found themselves in a good old-fashioned donnybrook for share of wallet” (Ferguson, 2005, p. 5).
Sport spectatorship has become an increasingly prominent form of entertainment
as well as an important part of the American economy in contemporary society. The
sports business is one of the largest and fastest growing industries in the United States.
A recent Plunkett Research (2007) report estimated the size of the entire U.S. sports
industry to be $410 billion as of 2007. Concerning sport spectatorship, Street & Smith’s
SportsBusiness Journal (2007) reported spectator spending at sporting events reached
an estimated $32.06 billion last year.
The growth of sporting events as a form of entertainment has led to an increase
in competition among sport organizations for the consumer entertainment dollar. Sport
teams must also compete with other entertainment providers, such as restaurants,
movie theaters, home television viewing, and video games, for a share of peoples’ time
and discretionary income. Because of the highly competitive entertainment
environment, James, Kolbe, and Trail (2002), suggested teams must attract, develop,
and maintain relationships with a substantial number of consumers in order to create
adequate income streams. However, in an era where marketers are under increasing
pressure from organizational stakeholders and shareholders to be financially
accountable, they must be increasingly careful in how they use their finite resources
(McDonald & Milne, 1997). Therefore, attracting, developing, and maintaining
relationships with the right customers, those that are most valuable, and offer the
greatest return on marketing expenditures, is paramount.
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Statement of the Problem
Despite the mounting pressure and recognized need to effectively employ limited
resources, Rust, Lemon, and Zeithaml (2004) noted that far too often, marketing
executives view marketing expenditures as short-term costs rather than long-term
investments and tend to rely on intuition and instinct when making strategic decisions.
This type of behavior undermines an organization’s ability to attract, develop, and
maintain relationships with valuable consumers and hinders the ability to receive the
greatest return possible on marketing expenditures. One reason many sport
organizations may rely on intuition and instinct is they have not developed, or do not
have access to a unified, data-driven system from which to make broad, strategic-
marketing decisions.
For some sport organizations, not having a system for collecting information
about existing and potential consumers may be a result of not having the resources
(i.e., number of personnel or budget) needed for establishing such a system. For
example, many smaller collegiate athletic programs throughout the United States,
whether at the Division 1, Division 2, or the Division 3 level, are constrained by small
budgets and too few personnel charged with marketing related responsibilities. For
example, one metropolitan university with a small, Division 1, collegiate athletic program
in the Southern United States has one individual responsible for developing,
implementing, and evaluating marketing strategies and initiatives for the entire
intercollegiate athletic program. Furthermore, this person’s other responsibilities include
fundraising, the recruitment of new donors, the recruitment of new sponsors, as well as
overseeing all season ticket sales. With such few resources, it is possible to
understand why marketing strategies based on intuition and instinct can supplant those
supported by concrete data.
For other sport organizations, such as professional sport franchises, adequate
resources may not be the sole impediment to the effective use of data-driven marketing
strategy development and implementation. Rather, barriers to the development,
implementation, or use of an effective system for managing consumer data may stem
from the prevailing culture within the team, front office, or league. The marketing
3
strategies and activities of many minor league baseball teams serves as an example of
how the prevailing culture within a league or team front office affects marketing
orientation and perspective. Review of the promotional schedules for most, if not all,
minor league baseball teams, for instance, illustrates that the teams rely heavily on
promotions as a strategy for attracting consumers. Rust et al., (2004) would likely argue
that promotions are short-term marketing investments that do not reflect a desire by
teams to understand the needs and wants of existing and potential consumers, thus
undermining the potential to develop meaningful relationships with those consumers.
Basing strategic marketing decisions on instinct and intuition rather than
consumer driven data indicates that an organization has not shifted its marketing
perspective from a product orientation to one that is customer oriented. The product
orientation reflects a management philosophy whereby an organization assumes that
customers will purchase a product so long as they can afford it (Tuckwell, 1991).
According to Kotler (2002), product oriented companies seek to gain a competitive
advantage by attempting to increase the attraction of their product through the addition
of extra features, or the use of modern technology, while neglecting to specify
consumer’s needs and wants and a manner to serve these specific needs and wants
better than the competition. In the context of the marketing of spectator sport, many
minor league baseball teams, for example, focus on the provision of new facilities,
program schedules, and promotions in their efforts to attract consumers. In other
words, they have focused on the physical components of their service offering, and not
necessarily on the needs and wants of the consumers who use the service. In addition
to not considering consumer needs, a critical weakness of the “if you build it, they will
come” approach is that many other service providers are able to provide the same, if not
better physical service components.
A product-focused approach to marketing prevents organizations from gaining a
true understanding of the needs and wants of its existing and potential consumers,
which limits their ability to develop meaningful relationships with these consumers.
Rust, Ambler, Carpenter, Kumar, and Srivastava (2004) lamented that a product
focused approach to marketing serves to undermine marketing’s credibility, threatens its
4
standing in the organization, and even threatens its existence as a distinct capability
within an organization.
A new paradigm that has emerged in the general marketing literature to help
guide managers to build strong and profitable relationships with consumers is customer
equity. Recognizing the value potential of current and future customers, Blattberg and
Deighton (1996) were the first to coin the term ‘customer equity’, and over the past
decade, marketing academicians and practitioners have begun to alter their
perspectives on marketing from the product-focused concept of brand equity to the
more consumer-oriented concept of customer equity. According to Hogan, Lemon, and
Rust (2002), the adoption of a customer-centered orientation has been spurred by
several major marketplace transformations: mounting pressure on managers to be more
accountable to financial stakeholders as a result of increased marketplace competition;
greater access to vast amounts of detailed customer information; and the emergence of
sophisticated technologies, which has raised consumers’ levels of expectations
regarding the possibilities of individual level marketing efforts by the organization. A
result of the organizational pressures and marketplace changes is that organizations
have had to adapt to, as well as develop and implement alternative strategies leading to
sustainable profits.
A customer equity orientated marketing approach necessitates that marketing
expenditures be viewed as investments in customer assets that lead to long-term value
for the firm (Hogan at al., 2002). In viewing customers as assets, firm’s are able to
identify the most appropriate marketing actions to acquire, maintain and enhance
customer assets and thereby maximize financial returns (Berger, Bolton, Bowman,
Briggs, Kumar, Parasuraman, & Terry, 2002). As the customer is viewed as a financial
asset, Blattberg and Deighton (1996) suggested that a firm’s customer equity should
therefore be managed like any other financial asset.
According to Blattberg, Getz, and Thomas (2001), the effective management of
the asset value of customer relationships requires a total marketing system based on
integrative business strategies. In other words, the authors noted that organizations
must develop and implement strategies that concurrently manage products as well as
customers throughout the customer lifecycle and “reframe brand and product strategies
5
within the context of their effect on customer equity” (p. 3). The proposed benefits
associated with the transition to a customer equity marketing system include: an
increased ability to make informed decisions regarding marketing investments in
relation to acquisition, retention and add-on selling; the capability to adjust the level or
depth of investment level in each of these activities as needed; a maximization of
profitability through the organization of processes and structures around acquisition,
retention, and add-on selling; and the utilization of customer interactions to reinforce
relationships and acquire new customers.
Blattberg and Deighton (1996) argued that one of the primary benefits of
adopting a customer equity approach to marketing is that it enables firms to compute
the asset value of customers so that informed decisions can be made regarding
marketing spending on customer acquisition, retention, and add-on selling, thus
maximizing the profitability of each over the course of their customer lifecycle. This
calculation enables competing marketing strategy options to be traded off on the basis
of projected financial return. Viewed from this perspective, the customer equity
paradigm may be defined as a “management approach for acquisition and retention,
geared to individual lifetime values of current and future customers with the aim of
brand. The focus of retention equity is on that part of the relationship between the
customer and the firm that is based on the actions taken by the firm and the customer to
establish, build, and maintain a relationship.
Building upon existing models (Blattberg & Deigthon, 1996; Rust et al., 2000),
Bayon, et al. (2002) presented a detailed process framework for understanding
customer equity. They proposed a customer equity marketing system comprised of four
primary, sequential stages each containing several specific actions. The four stages
17
included: 1) analysis; 2) planning; 3) implementation; and 4) control. A key component
of the analysis stage involved the recognition that a determination of the industry-
specific direct and indirect drivers of customer equity is an important first activity in
which firms must engage. Only then is it possible for firms to model and predict the
value of specific consumer segments. Although the authors did not specifically attempt
to identify precisely what the indirect drivers of customer equity are, their work is
significant because it recognized that an identification of industry specific indirect
variables is a crucial component towards the eventual calculation of a firm’s customer
equity.
Dias, Pilhens, and Ricci (2002) introduced the concept and benefits of fusion
analysis in understanding the drivers of customer value, and its relevance to customer
profitability and shareholder value. Fusion analysis was described as “the analysis of
the influence of macroenvironmental variables, such as brand and market drivers, at the
microbehavioural level” (Dias et al., 2002, p. 271). The researchers specifically tested
the differential impact of various brand drivers, such as pricing and advertising, on
various customer segments. Three particular insights were reported from the findings,
namely: 1) customer segments were found to differ on their current and potential value
to the brands within a category; 2) the contribution of different marketing variables have
varying impacts on different consumer segments; and 3) brand loyal customers are les
less motivated by promotions, but are influenced by advertising; and brand switchers
were found to be motivated purely by promotions. The results of this study are
significant because they demonstrate that knowing accurately how sales respond to
demand drivers at the customer level informs planning and decision making at the
marketing strategy development stage.
Bolton et al. (2004) proposed an integrated framework, called Customer Asset
Management of Services (CUSAMS) to understand and influence the value of customer
assets and to understand the influence of marketing instruments on those assets (see
Figure 2.02). The authors proposed that the foundation of the CUSAMS framework is
the specification of key customer behaviors that reflect the length, depth, and breadth of
the customer-service organization relationship: duration, usage, and cross- buying.
18
Table 2.01. Literature on the Antecedents of Customer Equity
Reference Key Focus
Lemon, Rust, and Zeithaml (2001); Rust, Zeithaml, and Lemon, (2000); Rust, Zeithaml, and Lemon (2004); Rust, Zeithaml, and Narayandas (2004).
Presented a strategic framework revealing the key drivers thought to increase a firm’s customer equity. Three key drivers of a firm’s customer equity, namely: value equity, brand equity and retention equity were proposed.
Bayon, Gutsche, and Bauer (2002)
Overview of customer equity as a process in marketing. Discussed management process, modeling, and segmentation.
Dias, Pilhens, and Ricci (2002)
Examined the impact of marketing activities on customer profitability and shareholder value.
Bolton, Lemon, and Verhoef (2004)
Proposed an integrated framework, called CUSAMS (customer asset management of services) to understand and influence the value of customer assets.
Chang and Tseng (2005)
An exploration of the mediating roles of the drivers of customer equity in the effect of relationship marketing activities on customer per capita revenue.
Voorhees (2006) Tested the efficacy of the customer equity drivers in predicting actual customer behaviors.
19
The framework was intended to be a starting point for a set of propositions regarding
how marketing instruments influence customer behavior within the relationship, thereby
The following section explains the steps for the first order CFA.
Specification
An important first step in the analysis of a confirmatory factor model is the
specification of a measurement model that is well grounded in prior empirical evidence
and theory (Brown, 2006). CFA specification is based on a strong conceptual
framework and on prior research that is more exploratory in nature (Brown, 2006).
Model specification is important because many different relationships among a set of
variables can be postulated with many different parameters being estimated. As such,
many different factor models can be postulated on the basis of different hypothesized
relationships between the observed variables and the factors (Schumacker & Lomax,
2004).
