THERESA NITHILA VINCENT,.pdf

A STUDY ON THE INFLUENCE OF PERSONAL VALUES ON THE SHOPPING STYLES OF YOUNG ADULTS TOWARDS PURCHASE OF APPARELS IN

BANGALORE CITY, KARNATAKA, INDIA

THESIS SUBMITTED TO THE BHARATHIDASAN UNIVERSITY, TRICHY

FOR THE AWARD OF THE DEGREE OF DOCTOR OF PHILOSOPHY IN COMMERCE

By

THERESA NITHILA VINCENT, M.Com, M.Phil

Under The Supervision and Guidance of

Dr(Mrs)D. CHRISTY SELVARANI, M.Com, M.Phil., MBA., Ph.D., Associate Professor & Research Advisor of Commerce,

Urumu Dhanalakshmi College, Trichy - 620 019.

PG AND RESEARCH DEPARTMENT OF COMMERCE, URUMU DHANALAKSHMI COLLEGE,

(AFFILIATED TO BHARATHIDASAN UNIVERSITY) TRICHY – 620 019

DECEMBER, 2013

Dr(Mrs)D. CHRISTY SELVARANI, M.Com, M.Phil., MBA., Ph.D., Associate Professor & Research Advisor of Commerce, Urumu Dhanalakshmi College, Trichy - 620 019

CERTIFICATE

Certified that the thesis entitled, “A STUDY ON THE

INFLUENCE OF PERSONAL VALUES ON THE SHOPPING

STYLES OF YOUNG ADULTS TOWARDS PURCHASE OF

APPARELS IN BANGALORE CITY, KARNATAKA, INDIA”, is a

bonafide record of work done by Mrs. THERESA NITHILA

VINCENT, under my guidance and supervision during the period

2010 – 2013.

This thesis represents independent work on the part of the

candidate.

Place:

Date:

(D. Christy Selvarani) SUPERVISOR

THERESA NITHILA VINCENT, M.Com, M.Phil. Research Scholar, Department of Commerce, Urumu Dhanalakshmi College, Trichy - 620 019

DECLARATION

I hereby state that the thesis for the Ph.D degree on “A STUDY

ON THE INFLUENCE OF PERSONAL VALUES ON THE

SHOPPING STYLES OF YOUNG ADULTS TOWARDS

PURCHASE OF APPARELS IN BANGALORE CITY,

KARNATAKA, INDIA”, is my original work and that it has not

previously formed the basis for the award of any degree, diploma,

associateship, fellowship or other similar title.

Place:

Date: (Theresa Nithila Vincent)

ACKNOWLEDGEMENTS

First and foremost, I thank God Almighty for His blessings and the Grace that he has given to me to complete this research work.

I record my deep sense of gratitude to my Research Guide Dr(Mrs)D. Christy Selvarani, M.Com, M.Phil., MBA., Ph.D., Associate Professor & Research Advisor of Commerce, Urumu Dhanalakshmi College, Trichy, for her wise guidance, useful suggestions and constructive criticisms. But for her invaluable help and sustained interest and encouragement, completing this work would have been impossible.

I'm grateful to Dr. S. Elango and Dr. Janet Rajakumari, the Doctoral committee members for their support and guidance throughout the course of this research work.

I am grateful to the Principal of Urumu Dhanalakshmi College, Trichy for granting permission and the constant encouragement provided for the successful completion of this research endeavour.

I express my sincere thanks to Dr. N. Subramani, Head, Department of Commerce, and all the faculty members of Urumu Dhanalakshmi College, Trichy for the necessary help extended to me during the research work.

I sincerely thank Ms. Saradha and Dr. P. Geeetha of Christ University for the support in statistical analysis of the data.

On a personal note, I deeply acknowledge and warmly appreciate the encouragement given right from the beginning by my husband, Mr. Vincent and my son Mervyn. I gratefully remember their patience, encouragement, support and understanding during the course of this research work. I am also grateful to my parents for their constant prayers.

I gratefully remember my colleagues, friends and well wishers whose support and encouragement helped me in completing this research work.

Theresa Nithila Vincent

CONTENTS

LIST OF TABLES i

LIST OF FIGURES v

CHAPTER NO. TITLE PAGE

NO.

1 INTRODUCTION 01

2 PROFILE OF THE STUDY AREA AND LEADING APPAREL RETAILERS IN BANGALORE, INDIA

30

3 REVIEW OF LITERATURE AND DESIGN OF THE STUDY

50

4 PERSONAL VALUES AND SHOPPING STYLES 101

5 ANALYSIS & INTERPRETATION OF DATA 119

6 FINDINGS, SUGGESTIONS & CONCLUSION 217

BIBLIOGRAPHY vi

APPENDIX

i

LIST OF TABLES

TABLE NO TITLE PAGE

NO

1 Age Structure Of India’s Population 5

2 Values Dimensions 27

3 Population Of Karnataka 34

4 Population Of Bangalore City [Urban] 35

5 Data Collection Locations 88

6 List of Values: LOV (Original)Kahle 1983 109

7 Description Of Consumer Decision-Making Style/ Traits 112

8 Consumer Styles Inventory CSI (original constructs) 113

9 Gender of Respondents 120

10 Education Level of Respondents 121

11 Regional Background of Respondents 122

12 Reliability Statistics for List of Values 124

13 Hierarchy of Values Important to Young Adults 125

14 Reliability Statistics for Value Dimensions 129

15 Hierarchy of Value Orientations in Young Adults 130

16 Reliability Statistics for Consumer Style Inventory 132

17 Preferred Shopping Style of Young Adults 135

18 Hierarchy of items under Perfectionist/High Quality Conscious style 138

19 Hierarchy of items under Brand Conscious/Price Equals Qualitystyle 139

20 Hierarchy of items under Novelty and Fashion Consciousstyle 139

21 Hierarchy of items under Recreational and Shopping Consciousstyle 140

22 Hierarchy of items under Price Conscious/Value for money style 141

23 Hierarchy of items under Impulsiveness/Careless style 141

24 Hierarchy of items under Confused by Overchoice style 142

25 Hierarchy of items under Habitual/Brand Loyal style 143

26 Intra-Correlations among Value Dimensions 144

ii

TABLE NO TITLE PAGE

NO

27 Intra-Correlations among individual Values 145

28 Intra-Correlations among Shopping Styles 146

29 Correlation between Values and Shopping Styles 149

30 Relationship between the value Sense of Belonging and Shopping Styles 150

31 Relationship between the value Simplicity and Shopping Styles 151

32 Relationship between the value Warm Relationships with Others and Shopping Styles 152

33 Relationship between the value Self-Fulfillment and Shopping Styles 153

34 Relationship between the value Being Well Respected and Shopping Styles 154

35 Relationship between the value Fun and Enjoyment of life and Shopping Styles 155

36 Relationship between the value Security & Comfort and Shopping Styles 156

37 Relationship between the value Self Respect and Shopping Styles 157

38 Relationship between the value Sense of Accomplishment and Shopping Styles 158

39 Relationship between the value Being Independent and Shopping Styles 159

40 Summary of Goodness-of-fit measures for the ‘Consumer Style Inventory’ used in the study - CSI 162

41 Relative Chi Square (CMIN/df) (Chi-square/Degrees of freedom) - CSI 163

42 Baseline Model - CSI 164

43 Parsimony-Adjusted Measures - CSI 166

44 Root Mean Square Error of Approximation (RMSEA) - CSI 167

45 Factors, standardized factor loading, AVE, CR and Coefficient Alpha for Shopping Styles - CSI 168

46 Summary of Goodness-of-fit measures for the ‘Value – Shopping Style’ measurement model - VSM 170

iii

TABLE NO TITLE PAGE

NO

47 Relative Chi Square (CMIN/df) (Chi-square/Degrees of freedom) - VSM 171

48 Baseline Comparisons - VSM 171

49 Parsimony-Adjusted Measures - VSM 172

50 Root Mean Square Error of Approximation (RMSEA) - VSM 172

51 Influence of overall values on the shopping styles of young adults towardsapparels 175

52 Influence of values on the ‘Perfectionist/High Quality Conscious’ shopping style 177

53 Influence of values on the ‘Brand Conscious/Price Equals Quality’ shopping style 178

54 Influence of values on the ‘Novelty and Fashion Conscious’ shopping style 179

55 Influence of values on the ‘Recreational and Shopping Conscious’ shopping style 180

56 Influence of values on the ‘Price Conscious/Value for money’ shopping style 181

57 Indicating influence of values on the ‘Impulsiveness/Careless’ shopping style 182

58 Influence of values on the ‘Confused by Overchoice’ shopping style 183

59 Influence of values on the ‘Habitual/Brand Loyal’ shopping style 184

60 Squared multiple correlations (R squared values) for Shopping Styles 185

61 Nature of Influence of Values on the Perfectionist/High Quality Conscious Shopping Style 186

62 Nature of Influence of Values on the ‘Brand Consciousness/Price Equals Quality’Shopping Style 187

63 Nature of Influence of Values on the ‘Novelty and Fashion Conscious’Shopping Style 188

64 Nature of Influence of Values on the ‘Recreational and Shopping Conscious’ Shopping Style 189

65 Nature of Influence of Values on the ‘Price Conscious/Value for Money’ Shopping Style 190

iv

TABLE NO TITLE PAGE

NO

66 Nature of Influence of Values on the ‘Impulsiveness/Careless’Shopping Style 191

67 Nature of Influence of Values on the ‘Confused by Overchoice’ Shopping Style 192

68 Nature of Influence of Values on the ‘Habitual/Brand Loyal’ Shopping Style 193

69 Differences in mean for shopping styles across gender 196

70 t test for shopping styles across gender 197

71 Differences in mean for shopping styles across Education Levels 199

72 ANOVA Indicating differences in shopping styles across education level of young adults 201

73 Differences in mean for shopping styles across Regions 203

74 ANOVA Indicating differences in mean for shopping styles across Regions 204

75 Differences in Mean for Value Orientations across Gender 206

76 t Test for Value Orientations across Gender 206

77 Differences in Mean for Value Orientations of Young Adults across Regional Background 208

78 ANOVA showing Value Orientations of Young Adults across Regional Background 209

79 Differences in Mean for level of influence of individual Values across Gender 210

80 t Test for Level of Influence of individual Values across Gender 211

81 Differences in Mean for level of influence of individual Values across Regional Background 213

82 ANOVA showing level of influence of individual Values across Regional Background 215

v

LIST OF FIGURES

FIGURE NO TITLE PAGE

NO

1 Map of India - States and Capitals 30

2 Bangalore City Map 33

3 The Value – Shopping Style Model 118

4 Gender Of Respondents 120

5 Educational Level of Respondents 121

6 Regional Background of Respondents 122

7 Path Diagram indicating the Value – Shopping Style Model Fit.

174

1

CHAPTER I

INTRODUCTION

THE INTERNATIONAL RETAIL MARKET ENVIRONMENT

The Global Retail Development IndexTM (GRDI) 20131 outlines some

important changes to the international retail environment. The report states that

developed-world retailing will face stagnant demand and tough price competition.

Emerging markets will enjoy faster growth as populations and incomes rise quite

rapidly.

There are opportunities for retailers seeking to grow and expand in fast-

growing developing markets such as South America, Brazil, Chile, and Uruguay.

The BRIC markets (Brazil, Russia, India, and China) remain as the magnificent

markets for global retailers.

By 2025, most retail investment will be in the developing world. Consumer

spending will be higher than in the developed world and modern retailing formats

will expand to meet the demand for branded, added-value and luxury goods and

services. Investment in modern retailing capacity will induce consumers to move

away from the traditional formats and will lead to increase in consumption2.

International retailers will have to reflect local needs and a significant core of local

retail business will remain.

The internet and social media will play an increasingly important part in

retailing as producers sell directly to consumers, although food and grocery will be

less affected. The integration of the virtual and physical worlds is fundamentally

changing consumers’ purchasing behaviours. There is a gradual diversion of sales

away from the high street and toward the internet. Multichannel shopping will

become more common, combining both internet and traditional shopping

approaches.

1The A.T. Kearney Global Retail Development Index (GRDI)™ 2013. 2 David Hurst, Andrew Black. (2011).The Changing Retailing Environment. International

Economics, IE WIT BP.

2

India was rated as the fifth most attractive emerging retail market in the

Global Retail Development Index of 30 developing countries in 2012. However, the

2013 GRDI places India in the 14 position. India’s Growth has slowed down, but it

is still strong. The global slowdown hasn't spared India, whose GDP growth rate

slipped to 5 percent, down from a 10-year average of 7.8 percent. Same-store sales

volume growth slowed in 2012 across retail, particularly for lifestyle and value-

based formats.

However, the long-term fundamentals remain strong for India, in particular,

the large, young, increasingly brand- and fashion-conscious population.

THE INDIAN RETAIL MARKET ENVIRONMENT

The Indian retail market is the fastest growing sector in the Indian economy

that accounts for 14 -15 percent of its GDP3. It offers tremendous potential to the

modern marketer. A number of changes have taken place on the Indian retail front

such as increasing accessibility of international brands, increasing number of malls

and hypermarkets and easy availability of retail space.

The India Retail Industry is gradually inching its way towards becoming the

next boom industry. The total concept and idea of shopping has undergone a radical

change, in terms of format and consumer buying behaviour, ushering in a revolution

in shopping in India. Indian consumers are demonstrating an increasing interest in

online shopping. The growing online retail market has become a very lucrative

business for international majors entering Indian markets. India has surpassed Japan

to become the world’s third largest Internet user after China and the United States.4

The trend is not only catching up in metros, but in smaller towns and cities as well.

The key factors in the growth of the organized retail sector in India can be

attributed to a large young working population with median age of 24 years, nuclear

families in urban areas and emerging opportunities in the services sector.

The future of the India Retail Industry shows promising growth of the market with

3http://en.wikipedia.org/wiki/Retailing_in_India 4Retail Industry in India. (2013). http://www.ibef.org/industry/retail-india.aspx

3

the government policies becoming more favourable and the emerging technologies

facilitating operations.

