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CONSUMER COMPULSIVE BUYING AND HOARDING IN A WORLD OF FAST
FASHION
Kathleen M. Higgins
Thesis Prepared for the Degree of
MASTER OF SCIENCE
UNIVERSITY OF NORTH TEXAS
August 2014
APPROVED:
Tammy Kinley, Associate Professor/Chairperson-Merchandising & Digital Retailing
Jessica Strubel, Lecturer-Merchandising & Digital Retailing
Christy A. Crutsinger, Professor-Academic Affairs, Vice Provost for Faculty Success
Higgins, Kathleen M. Consumer compulsive buying and hoarding in a
world of fast fashion. Master of Science (Merchandising), August 2014, 60 pp., 6
tables, 3 figures, references, 46 titles.
The purpose of this study was twofold: (1) to determine the relationships
between social media, fashion interest and fast fashion involvement and whether
these psychographic variables affect propensity for compulsive clothing buying
and (2) to determine whether a relationship exists between compulsive buying
and propensity toward hoarding.
Data was collected through consumer panel from Qualtrix. Screener
questions ensured that all respondents were adult females with an interest in
fashion. Responses yielded 232 usable surveys, which were analyzed using
SPSS software.
Social media was found to be positively related to fashion interest, fast
fashion involvement, and compulsive clothing buying. Compulsive clothing
buying was found to be positively related to all three compulsive clothes hoarding
symptoms: clothing clutter disorganization, clothing acquisition, and difficulty
discarding clothing.
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ACKNOWLEDGEMENTS
I would like to show my greatest appreciation and thanks to Dr. Kinley who not only
patiently guided my study but generously provided funding. Without her shared
knowledge and expertise this thesis would not have been possible.
Additionally I would like to thank my committee members Dr. Strubel and Dr.
Crutsinger for their insightful comments and feedback. Finally my deepest and heartfelt
appreciation goes to my friends and family, especially my parents for their unwavering
support and encouragement throughout this process.
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TABLE OF CONTENTS
ACKNOWLEDGEMENTS ................................................................................................................... i
LIST OF TABLES ....................................................................................................................... iv
LIST OF FIGURES ...................................................................................................................... v
Chapter I ....................................................................................................................................... 1
Purpose of the Study ................................................................................................................... 2
Theoretical Framework ............................................................................................................... 3
Hypotheses ................................................................................................................................... 7
Operational Definitions ................................................................................................................ 8
Chapter II .................................................................................................................................... 10
Review of Literature .................................................................................................................. 10
Consumer’s Fashion Interest ................................................................................................... 10
Fashion interest. ........................................................................................................................ 10
Fast fashion. ............................................................................................................................... 10
Fast fashion involvement. ......................................................................................................... 11
Compulsive Buying .................................................................................................................... 14
Compulsive clothing buying framework ....................................................................................... 14
Compulsive clothing buying model. ............................................................................................. 15
Social Media ............................................................................................................................... 16
Social Media Envy. .................................................................................................................... 17
Compulsive Hoarding ................................................................................................................ 18
Chapter III ................................................................................................................................... 21
Methodology ............................................................................................................................... 21
Instruments ................................................................................................................................. 22
Social media usage. .................................................................................................................. 22
Fashion interest. ........................................................................................................................ 22
Fast fashion involvement. ......................................................................................................... 22
Compulsive clothing buying instruments. .................................................................................... 22
Compulsive buying scale. ......................................................................................................... 23
Compulsive hoarding instruments. .......................................................................................... 23
Saving inventory revised (SI-R). .............................................................................................. 23
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Clutter image rating scale (CIR). ................................................................................................... 23
Analysis Plan .............................................................................................................................. 24
Chapter IV ................................................................................................................................... 25
Results ........................................................................................................................................ 25
2012 Census Data Comparison .............................................................................................. 27
Analysis of Hypotheses ............................................................................................................ 29
Data Analysis ............................................................................................................................. 30
Chapter V .................................................................................................................................... 37
Conclusions and Discussion .................................................................................................... 37
Discussion ................................................................................................................................... 38
Contributions to Research ........................................................................................................ 42
Recommendations ..................................................................................................................... 43
Limitations and Further Research ........................................................................................... 43
Appendix A ................................................................................................................................. 45
Appendix B ................................................................................................................................. 47
References ................................................................................................................................. 55
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LIST OF TABLES Page
1. Hypotheses and Tests ...............................................................................................24
2. Demographic Characteristics of Respondents ...........................................................26
3. Social Media Usage....................................................................................................29
4. Pearson Product Moment Correlations Between Survey Variables and Fashion
Interest........................................................................................................................31
5. Pearson Product Moment Correlations Between Compulsive Clothing Buying
Tendency and Survey Variables ................................................................................32
6. Analysis of Variance Findings for Compulsive Clothing Buying Tendency and Survey
Variables.....................................................................................................................33
7. Hoarding Profile of Study Participants........................................................................35
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LIST OF FIGURES Page
1. Compulsive Hoarding model based on Frost & Hartl, 1996, and Frost & Skeketee,
1998 .................................................................................................................................5
2. Compulsive Clothing Buying Model (Johnson & Attmann, 2009).................................5
3. Compulsive Buying and Hoarding of Clothing Model ..................................................8
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Chapter I
As storage is a critical dimension of consumption (Cwerner, 2001),
overconsumption can sometimes lead to an overwhelming accumulation of clothing and
lack of closet space. Specifically, unworn clothing can potentially cause a real storage
problem for consumers. Because of rapid fashion cycles, what is “in” is always
changing, causing consumers to feel pressure to continually update their wardrobes
(Cwerner, 2001). As consumers purchase clothing that is deemed fashionable, they
then either hold onto or discard old clothes that are considered “unfashionable” (Banim
& Guy, 2001). Still, despite what is currently deemed fashionable, the wardrobe often
contains both the up-to-date fashions and the out-of-date fashions, becoming a clothing
landfill. The wardrobe consists of both worn and unworn clothing, which women
consider each day when constructing their visual selves (Bye & McKinney, 2007).
These clothes become more than physical objects and take on the role of self-definition
for the wearer (Bye & McKinney, 2007). However, these kept unworn clothes have
been considered a sign of excess consumer culture, and could even suggest a
shopping addiction, such as compulsive shopping or buying (Banim & Guy, 2001).
According to a survey conducted by Woodward (2008), 12% of women’s wardrobes are
considered inactive, 51% have potential to be worn, and only 37% are actually active.
Further, as these inactive clothes are kept instead of discarded, in the extreme, it could
be argued these are hoarding tendencies.
The wardrobe, a physical space where both worn and unworn clothing is stored
(Cwerner, 2001), is designed for the ordering of clothing (Woodward, 2008). A well
organized wardrobe has become a symbol of status (Bye & McKinney, 2007). Media
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and television shows also emphasize the importance of purging old and unworn clothing
in one’s closet and embracing an updated look and new self (Bye & McKinney, 2007).
This obsession with order and space management has also sparked new
companies with services ranging from seasonal storage to closet consultants who
attempt to enable people to maintain control over their wardrobes (Cwerner, 2001).
Research suggests that time management has prompted the urge to simplify one’s life
through more advanced organizational practices (Cwerner, 2001). With clothes well
organized and easily accessible one can more easily maintain their fast paced lifestyles
(Cwerner, 2001). The study seeks to investigate developing sociological de-cluttering
trend and how it specifically relates to one’s wardrobe.
An additional trend influencing the world of fashion is the use of video bloggers
(vloggers) for the endorsements of products (Wood, 2012). Vloggers, specifically those
categorized as beauty vloggers, are known for sponsoring clothing in videos referred to
as “clothes hauls.” In these video posts, beauty vloggers, also referred to as floggers,
describe clothes they have either purchased recently or have been given for free in
exchange for endorsement. These floggers have accumulated millions of loyal and
trusting online subscribers/followers making them optimal endorsers. Thus, the present
study attempts to further investigate the impact these social media marketing
techniques have on the consumer’s decision to make compulsive purchases.
Purpose of the Study
Ultimately, this study seeks to determine why women particularly, are reluctant to
discard clothing. Is it because fast fashion makes it easy to acquire a lot of different
styles relatively inexpensively? Because a simple interest in fashion creates an
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enjoyment of clothing acquisition akin to reaction? Is there a social media influence with
the prevalence of fashion blogs and visual venues such as Pinterest? Therefore, the
purposes of this study are: (1) to determine the relationships between social media,
fashion interest and fast fashion and whether these psychographic variables affect
propensity for compulsive buying and (2) to determine whether a relationship exists
between compulsive buying and propensity toward hoarding.
Hoarding symptoms include clutter disorganization, acquisition, and saving
tendencies which are associated with excessive positive emotion with low-value
possessions (approach) and anxiety, fear, or sadness associated with loss of
possessions (avoidance). Since women often have an emotional attachment to clothing
(Banim & Guy, 2001), do they tend toward hoarding?