According to Long (1983), the specification of the confirmatory factor model
requires the researcher to make formal and explicit statements about the following six
items: 1) the number of common factors; 2) the number of observed variables; 3) the
variances and covariances among the common factors; 4) the relationships among
observed variables and latent factors; 5) the relationships among unique factors and
139
observed variables; and 6) the variances and covariances among the unique factors
(Long, 1983).
In the current study, the researcher is evaluating the latent structure for a model
of value equity in spectator sports. Substantive theory and prior exploratory factor
analysis involving a separate data set suggest that the latent structure of the current
stage of the study is predicted to be characterized by 16 first-order factors that
represent 16 distinctive ways in which spectators derive value from the consumption of
spectator sports: Amusement, Partying, Game Immersion, Escape, Aesthetics, Drama,
Experience Intensity, Family, Non-Family, Business Opportunities, Epistemic Value,
Monetary, Non-Monetary, Interaction Quality, Outcome Quality, and Satisfaction.
Identification
Once a confirmatory factor model has been specified, the researcher must
determine whether the model is identified. Model identification is concerned with
whether the parameters of the model are uniquely determined. A model is identified
when there are an adequate number of observed variances and covariances to estimate
all of the unknowns (Tate, 1998). The t-rule is a useful test for identification. The t-rule
is satisfied if the number of variances and covariances of the observed variables
(p[p+1]/2 where p is the number of x’s) is equal to or greater than the number of model
parameters to be estimated. The model parameters to be estimated include the
covariances of the latent variables, the factor loadings, and the measurement error
variances. In the current study a count of the free parameters is as follows:
• 74 factor loadings
• 74 measurement error variances
• 16 correlations among the latent variables
A total of 164 free parameters were estimated. The number of distinct values in the
matrix S is equal to 74(74+1)/2 = 2775. The number of values in S, 2775, is greater
than the number of free parameters, 164, with the difference being the degrees of
freedom for the specified model, df = 2775 – 164 = 2611. According to the order
condition, the current model is overidentified because there are more values in S than
parameters to be estimated (Schumacker & Lomax, 2004). As a result, a test of the
model is possible (Tate, 1998).
140
Estimation
Once identification has taken place, it is necessary to conduct an estimation of
the confirmatory factor model. The purpose for estimating the factor model is to find
estimates of the parameters that reproduce the sample matrix of variances and
covariances of the observed variables as closely as possible in some well-defined
sense (Long, 1983). Several different procedures can be used to estimate the
parameters of a confirmatory factor model, including: maximum likelihood (ML),
generalized least squares (GLS), unweighted least squares (ULS), weighted least
squares (WLS), and robust maximum likelihood. According to Brown (2006), the use of
maximum likelihood estimation is most appropriate in situations where there is a
sufficient sample size and indicators approach interval level scales. Given these
recommendations, maximum likelihood (ML) was used to estimate the parameters of
the factor model for Value equity.
Evaluation
Model evaluation is the next important step in the scale development process. At
this stage, all items were tested in the same model and were restricted to load on their
particular factors. The acceptability of the CFA solution was evaluated on the basis of
the goodness of fit statistics, the presence or absence of localized areas of strain, and
the interpretability, size, and statistical significance of the model’s parameter estimates.
First, the goodness-of-fit of the model was evaluated using a selection of goodness-of-fit
indices recommended by Brown (2006) including: chi-square statistic, standardized root
mean square residual (SRMR), root mean square error of approximation (RMSEA),
comparative fit index (CFI), and the Tucker-Lewis index (TLI). The TLI is referred to in
LISREL 8.1 (Jöreskog & Sörbom, 2006) as the non-normed fit index (NNFI).
The chi-square statistic is a measure of the overall or absolute fit of a model.
The resulting chi-square value is compared to a critical value for a selected alpha level
for statistical significance. A statistically significant chi-square value supports the
hypothesis that the model estimates do not sufficiently reproduce the sample variances
and covariance meaning the model does not fit the data the well (Brown, 2006). Thus,
a statistically insignificant result is desirable. However, Brown (2006) noted that the chi-
square index is rarely used as a sole index of model fit because it is often inflated by
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sample size, where large N solutions are commonly rejected on its basis even when
differences between model and sample variance and covariances are negligible.
Another measure of the absolute fit of a model is the SRMR. The SRMR is a
measure of the average discrepancy between the correlations observed in the input
matrix and the correlations predicted by the model. The SRMR, which is derived from
the residual correlation matrix, is calculated by summing the elements of the residual
correlation matrix and dividing the sum by the number of elements in the matrix and
then taking the square root of this result (Brown, 2006). Ranging in value from 0.0 to
1.0, with 0.0 indicating a perfect fit, Hu and Bentler (1999) suggested that an SRMR
close to .08 or below is indicative of a reasonably good fit.
The RMSEA, according to Brown (2006), is a measure of absolute model fit that
incorporates a penalty function in its calculation for poor model parsimony. With a
relative insensitivity to sample size, the RMSEA is an index that assesses the extent to
which a model fits reasonably well in the population. As with the SRMR, RMSEA values
of 0.0 indicate perfect fit. The upper value of the RMSEA are unbounded, however,
Brown (2006) noted it is rare for RMSEA values to exceed 1.0. Numerous
recommendations exist in the literature regarding the evaluation of the cut-off criteria for
determining the fit of a model. Hu and Bentler (1999) suggested values close to .06 or
below signify a reasonably good fit. Browne and Cudeck (1993) provided descriptive
anchors for various ranges of fit. For example, the authors proposed that RMSEA
values of less than 0.05 are indicative of good model fit, values less than .08 suggest
adequate model fit, and RMSEA values greater than 1.0 should be rejected. Finally
McCallum, Browne, and Sugawara (1996) proposed that values between .08 and 1.0
suggest a mediocre fit of the model to the data.
The CFI and NNFI are referred to as comparative fit indices (Brown, 2006), or
incremental fit indices (Hu & Bentler, 1998). These indices evaluate the fit of a
researcher-specified solution in relation to a more restricted, nested baseline model.
The baseline model is a “null” or “independence” model in which the indicator
covariances are fixed to zero and the variances are left unconstrained (Brown, 2006).
The NNFI differs slightly from the CFI in that it includes a penalty function for adding
freely estimated parameters that do not markedly improve the fit of the model. Hu and
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Bentler (1990) suggested that CFI and NNFI values that are close to .95 or greater are
indicative of reasonably good fit. Bentler (1990) proposed that CFI and NNFI values in
the range of .90-.95 are suggestive of acceptable model fit. An understanding of how
the various fit indices are calculated is crucial for the identification of localized areas of
strain in a poor fitting model. After the assessment of the overall fit of the model, the
researcher examined various measures of internal fit to identify potential sources of
misspecification.
A powerful indicator of the internal structure of a model is the fitted residuals
(Bagozzi & Yi, 1988). An examination of the fitted residuals is an appropriate method
for analyzing local areas of strain in a model (Brown, 2006) and for identifying sources
of misspecification (Anderson & Gerbing, 1988). Researchers have suggested that
residual values that are greater than .15 indicate an issue of misspecification
(McDonald, 2002).
In addition to the evaluation of model fit and localized strain, the standardized
factor loadings, confidence intervals, standard errors, t-values, construct reliabilities,
and average variance extracted (AVE) scores for the 16 constructs were calculated.
For the purposes of the current research project, convergent and discriminant validity
are two validation processes applicable for providing evidence of the construct validity
of psychological measures. Convergent validity was evaluated through an examination
of the significance of t-values and the average variance extracted (Fornell & Larcker,
1981). Discriminant validity was tested using the correlation threshold of .85
recommended by Kline (2000).
Finally, the researcher did not evaluate criterion-related validity in the current
study. Based on the definition of criterion validity presented earlier, this type of validity
is used to demonstrate the accuracy of a measurement instrument by comparing it with
another procedure, which has been demonstrated to be valid. Two-types of criterion-
related validity are predictive validity and concurrent validity. Predictive validity was not
assessed, as the purpose of this research was to develop a valid and reliable
instrument to assess consumers’ perceptions of value vis-à-vis the sport consumption
experience. At this stage, the researcher was not concerned with whether the
instrument could accurately predict future behaviors such as attendance, word-of-
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mouth, and switching. Future studies designed to measure the effect of perceptions on
future consumption habits would be concerned with the establishment of predictive
validity in order to use the developed instrument with confidence to discriminate
between consumers based on the measured outcomes. Recall that concurrent validity
refers to the degree to which a measurement instrument correlates with an established
and tested measure of the same construct. Thus, if the results are compared and have
a high correlation with an established (tested) measurement, one could say that the
measure has concurrent validity and is valid. As there have not been any previous
efforts to develop a comprehensive measure of value equity in spectator sports, it is not
possible to compare the results of this study to an established measure, and thus it is
not possible to establish concurrent validity.
Second Data Collection – Main Study
Based on the results of the first data collection of the main study, a modified 14-
factor, 64-item survey form was administered to 350 students enrolled at a
Southeastern University during the summer semester of 2007. The modifications to the
scale involved the rewording of the items to contain non-team specific language (see
Appendix H). Additionally, the tense of certain items was changed from present to past-
tense to account for the fact that students were asked about their previous consumption
experiences. Students were sampled from several disciplines across campus,
including: the College of Business, the College of Communications, Athletic Training,
and the Lifetime Activities Program. The survey administration resulted in a total of 285
useable questionnaires for a return rate of 81.4%. There were four reasons why the 65
forms were deemed unusable and thus omitted from the analysis: 1) the forms were not
returned (n = 32); 2) the forms were filled out incorrectly (n = 8); 3) the returned forms
had at least one complete page of questions left blank (n = 9); and 4) there were too
many (> 10%) missing values (n =16).
The sample size is considered to be appropriate given the literature on the
recommendations regarding sample size in factor analysis. In terms of the
recommended guidelines for the minimum necessary absolute sample size, Kline
(2000) and Gorsuch (1983) recommended that N should be at least 100. Guilford
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(1954) proposed that N should be at least 200, while Cattell (1978) argued the minimum
desirable N to be 250. Regarding the recommendations for the minimum ratio of
sample size, N to the number of variables being analyzed, p, Cattell (1978) believed this
ratio should be in the range of three to six, while Gorsuch (1983) argued for a minimum
ratio of five. The N:p ratio for this data collection was 4.45:1.
The researcher chose to survey a sample of students at this stage to further
examine the psychometric properties of the Value Equity in Spectator Sports Scale
across sports. The previous two data collections involved surveys of baseball
spectators. As the current research is a study of sport consumers, students were asked
to identify the last collegiate or professional sporting event they had attended. Students
were then instructed to respond to each question in the survey while thinking about that
consumption experience. Students were also asked to report the date on which they
attended that game, as well as the number of times they have attended games of the
identified team. The majority of the students reported that a college sporting event had
been the last they attended, while more than half of the sample reported having
attended their last game inside of six months. Additionally, a majority of the sample
reported that they had attended games of the indicated team more than one time. The
purposes of the qualification questions were twofold: First, it was necessary to provide
participants with a subject from which perceptions of value could be made. Second, the
responses to these questions provided evidence that the students sampled were
consumers of sporting events.
Recognizing that the length of time after consumption may adversely impact
perceptions, a chi-square difference test between those who had last attended a game
within six months and those who last attended a game more than six months ago was
computed on the mean scores for the manifest variables. This test was conducted to
establish that length of time after consumption did not affect perceptions. The results of
the chi-square analysis, which are presented in the next chapter, indicated there were
not any statistically significant differences between groups. As such, responses from
the two groups were combined in order to test the scale.
