SEGMENTATION OF THE LEATHER FOOTWEAR MARKET FOR …

SEGMENTATION OF THE LEATHER FOOTWEAR MARKET

FOR BUSINESS WEAR AS DETERMINED BY PRODUCT

INVOLVEMENT AND PRODUCT ATTRIBUTES

OF FEMALE AND MALE CONSUMERS

by

LESLIE ERNST EVERSON, B.S.

A THESIS

IN

CLOTHING, TEXTILES, AND MERCHANDISING

Submitted to the Graduate Faculty

of Texas Tech University in Partial Fulfillment of the Requirements for

the Degree of

MASTER OF SCIENCE

Approved

May, 2002

ACKNOWLEDGEMENTS

This research project would not have been possible without the guidance and

support of several individuals. In particular, I would like to extend special thanks to

Dr. Shelley Harp, chairperson of my committee, for her hard work, professionalism

and continuing dedication in advancing research in the field of Merchandising.

I would like to thank Dr. Patricia Horridge for her insightful suggestions and

never ending patience in helping me complete my mission and I greatly appreciate

the help of Dr. Randall Russ as a member of my committee.

I would also like to extend my sincere gratitude to the exceptional support

staff, Linda Gambles, Carlene Leatherwood, and Adrienne Trimble, in the

Department of Merchandising, Environmental Design, & Consumer Economics at

Texas Tech University.

The Leather Research Institute at Texas Tech University provided invaluable

support and guidance in researching leather products and footwear, and I thank Dr.

Dennis Shelly for allowing me the opportunity to use their facilities.

I show appreciation to Doug Hubbard for his help in my statistical analysis

and to Andrea Ernst for her continual support and encouragement.

I want to give special recognition to my two wonderful children, Jake and

Juliet-Danielle, and to my Mom and Dad, who without their love and faith in me,

none of this would be possible.

TABLE OF CONTENTS

ACKNOWLEDGEMENTS ii

ABSTRACT viii

LIST OF TABLES x

LIST OF FIGURES xli

CHAPTERS

I. INTRODUCTION 1

Statement of the Problem 3

Significance of the Study 4

Assumptions 5

Research Questions 5

Limitations of the Study 5

II. LITERATURE REVIEW 7

Market Segmentation 7

Segmentation Concept 8

Segmentation Bases 11

Segmentation Measurement Scales 13

Apparel Segmentation Studies 15

Product Involvement 27

Antecedents of Involvement 27

Measures of Involvement 30

Levels of Involvement 31

Apparel Product Involvement Studies 32

Product Attributes 41

Attribute Concept 41

Measures of Product Attributes 42

Attribute Categories 43

Apparel Attributes and Stimuli 45

Apparel Product Attribute Studies 46

Leather Footwear Industry 64

Leather Products Industry Structure 64

Leather Footwear Industry Overview 65

Domestic Footwear Market 67

Footwear Market Trends 68

Summary of Review of Literature 71

METHODOLOGY 74

Conceptual Framework 74

Selection of the Sample 76

Research Instrument 77

Development of the Questionnaire 77

Description of the Questionnaire 79

Collection of Data 82

Variables of the Study 83

IV

Statistical Analysis of Data 90

Research Questions 91

IV. RESULTS 93

Description of the Sample 93

Working Females 93

Working Males 95

Footwear Opinion Leadership 96

Working Females 97

Working Males 97

Footwear Preferences 100

Working Females 100

Working Males 107

Footwear Involvement 117

Working Females 117

Working Males 123

Footwear Purchase Criteria 126

Working Females 127

Working Males 127

Footwear Consumption Patterns 130

Working Females 130

Working Males 132

Footwear Characteristics 132

Working Females 132

Working Males 136

Personal Characteristics 137

Working Females 137

Working Males 146

Scale Reliability and Tree Validation 147

Analysis of Research Questions 147

Research Question 1 147

Purchase Criteria 147



Purchase Criteria 151


Summary of Findings of Research Questions 158



V. SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS 160

Summary of the Study 160

Summary of the Findings 162

Personal Characteristics 162

Footwear Opinion Leadership 164

VI

Footwear Preferences 165

Footwear Involvement 167

Footwear Purchase Criteria 168

Footwear Consumption Patterns 169




Conclusions and Implications 174



Recommendations for Further Research 179

Sample 179

Data Collection 179

Instrument Design 180

REFERENCES 181

APPENDICES

A. AMERICAN CONSUMERS'QUESTIONNAIRE 193

B. U.S. SAVINGS BONDS ENTRY FORM 203

C. PRELIMINARY POSTCARD 205

D. REMINDER POSTCARD 207

E. ANSWERTREE® SOFTWARE 209

VII

ABSTRACT

Footwear has become a complex, competitive, and global industry.

Successful manufacturers and retail organizations are placing increased

emphasis on market segmentation to maintain market share. The purpose of this

study was to (a) segment a nationwide random sample of working female

(n=139) and male (n=116) consumers on High Involvement (HI) and Low

Involvement (LI) and (b) identify extrinsic and intrinsic product attributes that

influence their evaluation and purchase of leather footwear for business wear.

Data was collected using a mail survey method via a self-administered

questionnaire. Respondents were classified as HI (n=101) and LI (n=100) using

a footwear involvement scale. AnswerTree® software was used to answer the

research questions.

Findings indicated that differences existed between HI and LI consumers

on purchase criteria and footwear characteristics. Segment characteristics

indicated that HI consumers considered quality, color, durability, and construction

important to very important, and brand and latest fashion important to not

important In their purchase criteria for leather dress shoes for business wear. LI

consumers rated quality and construction as important to very important, and

color, brand, latest fashion, and shoes In wardrobe important to not Important.

HI consumers considered footwear characteristics as natural, well

constructed, comfortable, and expensive. LI consumers considered footwear

characteristics as not natural, poorly constructed, comfortable, and inexpensive

viii

and expensive. An understanding of consumer involvement and the Importance

of product attributes utilized in the evaluation and purchase of footwear has the

potential to benefit both the manufacturer and retailer in developing effective

marketing strategies to Increase customer satisfaction and increase market share

in the leather footwear market for business wear.

IX

LIST OF TABLES

4.1. Fashion Opinion Leadership by Working Females 98

4.2. Fashion Opinion Leadership by Working Males 99

4.3. Footwear Preferences by Working Females 101

4.4. Favorite and Purchased Footwear Brands

by Working Females 108

4.5. Stores Shopped for Footwear by Working Females 110

4.6. Footwear Preference by Working Males 112

4.7. Favorite and Purchased Footwear Brands

by Working Males 118

4.8. Stores Shopped for Footwear by Working Males 119

4.9. Footwear Involvement by Working Females 121

4.10. Footwear Involvement by Working Males 124

4.11. Footwear Purchase Criteria by Working Females 128

4.12. Footwear Purchase Criteria by Working Males 129

4.13. Footwear Consumption Patterns by Working Females 131

4.14. Footwear Consumption Patterns by Working Males 133

4.15. Footwear Characteristics by Working Females 134

4.16. Footwear Characteristics by Working Males 135

4.17. Personal Characteristics by Working Females 138

4.18. Personal Characteristics by Working Males 142

4.19. High Involvement Leather Footwear Purchase Criteria: Gain Summary 152

4.20. Low Involvement Leather Footwear Purchase Criteria: Gain Summary 154

4.21. High involvement Leather Footwear Characteristics: Gain Summary 156

4.22. Low Involvement Leather Footwear Characteristics: Gain Summary 157

5.1 Research Question 1: Summary 171

XI

LIST OF FIGURES

4.1. Footwear Purchase Criteria: decision tree 148

4.2. Footwear Characteristics: decision tree 150

XII

CHAPTER I

INTRODUCTION

The scope of leather footwear operations has grown steadily since the

early 1980s (Ballance, Robyn, & Forstner, 1993). About 65% of the world

production of leather is estimated to go into leather footwear ("Perspective of

Leather," 2000). World shoe output was estimated at more than 11.8 billion pairs

in 1999 worth an estimated $150 billion at wholesale prices (Bulrski, 1999).

Therefore, footwear is recognized as a major sector of the leather industry and

considered of great economic importance on an International scale ("Global

Shoemaking Grows," 2001).

Developing countries now produce over 60% of the worid's leather, and

this proportion continues to grow. An increasing proportion of footwear is

manufactured in emerging markets, leading to greater global movement of

finished products. This trend should continue over the next 10-15 years as

global trading companies have little allegiance to individual countries or source of

products. Southeast Asia is expected to continue to play a dominant role in

footwear production with China currently responsible for 40% of production and

likely to continue growth. However, this projected growth in footwear production

will depend on a combination of economic factors, political relations, social

influences, and consumer preference for greater comfort and quality products

with increased demand for footwear with greater fitting tolerances (Buirski, 1999).

Per capita consumption of footwear varies widely throughout the world

and appears to give a reasonable indication of a country's general standard of

living ("Global Shoemaking Grows," 2001). The United States (U.S.) has been

seen for many years as the largest open footwear market in the worid with a

consumption of over 1700 million pair of shoes annually or 15% of the worid

market. With such large retail and consumer markets, American footwear

companies have stayed Important as specifers, controlling design, materials,

quality, and marketing even though manufacturing has moved primarily to foreign

operations ("Footwear Market Grows," 2000)

Consumer trends will continue to be important as predictors of lower per

capita consumption due to longer lasting footwear, an aging population, less

formal business dress, and consumer demand for value for money spent on

footwear (Buirski, 1999). The main drivers of change at the retail level include

clothing and footwear sold together, less footwear sold through specialty stores,

growth in catalog sales and the Internet, decrease in stock levels, and availability

of custom-made footwear. On the technical front, change will be influenced by

environmental legislation and the need to develop methods to provide high

product performance ("Best Footwear FonA/ard," 2000).

Due to the increasing effects of globalization, consumer demands, retail

structure, and technology, retailers are identifying market opportunities through

intensified gathering of data on consumer footwear purchase behavior and

shopping orientations via loyalty cards ("Best Footwear Forward," 2000). In turn.

to remain competitive, U.S. footwear sourcing companies and manufacturers will

need to develop a global vision of the industry with a thorough understanding of

the market, monitor major influences on the worldwide footwear industry, create

marketing alliances with members In the entire supply chain including design and

specification, and be knowledgeable of consumer and fashion trends (Buirski,

1999). The bottom line Is that both retailers and manufacturers are after the

same thing: customer loyalty. Market segmentation provides a way to

understand and enhance customer loyalty by enabling marketers to tailor

products and efforts to the needs of particular groups of customers (Kelly, 1998).

Statement of the Problem

The study was designed to (a) segment the female and male leather

footwear market within a set of U.S. consumers by their footwear involvement

and (b) identify product attributes (extrinsic and intrinsic) that influence their

purchase decisions and consumption behavior for leather dress shoes for

business wear. The specific steps undertaken to accomplish the research goals

were:

1. Determine High involvement (HI) consumers and Low Involvement (LI)

consumers based on beliefs and attitudes regarding shoes for business

wear,

2. identify group membership of HI consumers and LI consumers on

footwear purchase criteria and footwear characteristics, and

3. develop guidelines to classify HI and LI consumers on their purchase

behavior regarding leather dress shoes for business wear.

Included in the analysis were footwear opinion leadership, footwear preferences,

footwear involvement, footwear purchase criteria, footwear consumption

patterns, footwear characteristics, and personal characteristics.

Significance of the Study

This study extended the research in the area of market segmentation with

respect to product involvement and product attributes associated with a fashion

related product category. Marketers who base products and promotion on the

results of market segmentation as determined by product involvement and

product attributes can narrow their focus in targeting specific consumers.

The findings of this study will help leather footwear manufacturers and

retailers better identify marketing opportunities, develop the right product for each

target market, and subsequently adjust their prices, advertising, and sales

promotion to reach the target market efficiently. In addition, the study contributes

to the body of knowledge in apparel shopping behavior with a nationwide random

sample of female and male consumers with respect to the effect of product

involvement and product attributes on the evaluation of leather footwear

purchased and consumed for business wear usage situations.

Assumptions

There were several assumptions made for this study. The first

assumption was that subjects were representative of employed male and female

consumers in the U.S. Second, it was assumed that subjects understood written

instructions and answered Items on the questionnaire based on specificity,

action, target, context, and time. Third, subjects would report information

honestly and accurately.

Research Questions

Based on the purpose of the study and pertinent findings in the reported

literature, the following research questions were asked:

RQ1. Can HI and LI consumers be grouped by their assessment of the footwear

purchase criteria and footwear characteristics of leather dress shoes for

business wear?

RQ2. Can HI and LI consumers be classified on their leather footwear purchase

behavior, thus benefiting the retailer selling leather shoes to HI and LI

consumers in footwear purchase criteria and footwear characteristics?

Limitations of the Study

Several limitations to this research were identified. Participants were

employed male and female consumers from the entire U.S. who wore leather

dress shoes to work at least one day a week. A randomized national mailing list

of consumers was purchased from National Demographics & Lifestyles Inc.

(NDL). Subjects Included in the sampling frame were categorized as to working

males and working females. Footwear opinion leadership, preferences regarding

footwear worn for business wear, favorite and purchased footwear brands, stores

shopped for footwear, footwear involvement, footwear purchase criteria, footwear

consumption patterns, footwear characteristics, and soclodemographic

characteristics focused on classifying consumers by High or Low Involvement.

Additionally, results are only applicable to leather dress shoes purchased and

consumed for business wear. The consumers were surveyed during the summer

of 1998. Information was limited to that drawn by the responses on the

questionnaire. Therefore, caution should be employed in generalizing results to

other types of consumers, usage situations, and product categories.

CHAPTER II

LITERATURE REVIEW

The effectiveness of marketing strategy depends, in part, on how

accurately channel members define target consumers and develop product

assortments based on distinct purchase behavior. This review of related

research and literature focuses on market segmentation, product involvement,

product attributes, and the leather footwear industry.

Market Segmentation

Segmentation has evolved from an academic concept (Smith, 1956) into a

key marketing planning tool (Sheth, Sisodia, & Sharma, 2000). In this context,

segmentation provides a strategic marketing approach to understanding a

particular group of consumers' purchasing behavior (Kelly, 1998). In turn, the

accuracy of a firm's use of segmentation is an important criterion of competitive

market advantage (Sauerman, 1998). In order for segmentation to be

successful, the population must be described in measurable terms, be accessible

to promotional activities, be divided into homogeneous groups, and be potentially

profitable (Cross, 1999).

Market segmentation is the process used to break diverse markets into

smaller groups of potential consumers with similar characteristics who might

purchase products in the same way (Danneels, 1994). By selecting one or more

subgroups as targets for marketing activities, companies can determine the best

marketing mix or diversity of products needed to increase profitability in today's

marketplace (Sauerman, 1998). An effective segmentation program provides a

systematic approach for controlling market coverage resulting In higher sales

than mass-market approaches (Kelly, 1998). Thus, the objective of

segmentation research is to analyze markets, find unique opportunities, and

increase market share (Cross, 1999).

Recent changes in the market environment and advances in information

technology present new challenges and opportunities for market segmentation

(Sheth, Sisodia, & Sharma, 2000). Published segmentation research has

expanded to encompass a variety of application areas (Grier & Brumbaugh,

1999). Currently, marketing practitioners and researchers are focusing on topics

such as, micro marketing segmentation, global market segmentation, direct

marketing segmentation, retail segmentation, geodemographic segmentation,

segmentation for optimizing service quality, segmentation for customer

satisfaction evaluation, segmentation for new product development,

segmentation using single-source data, and so on (Myers, 1996; Wedel &

Kamakura, 1998; Weinstein, 1994; Wensley, 1995;).

Segmentation Concept

Smith (1956) first defined the market segmentation concept as viewing a

heterogeneous market as a number of smaller homogeneous markets, in

8

response to differing preferences; attributable to the desires of consumers for

more precise satisfaction of varying wants. Frank, Massy, and Wind (1972)

defined market segmentation as the recognition of the existence of multiple

demand functions and development of a marketing plan to match one or more of

the demand functions. This definition views market segmentation as a tool of

marketing.

Mahajan and Jain (1978) referred to market segmentation as a form of

research analysis directed at identification and allocation of resources among

market segments. Market segmentation, in this perspective, is seen as a way of

viewing the market rather than defined as a management strategy (Dickson &

GInter, 1987). In the most general of terms, market segmentation is a way to

break down a large group of consumers into smaller, more easily defined groups

that can be directly targeted based on distinct buying behavior (Kotler, 1988).

The way in which market segmentation is viewed leads to how market

segmentation is approached. The conceptual framework of market segmentation

that a company uses determines the way in which data is collected and utilized

(Wyner, 1999/2000). Therefore, researchers' or corporations' findings regarding

the quantity and properties of market segments will change with the conceptual

and analytical approaches to segment categorization (Dickson & GInter, 1987).

Methods employed in segmentation research can be classified in a variety

of ways. A segmentation approach is called a pn'on when the type and number

of segments are determined in advance by the researcher and post hoc when the

type and number of segments are determined by the results of data analysis

(Wyner, 1999/2000). Hybrid forms of segmentation combine a priori and post

hoc procedures (Wedel & Kamakura, 1998). Descriptive methods analyze the

associations across a single set of segmentation bases, with no distinction

between dependent and Independent variables. Predictive methods analyze the

association between two sets of variables, where one set consists of dependent

variables to be explained or predicted by the set of independent variables

(Magdison, 1994).

A customer-based versus product/service-based classification scheme

often is used as a theoretical framework for segmentation research. Customer-

based classification entails finding unique characteristics of consumers; for

example, demographics, psychographics, values, and needs, that distinguish

them in significant ways for marketing planning purposes. In comparison, a

product/service-based approach determines the types of benefits customers

want from specific attributes of certain products or services, usage rates or

patterns, and other aspects of the product/service usage situation (Myers, 1996).

Market segmentation is a theoretical concept involving artificial groupings

of consumers constructed by researchers and managers to help design target

marketing strategies (Ambler, 1999). The identification of market segments is

highly dependent on the bases and methods used In the segmentation process

(Wyner, 1995). Selection of appropriate segmentation bases and methods is

10

crucial with respect to the number and type of segments that are identified in

segmentation research, as well as to their usefulness to the firm (Smith, 1995).

The choice of a segmentation basis follows directly from the purpose of

the study (e.g., new product development, price setting) and the market in

question (e.g., retail, business to business, consumers) (Kohli & Jaworski, 1990).

The choice of different bases may lead to different segments being revealed; as

the application of different segmentation methods. Furthermore, the choices of

methods and bases are not independent. The segmentation method will need to

be selected on (a) the specific purposes of the segmentation study and (b) the

properties of the segmentation bases selected (Wedel & Kamakura, 1998).

Segmentation Bases

A segmentation basis is used to assign potential customers to

homogeneous groups. Different classifications of basis variables can be

employed to segment consumer markets (Myers, 1996). Basis variables or

characteristics generally are classified as customer or product/service related

and whether observable or unobservable. Furthermore, basis variables are

classified as either dependent or independent (Frank, Massy, & Wind, 1972).

Customer-based segmentation variables within the observable

classification fit into four groups: cultural, geographic, demographic, and socio

economic. Observable product/service bases comprise variables related to

buying and consumption behavior: user status, usage frequency, brand loyalty,

11

store loyalty and patronage, stage of adoption, and usage situations. Customer-

based unobservable segmentation variables fit into four groups: psychographics,

values, personality, and life-style. Unobservable product/service bases comprise

hierarchy variables related to benefits, perceptions, attributes, preferences, and

Intentions (Kotier, 1988).

Dependent variables are the desired outcomes to be explained or

understood. Independent variables are used to explain or predict the dependent

variables and provide diagnostics to indicate factors likely to affect the outcome.

Distinction between the two types of basis variables leads to the type of statistical

techniques selected for segmentation purposes. Dependence techniques use

independent variables to predict or explain dependent variables.

Interdependence techniques search for groups of people or items that are found

to be similar in terms of one or more sets of basis variables. All variables are

considered to be equal in terms of interest. No attempt is made to single out any

variables as more important as Is done in dependence analysis (Weinstein,

1994).

Cross (1999) suggested the use of five categories of variables when

segmenting consumer markets: demographics, geographies, psychographics,

user benefits, and product usage. Demographics are probably the most widely

recognized segmentation method and include attributes such as age, gender,

income, occupation, education, race, nationality, religion, and family size.

Geographic segmentation divides the market based on a market's location and

12

include population density and climate as well as subcultural values affecting

consumer's product needs, preferences, and purchasing behavior.

Psychographics segmentation divides the market by social class, lifestyle

descriptors, and personality traits. User benefits classify segments by what

consumers deem most important about the product (i.e., quality, service, speed,

and price). Product usage defines segments as regular users, potential users,

nonusers, ex-users, and first-time users.

Segmentation approaches using different types of basis variables yield

more actionable results on which to plan marketing decisions in contrast to the

theory that implies a single best basis for segmenting a market (Wilkie & Cohen,

1977). Attempts to use a single basis for segmentation such as demographics,

psychographics, brand preference, or product usage often result in incorrect

marketing decisions as well as a waste of resources. Within a diverse basis

variables framework, researchers have wide latitude in selecting specific factors

on which to focus and methodologies to use to segment a market. In addition, a

multiple basis variable approach provides a greater amount of information along

with Insights and understanding of the market that would not otherwise be

available (Dhalla & Mahatoo, 1976).

Segmentation Measurement Scales

The type of measurement scale selected to assess each basis variable is

determined by the kind of information to be collected and the objectives to be

13

met. Distinctions between the types of measurement scales in terms of which

basis variables are to be investigated are Important because they determine the

specific statistical technique that is required for a particular objective or type of

analysis (Myers, 1996).

Nominal scales consist of numbers designating categories that are in no

particular order and have no necessary relation to one another. Scale values, if

any, are used only for identification. Examples of such variables in consumer

segmentation research are ethnic background, geographic area, and occupation.

Ordinal scales consist of numbers in rank order, such that each number identifies

a category that is higher or lower in value than any of the previous categories.

The distance between consecutive values can vary considerably from one rank

order to another. Hence, the difference in values between three and four can be

greater or smaller than that between seven and eight. Examples in segmentation

research include rank orders of preference for brands and attribute performance

ranks (James, Brinberg, & Ackerman, 1986).

Interval scales consist of numbers whose difference in value are the same

for all consecutive numbers on the scale. Thus, the difference in value between

three and four Is approximately the same as between seven and eight. Interval

scales have no absolute zero point that indicates the complete absence of

whatever is being measured. Examples in segmentation include respondent

ratings of brand attributes, attitude statements, and lifestyle descriptions. Ratio

scales consist of numbers that have rank order of value, equal value differences

14

between consecutive numbers, and a zero point indicating no amount of what is

being measured. Segmentation examples include dollar amounts, frequency of

usage, and demographics such as age, income, and number of persons in a

family (Wind, 1978).

Apparel Segmentation Studies

Cassill and Drake (1987) investigated the relationship of life style and

evaluative criteria for apparel using a cross-national mailing list of female

consumers (n=842). Principal Components Factor Analysis was used to reduce

the number of lifestyle and evaluative criteria variables to 12 factors (eight

lifestyle, three social apparel evaluative criteria, and one employment apparel

evaluative criterion). Nineteen significant relationships existed between the

lifestyle and evaluative factors, suggesting that consumers choose apparel items

that fit into lifestyles. The results produced distinct market segments with variant

benefits sought from the use of apparel. The consumer segment that scored

high on Appropriateness emphasized the importance of clothing being attractive,

comfortable, suitable to individual, appropriate for occasion, good fit, and of good

quality fabric and construction. These consumers are self-confident, satisfied

with life, want to be physically attractive in fashionable clothing, and concerned

with price. The consumer segment scoring high on an Economic factor,

emphasized price, ease of care, and durability, and is characterized by traditional

values, purchasing American products, support of education, and above all.

15

concern for economy. The consumer segment that scored high on Other-

People-Directed emphasized apparel, which is fashionable, sexy, and conveys

an air of prestige. These consumers purchase American goods, value education,

and tend to move less frequently than the other two consumer groups.

Cassill (1990) examined female consumers' (n=383) employment

orientation on apparel decisions and evaluation of Imported apparel to more

closely define consumer profiles. Employment orientations were found to

significantly influence apparel decisions and the evaluation of imported apparel.

Results grouped the female consumer Into four distinct classifications, Career-

Oriented Working Women (53%), Just-a-Job Working Women (24%), Plan-to-

Work Housewives (19%), and Stay-at-Home Housewives (4%). Significant

differences were found among the different classifications. Employed women

were more likely to purchase brand name apparel and were willing to pay more

for branded apparel. Career-Oriented women placed more importance on the

fiber content In a garment and preferred a durable product to a fashion product.

Non-employed women indicated that apparel care was very important and

preferred to purchase apparel that did not require dry cleaning. Non-employed

women were more likely to prefer imported apparel and when priced lower than

domestic apparel, imported apparel is more acceptable. Plan-to-work women

were more likely to notice country of origin labels and found styling, appearance,

fit, and color selection of imported apparel very acceptable.

16

Shim and Kotsiopulos (1991) studied the segmentation of the big and tall

men's apparel market by clothing involvement and the relationship to consumer

characteristics and clothing shopping behavior. Participants (n=172) were

grouped into three classifications: low (n=45), medium (n=76), and high (n=51)

involvement in clothing purchases. The groups were compared on customer

characteristics such as clothing orientations, lifestyle activities, and

demographics, and on shopping behavior dimensions such as satisfaction with

clothing shopping experiences and clothing buying practices. Principal

components factor analysis with varimax rotation was utilized to develop

constructs of clothing orientation, lifestyle activities, and clothing buying

practices. Age, marital status, education, race, employment status, occupation,

and household total yearly income were Included in demographics.

The three groups were different in both instrumental usage of clothing and

the degree of fashion interest. The higher usage of clothing as a tool of

impression management and higher interest In fashion reflect high clothing

involvement. Among lifestyle activities factors, high clothing-involved consumers

indicated they frequently engaged in Cultural/Social activities. There were no

differences among the three groups in Sports Activities, Home/Family Activities,

and Club/Business Activities. Demographics did not influence the level of

clothing involvement among the big and tall men (Shim & Kotsiopulos, 1991).

The high-involved consumers were least satisfied with the general quality

of sale personnel. The higher the involvement with clothing, the more interest in

17

shopping, the more patronage to a particular store, and the more confidence in

putting together a professional wardrobe or in choosing the right clothes. The

amount of money spent on wardrobe per year appeared to be significantly

related to the level of involvement. Higher clothing-involved consumers were

clearly the heavy buyers in terms of dollars per year. High and low involved

consumers were not as concerned with the practical evaluative criteria (such as

construction features, care required, and fiber content) or price so much as those

who were in the middle of the involvement scale. None of the groups were

significantly different in terms of the infiuence of mass media and personal

sources such as friends or colleagues or In shopping around in different stores

for alternative sources (Shim & Kotsiopulos, 1991).