In 2012, India's retail sector reached an important landmark: The government

allowed 100 percent foreign direct investment in a single brand for the first time. In

multi-brand retail, the government allowed 51 percent FDI starting in early 2013.

This has opened the doors of the retail sector to international players that comes with

increased benefits to the consumer such as quality products and premium brands and

a boost to the economy. However, there are preconditions about investment,

sourcing, store locations, and state government approval.

Purchasing power of Indian urban consumer is growing and branded

merchandise in categories like Apparels, Cosmetics, Shoes, Watches, Beverages,

Food and even Jewellery, are slowly becoming lifestyle products that are widely

accepted by the urban Indian consumer. Indian retailers must recognize the value of

building their own stores as brands to reinforce their market positioning, to

communicate quality as well as value for money. Sustainable competitive advantage

will be dependent on projecting core values of the organisation in their retail brand

strategy combining products, image and reputation.

As per industry survey about 70 per cent of the retail consumption is

contributed by smaller towns of India. The youth in these pockets, generally try to

connect and get inspired by urban lifestyles and trends. The onset of the mall culture

in the smaller towns is opening up new avenues for the consumer to discover and

adapt to the new trend. These markets are still untapped and open up a plethora of

marketing opportunities. The semi-urban youth is equally digital savvy and in fact

their level of involvement with the digital medium is higher than youth in bigger

cities. Their contribution to e-commerce is more than their metro counter-parts.

4

TEXTILE & APPAREL RETAIL SECTOR IN INDIA5

India is the world’s second largest producer of textiles and garments after

China. The potential size of the Indian textile and apparel industry is expected to

reach US$ 221 billion by 2021, according to Technopak's Textile and Apparel

Compendium 2012. The textile and apparel industry is one of the leading segments

of the Indian economy and the largest source of foreign exchange earnings for India.

This industry accounts for 4 percent of the gross domestic product (GDP), 20

percent of industrial output, and slightly more than 30 percent of export earnings.

The textile and apparel industry employs about 38 million people, making it the

largest source of industrial employment in India. The growth and all round

development of this industry has a direct bearing on the improvement of the

economy of the nation.

Apparel is the second largest consumption category in malls.6 According to the

NCAER study,7consumers in India spend approximately nine percent of their

disposable income on clothing and footwear, compared to five percent for clothing

and shoes in the United States. Clothing expenditures in India tend to be relatively

higher for households with higher incomes.

There is a growing shift in preference towards Western clothing and branded

products, particularly across Tier I cities. Recognizing this, global brands are

making their mark and increasing their presence in India, whilst at the same time;

regional local brands are also increasing their competitive presence. The increasing

disposable incomes across key cities, comfort fitting and rich appeal are the major

factors that are expected to drive the apparel market towards long-term growth.

Apparel companies are expected to branch out to Tier II and Tier III city outlets

across India, which represent as yet an untapped market for branded apparel.

5http://www.ibef.org/industry/textiles.aspx, May 2013; and http://www.researchandmarkets.com/

reports/688195/textile_and_apparel_sector_in_india. 6Jaya Halepete, K.V. Seshadri Iyer. (2008). Multidimensional investigation of apparel retailing in

India.Emerald 36. 7Indian Demographics Report 1998

5

International apparel brands such as Zara, Mango, Arrow and Diesel are

increasing the presence of global brands in India. Certain local players such as Black

Bird, F Square, Ramraj and Mustard have also strengthened their presence in

southern India and provide tough competition to the national and international

brands. These brands are also expanding their base to other parts of India to become

national players8.

The major consumers of the Indian Apparel Market are the young adult

population. According to current estimates, India is one of the youngest countries in

the world in terms of its age structure. More than 50% of India's current

population is below the age of 25 and over 65% is below the age of 35. The table

given below presents the age structure of the population of India.

TABLE: 01

AGE STRUCTURE OF INDIA’S POPULATION

India Population Current Population of India in 2013 - 1,270,272,105 (1.27 billion)

Age structure

(2012 est.)

0-14 years: 29.3% (male 187,386,162/female 165,345,284)




65 years and over: 5.6% (male 31,892,823/female 35,225,003)

Source: http://www.indexmundi.com

The above table gives the estimated youth population structure at the all

India level during 2012. The numbers have changed since and apparently the size of

the youth population has grown tremendously. The population in the age-group of

15-34 increased from 353 million in 2001 to 430 million in 2011. Current

predictions suggest a steady increase in the youth population to 464 million by 2021

and finally a decline to 458 million by 2026.9

8Apparel in India, Euromonitor International. 2012 9The Hindu, April 17 2013.

6

By 2020, India is set to become the world’s youngest country with 64 per

cent of its population in the working age group. It is estimated, the average Indian

will be only 29 years old, compared with the average age of 37 years in China and

the United States, and 45 years in west Europe and Japan. With the West, Japan and

even China aging, this demographic potential offers India and its growing economy

an unprecedented edge that economists believe could add a significant 2 per cent to

the GDP growth rate and result in a massive and growing labour force which will

deliver profound benefits in terms of growth and prosperity.

This massive youth population provides an enormous consumer base for

marketers. Changes in the consumer patterns of young adults started happening with

the increase in availability of malls, cafés and increased disposable income; these

factors have changed the way youth today conduct themselves and manage their

funds. The changing profile of the young adult population is evident in the economic

independence displayed and the disposable income in their hands.

PRESENT DAY YOUNG ADULTS IN INDIA

Youth are emerging as digital shoppers as their comfort level with

technology is incredibly high. It is perceived that young adults feel handicapped

without technology10 and that the internet is providing young people with a platform

to carry out increasing portions of their offline life with regard to searching, seeking

information, creating content and using these inputs to shop online.

Today’s young consumer has developed a strong taste for shopping online. A

study by Microsoft Advertising and Aegis Media reveals that 2011 was a year of

‘digital shoppers’ in which at least 48 per cent of online shopping decisions were

spontaneous. The U’th Time Integrated Media Services quoted that “The primary

source of traffic for online shopping (and other e-commerce portals) plus social

media activity are young consumers (in the age group of 13 to 25). As a result, the

number of online shopping platforms has increased and expanded dramatically over

the last few years. People in the age group of 18-25 comprise a significant share of

10 Microsoft Advertising’s Pre Family Survey 2011

7

sales on these websites. There is also an increasing trend of repeat buying in this age

group. It has now become a regular practice for the young consumer to search for

customer reviews on the web, blogs, consumer forums and other social media

websites to gather insights before purchasing anything. Facebook has become the

most popular source for almost all information.11Prior to purchase what they

consider as assets, such as bikes, cars, mobile phones, branded apparels, etc., they

will search reliable information over internet. They discuss with peer-opinion

leaders among their friendship circle, listen to the experiences (related to that

product) of their close friends, check the credibility of that product in media

(advertisements and promotions) and then convince parents to access the product.

The family and parents are becoming more dependent on the younger members of

the family to take the purchase decision if the product is related to lifestyle and

fashion.

Extensive research is undertaken by young adults on the web about the

company, the quality of customer service, and the kind of products a retailer offers.

The young consumers do not end the purchase process after they acquire the

product, but voice their opinion on the web through various forums, social networks

and viral mail. They are even reactive enough to load a video on YouTube if they

find a fault in the product and these videos are considered to be more reliable and

credible (virally spread by the peer-network) to their peers against the brand or

product.

The young generation trusts friends and alternative media as the major

source of information before taking any decision. They consult each other a lot

more, critique instantly and voice their opinions to the world. Numerous brands,

both from India and outside, have made them spoilt for choice as they are faced with

a bewildering plethora of options in everything they do. And this unlimited choice

also makes them more demanding of a brand, from a brand’s perspective. They want

better quality, more value-for-money, superior experience and more.

11http://pitchonnet.com/blog/2012/08/21/ how-well-do-indian-marketers-understand-the-Indian-

youth/Pallavi Srivastava and ArshiyaKhullar

8

Globalisation and the opening up of the Indian economy have introduced the

Indian society to new cultural and social norms. However, this process has not

eradicated traditional Indian values and beliefs. Young people in particular want the

best of both worlds.

A recent survey by INgene Insights Consultancy reveals that India’s youth

has high respect for their parents for how they have struggled and achieved success

in spite of minimal career options available during their time. Moreover, they have

revealed that their aspiring icons in life are not any celebrity but their father or older

brother(s). Parental authority has considerable leverage in the life of most Indian

youth, though variations are due to education and socio-economic status. The youth

prefer to remain within the cultural codes of their family and social networks. The

vociferous individuality of the Western youth is not present among Indian youth

who are more embedded, and content to be, within the institution of the family. The

family remains a key institution in the life-world of Indian youth.

Dressing up in the latest styles is an important facet of self-expression held

by the youth. Though the modern youth do not run after designer clothes, their

wardrobes are up to date. While, for a casual gathering they might choose to wear

jeans and a branded T-shirt, for more formal occasions they prefer a traditional

dress: the girls will wear saris, while the boys don a sherwani.

Urban India today represents a combination of the traditional and the

modern. In a number of areas, modern values and practices are taking over.

Materialism is increasing; young people today understand the value of money and

believe that India must become a part of the global marketplace to ensure its future

economic success.

Young Adults in Bangalore

A demographically diverse city, Bangalore houses people of different

cultures and it comprises of a dynamic blend of young adults, belonging to various

religions, castes and communities who speak many languages. This diversity of

young adults of Bangalore represents the whole of India. Hence the general profile

9

of the young adult population of India holds good for the city of Bangalore.

Bangalore’s standard of living is better than in other metros. Hence, Bangaloreans’

life-style exhibits high level of brand awareness/consciousness.

Young Adults in Bangalore have information at their finger tips. They are

innovators of new products and trends and are early acceptors of change. This

segment is image conscious and places importance on keeping physically fit. They

are experiential; enjoy the arts and events from music concerts. The young adults

place significant importance on their community and friends. The advent of the

internet enables the youth to communicate with a number of people at one time and

therefore, friends could even include people they haven’t actually met before in

person. The young adult market is extremely media-savvy; they are cynical and

untrusting of advertising and marketing promises. They desire instant interaction

and gratification and they have a short attention span. There is a need to “belong”

and have “control,” they want to feel empowered, confident and independent.

A survey conducted by Hindustan Times and CNN-IBN in 2011 (carried out

by MaRS – Monitoring and Research Systems) on the population aged between 18-

25 years, spread across 18 major cities in India has revealed some very interesting

statistics and reflection of the mindset that youth in a city share. Contrary to what

many believe, majority of the youth do have the habit of saving as the report

suggests. Going by each city, the youth in Bangalore (64.2%) and Mumbai (62.8%)

spend the most. This could also be due to the assumption that they earn/get more

money than their counterparts in other cities. Most of the spending of the sample

population is on mobile phones (39.6%), food (22.6%) and clothes (22.6%); then

come movies (6.2%), personal grooming (4.6%), gifts (1.5%), and sports and gym

(0.7%) coming in with least spending percentage.

The young adult population in Bangalore mostly comprises of college-going

students and young IT professionals. Many of them are migrants to Bangalore for

the purpose of education or employment. Being away from home and on their own,

they have a weekend culture to visit the malls in the city for shopping, watching

10

movies and eating out. They possess a fairly good disposable income and studies

show that spending culture is quite high among them.12

YOUNG ADULTS SHOPPING BEHAVIOUR

Young adults are recognized as a specialized consumer segment for

marketers for many reasons. They are eager to consume and they are conscious of

their experience.13 The young adults within a family often influence the family

purchasing decisions.14 They are recognised as trend setters who influence

consumption change within other market segments. Young people are able to

influence the purchase and decision-making of others.15 At the period of transition

from adolescence to early adulthood, the young adolescents seek to establish their

own individual identity and form behaviour patterns, attitudes, values. They set their

own consumption patterns that extend to their old age. They make purchases to

define themselves and to create an identity of their own making.16 Many of these

patterns are carried well into individuals’ lifetimes.17 They act as agents of change

by influencing the society and culture.18 And from a marketing perspective, young

adults are considered as a market segment that forms a powerful consumer spending

group in their own way.

Globalisation and the subsequent opening up of the Indian economy have

introduced the Indian society to new cultural and social norms. New trends in

fashion, culture and lifestyle are emerging. The increasing reach of satellite

television and the rise in Internet usage has helped to facilitate the spread of these

12Hindustan Times Youth Survey 2011 13Sproles G.B. & Kendall, E.L. (1986).A methodology for profiling consumers’ decision-making

styles.Journal of Consumer Affairs, 20 (2), 267-279 pp. 14Turk, J. L. and N. W. Bell. (1972). “Measuring power in families.” Journal of Marriage and the

Family 34:215-223 pp. 15Grant, I. C. & Waite, K. (2003).Following the yellow brick road - young adults’ experiences of the

information super-highway.Qualitative Market Research: An International Journal, 6 (1), 48-57 pp.

16Holbrook, M. & Schindler, R. M. (1989).Some explanatory findings on the development of musical tastes.Journal of Consumer Research, 16 (1), 119-124 pp.

17Moschis, G. P. (1987). Consumer socialization: a life cycle perspective. Lexington Books. 18Leslie, E., Sparling, P. B. & Owen, N. (2001). University campus settings and the promotion of

physical activity in young adults: lessons from research in Australia and the USA. Health and Education, 101 (3), 116-125 pp.

11

new trends among young people. The younger generations have become more

independent and have accepted new ideas from western cultures.

Young adults attach great meaning to their appearance, and while shopping

for clothes they make their own decisions that will directly affect their appearance.19

The clothes they select become a means for communicating and enhancing

personality, attractiveness and allow them to belong to specific groups.20 Shopping

for apparels is an important part of the overall life pattern for this segment. Apparels

are important for young adults because they can augment social appreciation and

develop a positive self-esteem via their appearance. They are the ultimate decision

makers for the apparel products they consume, even if they are influenced by their

parents or friends.

