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Abstract

Researchers across disciplines have been studying the psychology of fans for decades. Seeking to better understand fan behavior and the various factors motivating fans, researchers have studied dozens of variables in hundreds of studies of different fan groups. To date, however, there have been relatively few attempts to integrate this sizable body of work, pulling together findings across from the field to with a broader, more holistic perspective. This book does exactly that, identifying and concisely summarizing research on 28 separate lines of inquiry on the psychology of fans and integrating it all into an empirically-validated model known as the CAPE model. Useful as a textbook for a fandom studies course and as a handbook for fan researchers, this book is essential reading for anyone looking to better understand the state of fan psychology and wanting to conduct their own research exploring the ins and outs of fans of all sorts!
CAPE: A Multidimensional Model of Fan Interest
CAPE: A Multidimensional Model of Fan Interest
Courtney N. Plante
Bishop’s University
Stephen Reysen
Texas A&M University-Commerce
Thomas R. Brooks
New Mexico Highlands University
Daniel Chadborn
New Mexico Highlands University
CAPE Model Research Team
Commerce, Texas, USA
ISBN: 978-0997628821
Copyright © 2021 CAPE Model Research Team
(Plante, Reysen, Brooks, & Chadborn)
Commerce, Texas, USA
Cover: Taya Ovod/Shutterstock.com
This book is licensed under a Creative Commons Attribution 4.0 International
License (CC BY-NC-SA 4.0)
Acknowledgments
We would like to thank long time collaborators Dr. Sharon Roberts and Dr.
Kathleen Gerbasi for aid in collecting data for furries and anime fans and Grace
Packard for collecting data for Star Wars fans.
Contents
Introduction
1
Chapter 1
Magnitude
13
Chapter 2
Participation
25
Chapter 3
Recreation
33
Chapter 4
Meaning-Making
41
Chapter 5
Direction/Guidance
47
Chapter 6
Personal Growth
53
Chapter 7
Fandom
59
Chapter 8
Social Interaction
67
Chapter 9
Novel Experience
77
Chapter 10
Escape
83
Chapter 11
Eustress
89
Chapter 12
Emotion
95
Chapter 13
Materialism
103
Chapter 14
Loyalty
111
Chapter 15
Fanship
117
Chapter 16
Uniqueness
127
Chapter 17
Creativity
131
Chapter 18
Aesthetics
139
Chapter 19
Knowledge
145
Chapter 20
Self-Esteem
151
Chapter 21
Desirability
157
Chapter 22
Economic Motivation
163
Chapter 23
Accomplishment
169
Chapter 24
Exclusivity
177
Chapter 25
Self-Disclosure
183
Chapter 26
Physical Attraction
191
Chapter 27
Pathology
199
Chapter 28
Special Bond
205
Chapter 29
Development of the Model
211
Chapter 30
Validation of the Scale
223
Chapter 31
Utility of the Scale
247
Conclusion
277
Appendices
279
References
295
1
Introduction
Allow us to start this book with a bold prediction: You’re probably a fan of
something. Be it a sport, television show, music group, or hobby, chances are
reasonably good that you enthusiastically and ardently engage in at least one
interest (Reysen & Branscombe, 2010).
Unimpressed by our prophetic ability? It’s probably because you know,
whether intuitively or through research, that fans are a ubiquitous part of modern
culture. The U.S. sport industry alone brings in more than 70 billion dollars
annually (Kim, Qian, et al., 2020; Yousaf et al., 2017), while global
competitions like the Olympics or the World Cup are among the most-viewed
events on the planet. Whether we’re talking about sport fans or binge-watchers
of a new Netflix original series, fans the world over spend a significant portion
of their valuable free time engaging in fan-related activities. One study found
that U.S. adults spend an average of 20 and 38 hours per week on their leisure
activities (Ruggeri, 2020) while, on the other side of the globe, Chinese college
students spend upwards of 9 hours per day on leisure (Chen & Liu, 2020).
People, rather paradoxically, take their leisure activities, very seriously.
Given the amount of time and money people spend on their interests, it was
inevitable that marketers and academics alike would show an interest in fans.
Part of this endeavor includes efforts to categorize fans into types or taxonomies.
To those in marketing, segmenting the market this way allows companies to
target products and advertising directly to the most interested potential
customers (Hunt et al., 1999). To academics, this sort of categorization allows
researchers to better understand the important dimensions and mechanisms
driving fan behavior.
In this book we’re building off the work of both of these groups. Specifically,
we’ll be looking at the variables used to distinguish between different “types” of
fans. Before we do, however, we should briefly review some of the different
taxonomic and typological approaches used by those studying fans, including
categorizing fans based on…
1. The nature of their identification with their fan interest.
2. Their engagement in specific fan-related behaviors.
3. The motivations underlying their fan interest.
4. A stage-like progression through their interest.
We should also mention, before we begin, two important caveats. First,
despite our treatment of these categorizations as conceptually distinct, there may
be associations between them. For example, fans who engage in one type of fan
behavior (e.g., attending fan conventions) may be differently motivated (e.g., by
social needs) than fans who engage in a different type of behavior (e.g., writing
fanfiction for reasons of self-expression). In this case, categorization based on
specific behaviors overlaps at least somewhat with categorization based on
motivation. This doesn’t detract from the utility of these categorizations, but
rather illustrates the complex interplay of dimensions driving differences
between any two fans.
The second caveat is that our summary of these different theoretical
approaches to organizing the academic literature on fans is far from exhaustive.
There are many more typesof fans and fan engagement than what we cover
here, including distinguishing fans from non-fans and anti-fans (Gray, 2003),
enjoyment and appreciation (Oliver & Bartsch, 2011), harmonious and
obsessive passion (Vallerand et al., 2003), subcultures within fandoms (e.g.,
creators, critics, collectors, joiners, and spectators, Hanna et al., 2011),
utilitarian and authentic (Wallace et al., 2014), and the related phenomenon of
parasocial connections with fictional characters and celebrities (e.g., Eyal &
Cohen, 2006). As you read the rest of this introduction and the chapters which
follow, keep this in mind: Our goal is to review the most influential or
theoretically-central dimensions of fans, not to catalogue every typology and
dimension ever created.
Categorizing Fans Based on Identification
The extent to which fans identify as fans of their fan interest is arguably the
dimension most widely used to differentiate fans from one another. Those who
identify more strongly with facets of their fan interest are bigger fans,” and
contrasted against those who identify less strongly. The particular facet being
identified with will vary from study to study as researchers focus on different
aspects of the interest. For example, one researcher may study identification
with the fan interest itself (e.g., “I strongly identify with anime”), a construct
referred to as “fanship.” Another researcher may assess identification with other
fans who share the same interest (e.g., “I strongly identify with other fans in the
anime community”), a construct referred to as “fandom.”
At first glance, you might think that the distinction between “fanship” and
“fandom” is an exercise in theoretical hair-splitting. After all, people who
identify with other fans probably also identify with the interest itself, right? As it
turns out, while the two constructs are highly correlated, they are far from
perfectly correlated and can be shown to be empirically distinct (Reysen &
Branscombe, 2010). For instance, fanship and fandom predict different fan
behaviors (e.g., Edwards et al., 2019). This being the case, a study which only
assesses fanship while ignoring fandom will necessarily get an incomplete
picture of the factors which predict fan behavior. Nevertheless, most fan studies
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assessing fanship do not also assess fandoma trend which, fortunately, has
been changing over time.
We’ll continue to discus the constructs of fanship (see Chapter 15) and
fandom (see Chapter 7) later in this book. For now, we’ll shift our focus to some
of the ways fanship and fandom have been assessed to give the reader a feel for
how scholars empirically distinguish highly-identified fans from less-identified
ones.