May, Shim, and Kotsiopulos (1992) researched tuxedo customers (n=90)

using criterion variables consisting of purchasers and renters classified as light or

heavy users. Predictor variables for the study included information search

patterns, clothing Involvement, product characteristics, clothing behaviors, and

consumer demographics. Results found six predictors to discriminate

purchasers from renters of tuxedos. The individual who purchased a tuxedo was

willing to pay significantly more than a renter was. Tuxedo owners spent more

time than renters in searching various media before making a purchase decision.

Purchasers tended to use some type of bank credit (e.g., MasterCard) while

renters tended to use cash or checks. The tuxedo purchasers tended to be

older, married, and has higher levels of education than renters.

18

Three factors appeared to discriminate heavy and light tuxedo users.

Heavy users were more concerned with the practical aspects of the tuxedo:

comfort, fabric types and quality, quality of construction, and value for the price.

The light tuxedo user relied more on the fashion advice and guidance of sales

personnel. The heavy tuxedo user spent more time seeking information before

making a decision on tuxedo usage. Heavy users were more likely to use some

form of bank credit to pay for purchases while light users tended to use cash or

checks. No significant differences were found with respect to consumer

demographics (May, Shim, & Kotsiopulos, 1992).

Summers, Belleau, and Wozniak (1992) investigated female customer

(n=598) psychographics dimension of perceptions of fashion and perceptions of

apparel shopping that was related to store patronage as well as demographic

characteristics. Twenty consumer perceptions were reduced to five factors by

factor analysis: Shopping Involvement, Importance of Clothing Image, Fashion

Commitment, Quality Conscious, and Fashion Aversion. Respondent's factor

scores were used as the dependent variables with patronage behavior and

demographic characteristics as the independent variables. Results revealed that

rural (n=320) and urban (n=278) consumers held similar perceptions of fashion

and of apparel shopping as measured by the five factors. Significant differences

in the factor scores were noted with type of stores patronized, shopping locales

favored, time spent shopping for apparel, ethnicity, age, martial status,

education, work status, and total family income.

19

Shopping Involvement, Fashion Commitment, and Quality Conscious were

significantly greater for individuals who shopped for themselves or family

members at clothing specialty stores than for respondents who shopped in

discount stores. Scores of respondents who shopped for apparel for themselves

or family members in discount or department stores were significantly higher on

Fashion Aversion than were the scores of respondents who shopped in clothing

specialty stores. As women spent more time shopping. Shopping Involvement,

Importance of Clothing Image, Fashion Commitment, and Quality Conscious

increased. Respondents who spent three hours or less shopping for apparel had

significantly higher scores on Fashion Aversion than did respondents who spent

more than three hours shopping (Summers, Belleau, & Wozniak, 1992).

Shopping Involvement and Fashion Commitment were higher for non-

whites than whites. Whites scored higher on Importance of Clothing Image than

non-whites. Younger respondents scored highest on Shopping Involvement and

Fashion Commitment while the oldest respondents scored the lowest. Older

respondents had significantly higher scores on Quality Conscious than did

younger respondents. The youngest respondents scored significantly lower on

Fashion Aversion than respondents in any of the other age categories.

Unemployed women scored significantly higher on Shopping Involvement and

Fashion Commitment than homemakers and retired women. Retired

respondents had a Quality Conscious score significantly higher than all other

respondents. Homemakers and retired respondents had significantly higher

20

scores on Fashion Aversion than did employed and unemployed respondents

(Summers, Belleau, & Wozniak, 1992).

Respondents who were not married had a significantly higher Fashion

Commitment than did married respondents. Married respondents had a

significantly higher score on Fashion Aversion than respondents who were not

married. Respondents with the least education had the highest scores on

Fashion Aversion while respondents with graduate study had the lowest scores.

Respondents with the highest total family Incomes had the highest scores on

Importance of Clothing Image, Fashion Commitment, and Quality Conscious

while respondents with the lowest family incomes had the lowest scores

(Summers, Belleau, & Wozniak, 1992).

Shim and Kotsiopulos (1992) examined the comprehensive relationships

among key variables, that impacted patronage behavior of apparel shopping with

female consumers (ri=482). Variables Included patronage behavior, store

attributes, shopping orientations, information sources, and personal

characteristics. Results suggested patronage profiles for discount stores,

specialty stores, department stores, and catalogs. Also, predictor of store

attributes, shopping orientations, and information sources were identified.

Based on the findings regarding prediction of patronage behavior, a profile

of apparel shopping patronage was developed. Respondents who patronized

discount stores for shopping apparel products were more likely to: place

importance on frequent special sale prices, price levels, or return policies; be

21

economic shoppers; use media information; be lower In social class; not be

concerned with clothing quality or variety of style; not be appearance managers;

not use credit cards; not read fashion publications; not be engaged in cultural

activities; and not be In the first stage of the family life cycle. The respondents

who patronized specialty stores for shopping apparel products were more likely

to: place Importance on clothing quality or variety of style; be concerned with

brand names or new fashion that stores carry; be appearance managers; be

fashion conscious; be heavily engaged in grooming activities; not be concerned

with frequent special sale prices, price levels, or return polices; and not be

economic shoppers. Respondents who patronized department stores for

shopping apparel products were more likely to be: mall shoppers and in the first

stage of the family life cycle. The respondents who used catalogs for shopping

apparel products were more likely to: have a catalog shopping orientation; not be

concerned with easy access of the stores; not be fashion conscious; not be

apathetic toward "Made-in-U.S.A"; not be mall shoppers; and not be local store

shoppers (Shim & Kotsiopulos, 1992).

The Infiuence of each of three sets of factors (shopping orientations,

information sources, and personal characteristics) on seven factors of store

attributes was investigated. Shopping orientations appeared to be most

Important, followed by information sources, and personal characteristics as

determinants of the importance of store attributes. In terms of shopping

orientations, appearance managers tended to place high importance on store

22

attributes such as visual image of store, quality/variety, brand/fashion, easy

access, and sale personnel. Brand or fashion conscious consumers placed

importance on brand name of store, customer services, or visual image of the

store. Shoppers who had convenience/time conscious shopping orientation

placed importance on easy access, while economic shoppers placed high

importance on frequent sales prices or on low price level and excellent return

policies (Shim & Kotsiopulos, 1992).

In terms of information sources, respondents who frequently used store

fashion promotional activities tended to think that sales personnel, customer

service, and visual image of store were Important. The respondents that

frequently read fashion publications tended to think that brand/fashion and

quality/variety were Important. Also, the respondents who rely on fashion

publications and less social interaction tended to be more self-confident in their

apparel decision-making (Shim & Kotsiopulos, 1992). In terms of personal

characteristics, respondents who stressed the importance of personal visual

image were concerned with a store's visual image.

Information sources and personal characteristics appeared to be of

relatively equal importance in predicting shopping orientations. Economic

shoppers and local store shoppers tended to use media while mall shoppers

used personal sources. The confident, brand and fashion conscious, less

convenience/time conscious, catalog-oriented shoppers, appearance managers,

and credit users tended to use fashion publications. Social class appeared to be

23

most important in predicting confident, brand conscious, catalog-oriented

shoppers, credit users, and less economically concerned shoppers. Grooming

activities appeared to be the most important predictor of the appearance

manager and fashion conscious shopper (Shim & Kotsiopulos, 1992).

Different personal characteristics tended to predict different types of

information sources for making apparel purchase decisions. Respondents who

were frequently engaged in cultural and grooming lifestyle activities tended to

use store fashion promotion and fashion publications while respondents who

were frequently involved with community projects and respondents who were in

the first stage of the family life cycle tended to use personal sources. Single

under 35 consumers were primarily mall shoppers, less convenience/time

conscious, and less apathetic toward "Made-in-U.S.A.". Shoppers under the age

of 35 were likely to be in good physical condition and were willing to expend

energy and time in shopping in a mall environment (Shim & Kotsiopulos, 1992).

Shim and Bickle (1994) completed a twofold consumer investigation

(n=610) designed to: (a) segment the female apparel market based on

descriptive clothing benefits sought by female consumers and (b) develop a

profile of each segment concerning psychographics, shopping orientations,

patronage behavior, and demographics. Using cluster analysis on benefits

sought factors; three groups were identified and classified as (a)

Symbolic/Instrumental Users of Clothing (51%), (b) Practical/Conservative Users

of Clothing (35%), and (c) Apathetic Users of Clothing (14%).

24

Results illustrated important differences among the three benefit segments

on 10 psychographics factors; Creative/Innovative, Independent/Opinion Leader,

City Prone, Friends-Oriented, Religious, Health/Exercise-Oriented, Education-

Oriented, Pessimistic-Finance Outlook, Overseas Travel Dreamer, Optimistic

Career Viewpoint, three shopping orientation factors; Shopping Enjoyment,

Fashion-Oriented Shopper, and Credit User, one patronage behavior variable;

stores shopped at most frequently, and seven demographic factors; education,

occupation, age, marital status, geographic region, residential area, and income

(Shim & Bickle, 1994).

Symbolic/Instrumental Users of Clothing were characterized by actively

using clothing as a means to enhance self-esteem, career advancement,

reputation, social status or prestige, femininity, sex appeal, fashion image, role

and appearance. In terms of psychographics, this group was innovative,

independent, socially oriented, exercise-health oriented, and optimistic about

education, career, and finance. Women in this category enjoyed shopping at

upscale stores, were fashion-conscious shoppers, and credit users. As

compared to other groups, this group was younger and represented a higher

social class in terms of education, occupation, income, and residential area.

Practical/Conservative Users of Clothing were characterized as

practicality-, individuality-, comfort-, and function-oriented. In terms of

psychographics, this group was independent and tended to be pessimistic about

financial outiook. Women in this category were not likely to enjoy shopping and

25

tended to be department store shoppers. As compared to other groups, this

group tended to be older, and represented a middle social class in terms of

education, income, and residential area (Shim & Bickle, 1994).

Apathetic Users of Clothing were characterized by the belief that clothing

was of no significance or did not provide them any means to assist themselves.

In terms of psychographics, this group was less likely to be independent or

creative/innovative, health-conscious or education oriented, and had pessimistic

views concerning finance and career outiook. Women in this category were not

likely to enjoy shopping or be fashion-conscious shoppers and tended to

patronize discount stores. As compared to other groups, this group was

divorced, separated, or widowed and represented a lower social class in terms of

education, occupation, and income (Shim & Bickle, 1994).

Kim and Lee (2000) examined segmentation of professionals (n=493)

based on benefits sought. Using cluster analysis, three distinct segments of

catalog shoppers were identified: Convenience Seekers (40.5%), Product

Seekers (27.1%), and Inactive Shoppers (25.9%). Full profiles of the benefit

segments were developed based on personal (demographics and lifestyle) and

situational (purchase for self versus for others; gifts versus non-gifts) variables.

Results indicated that Convenience Seekers, who tended to use catalogs out of

convenience, were more likely to be married professionals with highest levels of

self-confidence and fashion-consciousness, and to use clothing catalogs most

frequently for both themselves and others. Product Seekers, who exhibited

26

interest in product-related benefits (e.g., quality, variety, price and ease of

return), tended to be married professionals and most price-conscious. Inactive

Shoppers, displayed the lowest importance level for all identified benefits, tended

to be married male professional with lowest levels of fashion-consciousness and

self-confidence, and tend to use catalogs less frequently.

Product Involvement

The theory of consumer Involvement has had a major impact on the study

of consumer behavior in the last 30 years (Thomas, Cassill, & Forsythe, 1991).

While researchers agree that the study of involvement is important to explaining

and predicting behavior of the consumer there is little consensus on how to best

define and measure the construct of involvement (Zaichkowsky, 1985). The

reasons for the diversity in definitions and measures of involvement have been

attributed to different conceptualizations and operational indicators researchers

have applied to the term "Involvement" (Kahle & Homer, 1990).

Antecedents of Involvement

Previous research has examined the construct of consumer involvement

across a variety of marketing contexts (Lai, 1991). Involvement is generally

considered to be a function of three factors: (a) individual characteristics; (b)

situational factors Including purchase situation and the degree of risk perceived

in the purchase; and (c) physical characteristics of the product (Zaichkowsky,

27

1985). Researchers and practitioners tend not to use the term "Involvement"

alone but rather imply a distinction between types of involvement (Laurent &

Kapferer, 1985). The literature reveals involvement can be related to ego,

product, situation, values, brand, interest, and purchase.

Ego involvement happens when an issue or object is connected to a

person's distinctive set of likes or dislikes and their personal value system.

Product involvement refers to the degree in which a certain product class is

important to a person's highly held values or beliefs (Warrington & Shim, 2000).

Two areas of product involvement occur and can be classified as either

situational or enduring. Warrington and Shim (2000) defined situational

involvement as a short-term high degree of Involvement in a certain product

based on the situation in which the product may be purchased. Enduring

involvement reflects a consumer's continuing notice in a product category (Bei &

Widdows, 1999). In theory, enduring and situational involvement is specific to a

consumer's situation or value system (Warrington & Shim, 2000).

Brand commitment Is defined as an emotional or psychological

commitment to a brand (Beatty, Kahle, & Homer, 1988). General levels of

interest with a brand can lead to different levels of involvement. High and low

involvement deals with the importance that consumers place on certain

purchases (Celsl & Olson, 1988). High and low involvement can change over

product classes and among consumers. Therefore, much research has been

done on classifying high and low involvement consumers. Purchase-decision

28

involvement is the degree of involvement or concern that consumers have when

making purchasing decisions (Mittal, 1989).

Generally Involvement researchers agree that for consumers as a group,

products will vary in their ability to arouse involvement (Bloch, 1981). Andrews,

Durvasula, and Akhter (1990) described product involvement as it relates to the

degree of arousal that is generated in the consumer. Three major properties of

arousal were found: Intensity, direction and persistence (Flynn & Goldsmith,

1993). Intensity refers to the person's degree of involvement or motivation.

Levels of involvement range from low to high and vary across product or

situational lines. Direction refers to the object or issue to which a person is

motivated and persistence is defined as the time in which intense Involvement is

found.

In theory, involvement is considered an individual motivating difference

variable and depending on their level of involvement, consumers will differ in the

extensiveness of their purchase decision process (Laurent & Kapferer, 1985). In

this context, Involvement with products has been hypothesized to lead to greater

perception of attribute differences, perception to greater product importance, and

greater commitment to brand choice (Zaichkowsky, 1985). Researchers often

use the resulting behaviors as indicators of the level of involvement. Level of

involvement also has been measured as Independent of the behavior that results

from involvement (Zaichkowsky. 1985).

29

Measures of Involvement

The involvement literature suggests that no single scale (Vaughn, 1980) or

single-item measure of perceived importance (Traylor, 1981) can satisfactorily

describe, explain, or predict involvement. Involvement studies have

demonstrated that consumers differ not only in level of involvement but also in

type of involvement. Therefore, involvement can be classified in terms of

multiple facets, that need to be measured simultaneously to provide a full picture

of the type of involvement of a specific target group (Laurent & Kapferer, 1985).

Previous research has measured consumer involvement with products by

several methods; single and multiple item measures, instruments developed and

tested for one product category, and personal involvement levels (Traylor &

Joseph, 1984; Zaichkowsky, 1986). Involvement measures employed to

products have been composed of semantic differential scales, Likert statements,

and concentric scales, rank-ordering, and rating. These diverse measures pose

several problems for researchers. If conflicting results are obtained, discrepancy

may be due to different measures or to different behaviors. Single-item

measures may not capture the total involvement concept and may have low

reliability. Multiple-Item measures may not have been tested for internal

reliability, stability, or validity.

Involvement researchers have addressed development of standardized,

general, valid, and multiple-item measures of involvement that can be applied

across product categories (Traylor & Joseph, 1984; Laurent & Kapferer, 1985;

30

Zaichkowsky, 1985; Zaichkowsky, 1986). In total over the last 40 years, 23

measures have been developed to assess Involvement. Existing measures

conceptualize involvement in different ways from state of involvement with

products, advertisements, or situations in The Personal Involvement Inventory

(Zaichkowsky, 1985) to the antecedents of product involvement in The Consumer

Involvement Profile (CTP) (Kapferer and Laurent, 1985). Scales were generally

based on a semantic differential or Likert type formats, with the number of items

in instruments ranging from 3 to 33 and scale points ranging from 5 to 7

commonly used In measures (O'Cass, 2000).

Levels of Involvement

A consumer's level of Involvement with an object, situation, or action can

be determined by the level to which one has perceived it to be personally

relevant (Celsl & Olson, 1988). Consumers vary in the degree of Involvement

and effort they put Into shopping (Slama & Taschian, 1985). Such variations are

important to marketers because they effect consumers' reactions to different

marketing strategies. Kassarjian (1985) reported that consumers' connection

with shopping influences buying behavior and that different consumer types can

be Identified based on involvement. Products, themselves also can create high

and low Involvement Inherent to the product (Bloch, 1981). Thus, high and low

product Involvement among consumer groups can create significant market

groups.

31

Among researchers, there is some agreement on what constitutes the

differences between high or low involvement in a certain product category

(Zaichkowsky, 1985). Generally, low involvement consumers are perceived as

having (a) small amount of active Information seeking about brands, (b) small

amount of comparison shopping, (c) perceived similarity among different brands,

and, (d) no partiality for a particular brand (Zaichowsky, 1985). High involvement

consumers have been described as (a) engaging In more complex purchasing

decisions, (b) more brand loyal, (c) more likely to be opinion leaders, and, (d) are

more likely to generate negative cognitive responses to product-related

messages.

High involvement consumers want product information, personal attention,

and customer service (Warrington & Shim, 2000). Additionally, when high

involvement consumers are satisfied, they are more likely to develop store

loyalties (Warrington & Shim, 2000). Marketers can respond successfully to high

Involvement consumers' needs by targeting specific consumer characteristics,

purchase behavior, and product attributes to create and maintain market share.

Potentially, retailers, by segmenting high involvement consumers, can increase

sales and more effectively tailor product assortments and advertising messages.

Apparel Product Involvement Studies

Thomas, Cassill, and Forsythe (1991) using a sample (n=177) of female

apparel consumers from three Southern malls studied (a) if apparel involvement

32

is composed of more than one dimension and, if composed of more than one

dimension, (b) to determine if variation In apparel involvement dimensions is

explained by fiber information sources and demographics. Two involvement

factors emerged from the factor analysis (Dress to Express Personality and

Dress as a Signaling Device). The Dress to Express Personality factor was

defined as purchasing clothing to serve as an expression of a person's

psychological state or personality. The Dress as a Signaling Device factor was

defined as purchasing clothing to serve as a signaling device or means of

communication.

Analysis of covariance (ANCOVA) was used to determine if variation in

apparel involvement dimensions was explained by fiber information sources.

Principal components factor analysis with varimax rotation was used to Identify

dimensions of apparel involvement. Analysis of variance (ANOVA) was used to

test whether there were significant differences between the levels of the

demographic variables (age, education, occupation, income) and apparel

involvement factors (Thomas, Cassill, & Forsythe, 1991).

Results indicated that apparel involvement was multi-dimensional and

variation in apparel Involvement dimensions was partially explained by fiber

information sources. While the Dress to Express Personality factor was not

significantly infiuenced by fiber information sources, the apparel involvement

factor Dress as a Signaling Device was significantly influenced by one marketer-

33

dominated source (media) and one nonmarketer-domlnated source

(Interpersonal) (Thomas, Cassill, & Forsythe, 1991).

Additional analyses found that marketer-dominated sources worked

together to influence one apparel involvement factor. Dress as a Signaling

Device. When clothing served as a signaling device or as a means of

communication, clothing selection was significantly infiuenced by the combination

of various personal sources (retailer/Interpersonal) including sales associates,

family, friends, and reference groups. In addition, the Dress as a Signaling

Device factor was significantly infiuenced by the combined use of advertisements

and personal sources (media/interpersonal), indicating the importance of written

and verbal communication (Thomas, Cassill, & Forsythe, 1991).

Results from ANOVA indicated that there were significant differences

between the levels of three demographic variables (education, occupation.

Income) and one apparel involvement factor; Dress as a Signaling Device. Age

was not significant for this factor, and there were no significant differences

between the levels of the four demographic variables and the Dress to Express

Personality factor (Thomas, Cassill, & Forsythe, 1991).

Haynes, Pipkin, Black, and Cloud (1994) attempted to (a) identify decision

styles (number of stores known, considered, visited) with a sample of pregnant

consumers (n=100) using variables based on their choice set sizes at three

stages of the choice sets model (awareness, consideration, action) and (b) profile

the consumers within each decision style on variables descriptive of each major

34

type of patronage variable. Included in the analysis were consumer

demographics, shopping motivation, shopping process involvement, shopping

orientations (product, brand, price, non-store shopping, planning, time and

product), and desired retailer attributes.

Factor analysis was used to (a) confirm the existence of the proposed

constructs and (b) provide composite measures (factor scores) for use in

subsequent analyses. Six decision styles: narrowers (highest knowledge of

stores), shoppers (have the largest choice sets), apathetics (unlnvolved

shoppers), loyals (low to moderate choice set size), late bloomers (systematically

have larger choice set sizes), and avoiders (extremely low choice sets) were

profiled. The six decision styles were then outlined with a series of shopper and

retailer characteristics, with discriminant analysis used to identify the

differentiating variables from the set of all variables. The descriptive variables

consisted of (a) demographics (age, educational level, total household income),

(b) shopping dimensions (functional, symbolic, and experiential), (c) shopping

process involvement, and (d) career orientation level (Haynes, Pipkin, Black, &

Cloud, 1994).

Results showed that distinct decision styles were identified to reflect

consistent choice patterns through the decision process. The narrowers showed

less interest in the shopping process than other consumer types and consumers

in this group were the most homogeneous. The shoppers consider all retailer

attributes Important at the time to decide which store to patronize. The

35

apathetics, younger consumers. Indicated a high level of product Involvement,

but factors, such as their economic situation and lack of knowledge, may have

impacted their engagement in shopping. The loyals showed more interest in

obtaining high product variety and value for their money. This group indicated

high involvement with limited market participation. The late bloomers placed

more importance on convenience and value for their money when deciding which

store to patronize. Finally, the avoiders, who view shopping as a necessity,

showed low choice sets and low process involvement, due in part to an apparent

lack of time for shopping (Haynes, Pipkin, Black, & Cloud, 1994).

Eckman (1997) explored how male and female consumers (n=168) use

aesthetic attributes in their evaluations of the attractiveness of clothing with

respect to (a) use and relative importance of design elements and (b) effect of

consumer characteristics. To address age and fashion preferences, three years

marking the peak of distinctive fashion trends (1955 "Edwardian Dandy," 1967

"Peacock Revolution," and 1980 "Return of Conservatism") were Identified.

The sample was to be composed of 20 females and 20 males in each of

four age groups: 20 to 24 years of age, 31 to 35, 44 to 48, and 56 to 60. The

older three age groups were selected to include Individuals who were In their

early twenties, the age suggested as the critical period for development of

aesthetic preferences, during peaks of previous distinctive fashion trends. The

youngest group, composed of Individuals 20 to 24 years old at the time of the

study, was chosen to test the aesthetic preferences of young adults and to

36

explore aesthetic preferences that may form when individuals are In their early

twenties. Females were Included In the sample because it is generally believed

that women make or influence purchase of men's clothing (Eckman, 1997).

Current trends in men's suit styles were the basis for levels of the design

elements chosen. Eight design elements and corresponding levels were jacket

silhouette (narrow/wide), jacket length (short/long), drop or distance between

base of the neck and first button (high/low), neckline (without lapel/with lapel),

jacket color (olive/blue) and pant color (olive/blue). Individual subject ANOVAs

identified attributes and interactions that were significant in each subject's

aesthetic evaluations. A 4 (Age) X 2 (Sex) X 3 (Fashion Involvement) X 2

(Design elements) post hoc ANOVA was performed on the dependent variable

(average omega-squared values) to assess the effect of age, sex, and fashion

involvement on the subjects' use of design elements in their aesthetic

evaluations (Eckman, 1997).

Results showed interactions of one design element with six other

elements. The interaction of jacket silhouette and jacket pattern (78 significant

Interactions) affected the evaluations of more subjects than any main effect.

Interaction of jacket silhouette and jacket color (16 significant Interactions) and

jacket silhouette and pant color (12 Interactions) were significant for fewer

subjects. Interactions that influenced the fewest subjects were jacket silhouette

and neckline drop, and pant silhouette. Jacket length showed the most main

effects, followed by jacket pattern, drop, and neckline. Jacket length was the

37

dominant design element. The post hoc ANOVA show the design elements

differed in their effect on aesthetic evaluations. Moreover, the significant two-

way design by age interaction indicated the effect of the design elements differed

by age groups. The post hoc ANOVA also showed the Interaction of age, sex,

and fashion Involvement influenced subjects' use of design elements (Eckman,

1997).

Jin and Koh (1999) (a) proposed a model of clothing brand loyalty

formation considering five brand loyalty-related variables: consumer knowledge,

product involvement, perceived risk, information search, and consumer

satisfaction and (b) examined gender differences in the process of clothing brand

loyalty formation. The sample consisted of Korean male and female (n=505)

consumers. The amount of brand loyalty. Information search, and consumer

satisfaction were proposed to be influenced by the degree of consumers'

involvement with and knowledge about clothing, and perceived risk during

purchasing. Thus, brand loyalty, information search, and consumer satisfaction

were considered dependent variables and consumer knowledge, product

involvement, and perceived risk were considered independent variables.

Principal component factor analysis with varimax rotation was performed

on items relating to brand loyalty, consumer satisfaction, information search,

product involvement, consumer knowledge, and demographics. Results

indicated that the greater the consumer's knowledge and product involvement,

the greater the Information search. Also, the greater the consumer's product

38

involvement, customer satisfaction, and consumer's Information search, the

greater the brand loyalty. However, the greater the consumer's perceived risk

did not increase the information search (Jin & Koh, 1999).

Significant differences were found In the formation process of clothing

brand loyalty according to gender. The major difference between the females

and males was that the most influential variable in information search was

perceived risk for men, whereas product involvement was the most influential

variable for women. Overall, the results supported the proposed model as,

clothing brand loyalty formation developed along four paths: (1) Consumer

knowledge -^ Information search -^ brand loyalty, (2) Product involvement -^

infonnation search -> brand loyalty, (3) Perceived risk -^ Information search -^

brand loyalty, and (4) Product Involvement -^ consumer satisfaction -^ brand

loyalty. Therefore, it was concluded that brand loyalty was developed directly

from information search and consumer satisfaction. Consumer knowledge,

product Involvement, and perceived risk Indirectly influenced brand loyalty

through mediating variables of information search and consumer satisfaction (Jin

&Koh, 1999).

Warrington and Shim (2000) hypothesized that (a) product involvement

and brand commitment may not be highly correlated and if so, (b) product

involvement and brand commitment will differentiate a product category market

into four distinct consumer groups: high product involvement/strong brand

commitment (HP/SB), high product involvement/weak brand commitment

39

(HPAA/B), low product involvement/strong brand commitment (LP/SB), low

product involvement/weak brand commitment (LP/WB). Given the classification

model proved to be successful with the college student sample (n=615), it was

further postulated the four groups would display different consumption attitudes

or behavior for a specific clothing product category, jeans.

