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Florida State University Libraries
Electronic Theses, Treatises and Dissertations The Graduate School
2008
Interest and Needs in Men's BusinessClothingDiana Kendrick Sindicich
Follow this and additional works at the FSU Digital Library. For more information, please contact [email protected]
FLORIDA STATE UNIVERSITY
COLLEGE OF HUMAN SCIENCES
INTEREST AND NEEDS IN MEN‟S BUSINESS CLOTHING
By
DIANA KENDRICK SINDICICH
A Dissertation submitted to the Department of Textiles and Consumer Sciences
in partial fulfillment of the requirements for the degree of
Doctor of Philosophy
Degree Awarded Summer Semester, 2008
Copyright © 2008 Diana Kendrick Sindicich
All Rights Reserved
ii
The members of the Committee approve the dissertation of Diana Sindicich defended on June 13, 2008.
Catherine Black Professor Directing Research Rinn Cloud Committee Member Michael Hartline Committee Member Jeanne Heitmeyer Committee Member
Approved: Barbara Dyer, Chair, Department of Textiles and Consumer Sciences Billie Collier, Dean of the College of Human Sciences The Office of Graduate Studies has verified and approved the above named committee members.
iii
TABLE OF CONTENTS List of Tables …………………………………………………………………...………… v List of Figures ……………………………………………………………………………… vii Acknowledgements ………………………………………………………………………… viii Abstract …………………………….………………………………………………………. ix
CHAPTER 1
Introduction ………………………………………………………………………………… 1 Measuring Fit Issues ……………………………………………………………………….. 1 Purpose ……………………………………………………………………………………… 2 Research Questions ………………………………..……………………………………….. 2 Hypotheses ………………………………………………………………………………….. 2 Rationale for the Study ……………………………………………………………………... 3 Limitations ………………………………………………………………………………….. 4 Assumptions ………………………………………………………………………………… 4 Definition of Terms …………………………………………………………………………. 6
CHAPTER 2
Review of Literature ………………………………………………………………………... 8 Design Processes ………………………………………………………………………… 8 A Comparison of Two Design Process Models ……………………………………….. 8 Functional Design Process ……………………………………………………………… 9 Functional, Expressive, Aesthetic……………………………………………………..... 11 Interrelationship of the Models……………………………………………………………… 14 Process models and the FEA consumer needs…………………………………................ 14 A comparison of the process models…………………………………………………….. 14 Functional Design in Applied Research…………………………………………………….. 15 Fit……………………………………………………………………………………………. 15 Sizing……………………………………………………………………………………….. 16 Ease …………………………………………………………………………………………. 17 Sizing and Fit Issues………………………………………………………………………… 17 Military Sizing Studies……………………………………………………………………… 18 Current Commercial Sizing Systems………………………………………………………... 19 Clothing Interest…………………………………………………………………………….. 20 The Influence of Interest on Reported Clothing Problems………………………………….. 25
CHAPTER 3
Methods……………………………………………………………………………………… 27 The Functional Design Process Applied to the Current Study……………………………… 27 Instrument Development……………………………………………………………………. 28 Interpretation of the Factors……………………………………………………………...….. 29 The Final Instrument…………………………………………………………………….…... 32 Subjects……………………………………………………………………………………… 33 Data Analysis………………………………………………………………………………... 34
CHAPTER 4
Results and Discussion………………………………………………………………………. 36
iv
Demographics……………………………………………………………………………….. 38 Body Mass Index……………………………………………………………………………. 41 Separation of Groups………………………………………………………………………... 42 Research Questions………………………………………………………………………….. 42 Question 1: What fit issues are common in men‟s business clothing? Individual Issues…………………………………………………………….. 43 Shirts………………………………………………………………………… 43 Pants………………………………………………………………………… 47 Suits…………………………………………………………………………. 50 Question 2: How will men vary in clothing interest? Clothing Interest……………………………………………………………………... 56 Work Experience………………………………………………………......... 57 Clothing Interest and Reported Fit Issues…………………………………………………… 58 Between Data Groups Comparison of Interest Groups……………………………………… 58 Hypotheses……………………………………………………………………...................... 61 Overall Interest Groups…………………………………………………………………... 62
CHAPTER 5
Conclusions, Implications and Summary…………………………………………………… 65 Resolving Fit Issues………………………………………………………………………… 65 Future Studies……………………………………………………………………………….. 67 Conclusions………………………………………………………………………………….. 68
APPENDIX A
Paper Questionnaire…………………………………………………………………………. 71 Internet Questionnaire ………………………………………………………………………. 77
APPENDIX B
INSTITUTIONAL RESEARCH BOARD APPROVAL MEMOS………………………… 79
APPENDIX C
ERROR CHECKING PROCEDURES……………………………………………………… 83
APPENDIX D
ADDITIONAL TABLES …………………………………………………………………… 86
REFERENCES………………………………………………………………………………. 91
BIOGRAPHICAL SKETCH………………………………………………………………... 96
v
LIST OF TABLES
1. Example of an Interaction Matrix for Fireman‟s Coveralls…………………… 10
2. The Relationships Between Two Design Processes…………………………… 14
3. Sizing Methods for Men and Women………………………………………….. 20
4. Comparative Shirt Sizing Charts Among Selected Retailers………………….. 21
5. Comparative Shirt Sizing Charts Among Selected Retailers, continued..…….. 22
6. Comparable Pants Sizing Chart Among Selected Retailers…………………… 23
7. Factor Correlations……………………………………………………………. 31
8. Clothing Interest Factors………………………………………………………. 33
9. Group MC Demographics…………………………………………………….. 36
10. Group NT Demographics……………………………………………………… 37
11. Group Residency by State…………………………………………………….. 37
12. Comparison of Race between MC and NT…………………………………… 38
13. Comparison of Education between MC and NT……………………………… 39
14. Comparison of Annual Incomes between MC and NT……………………….. 39
15. Comparison of Marital Status between MC and NT…………………………. 40
16. Comparison of Occupations between MC and NT…………………………… 40
17. Body Mass Index Classification of Respondents……………………………… 42
18. Shirt Issues …………………………………………………………………… 44
19. Shirt Issue Correlations...……………………………………………………… 46
20. Pant Issues……………………………………………………………………... 47
21. Pant Issue Correlations, Group MC.…………………………………………… 48
22. Pant Issue Correlations, Group NT.…………………………………………… 50
vi
23. Suit Issues……………………………………………………………………… 51
24. Group MC: Suit Issue Correlations …………………………………………… 53
25. Group NT: Suit issue correlations…………………………………………….. 55
26. Mean Interest Scores………………………………………………………….. 57
27. Interest Group by Race Within Group MC……………………………………. 59
28. Interest Groups Correlations with Length Issues……………………………… 59
29. Significant Correlations Between Interest Group and Other Variables……….. 60
30. Correlations Between Interest Scores and Reported Issues…………………… 61
31. Correlation of Clothing Interest with Clothing Issues………………………… 62
32. Clothing Interest Sub-factors Correlations with Clothing Issues……………… 62
33. Clothing Interest Sub-Factors Internal Correlations…………………………… 63
vii
LIST OF FIGURES
1. DeJonge Functional Design Process………………………………………………………9
2. The FEA consumer needs model………………………………………………………...11
3. Gravely (1999) buyer behavior model for the purchase of men‟s business suits………..24
4. The Dejonge functional design process for men‟s business clothing……………………28
viii
ACKNOWLEDGMENTS
I would like to thank my parents and sister for their constant love and support, and for
teaching me to think critically about the world around me. Thanks to: Kathleen, Mariah, Doug,
Curt, Hui, Lisa, Grace, Nancy, the VS Guildies and all the members of Springtime Tallahassee
for their friendship and encouragement. All my professors and teachers throughout the years
have been a source of inspiration, encouraging my creativity and academic endeavors. I would
like to thank Dr. Catherine Black and the other members of my committee for their patience,
support and guidance throughout my research and coursework programs. Last but certainly not
least, I would like to thank my husband Neil for supporting me both emotionally and financially
during my years of graduate school.
ix
ABSTRACT
This study surveyed men to determine what issues exist with men‟s business clothing.
Their clothing interest was also surveyed to examine the relationship between clothing interest
and reported fit issues. Numerous fit issues were found, at rates that indicate high levels of
dissatisfaction with ready-to-wear clothing fit. Suit shoulder width and pants leg length were the
most frequently reported issues. Clothing interest was found to be correlated to number of fit
issues reported. Fashion forward thinking was not found to correlate with reported issues, but
two other sub-factors of interest, self-analytical and correctness were found to correlate. Possible
causes for the issues found in the study were discussed, but further studies into the precise nature
of each issue will be required for the issues to be fully resolved.
1
CHAPTER 1
INTRODUCTION
In today‟s competitive apparel market, menswear companies must work harder to
produce a profit. Marketers are now aiming their messages at the men themselves, in addition to
their female partners as was traditional in years past. The rise of the “metrosexual” label and the
widespread acceptance of the “Queer Eye” trend have changed the face of menswear retailing.
While it is more acceptable for men to shop, men still tend to gravitate towards the familiar. Men
are loyal to brands and stores, very price conscious, and usually choose comfort over fashion
(Frith & Gleeson, 2004). Several studies agree that men ranked fit as the most important clothing
selection criteria (Hogge, Baer, & Kang-Park, 1988, Liu & Dickerson 1999). Therefore, a
company with better fitting garments will have a competitive advantage among equals.
To gain competitive advantage in the menswear market, it is important to know what fit
issues are being encountered by men, so better fitting clothing can be designed. Clothing
researchers have concentrated on the obvious fit issues faced by female consumers (Ashdown,
1998; Ashdown & Delong, 1995; Black, 1988; Carroll & Kincade, 2007; Workman, 1991; Yoo,
Khan, & Rutherford-Black, 1999). A few retailers have conducted sizing studies, such as the
SizeUSA study which was sponsored by 20 companies in 2003; however, the retailers did not
freely distribute results (SizeUSA). Overall, little has been published regarding fit issues
encountered by the US male population.
Researchers have identified specific issues with today‟s mass market sizing system for
women; however the issues faced by men have not been thoroughly explored. Elderly men‟s fit
problems have been researched, however young and middle-aged men‟s clothing problems are
still unknown (Hogge et al., 1988). A thorough record of the fit problems faced by men of
different sizes and statures will be essential to the design of practical and market friendly
solutions.
Measuring Fit Issues
Absolute measures of fit require lengthy and difficult techniques to collect in a large
population (Ashdown & Delong, 1995). Another technique uses trained observers as judges of
fit, but the method has proved somewhat imprecise and the judges use a fixed set of fit criteria
that may not be shared by the men wearing the clothing (Ashdown, & O‟Connell, 2006).
2
When selecting clothing for purchase, consumers base their decisions on the perceived
qualities of each garment. These can include apparent construction quality, styling, the way the
garment feels on their body, their reflection in a mirror, or the comments of another person. In
order to improve men‟s initial perceptions of a design, this study will measure how they perceive
their existing clothing. Their reported opinions reflect their perceived experiences.
Purpose
The primary goal of this study was to investigate fit issues with men‟s ready-to-wear
business clothing. By gathering this information, steps can be taken to improve the fit of
menswear during the design stages of clothing production.
A second goal was to examine the relationship between men‟s clothing interest and
reported fit issues. It can be theorized that if a man does not care about his clothing or
appearance, constituting low clothing interest, he may not report fit issues to the same extent as a
man with high clothing interest. Therefore, the following research questions were developed.
Research Questions
Q1: What fit issues are common in men‟s business clothing?
Q2: Do men vary in clothing interest, and if so, how?
Q3: What is the relationship between reported fit issues and clothing interest?
Q4: Do men with low clothing interest report fewer fit problems than men with high clothing
interest?
High overall interest is expected to correlate with knowledge of good fit and proper
sizing, but knowledge alone does not guarantee satisfaction. With knowledge of good fit,
consumers may report a higher rate of fit problems.
Hypotheses
The literature suggests that subjects with high clothing interest will be very conscious of
their own clothing. This awareness suggests that high interest men will notice fit problems
wherever they occur, and is the basis for the following hypotheses:
H1: Men with low clothing interest will report significantly fewer fit problems than those with
high clothing interest.
The Clothing interest concept was measured using a modified version of the Creekmore Clothing
Importance scale (Creekmore, 1971; Gurel & Gurel, 1979). In a pilot study, selected sections of
3
the original scale were reduced into 6 factors: Fashion forward, Awareness of other‟s clothing,
Self-Analytical, Correctness, Socio-Psychological awareness, and Practicality. For this phase of
the study, three clothing interest factors were retained: Fashion Forward, Self-Analytical, and
Correctness. See page 27 for the rationale for the factors.
H2:
A: Men reporting high scores on the “Fashion Forward” subscale will report significantly
larger numbers of clothing issues than those reporting low clothing interest.
B: Men reporting high scores on the “Self-Analytical” subscale will report significantly
larger numbers of clothing issues than those reporting low clothing interest.
C: Men reporting high scores on the “Correctness” subscale will report significantly
larger numbers of clothing issues than those reporting low clothing interest.
Rationale for the Study
Although many studies have investigated clothing problems faced by elderly male
(Hogge et al., 1988) or female populations, (Black, 1988; Yoo et al., 1999), few have examined
the general consumer issues with menswear. Men‟s buying behaviors and attitudes towards
clothing have been studied, and found to be significantly different than those of women (Frith &
Gleeson, 2004; Gravely, 1999; Liu & Dickerson, 1999; Moore, Doyle, & Thomson, 2001).
Because of the differences in attitude, men may cope with clothing problems in different ways,
however no studies have established the relationship between the two variables.
Sizing issues in women‟s clothing have been re-examined in many ways, statistically and
categorically. Several studies have developed remarkably accurate sizing charts that
accommodate over 95% of their base datasets using advanced multivariable equations or
relatively simple segmentation strategies (Tryfos, 1986; Gupta & Gangadhar, 2004), however,
the same calculations have not been published for male datasets. Much of the research into the fit
of men‟s clothing has been performed by the US military or other uniformed services, using
athletically skewed datasets (Brantley, 2001; Gordon et al, 1989; Laing et al, 1999). Because of
this bias, it is important to examine the current sizing system to determine if it meets the needs of
the general male population.
The men‟s business clothing market has experienced growth in the beginning of this
decade, as men have become more image conscious and office environments have shifted back
4
towards formality. Recently sales have stagnated as the market has become more bargain
oriented due to an increasingly pessimistic economic outlook (Mintel, 2007), however, holiday
sales of menswear were up 2.3% in 2007, even while womenswear was down 2.4 % (Barbaro,
2007). For best sales, manufacturers and stores should have consistent sizing that fits their target
market. To achieve this, they need to know their target customer‟s attitude towards clothing and
general figure type. This study will help manufacturers and retailers establish the issues with
current sizing systems, and how different types of male consumers view their clothing.
Limitations
The generalization of the results will be limited by the sample used.
Not all men are highly knowledgeable about their business clothing. This may lead to
inaccurate reporting of fit issues. Diagrams were used to clarify terms which may be
unfamiliar for some respondents.
Some men may be unaware of what constitutes “good fit”, so underreporting may occur.
Men may vary in fit threshold, and so vary in reporting rate of fit issues, even when
garment fit and body shape are identical.
Assumptions
Clothing interest has been studied separately from fit using many different scales and
populations (Cosbey, 2001; Gurel & Gurel, 1979; Perry, Schultz, & Rucker, 1983). For this
study, the interactions between interest and the reported rate of fit problems were examined. This
may be significant due to the common misperception that men have no fit or sizing problems. A
lack of complaints from men who either do not care or do not know what constitutes good fit
may distort any survey of fit problems, including this one. If a constant rate of fit problems is
assumed, and a difference is found between the reported rates of fit problems between high and
low interest men, the actual incidence of fit problems may be much higher than indicated by the
overall numbers. While it is reasonable to assume that both high and low clothing interest men
may have the same number of fit issues, lack of clothing interest may be fueled by negative body
self image, identified as body cathexis in some studies (Shim et al., 1991). Those men who fall in
the extreme ranges of body size may find their body socially unacceptable, leading to negative
self image (Shim et al., 1991). These extreme bodies will be harder to fit under traditional sizing
systems, and can be expected to have more than the average number of fit problems. In this
5
situation, the assumption that men have a consistent incidence of fit problems may be false.
Evaluating several types of clothing interest will create a profile of the types of consumers who
are responding to the survey.
In summary, this study examined the interactions between men‟s clothing interest and fit
issues in order to determine how clothing manufacturers can improve the fit of their products. If
significant patterns are found in the reported fit issues, changes may be made in garments to
accommodate previously dis-accommodated populations. Patterns in clothing interest sub-factors
may also assist retailers in their marketing efforts.
6
Definition of Terms
Accommodation – “those individuals who can be reasonably fitted by some size” within those
available (Ashdown, 1998). Accommodation and dis-accommodation are statistically
defined in terms of aggregate loss of fit over a population:
I
d(xn,ys) = Σ[di(xni,ysi)]2
i=1
“bi represents the range in which fit is judged to be perfect and the ai govern the rate at
which fit deteriorates outside this range.”
ail(ln(ysi) - bi
l - ln(xni)), if ln(xni) < ln(ysi) - bil
di(xni,ysi) = 0, if ln(ysi) - bil ≤ ln(xni) ≤ ln(ysi) + bi
h∙ aih(ln(xni) - bi
h - ln(ysi)),
if kn(xni) > ln(ysi) + bih
“The function di(xni,ysi) which measures the degree of misfit between the prototype and
an individual for the ith variable.” (McCullough, Paal, and Ashdown, 1998, p.495)
Body Cathexis - “the evaluative dimension of body image and is defined as positive and negative
feelings towards one‟s body” (LaBat & DeLong, 1990, p.43).