In their approach to measuring fan identity, Daniel Wann and Nyla
Branscombe (1993) drew upon the social identity perspective, which posits that
the groups to which we belongfrom our national identity down to the sport
teams we cheer forimpact our self-esteem (Tajfel & Turner, 1979; Turner et
al., 1987). They construed an eight-item measure to assess the extent to which
their participants identified with a sport team, using a scale ranging from not
important to very important to answer questions like “How important is being a
fan of [insert team] to you?This Sport Spectator Identification Scale (SSIS) is
the most frequently-used measure of team identification in psychology, although
it’s not without its drawbacks. For one thing, the measure was designed with
sport fans in mind, meaning that some of the items were inapplicable for other
types of fans, like media fans (e.g., “How important is it to you that the team
wins?”). In response to these concerns, researchers would later develop fandom-
general measures of fanship inspired by the SSIS (Reysen & Branscombe, 2010).
The SSIS is not the only measure of fan identification to be derived from, or
applied to, sport fans in particular. Trail et al. (2003) based their points of
attachment scale on the idea that varsity sport fans may identify with different
aspect of a sport beyond the team. Their measure assesses:
! identification with players (e.g., “I am a big fan of specific players
more than I am a fan of the team”)
! identification with teams (e.g., “Being a fan of [insert team name] is
very important to me”)
! identification with coaches (e.g., “I am a big fan of Coach [insert
name]”)
! identification with the sport itself (“[insert sport] is my favorite sport”),
the university (e.g., “I identify with the university rather than with any
specific university team”)
! identification with the level of the sport (e.g., “I am a fan of college
[insert sport] regardless of who is playing”)
One notable flaw with the scale is its failure to assess identification with
other fans (i.e., fandom) despite assessing fan identification with so many other
facets of their interest.
Heere and James (2007) developed a different measure of sport team
identification grounded in the social identity perspective. Their measure includes
six subscales assessing:
! how the participant’s team is viewed by the general public (e.g.,
“Overall, my college football team is viewed positively by others”)
! how participants privately feel about their team (e.g., I feel good
about my college football team)
! the participant’s connection to their team (e.g., “I have a strong sense
of belonging to my college football team”)
! feelings of interdependence with a team (e.g., “My destiny is tied to
the destiny of the college football team”)
! fan-related behavior (e.g., “I am active in organizations that include
mostly fans of my college football team”)
! team-related thoughts and knowledge (e.g., “I am aware of the
tradition and history of my college football team”)
All six subscales were positively associated with fans psychological
commitment to their team, illustrating how the construct of fanship can itself be
broken down into its constituent parts.
More recently, Vinney et al. (2019) developed a measure of fan identity in a
sample of media fans rather than sport fans. Their analyses revealed three
dimensions or aspects of fans:
! extent of enthusiasm (e.g., “How passionate are you about your
favorite television show or movie?”)
! deeper appreciation of the interest (e.g., “Has helped me grow as a
person”)
! interaction with other fans (e.g., “I often talk about my favorite
television show or movie with a friend”).
While identification as a fan was one of the variables assessed in their study,
neither fanship nor fandom were present among the three dimensions of their
model.
Finally, we wrap up this section on fan identification by considering
measures of fandom, or felt connection to one’s fan group. Unlike many of the
fanship scales above, these scales were not designed in the context of fan groups.
Instead, they were adapted from studies of other groups (e.g., racial groups) for
use in fan studies. Such measures include unidimensional measures, such as
Doosje et al.’s (1995) four-item measure (e.g., “I see myself as a [insert group]”),
and multidimensional measures, such as Leach et al.’s (2008) five-dimensional
measure assessing:
! solidarity (e.g., “I feel committed to [insert group]”)
5
! satisfaction (e.g., “It is pleasant to be [insert group]”)
! centrality (e.g., “I often think about the fact that I am [insert group]”)
! individual self-stereotyping (e.g., “I have a lot in common with the
average [insert group] person”)
! ingroup homogeneity (e.g., “[insert group] people have a lot in
common with each other”)
In longer studies, where survey space is at a premium, researchers have also
used single-item measures of fan group identification (“I strongly identify with
other fans in the [insert group] community”) which have proven to be fairly
valid (Postmes et al., 2013; Reysen et al., 2013).
The scales we’ve reviewed in this section illustrate one approach researchers
have taken to meaningfully distinguishing fans from one another: Measuring
differences in the magnitude of their felt connection to their fan interest (or to
other fans). We’ll see these measures return in later chapters, but for now we
turn our attention to another means of differentiating fans: Measuring
differences in their tendency to engage in particular fan behaviors.
Categorizing Fans Based on Behavior
In a 1997 paper, Sutton et al. proposed a model of sport fans to help teams
ensure fan loyalty through rising ticket prices and losing streaks. The model
itself builds upon Wann’s conceptualization of fan identity by categorizing fans
based on whether they engaged in behaviors indicative of low, medium, and
high levels of identification. Low-identification fans tend to spend little money
on the team and are not especially involved in fan activities while medium-
identification fans are the most likely to bandwagon (like a team only when it’s
doing well) and interact with other fans. High-identification fans, in contrast, are
loyal during the team’s more difficult stretches and spending much of their free
time following the team’s exploits. The model ultimately categorized fans based
on their behavior despite labeling these behaviors as indicative of their degree of
team identification.
A few years later, Tapp (2004) proposed a model which similarly
distinguished sport fans based on their attitudinal and behavioral loyalty to their
team. The football fans in their study rated how loyal they considered
themselves to be (an attitude) and indicated how many games they had attended
(behavior). Based on the interaction of these two variables, Tapp proposed four
types of fans:
! “carefree casuals” who scored low in both and for whom football was
mere entertainment
! “committed casuals” who scored high only in loyal attitudes but did
not attend many games
! “repertoire fans” who were low in loyal attitudes but who frequently
attended games of their own team as well as other teams
! “fanatics” who scored high on both indices of loyalty and were avid
collectors of team-related memorabilia.
In this model, fan behavior was thus used to not only categorize fans, but
also to predict behaviors that franchise owners and investors would consider to
be practically useful (e.g., fans’ purchasing of team-related merchandise).
Taking a slightly different approach, Collins and Murphy (2018) proposed a
folk taxonomy based on three key variables: knowledge about the interest and its
history, socializing with others in the context of the object (e.g., talking about it
with others), and passion for the interest, sometimes to an irrational extent. The
authors posited six “types” of fans based on these variables:
! “geeks,” obsessive consumers who share knowledge about the interest
with others
!mavens,” who know more than geeks, but try to appear impartial
when talking about their interest
!alphas,” popular opinion leaders
! “evangelists,” who actively seek to promote their interest
! “fanboys,” who have an irrational passion for their interest
! “haters,” who intensely dislike the object of interest
The model is intuitively appealing and uses the language of fans themselves,
although it suffers from a clear description of how, quantitatively, the three
variables themselves contribute to the six types of fans.
In a final example of a behavior-centered fan typology, Hunt et al. (1999)
developed a model which recognizes five types of sport fans based on the
extremity of their behavior:
! “temporary fans” who don’t identify as a fan but who show interest for
a short period of time (e.g., during a winning season)
! “local fanswho happen to live in close proximity to the team
! “devoted fans” who feel connected to the team (i.e., the team is part of
their self-concept) and who will attend games and buy merchandise
! “fanatical fans” who are connected to the team but maintain important
other connections (e.g., family) and who attend games while painting
themselves in their team colors
! “dysfunctional fanswho are wholly consumed with the team and may
engage in extreme behaviors (e.g., violence to defend the team against
insult or threat)
Hunt and colleagues argue that this typology is a product of both behavior
and motivation, although the above categorization seems far more heavily based
7
on behavior than on motivation. Despite the straightforwardness of the
categories, Samra and Wos (2014) would later streamline the typology down to
just three categories: temporary, devoted, and fanatical fans. It’s also worth
noting that that much of this work has been theoretical in nature, with minimal
empirical evidence to validate the existence and distinctiveness of these
categories.