A Pearson correlation test performed between product Involvement and

brand commitment showed that the correlation between the two was not

significant. Respondents were classified by an examination of means and

standard deviations of the two constructs. ANOVA tests indicated that high-

product-involvement group differed significantly from the low-product-involvement

group and that strong-brand-commitment group differed from the weak-brand-

commitment group. ANCOVA revealed that the four involvement groups were

significantly different on three of the five factors; high price orientation, brand

consciousness, and fashion consciousness (Warrington & Shim, 2000).

HP/SB consumers were more Interested in both market and personal

sources of information and the importance placed on functional as well as

nonfunctional product attributes. HP/WB consumers significantly differed from

HP/SB on price sensitivity, fashion orientation, and brand consciousness, but

market and personal sources of brand information was Important to both

consumer groups. HP/WB consumers were less concerned with nonfunctional

product attributes. LPl\NB and LP/SB consumers were less likely to engage in

large amounts of decision-making relative to product category. The LP/WB

40

consumers were apathetic while LP/SB consumers tended to be habitual

(Warrington & Shim, 2000).

Product Attributes

Why consumers buy particular products has been an Issue addressed in

empirical and conceptual studies (Vriens & Hofstede, 2000). Market research

often aims at understanding the reasons underlying consumers' product

preferences. Most methods for Investigating product preference assume that

preferences are based on combinations of utilities consumers get from separate

product cues or attributes (Creusen & Schoormans, 1997). Differences in

consumer preferences are thus expected to be related to differences in product

attributes.

Attribute Concept

According to consumer behavior theories, the purchase of a product is

guided by consumers' assessment and evaluation of the attributes defining the

product. Consequently, consumers are infiuenced in product evaluations and

buying decisions by factors such as brand, price, and color. Consumer

researchers are interested not only In which cues are used and the relative

impact of each cue, but also with the ways the cues are combined to arrive at

judgments and choices (Liefeld, Wall, Ji, & Xu, 1993).

41

Eariy studies of consumer decision-making generally examined only one

cue at a time and frequently reported that the cue had considerable influence on

the perceptions of the product (Olson, 1977; Szybillo & Jacoby, 1974; Will &

Hasty, 1971). Researchers have suggested that consumer decision process

studies employing single cues over-estimate the size of the cue effects (ZeithamI,

1988). In multi-attribute studies, researchers have reported that the cue effects

diminish in magnitude when more cues are present in the choice or evaluation

situation (Abraham-Murali & Littrel, 1995a; Liefeld et al., 1993; Sinclair & Stalling,

1990).

Measures of Product Attributes

The majority of studies, which examined the effects of product attributes

on product evaluations and the purchase decision process, have focused on

rating or rankings of product attributes (Liefeld et al., 1993; Tull & Hawkins,

1990). However, the rating and ranking approaches cannot capture consumers'

willingness to compromise. Ranking can provide some measure of trade-offs

between attributes. Also rating and ranking measurements do not effectively

handle attribute levels in order to allow the determination of how much of one

attribute will compensate for a deficiency in another attribute (Liefeld et al.,

1993). The range of attributes is limited to the specific preselected cues included

on the rating and ranking measurement scales (Sinclair & Stalling, 1990).

42

To elicit a wider range of attributes used by consumers In the evaluation

process, researchers have used an open-ended discussion approach for data

collection via quantitative and qualitative research designs (Abraham-Murali &

LIttrell, 1995a). A disadvantage of free response data is that subliminally used

criteria for product evaluation may not be recognized by the naive consumer who

is unaware of the importance of the criteria (Nisbett & Ross, 1980). As with

predetermined lists, social desirability may have some effect if the respondent is

embarrassed to acknowledge Influence of some criteria.

Conjoint analysis was developed as a different measurement approach to

avoid the biases of explicit measurement of attribute importance (Liefeld et al.,

1993). The conjoint approach derives the importance individual consumers

attach to each attribute by observing consumers' preferences for or choices of

various combinations of product attributes and then decomposes these

judgments to estimate the respondent's utilities for each attribute and each level

of each attribute (Aaker & Day, 1990; Green & Tull, 1978; Lehmann, 1989).

Attribute Categories

Several researchers have attempted, through empirical and theoretical

papers, to distinguish among the assortment of product attributes and to propose

conceptual categories for the attributes (Abraham-Murali & LIttrell, 1995a).

Categories have been demonstrated using consumer products In general, a

product type such as clothing, or specific products such as blankets. Categories

43

have been proposed based on the type of attribute (Olson & Jacoby, 1972;

O'Neal, Hines, & Jackson, 1990) or on the relationships among attributes

(Geistfeld, Sproles, & Badenhop, 1977; Swan & Combs, 1976).

From an information theory perspective, a product can be perceived as an

array of cues, that are either intrinsic or extrinsic in nature (Olson & Jacoby,

1972). Intrinsic cues are product attributes, which are intrinsic to the product in

the sense that they cannot be changed or experimentally manipulated without

also changing the physical characteristics of the product. Extrinsic cues are

product attributes, which, while product-related, are not part of the physical

product, but added by retailers and manufacturers. Sweetness of a soft drink,

density of a garment's fiber, color of a gemstone, and sound clarity of a

stereophonic system are examples of Intrinsic attributes, while brand, price, type

of package, and country-of-origin are examples of extrinsic cues (Wheatley,

Chlu, & Goldman, 1981).

Extrinsic cues, when compared to intrinsic cues, are more general and

applicable to a wider range of products, whereas intrinsic cues are specific only

to a particular product (Lee & Yung-Chien, 1995/1996). Hence, it is believed that

consumers are generally more familiar with extrinsic cues than intrinsic cues, and

thus tend to rely more heavily on extrinsic attributes when evaluating products

(Dodds, Monroe, & Grewal, 1991; Han & Terpstra, 1988). Existing literature also

suggests that the extrinsic cue effects are not universal, but moderated by

consumer Individual differences (Lee & Yung-Chien, 1995/1996).

44

Researchers have postulated that, theoretically, intrinsic cues are likely to

have a higher "predictive" value (Cox, 1962; Olson, 1977). Attribute interaction

has been proposed as an Important area for investigation to gain a clearer

understanding of how multiple criteria, both intrinsic and extrinsic, are combined

in the product evaluation and purchase decision process. The majority of recent

attribute-based segmentation studies have utilized both extrinsic and intrinsic

cues.

Apparel Attributes and Stimuli

Previous research related to apparel has used intrinsic and extrinsic

product attributes to investigate overall judgments made by consumers. The

effects of extrinsic cues on overall judgment have been investigated more

frequently than the effects of intrinsic cues (Eckman, Damhorst, & Kadolph,

1990). Among the extrinsic cues, price and brand name have been studies most

extensively, both In isolation and in conjunction with other cues (Davis, 1985;

Forsythe, 1991; Hatch & Roberts, 1985; Lambert, 1972; Norum & Clarke, 1989;

Wheatley & Chlu, 1977). The intrinsic cues most frequently examined include

style, fit, design, fiber content, color, care, and appearance. Intrinsic and

extrinsic cues have been related to perceived usefulness, performance, and

quality (Eckman, Damhorst, & Kadolph, 1990; Flore & Damhorst, 1992; Szybillo

& Jacoby, 1974).

45

Application of a variety of stimuli and methods in the examination of

product attributes has been suggested as desirable to counteract the indigenous

forms of bias associated with any stimuli, measure, and data collection situation.

Stimuli used to assess clothing have included actual products, photographs of

products, illustrations of products, written product category descriptions and,

product names or lists. Attributes have been measured by rating and ranking

scales as well as open-ended questions eliciting free response data. Data

collection generally has been approached via structured in-depth interviews,

discussion guided focus groups, and structured self-administered questionnaires

(Eckman, Damhorst, & Kadolph, 1990).

Apparel Product Attribute Studies

Davis (1987) formulated two studies to investigate the acquisition and use

of objective information by female consumers in making subjective judgments of

clothing quality, judgments of clothing fashionability, and clothing purchase

decisions. A behavioral process approach using decision simulation tasks was

used for both studies to identify how much and just what information consumers

used in making clothing judgments.

In Study 1, female college students (n=65) participated in a "shopping"

task where they were asked to judge the quality of four white blouses and then

state which one they would "buy." In Study 2, female college students (n=55)

participated in a similar "shopping" task situation but they were asked to judge

46

the fashionability of four white blouses and then state which one they would

"buy." For both studies, information about each blouse was presented to the

subjects via an information display board, arranged In a matrix array with four

brands (brands A, B, C, and D) as columns of the matrix and 10 clothing

attributes (care label, department in store, fabric, fit, general construction,

manufacturer neck label, price, salesperson's opinion, store, and style) as rows.

In order to make their judgments, subjects were asked to select the Information

they would need from the information display board (Davis, 1987).

Content analysis of the attributes selected by the subjects revealed that, in

general, subjects in both studies disregarded approximately half of the available

information. On the average subjects selected only five (in Study 1) or six (in

Study 2) of the 10 attributes available for each brand. The two most heavily

accessed attributes in both studies were style and price with fabric, store, and fit

also selected by most subjects (Davis, 1987).

Although all brands were said to be of equally high construction and of

similar styling, brand D, the 100% cotton designer label blouse, was rated

significantly higher In quality and fashionability than the other blouses. However,

fabric and price were more important than quality and fashionability as criteria for

subjects' "purchase decision" (Davis, 1987).

Heisey (1990) determined (a) if consumers perceive quality differences as

a result of the "minimum information environment" (MIE) cues (care

requirements, country of origin, fiber content, and store type/prestige), (b) price

47

differences as a result of MIE cues, and (c) the relationship between perceived

quality and predicted price and any effect of store type/prestige on this

relationship. Female junior and senior Retail and Textiles and Clothing majors,

enrolled in an apparel course at a Midwestern university (n=40) were asked to

evaluate the quality and to estimate the price paid for four identical "fatigue type"

sweaters. Different hypothetical profiles of the MIE cues were attached to the

sweaters and all other labels were removed. Two levels were used for each MIE

cue. The levels for each variable were chosen to represent the extremes of that

variable's range for sweaters on the market at that time.

The sweaters were obtained from mass merchandise and outdoor

specialty stores and catalogs. The name of the stores that offered the lowest-

and highest-priced sweaters were used as the two levels for vendor. The care

procedures used represented the most restrictive and the least restrictive labels

found in the product assortments from which the sweaters were selected. The

fiber content levels used were the two most commonly found on "cotton" type

sweaters. One level for country-of-origIn was domestic, and the other was a high

volume Asian exporter to the U.S (Heisey, 1990).

Differences in perceived price were analyzed using analysis of variance

with subject as the blocking factor. Quality ratings for sweaters that were labeled

100% cotton averaged 14% higher than for sweaters labeled cotton/acrylic;

however, predicted prices for the all cotton sweater averaged only 5.8% higher

than for those bearing the blend label. Predicted prices for sweaters that were

48

labeled as having been purchased from the specialty store averaged 23.4%

higher than those from the mass merchandiser; however the quality ratings for

the same sweater averaged only 6.0% higher than those from the mass

merchandiser. No interactions of care with other MIE cues were significant

(Heisey, 1990).

Significant differences in perceived quality were detected for fiber content

and vendor prestige/type. Differences were detected in perception of quality and

prediction of price related to MIE cues. A direct, positive relationship between

price and quality was found, with store type/prestige and fiber content appearing

to influence predicted price through modifying effects on the perception of quality.

No effects due to the country-of-origin and care procedures could be detected on

either predicted price or perception of quality (Heisey, 1990).

Eckman, Damhorst, and Kadolph (1990) invesfigated the importance of (a)

intrinsic and extrinsic criteria in purchase decisions for women's apparel, and (b)

criteria in both rejecting and accepting garments for purchase. Female

consumers (n=80) were Interviewed at two apparel specialty stores using a

combination of three procedures: (a) free response or open-ended interviews to

obtain descriptions of salient evaluative criteria in consumers' own words, (b)

garments personally selected by the respondents were the product stimuli

evaluated by the respondents, and (c) interviews conducted at polnt-of-purchase

or rejection. Attributes categories related to (a) aesthetic criteria, (b) "usefulness"

49

criteria relating to utilitarian concerns as to how usable the garments would be,

(c) performance and quality criteria, and (d) extrinsic criteria.

Fifty-two of the 80 respondents were purchasers and 28 were non-

purchasers. Overall, intrinsic criteria were used more often than extrinsic criteria

for clothing evaluation. Styling, color/pattern, fit, fabric, appearance, and price, in

that order, were the most frequently mentioned criteria for evaluating specific

garments. Almost 55% of these responses pertained to aesthetic factors. The

70 responses in the performance and quality categories indicated substantial

concern among subjects about performance, especially fit. The total of 30

responses among the usefulness categories Indicated less concern about

selecting garments to make maximum use of the wardrobe. Appropriateness,

utility, uniqueness, brand, and competifion were mentioned so infrequentiy that

these criteria may be of minimal concern to the consumer (Eckman, Damhorst, &

Kadolph, 1990).

Purchasers gave 175 responses; they used 147 responses to describe

what they liked and 28 responses to describe what they did not like about the

garments purchased. The majority of the purchasers' positive responses were in

the color/pattern, styling, fit, fabric, and price categories. Styling, fit, and

workmanship contained 60.7% of the negative responses from purchasers.

However, 29 of the 51 purchasers stated that there was nothing they did not like

about their garments (Eckman, Damhorst, & Kadolph, 1990).

50

Non-purchasers gave 121 responses; they used 76 responses to describe

what they liked and 45 responses to describe what they did not like about the

gamients. Styling, color/pattern, fabric, and comfort categories contained 70.7%

of the positive responses from non-purchasers. A majority of non-purchasers'

negative responses related to the styling, appearance, and fit categories.

For purchasers and non-purchasers, the most often-used category for

descriptions of what purchasers did not like about their garments was styling;

likewise, the most often-used category for descriptions of what non-purchasers

liked and did not like was styling. Many of the negative style comments were

about specific features such as collar length and garment length. Fabric ranked

fourth among criteria mentioned positively by purchasers and third among criteria

liked by non-purchasers. About 30% of these responses included specific

mention of cotton.

Overall, four major types of criteria emerged as important to respondents

(aesthetic, usefulness, performance and quality, and extrinsic criteria). The

aesthetic set of intrinsic criteria included directly observable compositional

characteristics. I.e., the criteria of style, color and pattern, fabric, and

appearance. Visual criteria seemed to have the greatest impact on selection of

garments for trial in the dressing room and subsequent purchase of a garment.

Visual characteristics fulfilled several implicit expectations, such as fashionability

or popularity, aesthetic appeal, and self-expression (Eckman, Damhorst, &

Kadolph, 1990).

51

Both purchasers and non-purchasers mentioned more criteria when

describing what they liked than what they disliked about the garments, probably

because respondents found the garments appealing or they would not have tried

them on. However, overall non-purchasers had proportionately more to say

about the garments (Eckman, Damhorst, & Kadolph, 1990).

Johnson and Workman (1990) investigated whether (a) care instructions

as a separate cue affected perceptions of garment quality, future performance,

estimated retail price, and likelihood of purchase, (b) subjects intended to follow

the recommended care instructions when caring for a garment, and (c) particular

store type Is associated with certain care Instructions. Undergraduate female

students (n=84) received a sketch of a garment along with one of two care

instructions (hand wash and dry flat or professionally dry-clean), recorded their

perceptions of garment quality and price, predicted the garments future

performance, and indicated the likelihood of purchasing the garment.

MANOVA was performed to determine the overall effect of the

independent variable, care Instructions, on the dependent variables (quality,

future performance If care instructions were followed, confldence that the

garment would retain its appearance, likelihood of purchase, and retail price)

(Johnson & Workman, 1990).

Results showed that care instructions did not significantly influence

perceptions of garment quality, retail price, confidence that the garment would

retain its appearance, or likelihood of purchase. However, predictions of the

52

garment's future performance did vary significantly by care instructions.

Instructions to professionally dry-clean resulted in more favorable predictions

about the garment's future performance than did hand wash and dry flat care

instructions (Johnson & Workman, 1990).

Of the 37 subjects who received the care instructions "professionally dry-

clean," 22 indicated that the garment would be sold in specialty stores, and 15 in

department stores. Of the 46 who received the care instructions "hand wash and

dry flat," 25 indicated that the garment would be sold in specialty stores, 19 In

department stores, one in discount stores, and one in an off-price store (Johnson

& Workman, 1990).

Of the 38 subjects that received the care instructions indicating that the

garment should be professionally dry-cleaned; only 17 said this was how they

actually would care for the garment. Five subjects would "hand wash, dry flat,"

seven would "machine wash, dry flat," and one would "machine wash, tumble

dry." In addition, of the 46 who received the "hand wash, dry flat" care

instructions; only 21 indicated they would actually care for the garment as

recommended (Johnson & Workman, 1990).

Subjects did not use care instructions in evaluating garment quality, price,

or likelihood of purchase. These results suggest that care instructions are cues

in which consumers lack confidence or find difficult to evaluate, or that cues do

not have predictive value in evaluations of apparel quality, price, or likelihood or

purchase (Johnson & Workman, 1990).

53

Forsythe (1991) examined (a) the effect of one extrinsic cue (brand name)

and intrinsic cues (actual product characteristics) on evaluations of the quality

and price of private, designer, and national brand products, and (b) the mediating

effect of consumer decision-making style on evaluations of quality and price for

designer and national brand products. A field experiment with shoppers in a

large urban mall (n=164) was used to examine the influence of brand name on

consumers' perceptions of apparel quality and price. Men's shirts were selected

as the stimulus product as a product category with which most consumers are

familiar and because both brand name and actual product characteristics could

be used by consumers In evaluating shirts. National, private, and designer

brands, which had high name recognition among consumers, were chosen for

this study in order to maximize the usefulness of the findings.

Each subject was asked to examine only one of the three shirts and to

rate the shirt examined on five 5-point Items of a bipolar scale measuring

perceptions of fabric quality, quality of notions, construction quality, design

quality, and overall quality. Each scale item has endpoints labeled high and low.

Consumer decision-making style was identified through a two-step process using

the Consumer Styles Inventory measure developed by Sproles and Kendall

(1986) principal components factor analysis Isolated independent measures of

key decision-making constructs from statements regarding shopping attitudes.

Second, cluster analysis was used to group shoppers into either brand or quality

conscious scores (Forsythe, 1991).

54

Results of the ANOVA showed that brand name (the Independent

variable) did not affect perception of garment quality (the dependent variable).

The finding of no significant differences in perceived quality among the three

brands supports the hypothesis that perception of apparel quality will not vary as

a function of brand name when evaluating the actual product. Therefore,

consumers appear to rely primarily on intrinsic cues (actual garment

characteristics) rather than brand name when evaluating the quality of apparel

items. These findings show that actual garment characteristics are more

important than brand name in evaluating garment quality and suggest that the

assumption that consumers associate quality in apparel with brand name may be

erroneous (Forsythe, 1991).

Brand name did appear to influence shoppers' perception of price. The

designer brand was perceived to be signiflcantly more expensive than national

and private brands; however, price perceptions for national and private brands

did not differ. Brand and quality conscious shoppers differed with respect to the

price attributed to the shirts but not the quality. Overall, brand conscious

shoppers attributed significantly higher prices to the shirts than did quality

conscious shoppers (Forsythe, 1991).

Results also showed that brand conscious shoppers perceived private

brand shirts similar to designer brand shirts whereas quality conscious shoppers

perceived private brand shirts to be more like the national brand with respect to

price. Brand conscious shoppers priced the private brand similar to the mean

55

price for designer brands whereas quality conscious shoppers priced the private

brand similar to the mean price for national brands. Thus, consumer decision

making style does appear to be a mediating factor in the perception of apparel

price, but not quality, when both brand name and the actual product are available

for evaluation (Forsythe, 1991).

Brand and quality conscious shoppers did not differ with respect to

gender, shopping frequency, education, martial status income level, type of store

shopped, or purchase of men's shirts within the last two years. Also, brand

conscious shoppers were no more likely than quality conscious shoppers to

indicate that brand was an important criterion in selecting apparel. This suggests

that brand conscious shoppers may be unaware of the importance of brand

name in clothing purchase decisions or they may be reluctant to admit the

Importance of brand to them. Quality conscious shoppers, on the other hand,

rated construction quality as more important than did brand conscious shoppers,

which suggests that quality conscious shoppers are more concerned than brand

conscious shoppers with intrinsic cues such as actual garment characteristics

(Forsythe, 1991).

Hines and O'Neal (1995) evaluated the underlying meaning of attributes

used by female consumers (n=25) to judge clothing quality by the cognitive

structure that exists between the evaluative criteria used to judge quality and

personal values. The means-end chain model provided the framework for the

study. Means-end theory assumes that (a) values play a dominant role in

56

guiding choice patterns, (b) all consumer actions have consequences, and (c)

consumers learn to associate a particular consequence to a particular action.

The "means" are identified as product attributes and the "end" as values

important to the consumer.

Fabric was the only attribute Identified by the majority of the subjects for

evaluating quality. At the inference level, subjects identified motives for selecting

attributes. These motives included expectation concepts and perception of

Image concepts that a high quality garment would create. As a group, subjects

expected the smooth fabric would not pick up lint or pill, would hold its shape,

and be durable. They also thought that fabric helped to create perceived images

of what a quality garment should look like in creating a good overall appearance.

Fabric was also Important for economic reasons. Fabric was perceived to have

had a salient effect on overall appearance and performance of the garment and

therefore, a major influence on evaluation of the quality (Hines & O'Neal, 1995).

Results indicated that consumers judge clothing quality for more than its

economic benefits. Social and psychological benefits were at least equally as

important. Social consequence concepts were mentioned in 77.5% of the chains

and psychological consequences in 78.5%. Consumers identified quality based

on attributes that they evaluated for performance, perceptual image,

workmanship, and expectations of the attributes. The social, psychological,

economic, physiological, and aesthetic consequences of the attributes selected

were factors that influenced use/avoidance of an attribute to evaluative quality.

57

Personal values also affected consequences that the subjects desired or

avoided. The findings indicate high quality garments play an Important role in

how women feel about themselves, how they perceive others to view them, and

how they assess economic value for money spent (Hines & O'Neal, 1995).

Abraham-Murali and LIttrell (1995a) attempted to: (a) generate a

comprehensive list of apparel attributes grounded in consumer vocabulary, (b)

arrange the attributes in conceptual themes and dimensional levels, and (c)

examine the attributes in ways that would be useful to different types of retailers.

Three objectives guided this research. A comprehensive list of apparel attributes

would be useful to researchers who sought to be inclusive of a broad range of

apparel attributes and for those who want to explore, in depth, a smaller group of

related attributes. Unidimensional attributes encompass a single characteristic,

often related to the composition or construction of a product. Multidimensional

attributes are a function of, or result from, two or more unidimensional attributes.

Five focus groups interviews were conducted with female consumers

(n=31) in four midwestern towns. The focus groups were designed in a three-

part format to parallel some of the evaluation process in different types of retail

settings. Four conceptual themes and a comprehensive list of 79 attributes were

developed. Words, phrases, and sentences used by the participants to describe

an experience, observation, or opinion about a clothing attribute that influenced

their clothing purchase decisions were regarded as units of data (Abraham-

Murali & Littrell, 1995a).

58

A coding guide was prepared by grouping similar attributes into broad

themes that would best describe them. Categories were Identified to make finer

distinctions within the themes. Data was content analyzed independently by two

trained judges. Percentages for each of the three parts of the discussion were

computed by dividing the number of units of data corresponding to a category of

attributes in a specific part of the discussion by the total number of units of

analysis in that part of the discussion (Abraham-Murali & LIttrell, 1995a).

Results showed that the attributes represented a multiplicity of product

characteristics that play a role in product choice and evaluation. Responses

were consistent in that four common themes (physical appearance (37%),

physical performance (24%), expressive (20%), and extrinsic (19%) emerged

across the five interviews. The four common themes were composed of

unidimensional and multidimensional attributes which were intrinsic and extrinsic

in nature. The 79 apparel attributes included concrete, tangible features of

clothing such as dress length, color, and fabric structure, as well as abstract and

Intangible attributes such as durability and whether the garment looked good on

the wearer (Abraham-Murali & Littrell, 1995a).

In addition, results showed that consumers are able to distinguish

between the physical appearance of the product and its instrumental and

expressive functions. Both unidimensional and multidimensional attributes were

used In cognitive processing of clothing attributes. The unidimensional attributes

are combined to form a prediction of, or inferences about, multidimensional

59

attributes. Both types of attributes appear to be important to consumers In

decision-making (Abraham-Murali & Littrell, 1995a).

Abraham-Murali and Littrell (1995b) researched apparel quality to: (a)

identify conceptual dimensions among a large set of apparel attributes at

expectation and post-purchase evaluation stages, and (b) ascertain how these

conceptual dimensions and other variables, such as patronage benefits,

demographics, and years of experience shopping with an mail-order company,

explained variance in perceptions of overall quality at the two evaluation stages,

and (c) propose a model for consumers' perceptions of apparel quality. Female

consumers (n=300) who had placed orders for one of three dresses from Land's

End, Inc. formed the sample for the study.

The data was analyzed in three stages. The first stage involved using t-

tests to assess whether there were differences in the responses between

consumers who had filled out the purchase questionnaire before receiving the

garment and those who had completed It after receiving the garment. Analysis

indicated no significant differences between the two groups (Abraham-Murali &

LIttrell, 1995b).

In the second stage, the expectation, post-purchase evaluation, and

perceived patronage benefit measures were analyzed using principal component

analysis. The expectation measure was consumers' responses to 61 attributes

in the purchase questionnaire. Consumers' responses to the same 61 attributes

in the post-purchase questionnaire were the post-purchase evaluation measure.

60

The benefit measure included 26 pre-purchase criteria that are related to

consumers' decisions to buy. In the final stage of data analysis, regression

models were used to Identify the "best" estimators of overall quality at the

expectation and post-purchase stages (Abraham-Murali & Littrell, 1995b).

Results showed that consumers' conceptualization of garments' quality

changes over time as a garment is purchased and used. In the expectation

analysis, 29 items factored into four factors (Care, Value, Style, and Product and

Services) but in the post-purchase evaluation analysis 39 items were Included

into four factors (Fabric, Care, Expressive, and Individuality). After using the

actual product the respondents' conceptualization included more attributes.

Through actual usage consumers became more informed about the garment and

the importance of attributes may have become clearer. More multidimensional

attributes emerged in the factors after consumers used the product than before

consumers had actual access to the dress (Abraham-Murali & Littrell, 1995b).

Findings also showed some difference in perception or salient factors of

quality at the two stages. In the expectation stage. Fabric and Garment

Construction were useful In predicting quality. The factors containing care items

emerged as important dimensions of quality at both expectation and post-

purchase evaluation stages. Appearance on the Body, Individuality and

Expression, Expressive, and Individuality factors did not contribute to

assessment of quality at either stage of evaluation (Abraham-Murali & Littrell,

1995b).

