Directions Week 2 AssignmentAfter doing some research on the C.docx

Directions: Week 2 Assignment:
After doing some research on the Carolina League, create a
PowerPoint presentation to the City Council of Charles Town
which specifically and thoroughly addresses the following
components:
· Overview of the Carolina League. This includes current
teams/cities/MLB affiliations, staff needed (list all positions
from the top to the bottom of the organization, coaches (list all
coaching positions needed for this new organization), and
facilities (list and explain what type of facilities will be
needed).
· Historical perspective of the Carolina League.
· Explanation of how a team in Charles Town, WV would
benefit the Carolina League and the city of Charles Town.
· Organizational goals of the Charles Town expansion team.
· Please create a mission statement and list the core values of
the Charles Town expansion team.
· Community relations and outreach opportunities for the team.
· SWOT analysis of having a minor League baseball team in
Charles Town.
· Proposed timeline for implementation, with specific details
either by month, or by quarter, based on the length of time
recommended.
Please create a PowerPoint presentation covering the areas
listed above for presentation to the City Council of Charles
Town, WV. Please be sure to review the "PowerPoint
Presentation Do's and Don’ts" document that’s attached.
Remember, the PowerPoint must be in bullet format and must
include a notes section. The notes section should be a summary
of the bullet points in your presentation, such that if you were
unable to make the presentation, someone else could make the
presentation for you by reading what you’ve written in the notes
section.
Remember, you will be handing this to the president and board

of trustees for review. Be sure to carefully proof your work, and
follow APA format throughout. Please include a title slide that
includes your name and the assignment topic, as well as a
reference slide at the end of your PowerPoint presentation
which includes a minimum of three (3) scholarly sources. Don't
forget that every source should be correctly cited throughout
your presentation on the appropriate slide.
Length of this section of your marketing plan: This assignment
should be approximately 10-12 PowerPoint Slides (not
including title page and references).
Johns Hopkins Nursing Evidence-Based Practice
Appendix E
Research Evidence Appraisal Tool
Evidence level and quality rating:
Article title:
Number:
Author(s):
Publication date:
Journal:
Setting:
Sample (composition and size):
Does this evidence address my EBP question?
Yes
No-Do not proceed with appraisal of this evidence
Is this study:
QuaNtitative (collection, analysis, and reporting of numerical
data)
Measurable data (how many; how much; or how often) used to
formulate facts, uncover patterns in research, and generalize

results from a larger sample population; provides observed
effects of a program, problem, or condition, measured precisely,
rather than through researcher interpretation of data. Common
methods are surveys, face-to-face structured interviews,
observations, and reviews of records or documents. Statistical
tests are used in data analysis.
Go to Section I: QuaNtitative
QuaLitative (collection, analysis, and reporting of narrative
data)
Rich narrative documents are used for uncovering themes;
describes a problem or condition from the point of view of those
experiencing it. Common methods are focus groups, individual
interviews (unstructured or semi structured), and
participation/observations. Sample sizes are small and are
determined when data saturation is achieved. Data saturation is
reached when the researcher identifies that no new themes
emerge and redundancy is occurring. Synthesis is used in data
analysis. Often a starting point for studies when little research
exists; may use results to design empirical studies. The
researcher describes, analyzes, and interprets reports,
descriptions, and observations from participants.
Go to Section II: QuaLitative
Mixed methods (results reported both numerically and
narratively)
Both quaNtitative and quaLitative methods are used in the study
design. Using both approaches, in combination, provides a
better understanding of research problems than using either
approach alone. Sample sizes vary based on methods used. Data
collection involves collecting and analyzing both quaNtitative
and quaLitative data in a single study or series of studies.
Interpretation is continual and can influence stages in the
research process.
Go to Section III: Mixed Methods
Appendix E

Page 6 of 10
Appendix E
The Johns Hopkins Hospital/ The Johns Hopkins University
5
Section I: QuaNtitative
Level of Evidence (Study Design)
Is this a report of a single research study?
A
· Yes
· No
Go to B
1. Was there manipulation of an independent variable?
· Yes
· No
2. Was there a control group?
· Yes
· No
3. Were study participants randomly assigned to the
intervention and control groups?
· Yes
· No
If Yes to questions 1, 2, and 3, this is a randomized controlled
trial (RCT) or experimental study.
LEVEL I
If Yes to questions 1 and 2 and No to question 3orYes to

question 1 and No to questions 2 and 3, this is quasi-
experimental.
(Some degree of investigator control, some manipulation of an
independent variable, lacks random assignment to groups, and
may have a control group).
LEVEL II
If No to questions 1, 2, and 3, this is nonexperimental.
(No manipulation of independent variable; can be descriptive,
comparative, or correlational; often uses secondary data).
LEVEL III
Study Findings That Help Answer the EBP Question
Skip to the Appraisal of QuaNtitative Research Studies section
Section I: QuaNtitative (continued)
Is this a summary of multiple sources of research evidence?
· Yes
Continue
· No
Use Appendix F
1. Does it employ a comprehensive search strategy and rigorous
appraisal method?
If this study includes research, nonresearch, and experiential
evidence, it is an integrative review (see Appendix F).
· Yes
Continue
· No
Use Appendix F
2. For systematic reviews and systematic reviews with meta-
analysis
(see descriptions below):
B
a. Are all studies included RCTs?
LEVEL I
b. Are the studies a combination of RCTs and quasi-
experimental, or quasi-experimental only?

LEVEL II
c. Are the studies a combination of RCTs, quasi-experimental,
and nonexperimental, or nonexperimental only?
LEVEL III
A systematic review employs a search strategy and a rigorous
appraisal method, but does not generate an effect size.
A meta-analysis, or systematic review with meta-analysis,
combines and analyzes results from studies to generate a new
statistic: the effect size.
Skip to the Appraisal of Systematic Review (With or Without a
Meta-Analysis) section
Appraisal of QuaNtitative Research Studies
Does the researcher identify what is known and not known
about the problem and how the study will address any gaps in
knowledge?
· Yes
· No
Was the purpose of the study clearly presented?
· Yes
· No
Was the literature review current (most sources within the past
five years or a seminal study)?
· Yes
· No
Was sample size sufficient based on study design and rationale?
· Yes
· No
If there is a control group:
· Were the characteristics and/or demographics similar in both
the control and intervention groups?

· Yes
· No
N/A
· If multiple settings were used, were the settings similar?
· Yes
· No
N/A
· Were all groups equally treated except for the intervention
group(s)?
· Yes
· No
N/A
Are data collection methods described clearly?
· Yes
· No
· Yes
· No
N/A
Was instrument validity discussed?
· Yes
· No
N/A
If surveys or questionnaires were used, was the response
rate > 25%?
· Yes
· No
N/A
Were the results presented clearly?
· Yes
· No
If tables were presented, was the narrative consistent with the
table content?

· Yes
· No
N/A
Were study limitations identified and addressed?
· Yes
· No
Were conclusions based on results?
· Yes
· No
Complete theQuality Rating for QuaNtitative Studiessection
Appraisal of Systematic Review (With or Without Meta-
Analysis)
Were the variables of interest clearly identified?
· Yes
· No
Was the search comprehensive and reproducible?
· Key search terms stated
· Yes
· No
· Multiple databases searched and identified
· Yes
· No
· Inclusion and exclusion criteria stated
· Yes
· No
Was there a flow diagram that included the number of studies
eliminated at each level of review?
· Yes
· No
Were details of included studies presented (design, sample,
methods, results, outcomes, strengths, and limitations)?
· Yes
· No

Were methods for appraising the strength of evidence (level and
quality) described?
· Yes
· No
Were conclusions based on results?
· Yes
· No
· Results were interpreted
· Yes
· No
· Conclusions flowed logically from the interpretation and
systematic review question
· Yes
· No
Did the systematic review include a section addressing
limitations andhow they were addressed?
· Yes
· No
Complete theQuality Rating for QuaNtitative Studies section
(below)
Quality Rating for QuaNtitative Studies
Circle the appropriate quality rating below:
A High quality: Consistent, generalizable results; sufficient
sample size for the study design; adequate control; definitive
conclusions; consistent recommendations based on
comprehensive literature review that includes thorough
reference to scientific evidence.
B Good quality: Reasonably consistent results; sufficient
sample size for the study design; some control, and fairly
definitive conclusions; reasonably consistent recommendations
based on fairly comprehensive literature review that includes
some reference to scientific evidence.
C Low quality or major flaws: Little evidence with inconsistent
results; insufficient sample size for the study design;
conclusions cannot be drawn.

Appendix E
Section II: QuaLitative
A
Is this a report of a single research study?
· Yes
this is
Level III
· No
go to II B
Complete theAppraisal of Single QuaLitative Research
Studysection(below)
Appraisal of a Single QuaLitative Research Study
Was there a clearly identifiable and articulated:
· Purpose?
· Yes
· No
· Research question?
· Yes
· No
· Justification for method(s) used?
· Yes
· No
· Phenomenon that is the focus of the research?
· Yes

· No
Were study sample participants representative?
· Yes
· No
Did they have knowledge of or experience with the research
area?
· Yes
· No
Were participant characteristics described?
· Yes
· No
Was sampling adequate, as evidenced by achieving saturation of
data?
· Yes
· No
Data analysis:
· Was a verification process used in every step by checking and
confirming with participants the trustworthiness of analysis and
interpretation?
· Yes
· No
· Was there a description of how data were analyzed (i.e.,
method), by computer or manually?
· Yes
· No
Do findings support the narrative data (quotes)?
· Yes
· No
Do findings flow from research question to data collected to
analysis undertaken?
· Yes
· No
Are conclusions clearly explained?
· Yes

· No
Skip to theQuality Rating for QuaLitative Studiessection
For summaries of multiple quaLitative research studies (meta-
synthesis), was a comprehensive search strategy and rigorous
appraisal method used?
B
· Yes
Level III
· No
go to Appendix F
Complete the Appraisal of Meta-Synthesis Studies section
(below)
Appraisal of Meta-Synthesis Studies
Were the search strategy and criteria for selecting primary
studies clearly defined?
· Yes
· No
Were findings appropriate and convincing?
· Yes
· No
Was a description of methods used to:
· Compare findings from each study?
· Yes
· No
· Interpret data?
· Yes
· No
Did synthesis reflect:
· Yes
· No

· New insights?
· Yes
· No
· Discovery of essential features of phenomena?
· Yes
· No
· A fuller understanding of the phenomena?
· Yes
· No
Was sufficient data presented to support the interpretations?
· Yes
· No
Complete the Quality Rating for QuaLititative Studies section
(below)
Quality Rating for QuaLitative Studies
Circle the appropriate quality rating below:
No commonly agreed-on principles exist for judging the quality
of quaLitative studies. It is a subjective process based on the
extent to which study data contributes to synthesis and how
much information is known about the researchers’ efforts to
meet the appraisal criteria.
For meta-synthesis, there is preliminary agreement that quality
assessments should be made before synthesis to screen out poor-
quality studies1.
A/B High/Good quality is used for single studies and meta-
syntheses2.
The report discusses efforts to enhance or evaluate the quality
of the data and the overall inquiry in sufficient detail; and it
describes the specific techniques used to enhance the quality of
the inquiry.
Evidence of some or all of the following is found in the report:
· Transparency: Describes how information was documented to
justify decisions, how data were reviewed by others, and how

themes and categories were formulated.
· Diligence: Reads and rereads data to check interpretations;
seeks opportunity to find multiple sources to corroborate
evidence.
· Verification: The process of checking, confirming, and
ensuring methodologic coherence.
· Self-reflection and self-scrutiny: Being continuously aware of
how a researcher’s experiences, background, or prejudices
might shape and bias analysis and interpretations.
· Participant-driven inquiry: Participants shape the scope and
breadth of questions; analysis and interpretation give voice to
those who participated.
· Insightful interpretation: Data and knowledge are linked in
meaningful ways to relevant literature.
CLower-quality studies contribute little to the overall review of
findings and have few, if any, of the features listed for
High/Good quality.
1
https://www.york.ac.uk/crd/SysRev/!SSL!/WebHelp/6_4_ASSE
SSMENT_OF_QUALITATIVE_RESEARCH.htm
2 Adapted from Polit & Beck (2017).
Section III: Mixed Methods

You will need to appraise both the quaNtitative and quaLitative
parts of the study independently, before appraising the study in
its entirety.
1. Evaluate the quaNitative part of the study using Section I.
Level
Quality
Insert here the level of evidence and overall quality for this
part:
2. Evaluate the quaLitative part of the study using Section II.
Level
Quality
Insert here the level of evidence and overall quality for this
part:
3. To determine the level of evidence, circle the appropriate
study design:
· Explanatory sequential designs collect quaNtitative data first,
followed by the quaLitative data; and their purpose is to explain
quaNtitative results using quaLitative findings. The level is
determined based on the level of the quaNtitative part.
· Exploratory sequential designs collect quaLitative data first,
followed by the quaNtitative data; and their purpose is to
explain quaLitative findings using the quaNtitative results. The
level is determined based on the level of the quaLitative part,
and it is always Level III.
· Convergent parallel designs collect the quaLitative and
quaNtitative data concurrently for the purpose of providing a
more complete understanding of a phenomenon by merging both
datasets. These designs are Level III.
· Multiphasic designs collect quaLitative and quaNtitative data
over more than one phase, with each phase informing the next
phase. These designs are Level III.

Complete the Appraisal of Mixed Methods Studies section
(below)
Appraisal of Mixed Methods Studies3
Was the mixed-methods research design relevant to address the
quaNtitative and quaLitative research questions (or objectives)?
· Yes
· No
· N/A
Was the research design relevant to address the quaNtitative and
quaLitative aspects of the mixed-methods question (or
objective)?
· Yes
· No
· N/A
For convergent parallel designs, was the integration of
quaNtitative and quaLitative data (or results) relevant to
address the research question or objective?
· Yes
· No
· N/A
For convergent parallel designs, were the limitations associated
with the integration (for example, the divergence of quaLitative
and quaNtitative data or results) sufficiently addressed?
· Yes
· No
· N/A
Complete the Quality Rating for Mixed-Method Studies section
(below)
3 National Collaborating Centre for Methods and Tools. (2015).
Appraising Qualitative, Quantitative, and Mixed Methods
Studies included in Mixed Studies Reviews: The MMAT.

Hamilton, ON: McMaster University. (Updated 20 July, 2015)
Retrieved from http://www.nccmt.ca/ resources/search/232
Quality Rating for Mixed-Methods Studies
Circle the appropriate quality rating below
A High quality: Contains high-quality quaNtitative and
quaLitative study components; highly relevant study design;
relevant integration of data or results; and careful consideration
of the limitations of the chosen approach.
B Good quality: Contains good-quality quaNtitative and
quaLitative study components; relevant study design;
moderately relevant integration of data or results; and some
discussion of limitations of integration.
C Low quality or major flaws: Contains low quality
quaNtitative and quaLitative study components; study design
not relevant to research questions or objectives; poorly
integrated data or results; and no consideration of limits of
integration.
Requirements
Description of the Assignment
The critique will involve writing a two-page analysis of an
article as well as completing the Johns Hopkins Research
Appraisal Tool that is applicable to the article (qualitative).
You will critique a qualitative research article.
Criteria for Content
1. Introduction: Provide introduction to article topic/focus,
authors and specific aim of assignment.
2. Critique of Article (Body):
a. Identify the type of qualitative method of the study.
b. Content of critique should include at a minimum:
i. participant sampling,
ii. questionnaires/tools,

iii. ethics,
iv. analysis of findings,
v. limitations,
vi. discussion section,
vii. Summary: Application (translation) to practice specialty,
and future implications.
c. Refer to and complete the Johns Hopkins Research Appraisal
Tool.
Article Review Steps
Step 1: Select a qualitative research article on your topic of
interest published within the last three (3) years.
Step 2: Write a two-page critique of the article in a Word Doc
supported by course readings.
Step 3: Complete the Johns Hopkins Quantitative Research
Appraisal Tool. No credit for partially completed sections of
The Appraisal Tool.
Preparing the Assignment:
1. APA Format according to current edition.
2. Word Doc
3. Word Doc Format:
Cover page, no abstract, introduction (no heading per APA),
body of the paper/review, reference list, appendix with Johns
Hopkins appraisal doc. For review sections refer to your
readings and the Johns Hopkins Research Appraisal Tool.
List should include the chosen article and other resources used
to construct the review, such as Johns Hopkins Evidence Based
Practice: Model and Guidelines, and How to Read a Paper by
Greenhalgh (2014).
Rubric
Criteria
Ratings
Pts
This criterion is linked to a Learning OutcomeIntroduction
Required content for this section includes:

• Introduction to chosen article
• Succinct overview of assignment focus.
10.0 pts
Excellent
Content includes well-written, succinct, information that
includes: Article topic/focus, authors and specific aim of
assignment.
9.0 pts
V. Good
Content is well-written but omits or is thin in one area.
8.0 pts
Satisfactory
Section content is basic in its explanation of the article
(overview) and the purpose of the assignment but lacks specific
detail and depth.
5.0 pts
Needs Improvement
All content is included but difficult to piece together in its
explanation of the article (overview) and the purpose of the
assignment OR a piece of the content is missing, for example,
overview of assignment focus, yet what is written is well stated.
0.0 pts
Unsatisfactory
Missing OR Section content is vague in its introduction of the
article (overview) and the purpose of the assignment is missing
OR article overview is missing, and purpose of the assignment
is vague.)
10.0 pts
This criterion is linked to a Learning OutcomeCritique of
Article
Required content for this section includes:
• Methodological review specific to type (non-research versus
research): (use text and resources)
• Ethical review (not always present with guidelines or
systematic reviews)

• Analysis of findings
• Limitations
• Discussion
• Application to practice (translation)
• Future implications
50.0 pts
Excellent
All content is included in the critique with comprehensive
definitions, examples and with in-text citations that support the
article evaluation with depth.
46.0 pts
V. Good
All content is included in the critique. One or two sections may
be included without depth: For example, Definitions, examples
and with in-text citations that support the article evaluation
with depth. Or: All content has explanatory depth of analysis
including definitions, examples and in-text citations supporting
the analysis, however, a content area may be missing (such as
ethical review or limitations)
42.0 pts
Satisfactory
Two or three content areas are missing, or all content areas are
included but there is inconsistent depth/ integration of
definitions, examples and in-text citations that support the
article evaluation with depth
25.0 pts
Needs Improvement
Four or more content areas are missing, or all content areas are
included but there is little to no depth/ integration of
definitions, examples and in-text citations that support the
article evaluation with depth.
0.0 pts
Unsatisfactory
Critique is vague, without structure, without discernible
integration of definitions, examples, and in-text citations that
support the writing.