Business Clothing - clothing (suits, shirts, pants, and accessories) that is or could be worn in a
corporate workplace (definition new to this study).
Clothing Interest - “the extent to which an individual is favorably predisposed towards clothes”
(Kaiser, 1990).
Clothing Problem - “a source of concern relating to any specific garment type” (Black, 1988).
Garment Ease - “the difference between the size of the garment and the size of the wearer”
(Huck, Maganga, & Kim, 1997).
Fit - “The relationship of the size of the garment compared with the size of the wearer” (Huck,
Maganga, & Kim, 1997).
“A garment's fit involves interactions among multiple factors, including the size, proportions,
and posture of the wearer and the dimensions and drape of the garment.” (Ashdown &
O‟Connell, 2006)
7
Fit Criteria (Fit Preferences)- the amount of ease a person desires in various garment types
(definition new to this study). “Good fit varies as it is affected by the current fashion in
fit, the style and function of the garment, and the fit preference of the wearer.”
Fit Threshold - “the smallest difference in fit that can be sensed” (Ashdown & DeLong, 1995).
Pattern Grading - “accomplished by moving each point on the perimeter of the pattern the
amount needed to increase or decrease the pattern the desired amount” in order to
proportionally increase or decrease the overall size of a pattern to fit larger or smaller
individuals (Ashdown, 1998).
Selection Criteria - Outcomes from purchase and consumption experiences, which are expressed
with preferred attributes” (Engel, Blackwell, & Miniard, 1990 as cited in Liu &
Dickerson, 1999).
Size - “An item having specified measurements along certain dimensions” (Tryfos, 1986).
8
CHAPTER 2
REVIEW OF LITERATURE
This chapter contains an examination of past research on fit, sizing, clothing interest, and
the interactions between them. A review of design processes will be followed by the selection of
a design process to be used as the framework for the study.
Design Processes
The process of design has been modeled in several ways. While Lamb and Kallal (1993)
address the design criteria for the end product, DeJonge‟s functional design process methodically
presents steps designers should take to produce a functional end product.
A Comparison of Two Design Process Models
Many different models have been developed to formalize the design process. While most
designers do not consciously follow steps to achieve their final products, these models
adequately describe the processes involved. In her 2007 article on theory, Elaine Pedersen found
many different purposes for theory: explanation, prediction, sorting and organizing ideas,
advancement of knowledge, guidance of research, and description. Design process models serve
to describe the processes by which new products are designed in the industry, and to guide
further research-based product development. Research-based design draws on the published
literature to solve a design problem. Researchers can use newly developed materials and
techniques that may be too expensive or impractical for mass production. Commercial designers
create designs for their company‟s target customer, using established, well-tested techniques that
are cost-effective for their pricing goal. DeJonge‟s Functional Design Process (1984), and Lamb
and Kallal‟s (1992) Design Process theories describe events common to designers‟ creative
processes in order to guide systematic research. Lamb and Kallal‟s FEA consumer needs model
also helps scientifically describe the considerations involved in each decision during the design
process.
9
GENERAL REQUEST
EXPLORATION OF THE DESIGN SITUATION (divergence) General Objective Review of Literature Identify critical factors
PROBLEM STRUCTURE PERCEIVED (convergence) Data gathering User Input Materials Analysis Market Analysis
DESIGN SPECIFICATIONS
Activity assessment
Movement assessment
Impact assessment
Thermal assessment
Socio-psychological assessment
INTERACTION OF DESIGN CRITERIA
ESTABLISHED
State all criteria
Rank and chart criteria
Identify conflicts
PROTOTYPE DEVELOPMENT
DESIGN EVALUATION
Objective compare the performance of the design to the criteria
Subjective evaluation of the design
Figure 1. DeJonge Functional Design Process
Functional Design Process
In Susan Watkin‟s 1984 landmark book “Clothing: The portable environment,” DeJonge
outlined a process for the design of functional clothing (FDP). DeJonge‟s process comprises
seven steps: the general request, exploration of the design situation, problem structure perceived,
design specifications, interaction of design criteria established, prototype development, and
design evaluation. See Figure 1 for the visual representation of this process.
During the first step, General Request, the designer determines the goal or objective. For
example, a request might be customer driven, such as “our uniforms do not provide adequate
10
protection from the cleaning solutions” or the designer‟s inspiration. Rather than immediately
establishing set criteria, the designer must keep an open mind and explore the problem at hand.
For this reason, DeJonge views this step as a divergence, going from an initial idea to a broad
search for information.
The second step, Exploration of the Design Situation, is comprised of information
gathering from all available sources. It encompasses collection and organization of ideas. In this
step the designer narrows the conceptual scope of their search to identify the issues that will be
most critical to the success of the design.
Third, during the Problem Structure Perceived, the designer conceptualizes the problem
by interacting with consumers, analyzing the competing solutions to the problem, and
researching useful materials. User surveys about existing products can give the designer insights
into problems that may not have been immediately apparent. New materials may be available
that enable new design solutions.
Final criteria for the design are set during the Design Specifications phase of the process.
They are based on user surveys, and observation of the tasks required of the design. Movement
analysis can isolate the needed range of motion for each portion of the garment. Thermal,
protective, and aesthetic requirements are also set during this stage of the design process.
In the next phase of design, the factors influencing the final design are organized into an
interaction matrix. This matrix highlights which factors are compatible with each other and
which are in conflict.
Table 1
Example of an interaction matrix for fireman’s coveralls (Sindicich, unpublished)
Fireman‟s Coveralls Interaction
Matrix Minimize garment weight
Maximize fire protection
Minimize thermal retention
Maximize range of arm motion
No conflict No conflict No Conflict
Minimize garment weight
Accommodation needed
No conflict
Maximize fire protection
Accommodation needed
Conflict
Minimize thermal retention
No conflict Conflict
11
Designers can then do further research and develop strategies to resolve the conflicts
inherent in the problem at hand. This step is not found in other design process models.
Common to most process models, the Prototype Development stage brings the design to
reality. For each product, this stage of the design process will entail different actions, including,
but not limited to, patternmaking, fabrication, sourcing, production engineering, and costing.
While some design models are based on the manufacturing steps followed in the garment
industry, this model is primarily used in a research setting where prototype development may
follow a slightly different series of procedures.
The final step, Design Evaluation, includes testing, refinement, and finalization of the
design. Evaluation can be achieved through objective methods, such as range of motion
measurements, or subjectively through wear study surveys or visual judgments.
The FDP model is often used in the literature, both as a guide for methodical design
(Huck & Kim, 1997) scientific evaluations of design (Fowler, 2003) and in developing more
specialized models of design process (Krenzer, Starr, & Branson, 2000; Bye & Hakala, 2005;
Carroll & Kincade, 2007). It has also been used to advise businesses in effective product
development practices through outreach programs (Loker 2006).
DeJonge‟s functional design process was used to guide this study as part of a larger effort
to improve men‟s business clothing.
Functional, Expressive, Aesthetic
Lamb and Kallal‟s 1992 FEA Consumer Needs
Model was conceived as an aid “in developing
design criteria for a variety of customers.” It helps
designers conceptualize the problems they must
solve in their designs in order to best serve the end
user. While originally developed to assist student
designers in conceptualizing the design process, it
has since been successfully applied to several types
of design research.
As visually represented in Figure 1, the
consumer is the central core of this model. Adequate
Figure 2. The FEA consumer needs model (Lamb and Kallal
1992)
12
knowledge of the end user is key to the success of a design.
Consumers judge each product from within their cultural surroundings. Culture “acts as a
mediator or filter between the intended users of apparel and their requirements or desires in their
apparel items” (Lamb & Kallal, p.43). A product may function as intended but still be
unacceptable to the customer based on their cultural background. A design‟s success depends on
congruency with the target customer‟s culture. For example, a women‟s navy blue tank bathing
suit may function quite well as a swimsuit, but may be considered “frumpy” in some cultures and
scandalous in others. The model suggests that designers need to consider the cultural background
of their target customer during each step of the design process. In this study, men‟s business
clothes must be viewed within the workplace culture, which may vary by job type, residence, and
age of the respondent.
Design criteria are established by the designer in the initial steps in the design process.
The design criteria are requirements that the finished design must meet. The FEA model
classifies these criteria as Functional, Aesthetic, or Expressive concerns.
Functional criteria are concerned with a product‟s ability to perform the tasks required by
the customer. These include thermal regulation, protection from threats or nuisances, wearing
comfort, fit, range of motion, and other task oriented requirements. Even fashion clothing is
subject to functional restrictions. A garment that does not fit to the customer‟s satisfaction will
not be purchased, or if already purchased, will not be worn. For this reason it is important to
measure the fit issues experienced by the general population. These functional requirements are
filtered by the culture surrounding the user. A person in one culture may wear their pants close to
the body, while a person in another culture may wear theirs so loose that they almost fall off. The
designer must know their target customer to design suitable pants.
Expressive criteria control the non-verbal messages sent by the product. For example, a
uniform is created to express a consistent message about all employees of a company. A fashion
product must be congruent with the customer‟s self image in order to be purchased. Cultural
background determines how these messages are sent and interpreted. Out of cultural context,
expressive aspects of clothing may be misinterpreted or lost entirely. In the context of business
clothing, the wearer expresses their role in the workplace through their selection of clothes and
how they are worn.
13
Aesthetic concerns drive the fashion industry and are also a major concern in non-fashion
apparel, as even uniforms must be visually acceptable to the public. Tradition is a strong
aesthetic influence on many forms of dress. In some garments, the aesthetic concerns are
foremost, such as military dress uniforms. Military dress uniforms display features that were at
one time functional, but are now worn because they have always been there. The saber worn by
military officers is no longer a practical weapon, as a handgun is much more effective as a close
combat weapon, but the sword still serves both aesthetic and expressive functions during
ceremonial functions (Department of the Army, 2003). The last functional uses of the sword
were documented in the 1914 Saber Exercise manual. It now represents the combat readiness and
training of the wearer, expressing power, authority, and readiness for confrontation.
Aesthetically, the business suit has changed little in the twentieth century, and still
commands respect for the wearer. Demographic groups may vary in their interpretation of the
visual cues given in business dress. They also vary in their aesthetic preferences for business
suits (Gravely,1999).
Lamb and Kallal defined their general model for the design process with six steps:
Problem Identification, Preliminary Ideas, Design Refinement, Prototype Development,
Evaluation, and Implementation (p.44). Their model for design is driven by the consumer‟s
functional, expressive and aesthetic criteria for the product. These three criteria are established in
the Problem Identification stage. Following the preliminary ideas phase, where general
brainstorming is inspired by the FEA criteria, the design refinement stage involves careful
examination of each potential design for agreement with the criteria. Designers attempt to
balance the criteria, as they may conflict with each other. When developing prototypes, designers
or researchers take into consideration the consumer‟s practical FEA requirements. Evaluation of
prototypes is based on the functional, expressive, and aesthetic criteria. In the final evaluation, as
in most models, the designer can return to any previous step in the process if the evaluation
indicates that the prototype is not optimal.
The FEA model has been used in several different ways in the literature. First, the FEA
criteria are often used to establish benchmarks for evaluation stages of the design process (Choo,
2006). The FEA criteria have also been used to establish the critical factors involved in needs
assessment studies (Holland, 2007). Lamb and Kallal‟s process model is often cited during the
development of other design process models, but is less often actively used as a framework for
14
design (Parsons & Campbell, 2004). In this study, the FEA criteria will be most useful in
evaluating the resulting patterns.
Interrelationship of the Models
Process models and the FEA consumer needs
The Functional, Expressive, and Aesthetic consumer needs criteria can be applied to the
functional design process. Together they provide the designer with an extra depth of
understanding of the customer.
A comparison of the process models
The design process models share an underlying structure. Both the FDP and FEA design
processes share several aspects: 1) they are generally iterative, with the opportunity for a
designer to reconsider a previous step at any time, and 2) a set of basic phases. These phases are:
gathering information, generating ideas, finalizing the design, and evaluating the design. Some
other models also contain a step for the implementation of designs, including manufacturing and
distribution.
A significant difference between the FDP and the FEA design process model lies in how
the designer identifies the problem. See table 2 for a visual comparison of the FDP and FEA
design process models. Lamb and Kallal‟s process model begins with the identification of the
problem. DeJonge‟s FDP begins with “Design Situation Explored,” a broader examination of the
problem. By keeping an open mind and exploring the problem, the problem can then be
narrowed in the next phase of the DeJonge process, “Problem Structure Perceived.”
Table 2
The relationships between two design processes.
Lamb and Kallal (1992) DeJonge (1984)
Problem Identification General Request
Design Situation Explored
Preliminary Ideas Problem Structure Perceived
Design Refinement Specifications Described
Design Criteria Established
Prototype Development Prototype Developed
Evaluation Design Evaluation
Implementation
15
It only at this point that the problem is identified. In the FEA, the problem is explored after it is
isolated, which may pose a problem if the identified problem is only one symptom of a larger
problem. The juxtaposition of these steps gives the FDP a distinct advantage in situations where
the problem is not immediately clear, such as in the current examination of issues in menswear.
Functional Design in Applied Research
Over the years there have been many studies using functional design methods. The FDP
has been used in a variety of studies involving sports apparel, occupational garments and
protective gear. A few other studies have not noted their use of a design model but thoroughly
and methodically explore their targeted design situations.
The DeJonge functional design process was partially used in Fowler (2003) in an
evaluation of the comfort of ballistic vests. Neonatal clothing for the intensive care unit was
developed using the entire design process from general request to prototype evaluation (Bergen
et al., 1996) The FDP process allows designers to perceive the structure of the smaller challenges
to be overcome in their overall design process.
In-depth wear testing is performed in Crockford‟s (1977) study of fishermen‟s protective
clothing. The functional design process used in this study is not specific to one model, but could
be analyzed according to any process discussed above. It is an extremely thorough study that
takes into account many more variables than current studies would attempt. The researcher wear-
tested existing garments in a laboratory rain shed, interviewed and observed the fishermen at sea.
Crockford evaluated the existing garments and designed a new suit. The prototype and a new
commercially available suit were tested in the laboratory and in actual extended use at sea. The
new suit was highly preferable to the original suits. This study highlights the need for researchers
to observe the intended use. New designs coming on the market had seemingly useful features
that were being cut out by the sailors because the new feature had unanticipated side effects
(Crockford, 1977). This study exemplifies how the process of design can be scientifically
controlled and documented as a valuable part of the research literature.
Fit
Huck, Maganga and Kim (1997) define fit as “the relationship of the size of the garment
compared with the size of the wearer.” Several studies agree that men and women rank fit as the
16
most important clothing selection criteria (Hogge et al., 1988; Liu, & Dickerson, 1999;
Workman, 1991). If a garment does not fit to the wearer‟s standards, it will not be purchased.
These standards of fit are based in physical comfort, but also encompass our aesthetic
preferences and fashion trends. Clothing should conform, or fit, to the body without causing
discomfort or impeding movement. Ashdown and Delong tested expert judges‟ fit tolerances in
pants (1995). Their results showed that while wearing pants but without looking at the garments,
expert judges could only distinguish differences between pants two standard sizes apart. Ease is
the difference between the size of a garment and the size of the body. When allowed to view
themselves in a mirror, the judges could more accurately judge proper fit. Each man will have
different fit criteria; one may wear his clothing baggy, while another may prefer slim or tight
fitting garments. The clothing issues measured in this study are fit issues, but may have their
origins in dis-accommodation by current sizing standards.
Sizing
Sizing and fit are interrelated, since acceptability of fit is highly influenced by the size of
the garment. Sizing systems are a series of sizes designed with increasing measurements in an
attempt to maximize the number of people accommodated while limiting the number of sizes
manufactured. Manufacturers must balance the amount they spend to accommodate more
individuals with the additional cost incurred for each end-user.
Most people, men and women, have encountered ready to wear clothing that did not
match their body shape or dimensions. A garment size fits well if the wearer is satisfied with the
relationship between the garment and their body shape. A incorrectly sized garment could be too
small to cover the body, or so large that it is impractical. Judgment of fit is partially a subjective
decision, as some people prefer loose fitting clothing while others prefer it tight. Designers
should know their typical customer‟s fit preferences so that clothing will fit as that customer
expects. There are limits to the range of body dimensions fit by each size, therefore McCullough,
Paal, and Ashdown (1998) defined fit as “the correspondence of several body measurements to
values [body measurements] for which the garment is intended.”
Many recent research studies in sizing center on the development and testing of three
dimensional scanning technologies. AMS, or the Anthropometric Measuring System, is a
partially computerized method of size derivation based on measurements taken with a tailor‟s
17
measuring tape and software prediction. In testing at a Coast Guard uniform distribution center,
AMS had a 71% success rate, and was deemed unsuccessful (Brantley, 2001). Two factors
blamed for the failure are non-standardized measurement definitions and uneven fit criteria.
Automated measurement systems should be compared to 3D scanning systems, such as the one
used in Ring (2001), since the computer scan is most likely more accurate than manual
measurements. Ring reversed the traditional use of scanning technology, where a human is
scanned and sizing is generated from the resulting model, by using a computer program to
determine the best fit from a set of known garments. The man in the clothes, however, is the
ultimate judge of overall fit, even if he is fickle in his standards. For that reason, this study
collected self-reported clothing issues, rather than physically measuring clothing issues first-
hand. Self-reported clothing issues are indicative of the opinions of the current market‟s
consumers. Those opinions guide purchase decisions and are very important to apparel
manufacturers.