61

Actual garments were evaluated at two points in time, at the expectation

stage and at the post-purchase evaluation stage. Consumers' conceptualization

of Fabric, Care, and Individuality became more focused; however, the Expressive

factor broadened in meaning. Consumers seemed to need experience with the

product to completely conceptualize some complex, mullticomponent attributes

that are important and meaningful to them (Abraham-Murali & Littrell, 1995b).

Beaudoln, Moore, and Goldsmith (2000) investigated if fashion leaders

(n=72) and fashion followers (n=569) differed (a) in the importance they give to

12 selected apparel attributes (good fit, durability, ease of care, good price,

comfort, quality, color, attractiveness, fashlonableness, brand name,

appropriateness for occasion, and choice of style), and (b) in attitudes toward

buying domestic and imported apparel. A random list of 3000 women living in

Florida purchased from a commercial mailing list comprised the population for

the study. FIshbein's (1967) attitude model was used as the conceptual

framework. The model was used to measure attitudes toward buying domestic

and imported apparel. The questionnaire had three sections: the construct of

fashion leadership, attitudes toward buying domestic and Imported apparel

products, and apparel behavior and demographic questions. Goldsmith and

Hofacker's (1991) Domain Specific Innovativeness Scale (DSI) was used to

measure the construct of fashion leadership.

Results indicated that fashion leaders accorded more importance than

fashion followers to six of the 12 apparel attributes: color, attractiveness.

62

fashlonableness, brand name, appropriateness for occasion, and choice of

styles. These six attributes are associated with the image, the symbolic, the

glamorous, and the extrinsic aspects of the product. In contrast, the six other

attributes are associated with the intrinsic aspects and the "functional aspects" of

apparel (Beaudoln, Moore, & Goldsmith, 2000).

Fashion leaders and followers had a significantly more positive attitude

toward domestic apparel than toward imported products. However, among

fashion leaders, domestic and imported apparel were not significantly related to

the image or symbolic aspects of clothing. Therefore, more favorable attitudes of

leaders toward domestic apparel were associated with the functional aspects of

apparel. Fashion leaders gave significantly higher evaluafions than followers for

imported apparel on 8 of the 12 apparel attributes: good fit, quality, color,

attractiveness, fashlonableness, brand name, appropriateness for occasion, and

choice of styles. Although fashion leaders gave higher evaluations than followers

to the other four attributes (durability, ease of care, good price, and comfort),

differences were not large enough to be significant. However, both groups gave

a clear advantage to domestic made apparel, regarding durability, ease of care,

good price, and comfort, over imported apparel (Beaudoln, Moore, & Goldsmith,

2000).

No difference was found between the two groups regarding attributes

associated with the functional aspects of apparel. Considering that fashion

leaders are impulsive buyers, attributes such as color, fashlonableness, or

63

attractiveness may represent more determinant buying factors in the retail store.

Given the positive evaluation given by fashion followers toward domestic apparel

over imports, followers may be affected by social desirability when asked to

evaluate domestic versus imported apparel (Beaudoln, Moore, & Goldsmith,

2000).

Leather Footwear Industry

The leather footwear industry has continued to grow and maintain market

share even though new materials are being developed for footwear. However,

thoughts on how the footwear market will evolve are split. Some believe that

footwear is a global market that can be standardized, perpetuating mass

production of high volume uniform styling (Charlesworth, 2001). Others see

different countries and markets having their own specific needs, encouraging a

move away from volume production (Chariesworth, 2001). In either view, future

success in the footwear industry will depend on efficient global resourcing to

ensure that the right quantities of shoes in the right sizes are in the right retailers

at the right time ("Development In Footwear," 2000).

Leather Products Industry Structure

The leather industry consists of three stages; production of raw materials,

transformation of the raw materials into various types of leather, and the

manufacture of finished products. Links between the three stages are rather

64

unique in comparison with other manufacturing Industries. Hides and skins are a

by-product of the much larger meat and wool industries. Leather tanners and

finishers are the sole market for the raw materials, and the entirety of the off-take

is converted into leather

The leather industry produces about 18 billion square feet of leather per

year, and the total value is estimated at about $40 billion ("Perspective on

Leather," 2000). Price of the raw materials Is of overriding concern for users

although the supply is determined by conditions outside the leather Industry.

Hide and skin supply has increased by an average of only 1.5% annually in

recent decades ("The Up Down," 2001). Real pressure on cattle hide availability

in the US comes from export activity. Developing countries now produce over

60% of the world's leather, and this proportion Is growing ("Perspective on

Leather," 2000). Generally, leather demand exceeds supply and experts do not

believe this is likely to change ("The Up Down," 2001).

Leather Footwear Industn/ Overview

The leather footwear sector is a major part of the leather and leather

products industry, which is defined to include all aspects of tanning and finishing

as well as the production of finished products made from leather (Ballance,

Robyn, & Forstner, 1993). About 65% of the worid's production of leather is

estimated to go into leather footwear. Leather footwear as defined by shoes with

leather uppers Is estimated to account for 43% of total worid production. This

65

accounts for nearly 5000 million pairs of leather shoes consuming well over 11

billion square feet of upper leather including linings ("Global Shoemaking Grows,"

2001). Global production of footwear is estimated at around 11.8 billion pairs

(worth an estimated $150 billion at wholesale) ("Look of Leather," 2001) showing

an increase of 4.1% compared with previous annual increases of .03 In 1998,

5.0% in 1997, and 5.3% In 1996 ("Global Shoemaking Grows," 2001).

Overall, the global footwear market has remained static throughout the

90s, despite variations in production by region ("Worid Leather Markets," 1998).

However, new countries are now rising to prominence as shoemakers have

largely moved to Asia ("Global Shoemaking Grows," 2001). Production In Asia

continues to grow, increasing by 600 million pairs per year to bring its share of

worid production to 73.9%. China has contributed 400 million pairs towards this

increase and remains the dominant country in the footwear industry with a 51.4%

share of global production. The next largest producer is India at an estimated

700 million pairs followed by Indonesia and Brazil ("Global Shoemaking Grows,"

2001).

Legislation is forcing shoe companies to modify how products are made,

what they are made from, and how they can be recycled ("Components Go

Ecological," 2001). Significant steps have been made in the global leather

industry with regard to environmental issues. The bought-in items that have the

most significant impact on the environment are hides and skins and the leather

processing chemicals ("Components Go Ecological," 2001). Materials

66

development research Is addressing environmental concerns. Overall, chemical

and water use has been reduced In the manufacturing stages and a high level of

quality control ensures that the best use is made of hides and skins and the

chemicals required in their conversion into leather ("Perspective on Leather,"

2000). Product design and different material choices that address environmental

sustainability and product life cycle have become important alternatives to the

leather shoe industry and are now being explored by manufacturing companies.

Domestic Footwear Market

An increasing proportion of footwear is being manufactured in developing

countries, leading to greater global movement of finished products (Buirski,

1999). More exporters, offering merchandise at cheaper prices has had a

significant impact on the domestic market in terms of sheer volume ("Footwear

Market Grows," 2000). According to the Leather Industries of America (U.S.

Leather Industry Statistics, 2000), China currently accounts for nearly 984 million

pairs of shoes being imported to the U.S., ten times the volume of any other

importing country accounting for over 50% of U.S. footwear consumpfion

("Footwear Market Grows," 2000).

In the early 1980s, the U.S. was still manufacturing over 400 million pairs

of shoes a year. By 1986, and through the end of the decade, production was

fluctuating around the 300 million mark and the industry employed around 90,000

people. Exports started climbing strongly, rising from under 10 million pairs in

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1984 to over 16 million pairs In 1989. Production again took a downturn in 1994

to 243 million pairs and exports had more than doubled to over 34 million pairs.

By 1998, production had further decreased to 165 million pairs while exports

flattened out at around 34 million pairs ("Footwear Market Grows," 2000). The

Shoe and Allied Trades Research Association (SATRA) has forecasted that U.S.

footwear production will continue to fall, dropping to 122 million pairs by 2005

(Buirski, 1999).

No footwear market in the world compares to the U.S. in size, value, and

variety with an apparent consumption of some 1600 million pairs of shoes

annually. Nevertheless, in the last two decades, domestic shoemaking has

declined ("Footwear Market Grows," 2000). Pressure from importers combined

with the free trade opportunities created by NAFTA for Mexico have increased

imports to 93% of the total domestic market, forcing U.S. manufacturers to locate

manufacturing offshore, seek new export opportunities, and serve niche markets

as the best route to their continuing survival ("Footwear Market Grows," 2000).

Many U.S. shoe companies have moved to specifiers, controlling design,

materials, quality, and marketing to maintain market share and profitability

("Footwear Market Grows," 2000).

Footwear Market Trends

Footwear is much more than simply a functional item to keep the feet

warm and dry. Footwear Is part of a person's overall attire and appearance and

68

is perceived by the wearer to refiect their individuality and status ("Growth of

Branding," 2001). Shoes are essentially a fashion item subjected to periods of

fluctuating demand throughout the year ("The Up Down," 2001). Success with

product development is directly proportional to understanding current and future

product and consumer trends.

Currently, consumer confidence is at an eight year low and the footwear

industry is predicted to be flat in 2002 (Boettge, 2002). In the present

manufacturer to retailer supply chain, if a shoe sells well and the retailer cannot

secure a quick repeat order sales are lost. Equally, if the shoe does not sell well,

its price is reduced and again profit is lost (Charlesworth, 2001). Trends in color

from companies that produce dyes for tanners. Information on new shoe

components, and styling are Important for the leather shoe industry in developing

potentially profitable commercial products (McCallin, 1995).

Other factors that now affect the footwear industry are: extension of

branding in clothing to footwear, less footwear sold through specialty footwear

retailers, growth In home shopping though catalogs and the Internet, availability

of custom-made footwear, 3D visualization of footwear, less stock being carried

at retail, and intensified gathering of data on shopping habits through loyalty and

similar product differentiations techniques ("Best Footwear Fon /ard," 2000).

Emerging trends Important to retailers are: lower per capita consumption due to

longer lasting footwear, an aging population, less formal dress, and consumer

demand for value for money goods (Buirski, 1999).

69

The aging population, will have a significant effect on the types and

ranges of footwear products sold because of an increased demand for footwear

with greater fit tolerance and comfort (Buirski, 1999). Consumers also will want

more quality products and guarantees of workmanship when purchasing

footwear. The recent rise of the Internet has created different ways in which

footwear companies are meeting consumer needs. E-business varies from

traditional retail stores by allowing the business to become 'customer-centric' as

opposed to 'product-centric' (Smart, 2001). Instead of focusing on the production

of a range of products or services and then offering them to customers, the

company focuses on a partnership with customers to identify their needs and

then provide specialized products (Smart, 2001).

Mass customization in which the customer plays an active role in the

design of products and services now is being marketed on the Internet and in

retail stores (Martin, 1997). Mass customization Is a hybrid technique by which a

company produces mass merchandise yet can add unique features to individual

orders (Martin, 1997). Customers can mix and match design components such

as style, color, texture, sole options, and leather type. For example, the Custom

Foot Company has 10,000 variations available in women shoes alone. This

merchandising strategy provides consumers the option to customize footwear

without the expense of handmade shoes.

U.S. shoemakers and apparel manufacturers are now working together in

brand extension and diversification (Buirski, 1999). Branding is an important

70

aspect in the success of shoe companies branching into apparel production,

sports footwear manufacturers diversifying into other footwear classifications,

and apparel manufacturers expanding Into footwear production. In turn,

consumers like the ability to buy a full product package from a brand. For

example, Fila actually started as an apparel company and U.S. shoe sales

accounted for 40% of Fila's 1.2 billion sales in 1995 (Henricks, 1997).

Overall, how the footwear market will continue to develop is open for

debate. Consumers are still likely to buy shoes but lower per capita spending is

foreseen. The needs of the shoe manufacturer and the shoe retailer based on

future consumer trends are different. The manufacturer needs long production

runs and uncomplicated styling to maximize profits and the retailer needs low

volume supplies, a variety of styles, and quick restocking (Charlesworth, 2001).

Summary of Review of Literature

The U.S. footwear industry is facing many challenges with the decline of

domestic footwear production and the progressive movement to foreign

manufacturing. For example, China currently accounts for nearly 984 million

pairs of shoes being imported to the US ("Global Shoemaking Grows," 2001).

The future growth and prosperity of the footwear market will depend, in part, on

how accurately the target market is defined and on the development of product

assortments based on distinct purchase behavior. Segmentation based on

71

consumers' product involvement and their perceptions of product attributes can

contribute to successful targeting of specific profitable markets.

In order for segmentation to be successful, the market must be described

in measurable terms, be accessible, be divided into homogeneous groups, and

be potentially profitable (Cross, 1999). By segmenting the market, companies

can determine the best marketing mix or products needed to target particular

consumers (Sauerman, 1988). Current changes affecting marketers such as,

micro marketing segmentation, global market segmentation, direct marketing

segmentation, retail segmentafion, geodemographic segmentation, segmentation

for optimizing service quality, segmentation for customer satisfaction evaluafion,

segmentation for new product development, segmentation using single-source

data, and so on (Wedel & Kamakura, 1998; Myers, 1996; Wensley. 1995;

Weinstein, 1994) will all impact footwear retailers and manufacturers. An

effective segmentation program based on product Involvement and product

attributes will help analyze markets, find unique opportunities, and increase

market share (Cross, 1999).

Consumer behavior has been explained in part by the theory of consumer

involvement (Thomas, Cassill, & Forsythe, 1991). Customers will differ in the

extensiveness of their purchase decision process (Laurent & Kapferer, 1985) and

researchers agree that the study of Involvement is important to explaining and

predicting their behavior. Consequently, product involvement can lead to a

greater perception of attribute differences, product importance, and brand

72

commitment (Zaichkowsky, 1985). Variations In consumers' level of involvement

are important to marketers because they effect consumers' reactions to different

marketing strategies. Therefore, high and low Involvement with a product can

create significant market segments.

Differences in consumer preferences can be explained in part by

differences in product attributes. Why consumers buy particular products has

been an issue addressed in empirical and conceptual studies (Vriens & Hofstede,

2000). Previous research related to apparel has used intrinsic and extrinsic

product attributes to investigate overall judgments made by consumers.

The leather footwear industry has continued to grow and maintain market

share. However, the future profitability of the footwear industry depends in part

on how well marketers can continue to provide consumers with the right mix of

products and effectively target consumers based on their footwear preferences.

Segmentation based on product Involvement and product attributes can become

an effective tool to this end.

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CHAPTER III

METHODOLOGY

The purpose of this study was to determine If High Involvement (HI)

consumers and Low Involvement (LI) consumers differed in their purchase of

leather dress shoes for business wear by (a) Identifying group membership of HI

and LI on footwear purchase criteria and footwear characteristics and (b) building

guidelines to classify HI and LI on their purchase behavior regarding leather

dress shoes for business wear. Specific objectives focused on (a) identifying

predictor (I.e., independent) variables from footwear purchase criteria and

footwear characteristics using AnswerTree® to create decision trees, (b)

identifying nodes from decision trees having the highest proportion of HI and LI

consumers (i.e., HI and LI that are most likely to purchase leather dress shoes

for business wear), (c) calculating percentage of HI and LI consumers that

leather dress shoe retailers can reach by targeting a certain percentage of the

market, and (d) identifying HI and LI consumer characteristics in regard to their

ratings of footwear purchase criteria and footwear characteristics.

Conceptual Framework

The conceptual framework underlying this research is the relationship

between product involvement and product attributes that impact consumer

74

purchase behavior. Consumer involvement is defined as a person's perceived

relevance of a product or service based on inherent needs, values, and interests

(Zaichkowsky, 1985). Engel, Blackwell, and MIniard (1986) stated that clothing

was one of a few high involvement products, because clothing is perceived as

refiecting on one's self-image, clothing Is costly, the risks of a wrong decision are

high, and/or when the act of purchase or consumption takes place. It is of high

personal importance or relevance to the decision maker. However, the level and

risks may vary with the type of clothing. Consumer involvement with a particular

product is important because different levels of Involvement may lead to different

perceptions of attributes and to different choices (Howard & Sheth, 1969).

A basic premise underlying consumer behavior is that when making

purchase and consumption decisions, consumers search for product information

in order to discriminate between comparable products and make efficient

decisions (Assael, 1984; Bloch, 1981). The information-processing paradigm

suggests that in evaluating products, consumers seek and process Information

about alternative products and multiple product attributes (Anderson, 1981;

Chaiken, 1980). In turn, product characteristics, including intrinsic and extrinsic

attributes, are cues used by the consumer to develop perceptions of a product

and have an influence on the purchase decision and consumption process

(Baugh & Davis, 1989; Forsythe, 1988; Huddleston, Cassill, & Hamilton, 1993).

75

The concept of involvement appeared to be useful to segment consumers

by the degree and level of product involvement and then to investigate product

attributes used in the evaluation of a product that might result from different

levels of involvement. Based on the purpose of the study and the review of

literature, the following research questions were asked:

RQ1. Can HI and LI consumers be grouped by their assessment of the footwear

purchase criteria and footwear characteristics of leather dress shoes for

business wear?

RQ2. Can HI and LI consumers be classifled on their leather footwear purchase

behavior, thus benefiting the retailer selling leather shoes to HI and LI

consumers in footwear purchase criteria and footwear characteristics?

The procedure that was followed is divided into the following sections: (a)

Selection of the Sample, (b) Research Instrument, (c) Collection of the Data, (d)

Variables of the Study, and (e) Statistical Analysis of Data.

Selection of the Sample

The target population for this study was employed female and male

consumers from the entire U.S. who wear leather dress shoes to work at least

one day a week. A national cross-section of 1,000 female and 1,000 male

consumers was drawn for the study sample. National Demographics & Lifestyles

Inc. (NDL) selected subjects through a random sampling technique using a

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752,357 female database and a 3,327,143 male database. All subjects had an

equal and independent chance of being selected for the sample. NDL complies

a list of consumer names from purchasers of a variety of retail products via a

questionnaire composed of demographic and life style Interest area items.

Research Instrument

Development of the Questionnaire

A questionnaire was utilized for data collection. The instrument was

designed to elicit responses from females and males age 25 to 65 years in the

U.S. who wear leather dress shoes to work at least one day a week. A self-

administered mail questionnaire was constructed regarding the respondent's (a)

footwear opinion leadership, (b) preferences regarding footwear worn for

business wear, (c) favorite and purchased footwear brands, (d) stores shopped

for footwear, (e) footwear Involvement, (f) footwear purchase criteria, (g)

footwear consumption patterns, (h) footwear characteristics, and (i)

soclodemographic characteristics.

Information elicited in Items related to footwear: preferences, purchase

criteria, consumption patterns, and characteristics were Identified from a review

of related literature (Davis, 1985; Eckman, et al., 1990; Fiore & Damhorst, 1992;

Forsythe, 1991; HIavaty, Harp, & Horridge, 1997) and a series of focus group

interviews (Harp, Moore, & Horridge, 2001). The literature examined attributes

77

used in the information search and purchase decision for clothing. The focus

group discussions centered on attributes that influenced consumers' purchase

and satisfaction with leather dress shoes worn for business activities.

Footwear opinion leadership was measured with Items that focused on a

person's desire to own clothing of the latest style and the situation-specific

relevance of an object to a person that were adapted from previous instruments

(Hawes & Lumpkin, 1984; Salma & Taschian, 1987). Measures adopted from

Hawes and Lumpkin's study had internal consistency (Cronbach alpha of .60)

and adequate discriminant validity. Measures adopted from Slama and

Tashchian's study had internal consistency (Cronbach alpha of .61) and

adequate discriminant validity.

Footwear involvement was measured with items that focused on a

person's perceived importance/risk of a product, symbolic value, hedonic value,

and interest with a product that were adapted from previous instruments (Jain &

Srinivassan, 1990; Laurent & Kapferer, 1985). Measures adopted from Laurent

and Kapferer's study had internal consistency (Cronbach alphas ranging from

.72 to .90) and good discriminant validity. Measures adopted from Jain and

Srinivassan's study had internal consistency (Cronbach alphas ranging from .72

to .82) and good discriminant validity. The questionnaire was pretested with a

convenience sample of 30 consumers, 15 females and 15 males who were not

78

members of the focus groups or final sample drawn for the study, then refined

based on the findings and suggestions of the pretest group.

Description of the Questionnaire

The first section of the questionnaire elicited information regarding

footwear and apparel opinion leadership. Seven statements In Q-01 regarding

footwear opinion leadership were rated on a 5-polnt Likert scale (5=strongly

agree to 1=strongly disagree). The questions included; try new fashion ideas

before my coworkers, important that the clothes worn to work are the latest style,

try new and different places to shop for clothing, first to visit a new store opening,

and Importance of quality, fashion styling, and comfort in leather dress shoes.

The second part of the questionnaire elicited information designed to

determine the preferences about shoes for business wear. This section included

questions regarding: Q-02, how often leather shoes are worn to work, Q-03,

amount paid for leather dress shoes worn to work on sale and at regular price,

Q-04, number of leather dress shoes purchased at retail stores and catalogs in

the past two years (part a), and level of satisfaction (1=very satisfied to 6=very

dissatisfied) with selections from retail stores and catalogs (part b), Q-05, favorite

brand of leather dress shoes (part a), and if yes, identify brand names (i.e., from

list of 14 brands and an of/?ercategory) (part b), Q-06, which brand of leather

dress shoes purchased for business wear, Q-07, where most often shopped for

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leather dress shoes, Q-08, where leather footwear for business are most often

purchased, Q-09, purchasing criteria for leather dress shoes, Q-10, foot health,

Q-11, shoe size, Q-12, part of foot difficult to fit, and Q-13, evaluative

characteristics to determine leather dress shoe quality when purchasing.

The next section of the questionnaire was designed to elicit information

concerning footwear Involvement. Sixteen statements (Q-14) were rated on a 7-

polnt LIkert-like scale from 7=strongly agree to 1=strongly disagree. These 16

statements included the following items: (a) shoes for work are important, (b)

how important it is to wear shoes purchased for work, (c) tell a lot about persons

from shoe selection, (d) Interest In shoes worn for work, (e) problem with shoes

inappropriate for work, (f) shoes purchased for work not performing, (g) shoes for

work compatible with opinion of coworkers, (h) difficult to make a bad choice on

purchase of work shoes, (1) shoes express my personality, (j) uncertain of shoes

purchased for work, (k) shoes chosen for work carefully, (I) do not like type of

shoes purchased for work, (m) shoes purchased for work enjoyed the most, (n)

shoes worn to work matter, (o) shoes worn to work compatible with opinion of

self, and (p) purchasing shoes for work complicated.

Purchase criteria for footwear were obtained from Q-15. The question

included 19 product attributes, 10 extrinsic and 9 intrinsic. Each was assessed

on a 7-point LIkert-like scale ranging from 7=very Important to 1=not important.

Extrinsic product attributes included brand, latest fashion, style, price.

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attractiveness, country-of-origin, versatility, size, shoes in wardrobe, and retail

store or catalog. Intrinsic product attributes Included color, construction, hand-of

leather, quality, comfort, fabrication, fit, durability, and ease-of-care.

Consumption patterns for footwear were obtained in Q-16. Consumption

patterns were determined from a 7-point semantic differential summated rating

scale anchoring six bipolar scenarios composed of two extrinsic and four intrinsic

product attributes. The extrinsic product attributes were number of shoes in

wardrobe and price. The intrinsic product attributes were color and style, quality,

comfort versus attractiveness, and durability versus versatility.

Footwear characteristics were obtained in Q-17. Seventeen semantic

differential items anchoring 7-place response formats were based on a person's

feelings about the pair of leather dress shoes that were worn most often to work.

The extrinsic product attributes were fashion, contemporary versus traditional,

price, attractiveness, versatility, and brand. The intrinsic product attributes were

conservative versus casual, comfort, color, quality, breathabllity, care, natural

leather, touch, construction, durability, and fit.

The last section of the questionnaire was designed to elicit information on

personal characteristics. These 15 questions (Q-01 through Q-15) included the

following items: (a) family size, (b) number of children, (c) current employment of

adults in the home, (d) martial status, (e) gender, (f) age, (g) education, (h)

present employment status, (1) occupational category, (j) employment orientation,

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(k) length of time since last worked, (I) geographic region, (m) city size, (n) ethnic

background, and (o) income.

The questionnaire was formatted Into a booklet. The folded document

contained nine sections reproduced on white paper by a photocopy method that

provided quality close to the original typed copy. Procedures for proper ordering

of the questions and formulating of the pages were followed as per Salant and

Dillman (1994). The questionnaire included a front cover that explained the

questionnaire, confidentiality, and information about the U.S. savings bond entry.

A copy of the questionnaire may be found in Appendix A.

Collection of the Data

The research data were collected using the Total Design Method (Salant

& Dillman, 1994) for implementing mail surveys. A self-administered

questionnaire was mailed to randomly selected representatives of females and

males In the U.S. During the summer of 1998, 2,000 questionnaires were sent to

1,000 females and 1,000 males. Participation was voluntary and respondents

were Informed of the confidentiality of the investigation and rights as human

subjects.

In order to prompt the response and Increase the return rate, respondents

were informed of a drawing for one of two $100 U.S. saving bonds for

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participants who returned a completed questionnaire. See Appendix B for a

copy of the entry form.

A complete Implementation theme was followed for collection of the

research data. Correspondence was personalized, and all questionnaires were

numbered so that non-respondent, follow-up procedures could be efficienfly and

economically implemented. A preliminary postcard was mailed to Inform

subjects of the forthcoming questionnaire, research purpose, and to request

participation. See Appendix C for the preliminary postcard. The initial mailing;

including the questionnaire with a front cover Introducing the project and

instructions, savings bond entry form, and business reply envelope, was

executed one week after the preliminary postcard was sent. Twelve days after

the initial mailing, a follow-up postcard was sent to all non-respondents from the

first mailing. See Appendix D for the follow-up postcard. A second mailing

consisting of a front cover, questionnaire, and return envelope was mailed to ail

non-respondents three weeks after the initial mailing. Eight weeks after initiating

data collection, 245 questionnaires, 139 female and 116 male, were processed,

data tabulated, and subjected to statistical analysis.

Variables of the Study

The variables of the study were as follows:

1. Footwear opinion leadership data were summated by a

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response to Q-01 of the questionnaire. Footwear opinion leadership was

analyzed to determine the level of leadership. Subjects responded to a 5-

point Likert scale ranging from strongly agree (5) to strongly disagree (1),

with a mid-point of Indifferent (3). Opinion leadership was treated as a

continuous variable.

2. Footwear preferences were measured by responses to Q-02 through

Q -13 in Section 2 of the questionnaire. Shopping preference data of the

respondents were analyzed to determine shopping preferences toward leather

dress shoes for business wear.