Finally, the same procedures that were used to test the factor-structure from the
first data collection of the main study were used to test the first-order factor structure for
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the second data collection. Additionally, following the testing of the first-order factor
structure, the researcher chose to examine the second-order factor structure at this
stage as well. Marsh (1987) noted that the existence of a well-defined, a priori, first-
order factor structure is a precondition for testing higher order structures as successive
higher order models are based on it and its goodness of fit is the upper limit for the
goodness of fit for higher order models. Therefore, a second-order model was
calculated to test the notion that individual second-order dimensions integrate the first-
order variables.
Specifically, a second-order hierarchical CFA (HCFA) utilizing a two-step
procedure was computed to assess the Value Equity in Spectator Sport Scale (VESSS).
Hierarchical CFA models are used to examine hierarchical relationships between
constructs through the specification of higher-order factors with presumed direct causal
effects on lower order factors (Kline, 2005). Marsh and Hocevar (1988) noted three
differences between HCFA and traditional CFA models. First, estimates of
measurement error in the HCFA model are based on the agreement among multiple
measured variables (items or combined items). Second, HCFA allows for an a priori
factor structure hypothesized to underlie the multiple indicators of each scale to be
formally examined because HCFA is based on item-level estimation. Traditional CFA
models do not provide statistical testing information to evaluate or modify a priori
structures. Finally, HCFA models are capable of testing the assumption that error-
uniqueness for the items used to represent each scale are truly not correlated, which is
not available in traditional CFA models. According to Marsh (1987) the purpose of
HCFA is to explain covariation among the first-order factors with one or more higher-
order factors.
Higher-order factor analysis, or hierarchical factor analysis, is a theory driven
procedure in which the researcher imposes a more parsimonious structure to account
for the interrelationships among factors established by the CFA. According to Brown
(2006) the general sequence of a CFA-based higher-order factor analysis is as follows:
1) develop a good-fitting, conceptually valid, first-order CFA solution; 2) examine the
magnitude and pattern of correlations among factors in the first-order solution; and 3) fit
the second-order factor model, as justified on conceptual and empirical grounds.
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Step 8 – Development of Norms
The establishment of norms in psychological measurement refers to the
formalization of processes by making implicit standards explicit (Churchill, 1979). In an
effort to provide a preliminary reference for scale norms, range, means, and standard
deviations were reported for the scale scores of the main study and subsequently
compared to scores on the same measures found in the pilot study.
Summary
The current chapter presented the methodology employed in the current
research to conduct the main part of the study. Churchill’s (1979) eight-step procedure
for developing better measures was used to develop a multi-dimensional measure for
assessing the factors thought to comprise the value in attending sporting events. The
results of the study are presented in Chapter Five.
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CHAPTER V
RESULTS
The main study consisted of two separate data collections. The first data
collection (the second overall) for the main study was used for the initial confirmatory
factor analysis to test the reliability and validity of the modified subscales and to assess
model fit. The second data collection (the third overall) was used for subsequent
validation of the Value Equity in Spectator Sports Scale. The results of the two data
collections are presented in this chapter.
First Data Collection – Main Study
Based on the results of the pilot study, a modified survey questionnaire was
administered to spectators in attendance at a Jacksonville Suns’ baseball game at the
Baseball Grounds of Jacksonville in Jacksonville, Florida. The Suns are the ‘Double A”
minor league baseball affiliate of the Los Angeles Dodgers. The questionnaires were
distributed to 550 spectators situated throughout six different areas of the ballpark. A
total of 376 useable questionnaires were returned for a return rate of 68%. The sample
size for analysis met the minimum cases per variable ratio of five to one recommended
by Gorsuch (1983) and Hatcher (1998).
Characteristics of the Sample
Six demographic classification characteristics were measured in the survey
instrument for the main study: gender, age, marital status, household income, ethnicity,
and education. As indicated in Table 5.01, 55.4% of the respondents were male. In
terms of age, nearly 40% of the sample were between the ages of 35 and 49. Seventy
one percent of the sample was married, over 93% were Caucasian, and just over 40%
had completed at least an undergraduate degree. Finally, for household income, the
largest group was those earning more than $100,000 per year (28.4%) followed by
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Table 5.01. Demographic Characteristics of the Confirmatory Sample
Demographic Variables Frequency Valid Percent
Cumulative Percent
Gender Female 166 44.6 Male 206 55.4 Total 372 100.0 System Missing 4 Age 18-34 82 29.0 29.0 35-49 111 39.2 68.2 50-64 70 24.7 92.9 65+ 20 7.1 100.0 Total 283 100.0 System Missing 93 Marital Status Married 262 71.0 Single 65 17.6 Divorced 27 7.3 Widowed 10 2.7 Other 5 1.4 Total 369 100.0 System Missing 7 Household Income < $20,000 24 7.3 7.3 $20,000 - $39,999 43 13.1 20.4 $40,000 - $59,999 64 19.5 39.9 $60,000 - $79,999 63 19.2 59.1 $80,000 - $99,999 41 12.5 71.6 $100,000+ 93 28.4 100.0 Total 328 100.0 System Missing 48 Ethnicity Black/African American 15 4.1 Native American 3 .8 Asian / Pacific Islander 4 1.1 White/Caucasian 339 93.1 Latina/Latino 2 .5 Other 1 .3 Total 364 100.0 System Missing 12 Education High School Diploma 106 29.5 29.5 Trade/Professional 45 12.5 42.1 Junior College Diploma 60 16.7 58.8 Undergraduate Degree 99 27.6 86.4 Masters Degree 37 10.3 96.7 Doctoral Degree 12 3.3 100.0 Total 359 100.0 System Missing 17
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those earning between $40,000 and $59,999 (19.5%) and earners making between
$60,000 and $79,999 (19.2%).
Model Evaluation
The 16-factor model was tested using all 74 items retained from the exploratory
factor analysis (see Appendix D). The standardized factor loadings (β), confidence
intervals (90% CI), standard errors (SE), t-values (t), Construct Reliabilities (CR), and
average variance extracted for the 16 constructs are presented in Table 5.02. The
factor loadings ranged from.629 to .834 in amusement; .154 to .861 in partying; .603 to
.762 in experience intensity; .119 to .766 in game immersion; .357 to .884 in escape;
.593 to .754 in aesthetics;.297 to .868 in drama; .532 to .800 in non family; .765 to .861
in family; .738 to .799 in business opportunities; .813 to .927 in epistemic value; .376 to
.815 in monetary; .799 to .890 in non monetary; .586 to .825 in satisfaction; .439 to .880
in interaction quality; .434 to .914 in outcome quality.
Model Fit
As described in chapter four, several fit indices were used to verify the sub-scale
structure of the instrument. The measures of model fit employed in the current study
are presented in Table 5.03. The Χ2 value was 10286.05 (p < 0.00), which was not
satisfactory. Additional measures of model fit included: SRMR (.089), RMSEA (.089),
NNFI (.906), and CFI (.913). The model fit indices suggest that the fit of the data to the
model is adequate to mediocre.
Internal Consistency Reliability
The 74 items were examined for internal consistency based on an assessment of
the construct reliabilities. Construct reliabilities are reported in Table 5.02. The
construct reliability scores for each of the subscales were as follows: amusement (.84);
partying (.85); experience intensity (.74); game immersion (.75); escape (.75);
aesthetics (.73); drama (.77); non family (.86); family (.86); business opportunity (.83);
epistemic value (.90); monetary (.78); non monetary (.87); satisfaction (.79); interaction
quality (.96); and outcome quality (.90). Each of the 16 subscales scored above .70,
indicating good internal consistency.
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Construct Validity
Convergent validity. Five of the sixteen constructs did not meet the .50
threshold recommended by Fornell and Larker (1981) indicating poor construct validity.
The results of the test for convergent validity are presented in Table 5.02. Constructs
with low AVE scores included: experience intensity (.49); game immersion (.41);
aesthetics (.48); drama (.49); and monetary (.49).
An examination of the residual matrix of the current model (not included in the
results) revealed that 15.11% of the residuals were greater than .15. Items with the
highest residuals were associated with the following four factors: 1) Game Immersion;
2) Drama; 3) Escape; and 4) Interaction Quality. Five items specifically accounted for
54.28% of the high residuals - gamint8 (16.1%), drama4 (14.78%), esc3 (11.7%), party6
(7%), and iq15 (4.7%).
Discriminant validity. Table 5.04 shows the correlations among the 16 latent
variables. The correlations among the sixteen dimensions ranged from .002 to .986.
The correlation between interaction quality and outcome quality (.986) was above the
threshold specified by Kline (2000), as were the correlations between satisfaction and
interaction quality (.904); and between satisfaction and outcome quality (.853).
The results of the test for discriminant validity are presented in Table 5.05. The
results indicate that the test failed to discriminate among several constructs, suggesting
a lack of differentiation among the constructs. The constructs that proved to be the
most difficult were Satisfaction, Interaction Quality, and Outcome Quality. Each of these
constructs correlated with several other factors.
The results revealed that the initial measurement model failed to discriminate
between the two service quality constructs: interaction quality and outcome quality. As
such, a chi-square difference test was conducted on two competing models of service
quality to determine whether service quality is best represented as a one-factor or two-
factor construct. Using a chi-square difference test, the chi-square score from Model A
is subtracted from Model B's chi-square score. This difference represents the value of
chi-square difference that is tested. Model A's degrees of freedom are then subtracted
from Model B's degrees of freedom. This difference should correspond to the number of
paths that Model B lacks relative to Model A, and this is the degrees of freedom for
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the difference test. The chi-square difference value is then applied to a chi-square
table, using the computed degrees of freedom. If the test is significant, it suggests that
deleting the parameters in Model B adversely affected the fit of the model. Figure 5.01
depicts the two models of service quality.
The results of the chi-square difference test of the two models are reported in
Table 5.06. The difference of chi-square statistics for the two models was 12.77 with
one degree of freedom. The results indicated that there existed a significant difference
between the chi-square values of the two models at the .05 probability level, suggesting
that the two-factor model of service quality provided a better fit to the data than did the
one-factor model.
Discussion of First Data Collection – Main Study
The primary objective of this study was to develop a reliable and valid
measurement model of value equity in spectator sports. The current discussion will
focus on the results from the first data collection. Specifically, issues related to overall
model fit, internal structure fit, and model validity are discussed. Initial testing of the
components of value equity in the exploratory phase of the research resulted in a
reduction of the items in the measurement pool from 91 to 74. Consequently, the first
confirmatory factor analysis was conducted to identify the latent factors thought to
account for variation and covariation among the set of indicators specified by the
exploratory factor analysis conducted in the pilot phase of the research.
Overall model fit. A 16-factor, 74-item measurement model of value equity was
evaluated for overall fit using several indices of fit recommended by Brown (2006). The
overall model fit indices indicated that while the fit of the data was not terrible, there was
plenty of room for improvement. Although the Χ2 value was not satisfactory, Brown
(2006) noted that the chi-square index is rarely used in applied research as a sole index
of model fit as it can be sensitive to sample size. It was recommended that other fit
indices be relied upon more heavily in the evaluation of model fit. While the two
measures of comparative fit did fall within the .90 -.95 range indicating acceptable fit
(Bentler, 1990), the SRMR (.0892) and the RMSEA (.0892) were above the thresholds
specified by Hu and Bentler (1999) and Browne and Cudeck (1993) for acceptable fit.
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Table 5.02. CFA for the Value Equity Factors and Items: Item Loadings (β), Confidence Intervals (CI), Standards Errors (SE), t-values (t), Construct Reliabilities (CR); and Average Variance Extracted (AVE)
Comparative Fit Index (CFI) .913 .90 – .95 = acceptable fit (Bentler, 1990)
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Table 5.04. Factor Correlations for First Data Collection
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Table 5.05. Discriminant Validity Analysis for Model AVE’s
Factor Non-Discriminating Factors
Satisfaction Interaction Quality, Outcome Quality
Interaction Quality Satisfaction, Outcome Quality
Outcome Quality Interaction Quality, Satisfaction
Table 5.06. X2 difference test for One- and Two-Factor Models of Service Quality
Goodness of Fit Test of Invariance
Model X
2 df p-value CFI
X2 difference with the baseline model p-value
Model A 1428.36 188 .000 .96
Model B 1441.14 189 .000 .96 X2 difference(1) = 12.77 <.05
*The critical value of X2 with one degree of freedom is 3.841 at the .05 probability level.
