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
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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
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
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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
$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.
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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
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Social Media Usage Variables Frequency
(N=232) Percent
Facebook
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
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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
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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
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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
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.
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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
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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%
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
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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.
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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
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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,
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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).
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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
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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
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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
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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.
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Appendix A
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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.
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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
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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.
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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
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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
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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
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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!
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References
Anderson, L. (2014, April 12). The Instagram effect: How the psychology of envy drives
consumerism. Retrieved from http://plymouth.wickedlocal.com/article/20140412/
NEWS/304129939/12449/LIFESTYLE
Are you missing out on F-Commerce?.(2014). Retrieved April 14, 2014, from http://