3. Footwear Involvement was measured by response to Q-14 in Section

3 using a Likert-like scale. Involvement data were analyzed to determine beliefs

and attitudes of participants regarding shoes for business wear. Subjects

responded to a 7-point Likert-type scale ranging from strongly agree (7) to

strongly disagree (1), with a mid-point of indifferent (4). Footwear Involvement

was treated as a continuous variable.

4. Purchase criteria were measured by responses to Q-15 in Section 4 of

the questionnaire. Purchase criteria were product specific: leather dress shoes

for business wear. Data were analyzed to determine the importance of product

attributes in the purchase evaluation. The 19-product cues included

attributes of product image in two categories: extrinsic and intrinsic. Extrinsic

attributes were defined as Indicators of quality originating from outside the

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product, not inherent parts of the product. Intrinsic attributes were defined as

product characteristics created during product manufacturing. Extrinsic product

attributes included brand, latest fashion, style, price, attractiveness, country-of-

origln, versatility, shoes in wardrobe, size, and retail store or catalog. Intrinsic

attributes Included color, durability, construction, hand-of-leather, quality,

comfort, fabrication, ease-of-care, and fit. Subjects responded to a 7-point

Likert-type scale ranging from very important (7) to not important (1), with a mid

point of Important (4). Purchase criteria were treated as

a continuous variable.

5. Footwear consumption patterns were measured by responses to Q-16

in Section 5 of the questionnaire. Consumption patterns were product specific:

preferences with regard to leather dress shoe wardrobe. Consumption pattern

data of the respondents were analyzed to determine consumption motivation as

an act toward extrinsic and intrinsic product attributes (Kim, Laroche, & Joy,

1990). Consumption patterns were obtained from a 7-point semantic differential

summated rating scale anchoring six bipolar scenarios composed of two extrinsic

and four intrinsic product attributes. The extrinsic product attributes were

number of shoes in wardrobe and price. The intrinsic product attributes were

color and style, quality, comfort versus attractiveness, and durability versus

versatility. Each respondent rated the extent to which each of the scenarios

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described their consumption of footwear used for business wear. Consumption

pattern was treated as a continuous variable.

6. Footwear characteristics were measured by response to Q-17 in

Section 6 of the questionnaire. Footwear characteristics were product specific:

feelings about the pair of leather dress shoes most often worn to work. Footwear

characteristic data of the respondents were analyzed to determine feelings as a

motivation toward extrinsic and intrinsic product attributes (Kim, Laroche, & Joy,

1990). Subjects used a semantic differential scale anchoring 7-place response

fomnats. The feeling measure was composed of 6 extrinsic and 11 intrinsic

product attributes used in the purchase criteria measure. The extrinsic product

attributes were fashion, contemporary versus traditional, price, attractiveness,

versatility, and brand. The intrinsic product attributes were conservative versus

casual, comfort, color, quality, breathabllity, care, natural leather, touch,

construction, durability, and fit. Q-17 was treated as a continuous variable.

7. Personal characteristics were measured by responses to Q-01 through

Q-15 in the last section of the questionnaire. Personal characteristics were

defined as family size, number of children, current employment of adults in the

home, martial status, sex, age, education, present employment status,

occupational category, employment orientation, length of time not employed,

geographic region, city size, ethnic background, and income.

86

Family size-The household size was measured by the response to Q-01

in section 9 (Ownbey & Horridge, 1997). This variable was treated as a


Family life cycle-Family life cycle was measured by responses to Q-02,

Q-03, and Q-04 In section 9. Marital status and children related data of

the respondents were analyzed to determine life cycle categories. The life

cycle variable was composed of three components: marital status, number

of children, and presence of children in the household (Schiffman &

Kanuk, 1991, p. 39). Marital status was established on single, married or

cohabiting, and separated or divorced or widowed. This variable was

treated as a nominal variable.

Sex-The sex variable was measured by the response to Q-05 in section

9. This variable was treated as a nominal variable.

Age-The age variable was measured by the response to Q-06 in section

7 (Ownbey & Horridge, 1997). This variable was treated as a continuous

variable.

Educational attainment-The educational attainment variable was

measured by the response to Q-07 In section 9. The educational variable

consisted of (a) some high school, (b) high school graduate, (c) vocational

or technical school, (d) some college, (e) college graduate, (f) some

87

graduate work, (g) graduate degree, (h) other. This variable was treated

as a continuous variable.

Employment profile-Employment profile was measured by responses to

Q-08, Q-09, and Q-10 in section 9. Employment data of the respondents

were analyzed to determine employment categories. The employment

profile variable was composed of three components: employment status,

occupation, and career anchorage (Bartos, 1982; Cassill, 1990; Ericksen

& Sirgy, 1985). Employment status was established on full-time

employee, part-time employee, and full-time homemaker. Full-time

students, retired Individuals, and unemployed respondents were dropped.

Occupation was classified Into four categories; professionals, non

professionals, homemakers, and students, according to the occupation

designated by the respondents (Mitchell, 1983). Professionals were

classified as professional or technical, manager or administrator, and

sales worker. Non-professionals were classified as clerical worker, craft

worker or machine operator, service worker, and government or military

worker. Homemakers were classified as full-time homemaker. The other

category was assessed by the researcher and assigned to one of the four

employment status classifications. Students were classified as part-time

student or part-time employee. Career anchorage was defined as stay-at-

88

home, plan-to-work, just a job, and career oriented. This variable was

treated as a nominal variable.

Non-working status-The non-working status variable was measured by

the response to Q-11 In section 9. The non-working variable consisted of

(a) 1-6 months, (b) 7-12 months, (c) 1-2 years, (d) 3-5 years, and (e) Over

5 years. This variable was treated as a nominal variable.

Geographic region-The geographic location variable was measured by

the response to Q-12 In section 9. States were assigned to one of six

regions: (a) Northeast (ME, VT, NH, CT, PA, MA, NJ, NY, DE, Rl, MD.

OH, WV, IN, Ml, IL, and Wl), (b) Southeast (VA, KY, NO. SO. TN, GA, FL,

AL, and MS), (c) Midwest (MN, ND, SD, lA, NE, KS, and MO), (d) South

(AR, LA, OK, TX, NM, and AZ), (e) Rocky (WY, CO, MT, ID. UT, and NV),

and (f) Pacific (WA, OR, CA, AK, and HI). This variable was treated as a

nominal variable.

City size-The city population variable was measured by the response to

item 13 in section 9. The city population variable was consisted of less

than 2,500, 2,500 to 9,999, and 10,000 to 49,999, 50,000 to 74,999,

75,000 to 99,999. 100,000 to 199,999, 200,000 to 499,999. 500,000 or

more. The population figures were collapsed into three categories: (a)

rural with less than 2,500, 2,500 to 9, 999, 10,000 to 49,999; (b) urban

50,000 to 74,999; and (d) metropolitan 75,000 to 99,999, 100,000 to

89

199,999, 200,000 to 499,999, and 500,000 or more (Bureau of the

Census, 1993; Lavin, 1996). This variable was treated as a continuous

variable.

Ethnic background—The race or ethnic background variable was

measured by a response to Q-14 in section 9. The categories consisted

of (a) American Indian or Native American, (b) Asian or Pacific Islander,

(c) African American or Non Hispanic, (d) Hispanic, (e) Caucasian or Non

Hispanic, (f) Other. This variable was treated as a nominal variable.

Income-The annual household income variable was measured by the

response to Q-15 in section 9. The annual household income variable

consisted of (a) under $15,000, (b) $15,000 to $19,999, (c) $20,000 to

$24,999, (d) $25,000 to $29,999, (e) $30,000 to $34,999, (f) $35,000 to

$49,999, (g) $50,000 to $74,999, (h) $75,000 to $100,000, (1) Over

$100,000 (Ownbey & Horridge, 1997). This variable was treated as a


Statistical Analysis of Data

Before respondents from two mailings were combined for statistical

analysis, demographics for females and males were compared between

mailings, respectively. Females and males were compared on age, marital

status, family income, education completed, region currently resided in, and size

90

of city or town. No differences were found between the two mailings for females

and for males.

As a preliminary assessment, frequency and percentage distributions of

footwear opinion leadership, footwear preferences, footwear involvement,

footwear purchase criteria, footwear consumption patterns, footwear

characteristics, and personal characteristics, were determined. Cronbach's

alpha coefficient was calculated to measure internal consistency for the footwear

opinion leadership, footwear Involvement, footwear purchase criteria, footwear

consumption patterns, and footwear characterisfics. Cronbach's alpha levels

were deemed acceptable at 0.60.

Research Questions

To answer the research questions, respondents were classified as High

Involvement (HI) or Low Involvement (LI) using the footwear involvement scale,

Q-14. Subsequent to analysis, five questions (2, 8, 10, 12, and 16) were reverse

coded. The procedure included (a) calculating each participants mean score for

Q-14 and listing the means from low to high, (b) selection of the first 40% (n =

100) of the total sample as low involvement participants (M = 3.19 to M = 4.69.

(c) selecting the next 20% (n = 54) of the total sample as medium involvement

(M = 4.70 to M = 5.13), and (d) selecting the remaining 40% (n = 101) of the total

sample as high involvement (M = 5.14 to M = 6.63). To ensure that there were

91

distinct groupings of HI and LI participants, the middle 20% was eliminated from

further testing. Following the groupings by footwear Involvement, AnswerTree®

analysis was used on footwear purchase criteria (Q-15) and footwear

characteristics (Q-17). For the footwear characteristics scale, 10 Items (3, 6, 7,

9, 11, 12, 13, 14, 16, and 17) were reverse coded.

Data obtained from the footwear purchase criteria and characteristics

scales were analyzed statistically using AnswerTree® algorithm software to build

decision trees for each scale (Statistical Package for the Social Sciences

(SPSS), 1998). Decision trees were constructed using the likelihood ratio chi-

square statistic method. This was done by the CHAID (Chi-square Automatic

Interaction Detection) method. The analysis begins with a root node containing

all the cases in the sample data. In the current study, the root node was

composed of data from 100 High Involvement respondents and 101 Low

Involvement respondents. As the tree Is generated, the data branch into

mutually exclusive subsets based on some pattern of predictor variables.

Classification of the data was stopped when the number of cases in a subset

dropped below 20. The predicative value of each decision tree was verified by

cross-validation. In addition, gain scores as probability of response were

computed for the HI and LI samples for both decision trees. See Appendix E for

a description of the AnswerTree® 2.0, including definition of terms and

procedure. The level of significance was set at 0.05.

92

CHAPTER IV

RESULTS

The overall purpose of this study was to determine If HI consumers and LI

consumers differed in their purchase of leather dress shoes for business wear.

Information regarding respondents' selected footwear opinion leadership,

footwear preferences, footwear involvement, footwear purchase criteria, footwear

consumption patterns, footwear characteristics, and personal characteristics was

obtained through responses to a self-administered questionnaire. The

questionnaire for the study can be found in Appendix A.

Data were examined using descriptive statistics (i.e., frequency

distributions and means) and AnswerTree® algorithm software. The results of

the study are reported in four sections: (a) description of the sample, (b)

reliability of the scales, (c) analysis of research questions, and (d) summary of

findings of research questions.

Description of the Sample

Working Females

The population for this study was females in the U.S age 25 to 65 years.

The sample (N = 752,357) for the females consisted of a subsample (n = 1,000)

randomly drawn from a subject list obtained from National Demographics &

93

Lifestyles Inc. (NDL). Questionnaires were distributed to the sample group in

summer of 1998. A total of 1,000 questionnaires were sent to the sample in the

first mailing, of which 87 were returned undeliverable, a total of 179

questionnaires were returned by respondents, of which 114 were usable. Of the

65 questionnaires that were deemed unusable, 21 were not employed, 39 did

not wear leather dress shoes to work, and 5 were incomplete. Following the

second mailing 17 were returned undeliverable, a total of 87 questionnaires were

returned by respondents, of which 25 were usable. Of the 62 questionnaires that

were deemed unusable, 9 were not employed, 46 did not wear leather dress

shoes to work, and 7 were incomplete. Eight weeks after the Initial mailing, 266

questionnaires were returned of which 139 questionnaires were deemed usable,

yielding a 18% response rate.

The working female participants were compared to U.S. females (U.S.

Department of Commerce, 1997) on four demographics: age, education,

household income, and marital status. Differences were noted between female

groups on 3 of the 4 demographics. The exception was marital status. The

largest percentage of females, participants and U.S., were married. As to mean

age, participants were older (43.9 years) than U.S. females (37.8 years).

However, no difference was found between participants and U.S. females in the

distribution by age categories. The highest percentage of female (40.0%)

participants were college graduates and had household incomes of $50,000 to

94

$74,999 (31.2%), while the highest percentage of U.S. females (40.8%) were

high school graduates and had incomes of $35,000 to $49,999 (31.4%).

Working Males

The population for this study was males in the U.S. age 25 to 65 years.

The sample (N = 3,327,143) for the males consisted of a subsample (n = 1,000)

randomly drawn from a subject list obtained from National Demographics &

Lifestyles Inc. (NDL). Questionnaires were distributed to the sample group in

summer of 1998. Participation was voluntary and the male subjects were

informed of rights as human subjects. A total of 1,000 questionnaires were sent

to the sample In the first mailing, of which 107 were returned undeliverable, a

total of 177 questionnaires were returned by respondents, of which 91 were

usable. Of the 86 questionnaires that were deemed unusable, 17 were not

employed, 56 did not wear leather dress shoes to work, and 13 were incomplete.

Following the second mailing 42 were returned undeliverable, a total of 121

questionnaires were returned by respondents, of which 25 were usable. Of the

96 questionnaires that were deemed unusable, 9 were not employed, 64 did not

wear leather dress shoes to work, and 23 were Incomplete. Eight weeks after

the initial mailing, 298 questionnaires were returned of which 116 questionnaires

were deemed usable, yielding a 17.3% response rate.

95

The working male participants were compared to U.S. males (U.S.

Department of Commerce, 1997) on four demographics: age, education,

household income, and marital status. Differences were noted between male

groups on 3 of the 4 demographics. The exception was marital status. The

largest percentage of males, participants and U.S., were married. As to mean

age, participants were older (43.3 years) than U.S. males (35.3 years).

However, no difference was found between participants and U.S. males in the

distribution by age categories. The highest percentage of male (36.2%)

participants were college graduates and had household incomes of $50,000 to

$74,999 (32.1%), while the highest percentage of U.S. males (37.9%) were high

school graduates and had Incomes of $35,000 to $49,999 (29.2%).

Footwear Opinion Leadership

Footwear opinion leadership data were collected using the footwear

opinion leadership section of the research questionnaire. Seven statements

were used for the purpose of describing the footwear opinion leadership of

working females and males in regard to their clothing and shoe purchasing

practices for business wear.

96

Working Females

Table 4.1 summarizes the working females' response to footwear opinion

leadership. The largest percentage of females, regarding two statements

referring to the workplace, was Indifferent to trying new fashion ideas before co

workers (35.3%) and wearing clothes to work that were of the latest styles

(41.7%). When considering stores, the females agreed (33.1 %) that they liked to

try new and different places to shop for clothing but were indifferent (31.7%) to

visiting a new clothing store first. The remaining three statements referred to the

purchase of leather dress shoes using intrinsic criteria (I.e., quality, styling, and

comfort). The females strongly agreed that quality (53.2%) and comfort (77.7%)

were highly Important to the purchase of shoes, and agreed (44.6%) that styling

was highly important.

Working Males

Table 4.2 summarizes the working males' response to footwear opinion

leadership. Males, regarding their workplace, were either indifferent (36.2%) or

strongly disagreed (27.6%) to trying new fashion ideas before co-workers. As to

wearing clothes to work that were of the latest styles, 41.4% were indifferent and

19.8% agreed. When considering stores, males were indifferent (35.3%) or

agreed (28.4%) to trying new and different places to shop for clothing but

97

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99

strongly disagreed (40.5%) or disagreed (25.9%) to visiting a new clothing store

first. The remaining three statements referred to the purchase of leather dress

shoes using intrinsic criteria (I.e., quality, styling, and comfort). A majority of

males (77.6%) considered comfort highly important when purchasing leather

dress shoes, while the highest percentage of males strongly agreed (48.3%) that

quality and agreed (43.1%) that styling were also highly important.

Footwear Preferences

Footwear preferences data were collected using the footwear preferences

section of the research questionnaire. Twelve quesfions were used for the

purpose of describing the preferences of working females and males in regard to

leather dress shoes for business.

Working Females

Table 4.3 provides a summary of the females' responses to footwear

preferences. Females paid from $10 and less to $299 at regular price, with the

majority (55.4%) paying between $50 and $99. As to sale price, the amount paid

was from $10 and less to $199, with the highest percentage paying $40 to $99.

Females (48.2%) had not purchased shoes from a catalog in the past two years

had purchased one pair (10.1%). As to satisfaction with catalog selections, the

largest percentage (12.2%) of the 51 who did purchase from catalogs were

100

Table 4.3 Footwear Preferences by Working Females

Items n %

Sale Price Paid For Footwear Less than $10 $10-$19 $20-$29 $30-$39 $40-$49 $50-$99 $100-$199 $200-$299

Regular Price Paid For Footwear Less than $10 $10-$19 $20-$29 $30-$39 $40-$49 $50-$99 $100-$199 $200-$299 $300-$499

Number Shoes Purchased From Catalogs In Past 2 years 0 1 2 3 4 5 8 12 15 No response

15 5 22 26 28 38 5 0

10.8 3.6 15.8 18.7

20.1 27.3 3.6 0.0

33 0 0 7

6 77 15 1 0

23.7 0.0 0.0 5.0 4.3 55.4 10.8 0.7 0.0

67

14

10 7

5 2 1 1

1

31

48.2

10.1 7.2 5.0

3.6 1.4 0.7 0.7 0.7

22.3

101

Table 4.3 (cont.)

Items n %

Satisfaction With The Selection In Catalogs Very satisfied Satisfied Somewhat satisfied Somewhat dissatisfied Dissatisfied Very dissatisfied No response

12

17 14

3

3 2 88

8.6

12.2

10.1 2.2 2.2 1.4

63.3

Number Shoes Purchased In Retail Stores In Past 2 Years 0 1 2 3 4 5 6 7 8 9 10 12 15 16 17 20 24 25 No response

6 6 19 13 13 15 18 2 10 1 18 4

3 1 1 1 1

2 5

4.3 4.3 13.7 9.4 9.4 10.8 12.9 1.4 7.2 0.7

12.9 2.9 2.2 0.7 0.7 0.7 0.7 1.4

3.6

102

Table 4.3 (cont.)

Items n %

Satisfaction With The Selection In Retail Stores Very satisfied Satisfied Somewhat satisfied Somewhat dissatisfied Dissatisfied Very dissatisfied No response

Presence Of A Favorite Footwear Brand Yes No No response

Frequency Of Wearing Footwear During A Typical Week 0 1 2 3 4 5 6 7 No response

Purchase Attributes Better Quality Lower Price Better Selection Better Fit Better Comfort Other

33 58 27

6 1

3 11

23.7 41.7 19.4

4.3 0.7 2.2 7.9

84

53 2

60.4

38.1 1.4

13 8 11 23 17 57

1

6 3

23 96 44

41

76

5

9.4 5.8 7.9 16.5 12.2 41.0 0.7

4.3 2.2

16.5 69.1 31.7

29.5 54.7

3.6

103

Table 4.3 (cont.)

Items n %

Foot Health Excellent Good Fair Poor

Shoe Size Length 5 5'A 6 6 72 7 IVz 8 8 72

9 9 72

10 11 12

Shoe Size Width AA, S A, N B, M C,W D, EW E, EEW No response

Fitting Problems Side Width Heel Width Length Arch Instep Other None

43

73 16 7

3 5 10 14

11 17 22 19 20 6 6 3

3

9

13 81 18 3 1 14

51

31 13 22 18

11 28

30.9

52.5

11.5 5.0

2.2 3.6 7.2 10.1

7.9 12.2 15.8 13.7 14.4 4.3 4.3 2.2

2.2

6.5 9.4 58.3 12.9 2.2 0.7

10.1

36.7

22.3 9.4

15.8 12.9 7.9

20.1

104

Table 4.3 (cont.)

Items n %

Quality Descriptors Ranked As #1 Comfort Price Brand Quality Style Fit Appearance Hand-of-Leather Construction

Quality Descriptors Ranked As #2 Price Comfort Style Fit Quality Brand Hand-of-Leather Appearance Construction Color Heel height Fabrication

Quality Descriptors Ranked As #3 Style Price Brand Comfort Quality Appearance Color Heel Height Fabrication Attractiveness Durability

79 28 11

5

5 3 2 2 1

56.8 20.1 7.9 3.6

3.6 2.2 1.4 1.4 0.7

41

28 18 10 5 5 4 3 2 1 1 1

29.5 20.1 12.9 7.2 3.6 3.6 2.9 2.2 1.4 0.7 0.7 0.7

26 17 11 11 5

4

3 1

1

1

1

18.7

12.2 7.9 7.9 3.6

2.9

2.2 0.7

0.7

0.7 0.7

105

satisfied. Referring to the number of shoes purchased in retail stores during the

past two years, 13.7% purchased two pairs, and 12.9% purchased six pairs and

ten pairs, respectively. Females were satisfied (41.7%) or very satisfied (23.7%)

with their retail shoe purchases.

Leather footwear was worn to work five times (41.0%) or three times

(16.5%) during a typical week. A majority of the working females stated that

lower price (69.1%) and better comfort (54.7%) were reasons to purchase more

leather dress shoes for business wear. Foot health was considered good by a

majority (52.5%) of the females. As to shoe size length, a majority (56.1%) of

the females ranged in length from IVk to 9, while a majority (58.3%) wore a shoe

size width of B and/or M. Fitting problems were side width (36.7%) and heel

width (22.3%). When females were asked what evaluative characterisfics were

used to determine quality, they ranked comfort (56.8%) first, price (29.5%),

comfort (20.1%), and style (12.9%) second, and style (18.7%) and price (12.2%)

third.

Sixty percent of the females indicated that they had a favorite footwear

brand. The favorite footwear brands among working females were Nine West,

Naturalizer, Liz Claiborne, and Cole Haan, while the most purchased footwear

brands were Nine West and Naturalizer. The largest percentage of females

shopped for footwear at department stores (42.0%) and shoe stores (25.9%).

106

Dillard's, Nine West, JC Penney, and Macy's were the stores most shopped by

females (see Table 4.4 and Table 4.5).

Working Males

Table 4.6 provides a summary of the males' responses to footwear

preferences. At regular price males paid between $10 and less to $499, with a

majority (72.5%) paying $50 to $199. At sale price, males paid between $10 and

less and $299, with 59.4% paying $50 to $199 for leather dress shoes. A

majority of the male respondents (51.7%) had not purchased shoes from a

catalog in the past two years. As to the 26 males who had purchased from

catalogs, they (8.6%) were somewhat satisfied. Referring to the number of shoes

purchased In retail stores during the past two years, males (65.5%) had

purchased 1 to 4 pairs. Males were satisfied (43.1%) or very satisfied (25.0%)

with their retail shoe purchases.

Leather footwear was worn to work by a majority of males (54.3%) five

times during a typical week. A majority of the working males stated that lower

price (63.8%) was the reason to purchase more leather dress shoes for business

wears. Foot health was considered good by a majority (50.9%) of the males. As

to shoe size length, a majority (62.1%) of the males ranged from 8/2 to 11, while

the largest percentage (41.4%) wore a shoe size width of D and/or EW. Fitting

107

Table 4.4 Favorite and Purchased Footwear Brands

by Working Females

Favorite Footwear Brands Footwear Brands Purchased

Nine West (45) Naturalizer (36) Liz Claiborne (19) Cole Haan (17) Kenneth Cole (11) Anne Klein (9) Enzo Anglolini (7) Coach (6) Stuart Weitzman (8) Bandolino (4) Easy Sprit (4) Amalfi (3) Birkenstock (2) Eitenne Alginer (2) Worthington (2) Bass (2) Cobbles (2) Mason (2) Selby (2) Doc Martins (2) Nickels (2) Varieo (2) TImberiand (2) Hush Puppy (1) J. Crew (1) SestoMeucci (1) Candles (1) Bally (1) Joan & David (1) Evan Picone (1) Arche(l) Aerosoles (1) Old Main Trotters (1) Kittens (1) Rockport(1)

Nine West (28) Naturalizer (24) Liz Claiborne (9) Enzo Anglolini (6) Easy Sprit (5) Cole Haan (4) Worthington (4) Selby (4) Anne Klein (3) Nickels (3) SAS (3) Amalfi (2) Bass (2) Doc Martins (2) East Land (2) Hush Puppy (2) Kenneth Cole (2) Soft Spots (2) Stuart Weitzman (2) Aerosoles (1) Ann Taylor (1) Arche(1) Bally (1) Bandolino (1) Bare Traps (1) Buno Sport (1) Dr. Scholl's (1) Eitenne Alginer (1) Enrico Gori (1) Footiary Spekelen (1) Gucci (1) J. Crew (1) Jennifer Moore (1) Johansen (1)

108

Table 4.4 (cont.)


Enrico Gori (1) Mason (1) Sroi Unlsa (1) Mootsie Tootsie (1) Van Eli (1) Spanish Leather (1) Yea(1) St. Laurrent(l)

TImberiand (1) Yea(1) Zodiac (1)

109

store Types

Table 4.5 Stores Shopped for Footwear

by Working Females

n % Store Names

1. Catalogs 2. Discount Stores 3. Department Stores 4. Factory Outlet Stores 5. Apparel Specialty Stores 6. Shoe Stores

6 13 47 11 6

29

4.3 9.3

33.8 7.9 4.3

20.8

Dillard's (10) Nine West (9) JC Penney (8) Macy's (7) Foley's (5) Naturalizer (4) Payless Shoe Source (4) Hudson's (3) Shoe Carnival (3) Bass Outlet (2) Boston Store (2) Eddie Bauer (2) Famous Footwear (2) Marshall's (2) Mason (2) Nordstrom (2) Rich's (2) Sears (2) T.J. Maxx (2) Target (2) Wal-Mart (2) Alginer Outlet (1) Alex Shoe Store (1) Ann Taylor (1) Bacon's (1) Beall's(l) Burdines(l) Dejenairos (1) DenonTree (1) DSW Shoe Warehouse (1) Easy Sprit (1) Eitenne Alginer (1) Florsheim (1) Herbergers (1) J. Crew (1) Kaufmanns (1) K0(1) Lament's (1)

110

Table 4.5 (cont.)

store Types n % Store Names

Land's End (1) Lazarus (1) Lord & Taylor (1) Nicole Summer Catalog (1) Parisians (1) Paul's Shoes (1) Ralph's Shoe Store (1) SAS(1) Shirley's Shoes (1) Shoe Box (1) Stan's Bootery (1) Steinmart(l) Steken's{1) Strawberry's (1) Strow Bridges (1) Vanmour (1) Vantage Shoe Outlets (1)

111

Table 4.6 Footwear Preferences by Working Males

Items n %

Sale Price Paid For Footwear Less than $10 $10-$19 $20-$29 $30-$39 $40-$49 $50-$99 $100-$199 $200-$299

Regular Price Paid For Footwear Less than $10 $10-$19 $20-$29 $30-$39 $40-$49 $50-$99 $100-$199 $200-$299 $300-$499

Number Shoes Purchased From Catalogs In Past 2 years 0 1 2 3 4 8 No response

29 1 2 7 7

49 20

1

25.0 0.9 1.7 6.0 6.0

42.2 17.2 0.9

26 0 0 0 2

38 46 3 1

22.4 0.0 0.0 0.0 1.7

32.8 39.7

2.6 0.9

60 10 5 2 2 1

36

51.7 8.6 4.3 1.7 1.7 0.9

31.0

112

Table 4.6 (cont.)