Categorizing Fans Based on Motivation
The previous model attempted to categorize fans on the basis of the
motivations underlying their fan interest, although it’s debatable how strong a
role fan motivation played in the distinction. A model which directly
differentiates fans on the basis of their underlying motivation was developed by
Wann (1995), whose 23-item measure considered eight different motivations of
sport fans:
! eustress, the extent to which watching sports provides fans with
enjoyable stimulation
! self-esteem
! escape or reprieve from daily hassles
! entertainment
! economic benefits such as gambling
! aesthetic or artistic beauty
! group affiliation
! belongingness with other fans
! the opportunity to socialize with one’s family
American sport fans given the scale rated entertainment, eustress, group
affiliation, self-esteem, and aesthetics as the strongest motivators, respectively.
The resilience of these findings was more recently demonstrated in a sample of
South African soccer and rugby fans who scored similarly high on the same
motivators (Wiid & Cant, 2015).
Others have similarly attempted to differentiate fans on the basis of their
underlying motivation. For instance, Kahle et al. (1996) proposed a model that
would predict fan attendance at a sporting event based on fans’ underlying
motivations. The model suffered from operationalization and interpretation
difficulties, however. For instance, the variable labeled “compliance more
closely reflected the concept of friendship or belonging, the variable labeled
“camaraderie” more closely reflected entertainment, the variable labeled self-
defining experience was perhaps better construed as achievement, and “self-
expressive experience” could more accurately be described as a desire to watch
games live. Nevertheless, it was an attempt to do as Wann had done and
meaningfully distinguish fans based on their underlying motivations.
Milne and McDonald (1999) would later propose their own set of 16
motivations which included, among other motivations, stress release, self-
esteem, social needs, mental well-being needs, aesthetics, and achievement.
Some of these variables overlapped with Wann’s own motivations. Others
included variables posited by Kahle and colleagues. Still others were entirely
novel. The model itself failed to gain much traction, however.
Rhein (2000) likewise constructed a 12-item measure assessing different
facets of German music fans, some of which tapped into fan motivation. The
items included:
! Considering the music to be exciting
! Having knowledge about the music
! Being motivated by escapism
! Feeling that being a fan facilitates talking with others
! Seeing fan activities as a social activity
! Commitment to the fan interest
! Romantic attraction as a result of the fan interest
! Admiration for the interest and those involve in it
! Feeling distinct as a result of the interest
! Feeling a sense of achievement
! Feeling that the interest has changed one’s life
! Feelings of belongingness
A cluster analysis revealed three types of fans based on how high or low they
scored on the scale. As one might predict, fans who score higher on the scale
(and thus were more motivated, or had a wider base of motivations) are more
likely to consume and engage with the music (e.g., memorize lyrics) and to
interact with others who also like the music. While not the purest test of this
association, the results can be framed as evidence that fan motivation can predict
fan behavior.
In a more direct measure of fan motivation, Trail and James (2001) asked
203 U.S. baseball season ticket holders about their underlying motivations. The
measure ultimately assessed nine different motivations driving fanship:
! the desire for achievement (e.g., “I feel like I have won when the team
wins”)
! knowledge (e.g., “I read the box scores and team statistics regularly”)
! aesthetics (e.g., “There is a certain natural beauty to the game”)
! drama (e.g., “I enjoy the drama of a “one run” game”)
! escape (e.g., “Games represent an escape for me from my day-to-day
activities”)
! family (e.g., “I like going to games with my children”)
9
! physical attraction (e.g., “I enjoy watching players who are physically
attractive”)
! physical skills (e.g., “I enjoy a skillful performance by the team”)
! social (e.g., “Games are great opportunities to socialize with other
people”)
Astute readers will note that many of these items overlap with Wann’s
original set, although new variables (e.g., physical skills) were also proposed.
A few years later, Funk and colleagues (2004) proposed a different measure
which looked at 18 antecedents or motivations underlying sport fans’
involvement with women’s basketball:
! interest in basketball (e.g., “My interest in basketball sparked my
interest in the team”)
! interest in players (e.g., “The main reason why I attend is to cheer for
my favorite player”)
! bonding with friends (e.g., “Attending games gives me a chance to
bond with my friends”)
! socialization (e.g., “I like to talk with other people sitting near me at
games”)
! drama (e.g., “I like games where the outcome is uncertain”)
! the team (e.g., “I am a fan of the entire team”)
! community pride (e.g., “My connection to the community is why I like
the team”)
! support of women (e.g., “I attend games because I think it is important
to support women’s sport”)
! role models (e.g., “Players provide inspiration for girls and boys”)
! bonding with family (e.g., “Attending games gives me a chance to
bond with my family”)
! style of play (e.g., “The WNBA style of basketball is a more pure
form of basketball compared to the NBA’s style”)
! customer service (e.g., “I feel like customer satisfaction is important to
the game day staff”)
! excitement (e.g., “The games provide affordable entertainment”)
! knowledge (e.g., “Knowing the rules of basketball helps me to enjoy
the games”)
! vicarious achievement (e.g., “I feel like I have won when the team
wins”)
! wholesome environment (e.g., “There is a friendly, family atmosphere
at the games”)
10
! escape (e.g., “I like attending games because they provide me with a
distraction from my daily life for a while”)
While the scale contains more motivations than we’ve seen in any model so
far, there is also notable conceptual overlap between some of the subscales (e.g.,
socializing / bonding with friends/ family, interest in basketball / interest in
players / interest in the team). Some of the variables also seem unrelated or only
tangentially related to the fan interest (e.g., customer service). Later analyses
suggest that these variables load onto a smaller number of higher-order factors:
attraction, risk, centrality, and self-expression.
Chadborn et al. (2017) constructed a different 14-item measure assessing fan
motivation, this one emphasizing the functions that one’s fan interest provides
for them. The results revealed three dimensions representing the extent to which
one’s fan interest provides them with:
! a sense of purpose in life (e.g., “Provides me with a focus or sense of
purpose”)
! a sense of escapism (e.g., “Provides me with a break from life’s
stresses”)
! social connections (e.g., “Provides me with a chance to expand my
circle of friends”)
The researchers used the scales to test a mediation model wherein the
fandom’s ability to fulfill social needs mediates the link between fans’ fanship
scores and specific fan behaviors (e.g., displaying group symbols). Studies such
as these go beyond merely cataloguing different fan motivations and illustrate
the utility of distinguishing between fans on the basis of their underlying
motivations. The studies also hint at fan motivation as a potentially important
mechanism driving some of the psychological effects previously observed in
fans.
At the risk of belaboring the point, one final model by Todd and Soule
(2018) suggests that three different groups ultimately coalesce around a fan
interest: the fandom itself, the brand community, and the brand public.
Importantly, the authors propose that motivation was one of two variables that
influence this distinction, such that those in the fandom are motivated by
creativity, affiliation, and self-expression, those in the brand community are
motived by admiration and sharing information, and those in the brand public
are motivated by imitation and signaling their interest in uncreative and largely
unsocial ways. In short, alongside the previous study by Chadborn et al. (2017),
recent studies such as these which look at motivation-based typologies
demonstrate the necessity of considering fan motivation in any model attempting
to meaningfully compare fans.