50.0 pts
This criterion is linked to a Learning OutcomeJohns Hopkins
Appraisal Tool
50.0 pts
Excellent
All sections of the Appraisal Tool are completed for the correct
article review (for example, the non-research tool is used for
guidelines, the qualitative tool is used for qualitative review).
46.0 pts
V. Good
Tool is included, is the correct tool, and is missing: A. Non-
Evidence Tool: 1 of the 6 sections B. Evidence Tool: 1 section
missing
42.0 pts
Satisfactory
Tool is included, is the correct tool, and is missing: A. Non-
Evidence Tool 2 or 3 of the 6 sections B. Evidence Tool: 2
sections missing
25.0 pts
Needs Improvement
Tool is included and is missing: A. Non-Evidence Tool 4 or
more of the 6 sections B. Evidence Tool – 3 more sections
missing.
0.0 pts
Unsatisfactory
Tool is missing or the wrong tool is used.
50.0 pts
This criterion is linked to a Learning OutcomeOrganization &
Format
Requirements:
• Cover (title) page
• No abstract
• Introduction
• Body of paper and reference page must follow APA guidelines

as found in the current edition of the manual. This includes the
use of headings for each section of the paper except for the
introduction where no heading is used.
15.0 pts
Excellent
All aspects of paper follow APA guidelines (cover, no abstract,
introduction, headings (not on introduction), body of paper and
reference page
14.0 pts
V. Good
1-3 APA errors
12.0 pts
Satisfactory
4-5 APA errors
8.0 pts
Needs Improvement
6-9 APA errors
0.0 pts
Unsatisfactory
10 or greater APA errors
15.0 pts
Segmentation in Sports - Analyzing the Behavior
of the Sport's Consumer
Mihaela Constantinescu
Bucharest University of Economic Studies, Marketing Faculty
Abstract: Sport is a multifarious domain that can range from
100% involvement as a player to buying
sports equipment for everyday life activities, therefore the
sport's consumer can have an active involvement

(practicing a sport) or a passive one (taking part in sports as a
spectator or watching sport on TV), fact
that brings the necessity of a segmentation process in order to
better target the individual with the right
marketing tools. This paper presents the results of a marketing
research on the Romanian market that
analyses the behavior of the spbrt's consumer, his involvement
in the sports industry and the way sports
influences his life decisions.
Keywords: sports marketing, sport consumer, sport events,
segmentation
1. Introduction
Sport is a multifarious do-
main that can range from 100%
involvement as a player to buy-
ing sports equipment for every-
day life activities, therefore the
sport's consumer can have an
active involvement (praetieing
a sport) or a passive one (taking
part in sports as a speetator or
watehing sport on TV), faet that
brings the neeessity of a seg-
mentation proeess in order to
better target the individual with
the right marketing tools
To highlight the importance
of eonsumer behavior analysis,
espeeially for the marketing
strategy, it is sufficient to pres-
ent the reasons identified by Ch.
Miehon (2010), depending on

the time period eovered: short
term (to explain the behavior
and eonsumer attitudes towards
a produet or brand), long term
(to identify trends, design new
produets and to find suitable
message to target the audienee).
Before taking any deeision
about the market or consumers,
marketers must get familiar
with their needs and expecta-
tions, and how the individual re-
acts to various external stimuli,
as well as the process of reaching
a deeision on aetion taken and
purchase made, whether ratio-
nal or emotional.
In the process of buying and
eonsumption, the individual
may have multiple roles, all
equally important for market-
ers, in their attempt to make the
offer more attractive, the ulti-
mate goal being the purehase of
products offered. In some cases,
these roles are overlapping for
the same person, but usually
the marketing strategy must
take into account several target
audiences, all with influential
role in the purehase decision.
Once we have identified

the categories of population
with impact on consumer be-
havior, we carr~give a defini-
tion of the concept. According
_to the authors I. Cätoiu and N.
Teodorescu (1997), consumer
behavior is represented by all
acts, attitudes and decisions on
the use of his revenues for pur-
chases of goods, services and
for savings. M.Solomon (2005)
defines eonsumer behavior as
represented by the proeesses
involved in the seleetion, pur-
chase, use or abandonment of
goods, services, ideas or experi-
enees by individuals or groups
to satisfy their needs or wants.
The definition emphasizes that
consumer behavior should be
seen as a eontinuous proeess,
not limited to speeifie time ex-
change that takes place between
the customer and manufacturer.
Starting from these general
definitions given to eonsumer
behavior, we ean define sports
consumer as that person or enti-
ty that benefits from the offer of
produets and serviees from the
sports market, as a praetitioner,
spectator, viewer or sponsor.

2. Segmentation of the
sports market
Segmentation is a phase in
the marketing management
proeess (KotlerV 2008) and it re-
fers to dividing the market and
identifjang eonsumei^-segment&-
with similar behavior or needs.
On the sports market, the
segmentation proeess is based
on a series of soeio-demograph-
ic and behavioral criteria with
high relevance for the offer of
sports produet and services.
There is no universally accepted
opinion regarding the identifica-
tion of these criteria, primarily
due to the diversity that charac-
terizes the sport domain and the
38
motives for which an individual
or organization is involving it-
self in sports.
In his book "Sports Marketing.
A Strategic Perspective ", M.D.
Shank (2005) identifies the fol-
lowing categories of criteria for
segmentation: demographic

(gender, age, ethnicity or fam-
ily life cycle), socioeconomic
(income, education, occupa-
tion), psychographics (lifestyle,
personality, interests and opin-
ions), geographical (continent
and country of origin, city of
residence, chmate), behavioral
(purchase frequency, size pur-
chase loyalty) and criteria relat-
ed to the expected benefit (con-
sumer needs, desired features of
sports products or services).
Thierry Lardinoit and
Emmanuelle Le Nagard-Assayag
(2004) have developed a segmen-
tation according to the sport's
values, with emphasis on moder-
nity and creativity.
Tapp and Glowes (2002) pro-
pose two major criteria for this
process: the expected benefits
by the client (victory vs. enter-
tainment) and its hehavioral
commitment.
As can be seen, the authors
mentioned above only apply
market segmentation within the
business to consumer (B2C) sec-
tor, forgetting a very important
sports market segment - the or-
ganizations. Thus, the segmen-
tation process should start with

the legal status of the consum-
er, leading to the identification
of two categories: individual
consumers and organizational
consumers (Constantinescu,
2009). The second category of
consumers is mainly represent-
ed through sponsorships, but
there are situations where the
demand for products and ser-
vices is based on the sport needs
of an organization (such as the
need to organize sports competi-
tions between employees or the
need for easier access to services
offered by a gym for employees).
The segmentation process
deepens within the first catego-
ry - individual consumers, which
can be categorized in three cat-
egories according to the way
they are involving themselves
in sports: practitioner, spectator
and viewer.
Another criterion for seg-
mentation is based on reasons
that determine the sport behav-
ior of an individual, identify-
ing the following categories: 1)
those who like moving, not hav-
ing a favorite sport; 2) those who
are fans of a particular sport; 3)
those who are fans of a team; 4)

those who are fans of a athlete.
One can ohserve a relation of in-
clusion between these four cat-
egories. Thus, those who admire
a particular athlete automati-
cally hecome fans of the team for
which that athlete is playing,
also developing a special attach-
ment to the sport in which acti-
vates the respective team. And
those who develop a sense of ad-
miration for a sports team have
an inclination towards sports
and movement.
The literature provides many
methods of segmentation, but
their generality leads to a de-
crease in the degree of applica-
bihty in the market, if they are
not linked to a series of direct
researches through which the
particularities of the sport con-
sumer behavior can be identified
for each country or region. This
paper highlights" the results^
of such a research, conducted
within the urban population of
Romania.
3. Research methodology
To collect the necessary in-
formation, a nationwide survey
has been organized which aimed
to analyze the sport consumer

behavior, detailed in the follow-
ing objectives:
a) The percentage of popula-
tion that practices sport;
h) What sports are practiced;
c) The percentage of popula-
tion that are participating
in sports events as specta-
tors;
d) What type of sports events
are they participating in;
e) The percentage of popula-
tion that watches sports
events on TV;
f) What type of sports events
are they watching.
The survey was conducted on
a sample of 385 people, within
the Romanian urban popula-
tion, the probability of guaran-
teeing the research results is
95% (for which the t coefficient
is 1.96), with a margin of error
of ± 5%. The sampling process
used a stratified method, tak-
ing into account gender, age and
income criteria that ensured a
sample structure corresponding
to the Romanian population.

4. Research results
In order to highlight the par-
ticularities of the sports mar-
ket segmentation process in
Romania, research results will
be presented both in a univari-
ate analysis and bivariatej3ne__
for each research objective.
4.1. The percentage of
population that practices
sport
While in Europe the percent-
_age of those who practice sport
is 2/3, the results of the present
study show a share of only 41.7%
for Romania, which explains to
some extent the social problems
that our country is fighting -
physical inactivity and ohesity.
But this lack of sport in
Romania should not be gener-
alized, given that the decision
to practice sport is infiuenced
hy a number of socio-demo-
graphic characteristics, leading
to differences between certain
RRM-4/2013
39

segments of the population. For
example, the proportion of men
who play sports is 47.8%, while
for women is only 34%. The dif-
ferences are more visible in re-
gard to age categories, as can
be seen from Figure 1, where
the variation is from 64.8% for
those aged between 18 and 25
years to 12.3% for those over
55. Although it seems large, the
percentage recorded for young
people should not surprise us,
actually we expect it to be high-
er, given that they are in that
period of their life when sport
is part of the school curriculum.
Unfortunately, more and more
young people opt for exemp-
tion from these activities within
the education system, which
can only lead to a worsening of
the social problems mentioned
above (physical inactivity and
obesity), along with social inte-
gration and education problems.
The education level also has
a major influence on the deci-
sion to carry out sports activi-
ties, higher education leading
to greater number for those
practicing sports (from 11.1%
for those who have just gradu-

ated from middle school up to
61.5% for postgraduates).
4.2. Types of sports practiced
by Romanian population
As can be seen from Table 1,
the most commonly practiced
sport in Romania is football
(46.4% of respondents mention-
ing it). Somewhat odd is posi-
tioning tennis second, but the
explanation may be related to
the period of data collection -
summer, when the number of
places to practice this sport is
much higher. In the next two
places we find a category of
sports that are related to the
individual needs of body main-
tenance (aerobics, fitness, body-
building - 28.6% and running,
jogging - 23.6%). A sport that is
gaining more and more follow-
ers is basketball, and principal-
ly because of street competitions
for amateur players in formula
3 on 3 (a variant of the classic
sport that FIBA wishes to pro-
pose even as an Olympic sport).
Tahle 1. Types of sports
practiced hy Romanian
population (%)

Sport
soccer
tennis
aerobic, fitness,
bodybuilding
running, jogging
swimming
basketball
volleyball
table tennis
others
Percentage
46,4
37,9
28,6
23,6
22,1
21,4
20,0
17,1
41,4
The choice of sport is influ-
enced by a number of socio-de-
mographic characteristics of the
individual or the family they
come from, among which the
most important are gender, age
and level of education.

The correlation with gender
highlights major differences be-
tween men and women, the most
practiced sports by men being
football (70.6%), tennis (43.5%),
basketball (28.2%), swimming
(21.2 %) and table tennis (21.2%),
while women most often sports
practice body care sports, such as
100%
90%
80%
70%
60%
50%
40%
30%
: 20%
i 10%
I 0%
Figure 1. Percentage of population that practices sports,
hased on the age categories (%)
35,2%

18-25
years
26-35
years
36-45
years
46-55
years
Over 55
years
Total
Practicing sports a Not practicing sports
40
aerobics, fitness or bodybuilding
(52.8%), running/jogging (34%),
followed by tennis (28.3%), vol-
leyball (28.3%) and swimming
(22.6%).
The sports market segmenta-
tion process must take into ac-
count the age of practitioners,
given that bivariate analysis
between these two variables

showed that young (18-35 years
old) choose team sports, through
which they satisfy the need for so-
cialization, as well as the compet-
itive one (most frequently men-
tioned sports being football and
basketball), while adults (36-55
years) and elderly (over 55 years)
are oriented towards body care
sports, such as running or fitness.
Regardless of education level,
soccer remains first in the prefer-
ences of individuals, but decreas-
es as a percentage from 52.9% for
those with secondary education
to 29.2% for those with graduate
studies. The influence of educa-
tion level is felt when choosing
body care sports (aérobies, fit-
ness, jogging), whieh is much
more present in the lives of those
with higher education.
The choice of football as
the most practiced sport by
Romanian is not influenced ei-
ther by income. The difference
between income categories are
although accounted for sports
that require investment such
as fitness, aerobics and tennis,
which are more often practiced
by those with high incomes (over
2000 RON / month). This finan-
cial barrier can~ be overcome

through public policies that fa-
cilitate the access of population
to gyms or places in public areas
equipped with appliances and
sports equipment.
population that are
participating in sports
events as spectators
The number of passive par-
ticipants to sporting events
(viewers) does not differ much
from that of active participants
(practitioners/athletes), re-
search results showing a per-
centage of 44.7% of the urban
adult population participating
in sports events as spectator.
This low percentage is a nation-
al issue with major impact on
the sports industry in the first
place, but also on the popula-
tion's quality of life. The nega-
tive influence on sport industry
is highlighted by several indica-
tors with disastrous results in
recent years in our country:
- the income of clubs and
sports arenas is dimin-
ished by the lack of inter-
est from the public to par-
ticipate directly in sport-

ing events
- the attractiveness of the
event for potential sponsors
decreases because there
isn't a target audience as-
sociated with that event
- the revenues from the
sales of promotional prod-
ucts with team logos are
at the borderline of sur-
vival on the Romanian
market, not to mention
the sales for products sold
in association with sport-
ing events whieh individu-
als can purchase when
arriving to the stadium/
arena (refreshments and
snaeks); in the U.S. mar-
ket, this range of produets
assoeiated with participa-
tion in a sporting event
determines the American
consumer to spend an av-
erage of $ 115, according
to the index "Fan Cost Ex-
perience" conducted annu-
ally by Team Marketing
Report (http://fancostex-
perience.com/pages/fcx/
blog_pdfs/entry0000025_
pdf002.pdf).
Regarding the negative im-

pact on quality of life, this is re-
lated to the need for socialization
of the individual and to the vari-
ety of ways in terms of leisure,
dimensions of quality of life that
on the Romanian sports market
are not related in any way to at-
tending sporting events.
The deeision to attend sport-
ing events is influeneed by indi-
vidual eharaeteristics, the big-
gest difference being noticed be-
tween men and women (56.8%
of men compared with 30.1% of
women that said they partici-
pate in sporting events).
Another influenee on this de-
eision is related to the sport na-
ture of the individual; there is a
tendeney for those who praetice
sport to participate in a larg-
er number at sporting events
(61.9%) compared to those
who do not play sport (32.3 %).
Market segmentation based on
this correlation helps to identify
the message that will be sent to
persuade the target audience to
attend sporting events, for those
non-sporting types is not indi-
cated the association with move-
ment, because it isn't an impor-
tant motivating factor for them.