Though apparently the young adults all over the world display similar

characteristics, a deeper examination reveals the finer differential qualities which are

vital and often ignored while targeting this group as a valued consumer base. While

targeting young adults to sell their product, most fashion retailers in India blindly

follow the trends of U.S.A or Europe without prior survey and understanding,

expecting the Indian young consumer to exhibit similar preferences. These efforts

are unsuccessful.21

The buying behaviour of young adults involves a complex decision-making

process that is influenced by various external factors such as family, peer group,

society, culture and internal factors such as values, motives, perception, attitudes

and life-style. A predominant influencing factor among these is the basic value

system that is imbibed in them from their cultural background and parental

upbringing. Values are also formed through peer group interactions, educational

background and social media.

19UlunAkturan&NurayTezcan (2007).Profiling young adults: decision-making styles of college

students for apparel products. 6ème Journées Normandes De Recherche Sur La Consommation : Société Et Consommations 19-20 pp. Groupe ESC Rouen.

20Tatzel, M. (1982). Skill and motivation in clothes shopping: Fashion-conscious, independent, anxious, and apathetic consumers. Journal of Retailing, 58(4), 90-97 pp.

21KaustavSengupta. (2008). INgene Insights Consultancy.

12

APPARELS - A REFLECTION OF PERSONALITY

It is an universal belief that ‘Clothing Makes the Man (or Woman)’ perfect.

Clothes or apparels are an epitome of a culture. It is the symbol of expression of an

individual’s personality, social status, tastes and preferences, and lends to create

impressions about the wearer. People in different parts of the world have their own

style of dressing which symbolize their culture and status.

In today's diverse and dynamic societies, there is probably no other sphere of

human activity that reflects an individual’s values and life-styles better, than the

apparels that he/she chooses to wear. The dress of an individual is a kind of “Sign

Language” that communicates a complete set of information and is usually the basis

on which immediate impressions are formed. Apparel is a form of artistic expression

that reflects the cognitive, moral and social aspects of human life.

Apparels are worn in a public space. Therefore, it can be said that apparels

contribute to a person's identity as a man or woman.22Apparels articulate meaning

and facilitate construction of identity.23 People form initial impressions of others on

the basis of their physical attributes and observable behaviours.24 Observers can

form judgments based on a person’s conscious clothing decisions or behavioural

residue that reflects one’s personality. In today's multifaceted societies, apparels

deter as well as facilitate communication between highly disjointed social groups.25

Choice in apparels is regarded as claims of individuality that could be self-

directed or other-directed, i.e, individuals may choose apparels that reinforce their

identity or communicate their attitudes and values to others. An individual’s apparel

choices may consciously and unconsciously reflect elements of his or her

personality traits.

22Linda B. Arthur. (1999). Religion, dress and the body. Paperback.Berg Publishers. 23Crane, D. (2000). Fashion and its Social Agendas: class, gender, and identity in clothing. Chicago:

University of Chicago Press, 294 pp. 24Laura P. Naumann, 2009; Express yourself: Manifestations of personality in clothing and

appearance; The University of Texas at Austin. 25Crane, D. (2000) Fashion and Its Social Agendas: Class, Gender and Identity in Clothing,

University of Chicago Press, 294 pp

13

Clothing patterns may be regulated within the peer group by some unwritten

rules. Certain styles and colours of clothes may be approved or disapproved by the

group. Members of the group are expected to follow the group’s trends and even

pressured to dress in the same way. This is referred to as the “peer pressure”.

Clothing that does not conform to the group’s standards and expectations may be

criticized. Sometimes the pressure is gentle and serves just as a source of inspiration

for others. But it can also be strong and cruel, forcing people to either conform or

risk being excluded from the group26.

In western countries such as the United States and the United Kingdom,

culture dictates that youngsters are independent from an early age. They form their

own opinions and decide independently in all matters concerning their lifestyle.

They take independent decisions without consulting their parents and are responsible

and accountable for their actions. They belong to a free society and do not conform

to traditional values/culture in the manner of dressing or choosing clothes.

In countries like Saudi Arabia, Iran and Iraq, cultural traditions and religious

beliefs require people to strictly adhere to the specified norms. The community’s

values and beliefs strongly influence the choice of apparels worn by young adults of

these communities.

India is a country with rich cultural heritage and highly respected value

systems. The joint family system, which is a fundamentally conservative institution,

has given room for the more liberal nuclear family system. This transition has not

eradicated traditional Indian values and beliefs. The family remains a key institution

in the life-world of the Indian youth. Parental authority has considerable leverage in

the life of most Indian youth and they prefer to remain within the cultural codes of

their family and social network.27 Dressing up in the latest styles is an important

facet of self-expression strongly held by the Indian young adult segment. While for a

casual gathering they might choose to be dressed in jeans and perhaps a trendy T-

26Asma Kiran et. Al. (2002). Factors affecting change in the clothing patterns of the adolescent girls;

International Journal Of Agriculture & Biology 1560–8530/2002/04–3–377–378 pp. 27KaustavSengupta. (2008) .INgene Insights Consultancy.

14

shirt, for more formal occasions they prefer a traditional dress that conforms to the

norms, beliefs and value systems of the society.28

PSYCHOGRAPHIC SEGMENTATION OF THE YOUNG ADULTS'

CONSUMER MARKET

Every person in this world is a consumer of an incredible variety of goods

and services. However, each individual has different tastes, likes and dislikes and

follow diverse behavioural patterns while making purchase decisions. Gaining

knowledge of the consumer decision making process is the greatest challenge that

the marketers face world over.

Marketers adopt different strategies to kindle the interest of the consumer

and motivate them to act positively towards their product offerings. These

motivations are referred to as stimuli as they stimulate the buying desire in the

consumer. There are different marketing stimuli that reach consumers every day

which affect them at different levels and dimensions. There are marked behavioural

differences among consumers in the way in which they respond to these stimuli.

Some may prefer the brand, some may look at the price, some may buy the product

for prestige or status and some may respond to the advertisement. Although

marketers recognize the need to understand the differences in consumer behaviour,

rarely do they go beyond the demographic diagnosis of their consumers.

Usually the market is segmented on the basis of demographic variables such

as age, gender and income which fail to capture the complete characteristics of the

consumers. The problem is that even though individuals in a specific demographic

category share some common characteristics, the psychographic characteristics like

values, motivations and beliefs of these groups are not homogeneous.

Psychographics segmentation, based on consumer attitudes, opinions and

values, is a realistic approach that allows the marketer to look at their clients as real

people or entities, and understand how they feel, think, react and evaluate. While

demographic segmentation aims to group the market based on its similarities,

28Voices and Visons from India, 2004 © Commonwealth of Australia

15

psychographic segmentation helps to understand how people are different. The

consumers in the same demographic segment possess different psychographic

characteristics.

Psychographic segmentation helps the seller to determine how they must

approach customers belonging to a particular segment. 29Such segmentation offers

greater worth of the product for the customer. As a consequence, it generates greater

degree of customer satisfaction and customer loyalty, resulting in higher amount of

customer retention. For the marketer, psychographic segmentation helps to increase

the brand value of the company in the eyes of the customer and gives better inputs

for the design of new products that the customer would prefer. In the long run, the

company spends lesser amount of money on marketing as it is easier to target a

specific type of customer base. Thus, a psychographic approach in understanding

consumer behaviour would provide marketers with a distinctive competitive edge in

reaching their customers.

The common psychographic variables are attributes relating to personality,

values, attitudes, interests, and lifestyles. Among these, personal values play an

important role in understanding consumer behaviour as they are more central to an

individual's cognitive system. Marketers, fashion researchers and retailers should

understand how values influence the consumer behaviour and devise marketing

strategies to promote the sales of their product.

Values are commonly regarded as the most deeply rooted, abstract

formulations of how and why consumers behave as they do. Values exert a major

influence on the consumer’s decision making in any situation where a conflict of

choice exists. It is widely accepted that choice criteria are based on an individual's

social values. Personal values are acknowledged as an underlying determinant

29Narang, R. (2010). Psychographic segmentation of youth in the evolving Indian retail market. The

International Review of Retail, Distribution and Consumer Research Vol. 20, No. 5, December 2010, 535–557 pp.

16

of consumers' attitudes and behaviour.30 A significant number of researchers suggest

that values affect various aspects of consumer behaviour and attitudes.31

Values can therefore be said to be mental images that affect a wide range of

specific attitudes. These in turn influence the way a person is likely to behave in a

specific situation, e.g. purchase of new apparels: the evaluation, choosing among

alternatives and finally paying for a particular type of apparels, is largely a function

of core cultural beliefs and values. Values are passed on from parents to children

and are reinforced by the major institutions of society such as schools, business and

government, the mass media, reference groups, etc.32

While connotation differs, there appears to be a general agreement that

values influence consumer behaviour. The purchasing behaviour of the customer

reflects the actions which are based on a consequential relationship between his/her

values and consequential wants and actions.33

30Homer and Kahle.(1988). A structural equation test of the value-attitude-behaviour hierarchy.

Journal of Personality and Social Psychology, 54, 638-646 pp. 31Becker and Connor.(1981).Personal values of the heavy user of mass media. Journal of Advertising

Research, 21, 37-43 pp. 32Lawan, A. Lawan, Ramat Zanna. (2013). Evaluation of socio-cultural factors influencing consumer

buying behaviour of clothes inBorno State, Nigeria; International Journal of Basic and Applied Science, Vol 01, No. 03, Jan 2013, pp. 519-529 pp.

33Kaže, V. (2010).Paradigm shift in consumer segmentation to gain competitive advantages in post-crisis FMCG markets: Lifestyle or social values? The Journal of Economics And Management, 16, 1266-1273 pp.

17

NEED FOR THE STUDY

Apparel manufacturers spend millions in marketing research every year trying to

envisage the changing consumer behaviours. Insight into the consumer buying

behaviour or their decision-making process would help firms and organizations to

improve their marketing strategies by understanding the psychology of how

consumers think, feel, reason, and select between different alternatives; and how the

consumer is influenced by his or her value systems.

A three dimensional marketing strategy is required to ensure success and earn

returns on the investments made by marketers. Firstly, the need is to identify the

most promising target group of consumers for its products. Secondly, the market

must be segmented appropriately. Marketers should move from demographic

segmentation towards psychographic segmentation of the target consumers. Thirdly,

marketers must identify the product categories most preferred and used by the target

group.

The most promising target group of consumers in India are the young adults

due to its demographic dividend. India is considered as the world’s youngest country

in terms of its age structure. Recent studies on demographic profile of India’s

population reveal that more than 50% of the Indians are aged below 25 years and

more than 65% fall below the age of 3534. This indicates that the youth population in

India is a significant proportion of the total population and is emerging as a powerful

consumer segment especially for lifestyle and luxury products.

This predominance of youth in the population is expected to last until the year

2050. The "BRIC Report" (Brazil, Russia, India, China) by Goldman Sachs predicts

that the economies of Brazil, Russia, India and China would become larger forces

over the next 50 years The report states that India's economy could be larger than

Japan's by the year 2032 and that India could show the fastest growth in the next 30

34En.Wikipedia.org

18

years. This demographic potential offers India and its economy an unprecedented

edge, which is a significant competitive advantage.35

Young people in India have emerged as a significant target for many Indian and

foreign apparel companies. The existence of a huge young adult audience who

possess an insatiable requirement for fashion clothing gives tremendous scope for

clothing manufacturers, designers and marketers for business expansion, increased

revenues, higher profits, while at the same time the prevalence of multi-brands

provides tough competition.

The understanding of factors that influence the purchase of global and local

brands among the Indian young adult consumers will help the new retailers, both

domestic and foreign, who want to enter into the Indian market. The companies will

be in a position to understand the complexities of Indian consumers and customize

their products to have the right mix to meet the requirements and extract benefits

from the growing Indian market.

Apparels are one of the most preferred product categories where young adults

also have the authority to make independent buying decisions. It is important to

study the purchase behaviour of young adults towards apparels, because apparels are

the most frequently purchased item by young adults and they become trendsetters

and opinion leaders.36 Whatever young adults do today foreshadows what older

demographic groups will follow in the near future.

As young consumers are an important target group for apparels, it is

necessary to identify the factors that influence the apparels purchase behaviour.

Very less literature is available to know about what this consumer segment looks for

while considering apparel brands. Understanding this large segment appropriately is

crucial for apparel manufacturers and marketers as they promise longevity of market

and exert substantial influence on their parents’, peers as well as their own spending.

35The Hindu, April 17 2013. 36 S.M. Noble et al. (2009). What drives college-age Generation Y consumers? Journal of Business

Research 62, 617–628 pp.

19

In order to understand the influencing factors for purchasers of apparels among

Indian young adults, there is a need to understand their psychographic profiles so

that it becomes easy for the marketers to reach out to them or to target and position

themselves more appropriately. In India, psychographic profiling of consumers is

still in the stage of infancy. There is negligible information available in the public

domain regarding the psychographic profile of the Indian youth in the context of the

changing retail environment.37

It is imperative that a psychographic study be conducted by apparel

manufacturers and marketers to devise more effective strategies to tap this

segment.38 Further, the changing psychographic profile of young adults makes it

even more crucial for a continuous longitudinal study to keep track of changes and

incorporate them in the art of marketing.

Information on young-adult consumers’ decision-making style will be of

much use for organisations targeting Indian markets. Regardless of the fact that the

majority of the young adults are college students who are unemployed and their

earning comes mainly from educational loans and parental contributions, young

adults represent an extremely large and important market segment for many

products and services. They are seen as a lucrative market since they have higher

than average lifetime earnings and are just beginning a major transition period which

is a key time to change previous behaviours.39 Apparel manufacturers and marketers

are keen to target this group because they perceive them as potential loyal customers

both currently and in the future.40

The present study analyses the young adults’ shopping styles for apparels

from a psychographic perspective where values are considered as the underlying

trigger for specific purchase decision-making style. Apparel products are chosen

37Narang, R. (2010). Psychographic segmentation of youth in the evolving Indian retail market. The

International Review of Retail, Distribution and Consumer Research Vol. 20, No. 5, December 2010, 535–557 pp.