Theoretical Framework
Compulsive hoarding has three main symptoms: excessive clutter, excessive
acquisition, and difficulty discarding (Frost, 2010). First, excessive clutter has the
potential to hinder the use of a space for its intended purpose. Second, hoarders tend
to excessively acquire both free items and purchased items, and are also commonly
associated with compulsive buying. Finally, the tendency to have difficulty discarding or
the saving of worthless or worn-out possessions is also common (Steketee & Frost,
2003). These symptoms are measured using the Saving Inventory-Revised (SI-R)
Survey (Frost, Steketee, & Grisham, 2004). These same hoarding concepts of
possessions and living space will be applied specifically to clothing and the wardrobe.
As previously mentioned, wardrobe refers to the space where all clothing is stored. As
one’s clothing exceeds the wardrobe’s capacity, this behavior could suggest compulsive
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clothing hoarding. The hoarding framework is provided in the Compulsive Hoarding
Model (Figure 1). For the purposes of the present study, this model was adapted to
only include the final hoarding symptom variables: clutter disorganization, acquisition,
and saving. This study strives to only determine the presence of participants hoarding,
if any, and not the behavioral tendencies associated with the disorder. Thus, the
preceding variables, information processing, beliefs, family/individual history, approach,
and avoidance were not included. Instead the present study is focused solely on
whether compulsive clothing buyers also have clinically relevant hoarding symptoms.
As many as 75% of people who hoard also engage in compulsive buying
tendencies (Frost, Tolin, Steketee, Fitch, Selbo-Bruns, 2009). Thus the Compulsive
Clothing Buying model developed by Johnson and Attmann (2009) was implemented,
which measures a shoppers compulsive buying tendencies specifically in the context of
clothing (Figure 2).
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Figure 1: Compulsive Hoarding model based on Frost & Hartl, 1996, and Frost &
Skeketee, 1998
Figure 2: Compulsive Clothing Buying Model (Johnson & Attmann, 2009)
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Johnson and Attmann (2009) applied Mowen and Spears’ (1999) hierarchical
approach to analyze the relationships between compulsive buying and additional
variables previously associated with compulsive buying. Johnson and Attmann (2009)
include the variables neuroticism, materialism and fashion interest, and focused on
compulsive buying in the context of clothing. However, for the purposes of this study,
this model was narrowed even further to only include fashion interest in the Clothes
Hoarding Model (Figure 3). Neurtoticim and materialism were eliminated from the final
adapted model because they were classified as personality traits. However, fashion
interest was retained because of the focus on clothing overconsumption. This study
strives to identify behaviors associated with compulsive buying. Johnson and Attmann
(2009) also suggest that the rapid pace and variety of clothing choices available with
fast fashion provide a particularly attractive shopping experience for those who shop
compulsively. Thus, an additional variable, fast fashion involvement, retrieved from
Choi, Liu, Liu, Mak, & To (2010) was added to the Clothes Hoarding Model to measure
fast fashion’s potential influence on compulsive clothing buying behavior. Social media
was also included as a potential contributing factor to fashion interest and fast fashion
involvement. The speed and nature of fast fashion is complimented by the instant
exchange of information through social networking. Additionally, studies have shown
the impact of social media on the fashion consumer’s purchasing decisions (Tellefen,
Rosner, Osofsky, Caswell, 2013).
Although no significant gender differences have been found in the hoarding
symptoms of clutter and difficulty discarding, women have been found to have higher
acquisition levels (Frost & Hristova, 2011). Research suggests this gender
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differentiation could be due to cultural expectations of women to purchase more items
and to experience emotional satisfaction from shopping (Frost et al., 2004). However,
Frost, Steketee & Tolin (2011) found that more women met the criteria for compulsive
buying (64.8%) when compared to men (48%). Thus, it was decided to focus the
present research on women consumers only. Although research has been conducted
investigating the correlations of compulsive shopping and hoarding tendencies, no
research has been done explicitly in the context of women’s clothing.
Hypotheses
The cultural trend toward social media participation continues to grow. This new
communication channel enables a social discussion and critique that can have
participation of a great number of people beyond the immediate social circle. Social
networks such as Facebook, Pinterest and Instagram are influencing fashion consumer
purchasing behaviors (Tellefen et al., 2013). Therefore, the following hypotheses will be
tested:
H1 Participation with Social Media will affect Fashion Interest
H2 Fashion Interest will affect Fast Fashion Involvement
H3 The following tendencies of Compulsive Clothing Buying will be affected by
H3a Social Media
H3b Fashion Interest
H3c Fast Fashion Involvement
H4 Propensity toward Compulsive Clothing Buying will be positively related to the
hoarding tendencies:
H4a Wardrobe Clutter Disorganization
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H4b Clothing Acquisition
H4c Reluctance to Discard Clothing (saving)
Figure 3: Compulsive Buying and Hoarding of Clothing Model
Operational Definitions
Fashion interest. Fashion interest refers to the consumer’s level of interest and
importance for fashion apparel products (Johnson & Attmann, 2009).
Fast fashion. The fast fashion strategy allows retailers to provide the most
current and emerging trends quickly and rapidly to consumers (Choi, et al., 2010). Fast
fashion clothing is produced within a compressed lead time (Johnson & Attmann, 2009)
in order to match supply with uncertain demand (Cachon & Swinney, 2011).
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Fast fashion involvement. A consumer’s involvement level varies based on
the extent of their decision process and information searching (Choi, et al., 2010).
Different involvement levels affect the consumer’s comprehensiveness and ultimate
purchasing decision (Choi, et al., 2010).
Compulsive clothing buying. Compulsive buying is an abnormal form of
consumer behavior, in which the consumer experiences strong and uncontrollable urges
to shop and make purchases. Compulsive buying is often done to compensate for
unhappy events and/or low self-esteem. As the shopping experience raises the mood
of the consumer, it is only temporary, and is usually followed by feelings of shame or
depression (Johnson & Attmann, 2009).
Clutter disorganization. A symptom of hoarding, severe clutter and
disorganization of a living space results in precluded activities for which the space was
intended (Frost, et al., 2004). For the purposes of this study, the concept of clutter and
disorganization will be applied to the individual's clothing and wardrobe.
Acquisition. One of the three main hoarding symptoms, acquisition refers to an
extreme accumulation and failure to discard possessions that seem to be useless or of
little value (Hartl, Frost, Allen, Deckersbach, Steketee, Duffany, & Savage, 2004). This
study focusses only on the possession of clothing.
Saving. Saving, the final hoarding symptom, refers to difficulty discarding
possessions (Frost, et al., 2004). Those who hoard also tend to place higher value on
possessions making discarding very difficult. For this study, this variable will refer to
women’s tendencies to hold onto inactive and unworn clothing.
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Chapter II
Review of Literature
Consumer’s Fashion Interest
Fashion interest.
O’Cass (2004) explains that the effect of product interest and involvement is
investigated to more thoroughly understand purchasing and consumer behavior.
Involvement refers to the consumers’ interaction with the object (O’Cass, 2004), and
fashion clothing involvement specifically focuses on clothing interaction. A consumer’s
level of fashion clothing involvement is determined by the extent to which the consumer
considers this interaction to be a central, meaningful, and engaging activity in their life
(O’Cass, 2004). It is important to note that fashion clothing means different things to
different people, and therefore form different levels of attachments and interests
(O’Cass, 2004). Furthermore, when consumers consider fashion to be of great
importance and interest, they are thought to have high levels of fashion product
involvement (Yurchisin & Johnson, 2004).
Fast fashion.
Fast fashion emphasizes the efficiency and speed of production of fashion-
focused clothing at the lowest possible price for the consumer. Low prices make it easy
for the consumer to impulsively purchase items regardless of whether or not they are
truly needed. Today’s fashion consumer is interested in rapidly changing trends and is
quickly bored with current styles. With constant technological access, new fashions are
constantly evolving and developing, almost instantly exposing consumers to the latest
trends. Fast fashion trends are primarily directed towards young women, who glean
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fashion information through the internet and fashion magazines (Claudio, 2007). Since
young consumers are probably the most concerned with trends compared to other age
groups, they are also the most avid fast fashion shoppers (Morgan & Birtwistle, 2009)
These retailers target the young female population because they are the most
concerned with being up to date and fashionable (Claudio, 2007). Because these
clothes are so inexpensive, consumers are able to purchase more items, keeping their
wardrobe diverse and versatile. However, as the trends are continually evolving, are all
clothes in one’s wardrobe being worn and utilized, or are they tucked away and quickly
replaced?
Fast fashion involvement.