4.4. Types of sports events
Romanian are participating
in as spectators
The sports market segmen-
tation in Romania must take
account the attractiveness
of the events from this mar-
ket. Figure 2 shows that most
Romanians are participating in
domestie ehampionships events
(81.3%), the pereentage being
eut in half when it eomes to
the partieipation in European
or international ehampion-
ships (40.3%). This differenee
ean be explained primarily by
lower frequency of international
events in sports in general, but
also by low purehasing power
that characterizes our country
(knowing that the price of tick-
ets to such events is mueh high-
er than for national ehampion-
ship matches).
RRM-4/2013
41
Figure 2. Types of sports events tbat Romanian people are
participating
in as spectators (%)

100,0 1
80,0 -
60,0
40,0
20,0
0,0
81,3
Domestic championship
40,3
^1
European/World championship
9,7
Local events
Local events have the lowest
degree of attractiveness - 9.7%,
which indicates a lack of cohe-
sion in the local community re-
garding the sports dimension.
Although these events are prob-
ably the most affordable, it does
not enjoy a proper promotion,
hence the very low presence of
spectators. Their accessibility
makes the percentage of women

among the spectators to be high-
er (18.6%) than men (6.06%).
Another explanation for the pre-
ponderance of women is the fact
that local events are usually or-
ganized for junior athletes who
come with their parents.
Segmentation by age brings
again a difference in terms of
participation in local events
"where we have a higher pro-
portion of adolescents and el-
_derljL. One explanation for this
result may lie in the much less
available for these categories of
people to travel to other areas
for national or international
events, correlated with their
lower income.
Correlation with marital sta-
tus shows that participation as
spectator to events within the
domestic championship is most
common in the case of unmar-
ried (88.9%), while the mar-
ried participates, mainly, to
Romania's representative team
matches (45.2%)), local events
being preferred by divorced/wid-
owed, in correlation with their
older age (28.6%).

Regarding the sports cor-
responding to events involv-
ing Romanians as spectators,
whether national or interna-
tional, the flrst two are soccer
and handball. The difference be-
tween attending national sport-
ing events or international ones
is represented by gymnastics, a
sport for which our country has
a long and notable performance
worldwide, hence the greater
share of the audience when it
comes to international competi-
tions for this sport.
population that watches
sports events on TV
Although does not imply di-
rect participation in sporting
events, the consumer of sport-
ing events represent a very im-
portant market, for which me-
dia trusts invest millions in TV
broadcast and firms turn into
sponsors. This category of sport
consumers represent the major-
ity of fans, taking into account
that traveling to sports events
is not always possible, hence
the desire to watch the event
through media.

Precisely because it does not
require an equally big effort as
for practitioners and specta-
tors, the percentage of those
who said they are watching
sporting events on television is
quite high - 76%. We must how-
ever make a distinction between
the types of viewers, first of all
based on their involvement in
sport, because the decision to
watch sporting events on televi-
sion is influenced by the sport
behavior of the individual. The
research results showed that-
87.9% of those who play sports
also watch sporting events on
television, while the percentage
for those that do not practice
sport is 67.4%. This influence
can be continued with the corre-
lat ion with the spectator status_
- 96.6% of those participating
in sporting events as spectators
are also watching these events
on television, while the percent-
age for non-spectators is 60.2 %.
The segmentation process
can continue using the socio-de-
mographic characteristics such
as gender or education level. It is
expected to have a difference be-
tween men and women in terms
of watching sporting events on

television, as can be seen from
42 Mihaela Constantinescu
Figure 3. Percentage of population watching sports events on
TV,
based on the gender categories (%)
1 "
120,0
100,0
80,0
60,0
40,0
20,0
n n
87,1
62,7
Men Women Total
I Viewer B Non-̂ ewer
Eigure 3, the percentage of men
being 87.1% compared to 62.7%

for women.
The correlation with educa-
tion shows that with increasing
level of education increases also
the percentage of those who fol-
low sports events on television,
ranging from 50% for those who
have completed only middle
school to 92.3% for those with
graduate studies.
4.6. Types of sports events
watching on TV
Viewers should be segmented
not only by soeio-demographie
charaeteristics, but also by ex-
pectations and preferences in
terms sports watched on TV.
Although most often Romanians
attends the domestic champi-
onship matches, on television
they are watehing at a higher
frequeney European and world
ehampionships, as ean be seen
from Eigure 4. The explanation
for this inversion is in the much
higher attraetiveness of sueh
international events, whieh
inereases the number of view-
ers, to those who usually follow
sports events on television add-
ing the oeeasional ones. The lat-
ter represents a large pereent-

age in the ease of the Olympies,
an event watehed by 66.8% of
Romanian population.
Figure 4. Type of sport event watched on TV (%)
European and world
championship 75,1
Olympic Games
Chompionships from other
countries
Other e«nts I
67,6
66,8
43,9
0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0 80,0
RRM-4/2013 43
Figure 5. Type of sport event watched on TV, based on the
gender categories (%)
Domestic Chompionships European and Olympic Games
championship from other world

countries championship
Other e«nts
I Men I Women
The correlation between
the status of spectator and the
viewer comes to uphold the idea
that people who participate in
sporting events as spectators
have a higher tendency to watch
these events also on TV, espe-
cially when it comes to domestic
championship matches.
Another possibility for view-
ers segmentation is based on
gender, observing from Figure
5 that both domestic champi-
onships and those from other
countries are pursued mostly by
men, the percentages balancing
in terms of European and world
championships, for Olympic
Games women's share being
even higher than men's (77, 1%
compared to 60.6%).
^Regarding the sports-
watched on TV, the present re-
search has shown that there are
no differences hetween the do-
mestic championships and those
from other countries, football
dominating all the time (as can

be seen from Table 2). The same
sport is refiected in first place
for European or world champi-
onships, but here also appears a
sport for which Romania is still
well represented - gymnastics.
For the Olympic Games,
Romanians don't have very
clearly defined preferences,
watching any broadcast of the
event, but there are certain seg-
ments of the population with
a predisposition towards gym-
nastics (38.7%) and athletics
(22.6%).
Table 2. Type of sport event
watched on TV, based on
competition type (%)
- Sport Percentage
soccer
handball
basketball
91,8
20,5
5,8
Championship from other
countries

soccer
handball
basketball
83,5
9,6
4,3
European and world
championship
soccer
haiidball
gymnastics
73,9
16,5
14,9
Olympics Games
an3rthing
gymnastics
athletics
45,2
38,7
22,6
5. Conclusions
The sports market segmenta-
tion can lead to identifying the

sports consumer categories on
every level, their characteris-
tics can be used to better match
the marketing strategy with the
needs and desires of individuals.
Thus we can make a portrait of
the consumer in the three steps
of his involvement in sports
activities:
Procesul de segmentare al
pieêi sportive poate conduce
la identificarea consumatorului
de sport pe fiecare nivel, car-
acteristicile acestuia putând
fi folosite pentru o mai buna
corelare a strategiei de market-
ing cu nevoile §i dorinêle indi-
vizilor. Astfel cä putem realizâ_
un portret al consumatorului pe
cele trei trepte de implicare în
activitäîle sportive:
- Practitioner - the main
segment is the singles
men aged 18 to 35 years,
who have postgraduate
studies and most often
play football, this segment
can be used as a factor
promoter for the segments
with a lower frequency of
practicing sports activi-
44

ties such as women or the
elderly, but we must keep
in mind that each seg-
ment can be motivated
by another factor in the
decision to do sports, so is
not recommended a single
message for all segments
identified;
Spectator - this type of
sport consumer includes
the one above, taking into
account that most specta-
tors are men and there is a
direct correlation between
sport and attending events
in this area; this segment
of fans attend more often
domestic championship
events, while women and
older people prefer local
events;
Viewer - this segment is
represented by both wom-
en and men, the differ-
ence standing in the type
of sporting event watched:
men are oriented towards
national championships
(either from us or from
another country), while
women are more receptive
to large events such as the

World Championships or
Olympic Games.
The segmentation must be
followed by an adaptation of the
supply from the sports market to
the needs and preferences that
result from sport consumer be-
havior analysis, whether prac-
titioner, spectator or viewer. At
the microeconomic level, this
translates into a market offer
better adapted, individualized
when possible (especially for
sports services). At the macro-
economic level, arises the need
to implement a national strate-
gy that promotes the positive ef-
fects of practicing sport on qual-
ity of life (especially for dimen-
sions such as health and educa-
tion), together with the social
effects that attending sporting
events has even as a spectator.
References
1. Cätoiu, L, Teodorescu, N. (1997),
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House, Bucharest
2. Constantinescu, M. (2009), Sports
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al approach to a relationship

perspective, ASE Publishing
House, Bucharest
3. Kotier, Ph., Keller, K.L. (2008),
Marketing Management, 5*'' Edi-
tion, Teora Publishing House,
Bucharest
4. Lardinoit, T., Le Nagard-Assay-
ag, E. (2004), Comment le mar-
keting sportif peut-il contribuer
au succès des nouveaux produ-
its?. Decisions Marketing, nr. 35,
p. 61-74
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teur, 3" Edition, Pearson Educa-
tion France, Paris
6. Shank, M.D. (2005), Sports Mar-
keting. A Strategic Perspective,
3rd edition, Pearson Education
International, New Jersey
7. Solomon, M., Tissier-Desbordes,
E., Heilbrunn, B. (2005), Com-
portement du consommateur,
6e Edition, Pearson Education
France, Paris
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carefree casuals to football anor-
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nr. 11, p. 1248-1270
9.http://fancostexperience.coiTi/pag-
es/fcx/blog_pdfs/entry0000025_
pdf002.pdf
RRM-4/2013
45
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ARTICLE
130
Journal of Sport Management, 2013, 27, 130-145
© 2013 Human Kinetics, Inc.
Shapiro and Ridinger are with the Dept. of Human Movement
Sciences – Sport Management Program, Old Dominion Uni-
versity, Norfolk, VA. Trail is with the Dept. of MSAL, Seattle
University, Seattle, WA.

An Analysis of Multiple Spectator Consumption
Behaviors, Identification, and Future Behavioral Intentions
Within the Context of a New College Football Program
Stephen L. Shapiro and Lynn L. Ridinger
Old Dominion University
Galen T. Trail
Seattle University
The growth of college sport over the last several years,
combined with increased competition for the sport
consumer dollar, has created a need to understand spectator
consumption behavior. In addition, the impact of a
new football program can generate interest that influences
future spectator spending decisions. Using identity
theory as a framework, the current study examined the
differential effects of past sport consumer behaviors on
various future sport consumer intentions within the context of a
new college football program. Consumption
intentions included attendance, sponsor support, and
merchandise purchases. Furthermore, this investigation
helped to determine how much variance past behaviors would
explain in behavioral intentions after controlling
for nine points of attachment. Data were collected from
spectators of a Football Championship Subdivision
(FCS) football program located in the Mid-Atlantic region. The
findings suggest past behavior predicted
future intentions; however, the amount of variance explained
varied dramatically depending on specific past
behaviors and points of attachment. These results can help sport
marketers develop strategies to capitalize on
the interest generated through new athletic programs.

College athletic departments have continued to
increase generated revenues over recent years. According
to Fulks (2011), National Collegiate Athletic Association
(NCAA) Division I Football Bowl Subdivision (FBS)
schools, which is the highest level of college football
competition in the Unites States, saw a 9.5% increase
from 2009 to 2010 in median generated revenue. NCAA
Division I Football Championship Subdivision (FCS)
schools, which are one level below FBS schools in regard
to football competition, experienced even larger median
revenue increases (14%) over the same time period. How-
ever, total expenses have increased at approximately the
same rate. Only 22 college athletic programs reported a
profit in 2010 (Fulks, 2011).
In the current financial landscape of college sport,
revenue growth is essential to cover the increase in costs.
The primary areas of college athletic revenue, which
include ticket sales, charitable contributions, sponsorship,
broadcasting rights, and merchandise purchases (Fulks,
2011) are primarily spectator driven. Fans purchase tick-
ets and merchandise, make annual contributions, support
program sponsors, and consume games through mediated
channels (i.e., television, team/league websites, social
media). Past fan consumption behavior through various
means helps determine how likely fans are to engage in
future sport consumption (Trail, Anderson, & Fink, 2000;
Trail, Fink & Anderson, 2003). This is further supported
by role identity and identity theory which suggests that
identity with certain activities influences behavior related
to those activities. According to Callero (1985), identi-
ties by their very nature, imply action. The relationship
between previous behaviors, identification, and future
behavioral intentions become particularly important in
a college athletics environment where spectator behav-

iors drive revenue production. Therefore, it is important
to understand spectator behavior and specifically, the
factors that may have an influence on future spectator
consumption intentions.
There is a wealth of literature examining the influ-
ence of identification on sport consumer behavior.
Previous research has focused on the development of
identification measures (Robinson & Trail, 2005; Wann
& Branscombe, 1993), the influence of team identification
on attendance (Laverie & Arnett, 2000; Trail, Anderson,
& Lee, 2006; Wakefield, 1995), and the influence of team
identification on various future consumption behaviors
(James & Trail, 2008; Trail et al., 2000, 2003, 2006; Trail,
Anderson, & Fink, 2005). Team identification has been
http://www.nassm.com/
http://www.JSM-Journal.com
An Analysis of Multiple Consumption Behaviors 131
shown to significantly influence consumption intentions
related to attending games and purchasing merchandise
(Trail et al., 2003, 2005, 2006), two vital revenue sources
in college athletics.
However, the literature examining the differential
effects of past consumption behaviors and identification on
future consumption intentions is limited. Only Trail et al.
(2006) focused solely on these relationships. The authors
argued that the influence of previous behavior and team
identification on future behavioral intentions is imperative
because consuming an event and establishing a connection
with a program helps move consumers up the fan commit-
ment escalator; which Mullin, Hardy, and Sutton (2007)

suggest increases overall consumption activity.
In addition, examining only one form of previous
consumption behavior (attendance), one facet of identi-
fication (team), and limited future intentions (attendance
and merchandise purchases) is only a piece of the puzzle.
Previous research supports the use of multiple facets
of identification and the importance of other revenue
sources (fundraising, sponsorship, broadcasting rights)
in addition to attendance and merchandise (Fulks, 2011;
Robinson & Trail, 2005; Trail, Robinson, Dick, & Gil-
lentine, 2003). Research examining multiple categories
of previous consumption behavior, identification, and
future intentions combined, is nonexistent.
It is especially important to examine multiple facets
of identification in the context of a new team. New sport
teams do not have a history of achievement or well
established traditions through which to attract fans. Thus,
the facets that influence the formation of identification
with a new team may be different from those that affect
identification with an existing team (Lock, Taylor, &
Darcy, 2011). Lock et al. (2011) found that the forma-
tion of new team identification was driven primarily by
identification with the sport, rather than with the specific
team. These authors encouraged the inclusion of multiple
points of attachment in future research on identification
with new sport teams.
As leagues expand and new teams emerge (Tierney,
2009), a better understanding of the identity fans develop
with a new team and its impact on consumptive behav-
iors may help maximize marketing opportunities. To be
viable in a competitive sports environment, a new team
must attract, develop, and maintain a relationship with
a substantial number of sport consumers (James, Kolbe,