38Srivatsa, H.S R. Srinivasan.R. (2007). Banking channel perceptions; An Indian youth perspective 39Warwick, J., P. Mansfield. (2000). Credit card consumers: College students' knowledge and

attitude. Journal of Consumer Marketing 17(7):617-626 pp 40Speer, T. (1998).College come-ons. American Demographics, 20 (3), 41-45. And, Feldman, J.

(1999).Back-to-school buying guide. Money, 28 (9), 165-168 pp.

20

because they are perceived as aesthetic, symbolic products tied to self-presentation.

Knowledge of apparel shopping behaviour will give significant input to develop

and/or test theories of shopping behaviour and could guide future research.

STATEMENT OF THE PROBLEM

The young adult population in India is emerging as a powerful consumer

segment. Understanding this crucial segment in depth is important to develop

specific marketing strategies for business sustainability. The challenge faced by

apparel manufacturers and marketers is to understand the young adults’ buying

behaviour to capture their attention and convert them into consumers who are brand

loyal.

Generalizing the youth segment is a common mistake done by many

manufacturers. Some apparel manufacturers have a tendency to dis-regard the young

adult segment on the assumption that such customers are not brand loyal. Proof for

this is uncertain. On the other hand, there are also those who argue that the purchase

habits developed during the young adult phase can remain with consumers for many

years after.

While this segment is a potentially lucrative target for many apparel

manufacturers and marketers, it is also complex and must be examined carefully.

Young adults perhaps form the most difficult demographic group to communicate

with. Not only they have a short attention span, they are also hard to describe in

terms of media consumption; they are inconsistent in brand preference, and it is

extremely challenging to connect to and hold their attention.

Past studies have attempted to establish an association of values with

consumer buying decision behaviour. Very few studies have been conducted relating

personal values to consumer behaviour of young adults in India. This study aims to

gain an insight into the influence of values on the shopping style of the young adults,

in the age group of 18 – 25 years, towards apparels. Studies based on consumer

values would help marketers understand why they make the choices they do and

21

help them devise more effective strategies to approach consumers belonging to a

particular value segment with appropriate marketing strategies.

It is expected that a psychographic analysis will give a more fine tuned and

accurate result on young adults’ buying behaviour than a general study on

youth.41Hence this study aims to answer the principal research question: Do personal

values influence the Shopping Style of Young Adults towards Purchase of

Apparels?

This study titled “A STUDY ON THE INFLUENCE OF PERSONAL

VALUES ON THE SHOPPING STYLES OF YOUNG ADULTS TOWARDS

PURCHASE OF APPARELS IN BANGALORE CITY, KARNATAKA, INDIA” is

undertaken by the researcher to answer the research question stated above.

SCOPE OF THE STUDY

The study is conducted in the urban areas of Bangalore which has a

cosmopolitan population exhibiting a modern lifestyle. The respondents for the

study are young adults who belong to the age group of 18 – 25 years. The variables

under study are ten values adapted from Kahle’s List of Values- LOV (1983) and

eight shopping styles adapted from Sproles and Kendall Consumer Style Inventory-

CSI (1986) and the demographic profile of the respondents. The study restricts only

to young adult shopping styles towards purchase of apparels.

41Vincent. N & Christy Dr. S. (2011).Psychographic Segmentation of Young Adult Consumers - A key to developing Sustainable Marketing Strategies – Global Journal of Arts & Management – October 2011

22

OBJECTIVES OF THE STUDY

The following are the objectives of the present study:

1) To identify the values which are perceived to be important among young

adults.

2) To segment young adult consumers based on their shopping styles towards

purchase of apparels.

3) To examine the relationship between values and shopping styles of young

adults towards purchase of apparels.

4) To develop a ‘Value-Shopping Style Model’ and analyze the influence of

values on the shopping styles of young adults towards purchase of apparels.

5) To explore the differences in the shopping styles among young adults across

demographics such as gender, education levels and regional background, and

6) To explore the differences in the value perception and value orientation of

young adults across demographics such as gender and regional background.

RESEARCH HYPOTHESES

The study will also endeavour to establish the validity of the research

hypotheses drawn from the objectives and set out below:

H1 There is no significant influence of values on the various shopping

styles of young adults towards purchase of apparels.

H2 There is no significant influence of values on the various dimensions of

the shopping styles of young adults towards purchase of apparels.

H3 There is no significant difference in the shopping styles of young adults

towards purchase of apparels across gender


towards purchase of apparels across education levels.


towards purchase of apparels across regional background.

23

H6 There is no significant difference in the orientation of young adults

towards External Values, Internal Interpersonal Values and Internal

Individual Values across gender.

H7 There is no significant difference in the orientation of young adults


Individual Values across regional background.

H8 There is no significant difference in the level of influence of individual

values on young adults across gender.

H9 There is no significant difference in the level of influence of individual

values on young adults across regional background.

CONCEPTS AND DEFINITIONS

1) Young Adults (Sample Base)

For the purpose of this study young adults refer to Male or Female persons

aged between 18 - 25 years of age. The age reference for young adults is as defined

for youth by the United Nations42 and as defined by India Youth Policy 201043.

Young Adults are a section of the Youth Group. Youth relates to an age

group that is transiting between childhood and adulthood and may comprise of a

conglomeration of sub-groups with differing social roles, expectations and

aspirations. However, there is no uniformity in the definition of youth among

different countries.

International definitions of Youth

The UN defines youth as those in the age-group of 15-24 years.

The UNICEF defines youth in the age bracket of 15-30 years.

The Common Wealth defines youth as those in the age-group of 15 to 29 years.

42 unesco.org/new/en/social-and-human-sciences/themes/youth/youth-definition 43http://yas.nic.in/

24

Tourism Australia defines the youth segment as males and females, aged between 18

and 30 years.

According to the World Bank, ‘The term youth in general refers to those who are

between the ages of 15 to 25.’

US Government describes youth as “A person... under 21 years of age”.

The Tasmanian Government defines youth as “People between the ages of 12 and

25”.

India’s Definition of Youth

India's National Youth Policy (NYP), 2012 aims to cover the age-bracket of 16-

30 years. However, the NYP recognised that all young persons within this age-group

are unlikely to be a homogeneous group, sharing common concerns and needs and

having different roles and responsibilities. Therefore, it further divides this broad

age-bracket into three subgroups:

a) The first sub-group of 16-21 years also covers adolescents whose needs and

areas of concern are substantially different from youth under the other age-

groups.

b) The second sub-group of 21-25 years includes those youth who are in the

process of completing their education and getting into a career.

c) The third sub-group of 26-30 years comprises of young women and men

most of whom have completed their education, including professional, and

are, more or less, settled in their job and in their personal life.

Indian government organisations such as the Indian Youth Congress and the

Akhil Bhartiya Vidyarthi Parishad consider those below the age of 35 as youth.

While the youth affairs ministry allows those in the 15-35 age groups to enrol in

clubs under the Nehru Yuva Kendra Sangthan, the National Youth Corps pegs the

age category at 18-25.

25

2) Values (Independent Variable)

Milton Rokeach (1979), a prominent social psychologist, defines values as

“an enduring belief that a specific mode of conduct or end-state of existence is

personally or socially preferable to an opposite or converse mode of conduct or end-

state of existence. They serve as a standard or criteria to guide not only action but

also judgment, choice, attitude, evaluation, argument, exhortation, rationalization,

and…attribution of causality”.

Values are the core principles that an individual upholds in life which directs

thought and drives action44. Personal values are individuals’ beliefs about what is

right or good and what is wrong or bad, and determine not only what is acceptable

and unacceptable to individuals, but also what people’s needs are, the way they

satisfy those needs, and the way they establish and achieve their goals. Values have

profound influence on consumer behaviour.

The values investigated in the study are: self-respect, security, warm

relationships with others, self fulfillment, a sense of accomplishment, being well

respected, a sense of belonging, fun and enjoyment, simplicity and being

independent.

3) Shopping Style (Dependent Variable)

A Consumer Shopping style is defined as “a mental orientation

characterizing a consumer's approach in making choices. It is a basic consumer

personality, analogous to the concept of personality in psychology”.45 It can be

identified by measuring general orientations of young consumers toward shopping

and buying.

The Consumer Styles Inventory developed by Sproles & Kendall describes

eight mental orientation of consumers in their decision-making process viz.,

44Vincent. N & Christy Dr. S. (2013). Personal values approach for a better understanding of

consumer behaviour. International Journal of Innovative Research & Development, Vol 2 Issue 3 March 2013, pg. 511

45Sproles G.B. & Kendall, E.L. (1986).A methodology for profiling consumers decision-making styles. Journal of Consumer Affairs, 20 (2), 267-279.

26

perfectionist/high-quality conscious; brand conscious/price equals quality; novelty

and fashion conscious; recreational &shopping conscious; price conscious/value-

for-money; impulsiveness/Careless; confused by over-choice; and habitual/brand-

loyal.

4) Psychographics

Psychographics is the study of personality, values, attitudes, interests, and

lifestyles. Since this area of research focuses on interests, activities, and opinions,

they are also called IAO variables. Psychographic studies of individuals or

communities can be valuable in the fields of marketing, demographics, opinion

research and social research in general. They can be contrasted with demographic

variables (such as age and gender), behavioural variables (such as usage rate or

loyalty), and organizational demographic variables (sometimes called firmographic

variables), such as industry, number of employees, and functional area.

When a relatively complete profile of a person or group's psychographic

make-up is constructed, it is called a "psychographic profile". Psychographic

profiles are used in market segmentation as well as in advertising. Psychographics

can also be seen as an equivalent of the concept of "culture" when it is used for

segmentation at a national level. :46

5) Apparels

The Dictionary meaning of the word ‘Apparels’ is ‘Clothing, especially outer

garments; attire.’47 In this study the term apparels refers to all types of outer

garments- formal wear and casual wear, clothing worn by young adults in India.

6) Value Dimensions

Values are beliefs or mental orientations that are independent in nature.

Categorising the individual values into dimensions such as External, Internal

Interpersonal and Internal Individual values provides scope for studies to analyse the

46 http://en.wikipedia.org/wiki/Psychographic 47 www.thefreedictonary.com

27

value orientations of individuals and group them under similar categories for

branding and positioning. According to Kahle’s original value constructs, the nine

independent values were grouped under three categories which are given in the

following table:

TABLE: 02

VALUE DIMENSIONS

S.NO Category of value Value Label 1 External Values Sense of Belonging 2 Being well respected 3 Security 4 Internal Interpersonal Values Warm relationship with others 5 Fun and enjoyment of life 6 Internal Individual Values Self fulfillment 7 Self-respect 8 A sense of accomplishment 9 Excitement

Source: List of Values – Kahle (1983)

28

LIMITATIONS OF THE STUDY

1. This study is limited to young adults who belong to the age group of 18-25

years. Due to limited time and cost constraints it is not possible for the

researcher to cover the population belonging to other age group.

2. Personal values are culture specific and the study pertains to Bangalore City

alone. Hence, findings of the study may not be applicable to other states with

different cultures.

3. The study is conducted by drawing sample respondents from the population

of young adults residing in the cosmopolitan city of Bangalore in India.

Inferences drawn do not provide conclusive evidence to any social

characteristics in particular though they aid in identifying underlying trends.

ORGANISATION OF CHAPTERS

The thesis of the study is divided into six major chapters. The first chapter

deals with an introduction to the International and National Retail market

environment, the Apparel Sector in India, a profile of young adult consumers in

India and psychographic segmentation. The chapter also presents the need for the

study, statement of the problem, research objectives, research hypotheses, concepts

and definitions and limitations of the study.

The second chapter presents a brief profile of Bangalore City, its historical

background, geographic profile, population profile and economic profile and a brief

profile of five leading Garment Manufactures in India who have a large brand

visibility in Bangalore and the Readymade Garments Industry in Bangalore.

The third chapter projects the various literatures reviewed by the researcher

that served as the foundations of this study. The literatures are grouped on variable

basis and presented in a chronological order within the categories. The four

classifications based on variables are: (1) Studies on Values; (2) Studies using

Consumer Styles Inventory; (3) Studies on Young Adults; (4) Studies on

Apparels/clothing buying behaviour. The research gap and the dimension of the

study are also specified. This is continued with the research design giving the blue

29

print of the methodology adopted by the researcher to attend to the research

objectives. It presents a detailed description of the sampling and data collection

procedure, and the frame-work for analysis to establish the findings. A detailed

description of the various analytical tools used is also presented here.

The fourth chapter presents a detailed description on Personal Values and

Shopping Styles. The basis of the model development is elaborated in this chapter.

The chapter finally presents a diagram of the proposed ‘Value-Shopping Style

Model’ tested in the study.

The fifth chapter presents the detailed analysis of the primary data with the

help of statistical tools and the research hypotheses that are being tested. Tables are

supported with detailed interpretations and implications.

The sixth chapter presents the significant findings of the study and deals with

some concrete suggestions and conclusions.

30

CHAPTER II

PROFILE OF THE STUDY AREA AND LEADING APPAREL

RETAILERS IN BANGALORE, INDIA

An understanding of the context in which this study is undertaken is

imperative to draw meaningful insights into the results obtained. In this section a

brief description of the location of the study and the apparels market in Bangalore is

presented. To elaborate, this study has been conducted in the cosmopolitan city of

Bangalore, India. The respondents were young adults in the age group of 18 – 25

years, residing in Bangalore. The study examines the influence of values held by this

consumer segment on their shopping style or purchase decision-making style for

apparels.

PROFILE OF BANGALORE CITY, INDIA

FIG. 1

MAP OF INDIA-STATES AND CAPITALS

Source: www.en.wikipedia.org

31

Bangalore, also known as Bengaluru, is the Capital city of Karnataka.