O’Cass (2004) refers to fashion involvement as the extent to which the consumer
views fashion as a central and meaningful activity in their life. Different levels of
involvement influence the consumer’s decision and information search in regards to fast
fashion and fast fashion brands (Choi, et al., 2010). According to Choi, et al. (2010), a
higher level of fast fashion involvement does encourage consumers to further evaluate
fast fashion brand extensions. The rapid cycles of fast fashion is often accredited to the
sociocultural lifestyle changes of the consumer, who is continuously aware of the latest
fashion trends and as a result feels compelled to adapt to the reality in an affordable
manner (Gabrielli, Baghi, & Codeluppi, 2013). Fast fashion attracts the consumer who
no longer makes purchases out of necessity. Its efficient production process allows for
low prices and continued renewed selection in stores. With social media, both
marketers and consumers are able to upload, share, and exchange images of the latest
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fashion in real time further propelling the fast fashion process.
The role of clothing.
For many women, clothing serves as a direct representation of their personality
(Bye & McKinney, 2007). Individuals desire acknowledgment from others that they
have achieved self-definition (O’Cass, 2004). To achieve this sense, individuals engage
in behaviors associated with symbols, such as purchasing, wearing, and displaying
clothing, until the individual feels they have both convinced others and themselves of
their desired self-definition (O’Cass, 2004). Bye & McKinney (2007) suggest that the
contents of the wardrobe allow “women to piece together their visual self-representation
to the world while meeting their functional, emotional, and aesthetic needs” (p. 484). As
a result, the wardrobe becomes a clothing library allowing the owner to combine its
contents to create their final presentation of self (Cwerner, 2001). Bye & McKinney
(2007) explain that meaning can be transferred from the clothing to the individual. The
meaning associated with the clothing interferes with the process of discarding. For
separation from self to take place, the individual must remove the meaning from the
object. However, most extant research focuses on the self-defining role of worn
clothing versus the role of stored clothing (Cwerner, 2001).
Elliott (1994) proposed that consumers may even be compelled to compulsively
purchase clothing in order to achieve a more accurate representation or even to create
an idealized self. “Consumers may compulsively buy products such as clothing to
match their subjective perceptions of themselves with a socially desirable or required
appearance as a self-defining goal” (Elliott, 1994, p. 395). Clothing products are used
as symbols of self-completion because they may communicate an ideal self-image or
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increase self-confidence (Yurchisin & Johnson, 2004). According to Johnson and
Attmann (2009), clothing is a material possession that holds a significant status and can
symbolize an individual’s identity.
The process of shopping for clothing in itself is a highly emotionally charged
experience for the consumer (Bye & McKinney, 2007). From the very beginning of the
clothing relationship, an emotional connection has been created and has the potential to
deepen over time and can be the cause of conflict when a garment inevitably needs to
be discarded (Bye & McKinney, 2007). This deepened relationship suggests that
clothing has personal meaning for the owner that extends past whether it is being worn
or stored (Banim & Guy, 2001).
Banim and Guy (2001) explored women’s relationships with their clothes,
specifically unworn clothing. They outlined three inter-dependent views based on these
relationships, “the woman I want to be,” “the woman I feel I could be,” and “the woman I
am most of the time.” It was in these three ways they found that women used clothes to
define themselves. Banim and Guy (2001) gathered research from fifteen women who
provided an essay reflecting their fashion interests, a two week clothing, and were
interviewed alongside their wardrobes. When investigating the role of kept clothing,
women referred to their clothes in terms of changing and enduring aspects of self.
Thus, unworn clothing was broken into three categories: discontinued identity,
transitional identity, and continued identity (Banim & Guy, 2001). Discontinued identity
refers to an identity the owner no longer feels represents them; these associations
related to these items are usually negative. Transitional identity refers to the clothes
that the owner is not currently wearing but still considering the item’s fate. Continued
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identity are clothes that the owner will always keep but are likely to never wear (Banim
& Guy, 2001).
Compulsive Buying
Compulsive buying is chronic recurring buying that becomes the initial response
to negative events or feelings (Park & Burns, 2005). The tendency for the compulsive
consumer to make purchases is triggered by stress and anxiety. The purchases are
meant to temporarily alleviate these negative feelings, however these same purchases
are often followed by additional negative feelings of shame or depression. Additional
outcomes may include family and/or marital discord, anxiety, frustration, and financial
debt (Christenson, et al., 1994).
Like compulsive shoppers, hoarders also often experience repercussions for their
behavior. Both are very deconstructive tendencies but are meant to make the
buyer/hoarder feel better temporarily. Because these feelings of relief are only
temporary, the buyer/hoarder has to continually purchase possessions to escape
negative thoughts and anxiety (DeSarbo & Edwards, 1996). Compulsive buying differs
from impulse buying which is specific to one product at a particular moment.
Compulsive buying is ongoing and focuses on the entire buying process, not just the
purchases (Park and Burns, 2005).
Compulsive clothing buying framework
Mowen and Spears’ (1999) hierarchical approach consisting of cardinal, central,
and surface traits was used to analyze the relationships between compulsive buying
and associated variables: neuroticism, materialism, and fashion interest. Neuroticism
“contrasts even temperedness with negative emotionality” (Johnson & Attmann, 2009,
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p. 397). It is also related to cognitive and behavioral styles that are associated with the
tendency to experience distress. Someone who has high neuroticism is considered to
be anxious and worrisome (Johnson & Attmann, 2009). Richins (2004) defines
materialism as the “importance ascribed to the ownership and acquisition of material
goods in achieving major life goals or desired states” (p. 210). Material values
encompass three main domains: the use of material possessions to measure the
success of oneself and others, the centrality of possessions in a person’s life, and that
the acquisition of possessions lead to happiness and life satisfaction. Overall, an
extreme materialistic person believes self-fulfillment is achievement through material
possessions. Fashion interest is one of four dimensions that make up fashion
orientation (Gutman & Mills, 1982). Further research by Park and Burns (2005), found
that fashion interest was the only one of the four that correlated with compulsive
shopping, therefore Johnson and Attmann (2009) only included this variable in their
study.
Compulsive clothing buying model.
Mowen and Spears’ (1999) cardinal traits, also referred to as personality traits,
are defined as “the basic underlying predispositions of individuals that arise from
genetics and early learning history” (p.410). Johnson and Attmann (2009) employed
neuroticism as the only cardinal trait. Central traits were defined as, “narrower in
application and emerging from the interplay of cardinal traits, the culture which an
individual lives, and the learning history of the individual” ( p.410). Materialism and
fashion interest were employed as the central traits. Surface traits result from the
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outcomes of both the cardinal and central traits (Johnson & Attmann, 2009).
Compulsive clothing buying is a surface trait.
According to Johnson and Attmann (2009) studies have shown that both
consumer fashion interest (Park & Burns, 2005) and apparel product involvement
(Yurchisin & Johnson, 2004) have been highly correlated with compulsive buying. The
pressure of the fast fashion market makes shoppers particularly vulnerable to these
compulsive purchasing tendencies (Johnson & Attmann, 2009). Because fashion is
cyclical and changing at such a rapid pace, consumers may feel compelled to make
frequent purchases in order to keep up with the current fashions which can ultimately
lead to product accumulation (Johnson & Attmann, 2009). Fast fashion is particularly
attractive to compulsive consumers as it continually provides new clothing merchandise
(Johnson & Attmann, 2009).
Social Media
Tellefen et al. (2013) surveyed American women (n=1005) with social media
profiles on at least one social network to determine how these social channels
influenced their fashion purchases. Researchers determined two segments of female
social media users: fashionistas (28%) and social shoppers (15%). Women who
strongly agreed with the statement, “fashion and beauty are extremely important to me”
were categorized as fashionistas, while women who strongly agreed with “the brands
and products my friends use influence my own purchase decisions” were categorized as
social shoppers (Tellefen et al., 2013). According to Wilms (2013) 60% of fashionistas
and social shoppers are influenced by social media; 72% of social shoppers rely on
Facebook, while 56% of fashionistas were influenced by Facebook (Wilms, 2013).
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Roughly 50% of both fashionistas and social shoppers were influenced by Pinterest
(Wilms, 2013). With social media’s influence on consumer purchase behavior,
marketers are quickly recognizing the advantages of participating in these online
communities.
Social Media Envy.
Social media allows users to compare themselves to their peers on an extreme
scale, raising both personal and social expectations. Consequently consumers become
envious of what they do not have resulting in a phenomenon referred to lifestyle envy
and Instagram envy (Anderson, 2014). Most online users are depicting images of their
best selves to showcase to the rest of the world. These images are not portraying
reality and are usually staged as well as edited with filters to make images and items
appear as attractive as possible (Krishnamurthy, 2014). With constant access to envy
triggers, these feelings are almost unavoidable. As the ordinary user is exposed to
these idealized images, they are in turn trained to covet the unattainable
(Krishnamurthy, 2014).