Items n %

Satisfaction With The Selection In Catalogs Very satisfied Satisfied Somewhat satisfied Somewhat dissatisfied Dissatisfied Very dissatisfied No response

Number Shoes Purchased In Retail Stores In Past 2 Years 0 1 2 3 4 5 6 7 8 10 12 No response

Satisfaction With The Selection In Retail Stores Very satisfied Satisfied Somewhat satisfied Somewhat dissatisfied Dissatisfied Very dissatisfied No response

6 7 10 1 2 0 90

5.2 6.0 8.6 0.9 1.7

0.0 77.6

12 14 33 14 15 4 8 2 3 1 2 8

10.3 12.1 28.4 12.1 12.9 3.4 6.9 1.7 2.6 0.9 1.7 6.9

29

50 15 3 0 0 19

25.0

43.1 12.9 2.6 0.0 0.0 16.4

113

Table 4.6 (cont.)

61 51 4

52.6 44.0 3.4

Items n %

Presence Of A Favorite Footwear Brand Yes No No response

Frequency Of Wearing Footwear During A Typical Week 0 1 2 3 4 5 6 7 No response

Purchase Attributes Better Quality Lower Price Better Selection Better Fit Better Comfort Other

Foot Health Excellent Good Fair Poor

14 7 4

5 8 63 11 1 3

29 74 27 17 42 7

45 59 7

0

12.1 6.0 3.4

4.3 6.9 54.3 9.5 0.9 2.6

25.0 63.8 23.3 14.7 36.2 6.0

38.8 50.9 6.0 0.0

114

Table 4.6 (cont.)

Items n %

Shoe Size Length 6 72 7 72 8 8 72 9 9 72 10 11 11 72 12 12 72 13 14 No Response

Shoe Size Width AA, S A, N B, M C,W D, EW E, EEW No response

Fitting Problems Side Width Heel Width Length Arch Instep Other None

2 4 4 4

13 25 16 14 4 7 1 5 1

16

1 2 25 13 48 13 14

28 9 10 27 8 5 39

1.7 3.4 3.4 3.4

11.2

21.6 13.8 12.1 3.4

6.0 0.9 4.3 0.9 13.8

0.9 1.7

21.6 11.2 41.4 11.2 12.1

24.1 7.8 8.6 23.3 6.9 4.3 33.6

115

Table 4.6 (cont.)

Items

Quality Descriptors Ranked As #1 Comfort Price Brand Quality Style Fit Appearance Construction

Quality Descriptors Ranked As #2 Price Comfort Style Fit Quality Brand Appearance Construction Hand-of-Leather Durability

Quality Descriptors Ranked As #3 Style Price Brand Comfort Quality Appearance Color Durability Unique

n

53 21 15 4 7 4 1 1

30 32 6 2 4

12 2 1 1 2

6 19 7 6 6 2 1 1 1

%

45.7 18.1 12.9 3.4 6.0 3.4 0.9 0.9

25.9 27.6 5.2 1.7 3.4

10.3 1.7 0.9 0.9 1.7

5.2 16.4 6.0 5.2 5.2 1.7 0.9 0.9 0.9

116

problems were none (33.6%) and side width (24.1%). When males were asked

what evaluative characteristics were used to determine quality, they ranked

comfort (45.7%) first, comfort (27.6%) and price (25.9%) second, and price

(16.4%) and brand (6.0%) third.

A majority (52.6%) of the males Indicated that they had a favorite footwear

brand. The favorite brands among working males were Florsheim, Dexter,

Johnston & Murphy, and Cole Haan, while most purchased brands were

Florsheim and Dexter. The largest percentage of males shopped for footwear at

shoe stores (31.9%) and department stores (31.0%). JC Penney, Florsheim,

and Dillard's were the stores most shopped by males (see Table 4.7 and Table

4.8).

Footwear Involvement

Footwear involvement data were collected using the footwear involvement

secfion of the research questionnaire. Sixteen questions were used for the

purpose of describing the involvement of working females and males in regard to

leather dress shoes for business.

Working Females

Table 4.9 provides a summary of the footwear involvement by working

females. The female respondents did not indicate a majority rating on the 16

117

Table 4.7 Favorite and Purchased Footwear Brands

by Working Males


Florsheim (37) Dexter (25) Johnston & Murphy (10) Cole Haan (9) Allen Edmonds (6) Rockport (6) Mason (3) Stafford (3) Father & Son's (2) Kittens (2) Red Wing (2) Stacy Adams (2) TImberiand (2) Aerosoles (1) Bally (1) Bass(1) Boston Ian (1) Clarr(l) Coach (1) Dr. Scholl's (s) Hanover (1) Justin (1) Russell (1) SAS(1)

Florsheim (29) Dexter (20) Johnston & Murphy (6) Stafford (6) Cole Haan (5) Rockport (5) Allen Edmonds (5) Bass (4) Bally (3) Bostonian (3) Red Wing (3) TImberiand (2) Bates Lites(1) CCBene(l) Clarr(l) Dr. Scholl's (1) East Land (1) Hanover (1) Italian (1) Jarmon (1) Justin (2) SAS(1)

118

Table 4.8 Stores Shopped for Footwear

by Working Males

Store Types

1. Catalogs 2. Discount Stores 3. Department Stores 4. Factory Outlet Stores 5. Apparel Specialty Stores 6. Shoe Stores 7. Other 8. No Response

n

7 4

36 7 4

37 20

1

%

6.0 3.4

31.0 6.0 3.4

31.9 17.2 0.9

Store Names

JC Penney (14) Florsheim (9) Dillard's (6) Sears (5) K-Mart (3) Nordstrom (3) Bally Store (2) Bass Outlet (2) Destes (2) Kaufmanns (2) Mason (2) Robinson's Way (2) Shoro (2) Standard Brand Shoes(2) Allen Edmonds (1) Belk Clothing Store (1) Beairs(l) Blairs(l) Boston Store (1) Caverdars(l) CCBeene(l) Chernn Shoe(1) Cole Haan (1) Elcle Beesnaus(l) Eldor Boorman (1) Foley's (1) Gayfer's(l) Hanover (1) Hoffheiner's(l) Hudson's (1) Jarman (1) Johnston & Murphy (1) Lazarus (1) Macy's (1) Men's Warehouse (1) Mervyns(l) Nelman Marcus (1) Payless Shoe Source (1) Red Wing (1) Sake George (1)

119

Table 4.8 (cont.)

Store Types n % Store Names

SAS(1) Silver Mans (1) Value City (1)

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statements included in the footwear involvement section of the questionnaire.

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strongly agreed that shoes for work were very important. As to shoes for work

that did not perform well, females strongly agreed (44.6%) that lack of

performance troubled them a great deal. Three statements that female

respondents indicated agreement on were: "I choose my shoes for work very

carefully" (58.3%),"l am very interested in the shoes I wear to work" (56.8%), and

"Which shoes I wear to work matters to me a lot," (52.6%). The highest

percentage of females were indifferent on two statements: "I can really tell a lot

about a person by the shoes he/she selects for work" (33.8%) and "The type of

shoes that I wear to work is compatible with how I would like my co-workers to

think of me" (30.9%). Disagreement by females was indicated on two

statements:" I can't say that I particularly like the type of shoes that I wear to

work" (53.3%) and "When I purchase shoes for work it's not a big deal if I can't

wear them very often" (51.8%).

Working Males

Table 4.10 provides a summary of the footwear involvement by working

males. The male respondents did not indicate a majority rating on the 16

statements included in the footwear involvement section of the questionnaire.

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Important to me" (81.9%), "A purchase of shoes for work that doesn't perform

well troubles me a great deal" (75.0%), "I choose my shoes for work very

carefully" (72.4%), "I am very interested in the shoes I wear to work" (68.1%),

"The shoes I usually wear to work are the ones I enjoy the most" (67.3%), "Which

shoes I wear to work matters to me a lot" (61.2%),"lt's really a problem if I buy

shoes that are inappropriate for my job" (56.0%), and "The type of shoes that I

wear to work is compatible with how I like to think of myself (46.5%). In contrast

males disagreed with five statements: "When purchasing shoes for work, I am

never certain about my choice" (57.8%),"Purchasing shoes for work is rather

complicated" (55.1%), "When I purchase shoes for work it's not a big deal if I

can't wear them very often" (54.3%), "I can't say that I particularly like the type of

shoes that I wear to work" (54.3%), and "When I buy shoes for work, it's difficult

to make a bad choice" (43.9%). The highest percentage of males indicated

indifference to shoes expressing their personality (37.9%), shoes selected for

work that can tell a lot about a person (31.9%), and shoes being compatible with

how they would like for their co-workers to think of them.

Footwear Purchase Criteria

In the purchase criteria section of the research questionnaire, data were

collected on 11 extrinsic and 8 intrinsic footwear attributes. The respondents

were asked to rate the importance level of each purchase criterion.

126

Working Females

More than 95% of the respondents answered from very important to

important to eight purchase criteria (Intrinsic = 6; Extrinsic = 2) they considered

when purchasing leather dress shoes for business wear: fit (98.6%), quality

(97.9%). durability (97.2%), attractiveness (97.1%), comfort (97.1%),

construction (95.6%), color (95.6%), and size (96.4%). For five purchase criteria

(Intrinsic = 4; Extrinsic = 1), more than 90% of the respondents answered from

very important to important price (93.5%), style (93.5%), ease-of-care (91.3%),

fabrication (90.6%), and hand-of-leather (90.0%). The six remaining purchase

criteria (Extrinsic = 6) were rated by a majority of the working females, with

versatility (87.7%), shoes in wardrobe (85.6%), latest fashion (64.0%), retail

store or catalog (61.1%), and brand (58.3%) being considered very important to

important and country-of-origIn (69.1%) considered not important (see Table

4.11).

Working Males

As indicated in Table 4.12, more than 95% of the respondents answered

from very important to important on four purchase criteria (Intrinsic = 3; Extrinsic

= 1): fit (99.0%), size (98.2%), quality (95.8%), and durability (95.7%). More than

90% of the respondents answered from very important to important on six

purchase criteria (Intrinsic = 5; Extrinsic = 1): comfort (94.0%), style (93.5%),

127

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ease-of-care (93.1%), price (91.3%), fabrication (90.6%), and hand-of-leather

(90.0%). The nine remaining purchase criteria (Intrinsic = 2; Extrinsic = 7) were

rated by a majority of working males, with color (89.7%), construction (89.7%),

versatility (87.0%), attractiveness (85.3%), brand (74.1%), shoes in wardrobe

(65.5%), retail store or catalog (57.7%), and latest fashion (51.7%) being

important, and country-of-origin (56.0%) being not important.

Footwear Consumption Patterns

Footwear consumption data were collected using the footwear

consumption section of the research questionnaire. Participants determined

consumption patterns by responding to six scenarios on a continuum of seven

points.

Working Females

Table 4.13 indicates the footwear consumption patterns of females.

Working females purchased shoes that were basic in color and style (55.4%) and

preferred to have a small number of shoes but of high quality (74.2%). The

largest percentage of females could not decide between versatility and durability

(42.4%), comfort and attractiveness (36.0%), quantity and price (26.6%), and

quantity and usage (22.3%).

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Working Males

Footwear consumption patterns of males (see Table 4.14) indicated they

preferred to have a small number of shoes that had quality (75.9%), were basic

in color and style (68.9%), and were worn more often (59.5%). The largest

percentage of working males could not decide between versatility and durability

(37.0%), comfort and attractiveness (29.3%), and quantity and price (25.0%).

Footwear Characteristics

Tables 4.15 and 4.16 describe 17 of the footwear characteristics for

working females and working males. Included are ten intrinsic characteristics

(i.e., conservative versus casual, comfort, color, quality, breathabllity, care,

natural leather, touch construction, and fit) and seven extrinsic characteristics

(i.e., fashion, contemporary versus traditional, price, attractiveness, versatility,

brand, and durability).

Working Females

In describing leather dress shoes most often worn for business-related

activities, females stated their feelings were related to 70% of the intrinsic and

57.1% of the extrinsic characteristics. The intrinsic were fit well (82.0%), well

constructed (75.5%), comfortable (74.9%), high quality (73.4%), soft to the touch

(71.2%), basic in color (69.0%), and easy to care for (66.2%). The extrinsic were

132

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durable (74.2%), fashionable (69.1%), attractive (67.7%), and versatile (59.7%).

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characteristics (i.e., conservative versus casual, not breathable versus

breathable, and not natural versus natural) and three extrinsic characteristics

(i.e., contemporary versus traditional, inexpensive versus expensive, and

unfamiliar brand versus familiar brand).

Working Males

In describing leather dress shoes most often worn for business-related

activities, males stated their feelings were related to 80% of the intrinsic and

42.9% of the extrinsic characteristics. The intrinsic were fit well (86.3%), well

constructed (85.3%), high quality (83.6%), basic In color (74.2%), comfortable

(74.1%), natural (67.3%), easy to care for (64.7%), and breathable (49.9%). The

extrinsic were durable (74.1%), familiar brand (59.5%), and versatile (46.6%).

Working males did not express exact feelings related to four extrinsic

characteristics (i.e., unfashionable versus fashionable, contemporary versus

traditional, inexpensive versus expensive, and unattractive versus attractive) and

two intrinsic characteristics (i.e., conservative versus casual and hard to the

touch versus soft to the touch).

136

Personal Characteristics

Personal information was collected from female and male respondents on

(a) sex, age, marital status, education, income, and ethnic background, (b) family

size and number of children, geographic region, and city size, and (c) current

employment of adults in the home, present employment status, occupational

category, employment orientation, and length of time not employed. See Tables

4.17 and 4.18.

Working Females

Table 4.17 describes the personal characteristics of the working female

respondents. A majority of females were 36 to 55 years old (68.3%) with a mean

age of 43.9 years. The highest percentage was married (43.9%), with 23.0%

divorced and 20.1% single, never married. They were college graduates (28.1%)

or had some college (24.5%), and the highest percentage (48.9%) had

household incomes between $35,000 and $74,999. Most (84.2%) working

females were Caucasian, Non-Hispanic.

The family size included two persons (34.5%) or one person (29.5%). A

majority (69.8%) of the females did not have children living at home. Residence

was in urban areas (58.9%), primarily in three regions: Midwest (30.2%),

Northeast (29.5%), and South (18.7%).

137

Table 4.17 Personal Characteristics

by Working Females

Characteristics n %

Age 18-25 years 26-35 years 36-45 Years 46-55 years 56+ No response

Education Some high school High school graduate Vocational / Technical school Some college College graduate (B.S., B.A., etc) Some graduate work Graduate degree (M.S., M.A., M.B.A., Ph.D., Ed.D., etc) Other No response

Marital Status Single, never married Married Separated Divorced Widowed Cohabiting No response

Income Under $15,000 $15,000-$19,999 $20,000-$24,999 $25,000-$29,999 $30,000-$34,999 $35,000-$49,999 $50,000-$74,999 $75,000-$100,000 Over 100,000 No response

0 26 48 47 17 1

0 9 10 34 39 18 27 0 2

28 61 2 32 8 5

3

3 3 3 6 15 30

38

19

11

11

0.0 18.7 34.5 33.8 12.2 0.7

0.0 6.5 7.2 24.5 28.1 12.9 19.4 0.0 1.4

20.1 43.9 1.4

23.0 5.8 3.6 2.2

2.2 2.2 2.2 4.3 10.8 21.6

27.3

13.7

7.9

7.9

138

Table 4.17 (cont.)

Characteristics n %

Employment Status Full-time employee Part-time employee Full-time homemaker Full-time student Unemployed Retired

First Job Stature Yes No No response

Current Occupation Professional/Technical Manager/Administrator Sales Worker Clerical Worker Crafts Worker or Machine Operator Full-time Homemaker Full-time Student Service Worker Government or Military Worker Self-employed Other No response

Employment Orientation Career-oriented Just-a-job Plan-to-work Stay-at-home No response

112 24

0 0 1 2

8 127 4

71 28 8 14 2 0 0 8

3 0 4 1

104 16 16

2 1

80.6

17.3 0.0 0.0 0.7 1.4

5.8 91.4 2.9

51.1 20.1 5.8 10.1 1.4 0.0 0.0 5.8

2.2 0.0 2.9 0.7

74.8 11.5 11.5 1.4

0.7

139

Table 4.17 (cont.)

Characteristics n %

Geographic Location Northeast South Midwest Southeast Rocky Mountain Pacific No response

City Population Less than 2,500 2,500 - 9,999 10,000-49,999 50,000-74,999 75,000-99,999 100,000-199,999 200,000-499,999 500,000 or more No response

Adults Employed Outside the Home

None 1 2 3 or more No response

Children Living At Home None 1 2 3 4 Other No response

41 26 42 18 2

9 1

5 18 32 21 6 15 7

33 2

29.5 18.7 30.2 12.9 1.4

6.5 0.7

3.6 12.9 23.0 15.1 4.3 10.8 5.0 23.7 1.4

7 69 48 14 1

97 19 12 4

2

2 3

5.0 49.6 34.5

10.1 0.7

69.8 13.7 8.6 2.9 1.4

1.4 2.2

140

Table 4.17 (cont.)

Characteristics n %

Household Size 1 2 3 4 5 or more No response

Number Of Years In Business World

1-6 months 7-12 months 1-2 years 3-5 years 6-10 years 10-15 years Over 15 years No response

Period of Non-Employment 1-6 months 7-12 months 1-2 years 3-5 years Over 5 years No response or Currently Employed

Ethnic Background Native American Asian / Pacific Islander African American Hispanic Caucasian Other No response

41 48 25 14 10 1

29.5 34.5 18.0 10.1 7.2 0.7

0 1 0 10 15 23 88 2

3 1 0 0 0

)yed 135

7 1

8 3

117

2 1

0.0 0.7 0.0 7.2 10.8 16.5 63.3 1.4

2.2 0.7 0.0 0.0 0.0

97 1

5.0 0.7

5.8 2.2 84.2 1.4 0.7

141

Table 4.18 Personal Characteristics

by Working Males

Characteristics n %

Age 18-25 years 26-35 years 36-45 Years 46-55 years 56+ No response

Education Some high school High school graduate Vocational / Technical school Some college College graduate (B.S., B.A., etc) Some graduate work Graduate degree (M.S., M.A., M.B.A., Ph.D., Ed.D., etc) Other No response

Marital Status Single, never married Married Separated Divorced Widowed Cohabiting No response

Income Under $15,000 $15,000-$19,999 $20,000-$24,999 $25,000-$29,999 $30,000-$34,999 $35,000-$49,999 $50,000-$74,999 $75,000-$100,000 Over 100,000 No response

0 22 45 33 12 4

0 12 6 26 29 13 29 0 1

6 102

1 6 0 0 1

0 0 0

3 10 15 36 24

24

4

0.0 19.0 38.8 28.4

10.3 3.4

0.0 10.3 5.2 22.4

25.0 11.2 25.0 0.0 0.9

5.2 87.9 0.9 5.2 0.0 0.0 0.9

0.0 0.0 0.0 2.6 8.6 12.9 31.0 20.7

20.7 3.4

142

Table 4.18 (cont.)

Characteristics n %

Employment Status Full-time employee Part-time employee Full-time homemaker Full-time student Unemployed Retired

First Job Stature Yes No No response

Current Occupation Professional/Technical Manager/Administrator Sales Worker Clerical Worker Crafts Worker or Machine Operator Full-time Homemaker Full-time Student Service Worker Government or Military Worker Self-employed Other

Employment Orientation Career-oriented Just-a-job Plan-to-work Stay-at-home

109 4 0 0 1 2

9 102

5

54 39

7 0 4 0 0 3 6 0 3

101 9 5 1

94.0 3.4 0.0 0.0 0.9 1.7

7.8 87.9 4.3

46.6 33.6

6.0 0.0 3.4 0.0 0.0 2.6 5.2 0.0 2.6

87.1 7.8 4.3 0.9

143

Table 4.18 (cont.)

Characteristics n %

Geographic Location Northeast South Midwest Southeast Rocky Mountain Pacific

City Population Less than 2,500 2,500-9,999 10,000-49,999 50,000 - 74,999 75,000-99,999 100,000-199,999 200,000 - 499,999 500,000 or more No response

Adults Employed Outside the Home

None 1 2 3 or more No response

Children Living At Home None 1 2 3 4 Other No response

28 21 42 16 4

5

5 12 32 11 7 11 15 22 1

24.1 18.1 36.2 13.8 3.4 4.3

4.3 10.3 27.6 9.5 6.0 9.5 12.9 19.0 0.9

10 43 54 8 1

50 29 21 9 3 2

2

8.6 37.1 46.6 6.9 0.9

43.1 25.0 18.1 7.8 2.6 1.7

1.7

144

Table 4.18 (Cont.)

Characteristics n %

Household Size 1 2 3 4 5 or more

Number Of Years In Business World

1-6 months 7-12 months 1-2 years 3-5 years 6-10 years 10-15 years Over 15 years No response

Period of Non-Employment 1-6 months 7-12 months 1-2 years 3-5 years Over 5 years No response or Currently Employed

Ethnic Background Native American Asian / Pacific Islander African Amerlc:an Hispanic Caucasian Other No response

8 36 22 30 20

1 0 1 7 5

20 81

1

1 2 0 0 1

112

5 2 4 1

103 0 1

6.9 31.0 19.0 25.9 17.2

0.9 0.0 0.9 6.0 4.3

17.2 69.8

0.9

0.9 1.7 0.0 0.0 0.9

96.6

4.3 1.7 3.4 0.9

88.8 0.0 0.9

145

A majority (80.6%) of the females were full-time employees, with 17.3%

working part-time. The number of adults employed outside the home was one

(49.6%) or two (34.5%). They were in professional/technical (51.1%)

occupations and were career-oriented (74.8%). Females were currently

employed (97.1%), and their current employment was not (91.4%) their first job.

Working Males

Table 4.18 describes the personal characteristics of the working male

respondents. A majority of males were 36 to 55 years old (67.2%) with a mean

age of 43.4 years, were married (87.9%). They were college graduates (25.0%)

or had graduate degrees (25.0%), and a majority (51.7%) had household

incomes between $50,000 and $100,000. Most (88.8%) working males were

Caucasian, Non-Hispanic.

The family size included two persons (31.0%) or four persons (25.9%).

The largest percentage (43.1%) of the males did not have children living at

home, with 25.0% having one child at home. Residence was in urban areas

(57.8%), primarily in the Midwest (36.2%) and Northeast (24.1%).

A majority (94.0%) of the males were full-time employees, with 3.4%

working part-time. The number of adults employed outside the home was two

(46.6%) or one (37.1%). They were in professional/technical (46.6%) or

manager/administrator (33.6%) occupations and were career-oriented (87.1%).

146

Scale Reliabilitv and Tree Validation

Cronbach's alpha coefficients were determined for three scales: Footwear

Involvement, Footwear Purchase Criteria, and Footwear Characteristics. For the

footwear involvement scale the reliability was 0.73, footwear purchase criteria

0.83, and footwear characteristics 0.76. The predictive value of each decision

tree was verified by cross-validation. The classifier for the purchase criteria

scale was correct 67% of the time, for footwear characteristics 66%.

Analysis of Research Questions

Research Question 1

Purchase Criteria

As indicated in Figure 4.1, quality denotes the first-level split of High

Involvement (HI) and Low Involvement (LI) consumers of leather dress shoes for

business wear into Node 1, Node 2, and Node 3 (y^ = 35.09, df=2,p< .0001).

HI and LI rated quality as a very important criterion for the purchase of shoes

(Node 3). The highest number of LI rated quality as important (Node 2).

Respondents in Node 3 were further split into Node 7 and Node 8 (x = 9.62, df =

1, p < .05) by color. Both HI and LI indicated color to be important to not

important (Node 7), whereas the highest number of HI rated color as very

important (Node 8). Those participants rating color as very important were again

147

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important to very important in their purchase criteria.

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4, 5, and 6 (x' = 17.76, df=2,p< .01). The higher number of both HI and LI

were assigned to Node 6 where construction was rated as important to very

important. Node 6 was further split into Node 9 and Node 10 (x = 10.99, c/f = 1,

p < .01) by brand, where 31.0% of the target variable rated brand from Important

to not important. The purchase criterion, shoes in wardrobe, split Node 9 into

Nodes 13 and 14 (x = 9.17, df = 1, p < .05). Node 13, which was divided into

Node 15 and Node 16 (x' = 7.77, off = 1, p < .05) by latest fashion, contained a

high number (n = 41, 83.7%) of LI who rated shoes in wardrobe as important to

not important. The highest number at the fifth level split indicated latest fashion

was important to not important.


Referring to Figure 4.2, HI and LI respondents are divided by the footwear

characteristic, natural versus not natural, (x = 37.76, df= 2, p < .0001) into three

nodes. Node 1, Node 2, and Node 3. Node 3 showed the highest number of HI

chose natural over not natural as a characteristic of the pair of leather dress

shoes most often worn to work. LI indicated neither natural nor not natural but

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leaned toward not natural (Node 2). Node 2 was split into Nodes 4 and 5 by

poorly constructed versus well constructed (x = 13.66, df= 1, p < .01). The

higher number of LI saw poorly constructed to well constructed as a

characteristic of work shoes (Node 4), while the higher number of HI considered

work shoes well constructed (Node 5).

Node 5 was further split by Nodes 6, 7 and 8, by uncomfortable versus

comfortable (x' = 11.99, df= 2, p < .05). HI (Node 7) indicated their feelings

about leather dress shoes worn for business-related activities included

comfortable. LI (Node 8) had the same feelings, indicating work shoes were

comfortable. The respondents in Node 8 were divided (x = 8.75, off = 1, p < .05)

by inexpensive versus expensive. In Node 9 the higher number of LI varied

in response from inexpensive to expensive, whereas a small number of HI

considered shoes for work to be expensive.