Ease
Ease is “the difference between the size of the garment and the size of the wearer” (Huck,
et al. 1997). Ease is an actual measureable distance, whereas fit is a relationship. There are two
kinds of ease: garment ease and style ease. Garment ease is the distance necessary between the
garment and the body for appropriate range of movement. Style ease is extra distance added for
aesthetic reasons. For example, all men‟s jackets have a small amount to garment ease to allow
for raising the arms and bending the torso, while some have significant style ease to allow the
garment to have its own tailored shape apart from the body. Judgments of fit are often confused
by style ease taking the place of garment ease when the wearer‟s body dimensions exceed those
the design was intended for. For this reason, loose fitting styles are expected to have higher rates
of accommodation.
Sizing and Fit Issues
Studies developing alternate sizing schemes have focused on protective apparel where
aesthetics are secondary to function (See Laing, Holland, Wilson, & Niven 1999 for an
example). Fit problems have been examined for elderly men, but sizing was not examined
18
(Hogge, et al., 1988). Fit and sizing issues have not been documented for a broader male
population.
Uneven fit criteria and non-compliance to standardized sizing charts are two obstacles in
the reform of men‟s clothing sizing. Both ISO/TR 10652:1991 and ASTM D 6240-98 set out
similar standards for the sizing of men‟s clothing, however manufacturers often choose not to
comply with voluntary standards. The variations in sizing are viewed in the clothing industry as a
positive goal, so that each individual may find a well fitting garment somewhere, as complete
compliance would result in a limited number of men who could not find well fitting clothes
anywhere. Variation can be introduced at several points in the manufacturing process, but
idealized body forms and fit models used to create garments are the largest problem (Salusso-
Deonier, 1989; Workman, 1991).
Military Sizing Studies
Militaries around the globe have been on the forefront of sizing research, especially that
of the USA. Because of their need to clothe large numbers of soldiers, and their complete control
of the manufacturing and distribution of uniforms, they can save money by creating optimized
sizing systems that fit the largest number of soldiers using the smallest possible number of sizes.
In the mass market, retailers are hesitant to adopt new systems, fearing that consumers will not
understand and therefore not purchase garments using the new system. Gordon, Bradtmiller,
Clausner, McConville, Tebetts, and Walker‟s (1989) Anthropometric Survey of U.S. Army
Personnel is a large dataset which has been used in most sizing optimization papers since its
release to the public. The downfall of this military survey is inherent to the armed forces: their
members fall within a set age range, and are athletic due to rigorous training. Anyone outside the
normal range of military clothing sizes is excluded from service. The significance of this
problem has been confirmed by Marras and Kim (1993). Their findings showed that the
anthropometric measurements of an industrial population were significantly different from the
1989 military data. Further anthropometric surveys were conducted using body scanners by the
Textile Clothing Technology Corporation (TC2) as part of the SizeUSA study, but the results are
not publically available for use in research (Textile Clothing Technology Corporation).
19
Current Commercial Sizing Systems
The current men‟s sizing system in the US (ASTM D6240-98) is based on one or two
body measurements per garment. Pattern grading, the conversion of one sized pattern into
another, is “accomplished by moving each point on the perimeter of the pattern the amount
needed to increase or decrease the pattern the desired amount” in order to proportionally increase
or decrease the overall size of a pattern to fit larger or smaller individuals (Ashdown, 1998,
p.336). A linear grade adds the same amount between each set of two sizes, i.e. 1 inch is added to
the size 30 pattern at the waist to get size 31, and 1 inch is added to a size 46 to get a size 47.
Other grading systems may use varying increments for different ranges, i.e. 1 inch is added from
size 30 to 31, but 1.5 inches are added from 40 to 41.
Menswear is produced in the sub-classifications of, Average, Tall, and Big and Tall.
Table 3 is a comparative shirt size chart for four prominent menswear retailers. Unlike women‟s
clothing that is offered by the same retailers in both petite and regular versions of sizes 2-20, and
plus sizes from 14-32, table 3 shows that only 5 shirt sizes are available in two body type
categories from the same retailer. Dress shirts are sized by neck and arm length, therefore 16/34
would indicate a 16 inch neck and 34 inch arm length. While these are two important
measurements in a shirt, proportional differences are not accounted for. A size 16/34 may fit the
neck and arm length, but be the wrong length in the torso, causing the pocket to be too high or
low and the shirt tails to come out of or bunch inside of the consumer‟s pants. No circumference
measurements are specified, including chest, arm, wrist, or waist circumferences. It is important
to know whether this significantly affects the performance of current ready-to-wear. For that
reason, one research question for this study is “What fit issues are common in men‟s business
clothing?” These measurements vary widely in the human population, as indicated by past sizing
studies (Gordon et al., 2004). Suits are sized by chest measurement and height category: Short,
Average, and Tall. This reliance on a single fixed measurement requires many men to pay for
alterations to the other dimensions of their suits such as: sleeve length, waist circumference, and
leg length.
Overall, the men‟s sizing system is based on five fixed measurements and one height
classification. Women‟s sizing is based on three fixed measurements: bust circumference, waist
circumference, and hip circumference, as well as a general body type classification, petite,
average, or tall (Workman, 1991). The men‟s system has the advantage in total number of
20
measurements, but unlike in women‟s clothing where all four considerations are used for shirts
and dresses and three are used for pants, menswear is based on fewer per garment.
Table 3
Sizing Methods for Men and Women
Women‟s Clothing Men‟s Clothing
Shirts Numbered size - Bust, Waist, Hip Height class Neck , Sleeve
Pants Numbered size - Waist, Height class Waist, Inseam
Suits Numbered size – Bust, Height class Chest, Height class
Clothing Interest
Clothing interest is “the extent to which an individual is favorably predisposed towards
clothes” (Kaiser, 1990). Although little has been documented about men‟s clothing interest, a
model for buying behavior was developed by Gravely for a study of men‟s suits (Gravely, 1999).
The model is a combination of models from Engel, Blackwell, and Miniard (1995), Sproles
(1979), and Chen-Yu (1995). In the model, consumers must be aware of a product, interested in
the product, and form an evaluation of the product before deciding to purchase the product.
Because fit is the most important criteria in purchase decisions (Hogge et al., 1988; Liu, &
Dickerson, 1999; Workman, 1991), it is important to know whether clothing interest affects a
man‟s evaluation of the fit of their clothing. For this reason the second, third, and fourth research
questions were formulated: (2) “Do men vary in clothing interest, and if so, how?” (3) “What is
the relationship between reported fit issues and clothing interest?” and (4) “Do men with low
clothing interest report fewer fit problems than men with high clothing interest?”
21
Table 4:
Comparative Shirt Sizing Charts Among Selected Retailers
Neck Size
Sleeve Length
32 33 34 35 36 37 38 39 40
14
LE Regular JAB Regular
JC Regular
LE Tall JAB Tall
14.5
BB "Exact" JAB "Exact"
LE Regular BB "Exact" JAB "Exact"
BB "Exact" LE Tall
15
BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact" LE Regular
BB "Exact" JAB "Exact" JC Regular JAB Regular
LE Tall, BB "Exact" JAB "Exact" JAB Tall JC Tall
15.5
BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact"
LE Regular BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact" LE Tall
BB "Exact" JAB "Exact"
16
BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact" LE Regular
BB "Exact" JAB "Exact" JAB Regular JC Regular JAB Tall
LE Tall, BB "Exact" JAB "Exact" JC Tall
JC Extra Tall
16.5
BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact"
LE Regular BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact" LE Tall
BB "Exact" JAB "Exact Tall"
17
BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact" LE Regular JC Regular
BB "Exact" JAB "Exact" JAB Regular JC Tall
LE Tall BB "Exact" JAB "Exact Tall" JAB Tall, JC Extra Tall
17.5 BB "Exact"
BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact"
LE Regular BB "Exact" JAB "Exact"
BB "Exact" JAB "Exact Tall" LE Tall
BB "Exact" JAB "Exact Tall"
18
JAB "Exact Big"
BB "Exact" JAB "Exact Big"
LE Big BB "Exact" JAB "Exact Big"
BB "Exact" JAB "Exact Tall" LE Regular LE Big and Tall JC Regular JC Big Regular
BB "Exact" JAB "Exact Tall" JAB Regular JC Tall JC Big and Tall
LE Tall, BB "Exact" JAB Tall JC Extra Tall
22
Table 5:
Comparative Shirt Sizing Charts Among Selected Retailers, continued
Neck Size Sleeve Length
32 33 34 35 36 37 38 39 40
18.5
JAB "Exact Big"
BB "Exact", JAB "Exact Big"
BB "Exact" JAB "Exact Big" LE - Big
BB "Exact" JAB "Exact Tall" LE Regular
LE Big and Tall, BB "Exact" JAB "Exact Tall"
LE - Tall, BB "Exact"
19
BB "Exact" JAB "Exact Big"
LE Big BB "Exact" JAB "Exact Tall" JC Big Regular
BB "Exact" JAB "Exact Tall" LE Big and Tall
BB "Exact" JC Big and Tall
JC Extra Tall
19.5 LE - Big LE Big and Tall
20 JAB "Exact Big"
BB "Exact" JAB "Exact Tall"
LE Big BB "Exact"
BB "Exact" LE Big and Tall, JC Big and Tall
20.5 LE Big LE Big and Tall
21 LE Big JC - Big and Tall
LE Big and Tall
21.5 LE Big LE Big and Tall
BB= Brooks Brothers, JC= JCPenney, LE= Land’s End, JAB= Jos A. Bank
Sleeve size ranges were assigned to the larger end of the scale.
Sleeve sizes ending in .5 were rounded down.
23
Table 6
Comparable Pants Sizing Chart Among Selected Retailers
Waist Size Inseam Length
28 29 30 31 32 34 36 38 unknown length
28 Gap L, Gap L, Gap LE, WM
29 Gap Gap L, Gap L, Gap L, Gap
30 Gap L, Gap BB, L, D, Gap BB, L, D, Gap L, Gap Gap Tall LE, WM
31 Gap Gap BB, L, D, Gap BB, L, D, Gap L, Gap L
32 Gap L, D, Gap BB, L, D, Gap BB, L, D, Gap L, D, Gap L, Gap Tall L – B&T, Gap Tall LE, WM
33 Gap D, Gap BB, L, D, Gap BB, L, D, Gap L, D, Gap L, Gap Tall
34 Gap L, D, Gap BB, L, D, Gap D BB, L, D, Gap BB, L, D, Gap L, D, Gap Tall
L – B&T, D – B&T LE, WM
35 Gap Gap BB, D, Gap BB, D, Gap BB, Gap Gap Tall
36 Gap L, D, Gap BB, L, D, Gap D BB, L, D, Gap BB, L, D, Gap L, D, Gap Tall
L – B&T, D – B&T LE, WM
38 Gap L, D, Gap BB, L, D, Gap D BB, L, D, Gap BB, L, D, Gap D, Gap Tall
L – B&T, D – B&T LE, WM
40 Gap L, D, Gap BB, L, D, Gap BB, L, D, Gap BB, L, D, Gap
L – B&T, D, Gap Tall L – B&T LE, WM
42 Gap BB, L, D, Gap BB, L, D, Gap BB, D, Gap
L – B&T, Dockers L – B&T
LE, WM, WM B&T
44 Gap
BB, L, L – B&T, D, D – B&T, Gap
Gap
BB, L, L – B&T, D, D – B&T, Gap
BB, L – B&T, D, D – B&T L – B&T
LE, WM B&T
46 L - B&T, D - B&T, Gap
L – B&T, D – B&T, Gap
L – B&T, D – B&T
LE, WM B&T
48 L – B&T, D – B&T
L – B&T, D – B&T
L – B&T, D – B&T WM Big
50 L – B&T, D – B&T
L – B&T, D – B&T L – B&T WM Big
52 L – B&T, D – B&T
L – B&T, D – B&T L – B&T
54 L – B&T, D – B&T
L – B&T, D – B&T
56 L – B&T, D – B&T
L – B&T, D – B&T
58 L – B&T, D – B&T
L – B&T, D – B&T
60 L – B&T, D – B&T
L – B&T, D – B&T
BB= Brooks Brothers, LE= Lands End, D= Dockers, L= Levi, WM= Wal-Mart, B&T= Big and Tall Note: Odd sizes over 35 are not shown, as none of the companies offered pants in those sizes.
24
Based on Gravely‟s (1999) model, it can be inferred that men with high clothing interest
would be more critical of the fit of their clothing than those with low clothing interest. Their
actual issues may be reported more accurately if they are more interested in clothes. Therefore
the first hypothesis was developed (H1): Men with low clothing interest will report significantly
fewer fit problems than those with high clothing interest. Sub-factors of clothing interest are
significantly correlated with each other and should follow the same pattern as overall clothing
interest.
Figure 3. Gravely (1999) buyer behavior model for the purchase of men‟s business suits
25
The Creekmore Clothing Interest scale from Creekmore (1971) was divided by Gurel and
Gurel (1979) into eight component factors: concern for personal appearance, experimenting with
appearance, heightened awareness of clothes, conformity, and sensitivity to comfort, as well as
enhancement of individuality and security. High scores on “concern for personal appearance”
indicate that a person “invests time, energy, and money in their clothes and how they look in
them” beyond what the average person invests. This type of person would notice if any part of
their clothing did not fit. “Experimenting with appearance” measures willingness to try new
clothing. People with a “heightened awareness of clothes” have a more academic view of
clothing. They reflect on their clothing and analyze other people‟s use of apparel. “Conformity”
is a tendency to behave and dress as others in a peer group. Also of interest is the factor
“sensitivity to comfort”. Those individuals highly sensitive to tactile irritations may report more
fit problems, regardless of their scores on other clothing interest factors. “Enhancement of
individuality” measures how much someone uses clothing to define themselves to others.
Subjects scoring high in the final interest factor, “enhancement of security,” link clothing with
their self-confidence and self-image. LaBat and Delong (1990) and Shim, Kotsiopulos, and
Knoll (1991) found that negative body self-image results in negative evaluations of clothing fit
and aesthetic acceptability, with little regard to actual fit or appearance.
The Influence of Interest on Reported Clothing Problems
Moore et al. (2001) surveyed divorced men in the United Kingdom and found that
divorced male consumers are generally uncertain of what constitutes good fit. The subjects did
not know what size they wear, and did not trust salespeople to measure them. They were
disinterested in clothing and ignored their appearance completely for as long as possible. Lack of
interest in clothing may have prevented them from noticing or reporting clothing problems, such
as bad fit or disrepair. Across the overall male population, interest in clothing varies (Gravely,
1999). Those with little interest in clothing may underreport fit problems, while those with the
most interest may notice every single issue, even those that are not necessarily problems as
defined by a tailor. Any study of men‟s fit issues must take into account this variability.
Past literature has explored few of the clothing issues faced by men, but significant
research has been completed into the clothing issues and clothing interest of women. The
existing studies into menswear have found that there are racial differences in clothing interest
26
and aesthetic preferences in suits (Gravely, 1999), that divorced men have little concept of their
proper size or how to shop for clothing (Moore et al., 2001). Research has collected the clothing
issues of elderly men (Hogge et al., 1998). One study also found that men use clothing to modify
their body image (Frith & Gleeson, 2004). Researchers are beginning to notice the issues existing
in the menswear market (Frith & Gleeson, 2004; Hogge et al, 1998; Moore et al, 2001). This
study will attempt to bridge a gap in existing knowledge by examining the relationship between
clothing fit issues and clothing interest.
27
CHAPTER 3
METHODS
This chapter describes the functional design process (FDP) as used for this study. It also
covers the development of the questionnaire instrument including a pilot study, factor analysis
and subsequent labeling of new factors. The desired sample is profiled and the techniques used to
analyze the data are reviewed.
The Functional Design Process Applied to the Current Study
This study gathered the information necessary to identify some of the clothing issues
experienced by men. Information gathered for and by this study co51nstitutes the first three steps
in the DeJonge‟s (1984) functional design process as shown in Figure 4. First, a request or goal
is established. For this study, the overall goal was to learn what fit problems must be overcome
to design comfortable and attractive men‟s business clothing. This study incorporated both the
functional and aesthetic aspects of garments. The design situation was explored through a review
of the pertinent literature and informal discussions with men. The problem definition included
analysis of the questionnaire results, in order to isolate problems not mentioned in previous
literature. The third step in the functional design process is the perception of the problem: a
conceptualization of what is required to achieve the initial goal. The questionnaire results can be
combined with further research into specific common clothing problems to form a complete
picture of the situation. The final step of the study will be to formulate an interaction matrix for
the issues found in this and other future studies.
28
Figure 4. The Dejonge functional design process for men’s business clothing. Note: Italicized portions will fall within the scope of future research.
Instrument Development
In 2007 a pilot study was conducted to establish validity for a modified version of the
Creekmore Clothing Importance scale as used by Gurel and Gurel (1979). A group of men were
surveyed with a subset of the original questionnaire to adapt it for use with a male sample.
29
The Creekmore Clothing Importance Scale (1971) contains a total of 89 items addressing
8 factors. The scale was shortened by removing two factors not believed to be pertinent to the
current study: conformity and modesty. Each remaining factor was reduced to 6-8 questions
each, using the factor analysis from Gurel and Gurel (1979) as a guide. When two questions were
similar, the one with stronger loading was used. Several questions were eliminated due to
outmoded wordings, such as “Days when I feel low I wear my gayest clothes.” Others were
eliminated due to high loadings on two factors.