Bangalore being India’s leading IT exporter and the 4th largest technological hub in

the world and largest in Asia, is known as the Silicon Valley of India. The World

Economic Forum identified Bangalore as the Innovation Cluster. Located on Deccan

Plateau in the South Eastern part of Karnataka, Bangalore is spread across four

zones namely Bangalore North, Bangalore East, Bangalore South and Anekal. A

demographically diverse city, Bangalore is a major economic and cultural hub and

the second fastest growing major metropolis in India with an economic growth of

10.3%. The city possesses world class infrastructure in housing, education &

research. Bangalore is packed with restaurants, clubs, pubs, health spas, amusement

parks, supermarkets, theatres, cinemas, shopping malls, discotheques and other

necessities of a modern-day metropolitan lifestyle.

Bangalore is home to many well-recognized colleges and research

institutions in India. Numerous public sector heavy industries, technology

companies, aerospace, telecommunications, and defence organisations are located in

the city.

Historical Background48

The region of modern day Bangalore was part of several successive South

Indian kingdoms. Between the fourth and the tenth centuries, the Bangalore region

was ruled by the Western Ganga Dynasty of Karnataka, the first dynasty to set up

effective control over the region. The Western Gangas ruled the region initially as a

sovereign power (350 — 550 A. D.), and later as feudatories of the Chalukyas of

Badami, followed by the Rashtrakutas till the tenth century. The Begur Nageshwara

Temple was commissioned around 860 A. D. during the reign of the Western Ganga

King Ereganga Nitimarga I, and extended by his successor Nitimarga II. At the end

of the tenth century, the Cholas from Tamil Nadu began to penetrate in areas east of

Bangalore; they later began to extend their control over parts of present-day

Bangalore, such as Domlur on the eastern side of the city. Around 1004 A.D., during

the reign of Rajendra Chola I, the Cholas defeated the Western Gangas, and

48 http://en.wikipedia.org/wiki/Bangalore

32

captured Bangalore. During this period, the region of Bangalore witnessed the

migration of many groups - warriors, administrators, traders, artisans, pastorals,

cultivators, and religious personnel from Tamil Nadu and other Kannada speaking

regions. The Chokkanathaswamy temple at Domlur, the Aigandapura complex

near Hesaraghatta, Mukthi Natheshwara Temple at Binnamangala, Choleshwara

Temple at Begur, and the Someshwara Temple at Madiwala, all date from the Chola

era.

A succession of South Indian dynasties ruled the region of Bangalore until in

1537 A. D., KempéGowd —a feudatory ruler under the Vijayanagara Empire—

established a mud fort considered to be the foundation of modern Bangalore.

Following transitory occupation by the Mar th s and Mughals, the city remained

under the Mysore kingdom, which is now a part of the Indian state of Karnataka.

Bangalore continued to be a Cantonment of the British and a major city of

the Princely State of Mysore which existed as a nominally sovereign entity of

the British Raj. Following the independence of India in the year 1947, Bangalore

became the capital of Mysore state, and remained capital when the new Indian state

of Karnataka was formed in 1956.

In the 19th century, Bangalore essentially became a twin city whose

residents were predominantly Kannadigas, and the "cantonment" created by the

British, whose residents were predominantly Tamils. Throughout the 19th century,

the Cantonment gradually expanded and acquired a distinct cultural and political

salience as it was governed directly by the British and was known as the Civil and

Military Station of Bangalore. While it remained in the princely territory of Mysore,

the Cantonment had a large military presence and a cosmopolitan civilian population

that came from outside the princely state of Mysore, including Britons, Anglo-

Indians, and migrant Tamil labourers and contractors. The city, on the other hand,

had a largely Kannada-speaking population.

Bangalore experienced rapid growth in the decades 1941–51 and 1971–81,

which saw the arrival of many immigrants from northern Karnataka. By 1961,

Bangalore had become the sixth largest city in India, with a population of

33

1,207,000. In the decades that followed, Bangalore's manufacturing base continued

to expand with the establishment of private companies such as MICO (Motor

Industries Company), which set up its manufacturing plant in the city. Bangalore

experienced a growth in its real estate market in the 1980s and 1990s, spurred by

capital investors from other parts of the country who converted Bangalore's large

plots and colonial bungalows into multi-storied apartments. In 1985, Texas

Instruments became the first multinational corporation to set up base in Bangalore.

Geographical Profile49

Bangalore lies in the southeast of the South Indian state of Karnataka. It is in

the heart of the Mysore Plateau (a region of the larger Precambrian Deccan Plateau)

at an average elevation of 900 metres above sea level. Bangalore experiences

a tropical Savanna climate with distinct wet and dry seasons. Due to its high

elevation, Bangalore usually enjoys a more moderate climate throughout the year,

although occasional heat waves can make things very uncomfortable in the summer.

FIG. 2

BANGALORE CITY MAP

Source: en.wikipedia.org

49 http://en.wikipedia.org/wiki/Bangalore

34

The city is spread over an area of 2190 square kilometres. Its tree-lined

streets and abundant greenery have led to it being called the ‘Garden City’ of India.

It is connected by air, rail and road to all major cities of the country and has direct

international connections to many cities worldwide.

The clean and spacious city of Bangalore has many imposing structures full

of historic and modern architecture. The majestic Vidhana Soudha, a magnificent

post-independence structure housing the State Legislature and Secretariat, stands in

the centre of the city with its attractive dome and galleries. However, since local

entrepreneurs and the technology giant Texas Instruments discovered its potential as

a high-tech city in the early 1980s, Bangalore has seen a major technology boom. It

is now home to more than 250 high-tech companies. Including home-grown giants

like Wipro and Infosys.

Population Profile

TABLE: 03

POPULATION OF KARNATAKA

According to 2011 Population Census:

Population of Karnataka 61,130,704 Males: 3,10,57,742 Females: 3,00,72,962

Population of Karnataka consists of:

Hindu - 83%,

Muslim - 11%,

Christian - 4%,

Jains - 0.78% and Buddhist - 0.73%

Sex Ratio in Karnataka 1000 males for

every 968 females

Source:http://www.indiaonlinepages.com/population/karnataka-population.html

The total population of the State of Karnataka is 61,130,704. This amounts to

5.05% of the total population of India which is 1,21,01,93,422 as per 2011 census

data. The gender ratio is 1000 Males : 968 females for Karnataka, compared to the

940 females to 1000 males for India.

Karnataka is one of the major states of South India. Karnataka is the ninth

largest state in India in terms of Population. According to Population census of

35

2001, the Population of Karnataka was 5.273 crores (52.73 million). The Population

of Karnataka increased by 17.20% as compared to last census of India in 1991.

Karnataka is one of the top states in terms of literacy rate in India. Bangalore is the

top city with a population of over 1 million in Karnataka.

TABLE: 04

POPULATION OF BANGALORE CITY [URBAN]

According to 2011 Population Census:

Population of Bangalore 95,88,910 Males 50,25,498 Females 45,63,412

Population of Bangalore consists of:

Hindu –79.4%,

Muslim – 13.4%,

Christian –5.8%,

Jains –1.1% [Provisional population totals

census of India 2011 Govt of India]

Sex Ratio in Bangalore 1000 males for

every 908 females

Source:http://www.indiaonlinepages.com/

With an estimated population of 9,588,910, according to provisional Census

2011 data, Bangalore is the third most populous city in India and the 18th most

populous city in the world. Bangalore was the fastest-growing Indian metropolis

after New Delhi between 1991 and 2001, with a growth rate of 38% during the

decade. Residents of Bangalore are referred to as Bangaloreans in English and

Bengaloorinavaru in Kannada.

According to the 2011 census of India, 79.4% of Bangalore's population

is Hindu, roughly the same as the national average. Muslims comprise 13.4% of the

population, which again is roughly the same as the national average, while

Christians and Jains account for 5.8% and 1.1% of the population respectively;

double that of their national averages. The city has a literacy rate of 89%. Roughly

10% of Bangalore's population lives in slums, a relatively low proportion when

compared to other cities in the developing world such as Mumbai (50%)

and Nairobi (60%).

36

The official language of the state is Kannada, though, being a cosmopolitan

city many languages are spoken here. In Bangalore there are people speaking

languages such as Kannada(38.38%), Tamil (21.38%), Telugu (16.66%),

Urdu (12.65%), Malayalam (2.99%), Hindi (2.64%), and others. The cosmopolitan

nature of the city has resulted in the migration of people from other states to

Bangalore.50 English is widely understood, and spoken with variable fluency.51

The large number of central government and defence establishments with

many employees from northern India, movies and television have made Hindi a

widely understood language in the city. A majority of them belong to the middle

class and the upper middle class. Bangalore with its high growth rate and population

density has the most skewed sex ratio at 908 females for 1,000 males. According to

the data, literates constitute 76 per cent of the state’s total population aged six and

above and illiterates form 24 percent. Overall, the male literacy rate in the state has

gone up from 76.1 per cent in 2001 to 82.85 per cent in 2011, while female literacy

rate has increased from 56.87 per cent in 2001 to 68.13 per cent in 2011.

Economic Profile

With a Gross Domestic Product of $83 billion, Bangalore is listed 4th among

the top 15 cities contributing to India's overall GDP. Bangalore's

52,346 crore (US$9.6 billion) economy (2006–07 Net District Income) makes it

one of the major economic centres in India, with the value of city's exports

totalling 43,221 crore (US$7.9 billion) in 2004–05. With an economic growth of

10.3%, Bangalore is the second fastest growing major metropolis in India, and is

also the country's fourth largest fast moving consumer goods (FMCG) market. The

large number of information technology companies located in the city contributed

33% of India's 144,214 crores (US$26 billion) IT exports in 2006–07.

With a per capita income of 74,709 (US$1,400) in 2006–07, the city is the

third largest hub for high-net-worth individuals. The high per capita income in

Bangalore can be compared to top cities in the world. This is because most

50http://en.wikipedia.org/wiki/Bangalore 51Provisional Population Totals Census Of India 2011 Govt Of India

37

businesses focus on intellectual property, considered the future of business. As a

result there's a lot of capital flowing into the city. The standard of living is better

than in other metros. Bangaloreans’ life-style exhibits a high level of brand

awareness/consciousness. This is reflected in the increasing number of car and two-

wheeler owners, the number of people eating out and those who splurge on goods of

well-known brands.

The headquarters of several public sector undertakings such as Bharat

Electronics Limited (BEL), Hindustan Aeronautics Limited (HAL), National

Aerospace Laboratories (NAL), Bharat Heavy Electricals Limited (BHEL), Bharat

Earth Movers Limited (BEML) and HMT (formerly Hindustan Machine Tools) are

located in Bangalore. In June 1972 the Indian Space Research Organisation (ISRO)

was established under the Department of Space and headquartered in the city.

Bangalore's IT industry is divided into three main clusters —Software

Technology Parks of India (STPI); International Tech Park, Bangalore (ITPB);

and Electronics City. UB City, the headquarters of the United Breweries Group, is a

high-end commercial zone. Infosys and Wipro, India's third and fourth largest

software companies are headquartered in Bangalore, as are many of the global SEI-

CMM Level 5 Companies

Bangalore is the home to the biggest bio-cluster in India with 137

Biotechnology companies, making it 40% of the total 340 such units in the country;

a total of 87 Fortune MNCs, 2084 IT Companies and 195 BT companies are there in

Karnataka.

Bangalore is a Medical Hub due to the presence of World’s largest ‘healing

centre’ and ‘telemedicine centre’. A ‘Silk City’ with an investment of US $ 14.5

million (INR 70 Crores) is upcoming in the north Bangalore region. Business Week

placed Bangalore among the ‘Global Hot Spots of the 21st Century’.

The garment industries in the State of Karnataka are concentrated in

Bangalore where some of the largest export houses of the country exist. Overseas

buyers view Bangalore as an important location for sourcing of garments after

38

Bombay and Delhi. Brand images are being felt in this region and there is a great

potential for production of value added goods.

Field studies conducted in earlier researches have showed that there are

approximately 40,000 readymade garment-manufacturing units in India. Many

leading world fashion labels are being associated with Indian products. India is

being looked upon as a major supplier of high quality fashion apparels, which are

being appreciated in major international markets.

Cultural Profile

Bangalore is one of the most ethnically diverse cities in the country, with

over 62% of the city's population comprising migrants from other parts of India.

Being the fastest growing city of India, it comprises of a dynamic blend of people,

belonging to various religions, castes and communities. With the introduction of

information technology in the city, it has assumed an international character. IT

professionals not only from the various parts of India, but also that of the world, are

migrating to the city.

Bangalore is also a major centre of Indian classical music and dance. The

cultural scene is very diverse due to Bangalore's mixed ethnic groups, which is

reflected in its music concerts, dance performances and plays. Performances

of Carnatic (South Indian) and Hindustani (North Indian) classical music, and dance

forms like Bharat Natyam, Kuchipudi, Kathakali, Kathak, and Odissi are very

popular. Yakshagana, a theatre art indigenous to coastal Karnataka is often played in

town halls.

The two main music seasons in Bangalore are in April–May during the Ram

Navami festival, and in September–October during the Dusshera festival, when

music activities by cultural organizations are at their peak. Though both classical

and contemporary music are played in Bangalore, the dominant music genre in

urban Bangalore is rock music. Bangalore has its own sub-genre of music,

"Bangalore Rock", which is an amalgamation of classic rock, hard rock and heavy

metal, with a bit of jazz and blues init. Notable bands from Bangalore include The

39

Raghu Dixit Project, Kryptos, Inner Sanctum, Agam, All the Fat Children,

and Swaratma.

Bangalore is home to the Kannada film industry, which churns out about 80

Kannada movies each year. Bangalore also has a very active and vibrant

theatre culture with popular theatres being Ravindra Kalakshetra and the more

recently opened Ranga Shankara. The city has a vibrant English and foreign

language theatre scene with places like Ranga Shankara and Chowdiah Memorial

Hall leading the way in hosting performances leading to the establishment of the

Amateur film industry. Kannada theatre is very popular in Bangalore, and consists

mostly of political satire and light comedy. Plays are organized mostly by

community organizations, but there are some amateur groups which stage plays in

Kannada. Drama companies touring India under the patronage of the British Council

and Max Müller Bhavan also stage performances in the city frequently.