11
Categorizing Fans Based on Stage of Fanship
One final way to distinguish between different types of fans involves
conceptualizing fans as dynamic, rather than static. This means recognizing that,
over time, fans can become increasingly involved in their fan interest and
change in how they engage with it. Such changes may be both theoretically
interesting to researchers and of practical significance to those in marketing or
with a vested interest in fan consumption behaviors (e.g., artists).
Based on the idea that fans can change over time in a predictable fashion and
that fans can be distinguished on the basis of where they are in this transition,
Funk and James (2001) propose a psychological continuum model. In the model,
sport fans’ are expected to increase in the connection they feel with a particular
sport or team over time. The first stage along this continuumawareness
reflects fansinitial discovery of a team or sport. Next, fans become attracted to
the team or sport, which gradually gives way to attachment to the team, where
the team has become meaningful and important to the fan. Finally, at the far end
of the spectrum, fans develop a sense of intrinsic allegiance or loyalty to their
team. The researchers posit that fans at different points in this continuum differ
significantly from one another with respect to the motivations driving their
behavior, the behaviors they engage in, and in the situational factors that are
most impactful to them. For example, Wu et al. (2018) documents how Apple
fans, like sport fans, moved through analogous stages with respect to their
interest in Steve Jobs: Initial exposure to his story, fascination with his
personality, a sense of emotional connection to him, and eventual worship.
Along the way, their motivation and consumption of Apple products shifted to
reflect their movement along the continuum from awareness to allegiance.
Jia et al. (2018) took a somewhat different approach to this progression
approach in their work on fans of singer/actor Wallace Chung. The authors
created a hierarchy of progression that was based more on maturation and the
passage of time than on the extremeness of the fan’s interest over time. The
model starts with causal fans motivated by an interest in play and with little
cognitive or emotional investment. These casual fans become fascinated fans
that gather information and build their knowledge of the fan interest over time.
Fascinated fans may eventually become devoted fans, shifting from fanship into
fandom by joining clubs and communities of like-minded others while gaining a
sense of belonging. The next stage includes dysfunctional fans who excessively
idolize the object of their interest and try to boost the object’s popularity in
extreme or irrational ways. The final step, one which doesn’t reflect an increase
in extremeness or devotion, instead involves maturation and gaining a sense of
perspective when it comes to one’s fan interest, recognizing the importance of
12
avoiding dysfunctional fan behavior (e.g., eschewing extreme parasocial
connection in favor of instead seeing the celebrity as a faraway friend.) As with
many of the intuitively appealing models described in this chapter, the model
raises several important questions, such as whether all fans must necessarily go
through a dysfunctional stage before becoming self-reflecting and maturing in
their interests.
This Book
We’ve considered four different approaches fan scholars have adopted to
categorize and meaningfully distinguish between different fans: how or what
fans identify with (and to what extent), the behaviors fans engage in, fan
motivations, and progression through stages of maturation or devotion as a fan.
As we mentioned earlier, this review should not be taken as a systematic look
at all of the different ways scholars have studied fan groups. Instead, we
consider it to be a testament to the dizzying amount of time and effort scholars
have put into the task of organizing what is known about fans in a way that
allows us to meaningfully compare and contrast fans of all interests. In the
chapters that follow, we will attempt to do justice to this massive body of work
by detailing some of the theory and research behind 28 constructs related to fan
interest, each of which can be thought of as a plausible dimension on which to
differentiate fans. We’ll consider some of the ways these dimensions have been
assessed, research on the utility of these constructs for predicting important fan
outcomes, and places where theory on these constructs overlaps, given the much
broader problem in science of researchers inadequately talking to one another
and comparing notes, leading to countless instances of reinventing the wheel.
In the final chapters of this book, we then attempt to move beyond a review
of what has been done to what we believe is a plausible next step for the field.
We describe a series of studies designed to empirically derive and validate a
model that simultaneously takes many of these different dimensions into account.
In doing so, we hope to not only integrate and improve the state of the discourse
in the field through a common model and vernacular, but also to highlight
numerous areas of potentially fruitful research that may be going unnoticed
while avoiding all of the wheel-reinventing that so-commonly occurs in
especially interdisciplinary fields like fan research.
13
Chapter 1
Magnitude
Fan interests are as diverse as fans themselves. As such, the prospect of
finding dimensions on which to meaningfully compare groups as diverse as
sport fans and model train enthusiasts is a bit daunting. An easily solution is to
consider a dimension so basic that it can easily be applied regardless of what one
is a fan of. In this spirit, we devote the first chapter of this book to the question
of magnitude: Just how big a fan is someone?
Before we begin, lets quickly note that we’re distinguishing (at least
somewhat) the magnitude of one’s fan interest from their sense of fanshipthe
extent to which they explicitly identify as a fan. In reality, these two constructs
are quite highly correlated with one another. After all, those with a strong
interest in something are probably the people most likely to identify with that
same interest. Nevertheless, as these constructs have been investigated
independent of one another in prior research, well consider them separately.
We begin by reviewing the related psychological construct of fan
involvement and its theoretical underpinnings, given that magnitude may be
another way of assessing how involved someone is with their fan interest. We
then review examples of studies where different measures of involvement have
been adapted to the context of fans. Finally, we present some of our own work
in which we take a different approach to assessing the magnitude of a fan’s
interest, namely asking participants whether different magnitude-related labels
(e.g., avid, devout) describe the nature of their fan interest.
Involvement
Zaichkowsky (1985, p. 342) defines involvement as “a person’s perceived
relevance of the object based on inherent needs, values, and interests(for an in-
depth review of the topic in the context of marathon runners see Beaton et al.,
2011). In other words, the extent to which the object has become a part of a
person’s life. And while a definition from the 1980s may seem a bit dated,
theorizing on the topic can be traced back much further. In fact, modern
theorizing on involvement stems from at least two lines of inquiry put forth
decades ago by the renowned researchers Gordon Allport and Muzafer Sherif.
According to Allport, people become involved in activities that have both
hedonic and symbolic value and which become central to their life. This
approach to psychological involvement has proven fruitful in other, non-fan
domains. As Beaton et al. note, however, fan and leisure researchers tend to rely
more on Sherif’s conceptualization of ego-involvement.
14
Sherif and Cantril (1947) argued that the ego is neither innate nor a
personality, but rather is a collection of attitudes connected to the self and
determined by the situations people find themselves in. As they put it, “when
any stimulus or situation is consciously or unconsciously related to them by the
individual, we can say there is “ego-involvement”” (p. 117). Or, to put it simply,
the more psychologically connected we are to a thing (e.g., group, attitude), the
more ego-involvement there can be said to be. As an illustrative example,
moviegoers can be said to be exhibiting greater ego-involvement with a film’s
characters when the characters are similar to themselves, as they can more easily
imagine that they are those characters.
While modern fan researchers rarely trace their roots this far back, various
measures have been developed which assess fan involvement, largely as
conceptualized by Sherif and Cantril. Of note, nearly all of these measures have
assessed fan involvement in the context of sport fans and their involvement with
a particular team. For example, as we mentioned in the introduction, Funk et al.
(2004) put forth a measure assessing 18 different motivations to be a sport fan.
Many of these variables loaded onto factors like attraction, centrality, and self-
expressionfactors which might be considered “ego-involving” or relevant to
the self. Some researchers have, like Funk and their colleagues, similarly
attempted to study fan involvement via multidimensional scales. Others chose to
more directly assess fan involvement as a single dimension. What follows is a
brief review of both types of scales and some of the findings from research
employing them.