& Trail, 2002). In college football, as schools look to
develop stronger connections with students, alumni, and
the community, the growth of new programs has been
sizeable. This includes 42 new college football programs
in the 1980s, 22 in the 1990s, and 28 in the 2000s (Tier-
ney, 2009). Furthermore, 25 additional college football
programs are slated to begin by 2014 (McGuire, 2011).
Research on consumer attitudes and behavior within
the context of a new program is scant. Conceptual and
theoretical development of sport consumer identification
has focused on established teams, largely ignoring how
identification might vary for a new team or league (Lock
et al., 2011).
Therefore, the purpose of this study was to examine
the relationship between previous fan/spectator behavior,
identification, and future behavioral intentions, while
incorporating multiple facets of each of these variables
within the context of a new college football program.
Review of Literature
Early research in sport consumer behavior focused on
the factors that influence attendance (Demnert, 1974;
Hansen & Gauthier, 1989; Noll, 1974; Whitney, 1988)
or the development of economic models to predict atten-
dance (Baade & Tiehen, 1990; Greenstein & Marcum,
1981). However, these studies failed to examine con-
sumer behavior factors that influence future consumption
intentions. Individual factors such as consumer attitudes,
feelings, and emotions influence how sport fans think and
consume sport-related products and services (Mullin et
al., 2007). Therefore, as an extension to this early work,
later studies explored relationships between spectator
identification and consumption behaviors (Laverie &
Arnett, 2000; Madrigal, 1995; Wakefield, 1995; Wann
& Branscombe, 1993). Wann and Branscombe devel-

oped an instrument to measure team identification and
examined the impact of identification on fan behavior.
The results provided evidence that fans with high levels
of team identification appear to be more involved with
their team and more willing to invest time and resources
into being a fan. Madrigal (1995) extended this research
through an examination of the relationship between team
identification and fan satisfaction. Team identification
was found to have a dominant influence on fan satisfac-
tion. However, actual consumption was not measured
in this model. Wakefield (1995) also examined team
identification, but focused specifically on repatronage
intentions as an outcome variable. The author found a
positive relationship between team identification and
future intentions providing some of the first empirical
evidence regarding the influence of identification on
future consumption intentions.
The previous studies demonstrate the significant
role team identification plays in fan behavior. Fan iden-
tity can be further explained through identity theory
(Stryker, 1968, 1980; Stryker & Burke, 2000). Accord-
ing to Stryker (1980), identity theory is focused on the
concept that individuals develop identities through social
experiences and relationships. Multiple aspects of identi-
fication are internalized through these social exchanges.
It has been hypothesized that the higher the salience of
these identities, “the greater the probability of behavioral
choices in accord with the expectation attached to that
identity” (Stryker & Burke, 2000, p. 186). This is further
supported by Callero (1985), who stated that the most
discernable consequence of identity salience relates to
actual behavior. The relationship between identification
and behavior is apparent in both theoretical and practi-
cal terms. Stronger identity salience leads to increased
actions. The relationship between social experiences,

identification, and behavior has been supported in areas
132 Shapiro, Ridinger, and Trail
such as student involvement in university organizations
(Serpe & Stryker, 1987) and commitment to religious
activities (Stryker & Serpe, 1982).
Within the context of sport, Laverie and Arnett (2000)
examined spectator identification and behavior based on
identity theory. It was suggested that role identities are
formed through past sport-related experiences. High levels
of identity salience influence current attitudes and future
behavioral intentions. The authors found support for the
relationship between team identification and attendance.
However, the outcome variable used was past attendance.
No other behaviors or behavioral intentions were consid-
ered. Past behaviors have been shown to influence future
behavioral intentions in a variety of contexts (Ouellette
& Wood, 1998). However, to fully understand the role
identification plays on consumption behavior through an
identity theory framework, various past behaviors and
various future intentions should be examined.
Trail et al. (2005) extended the work of Laverie
and Arnett (2000) through the development of multiple
models examining relationships between team identifi-
cation, disconfirmation/confirmation of expectancies,
mood, self-esteem, and future behavioral intentions
(i.e., attendance, merchandise purchasing, overall team
support). These models were created from previous
theoretical (Trail et al., 2000) and empirical (Trail et
al., 2003) studies that combined multiple determinants
of spectator consumption in an effort to further under-

stand fan behavior. The findings provided evidence of
a direct relationship between team identification and
future behavioral intentions along with an indirect rela-
tionship between these two variables, influenced by fan
self-esteem.
In addition, team identification may influence spe-
cific consumption behaviors differently. Trail et al. (2003)
found that the relationships between team identification
and two types of consumption intentions (attendance and
merchandise purchasing) were different, as indicated
by the difference in factor loadings on the second-order
latent variable (future behavior; Trail et al., 2003). These
findings are further supported in the literature (James &
Trail, 2008).
Trail et al. (2006) developed a model based on
identity theory that focused exclusively on past atten-
dance, team identification, future intentions, and actual
attendance. This study was the first sport consump-
tion examination that included previous consumption
behavior, identification, and future behavior. The
authors proposed that past attendance would predict
preseason team identification, intentions to attend
games, and actual game attendance. Findings showed
that number of games attended explained approxi-
mately 21% of the variance in team identification
and past attendance and team identification combined
explained 48% of the variance in future intentions.
Although Trail et al. (2006) did not specifically test for
mediation in their model; there certainly is the poten-
tial for team identification to mediate the relationship
between past attendance and future attendance. These
results offer further support regarding the influence
of identification on future consumption behavior. In

addition, this study highlights the impact that previous
behavior can have on team identification.
In summary, the previous literature provides
empirical support for two distinct relationships, (1)
team identification and various spectator consumption
behaviors and (2) past behaviors and future intentions.
Additional research is needed to further understand these
relationships. First, various consumption behaviors, both
previous and future, in addition to attendance should
be considered (i.e., merchandise purchases, mediated
consumption, sponsor purchases). As mentioned previ-
ously, merchandise purchases, sponsorship agreements,
charitable contributions, and broadcasting contracts
generate significant revenue in college athletics. In 2010,
these areas accounted for approximately 28.4% of gener-
ated revenue for FBS schools and approximately 33.7%
of generated revenue for FCS schools (Fulks, 2011).
Furthermore, attendance is only part of the complete fan
experience. Many fans are not able to attend live games
due to cost, location, or other obligations. Still, these fans
can build identification through many of the alternative
consumption methods previously mentioned.
Second, other forms of identification in addition to
team identification must be considered. Previous research
has shown support for multiple points of attachment or
facets of identification (e.g., player identification, sport
identification, coach identification; Robinson & Trail,
2005; Trail et al., 2003; Woo, Trail, Kwon, & Anderson,
2009). Previous consumption experiences may differen-
tially influence various points of attachment and these
points of attachment may differentially affect aspects
of future intentions. Examining only team identification
limits the opportunity to reach other segments of the
fan market, which identify with alternative facets of the

organization.
However, the literature examining the connection
between past behaviors, multiple facets of identifica-
tion, and various future intentions is underdeveloped.
Trail et al. (2006) provided empirical evidence that past
behavior and identification combined provided a more
thorough explanation of the variance in future behav-
ioral intentions. However, this was the only study that
provided evidence of this relationship, and both previous
and future consumption behaviors were measured only
through attendance.
This becomes even more important when dealing
with a new program where team identification may not
yet have been established. The impact of a new football
program is a unique consumption experience which may
have an effect on various levels of identification and
future consumption behavior. There has been a substan-
tial growth of new sport teams in general and college
football programs in particular in recent times. A better
understanding of past behaviors and fan identification
effects on future intentions for sport consumption can
help cultivate a fan base for these new teams which is
vital to their existence.
However, only a few studies examined identification
in a new sport environment. James et al. (2002) found
the reasons for purchasing season tickets for a new Major
League Baseball team differed based on psychological
connection to the team. Lock, Darcy, and Taylor (2009)
examined member identification with a new club soccer

team in Australia and concluded that age and income
were related to identity strength. Lock et al. (2011) used
a mixed-method approach to understand key themes
driving the formation of new team identification for fans
of Sydney FC, a soccer team in the newly developed
Australian A-League. Their findings suggest that to attract
fan support, a new team should leverage existing social
identities such as identification with the sport or with
the city where the new team plays. None of these studies
looked at the impact of identification on future intentions.
The current study had two objectives. The primary
objective was to test the differential effects of various past
behaviors on multiple behavioral intentions. A second-
ary goal within this objective was to examine how much
variance past behaviors would explain in behavioral
intentions after controlling for points of attachment.
This methodology provides an evaluation of the total
amount of variance explained by points of attachment,
and helps to determine whether the points of attachment
entirely subsume (mediate) the variance explained by past
behaviors. The results will allow marketers and managers
to understand whether it is necessary to take into account
both past behaviors and points of attachment when trying
to ascertain the determinants of future sport consumer
behaviors. However, this type of analysis assumes that
points of attachment potentially mediate the relationship
between past behavior and behavioral intentions. Based on
identity theory and the previous literature on identification
and spectator consumption behavior noted above, this is
a valid assumption, but it should be tested in the current
data. Thus, the second objective was to test for mediation.
Method
Research Setting
The context for this study was a large public university in

the Mid-Atlantic region with an enrollment of approxi-
mately 23,000 students. It is the largest among several
colleges and universities in a metropolitan community
with a population of 1.5 million citizens, but has been
considered a commuter school for many years. Foot-
ball was essential to the university’s goal of shedding
its commuter image and developing a greater sense of
community on campus (Sander, 2010). After confirming
student, alumni, and community interest in 2005, the
Board of Visitors unanimously approved a plan to begin
playing football at the FCS level and the inaugural home
opener occurred on September 5, 2009.
Participants
Data were collected from a random sample of fans
(season ticket holders and students) who attended at least
one home football game during the inaugural season.
Interest in the new team resulted in 73% of the seats
being sold as season tickets. Another 20% of the seats
were reserved for students, 5% were complimentary
tickets for the athletic department, and 2% were provided
to the visiting team, half of those on consignment. The
only tickets available for purchase on game day were
those unsold by the visiting team. Thus, the two largest
groups, season ticket holders and students, were targeted
for this study. The sample was selected from a list of
season ticket holders and student ticket holders during the
inaugural season. A total of 3,000 season ticket holders
were randomly selected from a list of 14,450. In addition,
2,616 students were randomly selected from a database
which included all students who registered for tickets
and attended at least one game during the season. Online
surveys were sent to a total of 5,616 fans and 1,092 usable
surveys were returned for a response rate of 19.4%.

Instrumentation
The questionnaire used for the current study consisted
of four sections with a total of 55 items. The first section
had 12 items related to demographics to profile the typi-
cal respondent. The second section had items measuring
various forms of past consumption behavior including
attendance, television viewership, radio listenership, print
media consumption, merchandise purchases, member
status and length of membership in the annual donor
club, tailgating, and other mediated consumption (e.g.,
web content, Facebook, Twitter; see Table 1 for the list of
the items/scales used in this research and how they were
measured). These measures were adapted from earlier
investigations examining previous behavior (Trail et al.,
2003, 2005). Some of the questions were open-ended to
collect continuous numeric data (e.g., How many home
games did you attend this past season?). Other questions
(7; e.g., I listened to the weekly football coach’s show)
were measured on a 7-point Likert-type scale with end
points ranging from Strongly Disagree (1) to Strongly
Agree. Means and standard deviations along with reliabil-
ity measures are listed in Table 1. The internal consistency
was satisfactory for all multi-item past behaviors (alpha
values ranging from .85 to .86). The correlations among
the past behavior items/scales indicated that they could
not be reduced into higher order factors so they were used
as 11 distinct independent variables.
The third section of the survey included 27 items
measuring identification. The Points of Attachment Index
(PAI), a scale developed to measure facets of identifica-
tion with a sport program (Robinson & Trail, 2005), was
used to measure various aspects of attachment to the new
football program. The PAI consists of nine categories
of attachment (player, team, coach, university, sport,

community, athletic department, general sport fan, level
of sport), which have shown past reliability and validity
related evidence, with alpha scores ranging from .70 to
.88 (Robinson & Trail, 2005; Robinson, Trail, & Kwon,
2004; Woo et al., 2009) and Average Variance Extracted
134 Shapiro, Ridinger, and Trail
Table 1 Means (M) and Standard Deviation (SD) Values for the
Past Behaviors and Behavioral
Intentions
Item/Scale M (SD)
Past Behaviors
Television Consumption (mean score of two items: I watched
sports broadcasts on the local TV news for
information about the team; I watched TV for news about the
team—α= .86)
4.89 (1.84)
Print Media Consumption (I read about the (TEAM NAME)
football team in the daily sport pages.) 5.53 (1.79)
Radio Consumption (mean score of four items: I listened to the
weekly (TEAM NAME) football coach’s
show; I got my information about (TEAM NAME) football from
radio stations; I listened to the pregame
shows on the radio; I listened to the postgame shows on the
radio— α = .85)
3.31 (1.66)

Website (I read about the (TEAM NAME) football team on the
(TEAM NAME) website.) 5.26 (1.80)
Past Attendance (How many home (TEAM NAME) football
games did you attend this season? 0–7.) 6.10 (1.81)
Tailgating (7-point Likert-type scale, Very negative influence
on my attendance (-3) to Very positive
influence on my attendance (+3))
5.66 (1.39)
Facebook (I got information about (TEAM NAME) football
from Facebook.) 2.51 (1.88)
Twitter (I got information about (TEAM NAME) football
through Twitter.) 1.53 (1.28)
Annual Donor Club (6-point scale: How long have you been a
member of the (Donor) club? (1) Less than
a year, (2) 1–2 years, (3) 3–5 years, (4) 6–10 years, (5) 11–20
years, (6) More than 20 years)
2.58 (1.58)
Web Broadcast (I was aware that I could watch (TEAM NAME)
home games online at odusports.com.) 3.76 (2.43)
Merchandise Purchase (fill-in-the-blank item: Please estimate
the total dollar amount (if any) that you
spent during this current season on (TEAM NAME) football
team merchandise and paraphernalia for
yourself and others.)
$136.61 (194.87)

Behavioral Intentions Mean (SD)
Support Sponsors of Football team (mean score of three items:
When I’m planning to purchase a
product, I would be more likely to choose a particular brand if
that company sponsors (TEAM NAME)
athletics; I will support companies that sponsor (TEAM NAME)
athletics when I have a choice between
two products; When a company sponsors (TEAM NAME)
athletics, I am more likely to purchase their
products/services when I have that option (α = .96).
4.86 (1.46)
Purchase Football team Merchandise (Please estimate the total
dollar amount (if any) that you intend
to spend next year on (TEAM NAME) football team
merchandise and paraphernalia for yourself and
others.)
$129.03 (192.23)
Attend Football Games (What is the number of (TEAM NAME)
football home game(s) that you intend to
attend next season?)
6.93 (1.79)
Attend Men’s Basketball Games (I am likely to attend (TEAM
NAME) men’s basketball games.) 5.51 (1.58)
Attend Women’s Basketball Games (I am likely to attend
(TEAM NAME) women’s basketball games.) 4.15 (1.82)
Note: All items were measured on a 7-point Likert-type scale

ranging from Strongly Disagree (1) to Strongly Agree (7) unless
otherwise noted.
(AVE) values ranging from .48 to .73 (Robinson & Trail,
2005; Robinson et al., 2004; Woo et al., 2009). The PAI
items were measured on a 7-point Likert-type scale and
indicated good internal consistency (alpha values rang-
ing from .82–.93) and construct reliability (AVE values
ranging from .615–.809; Table 2).
Finally, the fourth section of the survey consisted
of items measuring future intentions. These items were
measured by asking participants how likely they were
to attend future football games, attend men’s basketball
games, attend women’s basketball games, consume spon-
sor (of the football team) products (3-item scale), and
purchase football team merchandise in the future. Future
intentions were adapted from previous examinations of
identification and future behavior (James & Trail, 2008;
Trail et al., 2003, 2005). These items were measured
individually using a 7-item Likert-type scale and were
retained as single items (except for the sponsored prod-
ucts scale which showed satisfactory internal consistency,
a = .96), with each used as the dependent variable in the
different regression analyses (see Table 1 for means and
standard deviations).
Procedure
Questionnaires were administered through an online
format. Surveys were sent out one week after the final
home game during the inaugural season. Each potential

participant received an introductory e-mail explain-
ing the purpose of the study along with a link to the
web-based survey. A follow up e-mail was sent to all
nonrespondents ten days later in an effort to increase
response rate. In addition, incentives were offered to
respondents who completed the survey. Respondents
had the option to enter a drawing to win one of several
prizes. The information collected for the drawings was
kept separate from survey responses to maximize ano-
nymity and confidentiality.
Table 2 Factor Loadings (β), Confidence Intervals (CI),
Standard Errors (SE), and Average Variance
Explained (AVE) Values for the Points of Attachment Index
(PAI)
Factor and Item β CI SE α AVE
Identification with the players .91 .773
I am a fan of the individual players on the team .788 .767–.809
.013
I am a big fan of specific players .923 .910–.936 .008
I consider myself a fan of certain players .920 .907–.933 .008
Identification with the team .90 .752
Being a fan of (university) football team is very important to me
.819 .800–.838 .012
I am a committed fan of (university) football team .887 .873–
.902 .009