The diversity of cuisine is reflective of the social and economic diversity of

Bangalore. Bangalore has a wide and varied mix of restaurant types and cuisines and

Bangaloreans deem eating out as an intrinsic part of their culture. Roadside

vendors, tea stalls, and South Indian, North Indian, Chinese and Western fast food

are all very popular in the city.

Bangalore has a number of elite clubs like the Century Club, The Bangalore

Golf Club, the Bowring Institute and the exclusive Bangalore Club, which counts

among its previous members Winston Churchill and the Maharaja of

Mysore. Bangalore's pleasant climate makes it a suitable place for a variety of

outdoor sports. Cricket is by far the most popular sport in Bangalore. Sports

personalities from Bangalore include national swimming champion Nisha Millet,

world snooker champion Pankaj Advani and former All England Open badminton

champion Prakash Padukone, former Indian cricket team captains Rahul

Dravid and Anil Kumble.

40

Educational Profile

Until the early 19th century, education in Bangalore was mainly run by

religious leaders and restricted to students of that religion. The western system of

education was introduced during the rule of Mummadi Krishnaraja Wodeyar.

Subsequently, the British Wesleyan Mission established the first English school in

1842, and the Bangalore High School was started by the Mysore Government in

1858.

Primary and secondary education in Bangalore is offered by various schools

which are affiliated to one of the boards of education, such as the Secondary School

Leaving Certificate (SSLC), Indian Certificate of Secondary Education (ICSE),

Central Board for Secondary Education (CBSE), International Baccalaureate (IB),

International general certificate of secondary education (IGCSE) and National

Institute of Open Schooling (NIOS). Schools in Bangalore are either government run

or are private (both aided and un-aided by the government). Bangalore has a

significant number of International Schools due to its expats and IT crowd.

Bangalore District is a renowned centre of learning, with numerous

legendary professional institutions, high schools, colleges and universities.

Premium institutes in the country like IIM Bangalore, National Law School, Indian

Institute of Science, etc. are in Bangalore. Leading international schools like

MallyaAditi International School, Ryan International School, Bangalore

International School attract students from all over the world.

The Bangalore University, established in 1886, provides affiliation to over

500 colleges, with a total student enrolment exceeding 300,000. The university has

two campuses within Bangalore – Jnanabharathi and Central College. University

Visvesvaraya College of Engineering (UVCE) was established in the year 1917, by

Bharat Ratna Sir M. Visvesvaraya. At present, the UVCE is the only engineering

college affiliated to Bangalore University. UVCE is one of the prestigious

institutions in India. Bangalore also has a large number of private Engineering

Colleges affiliated to Visvesvaraya Technological University. Notable among them

particularly for undergraduate degrees are BMS College of Engineering,

41

R.V. College of Engineering, P.E.S. Institute of Technology,M. S. Ramaiah Institute

of Technology, Sir M. Visvesvaraya Institute of Technology and Bangalore Institute

of Technology.

Indian Institute of Science, which was established in 1909 in Bangalore, is

the premier institute for scientific research and study in India. Nationally renowned

professional institutes such as the National Centre for Biological Sciences (NCBS),

University of Agricultural Sciences, Bangalore (UASB), Institute of Bio-informatics

and Applied Biotechnology [IBAB], National Institute of Design(NID), National

Institute of Fashion Technology (NIFT), National Law School of India

University (NLSIU), the Indian Institute of Management, Bangalore (IIM-B),

the Indian Statistical Institute and International Institute of Information Technology,

Bangalore (IIIT-B) are located in Bangalore. The city is also home to the premier

mental health institution in India, The National Institute of Mental Health and Neuro

Sciences (NIMHANS). Bangalore also has some of the best medical colleges in the

country, like St. John's Medical College(SJMC) and Bangalore Medical College and

Research Institute (BMCRI). The M. P. Birla Institute of Fundamental

Research Institute has a branch located in Bangalore.

Readymade Garments Industry in Bangalore52

The garment industries in Karnataka are concentrated in Bangalore where

some of the largest export houses of the country are situated. Today, overseas buyers

view Bangalore as an important location for the sourcing of garments after Bombay

and Delhi.

Brand images are being felt in this region and there is a great potential for

production of value added goods. Garment industries in Bangalore started from the

period of British colonisation. M/s. Bangalore dressmaking Co. was the first unit,

started to manufacture garment in Bangalore during 1940, which was started by

Mr.Vittal Rao. During the rule of British, there was a need of clothing dress

materials. This led to the development of RMG industries in Bangalore. Apart from

RMG industries, there were silk weaving industries in Bangalore, which led to the 52Devaraja, T.S. (2011). Indian Textile and Garment Industry- An Overview

42

development of silk exporters also. After India’s independence in 1947, the

industries started picking up slowly to cater the needs of dresses of the common man

and local market. The industry started flourishing. After the de-reservation of

garments, big players like Mafatlal, Arvind Mills, etc. started entering the field and

occupied places in the sector which indirectly affected the small scale sector.

There are about 3000 RMG units in and around Bangalore. Most of the

buying agencies in the world have established their branch office in the city. Apart

from this, Apparel Park, at Doddaballapur has started functioning in a big way. In

India, RMG units are concentrated in the cities like Delhi, Mumbai, Kolkata,

Bangalore, Chennai, Jaipur, Tirupur, and Ludhiana. There is a difference in the end

products manufactured at Bangalore and other places. RMG are mainly made for

export house. There are many SSI units mainly doing job work providing supports to

the SMEs like GE, Arvind Fashion, Sonal Holding, Texport Syndicate units in the

cluster. The technology and manufacturing processes are the same as those used in

other regions.

In Bangalore, garment units are mainly concentrated in the following areas:

Bommanahalli, Bommasandra, Peenya, Yeswanthpur, Rajajinagar Industrial Estate

and Industrial town. The important products manufactured here are: Ladies Jacket,

Blouses, Churidar sets, Petticoats, and Gents Trousers, Shirts, and T-Shirts.

Development of RMG units in Bangalore was started in the year 1970

onwards by leading exporters like Gokaldas export, Ashoka export, Continental

Exports, Leela Fashions, Texport Overseas etc. Later, small industries (fabricators)

were started by taking the orders from large scale. Most important reasons for

developments of RMG is the availability and sourcing of export fabrics from places

like Salem, Erode and Coimbatore which are nearest to Bangalore. The other

reasons, which contributed for the development of industries, are availability of

space, availability of raw material, skilled labour, existence of airport/cargo

container depot/infrastructure, flexible specialization, entrepreneurship.

There has been increase in the number of RMG units in Bangalore since

1990. At present there are about 900 active readymade garment manufacturers and

43

exporters, the number is likely to increase as per the reports of Apparel Park at

Doddaballapur. Karnataka Industrial Area Development Board is in the process of

acquiring the lands for the further expansion of the park. There are about 1600

fabricators who are doing job work for these exporters, apart from domestic market

needs. There are 50 embroidery units who are supporting these units for value

addition. Broad sub-grouping of the products is as follows: Readymade garments for

Gents: 60%; RMG for ladies: 30%; RMG for kids: 10%. The economy of Bangalore

is inextricably mixed up with that of readymade garment industry. Thirty per cent of

the Readymade Garments of the country are made in this region. This is the third

biggest readymade garment manufacturing cluster in the country.

Brief Profile of Leading Apparel Retailers in India who have a large brand

visibility in Bangalore

Mudra Life Style Limited53

The Mudra Group, started its operations in 1986 and are in the textile

industry having facilities for fabrics & garments manufacturing, processing, design

development and sampling, etc. Mudra manufactures fabrics and garments for

domestic and export market. The brand “MUDRA” has built a strong goodwill for

itself in the domestic market and commands a premium. They are gradually moving

towards garment manufacturing mainly in the designer shirts and ladies wear

segments to capitalize on the huge opportunity unleashed by the removal of

quotas. Mudra’s product portfolio consists offinished fabric; processing and

garments comprising of –Men’s Wear –Shirts; Ladies Wear – Tops, Skirts; and Kids

Wear.

Mudra follows the concept of complete lifestyle for men, women and

children. Mudra caters to well known names in the fashion market with its ability to

offer collections that are set to seasonal fashion trends, colours, patterns and

international designs. To realize the fabric into brilliant expressions of styling, the

company has set in-house state-of-the-art garment manufacturing units, wherein

fabric get realized into quality finished products. Mudra houses the complete 53http://www.mudralifestyle.com/

44

technology for manufacturing the perfect garment that speaks of global lifestyle and

quality. The Garment manufacturing units are equipped with high-tech machines

like Juki stitching, Brother, interlocking, button stitching, automatic cutting, fusion

and automatic steam ironing.

With an annual capacity of 7.20 million garments, Mudra offers high quality

garments for buyers in over 30 countries worldwide. Mudra has spread business

over to both domestic and global customers. It caters to national brands like

Raymonds and Arvind Mills. International houses associated with Mudra are Zara,

Cortefil, Carrefour, Wal-Mart and its brands, like Weekends, George, Non-stop,

Metropolis and other brands like Tricos, American Juliet & Liver Pool.

Mudra has garment manufacturing plants in Bangalore, Daman and Vapi,

India. A Complete range of specialized machines needed for all critical operations

like cutting, sewing, pressing, finishing and quality control are housed under one

roof ensuring speed, consistency and quality.

Gokaldas Exports Ltd54

Gokaldas Exports Ltd (GEL) was incorporated in 1979. GEL is a major

player in the readymade garment industry across the globe. The company which is

an ISO 9001:2000 Certified Company is one of the largest manufacturer/exporter of

Outerwear, Blazers and Pants (Formal and Casuals), Shorts, Shirts, Blouses, Denim

Wear, Swim Wear, Active and Sports Wear.

The subsidiaries of the company are Madhin Trading Pvt Ltd, Magenta

Trading Pvt Ltd, Rafter Trading Pvt Ltd, Reflextion Trading Pvt Ltd, Deejay

Trading Pvt Ltd, Rishikesh Apparels Ltd, Vignesh Apparels Pvt Ltd, SNS Clothing

Pvt Ltd, Seven Hills Clothing Pvt Ltd, Glamourwear Apparels Pvt Ltd, Rajdin

Apparels and All Colour Garments Pvt Ltd. Gokaldas Exports Pvt Ltd and Unique

Creations (Bangalore) Pvt Ltd was merged with the company with effect from 1st

April 2004. During 2004-05, the company had set up three new factories at

54http://www.indiainfoline.com

45

Bangalore-at Bommasandra Industrial Area, at Yeshwanthpur, and one at

Doddaballapur.

The new state-of-the-art laundry facility at Bangalore was commissioned in

June'06. The company also commissioned knit wear unit at Bangalore during 2005-

2006 The expansion programme at Chennai, Hyderabad, and Mysorewas also under

progress during the year.

Gokaldas Exports has four decades of partnering the world's most trusted

fashion labels, 30 state-of-the-art factories and 32,000 employees. Gokaldas have

led the Indian readymade garment industry, year after year, earning customer

loyalty, winning industry awards and growing reputation for reliability. They had

done it by orienting to fashion trends and customer needs, investing in the latest

technology, relentlessly training the highly-skilled workforce and setting the highest

standards in both the production process and the end-product. Shri J. H. Hinduja is

the Founder.

Arvind Limited55

Arvind Ltd is the largest cotton textiles manufacturer and exporter in India.

They are the leading player in the branded garments in the domestic market. The

company's principal business consists of manufacturing and marketing of Denim

Fabric, Shirting Fabric, Shirts, Knitted Fabric and Garments. The company has

acquired the rights to market international brands such as Lee, Wrangler, Arrow and

Tommy Hilfiger in India. The company also owns popular brands such as Newport,

Flying Machine, Excalibur and Ruf&Tuf. Arvind Ltd houses their production

facilities at Ahmedabad, Mehsana, Gandhinagar in Gujarat; Pune in Maharashtra,

and Bangalore in Karnataka.

Arvind Ltd was incorporated in the year 1931 as Arvind Mills Ltd by three

brothers Kasturbhai, Narottambhai and Chimanbhai. In the year 1934, they

established themselves amongst the foremost textile units in the country. They were

the first company to bring globally accepted fabrics such as Denim, yarn dyed

55http://www.arvindmills.com

46

shirting fabrics & wrinkle free gabardines to India in the year 1986. In the year

1987, they started retail outlets for Arrow brand and became the first company to

bring the international shirt brand Arrow to India.

During the year 2003-04, the company expanded their shirts manufacturing

capacity from 2.4 million pieces to 4.8 million pieces per annum. During the same

year, their subsidiary company, Arvind Spinning Ltd commenced their operation. In

March 2005, the company commenced their operations of producing Jeans in

Bangalore with the installed capacity of 4 million pieces per annum. During the year

2005-06, new Denim collection was launched which was aimed at the Super

Premium brands of the USA, Europe, Japan& Korea. The Company has a joint

venture company namely Arvind Murjani Brand Pvt Ltd, through which they hold

license to sell Tommy Hilfiger brand apparel in India. The operations of Arvind

Brands Limited and their subsidiaries were merged with the company with effect

from April 1, 2006. The wholesale branded apparel business of Arvind Fashions Ltd

has been sold to VF Arvind Brands Pvt Ltd with effect from August 31, 2006. In

March 2008, the company signed an exclusive license agreement with the Philips-

Van Heusen Corporation for designing, distribution and retailing of IZOD brand

apparels in India. From May 2008, the company name was changed from Arvind

Mills Ltd to Arvind Ltd.

Arvind has a strong focus on Research and Development for process

improvement, cost reduction and new product development. This is evident in the

fact that Arvind continuously modifies its production process to enhance flexibility

on the use of various types and quality of cotton.

