Interest and Needs in Men's Business Clothing Diana Kendrick Sindicich

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2008 Interest and Needs in Men's Business Clothing Diana Kendrick Sindicich

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COLLEGE OF HUMAN SCIENCES

INTEREST AND NEEDS IN MEN‟S BUSINESS CLOTHING

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

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.

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

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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

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

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

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

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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.

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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.

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).

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

2 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

3 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

4 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.

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 2 d(xn,ys) = Σ[di(xni,ysi)] 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.” l l l ai (ln(ysi) - bi - ln(xni)), if ln(xni) < ln(ysi) - bi

l h h h di(xni,ysi) = 0, if ln(ysi) - bi ≤ ln(xni) ≤ ln(ysi) + bi ∙ ai (ln(xni) - bi - ln(ysi)), h if kn(xni) > ln(ysi) + bi

“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)

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).

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.

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 Movement Impact Thermal Socio- assessment assessment assessment assessment psychological assessment

INTERACTION OF DESIGN CRITERIA ESTABLISHED State all Rank and Identify criteria chart criteria conflicts

PROTOTYPE DEVELOPMENT

DESIGN EVALUATION Objective compare the Subjective evaluation performance of the of the design design to the criteria

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

9 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 Minimize Maximize fire Minimize Matrix garment weight protection thermal retention Maximize range No conflict No conflict No Conflict of arm motion Minimize Accommodation No conflict garment weight needed Maximize fire Accommodation Conflict protection needed Minimize No conflict Conflict thermal retention

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. Figure 2. The FEA consumer needs model (Lamb and Kallal As visually represented in Figure 1, the 1992) consumer is the central core of this model. Adequate

11 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.

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

13 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

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

15 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

16 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

(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).

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

19 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?”

Table 4: Comparative Shirt Sizing Charts Among Selected Retailers

Neck Sleeve Length Size 32 33 34 35 36 37 38 39 40 LE Regular JAB JC LE Tall 14 Regular Regular JAB Tall LE Regular BB BB "Exact" "Exact" BB JAB JAB "Exact" 14.5 "Exact" "Exact" LE Tall BB "Exact" BB JAB "Exact" "Exact" LE Tall, BB JAB JC BB "Exact" "Exact" "Exact" Regular JAB "Exact" JAB LE JAB JAB Tall 15 "Exact" Regular Regular JC Tall LE Regular BB BB BB "Exact" "Exact" "Exact" BB "Exact" BB "Exact" JAB JAB JAB JAB "Exact" JAB 15.5 "Exact" "Exact" "Exact" LE Tall "Exact" BB "Exact" BB "Exact" LE Tall, BB BB JAB JAB "Exact" BB "Exact" "Exact" "Exact" "Exact" JAB Regular JAB JAB JAB LE JC Regular "Exact" JC Extra 16 "Exact" "Exact" Regular JAB Tall JC Tall Tall

BB BB BB BB "Exact" "Exact" "Exact" "Exact" LE Regular JAB BB "Exact" JAB JAB JAB BB "Exact" "Exact" JAB "Exact 16.5 "Exact" "Exact" "Exact" JAB "Exact" LE Tall Tall" LE Tall BB "Exact" BB "Exact" JAB JAB "Exact BB BB BB "Exact" "Exact" Tall" "Exact" "Exact" JAB "Exact" JAB JAB Tall, JAB JAB LE Regular Regular JC Extra 17 "Exact" "Exact" JC Regular JC Tall Tall

BB LE Regular BB "Exact" "Exact" BB "Exact" JAB "Exact BB "Exact" BB JAB BB "Exact" JAB Tall" JAB "Exact 17.5 "Exact" "Exact" JAB "Exact" "Exact" LE Tall Tall" BB "Exact" JAB "Exact BB "Exact" Tall" JAB "Exact LE Regular Tall" BB LE Big and JAB LE Tall, "Exact" LE Big Tall Regular BB "Exact" JAB JAB BB "Exact" JC Regular JC Tall JAB Tall "Exact "Exact JAB "Exact JC Big JC Big and JC Extra 18 Big" Big" Big" Regular Tall Tall

Table 5:

Comparative Shirt Sizing Charts Among Selected Retailers, continued

Neck Size Sleeve Length 32 33 34 35 36 37 38 39 40

BB LE Big and "Exact", BB "Exact" BB "Exact" Tall, JAB JAB JAB "Exact JAB "Exact BB "Exact" "Exact "Exact Big" Tall" JAB "Exact LE - Tall, 18.5 Big" Big" LE - Big LE Regular Tall" BB "Exact" LE Big BB "Exact" BB "Exact" JAB "Exact JAB "Exact BB "Exact" Tall" Tall" BB "Exact" JAB "Exact JC Big LE Big and JC Big and JC Extra 19 Big" Regular Tall Tall Tall

LE Big and 19.5 LE - Big Tall

BB "Exact" LE Big and BB "Exact" Tall, JAB "Exact JAB "Exact LE Big JC Big and 20 Big" Tall" BB "Exact" Tall

LE Big 20.5 LE Big and Tall

JC - Big LE Big 21 LE Big and Tall and Tall

LE Big 21.5 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.

Table 6

Comparable Pants Sizing Chart Among Selected Retailers

Waist Size Inseam Length unknown 28 29 30 31 32 34 36 38 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

L – B&T, 32 Gap L, D, Gap BB, L, D, Gap BB, L, D, Gap L, D, Gap L, Gap Tall Gap Tall LE, WM

33 Gap D, Gap BB, L, D, Gap BB, L, D, Gap L, D, Gap L, Gap Tall

BB, L, D, L – B&T, 34 Gap L, D, Gap BB, L, D, Gap D BB, L, D, Gap Gap L, D, Gap Tall D – B&T LE, WM

35 Gap Gap BB, D, Gap BB, D, Gap BB, Gap Gap Tall BB, L, D, L – B&T, 36 Gap L, D, Gap BB, L, D, Gap D BB, L, D, Gap Gap L, D, Gap Tall D – B&T LE, WM BB, L, D, L – B&T, 38 Gap L, D, Gap BB, L, D, Gap D BB, L, D, Gap Gap D, Gap Tall D – B&T LE, WM

BB, L, D, L – B&T, D, 40 Gap L, D, Gap BB, L, D, Gap BB, L, D, Gap Gap Gap Tall L – B&T LE, WM BB, D, L – B&T, LE, WM, 42 Gap BB, L, D, Gap BB, L, D, Gap Gap Dockers L – B&T WM B&T BB, L, L – BB, L, L – BB, L – B&T, D, D – Ga B&T, D, B&T, D, D LE, WM 44 Gap B&T, Gap p D – B&T, Gap – B&T L – B&T B&T L - B&T, D - L – B&T, D – L – B&T, LE, WM 46 B&T, Gap B&T, Gap D – B&T B&T

L – B&T, D – L – B&T, D – L – B&T, 48 B&T B&T D – B&T WM Big

L – B&T, D – L – B&T, D – 50 B&T B&T L – B&T WM Big

L – B&T, D – L – B&T, D – 52 B&T B&T L – B&T

L – B&T, D – L – B&T, D – 54 B&T B&T

L – B&T, D – L – B&T, D – 56 B&T B&T

L – B&T, D – L – B&T, D – 58 B&T B&T L – B&T, D – L – B&T, D – 60 B&T 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.

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

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

25 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.

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.

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.

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.

“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.

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 Experimentin Heightene Enhancemen Enhancemen Sensitivit for g with d t of security t of y to appearanc appearance awareness individuality comfort e of clothes Fashion Pearson .559(**) .849(**) .502(**) .525(**) .914(**) .352(*) forward Correlatio n Sig. (2- .000 .000 .000 .000 .000 .016 tailed) Analytical of Pearson .589(**) .720(**) .747(**) .495(**) .618(**) .404(**) others’ Correlatio n clothing Sig. (2- .000 .000 .000 .000 .000 .005 tailed) Self Pearson .374(*) .524(**) .634(**) .708(**) .348(*) .662(**) analytical Correlatio n Sig. (2- .010 .000 .000 .000 .018 .000 tailed) Correctness Pearson .839(**) .389(**) .384(**) .241 .328(*) .672(**) Correlatio n Sig. (2- .000 .007 .009 .106 .026 .000 tailed) Socio- Pearson .236 .525(**) .384(**) .938(**) .553(**) .298(*) psychologica Correlatio n l awareness Sig. (2- .114 .000 .008 .000 .000 .044 tailed) Practicality Pearson .311(*) .234 .534(**) .128 .120 .674(**) Correlatio n Sig. (2- .035 .117 .000 .398 .428 .000 tailed) N=46, ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).

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.

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 I can find up-to-date fashions in my size statements 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

33 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.

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.