According to research, social media users find ways to cope with their feelings of
envy (Golijan, 2013). Some decrease or discontinue social media use completely, while
others alter the content of their posts (Golijan, 2013). Women’s posts usually highlight
their appearance and social lives, whereas men tend to boast about their
accomplishments (Golijan, 2013). Additional studies have revealed that Facebook does
effect mental health causing users to be more self conscious about their bodies and
weight as well as causing them to be more self-indulgient and spend more (Golijan,
2013).
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Compulsive Hoarding
Compulsive hoarding is defined as “the acquisition of, and inability to discard,
possessions of limited value, to a degree that precludes appropriate use of living spaces
and creates significant distress or impairment in functioning” (Grisham & Barlow, 1982,
p.45-46). Thus, an extreme accumulation of unworn clothing could suggest an individual
has a tendency to hoard. Cherrier (2010) explains that the tendencies of functional
hoarders have little to no effect on their lifestyles and ability to interact socially, as
opposed to hoarders with obsessive-compulsive disorders (OCDs).
Although hoarding was previously considered to be a subtype of obsessive
compulsive disorder (Grisham & Barlow, 2005), it is now regarded as a distinct disorder
(Frost & Hristova, 2011). Hoarding has also been found to be associated with a
spectrum of impulse control disorders (ICDs), specifically compulsive buying (Grisham
& Barlow, 2005). Frost & Hartl’s (1996) research suggests the connections to
compulsive buying, since the purchase and acquisition of objects that are clearly
frivolous and unnecessary provide comfort to the consumer.
Previous research has suggested that people acquire possessions as a way to
relate to the world around them (Grishham & Barlow, 2005). This description seems
applicable to the way people use their clothes to represent themselves. However, those
who hoard tend to find security from - and develop attachments to - their possessions
rather than to other people (Grisham & Barlow, 2005). As a result, the hoarder is
completely consumed with their possessions. Narratives collected by Cherrier (2010)
showed that the possessions or objects usually embodied a specific place or
occurrence for the owner. As these physical objects are held, research suggests they
19
evoke a more powerful emotional response than a photograph, becoming memory
vessels. Sometimes objects were associated with specific individuals and preserving
the memory of their relationship. According to Cherrier (2010), these relationships
could vary from close family member to acquaintance.
Those who hoard do so because of the emotional response they have related to
an item or possession. When items are acquired and not discarded, the hoarder is
avoiding the feelings of anxiety that are associated with this decision making process.
Because the saved items provide a feeling of pleasure and comfort, these saving
actions are only reinforced (Grisham & Barlow, 2005).
Researchers have also proposed that the tendency to collect and accumulate
goods is a natural instinctual behavior utilized as a way of ensuring survival when
resources are scarce (Grisham & Barlow, 2005). However, among those individuals
who compulsively hoard, this tendency is extreme and sometimes even dangerous and
can result in the significant disruption of the hoarders life and the family’s well-being
(Frost & Gross,1993).
Studies have shown that those who hoard have difficulty determining the value of
possessions when organizing and discarding items due to information processing
deficits. A study investigating the correlation between hoarding and memory compared
hoarders and a control group. The hoarding participants recalled less information for
both verbal and nonverbal tests and used less efficient organizational techniques (Hartl
et al. 2004). The hoarding participants lacked confidence in their memory and had
trouble with decision making. Attention deficiency is also common in hoarders who
struggle to stay focused when choosing to either keep or discard items and often shift
20
their attention from one item to the next (Grisham & Barlow, 2005). Hoarders feel that
all their possessions are disproportionately valuable no matter what the item and its
actual value. This contributes to their indecisive behavior when attempting to either
choose to keep or discard an item.
21
Chapter III
Methodology
This study focused on women’s relationship with their clothing, and specifically
sought to determine their potential for reluctance to discard. Contributing factors
investigated included the influence of social media, fashion interest, fast fashion
involvement, tendency to be a compulsive buyer, and potential hoarding. Four
hypotheses were formulated to address this research problem.
An online pre-test was distributed (N=56) to University of North Texas
undergraduate students to determine any potential survey errors. A few minor
adjustments were made to ensure clarity of final data collection. The survey was then
submitted to the UNT Institutional Review Board and approved after additional survey
adjustments were made (See Appendix A & Appendix B).
Data analyzed for the study were collected via online surveys using Qualtrix
software. The participants were acquired through a purchased consumer panel from
Qualtrix.com. Screener questions located at the beginning of the survey ensured that
respondents were eighteen years or older, female, and had an interest in fashion. The
survey was open from March 11, 2014 to March 14, 2014 resulting in a total of 247
completed surveys which yielded 232 usable surveys. Data was analyzed with SPSS
software; specific tests used were Pearson’s Product Moment Correlation, one-way
ANOVA and simple frequency for the demographic information.
22
Instruments
Social media usage.
Social media usage was measured on a five-item scale where 1 = never, 2 =
rarely, 3 = sometimes, 4 = often, and 5 = several times per day. This scale was
designed to determine the amount of time the consumer spent on the different forms of
social media: Facebook, Pinterest, Fashion Blogs, Twitter, and Instagram.
Fashion interest.
Fashion interest was measured with Gutman & Mills’ (1982) five-item scale
where 1= strongly disagree and 5= strongly agree. This scale was designed to
measure the consumer’s interests as they relate to their acquisition of fashion
merchandise (Gutman & Mills, 1982). A chronbach’s alpha of between 0.80 and 0.87
was computed for this scale (Gutman & Mills, 1982).
Fast fashion involvement.
Fast fashion was included as an additional fashion related variable to Johnson and
Attmann’s (2009) original framework in order to more specifically analyze the effect of fast
fashion on compulsive clothing buying. This five-item Likert scale was tested using a 6-
point scale, where 6= Strongly Agree and1= Strongly Disagree.
Compulsive clothing buying instruments.
Developed by Johnson and Attmann (2009), the compulsive buying framework
was measured using a five-item scale where 1 = strongly disagree and 5 = strongly
agree. This scale was meant to investigate compulsive consumption, specifically in the
context of clothing. For the purposes of this study, the only original variables tested
were fashion interest and compulsive clothing buying.
23
Compulsive buying scale.
The compulsive buying scale measured five dimensions of compulsive buying.
These include tendency to spend, compulsion/drive to spend, feelings about and
experienced while shopping, dysfunctional spending, and post-purchase guilt (Edwards,
1993). The thirteen item scale is meant to classify the buyer’s level of compulsiveness:
low (borderline), medium (compulsive), and high (addicted), in addition to non-
compulsive shopping and recreation (Edwards, 1993). Though this scale was originally
used by Edwards (1993) it was adapted by Johnson and Attmann (2009) in their
Compulsive Clothing Buying scale.
Compulsive hoarding instruments.
Saving inventory revised (SI-R).
The SI-R contained 23 items using a Likert-type scale from 0 to 4. Questions are
designed to measure the three key hoarding symptoms: clutter disorganization (9
items), difficulty discarding clothing (7 items), and acquisition (7 items). These variables
were modified to fit the context of apparel and renamed as: compulsive clothing buying,
clothing clutter/ disorganization, and clothing acquisition. Thus, survey questions were
additionally adapted. For example, “possessions” was replaced with clothing, and
“living area” was replaced with closet/ wardrobe.
Clutter image rating scale (CIR).
The CIR consisted of nine color images of a room cluttered at varying degrees
(Frost, Steketee, Tolin, & Renaud, 2008). Participants were asked to choose the image
that best represented the amount of clothing in their home. Scores ranged from 1=
least cluttered and 9= most cluttered.
24
Analysis Plan
The collected data was analyzed using Statistical Package for the Social
Sciences SPSS. Hypothesis testing was conducting according to the following
schedule:
Table 1
Hypotheses and Tests
Hypothesis Variables Statistical Test H1 Participation with Social Media will
affect Fashion Interest Social Media Fashion Interest (scale)
Correlation
H2 Fashion Interest will affect Fast Fashion Involvement
Fashion Interest (scale) Fast Fashion Involvement (scale)
Correlation
H3a Compulsive clothing buying will be affected by social media.
Social Media Compulsive Buying (High, Medium, Low)
Correlation
H3b Compulsive clothing buying will be affected by fashion interest.
Fashion Interest (scale) Compulsive Buying (High, Medium, Low)
ANOVA & Correlation
H3c Compulsive clothing buying will be affected by fast fashion involvement.
Fast Fashion Involvement (scale) Compulsive Buying (High, Medium, Low)
ANOVA & Correlation
25
H4a Propensity toward compulsive clothing buying will be positively related to the approach hoarding tendency, wardrobe clutter disorganization.
Compulsive Buying (High, Medium, Low) Wardrobe Clutter Disorganization (scale)
ANOVA & Correlation
H4b Propensity toward compulsive clothing buying will be positively related to the approach hoarding tendency, clothing acquisition.