Consumer Involvement Profile
Building on research looking at consumer involvement profiles (Laurent &
Kapferer, 1985), Havitz and Howard (1995) examined the stability of an
involvement measure across several seasons for fans of different recreational
activities (windsurfing, skiing, golf). Their measure assessed four subscales of
involvement:
! attraction/importance of the activity (e.g., “Golf interests me”)
! the activity as an informative sign (e.g., “You can tell about a person
by whether or not they golf”)
! consequences of risks related to the activity (e.g., “If my choice
proved to be poor, I would be upset”)
! risk probability (e.g., “I always feel at a loss when choosing golf
courses”)
In addition to finding support for the scale’s four-factor structure, the results
of the study found that, indeed, involvement scores were relatively stable across
seasons. Others using the same scale, however, found a different factor structure.
15
Laurent and Kapferer (1985), for example, found evidence for a five-dimension
structure, while Kyle et al. (2002) observed three factors. In a study of women’s
basketball fans, Kerstetter and Kovich (1997) found that the items only loaded
onto two factors.
Despite concerns about the reliability of the scale’s factor structure, however,
the measure itself and variants thereof have been used across a variety of studies
to assess the association between fan involvement and other important variables.
In a sample of tennis fans involvement was positively correlated with resistance
to change, psychological commitment, fan attraction toward tennis, and
behavioral loyalty (Bee & Havitz, 2010). In another study, involvement
predicted flow experiences and enjoyment of leisure activities (Havitz &
Mannell, 2005). In a sample of Turkish birdwatchers, involvement was
positively related to the centrality of the hobby (e.g., “I would rather go birding
than do most anything else”) and well as dedication to it (e.g., “I find that a lot
of my life is organized around birding;” Çakici & Harman, 2007). And, lest you
think the applicability of this study’s findings was limited only to Turkish
birdwatchers, a study of American birdwatchers found that subscales of the
involvement scale were positively related to commitment, consumptive behavior,
attendance at birdwatching events, and even the ability to correctly identify birds
(Kim et al., 1997).
Personal Involvement Inventory
Somewhat analogous to Havitz and Howard, who adapted their measure of
involvement from research on consumer profiles, Shank and Beasley took a
measure of consumer involvement with specific products and adapted it for use
in fan research. The scale in question was developed by Zaichkowsky (1985)
and asked participants to rate products on a series of bipolar adjectives such as
“relevant/irrelevantor “desirable/undesirable.This measure of participants’
involvement with the products was found to predict consumer behavior (e.g., the
desire to seek out and read information about the product.) Zaichkowsky (1994)
later revised the measure to include two both an affective component and a
cognitive component.
It was this revised, two-dimensional measure that Shank and Beasley (1998)
validated for use as a measure of fan involvement in U.S. sport fans. The
measure was streamlined down to eight items which loaded onto the same
affective (e.g., “exciting”) and cognitive (e.g., “relevant”) dimensions proposed
by Zaichkowsky. The authors found that greater involvement across these two
dimensions was associated with greater fan-related consumption among their
sample of sport fans.
16
Now called the personal involvement inventory, the scale has since been
used in a variety of sport fan studies worldwide, proving itself useful as a
predictor of theoretically and practically important variables. Notable examples
of the personal involvement inventory’s use include:
! In a sample of fans at a U.S. woman’s basketball game, involvement
scores predicted fan satisfaction, salience of fan identity, felt attachment
to the team, and frequency of game attendance (Laverie & Arnett, 2000)
! Fantasy football fansinvolvement scores predicted loyalty to their
favorite team (Dwyer, 2011) and to team identity salience (Larkin &
Fink, 2016)
! In a sample of NASCAR fans, involvement was positively associated
with fans’ identification with the sport itself, repeat purchases, and
consumption of NASCAR-related media (Goldsmith & Walker, 2015)
! Involvement was positively correlated with loyalty, fan identification,
and frequency of sport consumption in a sample of Australian rugby
fans (Stevens & Rosenberger, 2012)
! Involvement scores were predicted by perceptions of a team’s
sophistication and credibility in Greek sport fans (Tsiotsou, 2010)
Enduring Involvement Index
In 1986, Bloch et al. constructed the enduring involvement index which
measures a person’s (1) interest in a product, (2) frequency thinking about a
product, and (3) importance of a product to themselves. Research with this scale
revealed that those who were more involved with a product ultimately had a
greater interest in seeking out information about the product. As a real-world
example, someone in the market for a new computer (i.e., highly-involved)
might seek out more information about the computer (e.g., reading articles,
browsing stores) and even enjoy the search itself.
Bennett et al. (2009) gave the measure to a sample of participants at a
sporting event sponsored by the beverage Mountain Dew. The authors found
that scores on the measure of enduring involvement predicted fan spectatorship
(e.g., consuming more media about action sports), behavioral involvement (e.g.,
talking to others about action sports), sport-related consumption (e.g.,
purchasing action sports apparel), and brand use (e.g., drinking Mountain Dew).
The same measure of involvement has also proven effective in predicting future
game attendance in a sample of Australian rugby fans (Hill & Green, 2000).
Product Enduring Involvement Scale
Akin to several of the measures we’ve already reviewed, Higie and Feick
(1989) developed a scale to asses participants’ involvement with a product. The
scale asked participants to rate items using a series of bipolar continuums (e.g.,
17
“fun not fun,” “tells me about a person shows nothing”). The result was a
two-factor structure consisting of a hedonic component and a self-expression
component, both of which contributed to a person’s involvement with a product.
Those who scored higher on the scale spent more time seeking out information
about the product, talking about the product with others, and trying to
influencing the purchasing decisions of their friends with respect to the product.
As we’ve seen with other measures, fan researchers would adopt the measure
for use with fans, sport and non-sport alike. In a sample of fans attending a
women’s basketball game, involvement scores were positively correlated with
feeling satisfied about the game, fan identity salience, attachment to the team,
and frequency of game attendance (Laverie & Arnett, 2000). In a sample of
Japanese comics fans, Katsumata and Ichikohji (2014) similarly found that fan
involvement was positively related to purchasing and consuming comics. This
same study also revealed that the associations differed depending on the nature
of fan themselves, whether they were artists who made comics for their own
enjoyment or produced comics for profit.
Recreation Involvement
In these last two sections we’ll consider measures that weren’t developed in
the context of consumer research. The first, developed by McIntyre and Pigram
(1992), was constructed specifically to measure peoples’ involvement in
recreational activities across three dimensions:
! attraction to the recreational activity (e.g., “Camping is one of the
most satisfying things I do”)
! self-expression through the activity (e.g., “Camping says a lot about
who I am”)
! centrality of the activity to one’s life (e.g., “I find that a lot of my life
is organized around camping”)
When the scale was given to people hiking the Appalachian trail, their
involvement scores predicted identification with the location of the recreational
activity (e.g., “This trail means a lot to me”) as well as feelings of dependence
on the location (e.g., “Hiking here is more important than hiking in another
place:” Kyle et al., 2003). Similar results were found for individuals sampled in
Cleveland metroparks (Kyle & Mowen, 2005).
Kyle et al. (2007) later added two dimensions to the measure: a social
bonding subscale (e.g., “I enjoy discussing [insert activity] with my friends”)
and an identity affirmation subscale (e.g., “When I participate in [insert activity],
I can really be myself”). When given to samples of campers and fishers in South
Carolina, the five involvement dimensions predicted like satisfaction and
frequency of camping and fishing.