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 223 297 103 400 201.15 47.197 (lbs.) Height (in.) 232 32 59 91 70.556 3.602 Age (yrs.) 233 35 20 55 28.71 8.437

Table 10 Group NT demographics N Range Minimum Maximum Mean Std. Deviation Weight 99 200 135 335 203.27 42.179 (lbs.) 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%

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.

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

35% 30% 25% 20% MC 15% NT 10% 5% 0% 109,999 110,000- 150,000- 200,000 Under 20,000- 50,000- 80,000- 20000 149,999 199,999 andup 49,999 79,999

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.

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.

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.

Table 17 BMI classification of respondents NHANES BMI MC NT Overall Data* range 2003-2004 Frequency Percent Frequency Percent Frequency Percent Percent Underweight Below 7 3.1 0 0 7 2.2 1.6 18.5 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 83 37.2 27 27.3 110 34.3 29.9 above 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.

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 43

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 Percentage Percentage Reporting Reporting 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

44 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

45 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

Sleeve Length Can find shirts that fit sizeNeck Issues Collar size Issues height Pocket Issues Button spacing Issues Shirttail length issues Sleeve length issues Cuff circumference issues Waist circumference Issues Neck Pearson Size Correlati .452(**) .142 .010 -.050 -.074 -.294(**) .031 -.221(*) -.140 .006 on Sig. (2- .000 .152 .922 .615 .457 .003 .755 .025 .157 .949 tailed) N 58 103 106 104 104 103 106 103 104 105 MC Sleeve Pearson Lengt Correlati 1 .018 -.004 .095 -.005 -.091 .330(**) .167 -.073 .192 h on Sig. (2- .893 .975 .478 .968 .499 .010 .214 .584 .149 tailed) N 60 57 59 58 58 58 60 57 58 58 Neck Pearson Size Correlati .403(**) .055 -.055 -.075 -.010 .358(**) -.093 .006 -.172 -.249(*) on Sig. (2- .000 .590 .592 .465 .924 .000 .364 .952 .093 .015 tailed) N 98 97 97 97 97 97 97 97 97 94 NT Sleeve Pearson Lengt Correlati 1 -.048 .116 -.112 .031 -.067 -.243(*) -.501(**) .022 .095 h on Sig. (2- .640 .256 .276 .764 .512 .016 .000 .831 .363 tailed) 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

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 MC NT Overall Issue 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

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 Crotch Legs too length too Hips too Leg too Seat too short/long short/long tight/loose tight/loose tight/loose MC Pearson -.120 -.020 -.032 -.063 -.041 Waist Correlation Size Sig. (2- .080 .771 .644 .359 .549 tailed)

N 212 212 209 212 212 Pearson -.055 .020 -.023 -.061 .080 Inseam Correlation Sig. (2- .512 .809 .791 .468 .343 tailed) N 142 142 140 143 142 Pants Pearson 1.000 .178(**) .023 -.205(**) -.089 legs are Correlation Sig. (2- .008 .739 .002 .187 tailed) N 223.000 220 218 220 221 Pants Pearson 1.000 -.217(**) .015 -.153(*) crotch Correlation length Sig. (2- .001 .826 .022 is tailed) N 223.000 219 221 222 Pants Pearson 1.000 .033 .268(**) hip is Correlation Sig. (2- .625 .000 tailed) N 220.000 219 219 Pants Pearson 1.000 .068 leg is Correlation Sig. (2- .316 tailed) N 223.000 221 Seat of Pearson 1.000 pants Correlation Sig. (2-

tailed) N 223.000

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.

Table 22 Pant issue correlations, Group NT NT Pearson -.025 -.021 -.272(**) -.265(**) -.262(*) Waist Correlation Size Sig. (2- .806 .836 .007 .009 .010 tailed)

N 96 96 96 96 95 Pearson -.219(*) -.253(*) -.157 -.247(*) -.283(**) Inseam Correlation Sig. (2- .032 .013 .127 .015 .005 tailed) N 96 96 96 96 95 Pants Pearson 1.000 .240(*) .169 .163 .196 legs are Correlation Sig. (2- .019 .100 .113 .057 tailed) N 96.000 96 96 96 95 Pants Pearson 1.000 .219(*) .176 .322(**) crotch Correlation length Sig. (2- .032 .086 .001 is tailed) N 96.000 96 96 95 Pants Pearson 1.000 .362(**) .585(**) hip is Correlation Sig. (2- .000 .000 tailed) N 96.000 96 95 Pants Pearson 1.000 .428(**) leg is Correlation Sig. (2- .000 tailed) N 96.000 95 Seat of Pearson 1.000 pants Correlation 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.