I consider myself to be a “real” fan of the (university) football
team .893 .879–.907 .009
Identification with the coach .87 .705
I am a big fan of (head coach) .788 .765–.810 .014
I would experience a loss if (head coach) was no longer the
coach .850 .831–.868 .011
Being a fan of (head coach) is very important to me .878 .861–
.895 .010
Identification with the university .85 .665
I feel connected to numerous …
Applied Economics, 2009, 41, 3209–3214
Attendance and promotions in
minor league baseball: the
Carolina League
Richard J. Cebula, Michael Toma* and Jay Carmichael
Economics Department, Armstrong Atlantic State University,
Savannah,
GA 31419, USA
This empirical study investigates determinants of attendance at

minor
league baseball games in the Carolina League in 2006. The
focus of the
analysis is on the effect of a wide variety of game-day
promotions on
attendance on a game-by-game basis, rather than aggregate
attendance
during the season. The Ordinary Least Square (OLS) results
imply that
attendance is positively a function of per capita income in the
city or
county hosting the team, runs scored by the home team, Friday
and
Saturday games, and promotions that provide cost-reduced food
or
beverages, low- and high-value merchandise and post-game
fireworks.
Attendance is negatively a function of home team errors,
Monday games
and possibly rainy conditions during the game. An unusual
finding with
respect to minor league baseball is that team performance
variables affect
attendance. However, home team runs scored and home team

errors
contribute to the overall entertainment experience for the home
team fans,
and thus yield plausible effects on attendance.
I. Introduction
The operation of Major League Baseball (MLB)
teams is a remarkably complex enterprise involving
the marketing of a diverse multi-dimensional enter-
tainment commodity (Demment, 1973; Scully, 1974,
1989; Baade and Tiehen, 1990; Quirk and Fort, 1992;
Zimbalist, 1992; Burger and Walters, 2003). Indeed,
as a consequence, there has developed rather sophis-
ticated theoretical as well as empirical literature
dealing not only with baseball but also with other
professional sports as well as amateur sports, partic-
ularly in the US (El-Hodiri and Quirk, 1971; Koch
and Leonard, 1978; Grimes and Chressanthis, 1994;
Vrooman, 1995; Solow and Krautmann, 2007).
1

At the uppermost level is the MLB franchise team’s
playing games in either the National League or
American League. This level of marketing involves
myriad forms of de facto ‘services’/‘commodities’,
especially the playing of MLB games (predominantly
in the form of regular season games), which generates
revenues not only through ticket sales, television
revenue and radio revenue but also through conces-
sion sales (soft drinks, beer, hot dogs, popcorn,
candy) and merchandising, for example, the sale of
team baseball caps, shirts of star players, baseballs,
bats, pennant flags and the like.
At another level of MLB is the multi-tiered system
of minor league teams, a mechanism through which
screening of players with greater potential for MLB
playing occurs and through which development of
players with talent occurs such that at least some
*Corresponding author. E-mail: [email protected]
1
The reader is also referred to the innovative survey by Fort and

Quirk (1995).
Applied Economics ISSN 0003–6846 print/ISSN 1466–4283
online � 2009 Taylor & Francis 3209
http://www.informaworld.com
DOI: 10.1080/00036840903286323
portion of minor league players eventually, and
sometimes quickly, are ‘called up’ to the MLB team
for a chance to make the MLB team roster.
Managers of minor league teams want to maximize
team success, as well as to help develop players to
reach their potential. Arguably, the most successful
minor league teams develop players through a com-
bination of coaching/direction, conditioning and
other means. Arguably, more successful minor
league teams help to avert their own extinction over
the long run by attracting larger crowds. Presumably,
these larger crowds serve to generate favourable
attendance data and revenues that make them less
of a financial burden to the MLB franchise. Teams
with poor attendance records are more likely to be
a financial burden and ultimately become candi-
dates for phasing out. Moreover, in theory, when
‘successful’ minor league teams attract larger crowds,
they can in effect use the ‘roar of the crowds’ to
encourage (‘psych’) young would-be MLB candidates
to respond to the crowd and play to their capacity
so as to attract the attention of their host MLB
team while becoming more accustomed to playing
in front of larger and perhaps more vocal audiences.
Indeed, learning to adjust to heckling may be yet

another side benefit of performing in front of larger
(and arguably more vocal) crowds.
Attendance at minor league games is the focus
of this study. In particular, the objective of this
study is to identify key factors that determine the
attendance record of minor league baseball teams.
To ensure greater comparability of data between
teams and hence relevance of the results, this
study focuses upon a single grouping of teams, the
Carolina League, and a single minor league baseball
season, 2006.
2
II. The Framework
The framework of analysis is one in which attendance
at minor league baseball games is largely a reflection
of factors influencing the demand for home team
tickets for game j. To begin this analysis, it is argued
that the higher the per capita income in the host
county (or host city) for a minor league team, the
greater the demand for tickets in that county, ceteris
paribus, as implied directly or indirectly in a number
of prior studies (Baade and Tiehen, 1990; Fort and
Quirk, 1995; Cebula and Belton, 1996; Solow and
Krautman, 2007). The term PCIj represents the 2005
per capita income in the host county or host city
where game j was played. Naturally, the demand for
minor league tickets is expected to be a decreasing
function of ticket price, ceteris paribus. The term TPj
represents the price of a general admission ticket on
game day for the home team’s j-th game. Team
performance has been argued/found to profoundly

affect the economic well-being of professional base-
ball teams (Baade and Tiehen, 1990; Fort and Quirk,
1995; Cebula and Belton, 1996; Solow and
Krautman, 2007). This study measures team perfor-
mance for the j-th minor league team in two ways: the
cumulative mean number of home team fielding
errors per game over the course of the season (ERRj);
and the mean number of runs scored per game by
the home team over the course of the season (RUNj).
The demand for tickets is expected to be a decreasing
function of ERRj, ceteris paribus, and an increasing
function of RUNj, ceteris paribus. Arguably, home
team fans prefer their team to make fewer errors
(manifest good fielding/defense) and score more runs
(manifest good offense). Next, minor league baseball
fans presumably prefer to attend games when the
weather is not rainy, ceteris paribus. The variable
RAINj is a binary variable indicating whether there
was precipitation present during the course of game j.
Arguably, the demand for minor league game
tickets might reflect various marketing efforts direc-
ted at attracting fans by making attendance a more
pleasurable family experience. General data reflecting
such marketing efforts for each of the teams in the
Carolina League assume the following four forms:
LOWVALj (a binary variable reflecting whether low
value merchandise was ‘given away’ upon entrance to
the stadium at game j, e.g. key chains or magnetized
team schedules),
3
HIGHVALj (a binary variable
indicating whether higher value items were given
away upon entry into the stadium at game j, e.g. hats,

jerseys or helmets),
4
FOOD/DRj (a binary variable
indicating whether discounts or specials on
2
The teams in the Carolina League (and their respective MLB
affiliations and county or city plus state where located) are as
follows: Frederick Keys (Baltimore Orioles, Frederick County,
MD); Kinston Indian (Cleveland Indians, Lenoir County,
NC); Lynchburg Hillcats (Pittsburgh Pirates, Lynchburg City,
VA); Myrtle Beach Pelicans (Atlanta Braves, Horry County,
SC); Potomac National (Washington Nationals, Prince William
County, VA); Salem Avalanche (Houston Astros, Salem City,
VA); Wilmington Blue Rocks (Kansas City Royals, New Castle
County, DE) and the Winston-Salem Warthogs (Chicago
White Sox, Forsyth County, NC).
3
Also included in this category of promotions are mugs, bobble
heads, calendars, water bottles, mouse pads, posters, team
photos, baseball cards and stadium replicas. Such items can, in
theory, tend to generate a degree of spectator loyalty.
4
Also include in this category are shirts, blankets, backpacks,
gym bags, baseball caps and more.
3210 R. J. Cebula et al.
concession items such as two-for-one hotdogs at or
before game time j were offered) and FIREWKSj

(a binary variable indicating whether a fireworks
show/display occurred following the conclusion of
game j). In each of these four cases, the expected
impact of the marketing policy/tool is expected to be
positive, ceteris paribus.
Finally, there are the temporal control variables,
that is, variables that reflect the day during the week
when game j was played. Arguably, such a variable is
needed to control for the fact that families are more
likely to attend games on certain days of the week,
especially Friday and Saturday, when the working
adults in the family are relatively more available,
than other days. Accordingly, dummy variables to
reflect whether game j was played on Monday
(MONj), Tuesday (TUj), Thursday (THj), Friday
(FRj), Saturday (SATj) or Sunday (SUNj) are
included in the model.
III. Empirical Model
Based upon the arguments provided above, the
following reduced-form equation is to be estimated
PERCAPACITYj
¼ a0 þa1PCIj þa2TPj þa3ERRj þa4RUNj
þa5RAINj þa6LOWVALj þa7HIGHVALj
þa8FOOD=DRj þa9FIREWKSj
þa10MONj þa11TUj þa12THj þa13FRj
þa14SATj þa15SUNj þu ð1Þ

where
PERCAPACITYj the total attendance at game j,
expressed as a percentage of the
seating capacity of the stadium
where game j was played during
the 2006 season for all of the
games in the Carolina League,
j¼1, . . . , 975;
a0 constant term;
u stochastic error term.
The Carolina League consists of eight teams
that played 975 games during the 2006 season. The
effective demand for tickets is described as a per cent
of the stadium capacity in each of the venues where
Carolina League games were played. Expressing the
dependent variable thus permits comparison across
stadiums of different capacities. All variables are
for the year 2006. Table 1 provides the data sources,
and Table 2 provides basic descriptive statistics
for the variables in the model. Observe that the
mean percentage attendance at the 975 Carolina
League games in 2006 was 52.29%, with a SD
of 27.6%.
Based on the arguments in the previous section
of this study, the following are the expected signs on
the coefficients for the economic, team-performance,

weather and marketing variables
a1 4 0, a2 5 0, a3 5 0, a4 4 0, a5 5 0,
a6 4 0, a7 4 0, a8 4 0, a9 4 0 ð2Þ
As for the days-of-the-week control variables, it is
expected that
a13 4 0, a14 4 0 ð3Þ
based on the argument that families can most easily
‘get together’ on Fridays (especially during the
evenings) and on Saturdays, when working parents
are more available. Interestingly, the 2 days of the
Table 1. Data sources
Variable Source
PERCAPACITYj Ballparks of Baseball (2007),
http://www.ballparksofbaseball.
com/aballparks.htm
PCIj US Department of Commerce,
Bureau of Economic Analysis
(2005)
TPj Team contacts*
ERRj http://www.minorleaguebaseball.
com/milb/stats/

RUNj http://www.minorleaguebaseball.
com/milb/stats/
RAINj http://www.minorleaguebaseball.
com/milb/stats/
LOWVALj Team contacts*
HIGHVALj Team contacts*
FOOD/DRj Team contacts*
FIREWKSj Team contacts*
MONj Team contacts*
TUj Team contacts*
THj Team contacts*
FRj Team contacts*
SATj Team contacts*
SUNj Team contacts*
Notes: *Team contacts – Frederick Keys, Deanna Davis
(2006), Assistant General Manager of Ticket Operations;
Kinston Indians, Katrina Carter (2006), Director of Sales
and Promotions; Lynchburg Hillcats, Erica Marcum
(2006), Ticket Manager; Myrtle Beach Pelicans, Dan
Kurland (2006), Director of Ticket Sales and Services;
Potomac Nationals, Doug McConnell (2006), Box Office
Manager; Salem Avalanche, Jeanne Boester (2006),
Director of Ticket Operations; Wilmington Blue Rocks,
Jared Forma (2006), Director of Ticket Operations;
Winston-Salem Warthogs, Brian Shollenberger (2006),
Director of Ticket Operations.
Attendance and promotions in the Carolina League 3211
week having the highest percentages of Carolina
League games are Friday and Saturday. By contrast,

the signs on the control variables for MONj, TUj and
THj should not be significantly positive because
Mondays, Tuesdays and Thursdays are generally
working days for most working parents. The argu-
ment regarding SUNj is unclear because although
most employed parents are not working on Sunday,
the family often has other family obligations, reli-
gious attendance and related activities, and possibly
preparation for the coming workweek during the
evening and/or afternoon on Sundays.
IV. Empirical Results
Estimating Equation 1 by OLS, adopting the
White (1980) heteroscedasticity correction yields
Equation 4
PERCAPACITYj
¼ 1:35
ðþ0:22Þ
þ0:0012PCIj
ðþ8:00Þ
�0:109TPj
ð�0:12Þ
�7:831ERRj
ð�3:76Þ
þ2:071RUNj
ðþ3:65Þ
�15:89RAINj
ð�1:87Þ

þ9:579LOWVALj
ðþ6:23Þ
þ13:693HIGHVALj
ðþ4:87Þ
þ5:662FOOD=DRj
ðþ2:31Þ
þ31:696FIREWKSj
ðþ11:20Þ
�4:67MONj
ð�2:00Þ
�4:23TUj
ð�1:62Þ
þ4:25THj
ðþ1:65Þ
þ6:40FRj
ðþ2:29Þ
þ19:62SATj
ðþ7:25Þ
þ0:81SUNj
þ0:33ð Þ
;
R2 ¼ 0:39; adj: R2 ¼ 0:38; F ¼ 41:48 ð4Þ
where terms in parentheses beneath coefficients are

signed t-values. Seven of the nine noncontrol
variables exhibit the expected signs and are significant
at the 5% level or beyond; only the ticket-price
variable fails to be significant at an acceptable
(i.e., 5%) level. Among the control variables, the
estimated coefficients on FRj and SATj are both
positive and statistically significant at the three and
one percent levels, respectively. None of the other
control variables are positive and statistically signif-
icant at the 5% level. The coefficient on MONj is
actually negative and significant at the 5% level.
Overall, ceteris paribus, the results for the control
variables suggest that Friday and Saturday games are
the most likely to attract large turnouts whereas
Monday is perhaps a day to avoid scheduling games
(if feasible). The coefficient of determination is 0.39,
so that the model explains nearly two-fifths of the
variation in the attendance variable as defined.
The F-statistic is significant at the 1% level, attesting
to the overall strength of the model.
As shown in Equation 4, the coefficient on the
per capita income variable is positive and significant
at beyond the 1% level, suggesting strongly that
locating a team in a venue with a higher per capita
income acts to raise attendance. By contrast, the
coefficient on the ticket-price variable is not statisti-
cally significant, suggesting that in the proximal price
range of general admission tickets, the ticket price is
not a significant factor in determining ticket pur-
chases. As a comparison, the average price of a
general admission ticket is less than that of an adult
ticket to a movie theatre. As for the home team
performance variables, ERRj and RUNj, the esti-
mated coefficients are both statistically significant
at beyond the 1% level and, respectively, negative

(as hypothesized) and positive (as hypothesized).
Thus, attendance at/ticket purchases to Carolina
League games are inversely impacted by fielding
errors committed by the home team and positively
impacted by runs scored by the home team. Team
performance counts! However, the loyalty of
Carolina League fans may be tested by inclement
weather. Namely, the coefficient on the RAINj
variable is negative and marginally statistically
significant, implying that rainy weather conditions
may dampen attendance, indeed, by as much as 16%.
Lastly, there are the impacts of the marketing
mechanisms. The estimated coefficients on each
of the four marketing variables, LOWVALj,
HIGHVALj, FOOD/DRj and FIREWKSj are posi-
tive and statistically significant at beyond the 1%
level. Thus, in 2006, when Carolina League home
teams offered fans enticements that fell under the
umbrella of LOWVAL, attendance rose on the
Table 2. Descriptive statistics
Variable Mean SD
PERCAPACITYj 52.29 27.6
PCIj 21.880 3.379
TPj 6.46 0.86
ERRj 1.153 1.1479
RUNj 4.997 4.234
RAINj 0.008 0.09
LOWVALj 0.217 0.412
HIGHVALj 0.0636 0.244
FOOD/DRj 0.071 0.257
FIREWKSj 0.138 0.346
MONj 0.127 0.333