Research Question 2

Purchase Criteria

Referring to Table 4.19, node statistics indicate that High Involvement (HI)

footwear consumers In nodes 5, 12, 10, 16, 14, and 7 have the highest

probability of response (i.e., index scores of 100% or greater) to criteria

considered when purchasing leather dress shoes for business wear. For

151

Node

Number

Table 4.19 High Involvement Leather Footwear Purchase Criteria:

Gain Summary

Node

Number 5

12

10

16

14

7

Node: n 11

40

7

5

12

56

Node: % 5.58

20.30

3.55

2.54

6.09

28.43

Node-I

Response: 10

36

6

3

7

32

by-Node

n Response: % 10.00

36.00

6.00

3.00

7.00

32.00

Gain: (%) 90.91

90.00

85.71

60.00

58.33

57.14

Index: (%) 179.09

177.30

168.86

118.20

114.92

112.57

Cumulative

Node: n Node: % Response: n Response: % Gain: (%) Index: (%) 5

12

10

16

14

7

11

15

11

51

58

63

75

131

134

178

5.58

25.89

29.44

31.98

38.07

66.50

68.02

90.36

10

46

52

55

62

94

95

100

10.00

46.00

52.00

55.00

62.00

94.00

95.00

100.00

90.91

90.20

89.66

87.30

82.67

71.76

70.90

56.18

179.09

177.68

176.62

171.98

162.85

141.36

139.66

110.67

Target Nodes

5

12

10

Quality (5,6)

Quality (7) +

Quality (7) +

Target Segment Characteristics ^ + Construction (4)

Color (7) + Durability (5-7)

Construction (5-7) + Brand (7)

16 Quality (5,6) + Construction (5-7) + Brand (1-6) + Shoes In Wardrobe (2-5) + Latest Fashion (6)

14 Quality (5,6) + Construction (5-7) + Brand (1-6) + Shoes in Wardrobe (6, 7) Quality (5,6) +Color (1-6)

Scale Rating: Very Important (7) - Not Important (1) ^ Number(s) In parenthesis indicates scale rating of node.

152

example. Node 5 with a response number of 10 HI has a response rate of

90.91%. The index number is 179.09%, meaning that the proportion of HI for

Node 5 is almost twice the response rate for all high involvement consumers of

leather dress shoes. The cumulative statistics (see Table 4.19) show that by

taking the best node (Node 5), 10.00% of HI can be reached by targeting 5.58%

of the market. To reach 50% of HI consumers, 29.44% of the market should be

targeted. The percentage reached can be increased to 100% by including all of

the nodes (5, 12, 10, 16, 14,7, 11, 15) listed in Table 4.19. The characteristics

that define the best node. Node 5, for HI footwear consumers are described in

Table 4.19 and include acknowledging quality and construction when purchasing

leather shoes for work. When Node 12 is reviewed, HI consider quality, color,

and durability in their purchase criteria for shoes.

As noted in Table 4.20, four nodes for Low Involvement (LI) footwear

consumers were found to have the highest probability of response to purchase

criteria for shoes worn to work. Nodes 4 and 1 each had a response rate or gain

score of 100% and index score of 203.09%. Looking at Node 15, there is a

response rate of 88.64% with an index score of 180.01%. The cumulative

statistics show that when 2.54% of LI are targeted in regard to footwear

purchase criteria, 5.15% can be reached. If 50% of LI consumers are to be

reached the 31.98% of the market must be targeted. Characteristics (see Table

153

Node

Number

1

15

11

Table 4.20 Low Involvement Leather Footwear Purchase Criteria:

Gain Summary

Node: n

14

44

Node: % 2.54

7.11

22.34

1.52

Node-by-Node

Response: n Response: % Gain: (%) Index: (%) 5 5.15

14 14.43

39 40.21

2.06

100.00

100.00

88.64

66.67

203.09

203.09

180.01

135.40

Node

Number

1

Cumulative

Node: n Node: % Response: n Response: % Gain: (%) Index: (%) 5 2.54 5 5.15 100.00 203.09

19 9.64 19 19.59 100.00

Scale Rating: Very Important (7) - Not Important (1) ^ Number(s) In parenthesis indicates scale rating of node.

203.09

15

11

7

14

16

10

12

5

63

66

122

134

139

146

189

197

31.98

33.50

61.93

68.02

70.56

74.11

94.42

100.00

58

60

84

89

91

92

96

97

59.79

61.86

86.60

91.75

93.81

94.85

98.97

100.00

92.06

90.91

68.85

66.42

65.47

63.01

51.61

49.24

186.97

184.63

139.83

134.89

132.96

127.98

104.82

100.00

Target Nodes

4

1

15

11

Quality (5,6) +

Quality (1,3,4)

Target Segment ( Construction (2,3)

Characteristics ^

Quality (5,6) + Construction (5-7) + Brand (1-6) + Shoes In Wardrobe (2-5) + Latest Fashion (1-5) Quality (7) + Color (7) + Durability (4)

154

4.20) indicate that the purchase criteria for business shoes by LI is quality and

construction, with not important to important.


Two nodes, Node 1 and Node 10, for HI footwear consumers had

response rates or gain scores of 100.00%, with index scores of 201.00%. See

Table 4.21. Nodes 7 and 3 were also considered within the "best" nodes for

examining the footwear characteristics of leather dress shoes worn most often to

work. Respectively, response rates were 86.67% and

69.66%. Referring to the cumulative statistics shown in Table 4.21, 5.00% of HI

consumers are reached by targeting 2.49% of the market. To reach 50% of HI

footwear consumers. Nodes 1, 10, 7, and 3 must be considered. Characteristics

of the shoes most often worn for work activities indicate well constructed,

expensive, and comfortable. HI footwear consumers were not definite in

considering leather footwear as not natural to natural.

As noted in Table 4.22, 24.88% of LI footwear consumers must be

targeted to reach 41.58% in terms of characteristics describing the leather dress

shoes they most often wear to work. If 50% of the market is desired then

33.84% must be targeted or both Node 4 and Node 9 must be considered.

Characteristics of the shoes worn for work activities indicate well constructed. LI

155

Node Number

1 10

Table 4.21 High Involvement Leather Footwear Characteristics:

Gain Summary

15

Node-by-Node Node: n Node: % Response: n Response: % Gain: (%) Index: (%)

2.49 5.00 100.00 1.49 3.00 100.00 7.46 13 13.00 86.67

Not Natural vs. Natural (2-6) + Poorly Constructed vs. 10 Well Constructed (6,7) + Uncomfortable vs. Comfortable

(7) + Inexpensive vs. Expensive (7) Not Natural vs. Natural (2-5) + Poorly Constmcted vs. Well Constructed (6,7) + Uncomfortable vs. Comfortable

Not Natural vs. Natural (6,7)

201.00 201.00

174.20 3 89 44.28 62 62.00 69.66 140.02

Node Number

1 10 7

3 6 9 4

Node: n 5 8

23

112 125 143 193

Node: % 2.49 3.98

11.44 55.72 62.19 71.14 96.02

Cumulative Response: n Response: %

5 5.00 8 8.00

21 21.00 83 83.00 89 89.00 92 92.00

100 100.00

Gain: (%) 100.00 100.00 91.30 74.11

71.20 64.34 51.81

Index: (%) 201.00 201.00 183.52 148.96 143.11 129.31 104.15

Target Nodes

1 Not Natural vs. Target Segment Characteristics ^

Natural (1)

Scale Rating: 7-point semantic differential summated format (e.g.. Not Natural = 1, Natural = 7) ^ Number(s) in parenthesis indicates scale rating of node.

156

Table 4.22 Low Involvement Leather Footwear Characteristics:

Gain Summary

Node

Number Node: n 50

18

13

Node: % 24.88

8.96

6.47

Node-by-Node

42 41.58 15 14.85

6.93

84.00

83.33

53.85

Response: n Response: % Gain: (%) Index: (%) 167-12

165.84

107.16

Node Cumulative Number

4

9

6

3

7

1

10

Node: n 50

68

81

170

185

190

193

Node: % 24.88

33.84

40.31

84.59

92.05

94.54

96.03

Response: i 42

57

64

91

93

93

93

n Response: % 41.58

56.43

63.36

90.09

92.08

92.08

92.08

Gain: (%) 84.00

83.82

79.01

53.53

50.27

48.95

48.19

Index: (%) 167.12

166.76

157.18

106.50

100.02

97.40

95.89

Target Nodes

4

9

Target Segment Not Natural vs. Natural (2-5) Well Constructed (1-5)

Characteristics ^ + Poorly Constructed vs.

Not Natural vs. Natural (2-5) + Poorly Constructed vs. Well Constructed (6,7) + Uncomfortable vs. Comfortable (7) + Inexpensive vs. Expensive (1-6) Not Natural vs. Natural (2-5) + Poorly Constructed vs. Well Constructed (6,7) + Uncomfortable vs. Comfortable (2-5) ^

Scale Rating: 7-point semantic differential summated format (e.g., Not Natural = 1, Natural = 7) ^ Number(s) In parenthesis indicates scale rating of node.

157

consumers were not definite in considering leather footwear as not natural or

natural, uncomfortable or comfortable, and inexpensive or expensive.

Summary of Findings of Research Questions

Research Question 1

RQ 1 asked if HI and LI consumers could be grouped by their assessment

of footwear purchase criteria and footwear characteristics of leather dress shoes

for business wear. In summary, the majority (12 of 19) of the purchase criterions

could not be classified. Referring to the seven criterions classified as predictors

of group membership, HI consumers considered quality (Node 3), color (Node 8),

and durability (Node 12) as important criteria when purchasing leather dress

shoes for business wear, whereas, LI consumers considered quality (Node 2)

and construction (Node 6) important and gave mixed ratings to brand (Node 9),

shoes in wardrobe (Node 13), and latest fashion (Node 15). See Figure 4.1. In

regard to footwear characteristics (see Figure 4.2) used to describe leather dress

shoes most often worn for business-related activities, HI stated natural (Node 3)

while LI stated not natural (Node 2) and poor construction (Node 4).

Research Question 2

RQ 2 asked If HI and LI consumers could be classified on their leather

footwear purchase behavior (i.e., footwear purchase criteria and footwear

158

characteristics of leather dress shoes for business wear). In summary, the HI

consumers were classified by their assessment of quality (very important to

important) and construction (important), whereas LI consumers considered

quality as very important to important and construction as important to not

important. HI could also be classified as to the combination of quality (very

important), color (very important), and durability (very important to important). LI

continued to be classified by their rating of quality (important to not important).

Though brand, shoes in wardrobe, and latest fashion characteristics classified

the HI and LI consumers, they showed no specific pattern (see Tables 4.19 and

4.20).

As to leather footwear characteristics, HI consumers were classified by

the not natural versus natural characteristics of their leather dress shoes worn for

business related activities, with a description of natural. LI consumers described

their footwear characteristics as not natural to natural and pooriy constructed to

well constructed. Both HI and LI were also classified by the combination of

natural, construction, comfort, and expense, with HI describing feelings of not

natural to natural, well constructed, comfortable, and expensive and LI

describing feelings of, well constructed, not natural to natural, uncomfortable to

comfortable, and inexpensive to expensive (see Tables 4.21 and 4.22).

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CHAPTER V

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

This chapter includes the following five aspects of the study: (a) summary

of the study, (b) scale reliability and tree validation, (c) summary of the findings,

(d) conclusions and implications, and (e) recommendations for further research.

Summarv of the Studv

The purpose of this study was to (a) segment the female and male leather

footwear market within a set of U.S. consumers by their footwear involvement,

and (b) identify extrinsic and intrinsic product attributes that influence their

purchase behavior for leather dress shoes for business wear.

The population for the study was employed females and males age 25 to

65 years in the U.S. who wore leather dress shoes to work at least one day a

week. A national cross-section of 1,000 female and 1,000 male consumers was

drawn for the study. National Demographics & Lifestyles Inc. (NDL) selected

subjects through a random sampling technique using a 752,357 female database

and a 3,327,143 male database.

The study was designed to determine (RQ -1) if High Involvement (HI) and

Low Involvement (LI) consumers can be grouped by their assessment of the

footwear purchase criteria and footwear characteristics of leather dress shoes for

business wear, and (RQ -2) if HI and LI consumers can be classified on their

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leather footwear purchase behavior, thus benefiting the retailer selling leather

shoes to HI and LI consumers in footwear purchase criteria and footwear

characteristics.

A self-administered mail questionnaire was constructed to obtain

information regarding the respondent's (a) footwear opinion leadership, (b)

preferences regarding footwear worn for business wear, (c) favorite and

purchased footwear brands, (d) stores shopped for footwear, (e) footwear

involvement, (f) footwear purchase criteria, (g) footwear consumption patterns,

(h) footwear characteristics, and (i) personal characteristics.

The research data were collected using the Total Design Method (Salant

& Dillman, 1994) for implementing mail surveys. During the summer of 1998,

2,000 questionnaires were sent to 1,000 females and 1,000 males. Participation

was voluntary and respondents were informed of the confidentiality of the

investigation and rights as human subjects.

A complete implementation theme was followed for collection of the

research data. Correspondence was personalized, and all questionnaires were

numbered so that non-respondent, follow-up procedures could be efficiently and

economically implemented. The initial mailing was executed one week after a

preliminary postcard was sent. Twelve days after the initial mailing, a follow-up

postcard was sent to all non-respondents from the first mailing. A second mailing

was mailed to all non-respondents three weeks after the initial mailing. Eight

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weeks after initiating data collection, 245 questionnaires, 139 female and 116

male, were processed, data tabulated, and subjected to statistical analysis.

Statistical procedures used to answer the research questions addressed

the following objectives: (a) identifying predictor variables from footwear

purchase criteria and footwear characteristics using AnswerTree(g) to create

decision trees, (b) identifying nodes from decision trees having the highest

proportion of HI and LI consumers (i.e., HI and LI that are most likely to purchase

leather dress shoes for business wear), (c) calculating percentage of HI and LI

consumers that leather dress shoe retailers can reach by targeting a certain

percentage of the market, and (d) identifying HI and LI consumer characteristics

in regard to their ratings of footwear purchase criteria and footwear

characteristics.

Summarv of the Findings

Personal Characteristics

Personal characteristics were defined as family size, number of children,

current employment of adults in the home, martial status, sex, age, education,

present employment status, occupational category, employment orientation,

length of time not employed, geographic region, city size, ethnic background, and

income.

162

1. (a) The majority of female respondents were 36 to 55 years old

(68.3%) with a mean age of 43.9 years. The highest percentage was married

(43.9%), with 23.0% divorced and 20.1% single, never married. They were

college graduates (28.1%) or had some college (24.5%), and the highest

percentage (48.9%) had household incomes between $35,000 and $74,999.

Most (84.2%) working females were Caucasian, Non-Hispanic.

1. (b) A majority of males were 36 to 55 years old (67.2%) with a mean

age of 43.4 years and, were married (87.9%). They were college graduates

(25.0%) or had graduate degrees (25.0%), and a majority (51.7%) had household

incomes between $50,000 and $100,000. Most (88.8%) working males were

Caucasian, Non-Hispanic.

2. (a) The female respondents' family size included two persons (34.5%)

or one person (29.5%). A majority (69.8%) of the females did not have children

living at home. Residence was in urban areas (58.9%), primarily in three

regions: Midwest (30.2%), Northeast (29.5%), and South (18.7%).

2. (b) The male respondents' family size included two persons (31.0%) or

four persons (25.9%). The largest percentage (43.1%) of the males did not have

children living at home, with 25.0% having one child at home. Residence was in

urban areas (57.8%), primarily in the Midwest (36.2%) and Northeast (24.1%).

3. (a) Females were currently employed (97.1%), and their current

employment was not (91.4%) their first job. A majority (80.6%) of the females

were full-time employees, with 17.3% working part-time. They were in

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professional/technical (51.1%) occupations and were career-oriented (74.8%).

3. (b) Males were currently employed (96.6%), and their current

employment was not (87.9%) their first job. A majority (94.0%) were full-time

employees, with 3.4% working part-time. They were in professional/technical

(46.6%) or manager/administrator (33.6%) occupations and were career-oriented

(87.1%).

Footwear Opinion Leadership

Footwear opinion leadership was analyzed to determine the level of

fashion leadership toward leather dress shoes worn for business wear.

1. (a) Females were indifferent to trying new fashion ideas before co

workers. Females agreed or were indifferent as to wearing clothes to work that

were of the latest styles.

1. (b) Males were either indifferent or strongly disagreed to trying new

fashion ideas before co-workers. Males were indifferent or agreed as to wearing

clothes to work that were of the latest styles.

2. (a) Females agreed that they liked to try new and different places to

shop for clothing but were indifferent to visiting a new store first.

2. (b) Males were indifferent or agreed to trying new and different places

to shop for clothing but did not agree with visiting new clothing stores first.

3. (a) For females, quality, comfort, and styling were highly important

when purchasing leather dress shoes.

164

3. (b) For males, comfort, quality, and styling were highly important when

purchasing leather dress shoes.

Footwear Preferences

Footwear shopping preference data were analyzed to determine shopping

preferences toward leather dress shoes for business wear.

1. (a) Females paid from $10 and less to $299 at regular price, with the

majority paying between $50 and $99. As to sale price, the amount paid was

from $10 and less to $199, with most paying $40 to $99.

1. (b) Males paid from $10 and less to $499 at regular price, with the

majority paying between $50 and $199. As to sale price, the amount paid was

from $10 and less to $299, with most paying $50 to $199.

2. (a) Females had not purchased shoes from a catalog in the past two

years or had purchased one pair. Females were satisfied with catalog

selections.

2. (b) Males had not purchased shoes from a catalog in the past two

years and were somewhat satisfied with selections.

3. (a) Females were satisfied with their retail shoe purchases and

purchased two to ten pairs in retail stores during the past two years.

3. (b) Males were satisfied or very satisfied with their retail shoe

purchases and purchased one to four pairs in retail stores during the past two

years.

165

4. (a) Females wore leather footwear to work five times or three times

during a typical week. A majority stated that lower price and better comfort were

reasons to purchase more leather dress shoes for business wear.

4. (b) Males wore leather footwear to work five times during a typical

week. A majority stated that lower price was the reason to purchase more

leather dress shoes for business wear

5. (a) Females considered foot health good. As to shoe size length,

females ranged in length from TA to 9, most wore a shoe size width of B and/or

M. Fitting problems were side width and heel width.

5. (b) Males considered foot health good. As to shoe size length, males

ranged from 8!4 to 11, while the largest percentage wore a shoe size width of D

and/or EW. No fitting problems were cited.

6. (a) Females determined quality, by comfort first; price, comfort, and

style, second; and style and price third. The females (60%) indicated that they

had a favorite footwear brand.

6. (b) Males determined quality, by comfort first, comfort and price

second, and price and style third. The males (52.6%) indicated that they had a

favorite brand.

7. (a) Females responded that Nine West, Naturalizer, Liz Claiborne, and

Cole Haan were the favorite footwear brands while the most purchased footwear

brands were Nine West and Naturalizer. Females shopped for footwear at

166

department stores and shoe stores. Dillard's, Nine West, JC Penney, and Macy's

were the stores most shopped by females.

7. (b) Males responded that Florsheim, Dexter, Johnston & Murphy, and

Cole Haan, while most purchased brands were Florsheim and Dexter. Males

shopped for footwear at shoe stores and department stores. JC Penney,

Florsheim, and Dillard's were the stores most shopped by males.

Footwear Involvement

Footwear involvement data were analyzed to determine beliefs and

attitudes of participants regarding shoes for business wear.

1. Cronbach alpha coefficient on the footwear involvement scale was

0.73.

2. (a) Female respondents strongly agreed that shoes for work were

very important, lack of performance troubled them a great deal, and agreed that

they choose shoes for work very carefully, and are interested in the shoes worn

for work.

2. (b) Male respondents agreed that shoes for work are very

important, performance of shoes for work troubles them a great deal, choose

shoes for work very carefully, and are very interested in the shoes worn to work.

3. (a) Females enjoy the shoes wom to work the most, and it's a problem if

shoes are inappropriate for their job. Females were indifferent that the type of

167

shoes worn to work is compatible with how they think of themselves, but agreed

that the shoes worn to work matter a lot.

3. (b) Males enjoy the shoes worn to work the most, its a problem if

shoes are inappropriate for their job, the type of shoes worn to work is

compatible with how they think of themselves, and shoes worn to work

matter a lot.

4. (a) Females disagreed that they never were certain about their choice

of shoes purchased for work, purchasing shoes for work is complicated, when

purchasing shoes for work, it is not a big deal if they can't wear them very often,

particulariy like the type of shoes that are worn to work and, it is difficult to make

a bad choice.

4. (b) Males disagreed that they never were certain about their choice

of shoes purchased for work, purchasing shoes for work is complicated, when

purchasing shoes for work, it is not a big deal if they can't wear them very often,

particularly like the type of shoes that are worn to work and, it is difficult to make

a bad choice.

Footwear Purchase Criteria

Footwear purchase criteria data were analyzed to determine the

importance of intrinsic and extrinsic product attributes in the purchase evaluation

of leather dress shoes for business wear.

168

1. Cronbach alpha coefficient on the footwear purchase criteria scale was

0.83.

2. The classifier for the footwear purchase criteria scale was correct 67%

of the time.

3. (a) Females consider fit, quality, durability, attractiveness, comfort,

construction, color, and size very important.

3. (b) Males considered, fit, size, quality, and durability very important or

important.

4. (a) Females considered price, style, ease-of-care, fabrication, and

hand-of-leather important or very important.

4. (b) Males considered comfort, style, ease-of-care, price, fabrication,

and hand-of-leather as important.

5. (a) The working females rated versatility, shoes in wardrobe, latest

fashion, retail store or catalog, and brand as very important to important and

country-of-origin was considered not important.

5. (b) The working males rated color, construction, versatility,

attractiveness, brand, shoes in wardrobe, retail store or catalog, and latest

fashion as being important, and country-of-origin being not important.

Footwear Consumption Patterns

Footwear consumption pattern data were analyzed to determine

consumption motivation as an act toward intrinsic and extrinsic product attributes.

169

1. (a) Females purchased shoes that were basic in color and style and

preferred to have a smaller number of shoes but of high quality.

1. (b) Males purchased shoes and preferred to have a smaller number of

shoes but of high quality, that were basic in color and style, and were worn more

often.

2. (a) Females could not decide between versatility and durability,

comfort and attractiveness, quantity and price, and quantity and usage.

2. (b) Males could not decide between versatility and durability, comfort

and attractiveness, and quantity and price.


Footwear characteristic data were analyzed to determine feelings as a

motivation toward intrinsic and extrinsic product attributes.

1. Cronbach alpha coefficient on the footwear characteristics scale was

0.74.

2. The classifier for the footwear characteristics scale was correct 66% of

the time.

3. (a) Females stated their feelings were related to 70% of the intrinsic

and 57.1% of the extrinsic characteristics. The intrinsic were fit, construction,

comfort, quality, touch, color, and care. The extrinsic were durability, fashion,

attractiveness, and versatility.

3. (b) Males stated their feelings were related to 80% of the intrinsic and

170

42.9% of the extrinsic characteristics. The intrinsic were fit, construction, quality,

color, comfort, natural leather, care, and breathabllity. The extrinsic were

durability, brand, and versatility.

4. (a) Working females did not express exact feelings related to three

intrinsic characteristics (i.e., conservative versus casual, not breathable versus

breathable, and not natural versus natural) and three extrinsic characteristics

(i.e., contemporary versus traditional, inexpensive versus expensive, and

unfamiliar brand versus familiar brand).

4. (b) Working males did not express exact feelings related to four

extrinsic characterisfics (i.e., unfashionable versus fashionable, contemporary

versus traditional, inexpensive versus expensive, and unattracfive versus

attracfive) and two intrinsic characterisfics (i.e., conservative versus casual and

hard to the touch versus soft to the touch).

Research Question 1

Refer to Table 5.1 for a summary of the decision trees. Involvement levels

are described by leather footwear purchase criteria and characteristics.

Research Question 2

HI footwear purchase criteria consumers. To reach 50% of HI consumers,

29.44% of the market should be targeted. The percentage reached can be

increased to 100% by including all of the "best" nodes (see Table 4.19). HI

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Table 5.1 Research Question 1: Summary

Involvement Level HI

LI

Footwear Purchase Criteria Attribute Quality, Color Durability, Construcfion Brand, Latest Fashion Quality Construction Color, Brand, Latest Fashion,

Shoes in Wardrobe

Rating Very Important Important to Very Important Important to Not Important Very Important Important to Very Important Important to Not Important

Involvement Level HI

LI

Footwear Characteristics Attribute Shoes Worn Most Often Not Natural vs. Natural Natural Poorly Constructed vs. Well Constructed Well Constructed Uncomfortable vs. Comfortable Comfortable Inexpensive vs. Expensive Expensive Not Natural vs. Natural Not Natural Poorly Constructed vs. Well Constructed Pooriy Constructed Uncomfortable vs. Comfortable Comfortable Inexpensive vs. Expensive Inexpensive & Expensive

172

footwear consumers were characterized by quality (Important to Very Important),

construcfion (Important to Very Important), color (Not Important to Very

Important), and brand (Not important to Very Important) in their purchase criteria

for leather dress shoes worn for business activities.

LI footwear purchase criteria consumers. To reach 50% of LI consumers,

31.98% of the market must be targeted. The percentage reached can be

increased to 100% by including all of the "best" nodes (see Table 4.20). LI

footwear consumers were characterized by quality (not important to important)

and construcfion (not important to important) in their purchase criteria for leather

dress shoes worn for business activities.

HI footwear characteristics consumers. To reach 50% of HI consumers,


increased to 100% by including all of the "best" nodes (see Table 4.21). HI

footwear consumers were characterized by not natural versus natural (not natural

and natural), pooriy constructed versus well constructed (well constructed),

uncomfortable versus comfortable (comfortable), and inexpensive versus

expensive (expensive) in describing a pair of leather dress shoes most often

worn to work.

LI footwear characteristics consumers. To reach 50% of LI consumers,


increased to 100% by including all of the "best" nodes (see Table 4.22). LI

footwear consumers were characterized by not natural versus natural (not natural

173

and natural), pooriy constructed versus well constructed (pooriy constructed and

well constructed), uncomfortable versus comfortable (uncomfortable and

comfortable), and Inexpensive versus expensive (inexpensive and expensive) in

describing a pair of leather dress shoes most often worn to work.

Conclusions and Implications

Retailers often want to know how to more effectively tailor their marketing,

advertising, and promofional activities based on a specific market segment to

which a consumer belongs but lack precise identifiers needed to predict group

membership. Overall, the analyses offer considerable support for the

assumption that (a) the female and male leather footwear market within a set of

U.S. consumers can be segmented by their footwear involvement, and (b)

identified extrinsic and intrinsic product attributes can influence their purchase

decisions for leather dress shoes worn for business wear.

Classificafion analysis can address target markefing by assigning High

Involvement (HI) and Low Involvement (LI) consumers to groups based on

footwear purchase criteria and footwear characteristics. Then market share can

be predicted in terms of the contributions each product attribute makes to the

share. Therefore, product development and introduction, retail merchandise

assortments, and market share predictions can be built on a data set with both

group membership and individual characterisfics.

174

Research that addresses large quantities of categorical variables and is

product-person-situatlonal specific has the potential to assist marketers in

making the retail environment more productive, thereby increasing customer

satisfaction with a purchased product, brand and store loyalty, repeat purchases,

and ulfimately profitability and market share. This study demonstrated that data

reducfion and variable screening have the potential to more accurately segment

and classify consumers with regard to leather footwear purchased and worn for

business activities.