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 Percentage Percentage Reporting Reporting 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

51 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.

Table 24 Group MC: Suit issue correlations Pants of Shoulders suits are Jacket too too Torso too Pants too Sleeve too right size short/long wide/narrow small/long small/large short/long Chest Pearson .130 -.062 .098 .009 .138 .038 Size Correlation Sig. (2-tailed) .258 .597 .401 .941 .230 .746

N 77 75 75 75 77 77 Waist Pearson .134 -.083 .091 .041 .027 .083 Size Correlation Sig. (2-tailed) .053 .232 .194 .559 .695 .233

N 209 207 207 207 207 207 Inseam Pearson -.050 .087 .115 .096 -.109 .010 Correlation Sig. (2-tailed) .560 .310 .179 .263 .202 .907 N 139 137 137 137 138 138 Neck Pearson .029 -.222(*) -.071 -.057 -.023 -.104 Size Correlation Sig. (2-tailed) .775 .027 .483 .574 .819 .302

N 102 99 99 99 101 101 Sleeve Pearson .159 .008 .104 .107 .171 .005 Length Correlation Sig. (2-tailed) .226 .954 .438 .424 .196 .972

N 60 59 58 58 59 59 Age Pearson 0.172 .120 .149(*) -.012 .159* .110 Correlation Sig. (2-tailed) .010 .078 .028 .858 .019 .105 N 220 218 218 218 218 218 Height Pearson .075 -.192(**) .015 -.071 -.084 -.248(**) Correlation Sig. (2-tailed) .266 .004 .824 .300 .217 .000 N 220 218 218 218 218 218 Weight Pearson .158(*) -.174(*) .276(**) -.119 -.128 -.137(*) Correlation Sig. (2-tailed) .022 .012 .000 .086 .064 .047 N 211 209 209 209 209 209 BMI Pearson .142(*) -.086 .280(**) -.087 -.105 -.043 Correlation 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. 53

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.

Table 25 Group NT: Suit issue correlations Pants of Shoulders Sleeve suits are Jacket too too wide/ Torso too Pants too too right size short/long narrow small/long small/large short/long Chest Pearson .347(**) .015 -.234(*) -.250(*) -.244(*) -.069 Size Correlation Sig. (2-tailed) .001 .890 .029 .019 .022 .525 N 88 88 87 88 88 88 Waist Pearson .275(**) -.016 -.179 -.470(**) -.403(**) -.070 Size Correlation Sig. (2-tailed) .008 .878 .090 .000 .000 .510 N 92 92 91 92 92 92 Inseam Pearson -.135 -.286(**) -.163 -.057 -.087 -.230(*) Correlation Sig. (2-tailed) .200 .006 .123 .588 .408 .027 N 92 92 91 92 92 92 Neck Pearson .208(*) .028 -.196 -.218(*) -.129 -.117 Size Correlation Sig. (2-tailed) .047 .788 .063 .036 .222 .267 N 92 92 91 92 92 92 Sleeve Pearson .131 -.325(**) -.331(**) -.115 -.049 -.416(**) Length Correlation Sig. (2-tailed) .214 .002 .001 .275 .643 .000 N 92 92 91 92 92 92 Age Pearson -.041 -.168 -.093 -.110 -.188 -.155 Correlation Sig. (2-tailed) .705 .117 .389 .303 .078 .146 N 89 89 88 89 89 89 Height Pearson .122 -.330(**) -.475(**) -.042 -.009 -.337(**) Correlation Sig. (2-tailed) .247 .001 .000 .691 .930 .001 N 92 92 91 92 92 92 Weight Pearson .262(*) -.080 -.292(**) -.381(**) -.281(**) -.156 Correlation Sig. (2-tailed) .012 .449 .005 .000 .007 .139 N 92 92 91 92 92 92 BMI Pearson .228(*) .076 -.086 -.409(**) -.315(**) .001 Correlation 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).

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.

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%

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.

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.

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,

60 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).

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 -.050 -.186(**) -.227(**) Correlation Sig. (2-tailed) .411 .002 .000 N 270 269 270 Width Issues Pearson -.044 -.147(*) -.215(**) Correlation Sig. (2-tailed) .462 .013 .000 N 284 283 284 Length Issues Pearson -.039 -.158(**) -.096 Correlation 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).

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 Width Length Fashion Self- Issues issues issues Forward 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.