TUj 0.1456 0.353
THj 0.131 0.338
FRj 0.161 0.368
SATj 0.1589 0.366
SUNj 0.135 0.342
average by roughly 10 percentage points for the game
in question, ceteris paribus. Alternatively, when home
teams in the Carolina League offered the enticements
that fell under the more costly umbrella of
HIGHVAL, attendance rose for the game in question
on average by roughly 14 percentage points, ceteris
paribus. Enticements falling under the umbrella of
FOOD/DRj on average for the game in question
acted to raise attendance by 6 percentage points,
ceteris paribus. Finally, home teams in the Carolina
League that chose to offer the costly displays of
fireworks (FIREWKSj) on average experienced a
32 percentage point boost in attendance for that
game, ceteris paribus. Thus, on average, taken one
at a time, each of these marketing options offered
by itself had a significant effect on attendance,
ceteris paribus.
In pursuing higher attendance levels, however,
management must be cognizant of increased operat-
ing costs associated with each option and must be
very circumspect as to how these (or other) marketing
tools might be optimally combined. Clearly, sound
marketing strategy would seem to require that
management simultaneously consider all of the
factors that influence ticket purchases, including

day of the week. It is likely, for example, that
Monday night fireworks displays or some other
costly marketing strategy for Monday night games
might well yield negative net benefits. Furthermore,
the repeated, commonplace use of any of these
marketing tools could easily lead to diminishing
returns and disappointing outcomes. For example,
offering fireworks displays, which are quite expen-
sive, every night over any extended period, would
clearly yield diminished benefits over time as fans
came to take the displays for granted. The same could
prove true for any of the marketing tools. Finally,
it would be folly to simply assume that the same
marketing strategy that worked in one year would
necessarily work as well in subsequent years.
Anything from demographic changes to volatile
economic conditions to increased competition for
the entertainment dollar could act so as to require
a dynamic process of marketing formulation and
re-formulation.
V. Conclusion
This study has investigated determinants of atten-
dance at minor league baseball games. Using data
from the Carolina League for 2006, it was found that
attendance, expressed in relative terms as the number
of persons in attendance as a percent of stadium
capacity, was directly related to the per capita
income of the county or city of the host team, the
home team’s runs scored record, the enticement of
low value marketing, the enticement of high value
marketing, fireworks displays, special-offer food and
drink deals, and scheduling on Fridays or Saturdays.
It was also found that attendance for the home team

was negatively affected by a poor fielding record
(in terms of fielding errors) and possibly by inclement
(rainy) weather. In addition, Mondays are a poor
choice for scheduling a home game, whereas general
admission ticket prices are not a factor. Finally, it is
emphasized that the strength of the marketing tools
at management’s disposal offers not only opportu-
nities but complex challenges.
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Are Sport Consumers Unique?
Consumer Behavior Within Crowded Sport Markets
Hunter Fujak and Stephen Frawley
University of Technology Sydney
Heath McDonald
Swinburne University of Technology
Stephen Bush
University of Technology Sydney
Sport consumers and markets have traditionally been thought to
exhibit unique behaviors from traditional consumer products,
particularly in respect to perceptions of loyalty. Yet, despite
sport landscapes becoming increasingly crowded, there has been
scant
research measuring consumers’ repeat behavior in the context of
the dense sports market. Through this research, we address this
gap by applying Dirichlet modeling against the behaviors of
1,500 Australian sport consumers. Two questions are explored:
First,
do sport attendance markets exhibit purchase characteristics
distinct from typical consumer markets? Second, do consumers
treat
sport leagues as complimentary or substitutable goods? The
results provide evidence that consumer patterns within the sport
attendance market are consistent to other repeat-purchase
consumer markets. This finding further diminishes the long-held
notion
that sport requires unique methods of management.
Furthermore, it was found that fans consume sport teams as
complimentary
products. As sport teams largely share their fans with other
teams, practitioners must reorient their expectations around fan
loyalty.

Keywords: consumer markets, Dirichlet, duplication of
purchase, repertoires, sport leagues
Commercial and technological developments within the
sport and media industries have facilitated considerable growth
in the opportunities to consume sport. Accordingly, the value of
the North American sport market is projected to be valued at
$71.6 billion in 2018 (PricewaterhouseCoopers, 2015). Along
with
new consumption formats, commercialization has also led to an
expansion in volume of teams and leagues competing for
consumer
hearts and wallets (James, Kolbe, & Trail, 2002). As Byon,
Zhang,
and Connaughton (2010) noted, “with such a crowded sport
marketplace, sport consumers have many options in which to
spend their leisure time and discretionary dollars. As a result,
professional sport organizations face stiff competition in an
effort
to gain market share” (p. 143).
Although there appears to be consensus that sport markets are
increasingly competitive and crowded (McDonald, Karg, &
Lock,
2010), there appears to be scant research that attempts to
quantify
the behavior and structure of such crowded sport markets
(Field,
2006). The scarcity of such research is particularly surprising
given
the centrality of competition to the sport sector: “Managing the
implications of competition, both on and off the field, is a
critical
success factor and a strategic imperative in its own right.
Compe-

tition, therefore, is the heart and soul of sport management”
(Shilbury, 2012, p. 2). Although sport consumption has emerged
as a vital area of research, the field has largely focused on fan
behavior within individual sports rather than the consumer
markets
in which teams compete (Pelnar, 2009). Through this research,
we
begin to remedy this shortcoming by undertaking an analysis of
sport consumer behavior within sport markets that feature a
high
degree of consumption choice.
Corresponding to an increase in off-field competition, sport
has continued along a path away from leisurely pastime toward
organized business practice, resulting in increasingly
professional
management strategies (Robinson, 2008). Yet, as sport manage-
ment becomes increasingly sophisticated, contention surrounds
whether corresponding strategies should be based upon broader
management principles or specialized from within the sport
man-
agement discipline (Chalip, 2006; Costa, 2005). In relation to
whether sport belongs as a distinct field of academic enquiry,
Chalip (2006) notes “The fundamental concern has therefore
been
whether sport management is a unique discipline or is one that
merely derives applications from theories originating in the so-
called ‘home disciplines’” (p. 2).
The defense of sport management as a distinct field has largely
been underpinned by the articulation of unique attributes innate
to
the discipline, which require distinct management practices
(Baker,
McDonald, & Funk, 2016). Neale’s (1964) identification of the

peculiar economics of professional sport confirms that such
artic-
ulation does not represent a new endeavor. However, more con-
temporary management-orientated research by Stewart and
Smith
(1999, 2010) have identified that although sport retains unique
attributes, these unique elements are often overstated, can be
found
in other products and markets, and have diminished over time.
Nonetheless, these unique attributes appear to still largely
underpin
Fujak, Frawley, and Bush are with the University of Technology
Sydney, Sydney,
New South Wales, Australia. McDonald is with the Swinburne
University of
Technology, Hawthorn, Victoria, Australia. Address author
correspondence to
Hunter Fujak at [email protected]
362
Journal of Sport Management, 2018, 32, 362-375
https://doi.org/10.1123/jsm.2017-0318
© 2018 Human Kinetics, Inc. ARTICLE
mailto:[email protected]
https://doi.org/10.1123/jsm.2017-0318
sport management. Baker et al. (2016) point to numerous widely
used introductory sport management and marketing textbooks
(e.g., Mullin, Hardy, & Sutton, 2014; Pedersen & Thibault,
2014) that include chapters discussing the uniqueness of sport,

suggesting the uniqueness remains an integral component of the
sport management self-narrative.
One feature of the sport market that has historically been
considered to distinguish it from other industries is the
perceived
loyalty and passion of sport consumers. Distinct from the
typical
rational decision-making consumer, the sport product has
histori-
cally been positioned as an “ephemeral experience mired in the
irrational passions of fans, commanding high levels of product
and
brand loyalty, optimism and vicarious identification” (Smith &
Stewart, 2010, p. 3). Although such characterization of sport
fans
provides for a simple narrative, the degree to which sport con-
sumers in fact exhibit particularly unique consumer behaviors is
becoming increasingly disputed. Observational evidence in fact
suggests that supporting multiple sport teams is possible, if not
common, although vigorous academic confirmation of such has
yet
to occur (Baker et al., 2016; McDonald et al., 2010). This repre-
sents a significant theoretical disconnect, given that consumer
buying behavior in other highly competitive repeat-purchase
indus-
tries, such as fast-moving consumer goods (FMCG) and profes-
sional services, has now been well defined (Ehrenberg, Uncles,
&
Goodhardt, 2004). Significantly, such research has provided
evi-
dence that consumer behavior across many varied competitive
industries conform to consistent behavioral patterns that result
in
predictable market structures (Bound, 2009). Whether such
behav-

ioral predictability occurs in a sporting context has largely yet
to be
addressed, though it is highly significant given the long-held
belief
that sport consumers in fact display unique behaviors.
Thus, through this research, we attempt to address this critical
gap by providing a quantitative analysis of consumer behavior
in
two crowded sport markets where multiple teams and leagues
compete. This is achieved by adopting Ehrenberg’s (1971) well-
established framework of buyer behavior within repeat-purchase
markets, utilizing the negative binomial distribution (NBD)
Dirich-
let model of market analysis (Bassi, 2011). The core research
purpose therefore is to understand sport consumption patterns
within selected geographic markets and is underpinned by two
key research questions (RQs):
RQ1: Do sport consumer markets exhibit purchase character-
istics typical of repeat-buying consumer markets?
RQ2: Do consumers treat sporting teams as complimentary or
substitutable goods?
The paper is presented in five parts. The first part examines the
relevant literature in respect to consumer markets and sport
land-
scapes. The second part outlines the methods deployed in this
study. Subsequently, the third part of the paper includes the
data
analysis, and the fourth part has the research findings and their
implications. The fifth and final part concludes with ideas for
future
research.

Literature Review
Consumer Behavior in Repeat-Purchase Markets
Owing to its financial significance, consumer behavior in
repeat-
purchase markets represents a comprehensively researched aca-
demic field (Sharp, Wright, & Goodhardt, 2002). Critical to the
field is the work of Ehrenberg (1971), who found that an NBD
was
well fit to analyze the market level data of industries in which
consumers made repeat purchases. Goodhardt, Ehrenberg, and
Chatfield (1984) developed this into the functional “Dirichlet”
model—a model theorizing that buyers have steady buying pro-
pensities and that these buying propensities vary across the
popu-
lation according to certain statistical distributions (Bound,
2009).
To measure this, the Dirichlet adopts a stochastic distribution in
predicting probabilistically both the number of purchases a
buyer
will make and the probability of each brand being bought on
each
purchase occasion in a particular time period (Goodhardt et al.,
1984). This model would later be developed into accessible
Excel-
based software by Kearns (2000) and later into R programming
language by Chen (2008).
The Dirichlet model has been found to be highly generalizable
and is considered one of the most validated models in the
business
marketing domain (Uncles, Ehrenberg, & Hammond, 1995).
Sharp
et al. (2002) noted that Dirichlet-type patterns have been found

across over 50 varied product and service categories and remain
valid both across countries and longitudinally. Ehrenberg et al.
(2004) provide a comprehensive summary of the breadth of such
research, although some illustrative examples are provided
further
below. Considerable focus, however, has centered on the FMCG
market given its repeat-purchase nature (Dawes, 2016;
Ehrenberg,
Goodhardt, & Barwise, 1990; Ehrenberg et al., 2004; Uncles et
al.,
1995). Aside from being highly generalizable, Dirichlet
modeling
has also been found to be relatively robust when applied in
settings
that depart from the model’s underlying assumptions. One such
assumption toward which the model appears robust is that the
market
of analysis is stationary in nature, which does not reflect
commercial
reality in most instances (Ehrenberg, 2000; Wright & Sharp,
1999).
A key to the Dirichlet model is the parsimonious manner by
which it validates multiple empirical marketing generalizations
and/or principles. Sharp et al. (2002) distinguished five such
generalizations the body of research has validated and which
the NBD-Dirichlet model accurately predicts: First, differences
in market share are largely due to differences in penetration—
higher share brands are bigger largely because they have more
customers than lower share brands. This illustrated within
Erhen-
berg et al.’s (2004) analysis of the U.S. coffee market from
1992.
The third (Taster’s Choice) and fourth (Nescafe) largest brands
held distinct market shares of 17% and 11% despite similar
average

annual purchase rates (2.8 vs. 2.7). Rather, the source of their
divergent market share was resultant from their differing annual
penetration rate: 9% compared with 6%. Second, the
comparatively
small differences between brands in average purchase frequency
and other loyalty statistics follow the double-jeopardy pattern
identified by McPhee (1963): Not only do small brands have
fewer
buyers, but also these buyers are slightly less loyal. This was
the
case in the Italian beer market between 2001 and 2004 (Bassi,
2011). Market leading brand Moretti (market share of 14.48%)
held
a 12.05% proportion of solely loyal buyers, compared with
market
laggard Bud (0.81% market share) with 8.79% solely loyal
buyers
(Bassi, 2011). Third, a brand’s customers, on average, buy other
brands more often. This is because most customers buy from a
repertoire of brands. This generalization is evident within Singh
and Uncles (2016) analysis of the U.K. breakfast cereal market.
Although Kellogg’s Corn Flakes was the market leading brand
(9%
market share), it accounted for only a 16% share of its
customer’s
annual cereal consumption requirements. Fourth, solely loyal
buying (i.e., the proportion of customers who only buy one
brand)
is relatively rare and declines over time. Within the Australian
retail
JSM Vol. 32, No. 4, 2018
Are Sport Consumers Unique? Consumer Behavior 363
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fuel industry, for instance, the average rate of solely loyal
buying
was found to be 8.3% (Sharp et al., 2002). Solely loyal buyers
are
also lighter buyers of the overall category while, by contrast,
heavier buyers tend to buy more brands but are less likely to be
solely loyal. Fifth, brands share their customers with other
brands
in line with each brand’s penetration—this is known as the
duplication of purchase law. These empirical principles
represent
the key measures tested within RQ1 (see Table 1).
In relation to the fourth empirical marketing generalization,
Sharp et al. (2002) observed that repeat-purchase markets are
polarized by either repertoire- or subscription-buyer behaviors.
Repertoire-pattern markets are characterized by consumers who
satisfy their consumption requirements from within a repertoire
of
brands. Notably, these buyers are described as exhibiting
polyga-

mous loyalty, which represents a departure from much of
traditional
marketing literature classifying consumers dichotomously as
either
“loyal” or “switchers.” In contrast, subscription-market patterns
differ in that consumers typically allocate most of their category
to
one provider. This has been found to be the case for instance in
the
credit card market, in which the average rate of solely loyal
usage
was found to be 79% in New Zealand (Sharp et al., 2002).
Notably,
from empirical observation to date, there do not appear be any
markets that occupy the middle ground between these two ex-
tremes. The distinction between repertoire and subscription
mar-
kets has significant implications for marketing practice. Brands
competing within repertoire markets are more likely to share
customers with competitors, impacting the strategic orientation
of marketing initiatives such as loyalty programs (Uncles,
Dowling, & Hammond, 2003). Within repertoire markets, a
brand
is better served to increase its penetration within the market
than
attempting to develop solely loyal buyers. Brands within
subscrip-
tion markets should focus on minimizing customer switching
and
maximizing new customer gain (Sharp et al., 2002).
Sport Consumer Behavior in Crowded Sport
Markets
Despite the application of the previously discussed generalized
marketing principles in a variety of empirical settings, sport

markets are only beginning to receive similar academic
attention
(Baker et al., 2016; Funk, Alexandris, & McDonald, 2016).
More
typically, research surrounding sport consumers has focused
upon
developing typologies and continuums to define their
connection to
individual teams and sports (Funk & James, 2001; Giulianotti,
2002; Mahony, Madrigal, & Howard, 2000; McDonald & Milne,
1997; Mullin, Hardy, & Sutton, 1993, 2014; Tapp & Clowes,
2002). However, although such sport segmentation models have
become robust in understanding fandom toward single sports
and
teams, they do not address consumer behavior in the context of
choice across sport brands at a market level.
The scarcity of holistic sport market research is perhaps of
some surprise, given that the sector represents a particularly
noteworthy field for such endeavor due to widely debated
conten-
tion around the degree to which sport contains unique product
and
marketing characteristics that distinguish it from other
industries
(Baker et al., 2016). Researchers have previously postulated
that
such empirical generalizations may not necessarily hold in the
case
of professional sport team brands (Gladden & Funk, 2001). In
contrast, some researchers consider sport team supporters to
exhibit
loyalty patterns similar to those in nonsport contexts (Tapp,
2004).
Smith and Stewart (2010) provided an evaluation of these

special
features and their advocates, conflating 10 distinct features
from the
original work of Stewart and Smith (1999) into four dimensions
in
their follow-up critique. These are as follows:
a. Sport is a heterogeneous and ephemeral experience mired in
the irrational passions of fans, commanding high levels of
product and brand loyalty, optimism, and vicarious
identification.
b. Sport favors on-field winning over profit.
c. Sport is subject to variable quality, which in turn has im-
plications for the management of competitive balance and
anticompetitive behavior.
d. Sport has to manage a fixed supply schedule (Smith &
Stewart, 2010, p. 3).
Overall, Smith and Stewart’s (2010) critique considered the
uniqueness of sport to be overstated and having diminished
since
their initial postulations. In relation to the first dimension,
while
they now consider sport consumption behavior to be an
exemplar
rather than exception of contemporary consumer behavior, they
note: “Sport is still characterized by fierce, loyal, and
passionate
fans who experience a strong, vicarious identification with their
players and teams. It remains one of the few products that
delivers
engaging experiences that become part of our collective
memory”