The results of factor analysis on the pilot data formed different factors than those found
by Gurel and Gurel (1979). For brevity, the factors from Gurel and Gurel‟s 1979 article will be
referred to as the original factors, labeled in italics. The factors developed through the pilot study
factor analysis will be called the pilot study factors. The original factors were: concern for
personal appearance, experimenting with appearance, heightened awareness of clothes,
conformity, modesty, sensitivity to comfort, enhancement of individuality and enhancement of
security. The pilot study factors are fashion forward, analytical of other’s clothing, self-
analytical, correctness, socio-psychological awareness, and practicality. The pilot study
factors, labeled in bold, are explained below.
Interpretation of the factors
Factor 1 indicates a fashion forward viewpoint of clothing. These people want to
innovate and try new styles. Fashion forward is also significantly correlated with two original
factors: Experimenting with Appearance (r =.849, p<.001) and Enhancement of Individuality (r
=.914, p<.001). Fashion forward men want to innovate and experiment with their clothing, thus
the link to both original factors is logical. Frith and Gleeson (2004) found that men report lack of
interest in their appearance, but also that they wanted to look good in their clothing. The
stereotypical male does not pay attention to clothing and his appearance, but a range of responses
to both this study and Frith and Gleeson‟s survey revealed that men do not necessarily follow
that pattern.
Men scoring high on factor 2, Analytical of Others’ Clothing, analyze the clothing worn
by those around them, experiment with their appearances and plan their purchases in advance.
Unlike some other factors, this one seems fragmented, but the underlying concept connecting the
characteristics appears to be the tendency to think scientifically or logically about clothing.
30
“What are those around me wearing? What are people doing that is successful? What can I buy
that will be successful for me? These underlying questions seem to be central to this concept.
Frith and Gleeson (2004) found that men consciously modify their outward appearance with
clothing. The relationship of this concept with Heightened Awareness of Clothes (r = .747,
p<.001) and Experimenting with Appearance (r = .720, p<.001) seem logical.
Self-Analytical or factor 3 reflects willingness to self-analyze. These men learn from
their current clothing look and feel, and then attempt to apply that information. Both
Enhancement of Security (r = .708, p<.001) and Sensitivity to Comfort (r = .662, p<.001) are
correlated with this factor, but both original factors are more highly correlated with other current
factors. The relationship with the former factor may indicate an awareness of how clothing
serves as a buffer between men and the world around them. Comfort is one of the easiest aspects
of clothing to observe and modify, therefore a relationship to Sensitivity to Comfort is not
surprising.
Factor 4, Correctness relates to an individual‟s desire to be well-coordinated, neatly
dressed, and in attire appropriate for the situation at hand. Frith and Gleeson (2004) found that
men have a strong desire to dress according to cultural ideals. It encompasses correctness for
both social situations and personal expectations. Correctness correlates with the original factors
Concern for Appearance (r= .839, p<.001) and Sensitivity to Comfort (r = .672, p<.001). This
factor‟s relationship with personal appearance is paramount. Comfort is not as obviously related;
however, the mental aspects of comfort may be quite important to these individuals. Wearing
inappropriate clothes could be more uncomfortable than an itchy wool sweater for some
individuals.
Socio-psychological Awareness, or factor 5, indicates use of clothing as a tool for
psychological self-manipulation, and for establishing a public identity. The factor correlates
almost exactly with Enhancement of Security (r=.938, p<.001). It is a subset of questions from
the original Enhancement of Security factor identified by Gurel and Gurel (1979). Three
questions from the Gurel and Gurel (1979) factor became parts of other factors in this analysis.
The subset remaining indicates a positive use of clothes for psychological reasons, not just for
security. There was a negative loading for the question “I select clothes which do not call
attention to myself in any way,” which indicates that high scoring individuals used clothing to
call attention to themselves.
31
Factor 6, Practicality reflects a practical attitude towards clothing; these respondents
were money conscious and comfort oriented. Practicality is one of three current factors that
highly correlates with Gurel and Gurel‟s (1979) Sensitivity to Comfort. Comfort is indeed a very
practical concern. Thrift with money and time are also concerns for the individuals scoring
highly on this factor. Some individuals responded that they would wear clothing with buttons or
snaps missing. For this reason, these individuals would not be expected to correlate with
Correctness, which implies neatness; however that is the pilot study factor that correlated most
significantly with Practicality (r =.460, p<.001)
Table 7 Factor correlations
Concern
for
appearanc
e
Experimentin
g with
appearance
Heightene
d
awareness
of clothes
Enhancemen
t of security
Enhancemen
t of
individuality
Sensitivit
y to
comfort
Fashion
forward
Pearson Correlation
.559(**) .849(**) .502(**) .525(**) .914(**) .352(*)
Sig. (2-tailed)
.000 .000 .000 .000 .000 .016
Analytical of
others’ clothing
Pearson Correlation
.589(**) .720(**) .747(**) .495(**) .618(**) .404(**)
Sig. (2-tailed)
.000 .000 .000 .000 .000 .005
Self
analytical
Pearson Correlation
.374(*) .524(**) .634(**) .708(**) .348(*) .662(**)
Sig. (2-tailed)
.010 .000 .000 .000 .018 .000
Correctness Pearson Correlation
.839(**) .389(**) .384(**) .241 .328(*) .672(**)
Sig. (2-tailed)
.000 .007 .009 .106 .026 .000
Socio-
psychologica
l awareness
Pearson Correlation
.236 .525(**) .384(**) .938(**) .553(**) .298(*)
Sig. (2-tailed)
.114 .000 .008 .000 .000 .044
Practicality Pearson Correlation
.311(*) .234 .534(**) .128 .120 .674(**)
Sig. (2-tailed)
.035 .117 .000 .398 .428 .000
N=46, ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
32
The Final Instrument
The first section of the instrument asks how often and what type of business clothing the
respondents wear. This was to establish their exposure level and ensure that respondents are
referencing similar clothing for the rest of the survey.
The second section, Satisfaction with Garment Types, includes the items regarding fit
problems. Most were derived from Black (1988), however some are original and a small number
were based on Yoo et al., (1999). Original pictograms were inserted to ensure respondents
answered regarding the correct item of clothing. For each garment type (shirt, pants, and suits),
respondents reported the size they normally wear. It is reasonable to expect accurate reporting of
the size they wear, however the subjects may wear an inappropriate size. Self-reported size was
expected to be a more accurate gauge of the respondent‟s body size than actual body
measurements as subjects were not trained in how to take their own measurements, and some
may not possess a tailors measuring tape.
Clothing interest is of key importance to this study, and an overall self assessment was
added to the beginning of the clothing interest section. The single question response was
compared to overall interest scores to check reliability. After the pilot study, but before the
administration of the survey for this study, specific factors were selected for their pertinence to
the current goal, to 19 questions in three factors. Those factors are: Fashion Forward, Self-
Analytical, and Correctness. See Table 8 for the factors and the corresponding questions. The
questions were presented in random order. One, marked with an asterisk, will require reverse
coding. Each sub-factor was correlated with overall interest, therefore (H2A): “There will be a
significant positive relationship between „Fashion Forward‟ clothing interest and the number of
fit issues reported”, (H2B): “There will be a significant positive relationship between „Self-
Analytical‟ clothing interest and the number of fit issues reported”, and (H2C): “There will be a
significant positive relationship between „Correctness‟ and the number of fit issues reported.”
The final section of demographic questions also includes one original question, asking
respondents to self-report their fitness level. This question was used to interpret their body shape
and size. When paired with their sizes worn, fitness level helps distinguish between tall, slim and
short, heavy men who wear the same size shirts.
33
Table 8 Clothing interest factors
Factor Statements
Fashion forward I try to buy clothes which are very unusual
When new fashions appear on the market, I am one of the first to own them
I try on clothes in shops just to see how I will look in them without really planning to buy
I try on some of the newest clothes each season to see how I look in the styles.
I read magazines and newspapers to find out what is new in clothing
I am more concerned about the care of my clothing than my friends are about theirs
I enjoy wearing very different clothing even though I attract attention
Self-Analytical I get rid of garments I like because they are not comfortable
I wonder why some clothes make me feel better than others
I wonder what makes some clothes more comfortable than others
I use clothing as a means of disguising physical problems and imperfections through
skillful use of color, line, and texture
I get bored with wearing the same kind of clothes all the time
Certain clothes make me feel more sure of myself
Correctness I have something to wear for any occasion that occurs
I am irritable if my clothes are uncomfortable
My appearance in business clothing is important to me
It bothers me when my outfit is not color coordinated
I like dark or muted colors rather than bright ones for my clothes *
It bothers me when my shirt tail keeps coming out
Non-factor statements
I can find up-to-date fashions in my size
Wearing fashionable business clothing helps me achieve my career goals
Income, marital status, education and race were correlated with clothing interest and the
number of fit problems. Gravely (1999) found that black males generally had higher clothing
interest than white males. A free response section was included to capture any other insights or
complaints the respondents have about clothing.
Subjects
The population targeted for this study was men between the ages of 20 and 55 who
purchase ready-to-wear business apparel in the USA. Twenty-year old men have graduated from
their teenage years and entered college or are already beginning their professional careers. Those
over 55 begin to experience changes in body shape due to the aging process. The fit problems of
this older group have been studied separately by Hogge, Baer, and Kang-Park (1998). Each man
has aesthetic preferences that influence what they consider a fit problem. For this reason, this
study was limited to business clothing, which has a somewhat defined standard for acceptable fit.
The sample largely comprised men from the southeastern USA. Because international
34
differences in selection criteria and clothing attitudes have been documented in the literature (Liu
& Dickerson 1999), the results should not be generalized internationally. Generalization across
the USA may be limited due to regional differences in available brands and cultural differences
in various areas of the country.
Data was collected from two sources. First, 300 surveys were distributed and a sample of
298 responses was collected from volunteers via paper surveys at “MegaCon” a regional comic
book and pop-culture convention in Orlando, FL (group MC). Volunteers were solicited from the
ticket sales line, a semi-random arrangement of people. Those participating received a free comic
book. The respondents varied from age 18 to 55. For this study, only those at or above 20 years
of age were included in the analysis. Removal of incomplete or incorrectly completed surveys
left 233 usable survey responses (See Appendix C). The study will include 78% of the original
298 completed group MC surveys.
A further 100 responses were collected via an online survey using HostedSurvey.com
(group NT). Respondents were invited to participate by a regional menswear company, Nic‟s`
Toggery, via an email. All but one response was useable, however some respondents did not
complete the final section of the survey.
The total number of usable surveys was 332. Specific questions may have fewer
responses, as some questions were left blank or omitted due to unclear responses. Please refer to
Appendix C for a detailed explanation of the error checking procedures used to screen the
responses.
Data Analysis
To evaluate the results of the survey in terms of the research questions, the fit issues of
each respondent were tabulated. Within each clothing item (shirt, pants, etc.), size and body area,
frequencies of fit problems were tabulated separately. For each size or size range, a large number
of fit issues in one or more areas could indicate problems with the grading scale used to
determine that size. The particular fit problems faced by categories of individuals will direct later
redesigns of men‟s clothing. Each subject‟s reported fit problems were summed into a total
number. These statistics address research question number one.
35
The second research question, “How will men vary in clothing interest?” was addressed
by tabulating overall and sub-scale scores. The scores were analyzed for correlations to
demographic variables and specific fit issues.
To answer the third and fourth research questions, “What is the relationship between
clothing interest and reported fit issues?” and “Will men with low clothing interest report fewer
fit problems than those with high clothing interest?” the sample was divided in three sections by
interest scores: high, medium, and low clothing interest groups. The middle group, comprising
approximately 29% of the total sample was removed and the two remaining groups (low and
high) were compared in total number of fit problems reported. If the actual frequency of fit
problems is assumed to be constant in the population, this comparison of high and low interest
individuals highlights different reporting rates. If those falling in the high or low groups share
characteristics, the previous assumption may be incorrect. Either conclusion will clarify the
relationships between the variables.
Based on Gravely, 1999, it is expected that race will correlate with variations in clothing
interest. Not all of the demographic variables may be relevant to the final model. Of special
interest is the relationship between the interest factors and number of reported fit issues, and that
between the body size variables (height, weight, size worn, and fitness level) and number of
reported fit problems.
36
CHAPTER 4
RESULTS AND DISCUSSION
This chapter addresses the demographics of the sample used for this study and presents
comparisons are drawn between the sample groups. Each research question is addressed with
statistical analysis of the data, and the hypotheses are confirmed or refuted as appropriate.
Demographics
The demographic and physical traits of both groups were analyzed separately to
determine whether enough between-groups differences existed to require analysis of each group
separately. The age of group MC‟s respondents was clustered at the lower end of the range,
resulting in a mean of 28.71 years of age (Table 9). The height of respondents had a wide range
due to one exceptional case. One respondent was 7 foot 7 inches tall. The remainder of the
population ranged from 4 foot 11 inches to 6 foot 6 inches tall. Because of the size of the sample,
this result does not strongly affect the mean result. The outlier height was retained. Weight
ranged widely, from 103 pounds to 400 pounds. Weight and age did not correspond directly to
height, as there was a variety of body types represented.
NT‟s demographic and physical characteristics were more homogenous than MC‟s (Table
10). The ranges of ages, heights, and weights were smaller. Comparatively, NT was slightly
taller, with a mean height of 71.3 inches versus the MC mean of 70.6. Height differences were
not statistically significant (p=.07). The NT group was also significantly older, with a mean age
of 44, versus the MC mean of 28.7 years of age (t = -12.8, p<.001). The MC and NT groups did
not vary significantly in mean weight, at 201 and 203 pounds.
Table 9 Group MC demographics
N Range Minimum Maximum Mean Std. Deviation
Weight (lbs.)
223 297 103 400 201.15 47.197
Height (in.) 232 32 59 91 70.556 3.602
Age (yrs.) 233 35 20 55 28.71 8.437
37
Table 10 Group NT demographics
N Range Minimum Maximum Mean Std. Deviation
Weight (lbs.)
99 200 135 335 203.27 42.179
Height (in.) 99 16 64 80 71.30 3.008
Age (yrs.) 96 33 22 55 44.04 10.399
MegaCon draws the majority of its attendance from Florida, although some people travel
from across the country to attend. Eighty-three percent of respondents were from Florida (Table
11). Those who reported their city of residence, rather than state only, lived in many regions of
the state, with the smallest number from the northwest “Panhandle” region of Florida. This
makes sense, as the travel distance is farthest for that region of Florida.
Table 11 Group residency by state
MC NT
Frequency Percent Frequency Percent
AL 1 .4%
CA 1 .4%
FL 194 83.3% 68 76.4%
GA 5 2.1% 6 6.7%
ID 1 1.1%
IL 1 1.1%
MA 5 5.6%
NC 1 .4%
NJ 2 2.2%
NM 1 .4%
NY 3 3.4%
OK 1 .4%
OR 1 1.1%
PA 2 .9%
PR 1 .4%
SC 1 .4%
SD 1 .4%
TX 1 1.1%
WA 1 .4%
38
The NT group was pulled from the customers of a menswear retailer in Florida, so the
geographic distribution of respondents in group NT was expected to be limited. Although 76%
were from Florida, others reported residency from 8 other states across the country. This group
included a larger percentage of respondents from outside Florida.
Past studies have found differences in clothing interest between racial groups, and the
racial makeup of the 2 groups is shown in Table 12. The majority of the MC group was
Caucasian, however a significant portion of the sample was Hispanic. This may be due to the
racial makeup of the state of Florida. In the 2003 American Community Survey, 18.7% of
Floridians reported Hispanic descent. The low percentage of African-American respondents may
be related to the subject of the convention. Comic books have long struggled to gain an African-
American audience with little success (Donald). NT was over 90% Caucasian, with little ethnic
diversity. The significant difference in ethnic makeup between MC and NT is shown in Table 12.
Table 12 Comparison of race between MC and NT
MC NT
Race Frequency Percentage Frequency Percentage
Caucasian 155 70.45% 80 92.0%
African-American 11 5% 3 3.4%
Hispanic 46 20.91% 2 2.3%
Asian 2 0.91% 1 1.1%
Other 6 2.72% 1 1.1%
Total 220 87
The groups displayed differences in educational level (Table 13). As could be expected
by the low mean age of the MC group, few had attained graduate degrees, and only a third of the
respondents had received a bachelor‟s degree. Fifty-two percent reported “some college,” a
figure that could indicate current enrollment in college. The MC group may contain many
individuals who have not yet entered the professional job market. In contrast, group NT is highly
educated, with 86 percent holding a bachelor‟s or higher degree.
39
Table 13 Comparison of education between MC and NT
MC NT
Frequency Percent Frequency Percent
Some High School 1 .4 0 0
High School diploma 30 13.15 3 3.4
Some college 119 52.19 9 10.2
Bachelor‟s degree 50 21.93 33 37.5
Some graduate school 6 2.63 12 13.6
Graduate or Professional Degree 22 9.65 31 35.2
N= 228 88
The majority of the MC group reported household incomes below $50,000 (72%) as
shown in table 14. Only 11% reported an income above $109,999. The NT group‟s annual
household income was fairly evenly distributed, with the largest percentage reporting over
200,000 dollars per year. Few reported annual incomes below 50,000 dollars per year. The retail
store whose clients made up the sample is priced at the high end of the local market, thus these
results are not surprising. The MC group‟s clothing purchase capability is significantly lower
than that of the NT group.
Table 14 Comparison of annual incomes between MC and NT
0%
5%
10%
15%
20%
25%
30%
35%
Und
er
20000
20,0
00-
49,9
99
50,0
00-
79,9
99
80,0
00-
109,9
99
110,0
00-
149,9
99
150,0
00-
199,9
99
200,0
00
and u
p
MC
NT
While a large majority (82%) of the NT group was married (Table 15), the MC group
was mostly single (68.5%). Slightly less than 30% of the MC group reported that they were not
currently dating. Only 26.5 % of group MC reported being married, 55.5% less than group NT.