Compulsive Buying (High, Medium, Low) Clothing Acquisition (scale)
ANOVA & Correlation
H4c Propensity toward compulsive clothing buying will be positively related to the approach hoarding tendency, reluctance to discard clothing (saving).
Compulsive Buying (High, Medium, Low) Reluctance to Discard Clothing (scale)
ANOVA & Correlation
Chapter IV
Results
As this study sought to determine the existence and potential sources of clothes
hoarding among women, the following relationships were tested. First, whether social
26
media, fashion interest, and fast fashion involvement influence compulsive clothing
buying. Second, whether compulsive clothing buying is related to compulsive clothing
hoarding (clothes clutter disorganization, clothing acquisition, and reluctance to
discarding clothing).
Sample Demographics
The demographic profile of the respondents presented in Table 2, indicates that
ages ranged from 21 to 46 (M= 36.64). There was a higher response rate among the
older respondents ages 39 to 46 accounting for 43.2 percent of the sample.
Approximately 17%, also had a household income ranging from $70,000 to $99,999.
Fifty-eight percent of respondents were married, 36% were single, and 6% selected
other. Most respondents had a high school education or greater.
Table 2 Demographic Characteristics of Respondents Variables Age
Mean 36.64 - Minimum 21 - Maximum 46 -
Frequency (N=232)
Percent
Household income Less than $10,000 20 9.0% $10,000 - $19,999 30 13.0% $20,000 - $29,999 24 10.0% $30,000 - $39,999 26 11.0% $40,000 - $49,999 31
13.0% $50,000 - $59,999 25 11.0% $60,000 - $69,999 14 6.0% $70,000 - $99,999 40 17.0%
27
$100,000 - $149,999 14 6.0% $150,000 - $199,999 5 2.0% $200,000 or more 3 1.0%
Marital status Married 134 58.0% Single 83 36.0% Separated, widowed, divorced 15 6.0%
Education Elementary/middle school 1 0.0% Some high school 4 2.2% High school graduate 63 27.0% Some college, no degree 61 26.0% Associate/technical degree 36 16.0% Bachelor’s degree 49 21.0% Graduate/professional degree 18 8.0%
2012 Census Data Comparison
The 2012 American Community Survey recorded a total population sample of
313,914,040, including both males and females of all ages with females accounting for
50.8%. The total number of respondents 18 years and older was 240,203,630 with
51.4% (123,464,665.82) being female (U.S. Bureau of the Census, 2012). Of the adult
female population, 29.38% were 18 to 34 years, 50.91% were 35 to 64 years, and
19.71% were 65 years or older (U.S. Bureau of the Census, 2012). As a comparison to
the response rate of the present study, the 2012 American Community Survey received
a higher response rate from ages 35 to 64 similar to the current study’s higher response
from respondents ages 39 to 46. It also received a smaller response from the younger
respondents ages 18 to 34 similar to the current study’s lower response from ages 18 to
34. Finally, the 2012 American Community Survey also received a minimal response
from participants 65 years or older, just as this age group is completely unrepresented
in the current study.
28
Marital status of female respondents 15 years and older consisted of, 46.3%
married, 9.2% widowed, 12.4% divorced, 2.5% separated, and 29.6% never married
(U.S. Bureau of the Census, 2012). Again demographic responses are comparable to
the current study with most respondents recording they are married, followed by single
respondents, and the least amount of respondents stating to be separated, widowed or
divorced.
Eighty-seven percent of female respondents received a high school education or
higher and 29.1% received a bachelor’s degree or higher, while 10.9% of the entire
male and female population received a graduate or professional degree (U.S. Bureau of
the Census, 2012). Just as the current study, high school graduates had the highest
response percentage, with a slightly lower bachelor's degree response, and the smallest
graduate/professional response.
Lastly, mean earnings for full-time year-round female workers was $47,001 (U.S.
Bureau of the Census, 2012). Again comparable results were found, with the mean
annual income range for the current study also being $40,000 to $49,999.
The level of social media usage among respondents is provided in Table 3.
Facebook was the preferred social media site, with 58.6% of respondents checking it
several times per day and only 9.9% never checking. The other preferred social media
sites in descending order were Pinterest (12.5% used several times per day) Twitter
(10.8% used several times per day), and Fashion Blogs (10.8% used several times per
day). The least used social media site among respondents was Instagram with only
5.6% checking several times per day and 51.7% never checking.
Table 3
29
Social Media Usage Variables Frequency
(N=232) Percent
Never 23 9.9% Rarely 7 3.0% Sometimes 20 8.6% Often 46 19.8% Several times per day 136 58.6%
Pinterest Never 77 33.2% Rarely 30 12.9% Sometimes 47 20.3% Often 49 21.1% Several times per day 29 12.5%
Fashion Blogs Never 101 43.5% Rarely 32 17.7% Sometimes 45 16.8% Often 45 11.2% Several times per day 9 10.8%
Twitter Never 101 43.5% Rarely 41 17.7% Sometimes 39 16.8% Often 26 11.2% Several times per day 25 10.8%
Instagram Never 120 51.7% Rarely 34 14.7% Sometimes 32 13.8% Often 33 14.2% Several times per day 13 5.6%
Analysis of Hypotheses
Three hypotheses were proposed for this study. Data were statistically analyzed
for application to the specific hypotheses. The data were received from Qualtrix in
30
SPSS format and all were complete records. With all statistical procedures used in the
present study, a probability level of .05 or less was considered significant.
Means, standard deviations, Pearson Product Moment Correlations, and
Analysis of Variance (ANOVA) were used for analyses of the hypotheses. The mean
and standard deviation allowed comparison of variables using measures of central
tendency. The ANOVA was used to compare two or more groups to determine whether
a significant difference existed between mean scores of the groups being compared. A
significant difference would indicate the two populations probably do not have the same
mean. When post hoc tests were required to determine which groups possessed
different means, the Scheffe’ test was used. Pearson Product Moment Correlations
were also computed for some hypotheses. The correlation procedure was used for
situations involving continuous and scale variables.
Data Analysis
H1: Social media and fashion interest.
Hypothesis 1 predicted that participation with social media will affect fashion
interest. Pearson Product Moment Correlation analysis indicated a strong positive
relationship between use of social media and fashion interest. The strongest
correlations were with fashion blogs (r = .636, p <.0001) and Instagram (r = .474, p
<.0001), followed by moderate correlations with Twitter (r = .361, p <.0001), Pinterest (r
= .303, p <.0001), and Facebook (r = .202, p <.002). Respondents who indicated they
use the social networks more often also indicated a higher interest in fashion (Table 4).
Therefore, H1 was accepted.
Table 4
31
Pearson Product Moment Correlations Between Survey Variables and Fashion Interest Variables r Sig. H1: Fashion Blogs and Fashion Interest 0.64 0.0001
H1: Instagram and Fashion Interest 0.47 0.0001 H1: Twitter and Fashion Interest 0.36 0.0001 H1: Pinterest and Fashion Interest 0.30 0.0001 H1: Facebook and Fashion Interest 0.20 0.002 H2: Fast Fashion Involvement and Fashion
Interest 0.80 0.0001
H2: Fashion interest and fast fashion involvement.
Hypothesis 2 predicted that fashion interest will affect fast fashion involvement.
Pearson Product Moment Correlation analysis indicated a strong positive relationship
between fashion interest and fast fashion involvement (r=.799, p<.0001). Participants
who had a high fashion interest also indicated a high level of fast fashion involvement
(Table 4), therefore H2 was accepted.
H3a: Compulsive clothing buying and social media.
Hypothesis 3a predicted that compulsive clothing buying will be affected by social
media. Pearson Product Moment Correlation analysis indicated a strong positive
relationship between use of social media and compulsive clothing buying. Positive
correlations were found between each of the social media and compulsive clothing
buying. The strongest correlations were with fashion blogs (r = .448, p <.000) and
Instagram (r = .280, p <.0001), followed by moderate correlations with Twitter (r = .220,
p <.001), Facebook (r = .186, p <.005), and Pinterest (r = .152, p <.021). As the
consumers’ social media usage increases, so does their tendency to compulsively buy
clothes (Table 5). Hypothesis H3a was accepted.
Table 5
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Pearson Product Moment Correlations Between Compulsive Clothing Buying (CCB) Tendency and Survey Variables Variables r Sig. H3: CCB and Fashion Blogs 0.45 0.0001 H3a: CCB and Instagram 0.30 0.0001 H3a: CCB and Twitter 0.22 0.0010 H3a: CCB and Facebook 0.19 0.0050 H3a: CCB and Pinterest 0.15 0.0210 H3b: CCB and Fashion Interest 0.67 0.0001 H3c: CCB and Fast Fashion Involvement 0.66 0.0001
H4a: CCB and Clothing Clutter Disorganization
0.43 0.0001
H4b: CCB and Clothing Acquisition 0.69 0.0001 H4c: CCB and Reluctance to Discard
Clothing 0.48 0.0001
H3b: Compulsive clothing buying and fashion interest.