18
Since then, the measure has seen extensive use worldwide and has been
found to be associated with numerous fan-relevant thoughts, attitudes, and
behaviors:
! In a sample of Taiwanese baseball fans, involvement was positively
related to team identification, knowledge of the team, and intention to
watch games (Gau et al., 2019)
! Hargrove (2011) surveyed women in an outdoor recreation program
and found that involvement predicted activity involvement, frequency of
participation, and satisfaction
! In a sample of Greek tennis club members, subscales of recreational
involvement predicted intrinsic motivation to play recreational tennis
(Alexandris, 2012)
! Japanese participants’ involvement with a Korean celebrity was
positively related to intention to visit South Korea (Lee et al., 2008), a
finding similarly found in a sample of Taiwanese participants (Yen &
Teng, 2015)
! In a study of Busan International Film Festival attendees (South
Korea), recreational involvement scores were positively associated with
identity salience, psychological commitment, and loyalty to the festival
(Lee et al., 2016)
! Recreational involvement was associated with purchasing intentions
(Nassis et al., 2012) and with commitment to the team (Tachis & Tzetzis,
2015) in Greek football fans, with word of mouth advertising in Greek
basketball fans (Nassis et al., 2014), and with frequency of consuming
sport-related media in Greek volleyball fans (Zetou et al., 2013)
! Taiwanese baseball fans showed a positive relationship between
recreational involvement and well-being (Pan et al., 2018)
Sport Team Involvement
In this final section on fan involvement we review a study by Shuv-Ami et al.
(2015), who assessed fans’ commitment to a sport team with a measure that
included three items assessing involvement (“I connected and am emotionally
involved with my basketball team,” “My basketball team is important for me,”
“I am involved and interested in my basketball team”). The measure, which also
included subscales related to loyalty, satisfaction, and performance, was
positively associated with positive attitudes toward the team, recommending the
team to others, and intention to consume. Subsequent research using the scale
similarly found that involvement with a sport team positively correlated with
fandom identification, fan satisfaction, optimism, and behavioral loyalty (Shuv-
Ami & Alon, 2020) and with love for one’s team, hate for a rival team,
19
identification with the sport, team loyalty, and willingness to pay a premium
price to watch one’s favorite team (Shuv-Ami et al., 2020).
Magnitude Labels
So far we’ve reviewed a sizable body of research which shows the
importance of involvement when it comes to predicting fan attitudes and
behavior regardless of the specific measure used, the region where the study is
being conducted, or whether the study involves sport fans or non-sport fans.
This chapter, however, is about magnitude of fan interest. While involvement
can be argued to be an imperfect, proxy measure of magnitude, the two concepts
are arguably not one and the same. To this end, we’ll finish this chapter by
considering converging evidence looking at another approach to assessing
magnitude of fan interest: the extent to which fans identify as a big fan of
something.
We begin with research by Vinney et al. (2019), who constructed a measure
of fan identity in two samples of media fans. The measure included three
dimensions, enthusiasm, appreciation, and social interaction, the first of which is
the most presently relevant. Fan enthusiasm consists of three items asking fans
how much they love a particular television show, how passionate they are about
the show, and how big of a fan they are of the show. Scoring high in fan
enthusiasm (magnitude) was ultimately related to the extent to which fans liked
a show and reported being passionate about it.
In a 2017 study of Greek football fans, Yannopoulos (2017) attempted to
meaningfully segment the market of football fans. The author argued that there
are three types of fans:
! ardent fans (e.g., “Football is like a religion to me”)
! rational fans (e.g., “The cost of the game affects my attendance”)
! casual fans (e.g., “I like all types of sports”)
Subsequent cluster analysis on additional data (e.g., fan motivation) found
that the ardent fan label was strongly associated with fanatical behavior,
including consuming more sports and generally being more engaged and
committed fans than those who identified with the “rational” or “casual” fan
labels. In short, like fan involvement, higher-magnitude fans engage in more fan
behaviors and are more passionate, committed fans.
We’ll finish up this section by describing the results of two studies we
conducted to assess magnitude of fan interest using a novel, single-item measure.
The item is based on fans’ willingness to identifying with labels related to the
magnitude of their fan interest. In the first study, we asked U.S. college students
(N = 2,525, 73.6% female; Mage = 22.49, SD = 7.14) to list their favorite fan
interest before completing measures related to that interest. Among those
20
measures was the single-item magnitude scale which asked fans to pick one of
five options, increasing in magnitude, which best described them:
!I have a LOW LEVEL of fan interest or involvement”
!I am SOMEWHAT of a fan”
! “I would describe myself as a MODERATE fan”
! “I regard myself as a DEVOUT fan, as this fandom is important
to me”
! “I regard myself as an AVID fan, as this fandom plays a central role in
my life”
We also next asked participants about the frequency with which they
engaged in specific fan-related behaviors on a 5-point scale (from 1 = not at all
to 5 = very frequently), including:
! Purchasing merchandise (“I purchase and/or wear/display items
associated or identified with the fandom (dvd, toys, clothing, etc.)”)
! Attending gatherings (“I attend meetings, meet-ups, concerts, games,
conventions, or any other gathering associated with the fandom”)
! Talking with ingroup members (“I talk and share with other members
of the fandom”)
! Producing fan-made works (“I find creative inspiration to produce
music, art, fanfiction, or other works based on the fandom”)
! Talking with non-ingroup members (“I share my experiences and/or
fan interest with non-members of the fandom (non-fans)”)
As shown in Table 1.1, the most common label fans applied to themselves
was “devout” (39.8%), followed closely by “moderate” (34.8%) and then by
“avid” (15.5%).
Also shown in Table 1.1, those who used higher-magnitude fan identity
labels engaged in more fan-related behavior. Specifically, those identifying with
the lowand somewhatlabels tended to be comparable to one another while
moderate,” devout,” and avidfans tended to significantly differ from one
another, becoming increasingly involved in fan-related behavior with each jump
in magnitude.
We also examined participants’ scores on a measure of fanship (Reysen &
Branscombe, 2010; see Chapter 15) and fandom identification (Obst et al.,
2002a, 2002b; see Chapter 7) using a 5-point scale from 1 = strongly disagree to
5 = strongly agree. Again, fans identifying with the lowand somewhat
labels tended to be similar while moderate,” devout,” and avid” fans were
significantly different from one another in a linear fashion, with higher fanship
and fandom scores for higher-magnitude fans.
21
Table 1.1
Mean Differences in Degree of Magnitude of Being a Fan
Variable
Low
Somewhat
Moderate
Devout
Avid
n
72
179
879
1004
391
Purchase Merchandise
1.78a
1.99a
2.49b
3.34c
4.04d
Attend Gatherings
1.65a
1.74a
1.89a
2.51b
3.28c
Talk with Ingroup
1.71a
2.01ab
2.16b
2.78c
3.60d
Produce Fan Art
2.13a
2.77b
3.34c
4.14d
4.57e
Talk with Non-Ingroup
2.06a
2.47b
3.02c
3.64d
4.03e
Fanship
2.05a
2.36b
2.81c
3.56d
4.16e
Belonging
3.11a
3.31b
3.69c
4.19d
4.40e
Shared Values
3.00a
3.04a
3.28b
3.67c
3.91d
Emotional Connection
2.91a
2.78a
2.98a
3.41b
3.68c
Influence
2.36a
2.47a
2.39ab
2.66b
3.07c
Conscious Identification
2.38a
2.49a
2.56a
3.21b
3.85c
Global Sense Community
3.04a
3.20a
3.50b
4.02c
4.32d
Note. Means with different subscripts are significantly different (p < .05).