State-of-the-art technology and equipment have made Arvind one of the

leading producers of denim in the world, paving the way for the Company to emerge

as a global textile conglomerate. This cutting edge position comes to Arvind

courtesy technologies such as Open-end Spinning, Foam Finishing, Mercerizing,

Slasher-dyeing, Rope-dyeing, Air-Jet, Projectile and Wet Finishing. Arvind’s quality

fabrics are in high demand in the markets of Europe, US, West Asia, the Far East

and Asia Pacific.

47

Design, Innovations and Sustainability have been their core competency and

have played a key role in their success. The use of sophisticated ultramodern

technology under the guidance of world-renowned designers has enabled Arvind to

deliver many firsts in the international markets. All their products are designed and

modelled on the basis of expert design inputs coming from designers based out of

India, Japan, Italy and the United States. All Arvind Denim products come with the

hallmark of distinctiveness and quality.

Arvind has carved out an aggressive strategy to verticalize its current

operations by setting up world-scale garmenting facilities and offering a one-stop

shop service, by offering garment packages to its international and domestic

customers. With Lee, Wrangler, Arrow and Tommy Hilfiger and its own domestic

brands of Flying Machine, Newport, Excalibur and Ruf&Tuf, Arvindhas set its

vision of becoming the largest apparel brands company in India.

Arvind runs India's largest Value Retail Chain - MegaMart. The MegaMart

format offers a unique and differentiated proposition to the consumers. It offers

mega brands at very low prices and provides a retail experience of a high-end

department store.

Trent Ltd., ‘Westside’56

Established in 1998 as part of the TATA Group, Trent Ltd operates

Westside, one of India’s largest and fastest growing chains of retails stores.

The Westside stores have numerous departments to meet the varied shopping

needs of customers. These include Menswear, Women’s wear, Kid’s wear,

Footwear, Cosmetics, Perfumes and Handbags, Household Accessories, Lingerie,

and Gifts. The company has established 74 Westside departmental stores (measuring

15,000 - 30,000 square feet each) in Ahmedabad, Bangalore, Chandigarh, Chennai,

Delhi, Gurgaon, Ghaziabad & Noida, Hubli, Hyderabad, Indore, Jabalpur, Jaipur,

Kanpur, Kolkata, Ludhiana, Lucknow, Mangalore, Mumbai, Mysore, Nagpur,

Nashik, Pune, Raipur, Rajkot, Surat, Vadodara and Jammu.

56http://www.mywestside.com

48

In a rapidly evolving retail scenario, Westside has carved a niche for its

brand of merchandise creating a loyal following. With a variety of designs and

styles, everything at Westside is exclusively designed and the merchandise ranges

from stylized clothes, footwear and accessories for men, women and children to

well-co-coordinated table linens, artefacts, home accessories and furnishings. Well-

designed interiors, sprawling space, prime locations and coffee shops enhance the

customers’ shopping experience.

Shoppers Stop Ltd.57

An Indian retail sector major, Shoppers Stop Limited (SS) opened its door in

the year 1991, the foundation was made by K Raheja Corp and it was incorporated

on 16th June 1997 as a private limited company. It started operations with the first

store in suburban Mumbai and is now a multi-channel retailer with 24 large format

department stores and online presence.

From its inception, Shoppers Stop has progressed from being a single brand

shop to becoming a Fashion & Lifestyle store for the family. Today, Shoppers Stop

is a household name, known for its superior quality products, services and above all,

for providing a complete shopping experience. It provides retail range of branded

and own label apparel, footwear, perfumes, cosmetics, jewellery, leather products

and accessories, home products, books, music and toys. Shopper’s Stop operates in

the cities of Mumbai, Delhi, Kolkata, Chennai, Bangalore, Hyderabad, Pune, Jaipur

and Gurgaon.

The first store was opened in the year 1991 at Andheri, a suburb in Mumbai,

only with Menswear and the Ladieswear was introduced in the year 1992. After a

year, the company added Children & non-apparels to its list in 1993.

The status of the company was changed to a deemed public limited company

in December of the same incorporation year 1997. SS's status was further converted

to a full-fledged public limited company on 6th October 2003.

57http://corporate.shoppersstop.com/corporate/history.aspx

49

The Company was honoured with Emerging Market Retailer of the Year

award in 2008. In April of the same year, 2008, SS had unveiled its new logo and

introduced the new expression of the brand. SS bagged Department Store of the

Year award in November of the year 2008 for its reputation in the industry.

Shoppers Stop retails products of domestic and international brands such as

Louis Philippe, Pepe, Arrow, BIBA, Gini & Jony, Carbon, Corelle, Magppie, Nike,

Reebok, LEGO, and Mattel. Shopper’s Stop retails merchandise under its own

labels, such as STOP, Kashish, LIFE and Vettorio Fratini, Elliza Donatein,

Acropolis, etc. The company is also a licensee for Austin Reed (London), an

international brand, who’s men's and women's outerwear are retailed in India

exclusively through the chain. In October 2009, Shoppers Stop bought the license

for merchandising Zoozoo, the brand mascot for Vodafone India.

Shoppers Stop introduced international brands like CK Jeans, Tommy

Hilfiger, FCUK, Mustang, Dior, etc. across the stores. The focus of the reposition

was on the service, ambience upgradation and customer connect. Shoppers Stop

connects with the youth audience through adopting the communication routes

relevant to youth, up the fashion quotient through merchandising, and creates an

ambience that connects with their mindset.58

58http://en.wikipedia.org/wiki/Shoppers_Stop

50

CHAPTER III

REVIEW OF LITERATURE & DESIGN OF THE STUDY

The purpose of this research is to explore the influence of personal values on

the young adults’ shopping style for apparels. In this chapter, a review of the

literature pertinent to the study is presented. An examination of studies on the

psychographics and values is followed by a review of studies using the CSI –

Consumer Style Inventory. This is followed by review of studies on youth, and

finally literature relative to apparels/clothing behaviour is examined. The guiding

research questions and the model development were formulated based on these

studies.

STUDIES ON PSYCHOGRAPHICS/VALUES

Munson & McQuarrie (1988),59 tried to shorten the Rokeach Value Survey

(RVS) to reflect on consumption relevant values. Researchers identified a subset of

24 value items as maximally relevant to product consumption. Using this 24 item

subset, the researchers constructed a Values Instrumentality Inventory which

demonstrated satisfactory psychometric properties with respect to its internal

consistency, stability over two independent samples, and factor structure. Thus,

conclusions made were, the values reduction methods investigated here could be

used to purge the RVS of values which are largely irrelevant or tangential to most

consumption behaviors.

Shrum et.al, (1990),60 examined individual differences in the stability of a

target value in the Rokeach Value Survey (RVS). All participants ranked and rated

the values of the RVS and completed a scale measuring private self-consciousness

and the participants in the control condition received no communication. The results

from the study provided a considerable support for reasoning that degrees of private

59Munson, J. M., &McQuarrie, E. F. (1988). Shortening the Rokeach value survey for use in

consumer research. Advances in Consumer Research, 15, 381-386 pp. 60Shrum, L. J., McCarty, J. A., & Loeffler, T. L. (1990). Individual differences in value stability: Are

we really tapping true values. Advances in Consumer Research Volume, 17, 609-615 pp.

51

self-consciousness are related to value stability. Results also indicated that the

individuals who were high in self-consciousness were more aware of the values.

Allen (2001),61 assessed a method for uncovering the direct and indirect

influences of human values on consumer decisions. It was found that the ability to

identify a relationship between consumer values and the image of a product/service

is especially useful in situations where brand image is more important to the

consumer's decision making than the specific features of the product. The results

from the study indicated that the advertiser always faced problems regarding how to

identify which values the consumer associated with the product and how to

incorporate that knowledge into the words and pictures within the advertisement.

Kim(2002),62 developed and tested a conceptual model that featured the role

of personal value structures in guiding individuals’ environmentalism. The study

examined how personal values affected the perception of pro-environmental

attributes and buying-green products. It explored the effects of cultures on personal

value orientations and commitments to pro-environmental behaviours. Thus, as a

result, the study demonstrated that personal values play an important role in

determining individuals' environmental sensibility and suggested that the

relationship between attitudes and behaviour are stronger in some cases than in

others.

Roper (2002),63 conducted a study to identify values of American consumer

groups. Six groups namely: strivers, devouts, creatives, fun seekers, altruists and

intimates. It was found that the strivers are more materialistic than any of the other

groups and they seeded power, wealth and status. Brands were looked into for status

and self-definition and are most likely to attribute wealth and personal success.

Finally, the researcher intimated that the consumers who earned highest house hold

61Allen, M. W. (2001). A practical method for uncovering the direct and indirect relationships

between human values and consumer purchases. The Journal of Consumer Marketing, 18(2), 102-120 pp.

62Kim, Y. (2002). The impact of personal value structures on consumer pro-environmental attitudes, behaviors, and consumerism: A cross-cultural study. ProQuest, UMI Dissertations Publishing.

63Roper, S. W. (2002). New age consumers: attitudes and values. Proquest, 121.

52

income were ranked under family and leisure activities which formed the most

important part of life.

Kittichai (2005),64 the paper attempted to establish the overall hierarchical

flow of the cultural values of materialism, individualism, and collectivism with

regard to consumers’ perceived symbolic and functional roles of price, which in turn

affected the on-going search and mall shopping behaviour for apparel products

based on the combined sample from two cultures, American and Korean. The

findings illustrated the cross-cultural validation using the hierarchical model of

values-price perception on-going search shopping behaviour. However, the

underlying constructs explained that such flow differed considerably across the

cultures. Finally, concluded that a considerable degree of cross-cultural research

recognized the impact of cultural values of individualism and collectivism on

individuals’ consumption behaviour.

Kropp et.al, (2005),65 examined the inter-relationships between values,

collective self-esteem, and consumer susceptibility to interpersonal influence.

Results indicate that external and interpersonal values are positively related to the

normative component of consumer susceptibility to interpersonal influence, while

internal values are negatively related to the normative component of consumer

susceptibility to interpersonal influence. The researchers found that consumer

susceptibility to interpersonal influence is an important factor in many consumer

purchases that related to self-image. It suggested that the relationship of values and

collective self-esteem to consumer susceptibility to interpersonal influence provided

valuable insights to managers regarding consumer purchasing behavior.

Anandan et.al, (2006),66studied the preferences of English newspaper

readers and segmented them on psychographic basis using Values & Life style

64Kittichai, W (2005). A hierarchical model of values, price perception, ongoing search and shopping

behaviors: A cross-cultural comparison. ProQuest, UMI Dissertations Publishing. 65Kropp, F., Lavack, A. M., &Silvera, D. H. (2005). Values and collective self-esteem as predictors

of consumer susceptibility to interpersonal influence among university students. International Marketing Review, 22(1), 7-33 pp.

66C.Anandan, M.Prasanna Mohanraj, &S.Madhu (2006), A Study of the Impact of Values and Lifestyles (VALS) on Brand Loyalty with Special Reference to English Newspapers. Vilakshan, XIMB Journal of Management, 97-102 pp.

53

(VALS), a tool created by the SRI International in 1978 to understand people’s

personality through their behaviours. The researchers analyzed the influence of

psychographic factors on brand loyalty using a Brand Loyalty scale, which

segregated the VALS segments for the study. It was found that Brand image are

related to psychographic profiles of the customers. Thus, based on the findings of

the study, it was suggested that different types of market dominance strategies were

necessary to sustain in the market environment.

Roy &Goswami (2007),67 examined the frequent clothing purchase behavior

of undergraduate urban college-goers in India and also assessed the value-

psychographic traits-clothing (VPC) purchase behavior hierarchy. A List of Values

(LOV) scale was used by the researchers for Exploratory Factor Analysis (EFA)

with principal components analysis and Varimax rotation. The results from the study

indicated that EFA of the LOV scale yielded two dimensions- outer-directed values

and inner-directed values. Thus, the study suggested that the marketers of clothing,

for college-goers should frame his/her product and build communication strategy in

such a way that it appeals to the fashion-conscious and innovative consumers.

Kevin Kuan-shun Chiu (2008),68 adopted a psychographic approach to

study how personal values could be associated with the demographic characteristics

to establish a market segmentation tool to understand the relative perceived

importance among various marketing mix elements for athletic foot wear. Kahle’s

LOV was used to explore the patterns of influence of personal values on consumer’s

decision-making process for a buying behaviour. The major findings indicated that

personal values were far more likely than demographic characteristics to

comprehend the significance that existed among different decision-making criteria

for sport shoes buying behaviour.

67Roy, S., & Goswami, P. (2007). Structural equation modelling of value-psychographic trait-clothing

purchase behavior: a study on the urban college-goers of India. Emerald Group Publishing Limited, 8(4), 269-277 pp.

68Kevin Kuan-Shun Chiu (2008) The Role of Psychographic Approach in Segmenting Young Adults’ Buying Behavior for Athletic Footwear.

54

Vigaray & Hota (2008),69 assessed the regular consumers of fashion

apparel, which focused on extending Schwartz’s motivational typology of values

and measured Spanish consumer values and identified actionable target markets and

consumer segments. The researchers found that there existed significant differences

with respect to Schwartz’s original typology and the differences are consistent with

the nature of values, as different cultures and societies could give origin to similar

value structures, but with values varied somewhat in intensity and direction. Thus,

the results showed that Schwartz’s typology is valid for most part in the Spanish

cultural context.

Thompson (2009),70 explored the validity of three constructs of Kahle’s List

of Values (LOV) - viz., Being Respected, Security and Self-fulfilment. Researcher

used qualitative exploration of the meanings individuals’ attached to the component

values of the LOV. A sample of under-graduate students were selected, using the

diary-interview method, students wrote the subjective definition of each value label

which were later clustered and analyzed using quantitative content analysis. No

single inclusive definition could be derived for any of the values examined from the

study. Thus, the researcher concluded that each value of the LOV was subjected to

the varied interpretations to the respondents. Hence clear definitions to the values

are to be provided in the scale for common understanding of the value labels.