40
Table 15 Comparison of marital status between MC and NT
MC NT
Frequency Percent Frequency Percent
Single, not dating 67 29.6 5 5.6
Single, dating 88 38.9 8 9.0
Married 60 26.5 73 82.0
Divorced 6 2.7 2 2.2
Widower 3 1.3 0 0
Other 2 .9 1 1.1
N= 226 89
Table 16 Comparison of occupations between MC and NT
MC NT
Frequency Percent Frequency Percent
Laborer 4 1.8 0 0
Student 22 10.3 2 2.4
Retail/Sales 27 12.7 8 9.8
Customer Service 27 12.7 4 4.8
Teacher 4 1.8 3 3.7
Military/Law Enforcement 10 4.7 1 1.2
Creative 16 7.6 0 0
Skilled Trades 13 6.1 2 2.4
Technical 38 17.9 4 4.9
Management 25 11.8 24 29.3
Administrative 11 5.2 17 20.7
Research/Analyst/Law 11 5.2 16 19.5
Medical 4 1.8 1 1.2
N= 212 82
MC comprised a wide variety of occupations; however the largest group was in technical
positions, such as computer networking (Table 16). Smaller numbers held customer service,
retail and management positions. The respondents in the NT group were largely in management
or law positions. The significant between-groups difference in employment determines the
culture in which the men are wearing their business clothing, thus affecting how they judge their
clothing.
41
Body Mass Index
The US government uses a calculated index called the Body Mass Index, or BMI to
gauge human body type. The National Center for Health Statistics uses the index to measure
children‟s growth rate, and the Center for Disease Control uses BMI to screen adults for weight
problems (CDC, 2007). The BMI formula is: weight (lb) / [height (in)]2 x 703 (CDC, 2007).
Table 17 shows the classification of the respondents from each group and the national data
collected in the National Health and Nutrition Examination Survey (NHANES) for 2003-2004
(National Center for Health Statistic, 2004). NHANES collects health and anthropometric data
on a wide US sample including men and women of all ages. It is used in numerous federal
government reports on the health of the American population. The raw data is available for
research purposes, such as this study.
Approximately 3% of the MC group respondents fell in the underweight category. Their
mean and median BMI was 28.4, slightly higher than the 27.9 mean BMI measured by the
NHANES study. NT respondents had a mean of 28.07, very close to the national mean. The
percentage of MC respondents falling in the obese range was 7.3% higher than the national rate
as measured by the NHANES study from 2003-2004, while the percentage of overweight
respondents was 8.7% lower than the national statistic (Table 17).
Percentage breakdowns for the NT group were similar to the national figures, except for a
complete lack of underweight respondents. The NT group contains 3.6 % more overweight and
2.5% fewer obese men. It could be argued that they are slightly healthier than the national
sample due to the lower percentage of obesity. The BMI measurement does not take into
consideration body composition and skeletal differences, so it is impossible to confirm the
previous statement.
Over both groups, the prevalence of obesity was 4.3% above the national average, while
overweight was 7.9% lower. Normal BMI‟s (30.5%) were recorded almost exactly at the
expected rate of 30.8%, so the combined sample should be representative of the overall US
population.
42
Table 17 BMI classification of respondents
BMI
range
MC NT Overall
NHANES
Data*
2003-2004
Frequency Percent Frequency Percent Frequency Percent Percent
Underweight Below
18.5
7 3.1 0 0 7 2.2 1.6
Normal 18.5-24.9 68 30.5 31 31.3 98 30.5 30.8
Overweight 25-29.9 65 29.1 41 41.4 106 33.0 37.8
Obese 30 and above
83 37.2 27 27.3 110 34.3 29.9
Total 223 99 321
* National Center for Health Statistics, NHANES dataset, cases selected by age 20-55, male gender.
Separation of Groups
For the statistical analysis of the data, the MC and NT groups were treated separately in
most cases due to significant demographic and physical differences between the groups. These
differences occurred in age, marital status, income, educational level, and occupation. The NT
group was older, more likely to be married, make more money, have attained higher levels of
education, and worked more often in executive positions than the members of group MC.
Research Questions
Question One
The first research question was: “What fit issues are common in men‟s business clothing?” In
order to evaluate the results of the survey in terms of this research question, the prevalence of
each clothing issue was determined. The fit issues of each respondent were tabulated. Clothing
issues related to vertical measurements and circumferential measurements were separately
tabulated. For each size or size range, a large number of fit issues in one or all areas could
indicate problems with the grading scale used to determine that size. The particular fit problems
faced by categories of individuals will direct later redesigns of men‟s clothing. The tabulated
issues were examined for correlations to several other variables. These statistics will answer
research question number one.
43
Individual Issues Respondents were asked to report whether certain aspects of their clothing
were acceptable or fell into polar categories such as “too small” versus “too large”. The answers
were placed in continuum order: too small, appropriate, and too large. For all issues, the largest
percentage of respondents reported acceptable fit. Of all the issues, the largest percentage (31%)
reported their pants legs were too long. Close behind were problems with their shirt neck size
being too tight (27.8%), suit shoulders too narrow (25.6%), pants of a suit sized too large
(24.5%), and shirt tail too short in length (23.9%). While pant leg length was a frequently
reported issue, pant legs are sometimes intentionally left un-hemmed or longer than needed with
the expectation that they will be hemmed after purchase. It was not possible to separate cases
where the issue was due to un-hemmed pants from those where the individual cannot purchase
the proper length pants off the rack.
Suit shoulder width issues in suits were reported by the highest percentage of participants
(40.2%), when counting both the excess and insufficient values in each area (too wide + too
narrow, too small + too large). Other problem areas reported by more than one third of
respondents were: suit sleeve length (40%), pant leg length (39.5%), suit pant size (37.7%), shirt
neck circumference (34.1%), shirt tail length (36.5%), shirt sleeve length (35.1%), and crotch
length (34.4%).
It should be noted that the most common problems for the MC and NT groups were
different. For group MC, suit shoulder width problems, shirt tail length, shirt sleeve length and
shirt neck problems were reported most frequently at rates of 47%, 38%, 38% and 37%
respectively. The NT group most frequently reported problems with suit pant size (59%), pant
leg length (45%), shirt sleeve length (45%), pant crotch length (44%), seat of pants (40%), torso
area (40%) and shirt waist circumference (37%). These rates are significantly higher than the
reporting rates of group MC. This could indicate that the NT group experiences more issues with
their clothing, or that they more accurately report issues that exist. The third possible reason for
the difference could be the shopping destinations frequented by the two groups. Because the
sample should be representative of the larger population, an apparel company could gain
significant market share if they solve even a few of the most common issues.
Shirts The most common problems identified for shirts were all related to the garments being
too small in a dimension (Table 18). The most common problems for group MC were neck
circumference (30.5%), shirt tails too short (26.7%), and shirt sleeves too short (26.6%). Group
44
NT‟s most frequent issue was waist area too loose (29.8%), with several other issues reported by
14% to18% of respondents. One important relationship to note is the high incidence of “neck too
tight” in group MC, while group NT had a significantly lower incidence of the same issue. As
shirts are normally selected by neck size, this indicates that the NT group was more likely to be
wearing the proper, larger size. As a consequence, the disparity in “waist too loose” reporting
rates may be caused by the MC group wearing shirts that are too small, with proper waist fit,
while the NT group wears shirts that are the proper neck size but too large in the waist area. The
same argument may apply to the between-groups disparity in the other top six most frequently
reported issues.
Table 18 Shirt issues
MC NT Overall
Issue Percentage Reporting
Percentage Reporting
Percentage Reporting
Neck Too tight 30.5 18.6 27.8
Shirt tails Too short 26.7 17.5 23.9
Shirt cuffs Too tight 24.2 16.5 21.9
Shirt sleeves Too short 26.6 10.3 21.6
Shirt waist Too loose 13.4 29.8 18.2
Shirt collar Too small 20.6 8.2 17.6
Shirt sleeves Too long 11.7 17.5 13.5
Shirt tails Too long 11.6 14.4 12.4
Shirt pocket Too high 7.2 9.3 7.8
Shirt waist Too tight 7.6 7.4 7.5
Shirt cuffs Too loose 8.1 4.1 6.9
Neck Too loose 5.2 8.2 6.3
Shirt buttons Too close together 6.8 3.1 5.7
Shirt buttons Too far apart 5.0 7.2 5.7
Shirt collar Too large 3.9 7.2 5.0
Shirt pocket Too low 5.4 2.1 4.4
Correlations. The correlations between sizes worn and individual issues were examined
to determine which are related. Those relationships could reveal that some issues lead to other
issues. For example, if a correlation is found between sleeve length issues and pocket placement
issues, or if a subject reports their shirt tail length is too long, they may have a shorter torso than
45
the designer intended the shirt to fit. The extra length in the torso would lead to the pocket
placement falling too low on the chest.
Neck size should correspond with overall width and length of a shirt, due to pattern
grading; proportionally increasing or decreasing the overall size of the pattern in all dimensions.
In the overall sample, including both MC and NT groups, neck size was found to significantly
correlate with issues with button spacing (r =.204, p<.01), shirt tail length (r = -.145, p<.05), cuff
circumference (r = -.148, p<.05) and waist circumference (r = -.189, p<.01) (See Appendix D,
table A1). In the MC group, neck size also corresponded to sleeve length issues, while in the NT
group it did not. In group MC, neck size is negatively correlated (r = -.294, p<.01) with button
spacing issues, indicating that smaller sizes have issues with buttons too far apart, while larger
sizes have buttons too close together. In group NT however, the variables were strongly
positively correlated (r = .358, p<.001) indicating the opposite relationship. The same opposite
relationship occurs between sleeve length and shirt tail length issues, except the MC group has a
positive relationship (r= .33, p<.01) and group NT has a negative relationship (r = -.243, p<.05).
Over the entire sample, sleeve length was found to correlate with button spacing issues (r = .171,
p< .05) and sleeve length issues (r = -.183, p<.05). These opposite results may indicate that the
origin of button spacing issues is more complex than others. Button spacing, tail length and
pocket placement are increased or decreased incrementally when grading sizes. The negative
relationship between neck size and button and sleeve length issues indicates a general decrease in
those issues as sizes get larger. The positive relationship between sleeve size and tail length
indicates that the issues are more common as sizes get larger. Large sizes are often available in
more sleeve lengths than smaller sizes; however it is worth investigating whether commercially
graded shirts adjust the overall length when varying sleeve size.
As discussed in the literature review, shirts are based on two dimensions of the body,
neck circumference and sleeve length, which can be easily measured by sales staff in order to
properly fit the customer. There is a significant difference in reported problems between the
groups (see Table 19) that could be explained by the source of each sample.
The largest portion of the MC group shops at department stores (48%) where they must
know their size before purchasing shirts, because less customer service is available. Group NT
was drawn from the client list of a high-end menswear store (74% reported shopping at men‟s
specialty stores). The menswear store‟s employees were observed carefully measuring each
46
client upon request and assisting them in the selection of the proper size shirt. Therefore the NT
group reported a smaller percentage of problems in areas directly related to neck and sleeve size
than those in the MC group. It can be inferred that if every man was periodically measured for
their proper size and given an easy way to remember it, such as a wallet card, the overall
satisfaction level with shirts may increase. The most important issues for the industry to consider
are those experienced by men wearing the proper size shirts and those that do not correlate with
size worn.
Table 19 Shirt issue correlations
Sle
eve
Len
gth
Can
fin
d s
hir
ts
that
fit
Nec
k s
ize
Issu
es
Co
llar
siz
e
Issu
es
Po
cket
hei
ght
Issu
es
Bu
tton
spac
ing
Issu
es
Sh
irt
tail
len
gth
iss
ues
Sle
eve
len
gth
issu
es
Cu
ff
circ
um
fere
nce
is
sues
Wai
st
circ
um
fere
nce
Issu
es
MC
Neck Size
Pearson Correlation
.452(**) .142 .010 -.050 -.074 -.294(**) .031 -.221(*) -.140 .006
Sig. (2-tailed)
.000 .152 .922 .615 .457 .003 .755 .025 .157 .949
N 58 103 106 104 104 103 106 103 104 105
Sleeve Length
Pearson Correlation
1 .018 -.004 .095 -.005 -.091 .330(**) .167 -.073 .192
Sig. (2-tailed)
.893 .975 .478 .968 .499 .010 .214 .584 .149
N 60 57 59 58 58 58 60 57 58 58
NT
Neck Size
Pearson Correlation
.403(**) .055 -.055 -.075 -.010 .358(**) -.093 .006 -.172 -.249(*)
Sig. (2-tailed)
.000 .590 .592 .465 .924 .000 .364 .952 .093 .015
N 98 97 97 97 97 97 97 97 97 94
Sleeve Length
Pearson Correlation
1 -.048 .116 -.112 .031 -.067 -.243(*) -.501(**) .022 .095
Sig. (2-tailed)
.640 .256 .276 .764 .512 .016 .000 .831 .363
N 98 97 97 97 97 97 97 97 97 94
** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Issues refers to reported problems on both ends of the continuum, e.g. too small and too large
47
Pants
Men in the study reported numerous issues with the fit of their pants. For each issue
shown in table 20, between 39.5% and 17.5% of the overall participants reported issues in one
direction or the other. For example, “legs too long” was reported by 30.1% while “legs too short”
was reported by 9.4%, totaling 39.5%. These high numbers indicate a very high level of
discontent. A past study of women‟s sizing optimization achieved an accommodation rate of
96% using fewer sizes than commercially available (McCullough, Paal, & Ashdown, 1998). If
the dis-accommodation rate for men in this age range is at least 25%, (the mean of the above
listed issue reporting rates), there is significant possibility for improvement through the
optimization of menswear sizing systems.
Many men‟s pants are designed slightly long to accommodate more men, with the
assumption that some may have the pants hemmed. Hemming can only take off a moderate
amount before the intended knee point on the leg is significantly lower than it was designed to
be. This problem is especially obvious in flared or boot-cut casual pants, but exists in tapered leg
trousers as well. The addition of extra length for hemming explains part of the high overall
percentage reporting excess length. In other cases, respondents may be wearing the wrong
inseam size. It is important for a future study to separate those wearing the wrong size through
ignorance from those wearing the wrong size because the correct size is unavailable.
Table 20 Pant issues
Issue MC NT Overall
Percentage Reporting Percentage Reporting Percentage Reporting
Legs Too long 26.9 37.5 30.1
Crotch length Too short 19.7 16.7 18.8
Seat of pants Too tight 12.6 29.5 17.6
Hip Too tight 11.8 24.0 15.5
Crotch length Too long 10.3 27.1 15.4
Seat of pants Too loose 13.5 10.5 12.6
Leg Too tight 7.2 15.6 9.7
Legs Too short 10.3 7.3 9.4
Leg Too loose 9.0 6.3 7.8
Hip Too loose 7.3 7.3 7.3
48
The second most frequent overall issue, insufficient crotch length, warrants further
investigation. The third and fourth most frequent overall issues were in the seat of the pants and
hips. Issues in both circumferential and vertical directions may indicate the need for two cuts of
pants.
Table 21 Pant issue correlations, Group MC
Legs too
short/long
Crotch length too short/long
Hips too tight/loose
Leg too tight/loose
Seat too tight/loose
MC Waist Size
Pearson Correlation
-.120 -.020 -.032 -.063 -.041
Sig. (2-tailed)
.080 .771 .644 .359 .549
N 212 212 209 212 212
Inseam
Pearson Correlation
-.055 .020 -.023 -.061 .080
Sig. (2-tailed)
.512 .809 .791 .468 .343
N 142 142 140 143 142
Pants legs are
Pearson Correlation
1.000 .178(**) .023 -.205(**) -.089
Sig. (2-tailed)
.008 .739 .002 .187
N 223.000 220 218 220 221
Pants crotch length is
Pearson Correlation
1.000 -.217(**) .015 -.153(*)
Sig. (2-tailed)
.001 .826 .022
N 223.000 219 221 222
Pants hip is
Pearson Correlation
1.000 .033 .268(**)
Sig. (2-tailed)
.625 .000
N 220.000 219 219
Pants leg is
Pearson Correlation
1.000 .068
Sig. (2-tailed)
.316
N 223.000 221
Seat of pants
Pearson Correlation
1.000
Sig. (2-tailed)
N 223.000
49
Correlations. To determine if there are patterns in the reported issues, the correlations
between issues and size worn were examined. In group MC, none of the reported issues correlate
significantly with pants size worn. This finding indicates there is either an even rate of problems
over the course of the size range, there is no pattern to the issues, or there are intervening
variables not taken into account. Each man‟s preferred style or favorite brand of pants may have
a more significant effect on what issues they experience than what size they wear. Those
variables were not measured in this study.
Vertical issues, leg and crotch length were significantly correlated (r = .178, p<.01). Of
the horizontal issues, only hip circumference and seat issues were correlated (r =.268, p<.001).
Crotch length issues were correlated to hip (r =-.217, p<.01) and seat issues (r = .153, p<.05),
while leg length and circumference were also correlated (r = -.205, p<.01). Negative correlations
were unusual, as crotch length is graded proportionately with the hip circumference; however the
NT group (See next page) displayed only positive relationships.
In group NT, however, there were correlations between both waist and inseam size and
reported issues. Inseam correlated with both vertical issues: leg length issues (r = -.219, p<.05)
and crotch length issues (r = -.253, p<.05). These findings indicate that as men wear longer
inseams they find the vertical lengths of their pants too short and vice versa. Waist size is
significantly correlated with hip circumference issues (r = -.272, p<.01), so men with larger waist
sizes experience tightness in the hips, while men with smaller waist size report looseness in the
hips. Leg circumference and seat fit issues were similarly correlated with both waist and inseam
size as shown in Table 22. Both issues are circumferential but seem to relate to both
circumferential and vertical size worn.