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Figure 5.01. Competing models of service quality for the X2 difference test
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Following the assessment of the overall fit of the model, the researcher examined
various measures of internal fit to identify potential sources of misspecification.
Assessment of internal fit. Based on the examination of indices, the following
observations were made and subsequent actions taken. The item loading for party6
(.154) suggested that this item did not load well on the Partying construct. The fitted
residuals also revealed this item to be problematic. Thus, party6 was removed from
further analysis. Another item that merited inspection was gamint8. This item did not
load well on the Game Immersion construct as its item loading of .119 was well below
the recommended .70. Also, this item was associated with the greatest percentage of
problematic residuals. More than 16% of the problematic residuals were found with this
item. Thus, it was decided to eliminate this item for further analysis in the respecified
model in order to remain consistent in the application of item removal criteria. Other
items that did not merit inclusion in the respecified model were drama4, mon5 and iq15.
These items did not load well on their respective constructs. The item esc3 was
retained as a measure of Escape despite not loading well on the construct as the
reliability and AVE score met the established cut-off values and it was important to
retain three measures of Escape.
Construct validity. Two measures of construct validity were examined in the
current research project, convergent validity and discriminant validity.
Convergent Validity
The results indicated that the AVE scores for five of the sixteen constructs did
not meet the .50 threshold recommended by Fornell and Larker (1981), including
experience intensity, game immersion, aesthetics, drama, and monetary.
Discriminant Validity
An examination of the correlation matrix for the current model revealed that the
correlations between Interaction Quality and Outcome Quality (.986); Satisfaction and
Interaction Quality (.904); and between Satisfaction and Outcome Quality (.853) each
exceeded the .85 threshold specified by Kline (2000).
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Measurement Model Respecification
The 16-factor model with 74 indicators needed to be modified to provide the best
fit to the data based on suggestions from the tests of model estimations and fit of the
internal structure. Bollen (1989) proposed two criteria for model respecification: 1) the
exclusion of items with poor fit to the data, and 2) the preservation of a minimum of
three items per construct. Based on the results of the first data collection of the main
study several modifications were made.
First, due to their high correlation, the initial measurement model failed to
discriminate between the two service quality constructs, namely: interaction quality and
outcome quality. In order to solve the problem the researcher considered two
scenarios: combining the two factors together resulting in one construct, and the
retention of the two separate factors. Two different models of service quality were
tested to determine whether service quality is best represented as a one-factor or two-
factor construct. The chi-square difference test was used to make a direct comparison
between the nested models (Bagozzi & Phillips, 1982). The results indicated there was
a significant difference between the chi-square values of the two models at the .05
probability level, suggesting that the two-factor model of service quality provided a
better fit to the data than did the one-factor model. As such, each of the dimensions of
service quality were retained in the model. The decision to retain both factors was also
supported by the literature, which views service quality as a two-dimensional construct
comprised of technical and functional elements (Grönroos, 1984).
Next, the item loadings for the Partying dimension were considered. The item
loading for party6 was .154. A low item loading indicates that the item does not load
well on the construct. Additionally, the fitted residual for party6 was high. High fitted
residuals indicate there exists a difference between the observed covariance matrix S
and the model-implied covariance matrix ∑ and that the model is misspecified. An
appropriate course of action for dealing with low item loadings is to drop the item from
the model. Misspecified items may also be dropped from the model. Thus, the
researcher decided to delete the item party6 from further analysis. Another item that
merited inspection was gamint8. This item did not load well on the Game Immersion
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construct as its item loading of .119 was well below the recommended .70. Also, this
item was associated with the greatest percentage of problematic residuals. More than
16% of the problematic residuals were found with this item. Thus, this item was also
eliminated from further analysis. The respecified model did not include gamint8 as a
measure of Game Immersion. Finally, the AVE score for Game Immersion (.41) was
well below the recommended threshold of. 50 indicating that more than half the total
variance of Game Immersion was derived from measurement error. The decision to
keep this construct in the measurement model was justified using the rationale that the
elimination of the underperforming measurement item (gamint8) would cause the
average variance extracted to increase sufficiently.
Other items that were not included in the respecified model due to low item
loadings were drama4, mon5 and iq15. Each of these items did not load well on their
respective constructs. There were also problems with the Escape construct. The item
esc3 did not load well on the construct. However, this item was retained as a measure
of Escape as the construct reliability and AVE score met the established cut-off values.
Next, an examination of the reliability and validity of the ‘Experience Intensity’
construct revealed that this construct was reliable. The reliability (.74) was above the
established threshold, while the AVE (.49) score was just below the recommended cut-
off threshold of .50. The results of the reliability and validity analysis should have led
the researcher to make a decision to include this construct in subsequent testing,
however this was not done. Rather, the researcher erroneously chose to eliminate this
construct from the model of value equity. See the footnote at the bottom of the page for
a detailed explanation for this decision.1
Next, an examination of the AVE scores for each of the scales indicated that five
of the sixteen construct did not meet the .50 threshold recommended by Fornell and
Larker (1981). The rationale for retaining or excluding experience intensity and game
immersion based on their respective AVE scores has been addressed. It was decided 1 Initially, the researcher computed Cronbach’s alpha scores as a measure of reliability and based on that information removed the items and proceeded with the second data collection. Much later, the researcher realized that a more appropriate measure of reliability in confirmatory factor analysis is a calculation of the construct reliabilities and not Cronbach’s alpha. As a result, the researcher acknowledges that the three items should have been retained, and future research should examine the construct to determine its viability in the model.
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by the researcher to keep the constructs of drama and monetary for subsequent testing
because the elimination of underperforming individual items within each of those scales
was expected to improve the AVE scores of those constructs.
Finally, while the reworded items for the Satisfaction construct did result in the
construct obtaining adequate reliability and AVE score, a decision was made to drop
Satisfaction from the model because of its failure to discriminate from the three other
constructs. This identification of non-discrimination was based on an examination of the
correlation matrix and on Kline’s (2000) threshold for discriminant validity. Satisfaction
was defined as a customer’s evaluation of pleasurable fulfillment of some need, desire,
or goal (Oliver, 1997). The relationship between satisfaction and value has been the
subject of much study. There has been general support in the literature for satisfaction
being an outcome of value. Woodruff (2003) noted that satisfaction is a customer’s
feelings, or emotional response, to cognitive evaluations of one or more use
experiences with a product. As indicated in the literature review, a majority of
researchers have empirically found support for viewing satisfaction as an outcome of
value as opposed to an antecedent (Brady, Cronin, & Hult, 2000). The failure of the
satisfaction construct to discriminate from two other factors, including, Interaction
Quality and Outcome Quality led the researcher to contend that satisfaction should be
regarded as an outcome of value. Each of the other measures of value assess
consumers’ cognitive evaluations of their experiences with the sport service. As such,
the researcher chose to eliminate satisfaction from the model.
Testing of the Modified Measurement Model
Model specification. Based on the modifications described above, a respecified
model comprised of 14 latent variables and 64 indicators was identified and tested using
the same data set. Figure 5.02 illustrates the relationships between the second-order
variables, latent variables, and indicators in the modified measurement model.
Entertainment Value comprises six latent variables measured by 22 indicators:
amusement (four indicators), partying (five indicators), game immersion (4 indicators),
escape (three indicators), aesthetics (three indicators), and drama (three indicators).
Social Value comprises three latent variables measured by 12 indicators: family (three
indicators), non-family (six indicators), and business opportunities (three indicators).
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Service quality comprises two latent variables measured by 21 indicators: interaction
drama (.79); non family (.86); family (.86); business opportunity (.83); epistemic value
(.90); monetary (.82); non monetary (.86); interaction quality (.97); and outcome quality
(.86). Each of the 14 subscales scored above .70, indicating good internal consistency.
Construct validity. Two measures of construct validity were examined for the
respecified model, namely, convergent validity and discriminant validity.
Convergent Validity
As illustrated in Table 5.02, the AVE scores ranged from .50 to .76. The AVE
score for each of the 14 constructs met the established .50 threshold. An examination
of the residual matrix of the respecified model revealed that 50 of 954 residuals (5.24%)
were greater than .15. According to McDonald (2002) residual values below .15 are
acceptable, while values greater than .15 indicate a possible misspecification of the
model. Items with the highest residuals were associated with the following three
factors: 1) Interaction Quality; 2) Partying; and 3) Amusement. Four of the items
accounted for over 50% of the high residuals, namely: iq11 (16%), party3 (14%), party7
(11%), and amuse1 (10%).
Discriminant Validity.
An examination of the correlation matrix presented in Table 5.08 revealed that
none of the correlations exceeded the .85 threshold specified by Kline (2000). The
results present sufficient evidence that the latent factors represent distinct constructs.
166
Table 5.07. CFA for the RESPECIFIED Value Equity Factors and Items: Item Loadings (β), Standards Errors (SE), Standard Deviations (SD), Construct Reliabilities (CR), and Average Variance Extracted (AVE)
Table 5.07 (cont.) CFA for the RESPECIFIED Value Equity Factors and Items: Item Loadings (β), Standards Errors (SE), Standard Deviations (SD), Construct Reliabilities (CR), and Average Variance Extracted (AVE)
D E P A R T M E N T O F S P O R T M A N A G E M E N T , R E C R E A T I O N M A N A G E M E N T , A N D P H Y S I C A L E D U C A T I O N
2 0 0 T U L L Y G Y M · T A L L A H A S S E E F L O R I D A · 3 2 3 0 6 - 4 2 8 0 P H O N E : ( 8 5 0 ) 6 4 4 - 4 8 1 4 0 0 · F A X : ( 8 5 0 ) 6 4 4 - 0 9 7 5
218
May 11, 2007
Mr. Kirk Goodman
General Manager
Jacksonville Suns Baseball Club
Baseball Grounds of Jacksonville
301 A. Philip Randolph Blvd.
Jacksonville, FL 32202
Dear Mr. Goodman:
I am a current employee in with the Florida State University Athletics ticket office and a Ph.D.
student studying in the area of Sport Management. I am writing to gain support for my
dissertation study, which focuses on the areas of consumer behavior and marketing. More
specifically, I am examining issues related to baseball spectators’ perceptions of value, service
quality, and satisfaction.
In order to acquire the necessary data for this study, I am seeking permission to survey spectators
at the Baseball Grounds of Jacksonville on Monday, May 21. The survey will be relatively short
in length, easy to complete, and will not disturb fans while the game is in progress. I am
currently conducting a similar study with the Seminoles baseball team. I have attached a copy of
the survey that I am using with the Seminoles. The survey used to for Suns’ spectators will be
similar.
The specific details of the study are as follows:
Purpose: My study involves a determination of sport consumer perceptions of the service experience at
sporting events. For this study, I am interested in examining baseball spectators’ perceptions of value and
service quality and their level of satisfaction with their experience at Suns’ games. I will also collect
information about consumption habits (including amount of money spent at Suns’ games, attendance
frequencies, media consumption habits, and merchandise consumption) and future attendance intentions.
Additionally, various demographic classification indicators will be collected, including: age, sex,
education level, household income level, marital status and ethnicity.
Dates: I am interested in distributing questionnaires on May 21, 2007 prior to the Suns final game versus
the Carolina Mudcats.