Finally, to disambiguate the association between magnitude and these other
conceptually similar variables, we conducted a factor analysis which included
the 11 fanship items, five items from the sense of community fandom
identification subscale, and the single magnitude item. As expected, the fanship
and fandom items loaded on separate dimensions, in line with prior research
suggesting that while fanship and fandom are related, they are empirically
distinct constructs (i.e., Reysen & Branscombe, 2010). More importantly, the
magnitude item loaded more strongly onto the fanship dimension than it did the
fandom dimension. This finding is in line with what we suggested at the start of
this chapter, that the concepts of magnitude and fanship are conceptually very
similar to one another.
The results of our first study suggest that those using higher-magnitude labels
are more likely to score higher on measures of fanship and fandom. These
findings also suggest that assessing magnitude of fan interest using a single item,
while not ideal, is valid and useful, particularly in circumstances when it is
difficult to use a longer measure (e.g., on longer surveys).
In a follow-up study of U.S. undergraduates (N = 896, 71.5% women; Mage =
20.72, SD = 5.21) we administered the same single-item magnitude measure
along with measures of specific fan behaviors. The measures tapped into
constructs including:
22
! Consuming official content (e.g., “I often watch, read, listen, or
otherwise engage with my fan interest”)
! Consuming fan made content (e.g., “I engage (e.g., watch, read) fan
made material related to my fan interest almost everyday”)
! Buying official merchandise (e.g., “I purchase officially licensed items
associated or identified with my fan interest”)
! Buying fan made products (e.g., “I purchase fan produced products
related to my fan interest”)
! Communicating with other fans in person (e.g., “I often communicate
with other fans of my interest in person”)
! Communicating with other fans online (e.g., “I talk with other
members of the fan community online (e.g., social media))
! Creating fan-made content (e.g., “I spend time creating or working on
videos, music, art or other material involving my fan interest”)
! Attending gatherings (e.g., “I often attend meetings or conventions
involving my fan interest”)
! Word-of-mouth transmission of fan interest to others (e.g., “I mention
this fan interest to others quite frequently”; adapted from Harrison-
Walker, 2001)
Table 1.2
Mean Differences in Behaviors by Degree of Magnitude of Being a Fan
Variable
Low
Somewhat
Moderate
Devout
Avid
n
15
55
371
297
158
Consume Official Content
3.12a
3.89b
4.24b
5.14c
6.08d
Consume Fan Content
2.39a
3.13a
3.20ab
4.09b
5.45c
Buy Official Products
3.11a
3.09a
3.74ab
4.74bc
5.67c
Buy Fan Products
2.53a
2.64a
2.79a
3.47ab
4.48b
Talk Face-to-Face
3.40a
4.00a
3.96a
4.93b
5.65b
Talk Online
2.31a
3.21ab
3.16ab
3.97b
5.08c
Create Fan Content
2.32a
2.77a
2.45a
3.09a
4.35b
Attend Gatherings
2.37a
2.84a
2.62a
3.12a
4.32b
Word of Mouth
2.92a
3.60ab
3.97b
4.99c
5.85d
Note. Means with different subscripts are significantly different (p < .05). 7-
point scale from 1 = strongly disagree to 7 = strongly agree.
23
As shown in Table 1.2, the pattern of results were almost identical to those in
the previous study. Specifically, fans labeling themselves as “low or
somewhat in the magnitude of their fan interest tended to be similar to one
another, alongside “moderatefans. In contrast, “avid” fans scored distinctly
high on most of the behavioral outcomes. The study thus shows that there is a
robust linear relationship between the magnitude of one’s fan interest and their
tendency to engage in fan-related behavior.
Conclusion
In this chapter we reviewed research on the first fan-related dimension from
our list, magnitude. It’s clear from the work reviewed that fan scholars and
marketers alike have been interested since at least the 1980s in devising ways to
measure magnitude of someone’s fan interest. The measures devised include
measures of involvement, scales derived for other purposes (e.g., consumer
behavior), and questions asking fans to indicate which magnitude-related label
most applies to them.
We’ve seen that the magnitude of one’s fan interest is strongly associated
with the way fans think, feel, and behave, with higher-magnitude fans
consuming more, identifying more strongly with, and being more engaged with
the broader fan community. We’ll see this similar trends for many of the other
dimensions in this book, with higher scores predicting stronger fan thoughts,
feelings, and behaviors. Few other dimensions match the simply and
intuitiveness of magnitude, however, which, when you boil it down, is just
asking someone how big a fan they are of something.
24
25
Chapter 2
Participation
In the previous chapter we reviewed the literature on magnitude of fan
interest, not only because a significant body of research shows that magnitude
predicts important outcome variables, but also because the distinction between
high- and low-magnitude fans can be easily recognized across fan groups,
regardless of the interest itself.
In the present chapter, we introduce fan participation, another seemingly
intuitive and obvious variable that lends itself to easy study across fan interests.
Fans participate in their fan interests in a variety of ways, including attending
events, reading and writing fanfiction, creating art, cosplaying, making music
and music videos, hosting local gatherings, and contributing to online forums.
An obvious way to differentiate fans from one another would be to compare
those who engage in some of these behaviors to those who engage in other
behaviors (e.g., fanfiction writers versus cosplayers). Alternatively, one could
focus their attention on a particularly diagnostic or high-impact fan behavior to
better understand the differences between fans who engage in more or less of
that behavior. In fact, it is difficult to whittle down the body of research on fan
participation precisely because so much of the existing fan research does exactly
this, examining similarities and differences between different fan behaviors and
their antecedents and outcomes. Speaking to this point, Kim et al. (2019)
conducted a meta-analysis on a sizable body of sport fan research dedicated
solely to the topic of sport fan game attendance, a single type of fan behavior.1
Since nearly every other chapter in this book examines specific fan behaviors
as an outcome, we’ve decided to approach this chapter in a slightly different
way. Rather than trying to synthesize and condense all of the relevant research
on this topican endeavor which would balloon this chapter’s length and cause
it to overlap with nearly every other chapterwe’ll instead start by briefly
describing a psychological theory used to predict specific fan behaviors. We’ll
then present some of our own research on the subject which, rather surprisingly,
shows that specific fan behaviors are not as useful as one might think when it
comes to understanding what it means to be a fan.
1 It’s understandable that so much research has focused specifically on fans’
consumptive behaviors (e.g., game attendance), given that marketers have a vested
interest in predicting and increasing fan spending.
26
The Theory of Planned Behavior
Icek Ajzen’s theory of planned behavior (1985, 1991) was not designed with
fan groups in mind. Nevertheless, the theory has been instrumental in helping
psychologists better understand and predict fan behavior. In a nutshell, the
theory of planned behavior posits that most day-to-day behaviors are volitional
in nature, usually preceded by a behavioral intention. Such intentions are
predicted by three key variables:
! Attitude toward the behavior: The extent to which your impression of
the target behavior is positive
! Subjective norms about the behavior: The perception that there is
societal pressure to engage in the behavior
! Perceived control over the behavior: The perceived ease or difficulty
of engaging in the behavior.
To better understand the theory, let’s apply it to the prediction of a specific
behavior: donating to charity. If one has a positive attitude toward the behavior
(e.g., giving to charity is good), if they perceive social norms as being favorable
to the behavior (e.g., their friends and family think giving to charity is good),
and if they perceive that it’s within their ability to engage in the behavior (e.g.,
they have the money to spare for a donation), then they are likely to form an
intention to do the behavior (e.g., they intend to give to charity). Ajzen
recognized that these are far from the only variables which can predict a given
behavior, but notes that these three variables are fairly consistently important.