Unlike in group MC, both horizontal and circumferential issues were significantly
correlated with other issues of the same type, as would be expected. Crotch length issues also
correlated with hip and seat circumference issues, which indicates that many men experience
tightness or looseness over the entire groin area.
50
Table 22 Pant issue correlations, Group NT NT
Waist Size
Pearson Correlation
-.025 -.021 -.272(**) -.265(**) -.262(*)
Sig. (2-tailed)
.806 .836 .007 .009 .010
N 96 96 96 96 95
Inseam
Pearson Correlation
-.219(*) -.253(*) -.157 -.247(*) -.283(**)
Sig. (2-tailed)
.032 .013 .127 .015 .005
N 96 96 96 96 95
Pants legs are
Pearson Correlation
1.000 .240(*) .169 .163 .196
Sig. (2-tailed)
.019 .100 .113 .057
N 96.000 96 96 96 95
Pants crotch length is
Pearson Correlation
1.000 .219(*) .176 .322(**)
Sig. (2-tailed)
.032 .086 .001
N 96.000 96 96 95
Pants hip is
Pearson Correlation
1.000 .362(**) .585(**)
Sig. (2-tailed)
.000 .000
N 96.000 96 95
Pants leg is
Pearson Correlation
1.000 .428(**)
Sig. (2-tailed)
.000
N 96.000 95
Seat of pants
Pearson Correlation
1.000
Sig. (2-tailed)
N 95.000
** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
Suits
Suits are worn by a smaller number of men than wear dress shirts or pants, as many
positions do not require the formality of a business suit. Some men wear suits only to religious
services or special occasions. Although most menswear retailers encourage their customers to
have their suits altered to fit according to traditional fit standards, there are some who do not
alter their suits, and others who are dissatisfied even though their suit fits.
51
Nearly a third of respondents reported that the shoulders of their suits were too narrow
(25%, Table 23). This problem may be due to the restrictive nature of the tailored cut of most
jackets. The traditional fit of a suit jacket restricts movement more than most coats, and is
therefore less comfortable. There were also a large number of subjects reporting that the
shoulders were too wide: a combined total of 40.2% of respondents had shoulder width issues.
Shoulder width of suits is therefore the most pervasive issue reported in the study. If the
shoulders of a garment fit incorrectly, problems cascade into other attached portions of the
garment. If the shoulders are too wide, the sleeves hang from a lower point on the arm, seeming
too long. The sleeve circumference may be loose, as it is not matched to the appropriate portion
of the arm. Extra fabric bunches in the underarm area. In the opposite case, narrow shoulders, the
underarms bind against the body, the sleeves seem short, and mobility is restricted further than
usual. Changes should be made to improve the shoulder comfort and fit of standard sized tailored
suits.
Table 23 Suit issues
MC NT Overall
Issue Percentage Reporting
Percentage Reporting
Percentage Reporting
Shoulders Too narrow 30.3 14.3 25.6
Pants Too large 15.6 45.7 24.5
Sleeve length Too long 15.6 37.0 21.9
Sleeve length Too short 22.5 7.6 18.1
Torso Too small 16.1 17.4 16.5
Jackets Too long 14.7 17.4 15.5
Shoulders Too wide 17.0 8.8 14.6
Torso Too large 11.0 22.8 14.5
Pants Too small 13.3 13.0 13.2
Jackets Too short 15.1 4.3 11.9
N=218 to 220 N=91 to 92
Sleeve length issues were reported by 38% of respondents. While sleeves can be fairly
difficult to shorten due to the wrist buttonholes and placket opening, lengthening sleeves is
equally difficult, and sometimes impossible if insufficient allowances are left in the seams.
Twenty-two percent reported that sleeves were too short, a number that could be reduced by
52
lengthening the standard sleeve length. There would be more men required to shorten their
sleeves, but shortening sleeves is always possible. To avoid the need for most sleeve alterations,
this study will look for patterns amongst height, chest size, sleeve length, and sleeve length
issues. There was no significant correlation between shirt sleeve length or chest size and suit
sleeve length issues (p=.972, p=.746).
Group MC correlations between sizes and suit issues are shown in Table 24. No
significant correlations were found between chest size and reported issues. Height category
(Short, Average, Tall) was found to have a small but significant correlation with jacket length
issues (r = .172, p<.05 ). This is a logical relationship, as jackets are sized by height category.
Because suit sizes are determined by a single measurement, chest circumference, and
general height classifications, reported issues with suits were also compared with reported neck,
sleeve, inseam and waist sizes in Table 24. The only significant correlations found in group MC
were between neck size and jacket length issues (r = -.222, p<.05 ), and between both length
issues and height category (Jacket length r =.172 , p<.05; Sleeve length r = .165, p<.05).
Negative correlation of jacket length issues and neck size may indicate a problem with the grade
rules for the smallest and largest sizes. Individuals wearing small neck sizes reported jackets
being too long, and those wearing large neck sizes reported jackets being too short. Patterns are
normally developed in a medium size, then graded up and down to smaller and larger sizes,
which may introduce a little too much dimension with each size increase or decrease. Of
particular interest was the lack of a significant correlation between issues where the pants of a
suit are the correct size and issues with waist (p=.053), chest (p=.258 ), or inseam size(p=.56 ) .
Pant waist and inseam size may be a moderating variable in the relationship between chest size
and pants being the right size.
Significant correlations were found between age, height and weight of group MC and
their reports of suit issues (Table 22). Both length issues, jacket length and sleeve length, were
also significantly correlated with height and weight. Shoulder width issues, a girth measurement,
was correlated to weight (r = .276, p<.001) and BMI (r = .28, p<.001).
The pant size issues were both correlated by age, however “Pants of suits are the right
size” was also correlated with weight and therefore BMI. Torso girth issues were not correlated
with any of the sizes or body measurements. These individuals may be wearing the wrong chest
size. All the significant correlations found for group MC had low Pearson correlation values.
53
Table 24 Group MC: Suit issue correlations
Pants of suits are right size
Jacket too short/long
Shoulders too
wide/narrow Torso too small/long
Pants too small/large
Sleeve too short/long
Chest Size
Pearson Correlation
.130 -.062 .098 .009 .138 .038
Sig. (2-tailed) .258 .597 .401 .941 .230 .746
N 77 75 75 75 77 77
Waist Size
Pearson Correlation
.134 -.083 .091 .041 .027 .083
Sig. (2-tailed) .053 .232 .194 .559 .695 .233
N 209 207 207 207 207 207
Inseam
Pearson Correlation
-.050 .087 .115 .096 -.109 .010
Sig. (2-tailed) .560 .310 .179 .263 .202 .907
N 139 137 137 137 138 138
Neck Size
Pearson Correlation
.029 -.222(*) -.071 -.057 -.023 -.104
Sig. (2-tailed) .775 .027 .483 .574 .819 .302
N 102 99 99 99 101 101
Sleeve Length
Pearson Correlation
.159 .008 .104 .107 .171 .005
Sig. (2-tailed) .226 .954 .438 .424 .196 .972
N 60 59 58 58 59 59
Age Pearson Correlation
0.172 .120 .149(*) -.012 .159* .110
Sig. (2-tailed) .010 .078 .028 .858 .019 .105
N 220 218 218 218 218 218
Height Pearson Correlation
.075 -.192(**) .015 -.071 -.084 -.248(**)
Sig. (2-tailed) .266 .004 .824 .300 .217 .000
N 220 218 218 218 218 218
Weight Pearson Correlation
.158(*) -.174(*) .276(**) -.119 -.128 -.137(*)
Sig. (2-tailed) .022 .012 .000 .086 .064 .047
N 211 209 209 209 209 209
BMI Pearson Correlation
.142(*) -.086 .280(**) -.087 -.105 -.043
Sig. (2-tailed) .039 .215 .000 .210 .132 .538
N 211 209 209 209 209 209
** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
Group NT There are many differences in the correlations found between the MC and NT
groups. The only 3 shared correlations were between “pants of suits are the right size” and
weight, “pants of suits are the right size” and BMI, and jacket length and height. Those issues
can be assumed to affect the entire population.
54
The NT group showed clearer relationships between size worn, physical characteristics
and issues reported. Circumferential measurements: chest size, waist size, and neck size all
correlate with “pants of suits are the right size” and torso width (Table 25). Two of those
measurements, chest size and waist size, correlated with improper pants size, although neck size
did not significantly correlate. Neck size has little physical relationship with pants size, and the
lack of relationship is not surprising. Height-based sizes: inseam, and sleeve length, are
correlated with sleeve length issues. Jacket length issues, also presumably height-based,
correlated with height, inseam, and sleeve length. Suit height category shows clear links to jacket
length issues; of those wearing short suits 55.6% reported that jackets are too long.
Shoulder width, the most pervasively reported issue in this study, was correlated with
chest size, sleeve length, height and weight. It did not correlate significantly with body mass
index, which is unusual as BMI is calculated from height and weight. Because it correlates
significantly with both length and circumference based measurements, it will be a more complex
issue to resolve.
One suit issue commonly reported in this study will be relatively easy to resolve. By
selling suit jackets and pants separately, no one will be dis-accommodated by the size of the
pants paired with their proper size jacket. Sleeve length issues will be more difficult to resolve,
but the first effort should be to fit men in the proper height category of suit, namely Regular, Tall
or Short. Second, retailers should encourage men to have sleeve length altered to fit properly, as
it is not a difficult or expensive alteration and would resolve most issues in that area. This
solution may still leave a portion of the population with sleeves that are too short. The most
prevalent and significant issue, shoulder width issues, can only be resolved when the true origin
of the issues can be determined.
55
Table 25 Group NT: Suit issue correlations
Pants of suits are right size
Jacket too short/long
Shoulders too wide/ narrow
Torso too small/long
Pants too small/large
Sleeve too
short/long
Chest Size
Pearson Correlation
.347(**) .015 -.234(*) -.250(*) -.244(*) -.069
Sig. (2-tailed) .001 .890 .029 .019 .022 .525
N 88 88 87 88 88 88
Waist Size
Pearson Correlation
.275(**) -.016 -.179 -.470(**) -.403(**) -.070
Sig. (2-tailed) .008 .878 .090 .000 .000 .510
N 92 92 91 92 92 92
Inseam Pearson Correlation
-.135 -.286(**) -.163 -.057 -.087 -.230(*)
Sig. (2-tailed) .200 .006 .123 .588 .408 .027
N 92 92 91 92 92 92
Neck Size
Pearson Correlation
.208(*) .028 -.196 -.218(*) -.129 -.117
Sig. (2-tailed) .047 .788 .063 .036 .222 .267
N 92 92 91 92 92 92
Sleeve Length
Pearson Correlation
.131 -.325(**) -.331(**) -.115 -.049 -.416(**)
Sig. (2-tailed) .214 .002 .001 .275 .643 .000
N 92 92 91 92 92 92
Age Pearson Correlation
-.041 -.168 -.093 -.110 -.188 -.155
Sig. (2-tailed) .705 .117 .389 .303 .078 .146
N 89 89 88 89 89 89
Height Pearson Correlation
.122 -.330(**) -.475(**) -.042 -.009 -.337(**)
Sig. (2-tailed) .247 .001 .000 .691 .930 .001
N 92 92 91 92 92 92
Weight Pearson Correlation
.262(*) -.080 -.292(**) -.381(**) -.281(**) -.156
Sig. (2-tailed) .012 .449 .005 .000 .007 .139
N 92 92 91 92 92 92
BMI Pearson Correlation
.228(*) .076 -.086 -.409(**) -.315(**) .001
Sig. (2-tailed) .028 .469 .415 .000 .002 .990
N 92 92 91 92 92 92
** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
56
Clothing Interest
Clothing interest was compiled into an overall score and three sub-scores for the factors
of Fashion Forward, Self Analytical, and Correctness. Overall scores were the calculated sum of
all questions in the interest section, including two that are not part of the sub-factors. Overall
scores fell between 28 and 94 with a mean of 59, out of a possible range from 21 to 105. Lower
scores indicate higher clothing interest.
Respondents were asked “Which best describes your interest in clothing: Indifferent,
Mild, Average, Strong, or Very Strong.” In this text, this question will be referred to as “reported
interest”, while the overall sum of responses on the interest section will be called “interest
score”. Reported interest was reverse coded to match the interest section. The correlation
between reported interest and the interest score was .509 (p<.001). While the respondents were
somewhat accurate in stating their clothing interest level based on a single question, the interest
scale provides more information. If the correlation was close to perfect, there would be no reason
to continue using the multipart scale, however in this case the larger scale does give more
insight.
Reported interest had a between groups difference in means of 1.22 on a five point scale,
showing that the NT group (M = 4.02) reported significantly higher interest levels than group
MC (M = 2.80) (t= -11.3, p<.001). The overall interest score, however, was only slightly
different per group, with a mean difference of 4.88 on an 85 point scale (MC M = 60.64, NT M =
55.76, t=3.7, p<.001). This implies that although the MC group did not initially describe
themselves as interested, they were in fact interested in their clothing. This result may stem from
the popular stereotype that men should not be overly concerned with their appearances. In the
general population, there are few men who would describe themselves as fashion connoisseurs.
The NT group reported a large percentage in executive positions, as would be expected from the
clients of an upscale menswear store. It follows that the societal pressure not to care about
clothing has less impact on those in executive positions where dress and decorum are paramount.
Interest score was also found to correlate most highly with the Fashion Forward subscale (r =
.826), while the other subscales correlated at .7 levels. This further indicates that men associate
“interest” in clothing with fashionability, rather than considering utilitarian interests. For these
reasons, the single question format is much less desirable for future studies.
57
Although a slight significant correlation was found between age and reported interest,
there was no correlation between age and interest score. The between groups difference in age
and reported interest is most likely the source of this correlation.
Weight (r = .205, p<.001), and BMI (r = .189, p<.001) correlated positively with the
Fashion Forward subscale but not the overall score or other sub-factors, indicating that heavier
men reported being less fashion forward. This may stem from self-consciousness, or from
inability to find properly fitted clothing in fashionable styles. Weight was not correlated
significantly with reported interest, however height (r = .13, p<.05) and BMI (r = -.12, p<.05)
were somewhat correlated with reported interest. They were not significantly correlated with
overall score or the sub-factors.
Work Experience
Respondents were asked whether they had any work experience in the clothing industry.
Those with work experience had a mean interest score of 53.5, while those without reported a
mean of 60.9, a difference equaling 8.7 % (Table 26). The largest mean difference between
groups was found in the Fashion Forward sub-factor. While this indicates that those with work
experience in the clothing industry have a higher interest in clothing and pay more attention to
fashionability, it is also probable that those with higher clothing interest are more likely to look
for jobs in the clothing industry. Cause and effect cannot be distinguished from the questions
asked this study.
Table 26 Mean interest scores
Without Experience With Experience Mean Difference
Interest Score 85 60.9 71.6% 53.5 62.9% 7.4 8.7%
Fashion Forward 30 23.4 78.0% 20.4 68.0% 3 10%
Self-Analytical 25 15.7 62.8% 14.5 58.0% 1.2 4.8%
Correctness 25 15.5 62.0% 14.2 56.8% 1.3 5.2%
58
Clothing Interest and Reported Fit Issues
To answer research questions three and four, the complete sample‟s respondents were
further separated into high and low interest sub-groups. Overall, the respondents were divided
into three groups based on their interest scores. These groups will be called Interest Groups. The
first group reported low clothing interest and had scores higher than or equal to 62.5. Medium, or
average clothing interest fell between 62.49 and 54.1. The high interest group reported scores
lower than or equal to 54. This resulted in 34% of valid responses in the high interest group, 29%
in the average group, and 36% in the low interest group. The following analysis was performed
on only the high and low groups in order to highlight the contrasts between high and low interest
individuals.
Twenty-nine percent of the MC group fell into the high interest group, while 42% of NT
group fell into the same category. The low interest group consisted of 43% of the MC group and
18.5% of the NT group. With such disparity, there may be a shift in results based on the
previously reported data source group differences.
Between Data Groups Comparison of Interest Groups
In order to determine if the between groups differences had an effect on the interest group
results, analysis will be run on the upper and lower thirds of each group separately. If the high
and low interest groups are determined within MC and NT individually, the scores separating the
groups are 57 and 65 for MC as well as 52.67 and 60 for NT.
Racial differences in clothing interest were found in Gravely‟s (1999) comparison of
suits. In the MC group, where respondents belonged to a variety of racial groups, the Hispanic
and African-American men fell more frequently in the high interest group, whereas the
Caucasian men fell slightly more often into the low interest group. This finding seems consistent
with Gravely‟s results, although Hispanic men were not a part of her sample. NT contained
insufficient non-Caucasian members to run this comparison.
It is of interest to note that no correlation was found between high/low interest group
membership and any other demographic variables. There was no significant correlation between
interest group membership and BMI, indicating that body proportion has little effect on clothing
interest.