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.

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,

65 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

66 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

67 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

68 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.

APPENDIX A

QUESTIONNAIRE

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

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.

Button Placement

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 14 I can find dress shirts that fit Strongly Agree Neutral Disagree Strongly reasonably well Agree Disagree

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

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 Neutral Disagree Strongly Agree 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

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 Neutral Disagree Strongly Agree Disagree 39 I can always find jackets in my size Strongly Agree Neutral Disagree Strongly Agree Disagree 40 I can always find suits that fit reasonably well Strongly Agree Neutral Disagree Strongly Agree Disagree 41 When I find a suit jacket that fits, the pants are also Strongly Agree Neutral Disagree Strongly the correct size Agree 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

Please indicate how much you agree or disagree with the following Strongly Strongly Agree Neutral Disagree statements: Agree 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 1 2 3 4 5 to own them 49. I try on clothes in shops just to see how I will look in them 1 2 3 4 5 without really planning to buy 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 1 2 3 4 5 look in the styles 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 1 2 3 4 5 than others 57. I use clothing as a means of disguising physical problems and 1 2 3 4 5 imperfections through skillful use of color, line and texture 58. I read magazines and newspapers to find out what is new in 1 2 3 4 5 clothing 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 1 2 3 4 5 business clothes 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 1 2 3 4 5 attention 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 1 2 3 4 5 career goals 67. It bothers me when my shirt tail keeps coming out 1 2 3 4 5

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 ____Average Other: ______

Thank you for completing this survey, Your time and effort are greatly appreciated!

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.

APPENDIX B

INSTITUTIONAL RESEARCH BOARD APPROVAL MEMOS

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

APPENDIX C

ERROR CHECKING PROCEDURES

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

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.

APPENDIX D

ADDITIONAL TABLES

Table A1

Shirt overall correlations

Overal l

Sleeve Length Can find shirts that fit Neck size Issues Collar size Issues Pocket height Issues Button spacing Issues Shirt tail length issues Sleeve length issues Cuff circumfere nce issues Waist circumfere nce Issues Neck Pearson Size Corre- .426(**) .104 .003 -.029 .080 .204(**) -.145(*) .011 -.148(*) -.189(**) lation Sig. (2- .000 .141 .968 .679 .262 .004 .040 .883 .036 .008 tailed) N 156 200 203 201 201 200 203 200 201 199 Sleeve Pearson Length Corre- 1 .008 .115 .047 .084 .171(*) -.106 -.183(*) .109 .083 lation Sig. (2- .921 .151 .563 .301 .034 .185 .023 .175 .307 tailed) N 158 154 156 155 155 155 157 154 155 152

Table A2

Pant overall correlations

Can find Crotch Legs too Hips too Leg too Seat too pants that length too short/long tight/loose tight/loose tight loose fit short/long Overall Pearson .002 -.009 -.023 .010 -.137(*) -.013 Waist Correlation Size Sig. (2- .974 .880 .691 .860 .016 .817 tailed)

N 210 308 308 305 308 307 Pearson -.026 -.286(**) -.156(*) -.050 -.030 -.049 Inseam Correlation Sig. (2- .761 .000 .016 .445 .646 .456 tailed) N 142 238 238 236 239 237 (a) – Responses not recorded for this question and group

Table A3

Overall correlations between reported suit issues and size worn

Pants of Shoulders Sleeve suits are Jacket too too Torso too Pants too too right size short/long wide/narrow small/long small/large short/long Chest Size Pearson .224(**) -.108 .086 -.257(**) -.110 .013 Correlation Sig. (2- .004 .170 .276 .001 .159 .868 tailed) N 165 163 162 163 165 165 Waist Size Pearson .190(**) -.081 .168(**) -.195(**) -.175(**) -.006 Correlation Sig. (2- .001 .164 .004 .001 .002 .914 tailed) N 301 299 298 299 299 299 Inseam Pearson -.084 -.231(**) .015 -.065 -.083 -.231(**) Correlation Sig. (2- .203 .000 .821 .327 .207 .000 tailed) N 231 229 228 229 230 230 Neck Size Pearson .107 .032 .051 -.031 -.007 -.024 Correlation Sig. (2- .136 .659 .488 .674 .918 .740 tailed) N 194 191 190 191 193 193 Sleeve Length Pearson .145 -.009 -.111 .045 .098 -.111 Correlation Sig. (2- .075 .911 .178 .587 .232 .173 tailed) 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

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

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

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).

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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.