Hypothesis H3b predicted that compulsive clothing buying will be affected by
fashion interest. Pearson Product Moment Correlation analysis indicated a strong
positive relationship between compulsive clothing buying and fashion interest (r = .672,
p <.0001). As the consumers’ interests in fashion increases, so did their tendency to
compulsively buy clothing (Table 5). Therefore, hypothesis H3b was accepted.
To further explore the effect of propensity toward compulsive buying on fashion
interest, a one-way ANOVA was employed. Tendency toward compulsive buying, was
divided into three categories based on the average participant responses on the scale.
A mean score of 1 to 2.5 was classified as low compulsive clothing buying, a mean
score of 2.5 to 3.5 was classified as medium compulsive clothing buying, and a mean
score of 3.5 to 5 was classified as high compulsive clothing buying. Analysis indicated
significant differences (F = 72.043, p = .0001) in fashion interest between the
33
compulsive buying groups. Because ANOVA indicates that a significant difference
exists, but does not indicate where the difference(s) are, the Scheffe’ post hoc analysis
was employed. Fashion interest differed significantly across the three levels (F =
72.043, p < .0001). ANOVA indicated high compulsive shoppers subjects (M = 3.82)
were more likely to have high levels of fashion interest compared to medium (M = 3.41)
and low compulsive shoppers (M = 2.32), as shown in Table 6.
Table 6 Analysis of Variance Findings for Compulsive Clothing Buying Tendency and Survey Variables Variables Low
Compulsive Clothing Buying Mean (n=62)
Medium Compulsive
Clothing Buying Mean (n=92)
High Compulsive
Clothing Buying Mean (n=78)
F
p <
Fashion Interest 2.32a 3.41b 3.82c 72.04 0.0001 Fast Fashion Involvement 2.57a 3.45b 3.68c 63.64 0.0001
Wardrobe Clutter Disorganization
1.22a 1.60b 2.14c 27.09 0.0001
Clothing Acquisition 1.89a 2.43b 3.21c 87.55 0.0001 Reluctance to Discard
Clothing 2.30a 2.68b 3.34c 33.41 0.0001
Note. Means sharing a common superscript are not significantly different by the Scheffe test. H3c: Compulsive clothing buying and fast fashion involvement.
Hypothesis H3c predicted that compulsive clothing buying will be affected by fast
fashion involvement. Pearson Product Moment Correlation analysis indicated a strong
positive relationship between compulsive clothing buying and fast fashion involvement (r
= .659, p <.0001). Respondents who indicated they had greater fast fashion
involvement, indicated a tendency to compulsively buy clothing (Table 5). Therefore,
hypothesis H3c was accepted.
34
A one-way ANOVA was computed to further define the relationship between
these two variables. Fast fashion Involvement differed significantly across the three
levels (F = 63.638, p = .0001). ANOVA indicated high compulsive shoppers (M = 3.68)
were more likely to have high levels of fashion interest compared to medium (M = 3.45)
and low compulsive shoppers (M = 2.57) as indicated in Table 6.
Compulsive Hoarding Profile
Each hoarding symptom was divided based on the average participant
responses on the scale. A mean score of 1 to 2.5 was classified as low compulsive
clothing hoarding, a mean score of 2.5 to 3.5 was classified as medium compulsive
clothing hoarding, and a mean score of 3.5 to 5 was classified as high compulsive
clothing hoarding. The compulsive hoarding profile of the respondents presented in
Table 7, indicates that most respondents had low compulsive hoarding tendencies.
Eighty-four percent of respondents scored low for wardrobe clutter and disorganization
with only 5.6% accounting for high wardrobe clutter and disorganization. Fifty-three
percent of respondents scored low for clothing saving and acquisition with 15.5%
scoring high. Finally, 44.2% of respondents scored low for reluctance to discard
clothing (saving) while 22.4% of respondents scored high. Of all three hoarding
symptoms, difficulty discarding had the highest respondent score for high compulsive
tendencies.
Second, the clutter image rating represented the amount of clothing in the
respondents wardrobe based on a scale from 1-9, with a score of 1 indicating least
clutter and 9 indicating most cluttered. Most participants chose images 1-4 accounting
35
for 95% of responses. Only 2 outlier respondents chose 9, the highest level of wardrobe
clutter.
Table 7 Hoarding Profile of Study Participants Variables Frequency Percent Wardrobe Clutter Disorganization
Low (1-2.5) 197 84.9% Medium (2.5-3.5) 22 9.4% High (2.5-5) 13 5.6%
Clothing Acquisition Low (1-2.5) 124 53.4% Medium (2.5-3.5) 72 31.1% High (2.5-5) 36 15.5%
Reluctance to Discard Clothing (Saving)
Low (1-2.5) 103 44.2% Medium (2.5-3.5) 77 33.0% High (2.5-5) 52 22.4%
Clutter Image Rating Scale 1 83 36% 2 85 37% 3 30 13% 4 20 9% 5 7 3% 6 2 1% 7 3 1% 8 0 0% 9 2 1%
Note. The hoarding scale was measured on a 5-point scale where 1=None and 5=Almost all/Complete. Note. The Clutter Image Rating Scale consisted of a series of 9 photographs in which a bedroom as depicted as neat (1) to extremely messy (9). This instrument is in Appendix B. H4a: Compulsive clothing buying and wardrobe clutter disorganization.
Hypothesis H4a predicted that compulsive clothing buying will be positively
related to wardrobe clutter disorganization. Pearson Product Moment Correlation
analysis indicated a strong positive relationship between compulsive clothing buying
36
and wardrobe clutter disorganization (r = .429, p <.0001). Respondents who indicated
they had greater wardrobe clutter disorganization, indicated a tendency to compulsively
buy clothing (Table 6). Therefore, hypothesis H4a was accepted.
Additionally, a one-way ANOVA was calculated to test for consumer wardrobe
clutter disorganization differences among the low, medium, and high compulsive
clothing buyers. Wardrobe clutter disorganization differed significantly across the three
levels (F = 27.092, p = .0001). While the mean scores were relatively low, ANOVA
indicated high compulsive clothing shoppers (M = 2.14) had higher levels of fashion
interest compared to medium (M = 1.60) and low compulsive clothing shoppers (M =
1.22) as indicated in Table 7.
H4b: Compulsive clothing buying and clothing acquisition.
Hypothesis H4b predicted that compulsive clothing buying will be positively
related to clothing acquisition. Pearson Product Moment Correlation analysis indicated
a strong positive relationship between compulsive clothing buying and clothing
acquisition (r = .691, p <.0001). Respondents who indicated a higher tendency to
compulsively buy clothing also had a greater tendency to acquire clothing (See Table
6), therefore H4b was accepted.
A one-way ANOVA was used to test for consumer clothing acquisition
differences among low, medium, and high compulsive clothing buying. Clothing
acquisition differed significantly across the three levels (F = 87.551, p < .0001). ANOVA
indicated high compulsive clothing shoppers subjects (M = 3.21) were more likely to
have higher clothing acquisition levels compared to medium (M = 2.43) and low
compulsive shoppers (M = 1.89) as indicated in Table 7.
37
H4c: Compulsive clothing buying and reluctance to discard clothing
(saving)
Hypothesis H4c predicted that compulsive clothing buying will be positively
related to reluctance to discard clothing. Pearson Product Moment Correlation analysis
indicated a strong positive relationship between compulsive clothing buying and
reluctance to discard clothing (r = .480, p <.0001). Respondents who indicated they
had a greater tendency to compulsively buy clothing, also admitted having more
difficulty discarding clothing (Table 6), therefore H4c was accepted.
Again, a one-way ANOVA was used to test for consumer reluctance to discard
clothing differences among the low, medium, and high compulsive clothing buyers.
Reluctance to discard clothing differed significantly across the three levels (F = 33.412,
p < .0001). ANOVA indicated high compulsive clothing shoppers subjects (M = 3.34)
were more likely to have high levels of difficulty when discarding their clothes compared
to medium (M = 2.68) and low compulsive clothing shoppers (M = 2.30) as indicated in
Table 7.
Chapter V
Conclusions and Discussion
This survey of adult female consumers sought to identify influences on women’s
clothes shopping and potential hoarding tendencies. Social media, fashion interest, and
fast fashion involvement were presented as potential contributing factors to these
behaviors. Social media usage does have an impact on the consumer’s fashion interest
38
and fast fashion involvement. As social media introduces the latest fashions to a wide
range of consumers quickly and regularly, they can respond in real time, providing a
virtual space, where the consumer’s interests and involvement of fashion can be
encouraged and strengthened. Social media is viewed as a way to improve customer
relationships as well as reach out to a larger audience (Mohr, 2013). Increased fashion
interest levels also increases the consumers’ likelihood to purchase fashion products.