Consumers benefit by market segmentation classification by having the

right merchandise mix available that better match product preferences and

product usage situafions. Results of segmentafion research in the footwear

market by product involvement and product attributes can contribute to the body

of knowledge in consumer behavior research related to apparel products and

assist manufacturers and retailers in meeting the needs of consumers in a

specific product classificafion, leather footwear for business wear.

Research Question 1

In terms of purchase criteria, (HI) consumers tended to consider quality,

color, durability, and construcfion to be important to them when purchasing

leather dress shoes used for business wear. Low Involvement (LI) consumers

were influenced by quality and construcfion. The differences among the two

consumer groups is consistent with the study by Thomas, Cassill, and Forsythe

175

(1991) that showed apparel product involvement is mulfi-dimensional and that

there are underlying dimensions of involvement.

As to attribute categories, both involvement groups considered intrinsic

attributes (HI - quality, color, durability, construcfion/ LI - quality and

construcfion) as very important to important in the product evaluafion and

purchase decision of leather footwear for business wear. Extrinsic attributes (HI

- brand, latest fashion/ LI - brand, latest fashion, shoes in wardrobe) were

considered as not important to important. According to Cox (1962) and Olson

(1977), intrinsic cues are likely to have a higher "predictive" value and extrinsic

cues are not universal but moderated by consumer individual differences (Lee &

Yung-Chien, 1995/1996).

The number of attributes (HI - 4 intrinsic, 2 extrinsic/ LI - 3 intrinsic, 3

extrinsic) used in the evaluation and purchase decision of leather footwear was

consistent with previous findings in which the number of product attributes in a

specific purchase situation was typically small (i.e., range of 3 to 7) (Ettenson,

Wagner, & Gaeth, 1988; Hsiao & Dickerson, 1995). Quality was considered by

HI and LI consumer groups as very important in the evaluafion and purchase of

leather footwear for business wear. Perceived quality in evaluafing apparel has

been well documented in the literature (Forsythe, 1991; Heisey, 1990; Hines &

O'Neal, 1995; Abraham-Murali & Littrell, 1995b). Results show consumers ufilize

mulficue Indicators, intrinsic and extrinsic, to measure apparel quality. As a

176

result, the issue of product attribute ufilizafion by consumers in apparel quality

judgments is an integral element in marketing strategy.

HI and LI consumers considered brand as important to not important

criterion in the purchase decision of leather dress shoes for business wear.

Product involvement was reported to be important in the formafion of brand

loyalty by Jin and Koh (1999) and Huddleston et al. (1993). Warrington and

Shim (2000) found product involvement and brand commitment were not highly

related. Forsythe (1991) proved that the absence of a significant relationship

between brand name and perception of quality among shoppers showed that

consumers rely primarily on actual product characteristics as an indicator of

product quality.

In terms of footwear characterisfics, HI and LI consumers placed similar

importance on footwear attributes, although the intensity of some product

descriptors differed between the two groups. HI consumers considered

characteristics of the shoes most often worn for work activifies natural, well

constructed, comfortable, and expensive, LI consumers considered footwear

characterisfics as not natural, poorly constructed, comfortable, and inexpensive

or expensive. This suggests that product attributes that influence consumers'

footwear purchase decisions may be similar but differences in market strategy

may be important in targefing HI and LI consumers.

177

Research Quesfion 2

Results of this study demonstrate that footwear purchase criteria and

footwear characterisfics operafionalizid by intrinsic and extrinsic product

attributes can be used to provide a profile for HI and LI consumer groups. To

target HI consumers, manufacturers and retailers should use this information to

identify product characteristics that connate the intrinsic attributes of quality and

construcfion and the extrinsic attribute of brand in the minds of the consumers on

labeling, advertising, and merchandising strategies based on product knowledge.

Bei and Widdows (1999) showed product involvement interacted with product

informafion and product knowledge. High involvement consumers are perceived

to have engaged in more complex purchasing decisions and are more brand

loyal (Zaichowsky, 1985). HI consumers may have more product knowledge and

perceive the quality and construcfion of shoes differently than LI consumers.

When targeting LI consumers, manufacturers and retailers should plan

merchandise assortments introducing high to low price levels in nafional brand

and private-label footwear and develop point-of-purchase displays and in-store

promotions that focus on quality descriptors and construction features to

sfimulate interest in leather footwear for business wear. Low Involvement (LI)

consumers have been identified as spending a small amount of fime actively

seeking informafion about brands and comparison-shopping (Warrington & Shim,

2000; Jin & Koh, 1999). By concentrafing on making the shoe purchase process

easy and convenient for LI consumers, manufacturers and retailers may possibly

178

create more interest during the product evaluafion and purchase phases,

increase sales, and gain market share.

Recommendations for Further Research

This study extended the research in the area of market research with

respect to product involvement and product attributes associated with a fashion

related product category. Significant results were found in analyzing the

research questions through decision tree analyses. Further research could:

Sample

1. Replicate a study of similar design with more diverse consumers (e.g.

African-Americans, Hispanics). The findings would better reflect the

demographic population in the US.

Data Collection

1. Replicate a study of similar design in a different fime frame (e.g.

September, October, November). As the data were collected in June, July,

August, a fime period many employed consumers are involved in relocation and

vacation activifies and perhaps not as predisposed to answering and returning

mail surveys. Findings with a larger sample and higher response rate would

verify if the results could be generalized to a wider populafion.

179

Instrument Design

1. Test the proposed research questions with open-ended questions

eliciting free response data obtained from in-depth interviews and/or focus group

sessions. Findings would generate product attributes grounded in the

consumers' vocabulary and counteract quantitative bias associated with

preselected evaluative criteria and product attribute rating and ranking scales.

2. Replicate a study of similar design that includes the business casual

dress usage situation. Findings would better reflect current business wear trends

and render more accurate segmentation.

3. Assess the consumption patterns for footwear on a 7-point Likert-type

scale ranging from strongly agree (7) to strongly disagree (1), with a mid-point of

indifferent (4). A Likert-type scale would perhaps generate more accurate and

measurable responses.

4. Assess perceived product quality with open-ended questions regarding

what attributes contribute to the quality of leather footwear. Responses would

provide insight as to how consumers categorize footwear quality and reflect the

intrinsic and extrinsic criteria used to make quality judgments.

5. Assess comfort and construction with open-ended quesfions regarding

what product characteristics contribute to the evaluation of comfort and

construction of leather footwear. Responses would provide insight as to the

product features consumers consider as determinants of comfort and

construction in leather footwear.

180

REFERENCES

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APPENDIX A

AMERICAN CONSUMERS' QUESTIONNAIRE

193

- A 1998 STUDY OF AMERICAN CONSUMERS --

Each time you purchase footwear, you make decisions regarding where to shop, what style and color to buy, and how much to spend. This survey is being conducted as part of an educational endeavor, by research associates at Texas Tech University in Lubbock, Texas, to better understand Americans' purchase and consumption patterns for footwear worn for business wear. We would appreciate it if you could take about 15 minutes to fill out the survey completely.

This quesfionnaire is not designed to sell you anything or solicit money from you in any way! You are one of a very small number of consumers that are being asked to provide information about shopping for footwear. Your name was drawn from a random sample of consumers from the entire United States. So that the results accurately represent the activities and opinions of American consumers, it is important that each questionnaire be completed and returned. It is also important that you, the person to whom the quesfionnaire is addressed, are the person that completes the survey.

Participation is voluntary. You may be assured of complete confidentiality. The questionnaire has an identification number for mailing purposes only. This number is necessary so that we may check your name off of the mailing list when the questionnaire is returned. Your name will never be placed on the questionnaire.

There are no right or wrong answers. If you have any questions, please call Shelley Harp or Lori Yoo at (806) 742-1762. After you have completed the questionnaire, please return it in the enclosed, p re-ad dressed, postage-paid envelope on or before August 24,1998 to: Shelley Harp, Leather Research Institute, Texas Tech University, Box 41162, Lubbock, Texas, 79409-1162

If you complete and return this survey, and want to be entered in a drawing to win a $100 U.S. Savings Bond being given in appreciation to respondents, please complete the enclosed entry card and return it with the completed questionnaire.

Leather Research Institute Texas Tech University

194

CONSUMER FOOTWEAR PROFILE

2.

3.

How would you describe your clothing and shoe purchasing practices for business wear? (Circle only One response per statement)

strongly Strongly Agree Indifferent Disagree

I often try new fashion ideas before my co-workers 5 4 3 2

It Is important that the clothes I wear to work be of the latest styles

I like to try new and different places to shop for clothing-

When a new clothing store opens, I am among the first to visit it

In purchasing leather dress shoes, I feel that quality is highly important

In purchasing leather dress shoes, I feel that fashion styling is highly important

When purchasing leather dress shoes, I feel that comfort is highly important

How often do you wear leather dress shoes to work — per week? DAYS

How much do you usually pay for a pair of leather dress shoes you wear to work?

Dollars — on sale Dollars — at regular price

4. How many pairs of leather dress shoes for business wear have you purchased for yourself during the past 2 years?

Pairs at Retail Stores

How satisfied were you with the selection in the retail stores:

• 1. Very Satisfied • 2. Satisfied • 3. Somewhat Satisfied • 4. Somewhat Dissatisfied • 5. Dissatisfied • 6. Very Dissatisfied

Pairs from Catalogs

How satisfied were you with the selection in the catalogs:

• 1. Very Satisfied • 2. Satisfied • 3. Somewhat Satisfied • 4. Somewhat Dissatisfied • 5. Dissatisfied • 6. Very Dissatisfied

195

5. Do you have a favorite brand(s) of leather dress shoes?

• I.Yes 0 2. No

If Yes, what are your favorite brand(s) of leather dress shoes? (Check All that apply)

• 1. Ann Klein • 6. Florsheim a i l . Nine West • 2. Allen Edmonds • 7. Johnston & Murphy • 12. Stafford • 3. Coach • 8. Kenneth Cole • 13. Stuart Weitzman • 4. Cole Haan • 9. Liz Claiborne • 14. Worthington • 5. Dexter • 10. Naturalizer • 15. Other (Specify)

6. Which brand(s) of leather dress shoe(s) do you most often purchase for business wear?

Brand(s)

7. Where do you most often shop for leather dress shoes for business wear? (Check One)

• 1. Catalogs • 4. Factory Outlet Stores • 7. Other (Specify) • 2. Discount Stores • 5. Apparel Specialty Stores • 3. Department Stores • 6. Shoe Stores

8. Where do you most often purchase leather dress shoes for business wear?

Store/Catalog Name(s)

9. What would get you to purchase more leather dress shoes for business wear? (Check All that apply)

• 1. Better Quality • 3. Better Selection • 5. Better Comfort • 2. Lower Price • 4. Better Fit • 6. Other (Specify)

10. How would you rate your foot health? (Check One)

• 1. Excellent • 2. Good • 3. Fair • 4. Poor

11. What Is your shoe size? LENGTH WIDTH

12. Which part of your foot is difficult to fit? (Check All that apply)

• 1. Side Width • 3. Length • 5. Instep • 7. None • 2. Heel Width • 4. Arch • 6. Other (Specify)

196

13. When you purchase leather dress shoes for business wear what evaluative characteristics do you use to determine quality? (e.g. price, brand, comfort, etc) (List at least One but no more than Three.)

1 _ 2.

14. The following statements reflect people's opinions about shoes for business wear, the scales below and circle the number which indicates the degree of your agreement or disagreement with each statement. (Circle One number per single scale.)

Use

strongly

Disagree

Shoes for work are very important for me -

When I purchase shoes for work. It's not a big deal if I cannot wear them very often

I can really tell a lot about a person by the shoes he/she selects for work

I am very interested in the shoes I wear to work

It's really a problem If I buy shoes that are Inappropriate for my job

A purchase of shoes for work that doesn't perform well troubles me a great deal

The type of shoes that I wear to work is compatible with how I would like my co-workers to think of me

When I buy shoes for work, it's difficult to make a bad choice

Shoes that I wear to work help me express my personality

When purchasing shoes for work, I am never certain about my choice

I choose my shoes for work very carefully -

I can't say that 1 particularly like the type of shoes that I wear to work

The shoes I usually wear to work are the ones I enjoy the most

Strongly

Agree

7

7

7

7

6

6

6

6

Indifferent

4

5

5

5

5

4

4

4

4

3

3

3

3

2

2

2

2

2

2

197

Which shoes I wear to work matters to me a lot -

The type of shoes that I wear to work is compatible with how I like to think of myself 7 6 5 4 3 2 1

Purchasing shoes for work is rather complicated- 7 6 5 4 3 2 1

15. Listed below are factors one might consider when purchasing leather dress shoes for Dusiness wear. Use the scales below and circle the number which best reflects your thoughts (Circle One number per single scale.)

Not

Color-

Prlce-

Shoes in Wardrobe-

Fabrication (Fabric/Leather, etc.)-

Size

Durability-

Ease-of-Care-

Very

Important Important Important

Brand 7 6 5 4 3 2

7 6 5 4 3 2

Latest Fashion 7 6 5 4 3

198

2

Style 7 6 5 4 3 2

7 6 5 4 3 2

Attractiveness 7 6 5 4 3 2

Country-of-Origin 7 6 5 4 3 2

Construction 7 6 5 4 3 2

Hand-of-Leather (soft/smooth/etc.) 7 6 5 4 3 2

Versatility 7 6 5 4 3 2

Quality 7 6 5 4 3 2

Comfort 7 6 5 4 3 9

Retail Store / or Catalog-

Fit

7 6 5 4 3 2 1

7 6 5 4 3 2 1

16. The following statements reflect people's opinions about their shoe wardrobe for business wear. Use the scales below and circle the number which best reflects your preference with regard to your leather dress shoe wardrobe for business wear (Circle One number per single scale.)

To have a large number of shoes and wear them less often. 1 2 3 4 5 6 7

To have shoes that are basic in color and style. 1 2 3 4 5 6 7

To have a large number of shoes but of lower quality. 1 2 3 4 5 6 7

To have shoes that are very comfortable but less attractive.

To have a large number of less expensive shoes

To have shoes that are more durable but less versatile.

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

To have a small number of shoes and wear them more often.

To have shoes that are unique in color and style.

To have a small number of shoes but of higher quality.

To have shoes that are less comfortable but very attractive.

To have a small number of more expensive shoes.

To have shoes that are more versatile but less durable.

17. Listed below are characteristics one might consider when describing their feelings about leather dress shoes worn for business related activities. Use the scales below and circle the number which best reflects your feelings about the pair of leather dress shoes which you most often wear to work. (Circle One number per single scale.)

Conservative

Unfashionable

Comfortable

The leather dress shoes I most often wear to work are:

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

Casual

Fashionable

Uncomfortable

199

Contemporary

Inexpensive

Attractive

Basic in Color

Low Quality

Breathable

Hard to Care For

Versatile —

Familiar Brand

Natural —

Durable

Hard to the Touch

Well Constructed

Fit Well

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

1 2 3 4 5 6 7

Traditional

Expensive

Unattractive

Unique in Color

High Quality

Not Breathable

Easy to Care For

Not Versatile

Unfamiliar Brand

Not Natural

Not Durable

Soft to the Touch

Poorly Constructed

Do Not Fit Well

Please provide the following information about yourself and your household for use in statistically analyzing the survey data..

1. How many people, including yourself, currently live in your home? (Check One)

• 1. Live Alone • 5. Five or More

• 2. Two • 3. Three • 4. Four

2. How many children under age 18 currently live at home with you? (Check One)

• 1. None • 5. Four

• 2. One • 3. two • 4. Three • 6. Other - - record exact number

3. How many adults in your household are currently employed outside the home? (Check One)

• 1. None • 2. One • 3. Two • 4. Three or More

4. What is your present marital status? (Check One)

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• 1. Single, Never Married • 3. Separated • 5. Widowed • 2. Married • 4. Divorced Q 6. Cohabiting

5. What is your gender? (Check One)

• 1. Female • 2. Male

6. What Is your age? YEARS OLD

7. What is the highest education level that you have completed? (Check One)

• 1. Some High School • 5. College Graduate (B.S., B.A., etc.) • 2. High School Graduate • 6. Some Graduate Work • 3. Vocational / Technical School • 7. Graduate Degree • 4. Some College (M.S., M.A., M.B.A., Ph.D., Ed.D., etc.)

• 8. Other (Specify)

8. What is your present employment status? (Check One)

• 1. Employed ~ full-time • 4. Full-Time Student • 2. Employed ~ part-time • 5. Unemployed • 3. Full-Time Homemaker • 6. Retired

If employed, is this your first job? (Check One)

• I.Yes • 2 . No

How long have you been working in the business world? (Check One)

• 1.1-6 months • 4. 3-5 years • 7. Over 15 years • 2. 7-12 months • 5 . 6-10 years

• 3. 1 -2 years • 6. 10-15 years

9. Which one of the following categories best describes your current occupation? (Check One)

• 1. Professional or Technical (e.g. accountant, artist, specialist, engineer, lawyer, librarian,

nurse, scientist, teacher, technician, writer, etc.) • 2. Manager or Administrator • 3. Sales Worker (e.g. insurance, salesperson, realtor, stockbroker, etc.) • 4. Clerical Worker (e.g. bankteller, bookkeeper, cashier, office clerk, postman, receptionist,

secretary, teachers aide, etc.) • 5. Crafts Worker or Machine Operator (e.g. barber, bus driver, factory worker, tailor, etc.) • 6. Full-Time Homemaker • 7. Full-Time Student • 8. Service Worker (e.g. barber, bartender, dental assistant, hair stylist, nursing aide, police

officer, sales associate, waitress, etc.) • 9. Government or Military Worker • 10. Other (Specify your job title and briefly describe what you do)

201

10. Which of the following categories best reflects your employment orientation'? (Check One)

• 1. Career-oriented • 2. Just-a-job • 3. Plan-to-work

• 4. Stay-at-home

11. If you are not presently working, how long has it been since you worked? (Check One)

• 1.1-6 months • 2. 7-12 months • 3. 1-2 years • 4. 3-5 years

• 5. Over 5 years

12. In which geographical region do you live? (Check One)

• 1. Northeast • 3. Midwest • 5. Rocky Mountain • 2. South • 4. Southeast • 6. Pacific

13. Which of the following best describes the size of city or town you live in? (Check One) • 1. Less than 2,500 • 4. 50,000 - 74,999 • 7. 200,000 - 499,999 • 2. 2,500 - 9,999 • 5. 75,000 - 99,999 • 8. 500,000 or more • 3. 10,000 - 49,999 • 6. 100,000 - 199,999

14. What Is your race or ethnic background? (Check One)

• 1. American Indian / Native American • 4. Hispanic • 2. Asian / Pacific Islander • 5. Caucasian / Non Hispanic • 3. African American / Non Hispanic • 6. Other - - specify

15. Which of the following income categories comes closest to the total yearly income before taxes of all working members of your household? (Check One)

• 1. Under $15,000 • 5. $30,000 - $34,999 • 2. $15,000 - $19,999 • 6. $35,000 - $49,999 • 3. $20,000 - $24,999 • 7. $50,000 - $74,999 • 4. $25,000 - $29,999 • 8. $75,000 - $100,000

• 9. Over 100,000

YOUR CONTRIBUTION TO OUR RESEARCH IS APPRECIATED. PLEASE MAIL THE QUESTIONNAIRE IN THE SELF-ADDRESSED, STAMPED ENVELOPE ON OR BEFORE AUGUST 24TH, 1998. IF THE STAMPED, SELF-ADDRESSED ENVELOPE IS MISPLACED, PLEASE RETURN THE QUESTIONNAIRE TO:

SHELLEY HARP LEATHER RESEARCH INSTITUTE

TEXAS TECH UNIVERSITY

202

APPENDIX B

U.S. SAVINGS BONDS ENTRY FORMS

203

U. S. SAVINGS BONDS ENTRY FORM

To be eligible for the $100 U.S. Savings Bond drawing, you must return this entry form with your completed questionnaire. Winners will be notified by telephone and the savings bond will be fon/varded to you August 24, 1998. Please print the information below.

Name:

Mailing Address:

Telephone Number {_

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APPENDIX C

PRELIMINARY POSTCARD

205

Dear Consumer:

We are writing to request your participation in a research study designed to explore consumer footwear preference for business wear. Your cooperation will assist in completing our consumer profile.

In a few days you will receive a survey-booklet in the mail. Directions for completion will be included in the booklet. Participation will involve about 15 minutes of your time. Your assistance in helping us complete the consumer study is appreciated.

Sincerely,

Shelley Harp, Research Associate

Leather Research Institute Texas Tech University Box 41001 Lubbock, TX 79409-5300

206

APPENDIX D

REMINDER POSTCARD

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ATTENTION! ATTENTION!

Recently, a questionnaire seeking information about your footwear preference for business wear was mailed to you. Your name was drawn from a random sample of consumers in the U.S.

If you have already completed and returned the questionnaire, please accept our sincere thanks. If not, please do so today. Because the questionnaire was sent to a small, but representative sample of consumers, it is extremely important that you be included in the study if the results are to accurately represent the America consumer.

Thank you very much for your support of this research project.

Sincerely,

Shelley Harp, Research Associate

Leather Research Institute Texas Tech University Box 41001 Lubbock, TX 79409-5300

208

APPENDIX E

ANSWERTREE® SOFTWARE

209

AnswerTreeCB) 2.0 is a computer learning system that creates classification

systems displayed in decision trees (SPSS, 1998). A classification tree is a

statistical procedure that is used to predict or classify membership of cases in the

classes of a categorical dependent variable from the measurement on one or

more predictor independent variables. The AnswerTreeCB) system (a) provides a

way to examine data and discover important groupings of cases, (b) allows key

variables to be found that identify group membership, and (c) fomiulates rules for

making predictions about the group membership of new cases. The data for the

study were analyzed using AnswerTree®.

There are several statistical algorithms to use when a "tree structure" is

done. The current study employed a method called CHAID (Chi-square

Interaction Determinant Analysis). CHAID modeling is an exploratory data

analysis method used to study the relationships between a dependent measure

and a large series of possible predictor variables that themselves may interact.

The dependent measure may be qualitative (nominal or ordinal) or quantitative.

For qualitative variables, a series of chi-square analyses are conducted between

the dependent and predictor variables.

CHAID diagrams should be thought of as a tree trunk with progressive

splits into smaller and smaller branches. The initial tree trunk or root node is all

of the participants or fargef variables in the study (The target variable includes

two or more target categories). A series of pred/ctor variables are assessed to

210

see if splitting the sample based on these predictors leads to a statistically

significant discrimination in the dependent measure.

For instance, if the dependent measure (i.e., target variable) is HI and LI

consumers and the potential independent measures (i.e., predictor variables) are

footwear purchase criteria and footwear characteristics, the first step would be to

assess whether there were different levels of HI and LI (i.e., separately referred

to as a target category) for two or more nodes formed on the basis of one of the

predictor variables. The most significant of these predictor variables would

define the first split of the sample, or the first branching of the tree. Then, for

each of the new nodes formed, it would be determined if the node could be

further significantly split by another of the predictor variables. And so on. After

each split, the question is again asked if the new node can be further split on

another variable, so that there are significant differences in the dependent

variable. The result at the end of the tree building process is that there are a

series of nodes that are maximally different from one another on the dependent

variable. At each step, statistical tests are made to determine if a significant split

can be made.

The procedure for AnswerTree® using CHAID includes the following six

steps:

1. Determine the tree growing criteria: (a) growing method, (b)

target variable, (c) predictor variables, and (d) stopping rules.

Current study: The growing method used was CHAID, target

211

variable included 100 HI consumers and 101 LI consumers,

predictor variables were footwear purchase criteria (n = 19) and

footwear characteristics (n = 17), and the stopping rule was

when the number of cases in a node dropped below 20.

2. Grow the decision tree. Current study: Decision trees or charts

that illustrated decision rules were created for footwear

purchase criteria (see Figure 4.1) and footwear characteristics

(see Figure 4.2).

3. Validate the tree. To assess how well the tree structure

generalizes from the data at hand to a larger sample, three

validation options are available: (a) partitioning, (b) cross-

validation, and (c) random seed. Current study: The cross-

validation method was used to estimate the risk or number of

cases correctly classified. Cross-validation uses all of the data

to build the tree. The risk estimate is computed by partitioning

the data into k separate groups or folds (where k is specified by

the user). Next, k trees are built using the same growing criteria

as the tree being evaluated. The first tree uses all folds except

the first, the second tree uses all folds except the second, and

so on, until each fold had been excluded once. For each of

these trees, a risk estimate is computed, and the cross-

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validated risk estimate is the average of these k risk estimates

for the k trees, weighted by number of cases in each fold.

4. Calculate the gain summary for each decision tree. The gain

chart indicates which nodes in the tree have the highest (and

lowest) response or profit. A gain summary is determined for

each node for each independent variable. Current study: The

gain score for each node was computed as the proportion, i.e.,

probability of response, of cases in the node to the overall

sample. Gain summaries were determined for the 100 HI

consumers and 101 LI consumers (see Tables 4.19 - 4.22).

Information is displayed as Node-by-Node and Cumulative.

Cumulative gains or values are accumulated, so that each row

indicates value for cases in that group plus all previous groups

(see Tables 4.19 - 4.22). The cumulative statistics can indicate

where to find the category variable (i.e., HI consumers) by

considering the nodes with Index (%) scores of 100% or greater.

The response % reveals the percentage of HI (i.e.. Node: %)

reached by targeting the best node, then by including the

second best node, and so on until the response % reaches

100% (e.g., in Table 4.19, Node 16, 60.00% of HI can be

reached by targeting 31.98% of the market).

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To calculate a Node-by-Node gain summary, the following

definitions apply:

a. Node: Nodes are branches of the root node, fonning

rows for each predictor variable.

b. Node n: Total number of participants of target variable in

a node.

c. Node % = Node n - Target Variable (N = 201).

d. Response n: Number of participants belonging to the

target category in a node.

e. Response % = Response n -r Category Variable (HI =

100, LI = 101).

f. Gain (%) = Response n ^ Node n

g. Index (%) = Response % -r Node %

5. Calculate analysis summaries or identifying segment

characteristics for each node Index (%) scores of 100% or

greater (i.e., summary includes a description, starting with the

first row, or the nodes that lead to the node behind described).

Scores of 100% or greater have a higher response rate than the

overall target variable, scores less than 100% have a lower

response rate than the overall target variable. Current study:

Segment characteristics were determined for all nodes identified

as having Index (%) scores of 100% or greater for HI and LI for

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footwear purchase criteria and footwear characteristics (see

Tables 4.19-4.22).

6. Calculate profits from the decision trees. Retailers and others

using the AnswerTree® computer learning system can specify

profits for each of the outcomes. Gain scores can then be

expressed as profits, rather than probabilities of response.

Current study: The researchers used AnswerTree® to work

through steps 1-5 for HI and LI, using probability of response in

step 4.

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