(p. 10). Despite broad acceptance that sport to some degree
retains
idiosyncratic features, it is unclear whether sport markets do, in
fact, behave differently than other industries in real-world
settings.
Among the first such papers to have tested broader consump-
tion patterns is that of McDonald and Stavros (2007), who
observed that the season ticket holder (STH) product category
appears to be characteristic of a subscription market. They
noted
that “in sporting clubs, consumers rarely ‘switch’ teams; thus,
the
issue is not one of attracting customers away from competitors,
but
rather reengaging, maintaining, or increasing the level of
partici-
pation of supporters” (2007, p. 219). The authors, however,
largely
measured the attitudes of existing and lapsed members rather
than
consumers’ propensity to hold multiple memberships therefore
precluding the possibility of Sharp et al.’s (2002) polygamous
loyalty. Similarly, McDonald (2010) measured the churn rates
of
STHs among several Australia Football League (AFL) teams,
once
again capturing consumers’ propensity to shift along the
continuum
Table 1 List of Generalized Marketing Principles
Principle Description
1 Differences in market share are largely due to differences in
penetration—higher share brands are bigger largely because

they have more customers than lower share brands.
2 The comparatively small differences between brands in
average purchase frequency and other loyalty statistics
follow a double jeopardy pattern: not only do small brands
have fewer buyers but also these buyers are slightly less
loyal.
3 A brand’s customers, on average, buy other brands more
often. This is because most customers buy from a repertoire
of brands.
4 Solely loyal buying (i.e., the proportion of customers who
only buy one brand) is relatively rare and declines over time.
5 Brands share their customers with other brands in line with
each brand’s penetration—this is known as the Duplication
of Purchase Law.
Note. Adapted from “Purchase Loyalty Is Polarised Into Either
Repertoire or
Subscription Patterns,” by B. Sharp, M. Wright, and G.
Goodhardt, 2002,
Australasian Marketing Journal, 10(3), pp. 7–20.
JSM Vol. 32, No. 4, 2018
364 Fujak et al.
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of casual ticket buyer to STH status within a single club, rather
than
supporting multiple clubs.
Focusing on broader notion of “support” for sport teams,
Doyle, Filo, McDonald, and Funk’s (2013) research suggested
that sport markets behave as repertoire markets. The researchers
explored the validity of the double-jeopardy principle in the
Australian sport context market in the context of attitudinal
loyalty,
finding partial support that the principle holds in a sport setting.
However, their research was limited to only National Rugby
League (NRL) and AFL fans as two broad groups, excluding
the remaining two football codes and other sport leagues that
compete within the market. This represents a significant
limitation,
as Wann, Grieve, Zapalac, and Pease (2008) observed,
clustering in
fans’ motivational profiles toward sports that share functional
attributes. The sport market may therefore be partitioned into
subsegments according to such functional similarities and
differences.
Baker et al. (2016) also successfully measured double jeop-
ardy in a sport setting, utilizing STH data to track AFL
attendance
across the 10 Melbourne-based clubs. Notably, the Dirichlet

model
was inaccurate at predicting 100% loyalty rates, indicating one
potential way that sport markets differ from other kinds. These
findings, however, were constrained to attendance within one
league and were unable to capture consumer-attendance
behavior
across the three remaining football codes that compete in the
market. Support was also found for the duplication of purchase
theory among Australian sport consumers, but once again, this
analysis was limited to AFL teams rather than the broader sport
market. However, Baker et al. (2016) noted these limitations to
be
an opportunity to further expand the topic, stating “further
replica-
tion should be undertaken to establish evidence for double
jeopardy
patterns : : : across multiple sports and national borders and in
more typical settings” (p. 388). This acknowledgment represents
the gap that this research endeavors to address.
From within the identified literature, it becomes apparent that
a significant gap exists in the underlying theory developed to
understand sport markets. Drawing from a considerable stream
of
work, researchers have identified and validated the unique char-
acteristics of sport management that distinguish it from other
industries. This has perhaps acted as partial justification for the
development of sport-specific theories and models to measure
sport consumption (Baker et al., 2016). Yet, broader marketing
theory has been shown to hold true in many empirical settings
(Sharp et al., 2002). Whether broader marketing theories are
applicable in a sport management context has significant
implica-
tions for the research approaches adopted by the discipline
going
forward.

Methods
Research Context
The study included an evaluation of sport consumer behavior
within two highly competitive sport markets located within
Australia’s two biggest cities, Sydney and Melbourne
(Australian
Bureau of Statistics [ABS], 2017). Sydney, Australia’s most
populous city (5.09 million residents) and largest from an eco-
nomic standpoint (responsible for 24.1% of gross domestic
prod-
uct), represents the primary case and was accordingly allocated
a larger sample of consumers (n = 2,039; ABS, 2018).
Melbourne,
Australia’s second largest city, represents the secondary case
(n = 459) and provides method replication and a point of case
comparison. These two cities represent logical points of
compari-
son, given they are not only similar in size but also in
professional
sport team concentration. Sydney was chosen as the primary
case
on the basis that it not only has a greater number of competitors
within its market but also has been shaped by a range of
physical,
historical, and socioeconomic factors that have led to greater
competitive intensity (Cashman & Hickie, 1990).
Acknowledging that leagues and teams in the Australian
market operate along a fully professional to semiprofessional
continuum, the population of the competitive landscape for this
study is restricted to leagues that are broadcast in their entirety
on

free-to-air or subscription television. Within this scope,
competing
for Sydney residents’ attention are 14 top-tier football clubs
across
four football codes, in addition to a further four professional
clubs
across the sports of netball, basketball, and cricket. Sydney rep-
resents a particularly noteworthy case, given its mix of
established
and emerging competitors. Rugby Union was Sydney’s first
foot-
ball code, with the city founding the country’s first governing
body
in 1874. The sport, however, remained amateur until 1996 when
the transnational “Super Rugby” competition established the
NSW
Waratahs as the sole and apex Rugby club in the region (Horton,
2009). Rugby League can similarly lay claim to first-mover
status
with the Sydney sport marketplace, being formed as a
breakaway
Rugby competition in Sydney featuring nine local teams in 1908
(Cashman, 2010). Today, the NRL consists of nine Sydney-
based
clubs (two of which are inaugural) within a 16-team national
competition (Low, 2008).
Soccer and AFL represent newer entrants to the Sydney sporting
landscape. The AFL began its expansion into the Sydney market
in
1982 as part of a greater strategic push to nationalize the sport
(Stewart & Dickson, 2007). In 2012, a second AFL team was
created
based in Western Sydney, making its first finals appearance in
2016.
After a considerable period of poor off-field governance,

a new soccer league known as the “A-League” commenced in
2005/2006 featuring eight single-city based, deethnicized clubs
(Georgakis & Molloy, 2016; Hay, 2011). Accordingly, the city’s
two top-tier A-League soccer clubs are comparatively fledgling
(5 and 13 years old) and similar to the AFL model, demarcate
along an East/West geographic border (Knijnik, 2015).
Similarly,
three of Sydney’s four nonfootball professional teams were
estab-
lished after 2007. Netball’s Australian-New Zealand
competition
(ANZ Championship) was established in 2008, whereas
cricket’s
Big Bash League (BBL), whose two Sydney teams also follow
an
East/West geographic divide, was formed in 2011 (Cricket
Australia,
2011). In 2016, Sydney’s 18 teams played in 14 different
Sydney
stadiums, with the greatest distance between stadiums being 77
km
between Brookvale Oval (Northern Sydney) and the Penrith
Stadium
(Western Sydney). A complete list of clubs is presented in
Table 2.
In comparison to Sydney, competition within the Melbourne
sport market has been a more recent phenomenon and accord-
ingly the market appears more established (Fujak & Frawley,
2013). Melbourne is the birthplace of AFL, with the first formal
set of rules (known as Melbourne Rules) conceived in 1859 and
the Victorian Football League established in 1896 (Hess,
Nicholson, Stewart, & de Moore, 2008). Nine AFL teams
operate
out of Melbourne, five of which are inaugural and the remaining
four having joined by 1925. Rugby League added their only

Melbourne team to the competition in 1998, Soccer’s two top
flight clubs were founded in 2004 and 2008 while Super Rugby
included a local team in 2011. Melbourne’s BBL cricket (2011),
netball (2008), and basketball (rebranded in 2014) teams were
also introduced more recently.
JSM Vol. 32, No. 4, 2018
Are Sport Consumers Unique? Consumer Behavior 365
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Participants and Materials
An independent panel provider was commissioned to collect
survey responses surrounding sport consumption within the
cities
of Sydney and Melbourne. In total, 2,572 respondents entered
the
survey, with 39% screened out for a lack of sport interest,
resulting
in 1,572 complete surveys. From the remaining 1,572 complete

surveys, another 74 were removed accordingly to quality control
procedures, leaving a final sample of 1,498. As the primary
case,
the final Sydney sample size was 1,191 sport consumers,
whereas
the final Melbourne sample size was 307 sport consumers.
The final sample had a slight male skew (52%), with an
average age of 44. Importantly, when compared against the
Australian Bureau of Statistics (ABS, 2017) on the basis of
statistical local areas, the sample was distributed geographically
evenly across both Sydney and Melbourne regions. This is
partic-
ularly significant from a methodological perspective in the
primary
case given Sydney’s geographic, social, and cultural diversity.
North and East Sydney are home to Sydney’s wealthier suburbs
and residents, characterized by higher incomes and lower unem-
ployment, whereas West and Southwestern Sydney have histori-
cally been more working class regions (ABS, 2017).
Participants were recruited by the independent panel provider
TEG …
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Franchise relocation and sport introduction: a
sports marketing case study of the Carolina
Hurricanes' fan adoption plan
Kelley, Scott W; Hoffman, K Douglas; Carter, Sheila . The
Journal of Services Marketing ; Santa Barbara
Vol. 13, Iss. 6, (1999): 469-480.
ProQuest document link
ABSTRACT
Franchise relocation and sport introductions are becoming
commonplace in professional sports. However, many
franchises have found that developing fan acceptance is often
challenging. The fan adoption process is presented
as a systematic framework that guides strategy development
from creating fan awareness through adoption.
FULL TEXT
Scott W. Kelley: Associate Professor of Marketing, School of
Management, Gatton College of Business and
Economics, University of Kentucky, Lexington, Kentucky, USA

K. Douglas Hoffman: Associate Professor of Marketing, College
of Business, Colorado State University, Fort
Collins, Colorado, USA
Sheila Carter: Marketing Manager, Carolina Hurricanes Hockey
Club, Morrisville, North Carolina, USA
Introduction
Franchise relocation and sport introduction, the introduction of
a sport to new markets, are becoming frequent
occurrences across sport categories. Fan acceptance of these
new "home teams" is crucial to the success of
these multi-million dollar moves and introductions. The
consumer adoption process provides sports marketers
with a systematic framework for the development of strategies
that facilitate fan movement from the awareness
stage to the adoption stage. When implemented effectively, the
fan adoption plan converts potential fans into avid
fans.
Case study methodology
In this paper, we utilize a case study methodology to investigate
a sports franchise's marketing activities directed

toward the facilitation of fan adoption. Case study research
methods have been advocated by a number of
researchers in the social sciences (e.g. Bonoma, 1985;
Eisenhardt, 1989; Yin, 1989). Case study research is
particularly appropriate when the phenomenon under
investigation does not lend itself to quantification and is
difficult to study outside of its natural setting (Bonoma, 1985).
In general, these methods also offer the benefits of
currency and high generalizability (Bonoma, 1985).
Consequently, the case study method utilized in this research
seems particularly appropriate and was designed and executed
with the intent of shedding light on:
https://search.proquest.com/docview/212652751?accountid=828
9
https://search.proquest.com/docview/212652751?accountid=828
9
- the marketing of new and/or relocated sports franchises; and
- the introduction of a relatively "new" sport to locations that
are unfamiliar with the sport being marketed.
Specifically, the marketing activities of the Carolina Hurricanes
Hockey Club during their inaugural season (1997-

1998) are examined.
Strategic marketing activities
A case study of the Carolina Hurricanes marketing program
provides marketing academicians with insight as to
how future research pursuits might be tailored to enhance our
understanding of the marketing of new or relocated
sports franchises as it pertains to the fan adoption process. This
case study may also prove to be a useful
teaching tool for academicians and a learning resource for
practitioners. Ultimately, it is hoped that the strategic
marketing activities discussed here will provide a link between
sports marketing academicians and practitioners
that will be mutually beneficial.
This research is organized as follows. First, some background
information concerning the Carolina Hurricanes
Hockey Club is provided. Second, some unique marketing
challenges associated with the Carolina Hurricanes are
discussed. Third, the marketing activities of the Hurricanes
during their inaugural season are presented and
discussed in the context of the fan adoption process, followed
by research implications resulting from this case

study.
Historical background
The history of the Carolina Hurricanes dates back nearly 30
years. In November 1971 the World Hockey
Association (WHA) awarded a franchise located in Hartford,
Connecticut. This franchise was formally named The
Hartford Whalers in January 1972. The Whalers competed quite
successfully in the WHA through the 1978-79
season. On June 22, 1979 the Whalers joined the National
Hockey League (NHL) along with three other WHA
hockey clubs, as the WHA was disbanded. The Hartford
Whalers were members of the NHL from the 1979-80
season through the 1996-97 season (Carolina Hurricanes 1997-
98 Media Guide, 1997).
Original franchise On May 6, 1997, Peter Karmanos, the chief
executive officer and governor of the Hartford
Whalers Hockey Club, announced that the Hartford Whalers had
reached a 20-year lease agreement with city
officials in Raleigh, North Carolina. At this time it became
official that the Whalers would be relocating to North
Carolina for the 1997-98 hockey season. The process of

relocating the franchise was complicated by the fact that
there was not a hockey arena that met NHL regulations
available in Raleigh at the time of the announcement. As a
result, the hockey club would play its games in the Greensboro
Coliseum until a new arena was built in Raleigh.
Greensboro is approximately a 90-minute drive from Raleigh.
On June 1, 1997, the Carolina Hurricanes set up their corporate
offices in Morrisville, North Carolina. The team
name, colors and logo were introduced at a press conference
held on June 16, 1997. Groundbreaking ceremonies
were held for the Raleigh Entertainment and Sports Arena on
June 21, 1997. This will be the permanent home of
the Carolina Hurricanes beginning in the 1999-2000 NHL
season. On October 3, 1997 the Carolina Hurricanes
played their first regular season home game against the
Pittsburgh Penguins at Greensboro Coliseum. This was a
landmark event in the five month long odyssey of moving the
operations of the hockey club from Hartford,
Connecticut to North Carolina.
Early marketing challenges

In their first season, the Carolina Hurricanes faced several
challenges that are becoming increasingly common in
today's sports marketing environment. However, many sport
franchises have had a difficult time overcoming these
initial obstacles that hinder fan acceptance. For the Hurricanes,
the most problematic challenges arose from
several circumstances including: the relocation of an existing
team, the introduction of a "new" sport to an area
that was unfamiliar with the sport of hockey, and the temporary
initial relocation of the franchise to Greensboro.
Relocation
Franchise location The Carolina Hurricanes were relocating
from an existing franchise location. This has become a
much more common occurrence in the world of professional
sports in recent years. For example, a number of
National Football League (NFL) franchises have moved in
recent years. The Cleveland Browns relocated to
Baltimore, becoming the Baltimore Ravens in 1996. The
Houston Oilers became the Tennessee Oilers prior to the
1997 NFL season and the Tennessee Titans at the conclusion of
the 1998 NFL season. The Los Angeles Rams are

now the St Louis Rams. The St Louis (football) Cardinals are
now the Arizona Cardinals; and the list goes on and
on.
Similarly, in recent years it seems there have been almost
annual rumors concerning the relocation of various
Major League Baseball (MLB) franchises. Some of these rumors
have involved longstanding MLB franchises such
as the Chicago White Sox, Pittsburgh Pirates, and Minnesota
Twins. In summary, the relocation of sports
franchises is a more and more frequent occurrence across a
variety of professional sports in recent years.
Sport introduction
The Carolina Hurricanes were also faced with circumstances
such that the sport they play is relatively under-
exposed and unknown in the south-eastern region of the USA.
The geographically closest NHL franchise is the
Washington Capitals which is approximately 275 miles from
Raleigh/Greensboro, but would hardly be considered a
south-eastern location. Two relatively new NHL franchises are
located in Florida - the Tampa Bay Lightning and the
Florida Panthers; and previously the Calgary Flames were less
than successful when located in Atlanta. Based on

past history and existing conditions, the introduction of a "new"
sport to an area (i.e. one in the introductory stage
of the product life-cycle) presents an interesting marketing
challenge.
Product life-cycle The introduction of a "new" sport is not a
totally uncommon problem. In fact, the diffusion of
innovations has been previously considered in a sports
marketing context (e.g. Higgins and Martin, 1996). For
example, Major League Soccer (MLS) franchises are currently
faced with a similar marketing problem as they
again try to "introduce" soccer to sports fans in the USA.
Other NHL clubs are, or have been, faced with this situation.
For example, the Los Angeles Kings, the Dallas Stars,
the Phoenix Coyotes, and the Nashville Predators have all at
some point in time been faced with introducing the
sport of hockey in their respective markets. The Women's
National Basketball Association (WNBA) and the
bankrupt American Basketball League (ABL) have also faced
the issue of introducing a "new" sport to their
respective markets.
Temporary tenant