Data Collection Procedure: The procedure for collecting the data will be similar to procedures that I
have used to collect data for other teams including the Florida State Seminoles, Montreal Expos, Montreal
Canadiens, Montreal Alouettes, and Tallahassee Titans. Through discussion with your organization prior
to the event, six to eight areas of the Baseball Grounds of Jacksonville will be targeted for survey
D E P A R T M E N T O F S P O R T M A N A G E M E N T , R E C R E A T I O N M A N A G E M E N T , A N D P H Y S I C A L E D U C A T I O N
2 0 0 T U L L Y G Y M · T A L L A H A S S E E F L O R I D A · 3 2 3 0 6 - 4 2 8 0 P H O N E : ( 8 5 0 ) 6 4 4 - 4 8 1 4 0 0 · F A X : ( 8 5 0 ) 6 4 4 - 0 9 7 5
219
distribution. These areas will be diverse in location so as to ensure that a cross-sample of
individuals is selected to participate. Surveys and golf pencils will be handed out to spectators in
their seats starting 45 minutes prior to the start of the game and will be collected before the game
starts. Included with the survey will be an introductory letter to introduce the purpose of the
study and to provide direction for its completion. In total, 500 surveys will be distributed. The
survey should take respondents between 10 and 15 minutes to complete.
Miscellaneous: All costs associated with printing, copying and travel are to be assumed by the
researcher. Requested of the organization are the following: (1) credentialing / ticketing for team
members to gain entrance to the Baseball Grounds of Jacksonville; (2) One parking pass for
research team members as deemed appropriate by the Suns
Follow-up: My intention is to have the results of the study ready for distribution to your offices
by the middle of July.
I hope that you feel a study such as this is both worthwhile and helpful towards the development
of a better understanding of the perceptions and preferences of Suns’ spectators. I am hoping
that you will assist in the completion of my study by allowing me access to survey Suns’
spectators at the Baseball Grounds of Jacksonville. Rest assured that at the completion of this
study I would provide the Suns with all of the results.
Please inform me if this proposal meets your approval. I will follow up this letter with a
telephone call in the next week. Should you have any questions regarding any aspect of this
study, please do not hesitate to call me at 850-284-8168, or by email at [email protected].
Thank you very much for your assistance.
Sincerely,
Dan Sweeney
Ph.D. Candidate
220
APPENDIX B
Human Subjects Committee Approval
221
222
APPENDIX C
Florida State Seminoles Baseball Questionnaire
223
Hello, We are Sports Marketing researchers from Florida State University. We are working in cooperation with Florida State Athletics to gain a better understanding of how fans evaluate their experiences at a Florida State baseball game.
Please take a few minutes and complete our survey. Participation is voluntary, and all results are anonymous and confidential to the extent allowed by the law. The survey should take about ten minutes to complete.
If you agree to participate, please answer each question to the best of your knowledge. You do not have to respond to any questions that you are not comfortable with. Sincere and honest responses to questions are greatly appreciated. Completion of the questionnaire is implied consent to use the data you have provided.
You will be asked to evaluate the experience using a series of scales and then to provide some brief background information. For each question below, please select the answer that best reflects your opinion by marking the appropriate circle or filling in the appropriate response.
You must be at least 18 years of age to participate. The data will be stored under lock and key on file on campus until one year after the study has been completed.
If you have any questions, please contact Daniel Sweeney at [email protected], Dr. Jeffrey James at [email protected], or The Florida State University IRB at 850.644.8633 located at the Office of Research, Innovation Park, 100 Sliger Building, Tallahassee, FL, 32306-2811.
Thank you in advance for your participation.
Sincerely,
Daniel Sweeney
224
Please rate the extent to which you DISAGREE or AGREE with each of the following items by circling the appropriate number in the scale beside each statement.
Disagree
1. It just wouldn’t be a Seminoles’ game if I didn’t party. 1 2 3 4 5 6 7
2. There is something special about being in the crowd at Dick Howser Stadium. 1 2 3 4 5 6 7
3. Watching Seminoles’ games is a very intense experience for me. 1 2 3 4 5 6 7
4. Seminoles’ games provide me with a distraction from my everyday activities. 1 2 3 4 5 6 7
5. I value the special events that are organized by the team. 1 2 3 4 5 6 7
6. The Seminoles’ other fans consistently leave me with a good impression of service.
1 2 3 4 5 6 7
7. I like Seminoles’ games because of the natural elegance of the game of baseball. 1 2 3 4 5 6 7
8. I enjoy spending time with my family at Seminoles’ games. 1 2 3 4 5 6 7
9. You can count on the ballpark employees to be friendly. 1 2 3 4 5 6 7
10. The price of Seminoles’ games is high compared to their competitors. 1 2 3 4 5 6 7
11. At Seminoles’ baseball games, you can rely on there being a good atmosphere. 1 2 3 4 5 6 7
12. I love the feeling of being surrounded by all of the fans. 1 2 3 4 5 6 7
13. I really get into the game when I watch Seminoles’ games. 1 2 3 4 5 6 7
14. I enjoy Seminoles’ games because they provide an opportunity to be with my friends.
1 2 3 4 5 6 7
15. Seminoles’ games provide me an opportunity to party. 1 2 3 4 5 6 7
16. Seminoles’ games give me a great opportunity to socialize with other people. 1 2 3 4 5 6 7
17. It takes minimal time to get the information I need about Seminoles’ games. 1 2 3 4 5 6 7
18. Seminoles’ games allow me to increase my knowledge of baseball. 1 2 3 4 5 6 7
19. I can count on the event staff taking actions to address my needs. 1 2 3 4 5 6 7
20. Overall, I am very satisfied with the services that I receive from Seminoles baseball.
1 2 3 4 5 6 7
21. Seminoles’ games provide me with a great opportunity to entertain my clients. 1 2 3 4 5 6 7
22. I like the uncertainty of a close game. 1 2 3 4 5 6 7
23. I concentrate very hard on the action on the field. 1 2 3 4 5 6 7
24. I like the gracefulness associated with the game of baseball. 1 2 3 4 5 6 7
25. Dick Howser Stadium’s layout never fails to impress me. 1 2 3 4 5 6 7
26. The other spectators do not affect the staff’s ability to provide me with good service. 1 2 3 4 5 6 7
27. You can count on the ballpark employees knowing their jobs. 1 2 3 4 5 6 7
28. The special activities going on before games are important to me. 1 2 3 4 5 6 7
29. Waiting time for service at Seminoles’ games is predictable. 1 2 3 4 5 6 7
30. There is a party atmosphere at Seminoles’ games. 1 2 3 4 5 6 7
Agree
Neutral
225
Please rate the extent to which you DISAGREE or AGREE with each of the following items by circling the appropriate number in the scale beside each statement.
31. Seminoles’ games enable me to increase my understanding of baseball strategy.
1 2 3 4 5 6 7
32. I feed off of the excitement of the crowd at Seminoles’ games. 1 2 3 4 5 6 7
33. I feel as much a part of the game as the players. 1 2 3 4 5 6 7
34. I am consistently pleased with the service at Seminoles’ games. 1 2 3 4 5 6 7
35. The price of Seminoles’ games is low. 1 2 3 4 5 6 7
36. The ambience at Seminoles’ baseball is what I am looking for at a game. 1 2 3 4 5 6 7
37. The staff tries to keep my waiting time for service to a minimum. 1 2 3 4 5 6 7
38. I like Seminoles’ games where the outcome is uncertain. 1 2 3 4 5 6 7
39. The attitude of the ballpark staff demonstrates their willingness to help me. 1 2 3 4 5 6 7
40. Overall, I am satisfied with my experience at Seminoles’ baseball games. 1 2 3 4 5 6 7
41. Seminoles’ games give me the chance to socialize with people from my work. 1 2 3 4 5 6 7
42. I like Seminoles’ baseball because they have the service that I want. 1 2 3 4 5 6 7
43. The action on the field is most important to me. 1 2 3 4 5 6 7
44. Seminoles’ games provide me with an escape from my daily life for a while. 1 2 3 4 5 6 7
45. I drink alcohol at the game, which is a big part of watching baseball games. 1 2 3 4 5 6 7
46. Seminoles’ games allow me to learn about the technical aspects of baseball. 1 2 3 4 5 6 7
47. It is easy to get the information I need about Seminoles’ games. 1 2 3 4 5 6 7
48. I enjoy Seminoles’ games because they are a good family activity. 1 2 3 4 5 6 7
49. The ballpark employees respond quickly to my needs. 1 2 3 4 5 6 7
50. The layout of Dick Howser Stadium serves my purposes. 1 2 3 4 5 6 7
51. Seminoles’ baseball games are expensive. 1 2 3 4 5 6 7
52. The excitement among the fans at Seminoles’ games is exhilarating. 1 2 3 4 5 6 7
53. When I am at a game, nothing else matters but the game. 1 2 3 4 5 6 7
54. Having a chance to see friends is one thing I enjoy about Seminoles’ games. 1 2 3 4 5 6 7
55. The special promotions that are a part of Seminoles’ games are meaningful to me. 1 2 3 4 5 6 7
56. I like to talk to other people sitting near me during Seminoles’ games. 1 2 3 4 5 6 7
57. The ballpark staff is able to answer my questions quickly. 1 2 3 4 5 6 7
58. I prefer watching a close game rather than a one-sided game. 1 2 3 4 5 6 7
59. It is easy to contact the Seminoles’ when I need to. 1 2 3 4 5 6 7
60. I like that people can get a little drunk if they choose to at the Seminoles’ games. 1 2 3 4 5 6 7
Neutral Agree
Disagree
226
Please rate the extent to which you DISAGREE or AGREE with each of the following items by circling the appropriate number in the scale beside each statement.
61. Seminoles’ games give me the opportunity to entertain potential clients. 1 2 3 4 5 6 7
62. The ballpark staff understands that waiting time for service is important to me. 1 2 3 4 5 6 7
63. My focus is on the game, and not the other activities at the stadium. 1 2 3 4 5 6 7
64. The event staff knows the kind of service its customers are looking for. 1 2 3 4 5 6 7
65. Seminoles’ games are reasonably priced. 1 2 3 4 5 6 7
66. The baseball staff understands that the atmosphere is important to me. 1 2 3 4 5 6 7
67. Seminoles’ baseball games provide me the opportunity to do something I haven’t done before.
1 2 3 4 5 6 7
68. I am able to get to Dick Howser Stadium quickly for Seminoles’ baseball games. 1 2 3 4 5 6 7
69. The attitude of the ballpark employees shows me they understand my needs. 1 2 3 4 5 6 7
70. I truly enjoy myself at Seminoles’ baseball games. 1 2 3 4 5 6 7
71. A close game involving the Seminoles is more enjoyable than a blowout. 1 2 3 4 5 6 7
72. I like the beauty and grace of sports. 1 2 3 4 5 6 7
73. The game is the most important thing at the stadium. 1 2 3 4 5 6 7
74. Being at Seminoles’ games gives me a chance to bond with my friends. 1 2 3 4 5 6 7
75. The Seminoles’ baseball experience enables people to drink heavily. 1 2 3 4 5 6 7
76. Interacting with other fans is a very important part of being at Seminoles’ games. 1 2 3 4 5 6 7
77. The event staff understands that I rely on their knowledge to meet my needs. 1 2 3 4 5 6 7
78. I am interested in experiencing new things. 1 2 3 4 5 6 7
79. The behavior of the ballpark staff indicates to me that understand my needs. 1 2 3 4 5 6 7
80. The special activities going on during the game are important to me. 1 2 3 4 5 6 7
81. The Seminoles understand that the design of their facility is important to me. 1 2 3 4 5 6 7
82. When I leave Seminoles’ games, I usually feel like I had a good experience. 1 2 3 4 5 6 7
83. Partying at Seminoles’ games is more interesting than watching the games. 1 2 3 4 5 6 7
84. Seminoles’ games allow me to get away from the tension in my life. 1 2 3 4 5 6 7
85. I believe that the Seminoles’ try to give me a good experience. 1 2 3 4 5 6 7
86. The employees at the ballpark understand that the other fans affect my perceptions of service. 1 2 3 4 5 6 7
87. The athletics department makes it easy for me to get tickets to Seminoles’ baseball games. 1 2 3 4 5 6 7
88. Seminoles’ games give me a chance to bond with my family. 1 2 3 4 5 6 7
89. Seminoles’ games give me the chance to experience something different. 1 2 3 4 5 6 7
90. The price of Seminoles’ games is high. 1 2 3 4 5 6 7
91. The event staff knows the type of experience its customers want. 1 2 3 4 5 6 7
Neutral Disagree
Agree
227
For each item below please circle the number that best describes your behavior.