59
Table 27 Interest group by race within group MC
Race
African-
American Caucasian Hispanic Asian Other Total
Interest score MC High 3 (75%) 44 (43%) 22 (81.5%) 0 3 (100%) 72 (52%)
Low 1 (25%) 58 (57%) 5 (18.5%) 2 (100%) 0 66 (48%)
Total 4 102 27 2 3 138
Table 28 Interest groups correlations with length issues
Interest groups MC Interest groups NT
Length issues Pearson Correlation -.188(*) -.004
Sig. (2-tailed) .035 .975
N 126 64
** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
Significant correlations were found between high and low interest groups within group
MC and several other variables (Table 28), indicating that the members of the high interest group
wore larger neck and chest sizes than their low interest counterparts. Pants sizes and other
aspects of shirt sizing were not significantly correlated. The MC high interest group was more
likely to have their shirts and pants altered. No significant correlation was found to having suits
altered, however due to the high prevalence of suit alterations, this finding was somewhat
expected. High interest men owned more suits and shirts than low interest men, not surprising as
those who are fashion forward reported shopping and trying on clothing more often. MC men in
the upper interest group were also more likely to have worked in the clothing industry. This
could be due to self selection for positions in clothing retail, or may have as much to do with
knowledge and awareness gained while working in the clothing industry. The only demographic
variable correlated with interest groups within group MC was education (r =.183, p<.05). Interest
groups within group NT were not significantly correlated with educational level (p = .720). As
there was both higher average and more consistent educational level and clothing interest in
group NT, there may still be a significant influence of education on clothing interest over the
population.
60
Table 29 Significant correlations between interest group and other variables Interest score MC Interest score NT
Neck Size Pearson Correlation .396(**) .182
Sig. (2-tailed) .001 .149
N 73 64
Has Shirts Altered Pearson Correlation -.199(*) .170
Sig. (2-tailed) .023 .180
N 130 64
Has Pants Altered Pearson Correlation -.187(*) -.013
Sig. (2-tailed) .029 .919
N 137 64
Chest Size Pearson Correlation .270(*) .212
Sig. (2-tailed) .044 .098
N 56 62
# of Suits Owned Pearson Correlation -.201(*) -.069
Sig. (2-tailed) .016 .589
N 143 63
# of Dress Shirts Owned Pearson Correlation -.182(*) -.121
Sig. (2-tailed) .029 .352
N 143 61
Overall Interest Pearson Correlation -.479(**) -.470(**)
Sig. (2-tailed) .000 .000
N 144 64
Work in Industry Pearson Correlation -.387(**) -.080
Sig. (2-tailed) .000 .532
N 143 64
a. Cannot be computed because at least one of the variables is constant.
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
Confirming the validity of the interest groupings, the high interest men from both MC
and NT reported higher overall interest in clothing on the single question scale. The NT men,
however, did not display significant correlations with any other issue variable (see Table A4,
Appendix D). This finding may have resulted from the higher level of service provided by their
retail source, including an insistence upon proper alterations whenever they are needed. It is
likely that both the high and low interest groups would usually have their garments altered as
needed, if the store employees encouraged them to do so. It may also result from their
occupations: many of the NT group members occupy positions requiring them to wear formal
business attire more frequently, leading to more clothing purchases. Because the NT group,
61
which seems to wear more accurate sizes and has their clothing altered more frequently shows no
significant relationship between interest level and size, there is probably no inherent link
between the two variables. The relationships between neck and chest size and interest group
found in group MC described on the previous page may be an indirect result of sizing issues,
rather than a link between interest and body size.
Hypotheses
To test hypothesis 1, “Men with low clothing interest will report significantly fewer fit
problems than those with high clothing interest,” the high and low interest groups for each source
group were compared in total number of reported issues, and number of height and
circumference issues. There was no significant correlation between interest group and issues for
group NT, however there is a significant correlation (r = -.188, p<.05) between length problems
and interest group within group MC. This indicates that those in the MC high interest group
reported fewer clothing problems than those in the MC low interest group.
Table 30 Correlations between interest scores and reported issues
Interest score NT Interest score MC
Issues Pearson Correlation -.020 -.162
Sig. (2-tailed) .876 .076
N 62 120
Width Issues Pearson Correlation -.037 -.113
Sig. (2-tailed) .774 .199
N 62 131
Length Issues Pearson Correlation -.004 -.188(*)
Sig. (2-tailed) .975 .035
N 64 126
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
62
Overall interest groups
In order to estimate the population it is necessary to compare all respondent‟s clothing
issues. Interest scores were compared with clothing issues, and the resulting correlations are
shown in Table 31.
Table 31 Correlation of clothing interest with clothing issues
Interest Score
Overall Issues Pearson Correlation -.140(*)
Sig. (2-tailed) .024
N 259
Width Issues Pearson Correlation -.133(*)
Sig. (2-tailed) .028
N 273
Length Issues Pearson Correlation -.057
Sig. (2-tailed) .353
N 267
** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
Table 32 Clothing interest sub-factors correlations with clothing issues
Fashion Forward Self Analytical Correctness
Overall Issues Pearson
Correlation
-.050 -.186(**) -.227(**)
Sig. (2-tailed) .411 .002 .000
N 270 269 270
Width Issues Pearson
Correlation
-.044 -.147(*) -.215(**)
Sig. (2-tailed) .462 .013 .000
N 284 283 284
Length Issues Pearson
Correlation
-.039 -.158(**) -.096
Sig. (2-tailed) .512 .009 .109
N 278 277 278 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
63
Significant correlations were found between overall interest score, overall reported issues
and width issues. The correlations were negative, indicating that high clothing interest
individuals (low scores) reported slightly more clothing issues than their low interest
counterparts (high scores). Length issues were not significantly correlated with clothing interest
score. Because interest score is significantly correlated with the total number of issues reported,
hypothesis 1 is supported.
Table 33 Clothing interest sub-factors internal correlations
Overall
Issues
Width
issues
Length
issues
Fashion
Forward
Self-
Analytical Correctness
Overall Issues Pearson Correlation 1.000 .923(**) .852(**) -.050 -.186(**) -.227(**)
Sig. (2-tailed) .000 .000 .411 .002 .000
N 282.000 282 282 270 269 270
Width issues Pearson Correlation .923(**) 1.000 .609(**) -.044 -.147(*) -.215(**)
Sig. (2-tailed) .000 .000 .462 .013 .000
N 282 296.000 283 284 283 284
Length issues Pearson Correlation .852(**) .609(**) 1.000 -.039 -.158(**) -.096
Sig. (2-tailed) .000 .000 .512 .009 .109
N 282 283 290.000 278 277 278
Fashion Forward Pearson Correlation -.050 -.044 -.039 1.000 .490(**) .380(**)
Sig. (2-tailed) .411 .462 .512 .000 .000
N 270 284 278 311.000 302 305
Self-Analytical Pearson Correlation -.186(**) -.147(*) -.158(**) .490(**) 1.000 .472(**)
Sig. (2-tailed) .002 .013 .009 .000 .000
N 269 283 277 302 307.000 302
Correctness Pearson Correlation -.227(**) -.215(**) -.096 .380(**) .472(**) 1.000
Sig. (2-tailed) .000 .000 .109 .000 .000
N 270 284 278 305 302 310.000
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
Correlations between the Fashion Forward sub-factor and clothing issues were
insignificant (Table 33), not supporting hypothesis 2a.
64
The Self-Analytical sub-factor is negatively correlated with both types of clothing issues
and therefore overall issues. This means that those reporting high clothing self-analytical interest
(low interest scores) reported higher numbers of clothing issues, supporting hypothesis 2b.
The third sub-factor, Correctness correlated negatively to overall issues and width
issues, however it did not significantly correlate with length issues. Hypothesis 2c is tentatively
supported, but the relationship should be explored further.
Clearly the Fashion Forward variable has something in common with the other two
interest sub-factors, as they are significantly correlated with Fashion Forward (r = .490, p<.001)
and (r = .380, p<.001) respectively. The lack of correlation between Fashion Forward interest
and reported issues may relate to the difference in concept between the sub-factors. Fashion
forward refers to those who innovate with their clothes. They are driven to try new clothing and
pay attention to trends. No item in the fashion forward sub-factor refers to forming a judgment
about their own clothing, beyond a superficial evaluation of how a style looks on them.
Both high self-analytical and correctness scores indicate that the respondent objectively
considers their clothes. Those scoring high on self-analytical interest constantly observe
themselves in an effort to improve themselves. The scale includes items about using clothing to
modify their appearance and giving attention to comfort. Self-analytical men notice good fit
through comfort and overall appearance.
Those scoring high on correctness are careful to conform to the standards of their culture,
including accepted standards of garment fit. They are careful to select comfortable clothes and
maintain their appearance to a high standard. Therefore both the relationships and lack of
relationships found in this study are logically explained.
65
CHAPTER 5
CONCLUSIONS, IMPLICATIONS AND SUMMARY
This study has investigated men‟s business clothing issues and men‟s clothing interest as
self-reported by two groups of consumers. It fulfilled several steps of the DeJonge design
process, beginning with the creation of an objective statement. Exploration of the design
situation occurred through a literature search, market sizing comparison, informal discussions
with male consumers, and informal observation of men in business clothing. In the next phase of
the process, problem structure perceived, this study created and administered both an instrument
to document the occurrence of specific fit issues and a gender-neutral instrument to measure
clothing interest. These instruments were able to record significant patterns in fit issues and
clothing interest that should provide insight into the design challenges for improving men‟s
business clothing. To complete the User Input section of the process, a focus group will be used
to gather any insights that could not be gathered by the current instrument. Market Analysis as
described in Figure 4 will complete the problem structure perceived section of the DeJonge
process.
Resolving Fit Issues
Critical issues found in this research should be addressed by designers in the future. Over
27% of respondents said that their shirt necklines were too tight, a number that could reflect the
purchase of the wrong size, the purchase of a garment based on a different measurement, such as
waist circumference, or a sensation of tightness caused by the garment touching all sides of their
neck. For a designer to improve the fit of necklines in the shirts they design, they must
distinguish between the previously mentioned situations.
If men are purchasing incorrect sizes, education and customer service will be essential to
improving customer satisfaction. Employees at the point of sale can assist men with the selection
of the proper size by taking their measurements, visually assessing the customer‟s body shape,
then directing them towards the proper size. Subclasses of sizes, such as big and tall, trim, or
athletic cut may be the most appropriate for certain body types, and sales staff should be well
educated in the exact dimensional difference between subclasses. Although measurements are
helpful in identifying the proper size, there are aspects of body shape that cannot be quantified
by circumference and length. Posture can significantly affect the drape of clothing on the body,
66
sometimes also affecting the size required to properly fit the body. Also, asymmetry cannot be
accounted for in simple circumferential measurements. It requires either a trained human
observer or more extensive measurements to adjust for these variations of body shape. While
body scanners can now match sizes very closely accounting for these variations, they are
currently financially impractical for most stores to install, and some users have concerns about
being scanned. Retail employee training and customer education are currently the most feasible
ways to prevent men from purchasing the wrong size garments.
If men are buying garments based on a body measurement other than those used to
differentiate between sizes, they would experience and report issues with the differentiation areas
of the garments, such as neck size, or chest circumference. Many of those were reported in this
study. One third of respondents reported problems with sleeve length, neck size, or pants leg
length. Each is a measurement by which clothing is chosen, and should not cause dissatisfaction.
The only explanation for a consumer tolerating problems with the normal selection areas is that
another part of their body is preventing them from selecting sizes by the normal means. For an
example, if a man‟s neck, shoulders, height and arms were congruent with the standards for a 15
inch neck, 32 inch sleeve shirt, but their waistline was too large for the 15/32 to button, they
would have to purchase larger neck size shirts in order to accommodate the waist circumference.
While they might be better suited to a Big and Tall 15/32, that shirt would be too long in torso,
and may be too broad in the shoulders and wide in the sleeve to meet their aesthetic preferences.
Suits are a specialized set of clothing that men sometimes only purchase if they hold a
position requiring them to wear a suit. When shopping for suits, almost all retailers provide
individual service including alterations and advice on fit and styling. Because of this service, one
could expect an overall improvement in fit over that of shirts and pants bought off a rack, but
there were some highly prevalent issues. Most critical is the width of jacket shoulders, which
was reported as too narrow by over 25% of respondents. It is possible that more ease should be
introduced to the sleeve cap of jackets for customers with larger than normal deltoid muscles, or
that extra width across the back may be needed to accommodate wide shoulders or a customer
who desires a less restrictive garment. The aforementioned changes would result in a less form-
fitting appearance across the torso and/or a slightly thicker sleeve. Future studies should
determine whether those aesthetic changes would be deemed acceptable by men. A skilled
custom tailor would be able to introduce extra width into their patterns without much outward
67
change to the garment, however altering a ready-to-wear suit may not lead to as satisfactory
results.
Future Studies
From this study several interesting questions arose that could not be answered with the
current instrument. First, are men wearing the correct size garments, or could a large portion of
clothing issues be resolved by a change in size? For example, a large number of problems were
reported in the MC group in both neck size and sleeve length, the main sizing measurements for
dress shirts. If men are wearing the proper size, they should not have problems with those
dimensions. This leads to the second question: are men wearing the wrong size because of
ignorance, or because their size is unavailable? While some men may randomly purchase shirts
with only a vague idea of their proper size, many others have been properly measured and know
the size they should be purchasing. The members of the NT group shop in a store that provides
one-on-one assistance in size selection. If they are forced to purchase shirts to fit another
dimension of their body that is disproportionate to their neck and sleeve length, perhaps revised
sizes or size variations like athletic cut or big and tall would be more successful in
accommodating their build. Third, does a man‟s preferred style or brand of clothing have more
influence on clothing issues than size worn or overall interest? If a brand‟s sizing specifications
are not appropriate for a specific customer‟s body type, the styling of the clothes may be
desirable enough that the customer continues to purchase poorly fitting garments.
Education will be vital to the resolution of men‟s clothing issues. A large portion of the
respondents were unfamiliar with basic terminology, such as “inseam”, and many did not know
their own size. Menswear retailers should attempt to measure each customer or provide another
method of determining proper size. Future sales can go more quickly and smoothly if the
customer is given an easy way to remember their size, such as an in-store database or a wallet
card.
Differences by race were uncovered in this study; however the implications of these
differences could be further explored. There was not a significant relationship between race and
reported clothing issues, but ethnic background has a significant and anthropologically
documented effect on a man‟s skeletal size, body shape, and muscle mass, such as typically
shorter height amongst Hispanics (McDowell et al., 2005). Specific brands may choose to tailor
their product sizing to a certain body type based on their target customer group‟s ethnic
68
background. The clothing interest differences found in this study between Caucasian and
Hispanic consumers also point to varied marketing strategies and a more or less fashion-forward
approach when marketing to specific ethnic groups. Past research also found that African-
American consumers vary from Caucasian consumers in clothing interest (Gravely 1999),
although this study had insufficient African-American respondents to confirm the previous
study‟s results. A future study including a larger number of Hispanic, African-American, and
Asian consumers would serve to further explore these differences.
Knowing the fit threshold for key body areas will assist designers in determining the
proper spacing between sizes. For example, if the smallest difference in wrist circumference men
can detect (their fit threshold) is .25 inches, the ideal range for the cuff circumference of the
garment can be calculated by the following formula: wrist circumference + desired ease < cuff
circumference < wrist circumference + desired ease + .25in.
Fit criteria may be more difficult to study, as they are individual to each man. They are a
result of the culture surrounding the consumer, their standards for comfort, and individual
aesthetic tastes. Some men may not want their business clothing to fit according to traditional
tailor‟s standards. This attitude may stem from comfort issues, such as hypersensitivity to collars
touching their neck. Non-traditional aesthetic preferences vary from extra slim fit to loose and
baggy. In addition to establishing fit threshold, an understanding of how fit criteria vary, whether
by culture, by geographic location, by income level, or other determining factors, will also be
needed before a designer can fully grasp the design situation. Knowing both will allow
companies to accurately fit their target consumer.
Conclusions
If this study has shown nothing else, it has documented that there are issues with existing
men‟s business clothing. While women‟s clothing is often studied, men‟s clothing deserves more
attention in scientific research. The high prevalence of dissatisfaction with business clothing
indicates shortcomings in the ready-to-wear offerings available to male consumers. The
population may prove difficult to study by conventional survey techniques, as many of the
respondents were unfamiliar with the necessary terminology to answer questions about clothing,
and did not know their proper size. Some men, perhaps those with extremely low clothing
interest, would not volunteer for studies of clothing, and it may not be possible to get a true
cross-section of the population. It may be more successful in future studies to use in-person
69
qualitative methods to gather information about men‟s clothing interest, especially those insights
that men may not have the vocabulary to understand when questions are posed using standard
terminology.
Because this study showed no link between clothing interest level and reporting rate of
clothing issues, future studies of fit and sizing issues do not need to take into account the effect
of interest on the accuracy of their results. The variables not measured in this study, fit threshold
and fit criteria, will be important to quantify for this population in future studies.
71
Thank you very much for taking this survey. We believe that it will take 10-12 minutes to answer these questions. Our goal is to find out your opinion. There are no right or wrong answers. All responses will remain confidential. This survey is to be completed by a male between the ages of 18 and 55.
In this survey “Business Clothing” refers to all clothing (suits, shirts, pants, and accessories) that is or could be worn in a corporate workplace. 1. How many suits do you own? ________
2. How many dress shirts do you own? ________
3. On average, how many days a week do you wear business clothing?________
4. Annually, how much do you spend on business clothing for yourself? ___________
5. What % of your business clothing do you buy yourself? _______%
6. Where do you buy the most business clothing (e.g. Macy‟s or Men‟s Wearhouse)? _________________________
5. What do you normally wear to work?
____Formal business attire ____Business casual attire ____Casual attire
6. What is your age? ___________ 7. Your height? _______ 8. Your weight? _______
9. Which best describes your interest in clothing?
____Indifferent ____Mild ____Average ____Strong ____Very Strong
10. Do you have work experience in the clothing industry? Y N
72
Listed below are specific garment types and common problems with each type. Please indicate the size you most commonly wear, and what fit problems you have with clothing of that size.