More specifically this study indicates that fashion interest encourages the consumers
natural tendencies to make compulsive clothing purchases. High compulsive clothing
shoppers were more likely to acquire clothing than discard it. As consumers acquire
more clothing items without discarding them, the probability of hoarding these items
increases.
Discussion
The results of this study suggest increased social media usage combined with
fashion interest and fast fashion involvement can also increase compulsive clothing
shopping tendencies. Findings from this study indicate that those with increased
compulsive clothing tendencies are also more likely to hoard clothes. Evidence shows
that as consumers have accepted and participated in social media, they consequently
are exposed to the latest fashions in real time making them more susceptible to
endorsements and advertisements, particularly those from fashion blogs. Overall, social
media is a major driving force behind overconsumption habits among consumers.
The impact of social media on fashion interest and compulsive buying.
Social media tested positively with fashion interest, with fashion blogs having the
highest correlation. As social media helps to feed the fashion interest of the consumer,
39
it provides a very useful marketing tool for promoting fashion products. Partly due to the
help of the internet, fashion is everywhere, and fashion blogs allow consumers a space
for unlimited self-expression (Mohr, 2013). By monitoring brand related conversations
through social media networks, marketers can more effectively identify influential
individuals and fashion leaders within an online community (Kumar & Mirchandani,
2013). Brands are now recognizing the role of fashion bloggers’ as the influencers and
trendsetters of fashion (Mohr, 2013). These influencers can promote products through
word of mouth in social media conversions potentially increasing sales (Kumar &
Mirchandani, 2013). Ultimately, the fashion blogger acts as a way of connecting the
brand with the target market.
Social media was also positively correlated with the tendency to compulsively
buy clothing. The consumer no longer has to seek out the latest fashions, instead the
consumer is continually exposed through varying social media networks. As consumers
are using their smart phones for many daily tasks, they are more easily accessible to
marketers who are aggressively targeting them through all means of technology. Most
social media forms are also connected to cell phones through apps and email
notifications, keeping the consumer constantly updated. Frequent updates, such as
sales and coupons appeal to the compulsive shopper and encourage their natural
inclination to shop. Marketing communications should strive to create awareness,
encourage dialogue, and gain the consumer’s trust (Persaud & Azhar, 2012). This
dialogue between consumer and brand is possible through social media. As marketers
establish online relationships with the consumer, gaining their loyalty and influencing
their purchasing decisions (Persaud & Azhar, 2012).
40
Social media enhances the fashion market by providing shoppers with an
environment that makes browsing the latest fashions accessible with the click of a
button. Selling via Facebook and Instagram comments has also made online shopping
even easier (“Are You Missing,” 2014). Now the consumer can comment “sold” beneath
the image of the item for sale and complete the transaction without leaving the social
network site (Are You Missing,” 2014). As the digital shopping experience continues to
become faster and more convenient, this only intensifies compulsive buying among
shoppers.
The impact of fashion interest on fast-fashion involvement and compulsive
clothing buying.
Over the past 20 years, the dynamics of the fashion industry have significantly
evolved with fast fashion’s speed to market and design as the leading forces of
competitiveness (Bhardwaj & Fairhurst, 2010). Since fast fashion has played such a
major role in the evolution of the fashion industry, it is not surprising that fashion interest
and fast fashion involvement would be positively correlated. Fashion interest and fast
fashion involvement were so strongly correlated, that they may be measuring the same
construct. A review of the literature indicates a general use of one or the other of the
concepts, but not both. It may warrant further study to determine whether these two
scales are really psychologically different in the consumer behavior context.
Fashion interest and fast fashion involvement were both positively correlated
with compulsive clothing buying. As the cycles of fashion are quickly changing,
consumers with high interest in fashion feel pressure to keep up with the current trends.
Social media sites allow both brands and consumers to upload and share images of the
41
latest fashions, creating idealized facades of products. As social media users are
continually exposed to these images, they in turn become envious of what they do not
have, ultimately feeling compelled to make purchases. The terms lifestyle envy and
Instagram envy have been coined referring to this phenomenon (Anderson, 2014). Fast
fashion makes it affordable for the consumer to purchase the latest trends to maintain
their social status. Past research has also shown that conformity motivation among
consumers influences participation of social e-shopping on social networking sites
(Kang & Johnson, 2013). Consumers who are concerned with group norms regarding
which products and brands to buy were likely to seek the opinions of others through
social networks sites (Kang & Johnson, 2013). The Instagram envy effect accompanied
by conformity motivations could be further propelling the speed at which fast fashion
trends spread through social networks. Further as these viral images are quickly
spreading, an envious consumer is likely to make more compulsive clothing purchases.
The impact of compulsive clothing buying tendencies on wardrobe clutter
and clothing acquisition.
Of the attributes measuring hoarding tendencies (wardrobe clutter
disorganization, clothing acquisition, and reluctance to discard clothing), clothing
acquisition was the most strongly correlated to compulsive clothing buying. American
consumerism emphasizes that having more is better, encouraging the trend of quantity
over quality. Fast fashion consumers are making purchases based on their ability to
buy in bulk, acquiring the largest amount of clothing for the least amount of money
(Watson & Yan, 2013). According to Watson and Yan (2013), fast fashion consumers
have impulse buying tendencies. While impulsive purchases can sometimes lead to
42
buyers remorse, fast fashion consumers avoid these feelings of guilt due to the
affordability of the products (Watson & Yan, 2013). Thus, the consumer’s purchases
are seemingly without repercussions encouraging their impulse buying tendencies.
Additionally, fast fashion consumers experienced instant satisfaction versus continued
satisfaction with their purchases (Watson & Yan, 2013). Consumers admitted to
dissatisfaction as merchandise either went out of style or began to fall apart (Watson &
Yan, 2013). However, as clothes quickly fall apart and are discarded, lack of buyers
guilt keeps the consumers motivated to revisit the fast fashion store to repeat the buying
cycle, acquiring additional clothes. Fast fashion creates a shopping experience that
encourages compulsive and overconsumption shopping tendencies.
As previously mentioned social media envy could also be contributing to this
desire to consume more. Consumers see what others have, or what they are perceived
to have, and then they want it too. Consumers have always compared themselves to
peers, however, until now, it has not been done on such an extreme scale (Anderson,
2014). As consumers compare themselves to thousands of social media users, the
lines between peers and celebrities are blurred (Anderson, 2014).
Contributions to Research
This research suggests that social media is an important variable influencing the
consumption behavior of shoppers. As consumers become more easily accessible
through their social media involvement, they are more vulnerable to target marketing.
Social media is also assisting the speed at which fast fashion is exchanged amongst
online consumers, encouraging the speed at which it is adopted. Additionally,
consumers should be cautioned of their impressionable nature causing them to be more
43
susceptible to social media envy. As a result, consumers feel compelled to purchase
items based on what is currently trending in fashion through endless images they are
presented with on social media sites. Psychologist may also be interested to find that
fast fashion and social media are major contributors to hoarding. As the convenience of
the digital age continues to improve, it may become more difficult for individuals with
hoarding tendencies to recover from their addictive behavior. Psychologists and clients
should consider these correlations when performing and undergoing treatment.
Recommendations
Overall, this study was successful in supporting the idea that social media and
fashion interest play major roles in the consumers’ potential to compulsively shop and
hoard clothing. Consumers should be cautioned as marketers are using social media
participation as a means of exploitation. Additionally, since fashion interest and fast
fashion involvement were so strongly correlated, it is likely they are measuring the same
construct. Further research should examine whether they are psychologically different.
Due to its affordability, fast fashion involvement should further be investigated for
potential correlations with consumer income.
This research only explores Compulsive Clothing Buying and Clothing Hoarding
on the surface level, but establishes a research foundation that could be further
investigated on a more psychological and emotional level.
Limitations and Further Research
There are a few limitations that may have inhibited this study. Since an online
survey was used to investigate social media participation this may limit the
generalizability of the study. It is likely that someone who participates in online surveys
44
is also more likely to spend more time online in general and therefore may have higher
social media participation. Also, a larger sample size may have been more beneficial
giving a more accurate representation of the female population. The sample was also
skewed a little older than expected, with only 17.7% of the respondents in the younger
female cohort (ages 21-29).