93. I use the Internet to get information about the Seminoles Baseball team. 1 2 3 4 5 6 7
94. I watch the Seminoles play baseball on television. 1 2 3 4 5 6 7
95. I read newspaper articles/editorials about the team. 1 2 3 4 5 6 7
96. I wear clothing that is related to the Seminoles Baseball team. 1 2 3 4 5 6 7
97. How many Seminoles games have you attended at Dick Howser Stadium THIS season? ________________________
98. How many Seminoles games do you think you will attend at Dick Howser Stadium NEXT season? _____________________
99. How much money do you spend at a Seminoles Baseball game (excluding tickets)? $________________ per game
Please tell us a little about yourself by checking or writing the appropriate response to the items below.
All information is confidential and will remain anonymous.
Gender: ___ Female ___ Male
Age: ________ Marital Status: ___ Married ___ Single ___ Divorced ___ Widowed ____ Other
Household Income: ___ less than $20,000 ___ $20,000 - $39,999 ___ $40,000 - $59,999 ___ $60,000 - $79,999 ___ $80,000 - $99,999 ___ $100,000 + Ethnicity: ___Black/African American (non-Hispanic) ___ Native American ___ Asian or Pacific Islander
___ White/Caucasian (non-Hispanic) ___ Latina/Latino ___ Other ____________________
Highest level of education you have completed: ___ High School ___ Professional / Trade School ___ Junior College ___Undergraduate Studies ___ Masters Studies ___ Doctoral Studies
Are you a Season Ticket Holder? ___ Yes ___ No
Thank you for taking the time to complete this questionnaire.
Disagree
Neutral Agree
228
APPENDIX D
Item Codes for Pilot Study Questionnaire
229
Dimensions and Items for Pilot Study Item
#
Amusement I value the special events that are organized by the team. 5 The special activities going on before games are important to me. 28
The special promotions that are a part of the team name games are meaningful to me. 55 The special activities going on during the game are important to me. 80 Partying It just wouldn't be a team name game if I didn't party 1 There is a party atmosphere at team name games. 30 Team name games provide me an opportunity to party. 15 I drink alcohol at the game, which is a big part of watching baseball games. 45 I like that people can get a little drunk if they choose to at team name games. 60 The team name baseball experience enables people to drink heavily. 75 Partying at team name games is more interesting than watching the games. 83 Crowd Experience There is something special about being in a crowd at name of stadium. 2 I love the feeling of being surrounded by all of the fans. 12 I feed off of the excitement of the crowd at team name games. 32 The excitement among the fans at team name games is exhilarating. 52 Game Intensity/Immersion Watching team name games is a very intense experience for me 3 I really get into the game when I watch team name games. 13 I concentrate very hard on the action on the field. 23 I feel as much a part of the game as the players. 33 The action on the field is most important to me. 43 When I am at the game, nothing else matters but the game. 53 My focus is on the game, and not the other activities at the stadium. 63 The game is the most important thing at the stadium. 73 Escape Team name games provide me with a distraction my everyday activities. 4 Team name games provide me with a distraction from my daily life for a while. 44 Team name games allow me to get away from the tension in my life. 84 Aesthetics I like team name games because of the natural elegance of the game of sport. 7 I like the gracefulness associated with the game of sport. 24 I like the beauty and grace of sports. 72
230
Dimensions and Items for Pilot Study (continued) Item
#
Drama I like the uncertainty of a close game. 22 I like team name games where the outcome is uncertain. 38 A close game involving team name is more enjoyable than a blowout. 71 I prefer watching a close game rather than a one-sided game. 58 Social Value Family I enjoy spending time with my family at team name games. 8 I enjoy team name games because they are a good family activity. 48 Team name games give me a chance to bond with my family. 88 Friends I enjoy team name games because they provide an opportunity to be with my friends 14 Having a chance to see friends is one thing I enjoy about team name games. 54 Being at team name games gives me a chance to bond with my friends. 74 Non-Acquaintances Team name games give me a great opportunity to socialize with other people. 16 I like to talk to other people sitting near me during team name games. 56 Interacting with other fans is a very important part of being at team name games. 76 Business Opportunities Team name games provide me with a great opportunity to entertain my clients. 21 Team name games give me a chance to socialize with people from my work. 41 Team name games give me the opportunity to entertain potential clients. 61 Service Quality Interaction Quality Attitude You can count on the ballpark employees to be friendly. 9 The attitude of the ballpark staff demonstrates their willingness to help me. 39 The attitude of the ballpark employees shows me that they understand my needs. 69 Behavior I can count on the event staff taking actions to address my needs. 19 The ballpark employees respond quickly to my needs 49 The behavior of the event staff indicates to me that they understand my needs. 79 Expertise You can count on the ballpark employees knowing their jobs. 27 The ballpark staff is able to answer my questions quickly. 57 The event staff understands that I rely on their knowledge to meet my needs. 77
231
Dimensions and Items for Pilot Study (continued) Item
#
Service Environment Quality Ambient Conditions At team name’s games, you can rely on there being a good atmosphere. 11 The ambience at Team name’s games is what I am looking for at a game. 36 The baseball staff understands that the atmosphere is important to me. 66 Design Factors The team name’s stadium/arena layout never fails to impress me. 25 The layout of stadium name serves my purposes. 50 The team name understands that the design of its facility is important to me. 81 Social Factors The team name’s other fans consistently leave me with a good impression of service. 6 The other spectators do not affect the staff’s ability to provide me with good service. 26 The employees at the ballpark understand that the other fans affect my perceptions of service. 86 Outcome Quality Waiting Time Waiting time for service at team name games is predictable. 29 The staff tries to keep my waiting time for service to a minimum. 37 The ballpark staff understands that waiting time is important to me. 62 Tangibles I am consistently pleased with the at team name games. 34 I like team name sport because they have the service I want. 42 The event staff knows the kind of service its customers are looking for. 64 Valence When I leave team name games, I usually feel like I had a good experience. 82 I believe that team name tries to give me a good experience 85 The event staff knows the type of experience its customers want. 91 Perceived Price Monetary The price team name games is high compared to their competitors. 10 The price of team name team name games is low (reverse coded) 35 Team name games are expensive. 51 Team name games are reasonably priced. 65 The price of team name games is high. 90
232
Dimensions and Items for Pilot Study (continued) Item
#
Non-Monetary It takes minimal time to get the information I need about team name games. 17 It is easy to get the information I need about team name games. 47 It is easy to contact the team name when I need to. 59 I am able to get to stadium name quickly for team name games. 68 The athletics department makes it easy for me to get tickets to team name games. 87 Epistemic Value Knowledge Team name games allow me to increase my knowledge of sport. 18 Team name games enable me to increase my understanding of sport strategy. 31 Team name games allow me to learn about the technical aspects of sport. 46 Novelty Team name games provide me the opportunity to do something I haven’t done before. 67 I am interested in experiencing new things. 78 Team name games give the chance to experience something different. 89 Satisfaction Overall, I am very satisfied with the services that I receive from team name. 20 Overall, I am satisfied with my experience at team name games. 40 I truly enjoy myself at team name games. 70
233
APPENDIX E
Jacksonville Suns Questionnaire
234
Hello, We are Sports Marketing researchers from Florida State University. We are working in cooperation with the Jacksonville Suns to gain a better understanding of how fans evaluate their experiences at a Suns baseball game.
Please take a few minutes and complete our survey. Participation is voluntary, and all results are anonymous and confidential to the extent allowed by the law. The survey should take about ten minutes to complete.
If you agree to participate, please answer each question to the best of your knowledge. You do not have to respond to any questions with which you are not comfortable. Sincere and honest responses to questions are greatly appreciated. Completion of the questionnaire is implied consent to use the data you have provided.
You will be asked to evaluate the experience using a series of scales and then to provide some brief background information. For each question below, please select the answer that best reflects your opinion by circling the appropriate response.
You must be at least 18 years of age to participate. The data will be stored under lock and key on file on campus until one year after the study has been completed.
If you have any questions, please contact Daniel Sweeney at [email protected], Dr. Jeffrey James at [email protected], or The Florida State University IRB at 850.644.8633 located at the Office of Research, Innovation Park, 100 Sliger Building, Tallahassee, FL, 32306-2811.
Thank you in advance for your participation.
Sincerely,
Daniel Sweeney Florida State University
235
Please rate the extent to which you DISAGREE or AGREE with each of the following items by circling the appropriate number in the scale beside each statement.
Disagree
1. Interacting with other fans is a very important part of being at Suns’ games. 1 2 3 4 5 6 7
2. Overall, I truly enjoy the time I spend at Suns’ baseball games. 1 2 3 4 5 6 7
3. Watching Suns’ games is a very intense experience for me. 1 2 3 4 5 6 7
4. Suns’ games provide me with a distraction from my everyday activities. 1 2 3 4 5 6 7
5. I value the special events that are organized by the team. 1 2 3 4 5 6 7
6. The Jacksonville Suns know the type of experience its customers want. 1 2 3 4 5 6 7
7. I like Suns’ games because of the natural elegance of the game of baseball. 1 2 3 4 5 6 7
8. I enjoy spending time with my family at Suns’ games. 1 2 3 4 5 6 7
9. The event staff understands that I rely on their knowledge to meet my needs 1 2 3 4 5 6 7
10. The price of Suns’ games is high. 1 2 3 4 5 6 7
11. The special activities going on during the game are important to me. 1 2 3 4 5 6 7
12. I love the feeling of being surrounded by all of the fans. 1 2 3 4 5 6 7
13. I really get into the game when I watch Suns’ games. 1 2 3 4 5 6 7
14. I enjoy Suns’ games because they provide an opportunity to be with my friends 1 2 3 4 5 6 7
15. Suns’ games provide me an opportunity to party. 1 2 3 4 5 6 7
16. Suns’ games give me a great opportunity to socialize with other people. 1 2 3 4 5 6 7
17. It takes minimal time to get the information I need about Suns’ games. 1 2 3 4 5 6 7
18. Suns’ games allow me to increase my knowledge of baseball. 1 2 3 4 5 6 7
19. I can count on the event staff taking actions to address my needs. 1 2 3 4 5 6 7
20. Overall, I am very satisfied with the services I receive at Suns’ games. 1 2 3 4 5 6 7
21. Suns’ games provide me with a great opportunity to entertain my clients. 1 2 3 4 5 6 7
22. I like the uncertainty of a close game. 1 2 3 4 5 6 7
23. I concentrate very hard on the action on the field. 1 2 3 4 5 6 7
24. I like the gracefulness associated with the game of baseball. 1 2 3 4 5 6 7
25. The layout of the Baseball Grounds of Jacksonville never fails to impress me. 1 2 3 4 5 6 7
26. The other spectators do not affect the team’s ability to provide me with good service. 1 2 3 4 5 6 7
27. You can count on the Suns’ employees knowing their jobs. 1 2 3 4 5 6 7
28. The special activities going on before games are important to me. 1 2 3 4 5 6 7
29. Suns’ games give me a chance to bond with my family. 1 2 3 4 5 6 7
30. It just wouldn’t be a Suns’ game if I didn’t party. 1 2 3 4 5 6 7
31. Suns’ games enable me to increase my understanding of baseball strategy. 1 2 3 4 5 6 7
32. I believe that the Suns’ try to give me a good experience. 1 2 3 4 5 6 7
Agree
Neutral
236
Please rate the extent to which you DISAGREE or AGREE with each of the following items by circling the appropriate number in the scale beside each statement.