The third challenge faced by the Carolina Hurricanes involved
their facility location. During the first two years of
their relocation the Carolina Hurricanes will play all of their
"home" games in Greensboro, North Carolina, a
distance of about 75 miles from their ultimate home in Raleigh,
North Carolina. Marketing a franchise in a location
geographically removed from its ultimate location presents
some unique marketing problems that the Hurricanes
were forced to address.
Taking up temporary occupancy of an arena in a city different
from the ultimate relocation destination of a
franchise would seem to be a rather unique circumstance.
However, in this day and age of professional sports
franchise relocation this situation has occurred in the past and
will no doubt occur again in the future. For
example, the Tennessee Oilers were faced with a remarkably
similar situation as they played their "home" games in
Memphis, Tennessee during the 1997 NFL season despite the
fact that ultimately their home field will be located in
Nashville, Tennessee approximately 180 miles away. Similarly,
the Carolina Panthers played their inaugural season

(1995) in Clemson, South Carolina before moving to their
ultimate home in Charlotte, North Carolina approximately
130 miles away.
Developing a fan adoption scheme
Sports marketing programs The consumer adoption process is
the mental process that an individual passes
through upon first hearing about a new product through its final
adoption (Kotler, 1997). Effective sports marketing
programs should develop effective fan adoption plans that
facilitate fan movement through these stages. An
examination of the Carolina Hurricanes' marketing activities
suggests that several marketing objectives were
targeted during their initial season that fit within the consumer
adoption framework. Our discussion of these
objectives is organized around the consumer adoption stages of:
(1) creating awareness;
(2) generating interest;
(3) facilitating evaluation;

(4) prompting trial; and
(5) ensuring adoption (see Table I).
The examples of fan adoption strategies discussed in this case
study are replete with managerial implications that
will aid sports marketers in their efforts to attract fans and to
help make franchise relocations and sport
introduction campaigns more successful.
Creating awareness
Marketing a brand Initially, it was imperative that the Carolina
Hockey Club created fan awareness for their brand.
A brand is defined by the American Marketing Association as a
"name, term, sign, symbol, or design, or
combination of them intended to identify the goods and services
of one seller or group of sellers and to
differentiate them from those of competition" (Keller, 1993, p.
2). In essence, aspects of sports marketing can be
viewed as a special case of marketing a brand (Keller, 1993, p.
18). During their first year of existence, brand-
related goals and objectives were deemed extremely important
to the short- and long-term success of the Carolina

Hurricanes Hockey Club. The brand-related marketing activities
of the Hurricanes first focused on building the
awareness of the Hurricanes brand.
Building brand awareness. It could be argued that nearly all of
the Hurricanes' marketing activities during their
inaugural season helped to create brand awareness. However,
several marketing activities implemented during the
course of the 1997-98 hockey season were specifically focused
on building brand awareness for the franchise.
Brand awareness focuses on the strength of customers' ability to
identify a brand under different conditions. A
high level of brand awareness is one of the essential outcomes
of effective marketing strategy.
Recognition and recall The two key aspects of brand awareness
are generally considered to be brand recognition
and brand recall. The relocation of the Hartford Whalers to
North Carolina resulted in a situation where there was
essentially no history associated with the newly created
Hurricanes franchise; hence, there was little to no brand
recognition or recall at this point. In order to address this issue,
the Carolina Hurricanes took measures to make

available the history of the Hartford Whalers franchise through
outlets such as the team media guide. However, the
main thrust in addressing the issue of team history was to
entrench the team and its representatives in the
Carolina community. In essence the underlying philosophy of
the franchise was that we do not have a franchise
history for our fans to draw upon; however, if we can become a
viable part of the Carolina community, the lack of a
team history may be less important to the fans. In short, because
the Carolina Hurricanes could not bring their own
ready-made history with them when they relocated, they took a
community entrenchment approach in an effort to
become a part of the history and culture of the Carolinas' past,
present and future.
Because the Carolina Hurricanes were a new franchise, the
process of building brand awareness started with the
actual creation of the brand. In a sense, the process began on
May 6, 1997 when it was announced that the
Hartford Whalers would be moving their operations to North
Carolina. A little over a month later on June 16, 1997 a
press conference was held in which the new team name, logo
and colors were introduced. The new team name
reflected what was uppermost in many of the minds of its

potential fans. Hurricanes Bertha and Fran had recently
ripped through the Carolinas. The new "brand name" was
immediately identifiable. Thus, the process of
creating/building brand awareness was initiated in earnest at
this press conference with the introduction of these
branding elements (see the Carolina Hurricanes' Official Web
site at http://www.caneshockey.com).
Generating interest
The second stage in the fan adoption process focused on
generating fan interest in the game of hockey in general
and the Carolina Hurricanes in particular. At this stage of the
fan adoption process marketing, activities focused on
creating a brand image for the Hurricanes and educating fans
about the game of hockey.
Interest stage Creating a brand image. It was important for the
Hurricanes to create a distinct brand image that
would move fans from the awareness stage to the interest stage
in the adoption process. Brand image involves
consumer perceptions about a brand. These perceptions are
based on brand associations held in consumer (fan)
memory (Keller, 1998). There are three main types of brand
associations used by consumers to formulate brand

image:
(1) attributes;
(2) benefits; and
(3) attitudes.
Because of the relatively new nature of the sport of hockey in
the region, one aspect of the Hurricanes' marketing
activities involved communicating attributes, benefits, and
attitudes toward the game of hockey itself. Several
marketing vehicles were created in an effort to educate potential
fans in the south-eastern region about various
aspects of the game of hockey. Marketing efforts were targeted
toward creating a stronger understanding among
fans regarding:
- the rules of hockey;
- the NHL and its structure, hockey positions;

- hockey strategy; and
- the history of hockey.
The game of hockey. One of the strategic objectives of the
marketing program for the Carolina Hurricanes during
their initial season focused on fan education. Specifically, if
fans had a better understanding of the game of
hockey and its intricacies it was felt that they would find the
games more enjoyable and entertaining (Zhang et al.,
1996). Toward this end the Carolina Hurricanes held a number
of Hockey Clinics in communities and schools in the
region. The Hurricanes also produced a video entitled "Hockey
101" that explained the game of hockey and its
rules. In addition to the clinics and video, a brochure entitled
"Hurricanes Hockey, Class In Session" was printed
and widely distributed at home games, hockey clinics, and
community events. In this brochure the game of hockey
was broken down into six simple lessons covering topics such as
player positions, speaking hockey, referees'
signals, and hockey equipment. Some of this information was
also included on a panel of the Hurricanes' pocket
schedule. Finally, a planned and concerted effort was made to
provide explanations of the rules at the games

themselves via the public address announcer and the jumbotron
screen.
Educating the fans The history of hockey. One of the common
features of most collegiate or professional sports
teams with a strong fan base is a well-developed appreciation
for the history of the game itself, as well as the
history of the team (Kelley and Tepper, 1998). From a
marketing perspective this presented an interesting problem
for the Carolina Hurricanes. First, the game of hockey was a
relatively new and unknown sport in the region.
Second, the Carolina Hurricanes were a new franchise in that
they had been relocated from Hartford. Although
admittedly it is difficult if not impossible to develop an
appreciation for the history of a hockey franchise when
there is none, the Hurricanes' marketers did strive to develop an
appreciation for the history of the game of hockey
among their fans.
Efforts in this regard covered a wide range of marketing
activities. For example, attending the first Carolina
Hurricanes regular season home game was promoted as a chance
to be a part of an historical night, and the
Hockey 101 video mentioned previously contained a segment
focusing on great plays, players and teams in the

history of hockey. In a similar vein, after the Carolina
Hurricanes inaugural season was completed, promotional
material promoting the second season included a list of the
"firsts" occurring during the inaugural season (e.g. first
goal, first assist, first hat trick, first shutout, etc.). The
Hurricanes occasionally even went as far as promoting
superstars on opposing teams, such as Wayne Gretzky and Eric
Lindros, so that fans could literally watch history
in the making. Providing fans with an historical perspective
during the Carolina Hurricanes' first season generated
interest and helped to continue to build a loyal fan following.
Facilitating evaluation
Evaluation stage The major objective of the evaluation stage is
to emphasize to potential fans the advantages of
the sport of hockey over the alternative forms of entertainment
available. The Hurricanes responded to this
challenge in two ways. First, the content of promotions
switched from informational and entertainment to
experiential. Traditional marketing media were used to
communicate the experiential benefits pertaining to

attending a Hurricanes' game.
This strategy was reinforced by uniting with NASCAR, the
stock car racing circuit, in a cross-promotional effort.
This strategy made good sense. NASCAR and professional
hockey share similar target market profiles, and a great
deal of the hockey season occurs during NASCAR's off-season.
In addition, fans experience many of the same
sensations at a hockey game as they do attending a NASCAR
event.
Furthermore, NASCAR is highly revered in the Carolinas. Jeff
Burton, a prominent NASCAR driver, served as a
spokesperson for the Hurricanes and drove a car with the
Hurricanes' logo prominently displayed at several
NASCAR events. This not only increased the Hurricanes'
exposure to potential fans, it also helped legitimize the
sport of hockey to its potential target market. This strategy
became particularly effective when Jeff Burton spoke
of the entertainment value offered by professional hockey.
Prompting trial
Behavioral perspective Building brand loyalty. The fourth stage
of the fan adoption process focuses on prompting

fan trial. In the case of the Carolina Hurricanes, fan trial was
pursued with the ultimate objective being the building
of brand loyalty. Brand loyalty is generally viewed from a
behavioral perspective (Keller, 1995). That is, brand
loyalty is inferred through repeat purchase behavior. Although
brand loyalty was the ultimate goal, in the initial
year of the Hurricanes' franchise a primary objective in this
regard was prompting fan trial. In other words, in order
to gain repeat purchasing loyal customers, the Hurricanes first
had to convince fans that attending a hockey game
for the first time was a good idea.
Toward this end, the Hurricanes offered a number of game night
promotions to attract new fans. Special ticket
package promotions were developed for and marketed to
selected demographic groups. For example, the "Student
Rush" program allowed students to purchase a discounted ticket
upon presenting their student ID. This program
was heavily promoted on regional college campuses. The
"Family Night" program offered a package of four tickets
with concessions and merchandise included as an incentive for
families to attend more games. This program was
heavily advertised through print ads and the Internet. In
addition to all of the promotional mechanisms created to

attract first time fans, a concerted effort was also made to make
sure that the experience of the first time fan was
a good one. This was deemed extremely important to the goal of
building brand loyalty and moving fans from the
trial stage to the final stage of the fan adoption process.
Creating/building brand awareness One promotion was
sponsored by the Carolina Ford dealers and involved giving
away Ford vehicles. Individuals test driving a Ford vehicle
received a pair of free Hurricanes tickets. In addition,
during the season Carolina Ford dealers gave away vehicles at
20 home games. This was an expensive promotion
from the perspective of the Hurricanes (i.e. the attendance bump
did not cover the cost of the promotion).
However, from the perspective of creating/building brand
awareness and facilitating fan movement from the
evaluation stage to the trial stage this was an extremely
successful promotion. It attracted a great deal of
attention from Hurricanes fans, non-fans, and the media as well.
Consequently, marketing strategies utilized to
achieve objectives associated with later stages in the adoption
process, such as the trial stage, may reinforce the
achievement of earlier stage objectives as well.

Ensuring adoption
As fans progressed through the adoption process, the ultimate
goal of the Carolina Hurricanes' marketing program
was to ensure the long-term adoption of their product - a fast
paced, family oriented entertainment experience.
Toward this end, marketing activities intended to deepen the
relationship between the Hurricanes organization and
its fans and strengthen the brand equity of the Hurricanes
Hockey Club were pursued.
Emphasis on entertainment value Relational strategies. The
multi-pronged effort to educate fans about the game
of hockey and facilitate the earlier stages of the fan adoption
process was generally well accepted by the targeted
audiences. However, after some time, marketers in the
Hurricanes organization realized that an over-emphasis on
the rules and intricacies of the game might be detracting from
the Hurricanes game experience. As a result, the
earlier focus on fan education regarding the rules of the game
was reduced. Instead, a stronger emphasis on the
entertainment value of Hurricanes hockey was put in place. In

short, it was decided that fun was more important
for the development of a strong fan base than a detailed
understanding of the rules and intricacies of the game of
hockey. Hence, the building of relationships and fan satisfaction
with the "sporting experience" became the
focuses of the Hurricanes' marketing efforts.
Coincidentally, in recent years there has been a change in the
focus of marketers in general from an emphasis on
individual transactions to an emphasis on relationships
(Webster, 1992). While this change has been occurring in
the general marketplace, it seems that it may be taking place in
the realm of sports marketing as well (Brenner,
1997; McDonald and Milne, 1997). Relationship marketing
involves a focus on the attraction, maintenance, and
enhancement of customer relationships (Berry, 1995). It is a
philosophy of doing business that focuses on keeping
and improving existing customer relationships (Zeithaml and
Bitner, 1996).
Several different levels of relationship marketing have been
identified by marketing researchers. Level one
relationship marketing focuses primarily on pricing as a
mechanism to attract customers and build their loyalty

(Berry, 1995). In the case of the Hurricanes some of their
marketing efforts (e.g. discount ticket prices) were
focused on building level one relationships. Strategic marketing
activities relying on pricing to attract fans
facilitated level one relationships. Because level one
relationships are typically built on pricing incentives, they are
also the easiest type of customer relationship to break. In many
instances a competitor's larger price break is all it
takes to break a level one relationship.
Social aspects Level two relationship marketing efforts focus
strongly on the social aspects of the service offering
(Berry, 1995). The Hurricanes' marketing efforts evolved during
their first season towards the building and
fostering of level two relationships. It was recognized that the
social aspects of the hockey entertainment
experience were vital to ensuring long-term fan adoption and
fan satisfaction with their night at the hockey arena.
In a similar vein, a greater emphasis was placed on community
relations activities undertaken by the Hurricanes.
This helped to foster the social bonds between the hockey club
and its fans. Hence, the stronger level two type of
relationship marketing was pursued.

In his writings on the consumption of performance, Deighton
(1992) notes that there are some different types of
performances that individuals consume. In the case of
Hurricanes' hockey two of these types of performance
seem most relevant - skill performance and thrill performance.
Skill performance and thrill performance both occur
in a naturalistic setting, with tension and uncertainty and
circumstances leading to the testing of values (Deighton,
1992). The distinctions between skill performance and thrill
performance arise when one considers the role of the
consumer in the event. In the case of skill performance, the
emphasis is on the consumers' role as an observer
where the activity is seen as relatively passive, with a strong
focus on the actors (i.e. the hockey players). On the
other hand, in the case of thrill performance, the emphasis is on
the consumers' role as an active participant in the
event where the activity is seen as involving, the audience is
integrated into the performance, and does not
maintain a single focus.
Thrill performance One might argue that the Hurricanes'
marketing focus was initially on promoting Hurricanes'
hockey as a skill performance in which it was important for the

fans to understand the intricacies of the game and
focus on the skills of the players. As the marketing activities of
the Carolina Hurricanes evolved during the course
of their first season, a greater emphasis was placed on the thrill
performance aspects of Hurricanes' hockey.
Instead of a single-minded focus on the hockey game and its
participants, other foci became important.
Hurricanes' hockey promotions began to focus on the
entertainment value and the social aspects of the event,
which in turn, facilitated the fan adoption process.
Strengthening brand equity. A final brand-related objective of
the Carolina Hurricanes Hockey Club involved the
strengthening of the brand equity of the Hurricanes brand.
Customer-based brand equity is the differential effect
brand knowledge has on customer responses to …

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