Dress Shirt 10. Neck size: __________ 11. Sleeve size: ___________
12. Overall, how satisfied are you with your current dress shirts?
Satisfied ____ ____ ____ ____ ____ Dissatisfied
13. Do you have your Dress Shirts altered? Y N
Please circle the situation that occurs most commonly in shirts:
16. The neckline is too small appropriate too large
17. The collar is too small appropriate too large
18. The pocket placement is too high appropriate too low
19. The front button placement is too close together appropriate too far apart
20. The shirt tail length is too short appropriate too long
21. The sleeve length is too short appropriate too long
22. The cuff is too tight appropriate too loose
23. The waist is too tight appropriate too loose
14 I can find dress shirts that fit reasonably well
Strongly Agree
Agree Neutral Disagree Strongly Disagree
Button Placement
73
Dress Pants/Slacks
24. Waist size:__________ 25. Inseam:__________
26. Overall, how satisfied are you with your current dress pants?
Satisfied ____ ____ ____ ____ ____ Dissatisfied
27. Do you have your Dress Pants/Slacks altered? Y N
28. I can find dress pants that fit reasonably well Strongly Agree
Agree Neutral Disagree Strongly Disagree
Please circle the situation that occurs most commonly in pants:
29. Is the leg length too short appropriate too long
30. Is the crotch length too short appropriate too long
31. Is the hip too loose appropriate too tight
32. Is the leg too loose appropriate too tight
33. Is the seat of your pants too loose appropriate too tight
74
Suits 34. Chest size:__________
35. Regular / Short / Tall (circle one)
36. Overall, how satisfied are you with your current suits?
Satisfied ____ ____ ____ ____ ____ Dissatisfied
37. Do you have your suits or jackets altered? Y N
38 I can always find jackets that fit reasonably well Strongly Agree
Agree Neutral Disagree Strongly Disagree
39 I can always find jackets in my size Strongly Agree
Agree Neutral Disagree Strongly Disagree
40 I can always find suits that fit reasonably well Strongly Agree
Agree Neutral Disagree Strongly Disagree
41 When I find a suit jacket that fits, the pants are also the correct size
Strongly Agree
Agree Neutral Disagree Strongly Disagree
Please circle the situation that occurs most commonly in suits:
42. Is the jacket too short appropriate too long
43. Are the shoulders too wide appropriate too narrow
44. Is the torso area too small appropriate too large
45. Are the pants too small appropriate too large
46. Is the sleeve length too short appropriate too long
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Please indicate how much you agree or disagree with the following statements:
Strongly Agree
Agree Neutral Disagree Strongly Disagree
47. I try to buy clothes which are very unusual 1 2 3 4 5
48. When new fashions appear on the market, I am one of the first to own them
1 2 3 4 5
49. I try on clothes in shops just to see how I will look in them without really planning to buy
1 2 3 4 5
50. I have something to wear for any occasion that occurs 1 2 3 4 5
51. I get rid of garments I like because they are not comfortable 1 2 3 4 5
52. The way my clothes feel to my body is important to me 1 2 3 4 5
53. I try on some of the newest clothes each season to see how I look in the styles
1 2 3 4 5
54. I am irritable if my clothes are uncomfortable 1 2 3 4 5
55. My appearance in business clothing is important to me 1 2 3 4 5
56. I wonder what makes some of my clothes more comfortable than others
1 2 3 4 5
57. I use clothing as a means of disguising physical problems and imperfections through skillful use of color, line and texture
1 2 3 4 5
58. I read magazines and newspapers to find out what is new in clothing
1 2 3 4 5
59. It bothers me when my outfit is not color coordinated 1 2 3 4 5
60. I like dark or muted colors rather than bright ones for my business clothes
1 2 3 4 5
61. I get bored with wearing the same kind of clothes all the time 1 2 3 4 5
62. I am concerned about the care of my clothing 1 2 3 4 5
63. Certain clothes make me feel more sure of myself 1 2 3 4 5
64. I enjoy wearing very different clothing even though I attract attention
1 2 3 4 5
65. I can find up-to-date fashions in my size 1 2 3 4 5
66. Wearing fashionable business clothing helps me achieve my career goals
1 2 3 4 5
67. It bothers me when my shirt tail keeps coming out 1 2 3 4 5
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Demographics
68. Where do you reside? __________________________________________ 69. What was your household pre-tax income last year? (optional)
____ Under 20,000 ____ 50,000-79,999 ____ 110,000-149,999 ____ 200,000 or more ____ 20,000-49,999 ____80,000-109,999 ____ 150,000-199,999
70. What is the highest level of education that you have completed?
____Some high school ____Bachelor‟s degree ____High school diploma ____Some graduate school ____Some college ____Graduate or professional degree Other (please specify):________________________
71. What is your occupation? ______________________________________ 72. What is your marital status?
_____ Single, not dating _____ Divorced _____ Single, dating _____ Widower _____ Married _____ Other: ____________________________
73. What is your race or ethnic group? 74. What is your overall fitness level?
____African-American ____Hispanic ____Very athletic ____Somewhat sedentary ____Caucasian ____Asian ____Somewhat athletic ____Sedentary Other: ___________________________
____Average
Thank you for completing this survey,
Your time and effort are greatly appreciated!
77
INTERNET SURVEY The online instrument contained exactly the same questions and possible answers in a format
similar to the following screenshot. Hosted Survey.com‟s survey creation tool was used to
program the survey. Questions were split onto different pages at headings from the paper format.
Results were automatically tabulated into an Excel spreadsheet that was then transferred into
SPSS for analysis.
81
INFORMED CONSENT FORM
This research is being conducted by Diana Sindicich, a graduate student under the direction of Dr. Catherine Black in the Department of Textiles and Consumer Sciences at Florida State University. The purpose of this research study is to collect information about men‟s business clothing and men‟s attitudes towards it. Your participation will involve completion of a questionnaire. The time commitment will be about 25 minutes. Your name will not be recorded and your identity will not be revealed when the findings are published. Your participation is voluntary. You may choose not to participate or to withdraw from the study at any time without prejudice. All of your answers to questions will be kept confidential to the extent allowed by law. Although there may be no direct benefit to you, your participation will provide the researcher with valuable insight into your attitudes towards clothing, as well as information about existing business clothing. This knowledge can assist her and others in developing improved clothing designs. You may contact Diana Sindicich at (850)644-2498 or at [email protected] with any questions regarding this research or your rights. If you have any questions about your rights as a subject/participant in this research, or if you feel you have been placed at risk, you can contact the Chair of the Human Subjects Committee, Institutional Review Board, through the Office of the Vice President for Research at (850)644-8633. For paper surveys: By completing this survey I certify that I have read and understand the above information. I freely and voluntarily give my consent to participate in the research project entitled “Interest and Problems in Men‟s Business Clothing”. I understand my responses will be kept confidential in a secure facility and that they will be destroyed by December 31, 2016 For online participants: By entering my email address and clicking “Submit” I certify that I have read and understand the above information. I freely and voluntarily give my consent to participate in the research project entitled “Interest and Problems in Men‟s Business Clothing”. I understand my responses will be kept confidential in a secure facility and that they will be destroyed by December 31, 2016. Email address:
Submit
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Error Checking of Responses
A large percentage of the unusable questionnaires were completed by men between the ages of
18 and 20. From the remaining questionnaires a set of rules was used to exclude unreasonable
answers to free response questions. Over the course of the data entry it became apparent that a
large portion of respondents were unclear about their sizes. Some reported “Don‟t Know”, while
others reported unreasonable responses.
1. Illegible or unclear responses were omitted from the dataset.
2. If two answers were given for a multiple choice question, the answers were omitted. In
the item “What do you normally wear to work,” where multiple answers were reasonable,
the more formal response was entered into the dataset.
3. If sleeve length was reported as a range of sizes, the lowest size was entered. If the
number of days per week business clothing was worn was reported as a range, the median
of the range was recorded.
4. Questionnaires with more than 50% of the questions left unanswered.
5. A small number of questionnaires included obviously sarcastic answers, such as “Your
Mom” listed as an occupation. Those questionnaires were discarded because there was no
way to guarantee the rest of the items were answered honestly.
6. Chest sizes identical to reported waist size were omitted.
7. When respondents gave multiple responses to “Where do you buy the most business
clothing?” the first response was entered.
8. Chest sizes under 30 were omitted, as the respondent may have given their neck size
instead of chest.
9. Sleeve lengths reported under 24 were omitted. Reported sleeve sizes over 38 were
checked against height and sleeve length responses. If a response was incongruent with
the height of the respondent relative to the bulk of the respondents with the same height,
it was omitted from the dataset.
10. Inseams reported under 20 were omitted when the respondent was under 5‟5” in height.
Inseams reported under 26 were omitted when the respondent was over 5‟5.”
11. Neck sizes reported under size 13 were omitted if the respondent reported a height of
5‟5” or taller. Neck sizes under 15 were omitted if respondents reported a height of 6‟ or
84
more. Neck sizes over 25 were omitted if the respondent reported their weight under
250lbs, and under 6ft tall.
The maximum and minimum values for all input items were checked to ensure that data entry
was accurate. All entry errors were corrected by re-entering the responses for the specific
questionnaire found to be in error.
86
Table A1
Shirt overall correlations
Overall
Sle
eve
Len
gth
Can
fin
d
shir
ts t
hat
fit
Nec
k s
ize
Issu
es
Co
llar
siz
e
Issu
es
Po
cket
h
eig
ht
Issu
es
Bu
tto
n
spac
ing
Is
sues
Sh
irt
tail
len
gth
is
sues
Sle
eve
len
gth
is
sues
Cu
ff
circ
um
fere
nce
iss
ues
Wai
st
circ
um
fere
nce
Iss
ues
Neck Size
Pearson Corre-lation
.426(**) .104 .003 -.029 .080 .204(**) -.145(*) .011 -.148(*) -.189(**)
Sig. (2-tailed)
.000 .141 .968 .679 .262 .004 .040 .883 .036 .008
N 156 200 203 201 201 200 203 200 201 199
Sleeve Length
Pearson Corre-lation
1 .008 .115 .047 .084 .171(*) -.106 -.183(*) .109 .083
Sig. (2-tailed)
.921 .151 .563 .301 .034 .185 .023 .175 .307
N 158 154 156 155 155 155 157 154 155 152
Table A2
Pant overall correlations
Can find pants that fit
Legs too short/long
Crotch length too short/long
Hips too tight/loose
Leg too tight/loose
Seat too tight loose
Overall Waist Size
Pearson Correlation
.002 -.009 -.023 .010 -.137(*) -.013
Sig. (2-tailed)
.974 .880 .691 .860 .016 .817
N 210 308 308 305 308 307
Inseam
Pearson Correlation
-.026 -.286(**) -.156(*) -.050 -.030 -.049
Sig. (2-tailed)
.761 .000 .016 .445 .646 .456
N 142 238 238 236 239 237
(a) – Responses not recorded for this question and group
87
Table A3
Overall correlations between reported suit issues and size worn
Pants of suits are right size
Jacket too short/long
Shoulders too wide/narrow
Torso too small/long
Pants too small/large
Sleeve too short/long
Chest Size Pearson Correlation
.224(**) -.108 .086 -.257(**) -.110 .013
Sig. (2-tailed)
.004 .170 .276 .001 .159 .868
N 165 163 162 163 165 165
Waist Size Pearson Correlation
.190(**) -.081 .168(**) -.195(**) -.175(**) -.006
Sig. (2-tailed)
.001 .164 .004 .001 .002 .914
N 301 299 298 299 299 299
Inseam Pearson Correlation
-.084 -.231(**) .015 -.065 -.083 -.231(**)
Sig. (2-tailed)
.203 .000 .821 .327 .207 .000
N 231 229 228 229 230 230
Neck Size Pearson Correlation
.107 .032 .051 -.031 -.007 -.024
Sig. (2-tailed)
.136 .659 .488 .674 .918 .740
N 194 191 190 191 193 193
Sleeve Length Pearson Correlation
.145 -.009 -.111 .045 .098 -.111
Sig. (2-tailed)
.075 .911 .178 .587 .232 .173
N 152 151 149 150 151 151
** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
Table A4
Interest group individual correlations
InterestscoreMC InterestscoreNT
Age Pearson Correlation .137 .183
Sig. (2-tailed) .102 .155
N 144 62
Height Pearson Correlation .029 -.020
Sig. (2-tailed) .730 .876
N 144 64
Weight Pearson Correlation .031 .162
Sig. (2-tailed) .712 .202
N 140 64
88
Table A4, continued
InterestscoreMC InterestscoreNT
Overall Satisfaction with shirts Pearson Correlation .004 .066
Sig. (2-tailed) .967 .603
N 137 64
Has Shirts Altered Pearson Correlation -.199(*) .170
Sig. (2-tailed) .023 .180
N 130 64
Can find shirts that fit Pearson Correlation .119 .074
Sig. (2-tailed) .178 .562
N 129 64
Shirt Neck is Pearson Correlation -.072 .076
Sig. (2-tailed) .400 .551
N 140 64
Shirt collar is Pearson Correlation -.025 .044
Sig. (2-tailed) .770 .728
N 138 64
Shirt pocket is Pearson Correlation -.062 -.195
Sig. (2-tailed) .467 .123
N 139 64
Shirt buttons are Pearson Correlation -.073 .053
Sig. (2-tailed) .397 .680
N 135 64
Shirt tail length is Pearson Correlation -.060 -.031
Sig. (2-tailed) .481 .811
N 141 64
Shirt sleeves are Pearson Correlation .057 .053
Sig. (2-tailed) .507 .680
N 137 64
Shirt cuffs are Pearson Correlation -.060 .093
Sig. (2-tailed) .486 .464
N 139 64
Shirt waist is Pearson Correlation .007 -.060
Sig. (2-tailed) .939 .640
N 139 63
Waist Size Pearson Correlation .007 .198
Sig. (2-tailed) .932 .116
N 137 64
Inseam Pearson Correlation .006 -.114
Sig. (2-tailed) .958 .368
N 89 64
Overall Satisfaction with pants Pearson Correlation -.014 -.170
Sig. (2-tailed) .868 .178
N 140 64
89
Table A4, continued
InterestscoreMC InterestscoreNT
Has Pants Altered Pearson Correlation -.187(*) -.013
Sig. (2-tailed) .029 .919
N 137 64
Can find pants that fit Pearson Correlation .102 .a
Sig. (2-tailed) .232 .
N 139 0
Pants legs are Pearson Correlation .001 .099
Sig. (2-tailed) .994 .437
N 139 64
Pants crotch length is Pearson Correlation -.071 -.010
Sig. (2-tailed) .402 .937
N 140 64
Pants hip is Pearson Correlation .036 -.164
Sig. (2-tailed) .675 .195
N 137 64
Pants leg is Pearson Correlation -.069 -.019
Sig. (2-tailed) .418 .882
N 139 64
Seat of pants Pearson Correlation .014 -.056
Sig. (2-tailed) .872 .661
N 140 63
Chest Size Pearson Correlation .270(*) .212
Sig. (2-tailed) .044 .098
N 56 62
Overall satisfaction with suits Pearson Correlation .118 -.037
Sig. (2-tailed) .175 .776
N 133 63
Has suits altered Pearson Correlation -.164 .180
Sig. (2-tailed) .056 .158
N 136 63
Can find jackets that fit Pearson Correlation .132 .214
Sig. (2-tailed) .119 .089
N 141 64
Can find jackets in their size Pearson Correlation -.013 .089
Sig. (2-tailed) .883 .486
N 141 64
Can find suits that fit Pearson Correlation .132 .210
Sig. (2-tailed) .119 .101
N 141 62
Pants of suits are right size Pearson Correlation -.020 .101
Sig. (2-tailed) .819 .426
N 139 64
90
Table A4, continued
InterestscoreMC InterestscoreNT
Jackets are Pearson Correlation .031 -.013
Sig. (2-tailed) .715 .920
N 140 64
Shoulders are Pearson Correlation .147 -.186
Sig. (2-tailed) .085 .144
N 139 63
Torso area is Pearson Correlation .121 .065
Sig. (2-tailed) .155 .609
N 139 64
The pants are Pearson Correlation .146 -.027
Sig. (2-tailed) .087 .833
N 138 64
The sleeve length is Pearson Correlation .030 -.059
Sig. (2-tailed) .725 .643
N 140 64
Overall Interest Pearson Correlation -.479(**) -.470(**)
Sig. (2-tailed) .000 .000
N 144 64
Work in Industry Pearson Correlation -.387(**) -.080
Sig. (2-tailed) .000 .532
N 143 64
Neck Size Pearson Correlation .396(**) .182
Sig. (2-tailed) .001 .149
N 73 64
Sleeve Length Pearson Correlation .035 -.018
Sig. (2-tailed) .826 .886
N 43 64
a. Cannot be computed because data was missing.
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
91
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BIOGRAPHICAL SKETCH
Education
Ph.D. in Apparel Product Development, Florida State University Anticipated graduation August
2008
M.S. in Clothing and Textiles, Florida State University
Creative Design program, December, 2003
B.A. in Music, Florida State University
April, 2002
Awards and Honors
Industrial Fabrics Association International, First Place winner of the Safety and Protective
Products Student Design Challenge 2005 for Fire Investigator‟s Coveralls.
Phi Beta Kappa, Spring 2002
Patents
Pending US Patent Application “Fire Resistant Coverall with Firearm Access Portal”
Juried Design Exhibitions
Mermaiden – International Textiles and Apparel Association, ITAA runway show, 2003.
White Evening Gown – Fashion Group International, Dallas Career Day runway show,
2001.