33. The Suns’ organization makes it easy for me to get tickets to Suns’ baseball games.
1 2 3 4 5 6 7
34. I am consistently pleased with the service at Suns’ games. 1 2 3 4 5 6 7
35. The price of Suns’ games is low. 1 2 3 4 5 6 7
36. The behavior of the event staff indicates to me that they understand my needs. 1 2 3 4 5 6 7
37. The staff tries to keep my waiting time for service to a minimum. 1 2 3 4 5 6 7
38. I like Suns’ games where the outcome is uncertain. 1 2 3 4 5 6 7
39. The attitude of the ballpark staff demonstrates their willingness to help me. 1 2 3 4 5 6 7
40. Overall, I am satisfied with my experience at Suns’ baseball games. 1 2 3 4 5 6 7
41. Suns’ games give me the chance to socialize with people from my work. 1 2 3 4 5 6 7
42. I like Suns’ baseball because they have the service that I want. 1 2 3 4 5 6 7
43. The action on the field is most important to me. 1 2 3 4 5 6 7
44. Suns’ games provide me with an escape from my daily life for a while. 1 2 3 4 5 6 7
45. I drink alcohol at the game, which is a big part of watching baseball games. 1 2 3 4 5 6 7
46. Suns’ games allow me to learn about the technical aspects of baseball. 1 2 3 4 5 6 7
47. It is easy to get the information I need about Suns’ games. 1 2 3 4 5 6 7
48. I enjoy Suns’ games because they are a good family activity. 1 2 3 4 5 6 7
49. The ballpark employees respond quickly to my needs. 1 2 3 4 5 6 7
50. The layout of the Baseball Grounds of Jacksonville serves my purposes. 1 2 3 4 5 6 7
51. Suns’ baseball games are expensive. 1 2 3 4 5 6 7
52. Partying at Suns’ games is more interesting than watching the games. 1 2 3 4 5 6 7
53. When I am at a game, nothing else matters but the game. 1 2 3 4 5 6 7
54. Having a chance to see friends is one thing I enjoy about Suns’ games. 1 2 3 4 5 6 7
55. The special promotions that are a part of Suns’ games are meaningful to me. 1 2 3 4 5 6 7
56. I like to talk to other people sitting near me during Suns’ games. 1 2 3 4 5 6 7
57. The ballpark staff is able to answer my questions quickly. 1 2 3 4 5 6 7
58. I prefer watching a close game rather than a one-sided game. 1 2 3 4 5 6 7
59. Suns’ games allow me to get away from the tension in my life. 1 2 3 4 5 6 7
60. I like that people can get a little drunk if they choose to at the Suns’ games. 1 2 3 4 5 6 7
61. Suns’ games give me the opportunity to entertain potential clients. 1 2 3 4 5 6 7
62. The ballpark staff understands that waiting time for service is important to me. 1 2 3 4 5 6 7
63. My focus is on the game, and not the other activities at the stadium. 1 2 3 4 5 6 7
64. The event staff knows the kind of service its customers are looking for. 1 2 3 4 5 6 7
65. Suns’ games are reasonably priced. 1 2 3 4 5 6 7
Neutral Agree
Disagree
237
Please rate the extent to which you DISAGREE or AGREE with each of the following items by circling the appropriate number in the scale beside each statement.
66. The baseball staff understands that the atmosphere is important to me. 1 2 3 4 5 6 7
67. The Suns understand that the design of their facility is important to me. 1 2 3 4 5 6 7
68. When I leave Suns’ games, I usually feel like I had a good experience. 1 2 3 4 5 6 7
69. The attitude of the ballpark employees shows me they understand my needs. 1 2 3 4 5 6 7
70. The Suns’ baseball experience enables people to drink heavily. 1 2 3 4 5 6 7
71. A close game involving the Suns is more enjoyable than a blowout. 1 2 3 4 5 6 7
72. I like the beauty and grace of sports. 1 2 3 4 5 6 7
73. The game is the most important thing at the stadium. 1 2 3 4 5 6 7
74. Being at Suns’ games gives me a chance to bond with my friends. 1 2 3 4 5 6 7
75. You can count on the ballpark employees to be friendly. 1 2 3 4 5 6 7
Please circle the number that best describes your behavior.
76. I buy Suns-related merchandise. 1 2 3 4 5 6 7
77. I use the Internet to get information about the Suns Baseball team. 1 2 3 4 5 6 7
78. I watch the Suns play baseball on television. 1 2 3 4 5 6 7
79. I read newspaper articles/editorials about the team. 1 2 3 4 5 6 7
80. Including this game, how many Suns games have you attended this season? ________________________
81. After this game, how many more Suns games do you think you will attend this season? _____________________
82. About how much money do you spend at a Suns Baseball game (excluding tickets)? $________________ per game
Please tell us a little about yourself by checking or writing the appropriate response to the items below.
Gender: ___ Female ___ Male
Marital Status: ___ Married ___ Single ___ Divorced ___ Widowed ____ Other
Ethnicity: ___ Black/African American (non-Hispanic) ___ Native American ___ Asian or Pacific Islander
___ White/Caucasian (non-Hispanic) ___ Latina/Latino ___ Other ______ ____________________
75
Highest level of education completed: ___ High School ___ Professional / Trade School ___ Junior College ___ Undergraduate Degree ___ Masters Degree ___ Doctorate Degree
Disagree
Neutral
Agree
Thank you for taking the time to complete this questionnaire!
Age: ________
Are you a Season Ticket Holder?
____ Yes ____ No
Neutral Disagree
Agree
238
APPENDIX F
Item Codes for Jacksonville Suns Questionnaire
239
Dimensions and Items for Main Study – Sample 1 Item
#
Entertainment Value
Amusement
I value the special events that are organized by the team. 5
The special activities going on before games are important to me. 28
The special promotions that are a part of the team name games are meaningful to me. 55
The special activities going on during the game are important to me. 11
Partying
It just wouldn't be a team name game if I didn't party 30
There is a party atmosphere at team name games. ---
Team name games provide me an opportunity to party. 15
I drink alcohol at the game, which is a big part of watching baseball games. 45
I like that people can get a little drunk if they choose to at team name games. 60
The team name baseball experience enables people to drink heavily. 70
Partying at team name games is more interesting than watching the games. 52
Experience Intensity
I love the feeling of being surrounded by all of the fans. 12
Watching team name games is a very intense experience for me 3
I really get into the game when I watch team name games. 13
Game Immersion
I concentrate very hard on the action on the field. 23
The action on the field is most important to me. 43
When I am at the game, nothing else matters but the game. 53
My focus is on the game, and not the other activities at the stadium. 63
The game is the most important thing at the stadium. 73
Escape
Team name games provide me with a distraction my everyday activities. 4
Team name games provide me with a distraction from my daily life for a while. 44
Team name games allow me to get away from the tension in my life. 59
Aesthetics
I like team name games because of the natural elegance of the game of sport. 7
I like the gracefulness associated with the game of sport. 24
I like the beauty and grace of sports. 72
240
Dimensions and Items for Main Study – Sample 1 (continued) Item
#
Drama
I like the uncertainty of a close game. 22
I like team name games where the outcome is uncertain. 38
A close game involving team name is more enjoyable than a blowout. 71
I prefer watching a close game rather than a one-sided game. 58
Social Value
Non Family
I enjoy spending time with my family at team name games. 8
I enjoy team name games because they are a good family activity. 48
Team name games give me a chance to bond with my family. 29
Team name games give me a great opportunity to socialize with other people. 16
I like to talk to other people sitting near me during team name games. 56
Interacting with other fans is a very important part of being at team name games. 1
Friends
I enjoy team name games because they provide an opportunity to be with my friends 14
Having a chance to see friends is one thing I enjoy about team name games. 54
Being at team name games gives me a chance to bond with my friends. 74
Business Opportunities
Team name games provide me with a great opportunity to entertain my clients. 21
Team name games give me a chance to socialize with people from my work. 41
Team name games give me the opportunity to entertain potential clients. 61
Perceived Price Monetary The price of team name team name games is low (reverse coded) 35 Team name games are expensive. 51 Team name games are reasonably priced. 65 The price of team name games is high. 10 Non-Monetary It takes minimal time to get the information I need about team name games. 17 It is easy to get the information I need about team name games. 47 The athletics department makes it easy for me to get tickets to team name games. 33
241
Dimensions and Items for Main Study – Sample 1 (continued) Item
#
Service Quality
Interaction Quality
You can count on the ballpark employees to be friendly. 75
The attitude of the ballpark staff demonstrates their willingness to help me. 39
The attitude of the ballpark employees shows me that they understand my needs. 69
I can count on the event staff taking actions to address my needs. 19
The ballpark employees respond quickly to my needs 49
The behavior of the event staff indicates to me that they understand my needs. 36
You can count on the ballpark employees knowing their jobs. 27
The ballpark staff is able to answer my questions quickly. 57
The event staff understands that I rely on their knowledge to meet my needs. 9
The baseball staff understands that the atmosphere is important to me. 66
The other spectators do not affect the staff’s ability to provide me with good service. 26
The staff tries to keep my waiting time for service to a minimum. 37
The ballpark staff understands that waiting time is important to me. 62
I am consistently pleased with the service at team name games. 34
I like team name sport because they have the service I want. 42
The event staff knows the kind of service its customers are looking for. 64
The event staff knows the type of experience its customers want. 6
Outcome Quality
The team name’s stadium/arena layout never fails to impress me. 25
The layout of stadium name serves my purposes. 50
The team name understands that the design of its facility is important to me. 67
When I leave team name games, I usually feel like I had a good experience. 68
I believe that team name tries to give me a good experience 32
Epistemic Value Knowledge Team name games allow me to increase my knowledge of sport. 18 Team name games enable me to increase my understanding of sport strategy. 31 Team name games allow me to learn about the technical aspects of sport. 46
Satisfaction
Overall, I am very satisfied with the services I receive at team name games. 20
Overall, I am satisfied with my experience at team name baseball games. 40
Overall, I truly enjoy the time I spend at team name baseball games. 2
242
APPENDIX G
Student Sample Questionnaire
- 243 -
Sport Consumer Survey
I am a Doctoral student in the Department of Sport Management, Recreation Management, and Physical Education at Florida State University. I am conducting a research study to gain a better understanding of how fans evaluate their experiences at sporting events.
Please take a few minutes and complete this survey. Participation is voluntary, and all results are anonymous and confidential to the extent allowed by the law. The survey should take about ten minutes to complete.
If you agree to participate, please answer each question to the best of your knowledge. You do not have to respond to any questions with which you are not comfortable. Sincere and honest responses to questions are greatly appreciated. Completion of the questionnaire is implied consent to use the data you have provided. You will be asked to evaluate your experiences using a series of scales and then to provide some brief background information. For each question below, please select the answer that best reflects your opinion by circling or writing the appropriate response in the space provided.
You must be at least 18 years of age to participate. The data will be stored under lock and key on file on campus until one year after the study has been completed.