The model has been well-supported empirically, even as researchers continue to
search for additional variables to add to the model’s ability to predict behavioral
intentions (e.g., Ulker-Demirel & Ciftci, 2020).
The theory of planned behavior has been used to predict behaviors as diverse
as riding the bus (Heath & Gifford, 2002) and illegally parking in emergency
lanes (Zheng et al., 2018). It also lends itself quite readily to predicting all
manner of volitional behavior, including specific fan behavior. Even so, the
theory of planned behavior has only rarely been applied to the prediction of fan
behavior. When it has, however, it’s proven rather fruitful. For example,
researchers have found that measuring attitudes, subjective norms, and
perceived control can allow researchers to predict participants’ intention to
revisit a festival in subsequent years (Alonso et al., 2015; Horng et al., 2013).
Others have used the same variables to predict consumption behavior, including
attending a sporting event (Cunningham & Kwon, 2003; Lu et al., 2011), going
to a fan convention (Reysen, Chadborn, & Plante, 2018), or purchasing
merchandise from a celebrity (Chiou et al., 2005).
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In short, those studies which have applied the theory of planned behavior to
fans have shown that fans’ attitudes, perceptions of subjective norms, and
perceived behavioral control can predict the intent to engage in fan-related
behaviors. But if it’s true that psychological variables can tell us something
about fan behavior, can those specific fan behaviors, in turn, be used to tell us
something meaningful and significant about the psychology of the fans who
engage in them?
True Fans
Fans, almost by definition, take the objects of their interest quite seriously.
As such, gauging the authenticity of a self-proclaimed fan’s interest is important
to many fans (e.g., see Plante et al., 2020 for a review). It’s the reason why
bandwagon fans of a team are held in low regard by lifelong fans and why
gamers often decry “fake gamer girls” as a threat to their fandom.
Given the importance of establishing authenticity for fans, as well as the
possibility that fans may rely on behavioral credentials to establish their
authenticity, we conducted a set of studies examining whether certain behaviors
are perceived by fans as differentiating “true” fans from casual, bandwagon, or
“wannabe” fans. Participants in the study (N = 219, 78.1% women; Mage = 23.21,
SD = 8.22) were U.S. undergraduate students. At the beginning of the semester
they completed a prescreening measure assessing whether they identified as a
fan of sport (n = 53), music (n = 49), media (n = 74), or a particular hobby (n =
43). Participants were later asked to rate the extent to which 22 specific traits
and behaviors were seen as representative of true fans (see Table 2.1 for the list
of items). Responses were made on a 7-point Likert-type scale from 1 =
unimportant to 7 = important.
As shown in Table 2.1, participants scored above the scale’s midpoint (i.e.,
4) on 11 of the items. In other words participants’ felt that these 11 traits and
behaviors in particular were especially indicative of what it means to be a true
fan. Rather tellingly, most of these higher-scoring items were traits, not specific
behaviors. In fact, many specific behaviors like club membership and spending
money on one’s interest were below the midpoint of the scale, indicating that
they were seen as not especially important as an indicator of being a true fan.
We next examined whether these traits and behaviors held together as
indicators of true fan status by conducting a principal components analysis with
an oblimin rotation. The eigenvalues and scree plot suggested that there were
four factors:
! Participation in the fan interest (items 7, 11, 12, 13, 14, 15, 16)
! Passionate commitment to the interest (items 1, 2, 3, 4, 5)
! Knowledge and evangelism about the interest (items 6, 8, 9, 10)
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! Willingness to sacrifice for the interest (items 17, 18, 19, 20, 21, 22)
Table 2.1
Means (Standard Deviation) of Important Characteristics of a “True
Fan”
Item
Mean (SD)
Item 1. Enthusiastic
6.41 (1.02)
Item 2. Loyal
6.21 (1.24)
Item 3. Passionate
6.19 (1.32)
Item 4. Committed
6.15 (1.24)
Item 5. Devoted
6.07 (1.34)
Item 6. Know a great deal of information about the fan
interest
5.11 (1.83)
Item 7. Emotionally connected with fan interest
5.09 (1.76)
Item 8. Try to get other friends to also like fan interest
4.69 (1.87)
Item 9. Spend large amounts of time on fan interest
4.48 (2.02)
Item 10. Spend a number of years as a fan of the
interest
4.26 (2.11)
Item 11. Obsessed
4.25 (1.99)
Item 12. Attendance at conventions
3.89 (2.03)
Item 13. Member of fan club (in person)
3.80 (2.05)
Item 14. Member of fan club (online)
3.78 (2.04)
Item 15. Create fan artifacts (e.g., art, stories)
3.41 (1.98)
Item 16. Write fan mail
3.34 (2.04)
Item 17. Willingness to spend large amounts of money
on fan interest
3.16 (2.08)
Item 18. Critique and write about the fan interest (e.g.,
online blogs)
3.09 (2.07)
Item 19. Willingness to skip work to engage in fan
interest
3.06 (2.06)
Item 20. Willingness to give up relationships to engage
in fan interest
2.55 (1.96)
Item 21. Only have friends that are also fans of the
same interest
2.51 (1.98)
Item 22. Willingness to incur bodily harm for the fan
interest
2.34 (1.99)
Note. 7-point Likert-type scale from 1 = unimportant to 7 =
important.
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Finally, we conducted a MANOVA with participants type of fan interest
(i.e., sports, music, media, hobby) as the independent variable and the four
factors (i.e., participation, passionate commitment, knowledge/evangelism, and
sacrifice) from the principal components analysis as the dependent variables.
The analysis revealed that scores on the four factors did not differ by the type of
fan interest the participant had. To put it another way, what it means to be a true
fan is similar across fan interestsand appears to have less to do with specific
behaviors than it does with the traits or personality of the fan themselves.
In a follow-up study, we asked U.S. undergraduates (N = 209, 74.6% women;
Mage = 23.20, SD = 6.74) to rate the same items from the previous study, but to
do so with respect to themselves, rather than for fans in general (e.g.,
“Regarding my favorite fan interest, I would say…” “I am devoted,” “I write fan
mail,” “I am obsessed”). Participants again indicated their interest in sport (n =
52), music (n = 43), media (n = 87), or a hobby (n = 27), and, again, these
groups did not substantively differ with respect to the four “true fans” factors.
Similar to the previous study, even when rating themselves and their own fan
behaviors, passionate commitment (M = 5.45) and knowledge and evangelism
(M = 4.50) were seen as stronger indicators of being a true fan than participating
in specific fan behaviors (M = 3.29) or being willing to sacrifice (M = 2.78).
In a final study, we asked another sample of U.S. undergraduates (N = 896,
71.5% women; Mage = 20.72, SD = 5.21) to indicate their favorite fan interest
and to complete a variety of measures related to their engagement in fan
activities. Like in the previous studies, participants completed a measure
assessing indicators of being a true fan, which again found that passionate
commitment (M = 5.24) and knowledge and evangelism (M = 4.20) were more
important than participating in specific fan behaviors (M = 3.34), and
willingness to sacrifice (M = 2.47) when it comes to what participants feel
makes them a “true fan.”
We also administered a short, 10-item measure of participants’ motivations
for being a fan (Schroy et al., 2016). Following the prompt “I am a fan of this
interest because of…”, participants rated the extent to which 10 different
motivations explained their fan interest (e.g., “Belongingness (social reasons),”
“Eustress (positive stress),” “sexual attraction”). These motivations were based
on Wann’s (1995) motivations (discussed in the introduction chapter) with two
additions: attention and sexual attraction. To examine which motivations
uniquely predict the four true fan dimensions, we conducted a series of four
regressions. In each regression we allowed the 10 motivations to simultaneously