This study could be extended to more thoroughly investigate a single social
media site and its relationship with the compulsive consumer. Pinterest, for example,
provides multiple sections of interests other than fashion for the “pinner” to browse
including: DIY, Art, Design, Hair & Beauty, Health & Fitness, etc. Which sections are
consumers spending the most time browsing, and how many pins actually result in a
purchase? If pinners are compulsively pinning without ever referencing pins later, could
they essentially be considered virtual hoarders? If pins are not referred to after pinning,
then what purpose does the act of pinning serve the pinner? Have pins merely become
a form of virtual window shopping, and only serve as inspiration, representing a fantasy
life the pinner cannot actually obtain? Mull and Lee (2014) suggest that the
engagement in Pinterest may provide entertainment or diversion from daily routines for
the user. Does pinning serve as an escape or form of relief from stress and anxiety
much like compulsive shopping and hoarding? Though some research has investigated
the motivational dimensions of using Pinterest, no studies were located that investigated
a purchasing outcome. No further research was located that investigated the
physiological and compulsive nature behind the act of pinning.
45
Appendix A
46
47
Appendix B Hello,
For my master’s thesis in the College of Merchandising, Hospitality & Tourism, I am conducting a survey on Consumer’ compulsive buying of clothing and potential hoarding. This research will help understand connections between clothing acquisition and post-consumption behavior. We are requesting that you participate in the study by answering a series of questions regarding your tendencies.
Your participation in this study is voluntary and all responses will be kept confidential.
Please answer all of the survey questions. Incomplete surveys cannot be included in final data analysis. This survey will take approximately 20 minutes of your time.
To participate, simply click the “next page” button below. You may choose not to answer any question and you may stop participating at any time. After completing the survey, please remember to click “finish.” By completing the survey, you give your consent to participate in the research.
Your demographic information will only be used to help the analysts and will be published in an aggregated form.
There are no foreseeable risks involved in this study.
Your participation in the study is voluntary.
If you have any questions, please contact me, Kathleen Higgins (Graduate student Investigator, Department of Merchandising and Digital Retailing, University of North Texas, [email protected].
Thank you very much for your time.
Sincerely,
Kathleen Higgins, Graduate student investigator, Department of Merchandising and Digital Retailing, University of North Texas [email protected]
Tammy Kinley, Ph.D., Chair Department of Merchandising and Digital Retailing, University of North Texas [email protected], 940-565-4842
We would appreciate your participation.
48
The following question will help measure your social media use.
Please indicate how often you use the following social networks:
Never Rarely Sometimes Often Several times per
day 1. Facebook 1 2 3 4 5
2. Pinterest 1 2 3 4 5
3. Fashion Blogs 1 2 3 4 5
4. Twitter 1 2 3 4 5
5. Instagram 1 2 3 4 5
The following 5 questions will help measure your fashion interest.
Please indicate the extent to which you agree or disagree with each of the following.
Strongly Disagree
Disagree Neutral Agree Strongly Agree
1. Because of my active life style,I need a wide variety of clothes.
1 2 3 4 5
2. I always buy at least one outfitof the latest fashion.
1 2 3 4 5
3. I never read fashionmagazines or pay attention to fashion trend.
1 2 3 4 5
4. I spend a lot of money onclothes and accessories
1 2 3 4 5
5. I spend a lot of time onfashion-related activities.
1 2 3 4 5
49
The following 6 questions will help measure your involvement in fast fashion specifically. Fast fashion refers to clothing that is produced in a compressed lead time, providing consumers with the latest emerging trends quickly and rapidly at a relatively low cost. Please indicate the extent to which you agree or disagree with each of the following. Strongly
Disagree Disagree Neutral Agree Strongly
Agree
1. I frequently search for more information about fast fashion brands via magazine or internet.
1 2 3 4 5
2. I am interested in those products in fast fashion brands.
1 2 3 4 5
3. It is not a big deal, if I make a wrong purchase decision from fast fashion brands. For examples, wrong purchase decision of buying a wrong size.
1 2 3 4 5
4. I need a short decision time when I buy a fast fashion brand’s product.
1 2 3 4 5
5. I think fast fashion brand ’ s product can give me a pleasant feeling.
1 2 3 4 5
6. I think fast fashion brands give a special meaning to their product.
1 2 3 4 5
The following 13 questions will measure your tendency to compulsively buy. Please indicate the extent to which you agree or disagree with each of the following.
50
Strongly Disagree
Disagree Neutral Agree Strongly Agree
1. I feel driven to shop and spend, even when I don’t have the time or the money on clothing.
1 2 3 4 5
2. I get little or no pleasure from shopping for clothing.
1 2 3 4 5
3. I hate to go shopping for clothing.
1 2 3 4 5
4. I go on clothing buying binges.
1 2 3 4 5
5. I feel “high” when I go on a clothing buying spree.
1 2 3 4 5
6. I buy clothing even when I don’t need any.
1 2 3 4 5
7. I go on a clothing buying binge when I’m upset, disappointed, depressed, or angry.
1 2 3 4 5
8. I worry about spending habits but still go out and shop and spend money on clothing.
1 2 3 4 5
9. I feel anxious after I go on a clothing buying binge.
1 2 3 4 5
10. I buy clothes even though I cannot afford them
1 2 3 4 5
11. I feel guilty or ashamed after I go on a buying binge.
1 2 3 4 5
12. I buy clothing I don’t need or won’t use
1 2 3 4 5
13. I sometimes feel compelled to go shopping for clothing.
1 2 3 4 5
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The following questions address how you store clothing.
None A
little A
moderate amount
Most/Much
Almost all/
Complete
1.How much of the living area in your home is cluttered with clothing? (Consider the amount of clutter in your kitchen, living room, dining room, hallways,bedrooms, bathrooms, or other rooms).
1 2 3 4 5
2.How much of your home does clothing clutter prevent you from using?
1 2 3 4 5
3.How much of your home is difficult to walk through because of clothing clutter?
1 2 3 4 5
4.To what extent do you have so many clothes that your room(s) are cluttered?
1 2 3 4 5
5.How much does clothing clutter in your home interfere with your social, work or everyday functioning?Think about things that you don’t do because of clothing clutter.
1 2 3 4 5
6.To what extent does clothing clutter in your home cause you distress?
1 2 3 4 5
7.To what extent do you feel unable to control the clothing clutter in your home?
1 2 3 4 5
8.How frequently does clothing clutter in your home prevent you from inviting people to visit?
1 2 3 4 5
9.To what extent does the clothing clutter in your home prevent you from using parts of your home for their intended purpose? For example, cooking, using furniture, washing dishes, cleaning, etc.
1 2 3 4 5
52
The following questions will help measure your level of difficulty when discarding clothing. None A
little A
moderate amount
Most/Much
Almost all/
Complete 1.How much control do you have over your urges to save clothing?
1 2 3 4 5
2.To what extent do you have difficulty throwing clothing things away?
1 2 3 4 5
3.How distressing do you find the task of throwing clothes away?
1 2 3 4 5
4.How strong is your urge to save clothes you know you may never use?
1 2 3 4 5
5.How often do you avoid trying to discard clothes because it is too stressful or time consuming?
1 2 3 4 5
6.How often do you decide to keep clothes you do not need and have little space for?
1 2 3 4 5
7.How often are you unable to discard a garment you would like to get rid of?
1 2 3 4 5
8. How much of your clothing is kept due to weight fluctuation?
1 2 3 4 5
The following questions will help measure your level of difficulty when acquiring clothing.
None A
little A
moderate amount
Most/Much
Almost all/
Complete
1.How much control do you have over your urges to acquire clothing?
1 2 3 4 5
2. How distressed or uncomfortable would you feel if you could not acquire clothing you wanted?
1 2 3 4 5
53
3. How strong is your urge to buy or acquire free clothing for which you have no immediate use?
1 2 3 4 5
4. How upset or distressed do you feel about your acquiring clothing habits?
1 2 3 4 5
5. To what extent has your saving or compulsive clothing buying resulted in financial difficulties for you?
1 2 3 4 5
6. How often do you feel compelled to acquire clothing you see? e.g., when shopping or offered free things?
1 2 3 4 5
7. How often do you actually buy (or acquire for free) clothing for which you have no immediate use or need?
1 2 3 4 5
Please choose the image that best reflects your wardrobe. 1
54
2 3 4 5 6 7 8 9
We request general demographic information to help with our analysis, but your information will NOT be used to identify you. 1. What is your gender?
a. Male b. Female
2. What year were you born? _______ 3. What is your Marital Status?
a. Married b. Single c. Other
4. What is the highest level of education you completed? a. Elementary/middle school b. Some high school c. High school graduate d. Some college, no degree e. Associate/technical degree, f. Bachelor's degree g. Graduate/professional degree 5. What is your annual income range? a. Less than $10,000 b. $10,000 to $19,999 c. $20,000 to $29,999 d. $30,000 to $39,999 e. $40,000 to $49,999 f. $50,000 to $59,999
g. $60,000 to $69,999 h. $70,000 to $99,999 i. $100,000 to $149,999 j. $150,000 to $199,999 k. $200,000 or more
Thank you for participating!
55
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