If you have any questions, please contact Daniel Sweeney at [email protected], Dr. Jeffrey James at [email protected], or The Florida State University IRB at 850.644.8633 located at the Office of Research, Innovation Park, 100 Sliger Building, Tallahassee, FL, 32306-2811.
Thank you in advance for your participation. Sincerely, Daniel Sweeney Ph.D. Candidate
Please answer the following questions related to your consumption of sporting events. Question #1: What was the last professional or collegiate game you attended in person?
Take a moment and think about your experiences at the last college/professional sporting event you listed on the previous page.
Now, please rate the extent to which you DISAGREE or AGREE with each of the following statements as they relate to the sporting event you are thinking about by circling the appropriate number in the scale.
Disagree Agree
1. Interacting with other fans is a very important part of being at a game. 1 2 3 4 5 6 7
2. You can count on the venue employees to be friendly. 1 2 3 4 5 6 7
3. The staff understands that the atmosphere at a game is important to me. 1 2 3 4 5 6 7
4. The game provided me with a distraction from my everyday activities. 1 2 3 4 5 6 7
5. I value the special events that are organized by the team. 1 2 3 4 5 6 7
Disagree Agree
6. The team knows the type of experience its customers want. 1 2 3 4 5 6 7
7. I like a game because of the natural elegance in the game. 1 2 3 4 5 6 7
8. I enjoy spending time with my family at a game. 1 2 3 4 5 6 7
9. The event staff understands that I rely on their knowledge to meet my needs 1 2 3 4 5 6 7
10. When I left the game, I felt like I had a good experience. 1 2 3 4 5 6 7
Disagree Agree
11. The special activities going on during a game are important to me. 1 2 3 4 5 6 7
12. A close game is more enjoyable than a blowout. 1 2 3 4 5 6 7
13. The organization understands that the design of their facility is important to me. 1 2 3 4 5 6 7
14. I enjoy a game because it provides an opportunity to be with my friends 1 2 3 4 5 6 7
15. The game provided me an opportunity to party. 1 2 3 4 5 6 7
Disagree Agree
16. The game gave me a great opportunity to socialize with other people. 1 2 3 4 5 6 7
17. It takes minimal time to get the information I need about the games. 1 2 3 4 5 6 7
18. The game enabled me to increase my knowledge of the sport. 1 2 3 4 5 6 7
19. I can count on the venue staff taking actions to address my needs. 1 2 3 4 5 6 7
20. The attitude of the facility employees showed me they understood my needs. 1 2 3 4 5 6 7
Disagree Agree
21. The games provide me with a great opportunity to entertain my clients. 1 2 3 4 5 6 7
22. I like the uncertainty of a close game. 1 2 3 4 5 6 7
23. I concentrate very hard on the action on the field. 1 2 3 4 5 6 7
24. I like the gracefulness associated with the sport. 1 2 3 4 5 6 7
25. The layout of the venue never fails to impress me. 1 2 3 4 5 6 7
Disagree Agree 26. The other spectators do not affect the team’s ability to provide me with good
service. 1 2 3 4 5 6 7
27. You can count on the facility employees knowing their jobs. 1 2 3 4 5 6 7
28. The special activities going on before a game are important to me. 1 2 3 4 5 6 7
29. The game gave me a chance to bond with my family. 1 2 3 4 5 6 7
30. It just wouldn’t be a game if I didn’t party. 1 2 3 4 5 6 7
245
Thinking about your experiences at the game you identified, please rate the extent to which you DISAGREE or AGREE with each of the following statments as they relate to the sporting event you are thinking about by circling the appropriate number in the scale.
Disagree Agree
31. The game enabled me to increase my understanding of the strategy of the sport. 1 2 3 4 5 6 7
32. I believe that the organization tries to give me a good experience. 1 2 3 4 5 6 7
33. The organization makes it easy for me to get tickets to a game. 1 2 3 4 5 6 7
34. I am consistently pleased with the service at the games. 1 2 3 4 5 6 7
35. The price of the game was low. 1 2 3 4 5 6 7
Disagree Agree
36. The behavior of the event staff indicates to me that they understood my needs. 1 2 3 4 5 6 7
37. The facility staff tried to keep my waiting time for service to a minimum. 1 2 3 4 5 6 7
38. I like games where the outcome is uncertain. 1 2 3 4 5 6 7
39. The attitude of the venue staff demonstrates their willingness to help me. 1 2 3 4 5 6 7
40. Being at the game gave me a chance to bond with my friends. 1 2 3 4 5 6 7
Disagree Agree
41. The game gave me the chance to socialize with people from my work. 1 2 3 4 5 6 7
42. I like the beauty and grace of sports. 1 2 3 4 5 6 7
43. The action on the field is most important to me. 1 2 3 4 5 6 7
44. The game provided me with an escape from my daily life for a while. 1 2 3 4 5 6 7
45. I drank alcohol at the game, which is a big part of watching the games. 1 2 3 4 5 6 7
Disagree Agree
46. The game enabled me to learn about the technical aspects of the sport. 1 2 3 4 5 6 7
47. It is easy to get the information I need about a game. 1 2 3 4 5 6 7
48. I enjoy a game because it is a good family activity. 1 2 3 4 5 6 7
49. The venue employees responded quickly to my needs. 1 2 3 4 5 6 7
50. The layout of venue served my purposes. 1 2 3 4 5 6 7
Disagree Agree
51. A game is expensive. 1 2 3 4 5 6 7
52. Partying at a game is more interesting than watching a game. 1 2 3 4 5 6 7
53. When I am at a game, nothing else matters but the game. 1 2 3 4 5 6 7
54. Having a chance to see friends is one thing I enjoy about a game. 1 2 3 4 5 6 7
55. The special promotions that are a part of a game are meaningful to me. 1 2 3 4 5 6 7
Disagree Agree
56. I like to talk to other people sitting near me during a game. 1 2 3 4 5 6 7
57. The venue staff is able to answer my questions quickly. 1 2 3 4 5 6 7
58. The game was reasonably priced. 1 2 3 4 5 6 7
59. The game enabled me to get away from the tension in my life. 1 2 3 4 5 6 7
60. I like that people can get a little drunk if they choose to at a game. 1 2 3 4 5 6 7
246
Thinking about your experiences at the game you identified, please rate the extent to which you DISAGREE or AGREE with each of the following statments as they relate to the sporting event you are thinking about by circling the appropriate number in the scale.
Disagree Agree
61. The game gave me an opportunity to entertain potential clients. 1 2 3 4 5 6 7
62. The venue staff understood that waiting time for service is important to me. 1 2 3 4 5 6 7
63. My focus is on the game, and not the other activities at the stadium. 1 2 3 4 5 6 7
64. The event staff knows the kind of service its customers are looking for. 1 2 3 4 5 6 7
Please tell us a little about yourself by checking or writing the appropriate response: Gender: ___ Female ___ Male Age: ________ Ethnicity: ___ Black/African American ___ Native American ___ Asian or Pacific Islander
___ White/Caucasian ___ Latina/Latino ___ Other _______________
Thank you for taking the time to complete this questionnaire!
247
APPENDIX H
Student Sample Questionnaire Item Codes
248
Dimensions and Items for Main Study – Validation Sample Item
#
Entertainment Value
Amusement
I value the special events that are organized by the team. 5
The special activities going on before a game are important to me. 28
The special promotions that are a part of a game are meaningful to me. 55
The special activities going on during a game are important to me. 11
Partying
It just wouldn’t be a game if I didn’t party. 30
The game provided me an opportunity to party. 15
I drank alcohol at the game, which is a big part of watching the games. 45
I like that people can get a little drunk if they choose to at a game. 60
Partying at a game is more interesting than watching a game. 52
Game Immersion
I concentrate very hard on the action on the field. 23
The action on the field is most important to me. 43
When I am at a game, nothing else matters but the game. 53
My focus is on the game, and not the other activities at the stadium. 63
Escape
The game provided me with a distraction from my everyday activities. 4
The game provided me with an escape from my daily life for a while. 44
The game enabled me to get away from the tension in my life. 59
Aesthetics
I like a game because of the natural elegance in the game. 7
I like the gracefulness associated with the sport. 24
I like the beauty and grace of sports. 42
Drama
I like the uncertainty of a close game. 22
I like games where the outcome is uncertain. 38
A close game is more enjoyable than a blowout. 12
249
Dimensions and Items for Main Study – Validation Sample (continued) Item
#
Social Value
Family
I enjoy spending time with my family at a game. 8
I enjoy a game because it is a good family activity. 48
The game gave me a chance to bond with my family. 29
Non-Family
I enjoy a game because it provides an opportunity to be with my friends 14
Having a chance to see friends is one thing I enjoy about a game. 54
Being at the game gave me a chance to bond with my friends. 40
The game gave me a great opportunity to socialize with other people. 16
I like to talk to other people sitting near me during a game. 56
Interacting with other fans is a very important part of being at a game. 1
Business Opportunities
The games provide me with a great opportunity to entertain my clients. 21
The game gave me the chance to socialize with people from my work. 41
The game gave me an opportunity to entertain potential clients. 61
Service Quality
Interaction Quality
You can count on the venue employees to be friendly. 2
The attitude of the venue staff demonstrates their willingness to help me. 39
The attitude of the facility employees showed me they understood my needs. 20
I can count on the venue staff taking actions to address my needs. 19
The venue employees responded quickly to my needs. 49
The behavior of the event staff indicates to me that they understood my needs. 36
You can count on the facility employees knowing their jobs. 27
The venue staff is able to answer my questions quickly. 57
The event staff understands that I rely on their knowledge to meet my needs. 9
The staff understands that the atmosphere at a game is important to me. 3
The other spectators do not affect the team’s ability to provide me with good service. 26
The facility staff tried to keep my waiting time for service to a minimum. 37
The venue staff understood that waiting time for service is important to me. 62
I am consistently pleased with the service at the games. 34
The event staff knows the kind of service its customers are looking for. 64
The team knows the type of experience its customers want. 6
250
Dimensions and Items for Main Study – Validation Sample (continued) Item
#
Outcome Quality
The layout of the venue never fails to impress me. 25
The layout of venue served my purposes. 50
The organization understands that the design of their facility is important to me. 13
When I left the game, I felt like I had a good experience. 10
I believe that the organization tries to give me a good experience. 32
Perceived Price
Monetary
The price of the game was low. 35
A game is expensive. 51
The game was reasonably priced. 58
Non-Monetary
It takes minimal time to get the information I need about the games. 17
It is easy to get the information I need about a game. 47
The organization makes it easy for me to get tickets to a game. 33
Epistemic Value
The game enabled me to increase my knowledge of the sport. 18
The game enabled me to increase my understanding of the strategy of the sport. 31
The game enabled me to learn about the technical aspects of the sport. 46
251
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BIOGRAPHICAL SKETCH
Name: Daniel Robert Sweeney Place of Birth: Montréal, Québec, Canada Date of Birth: June 25, 1975 Education: Wagar High School, 1992 Côte-St-Luc, Québec, Canada Diplôme D’Études Collégiales, 1994 Dawson College Montréal, Québec, Canada Bachelor of Education – Kinesiology, 1999 McGill University Montréal, Québec, Canada Master of Human Kinetics – Sport Management, 2003 University of Windsor Windsor, Ontario, Canada PhD – Sport Management, 2008 The Florida State University Tallahassee, Florida, USA Personal: Dan is married to Jamie Michelle Sweeney (nee Metz) of St. Louis,
Missouri. The two met in 2002 while they were both living in the Washington, D.C. area. They were married on June 24, 2006 in New Orleans, Louisiana – one of their favorite cities.
Employment: Dan is currently employed as an Assistant Professor of Sport
Management at the University of Arkansas at Little Rock.