Foula Kopanidis (2009),71 this paper develops a reliable and valid personal

values importance scale (PVIS) using a two phase approach designed to capture the

specific domains of the nine List of Values for application in the context of

education. The role of values as that of standard or criterion used in the formulation

of attitudes and guidance of behaviour is particularly relevant for marketers. Values

impact choice criteria and are instrumental in determining benefit segmentation.

Undergraduate students as a market are recognised as a relevant and important

segment by tertiary institutions, but few studies have taken on an approach to

69Vigaray, M. D. J., & Hota, M. (2008). Schwartz values, consumer values and segmentation: The

spanish fashion apparel case. Lille economic & management, 1-32 pp. 70Thompson (2009), Interpreting Kahle’s List of Values: Being Respected, Security, and Self-

Fulfillment in Context. UW-L Journal of Undergraduate Research XI, 1-9 pp. 71Foula Kopanidis. (2009).Towards the Development of a Personal Values Importance Scale (PVIS) -

Application in Education. ANZMAC 2009

55

examine personal values as an underlying driver. The results showed support that

the LOV scale consists of two underlying dimensions that of ‘internal’ and ‘external

values’. The internal dimension was measured by the four values of ‘self fulfilment’,

‘self of accomplishment’, ‘self respect’, and ‘excitement’. The external dimension

was measured and represented by the values of ‘being well respected’, ‘sense of

belonging’ and ‘warm relationships with others’. The data indicates that these

factors are convergent on these two dimensions and that the relationship of the PVIS

scale developed has discriminant validity.

Kaze & Skapars (2010),72 analysed the consumption patterns and consumer

behaviour in Latvian alcohol market, suggesting a behavioural consumer

segmentation model to the industry to gain competitive advantages. It was proposed

that both life-style and social values as behavioural segmentation approaches which

delivered applicable customer-centric insights and developed the Social Values

Model (Kaze 2010) linking human values, life-style and need states. This model was

applied to the Latvian alcohol market. The findings of the study revealed that life

style based segmentation offers simplicity but is negatively affected by situational

character. However, social values model offer better understanding of consumer

motivation than life style based model.

Mathews & Nagaraj (2010),73 together made a ‘Values, Attitudes and

Lifestyles’ analysis of youth based on gender to identify the behaviour of the youth

with reference to family, fashion, education, brand and shopping activities. For the

purpose of the studying Values, Attitudes and Lifestyles (VALS) a set of 15

statements on Activities, Interests and Opinions (AIOs) were asked to the

respondents. Then the statements were rated on 5 point Likert scale. It proposed that

market segmentation by gender revealed men and women respond differently to

marketing messages, and different marketing appeals influenced them differently.

Thus in order to market effectively the product, the marketers should know that

72Kaze, V., & Skapars, R. (2010). Paradigm shift in consumer segmentation to gain competitive

advantages in post-crisis FMCG markets: Lifestyle or social values? The Journal Of Economics And Management, 16, 1266-1273.

73 Mathews, S., & Nagaraj, H. (2010). An analytical study of vals on youth –implication to marketers.

56

among men and women there are certain differences in values and purchase

motivations on different items.

Narang. R (2010),74aimed to study and identify the psychographic segments

among the Indian youth and compare the results with the youth from other

developing nations. 270 students from various disciplines in the age group of 16-26

from various colleges in Lucknow were selected using stratified sampling method.

The researcher developed an instrument to profile the youth based on

psychographics. The instrument comprised of sixty seven AIO statements drawn

from literature review of previous studies and nine statements based on the LOV

Scale. Finally, the findings revealed that psychographic segmentation would provide

deeper insights into the leisure behaviour, motives, interests and activities of

different segments of the Indian youth to draw more meaningful and effective

marketing strategies for the marketers.

Rebecca Garnett, B.S. (2010)75. The purpose of this study was to determine

the effects of psychographic (shopping orientation, lifestyle, social class),

demographic (gender, ethnicity, age), and geographic (area of residence) variables

on time-related shopping behaviours when shopping for clothing for the self. Data

were collected via a questionnaire with an online survey company. Through analysis

of chi square statistics, ANOVA, Pearson product-moment correlation, and factor

analysis, it was found that psychographics and demographics affected time-related

and other shopping behaviours. Geographics was found to affect shopping

behaviour, but not specifically the time-related shopping behaviours studied. The

study also found that the demographic variables of gender, ethnicity, and age

affected time-related shopping behaviours and shopping preferences. Area of

residence was found to only affect general preference for bricks-and-mortar stores

versus online stores. Age was the only other variable in the study found to affect this

preference. Area of residence seems to be less interconnected to the psychographics

and demographics examined in this study.

74Narang, R. (2010). Psychographic segmentation of youth in the evolving Indian retail market. 75 Rebecca Garnett, B.S. (2010). Examining The Effects of Psychographics, Demographics And

Geographics On Time-Related Shopping Behaviors. University Of North Texas.

57

Fotopoulos et.al, (2011),76 aimed to validate the 42item PVQ (Schwartz's

portrait value questionnaire) typology, which is extensively been used in personal

values research, using a sample that is nationally representative, consisting of 997

consumers. The main objective was to investigate whether higher-than-average

regular purchasing of quality food products (i.e. organic and PDO labelled products)

coincided with stronger identification with specific PVQ values. However, findings

revealed that despite the emergence of a clear relation between consumers' self-

transcendence and security value similarity and higher-than-average frequency of

quality food purchasing, quality food consumers did not form a separate and clearly

diversified cluster if the PVQ inventory functions are treated as a basis for

segmentation. Finally the paper showed that values could be used to meaningfully

segment quality food consumers, but there is still much to learn regarding the

direct and indirect determinants of quality food purchase behaviour.

Jain et.al,(2011),77 explored the relationship between General Values and

Clothing Behaviour of College-going Students. The study was carried out on 160

girls from colleges in Jaipur, Rajasthan. Two scales were used – Ojha’s Value Scale

and Clothing behaviour scale developed by the researchers. Results indicated that,

students place economic value on top and their educational background does make

an impact on clothing behaviour. It was also found that aesthetic and economic

clothing values have more dominant positions in the value configuration of women

than any of the other clothing values.

76Fotopoulos, C., Athanasios, K., & Pagiaslis, A. (2011). Portrait value questionnaire's (pvq)

usefulness in explaining quality food-related consumer behavior. British Food Journal, 113(2).

77Jain, R., Singh, R., & Rankawat, K. (2011). General values and clothing behaviour of college going students.

58

STUDIES USING THE CONSUMER STYLES INVENTORY (CSI) ON

YOUTH

Arroba (1977),78 looked into the increased interest in teaching decision-

making skills, so the need for an empirically-derived classification system of

decision-making behaviours would have its growth and importance. Six styles of

decision making were accordingly isolated and validated by content analysis in the

research. Using cluster analysis, the styles were found to group into types along a

passive-active continuum of involvement in the decision. The results showed that

uses of styles were found to vary across situations, and to be related to the decision's

perceived importance and the decision-maker's control in the particular situation.

Hou & Lin (1986),79 used the CSI on non-student sample to investigate

shopping styles of working Taiwanese female. Both an exploratory factor analysis

and a confirmatory factor analysis were adopted to validate the CSI inventory. The

study also modified the measured items of the CSI, which was originally developed

by Sproles and Kendall (1986), and Susan (2005). A ten factor model was proposed

in the study in order to explore the shopping styles of Taiwanese working female.

Finally, four (Active Fashion Chaser, Value Buyer, Rational Shopper and Opinion

Seeker) of the ten dimensions have been confirmed by the use of the data that as

collected from working female from Kaohsioung and Taipei city in Taiwan.

Sproles & Kendall (1987),80 the research developed a short-form Consumer

Styles Inventory for easy application by classroom teachers. It has helped to

understand the varied approaches consumers use, educate consumers on the

decision-making approaches they pursue, and develop educational and informational

strategies that improve these approaches. In conclusion, it was recommended that

educators administered the Consumer Styles Inventory in the classes and discussed

the results with students in class. These applications would help students to gain

78Arroba, T. (1977). Styles of decision making and their use: An empirical study. British Journal of

Guidance and Counseling, 5(2), 149-158 pp. 79Hou, C., & Lin, Z. H. (1986). shopping styles of working Taiwanese females. Graduate School of

Marketing Management, National Chung Cheng University. 80Sproles, G.B., and Kendall, E.L. (1987). “A Short Test of Consumer Decision Making Styles.” The

Journal of Consumer Affairs, 5, 7-14 pp.

59

understandings while they are learning the consumer styles, and thus help to

improve or redefine the purchasing styles to better reflect the personal interests and

goals.

Sproles & Sproles (1990),81 the study examined the interrelationships

between individual learning styles and specific consumer decision-making styles.

Statistically significant relationships were found between 21 of the 48 learning style-

consumer style characteristic pairs. The research has implied that consumer decision

making is a function of the particular learning style a consumer has pursued. Thus,

the study is one step towards formally delineating the associations of human

learning and consumer decision making, but it is one of many steps that must be

taken before those relationships and their causal nature are to be understood.

Halfstrom, et.al, (1992),82 identified decision-making styles of young

consumers in Korea and investigated if those styles were similar to that of U.S.

young consumers. An instrument, based on previous research in the United States,

was administered to 310 college students in Korea. Data was factor analyzed and

alpha coefficients were computed for scale reliability. Thus, findings indicated the

generality of some consumers’ decision-making styles. Similarities and differences

between cultures were also discussed, and relevant implications were provided.

Durvasula et.al, (1993),83 the study examined the cross-cultural

applicability of a scale for were similar to Sproles and Kendall (1986) and were also

consistent with the stream of research that addressed the cross-cultural

generalizability of consumer behaviour measurement scales and procedures.

Examination of the scale's psychometric properties (i.e., dimensionality and

reliability) offers general support for the scale's applicability to different cultures.

Some differences were detected. However, the paper concluded with a discussion of

81Sproles, E.K., and Sproles, G.B. (1990). “Consumer Decision Making Styles As A Function Of

Individual Learning Styles.” The Journal Of Consumer Affairs, 24(1), 134-147 pp. 82Halfstrom, J. L., Chae, J. S., and Chung, Y. S. (1992). “Consumer Decision Making Styles:

Comparison Between United States and Korean Young Consumers.” Journal of Consumer Affairs, 26(1), 1-11 pp.

83Durvasula, S., Lysonski, S., & Andrews, J. C. (1993). A cross-cultural study of the generalizability of a scale for profiling consumers' decision-making styles. Journal of Consumer Affairs, 27(Summer), 55-65 pp.

60

these differences and the implications of the findings. As a result, their cross-cultural

generalizability remains unknown.

Lysonski et.al, (1996),84 conducted with undergraduate business students in

four countries to investigate the applicability of the Consumer Styles Inventory

keeping intact with other countries. The results of factor analysis were quite similar

to Sproles and Kendall (1986). However, the study confirmed seven of the eight

Sproles and Kendall decision-making styles, which excluded Price Conscious/Value

for Money. It was suggested that decision-making styles from the Consumer Styles

Inventory might be influenced by different cultures in other countries, as well as

different retail environments (types of retail stores available, whether consumers use

credit cards in the particular country). Thus the researchers concluded that there

might be specific decision-making style differences within cultures.

Shim (1996),85 attempted to conceptualize the distinct factors that would

characterize an adolescent’s consumer decision-making style from the perspective of

consumer socialization. Eight consumer decision-making styles were proposed to be

associated with the influence of socialization agents and antecedent variables (e.g.,

social structural and developmental variables). Antecedent variables, especially

social structural variables such as gender, ethnicity, main reason for working, and

the amount of parental allowance, demonstrated significant correlations with

consumer decision-making styles. Antecedent variables, however, were in general

found to be only distantly related to the influence of socialization agents.

Fan& Xiao (1998),86 administered the Sproles and Kendall (1986)

Consumer Styles Inventory to see if the consumer decision-making styles could be

generalised to Chinese college students. Their findings suggested that the decision-

making styles of Impulsive/Careless and Habitual/Brand Loyal were not

characteristic of the Chinese sample.

84Lysonski, S., Durvasula, S. and Zotos, Y. (1996), “Consumer Decision-Making Styles: A

Multicountry investigation”, European Journal of Marketing, Vol. 30, No. 12, pp. 10-21 pp. 85Shim, S. (1996). “Adolescent Consumer Decision Making Styles: The Consumer Socialization

Perspective.” Psychology & Marketing, 13(6), 547-569 pp. 86Jessie X. Fan, Jing J. Xiao (1998), Consumer Decision-Making Styles of Young-Adult Chinese

onsumers. Journal of Consumer Affairs.Volume 32, Issue 2, pages 275–294, Winter 1998.

61

Mitchell & Bates (1998),87 administered the Consumer Styles Inventory in

undergraduate students in the United Kingdom and expanded the categories of

consumer decision-making styles from eight (Sproles & Kendall, 1986) to ten. The

two new categories introduced were Time-Energy Conserving (Hafstrom et.al,

1992) and Store Loyalty. These new categories were re-combined with some

statements from Sproles and Kendall’s (1986) and other consumer decision-making

styles, such as Impulsiveness, Perfectionist and Brand Loyalty.

Siu & Hui (2001),88 the study attempted to validate a widely adopted US-

based Scale, Consumer Style Inventory (CSI), with a sample in China. It resulted in

a 29-item and 8-factor solution. The cross-cultural examination reinforced the

inventory as a universal theory in the area of decision-making style. Thus the overall

results compared favoured to those of the original study and provided a general

support to the inventory. The findings showed that four decision-makings styles,

namely: Perfectionistic, Novelty-Fashion Conscious, Recreational and Brand

Conscious, are common characteristics to both Americans and Chinese. Thus, study

has shed some light to global marketers who intend to enter the China consumer

market.

Walsh et.al, (2001),89tested the generalizability of Sproles and Kendall’s

consumer styles inventory (CSI) in different countries and therefore an attempt was

made to extend the original work which led the authors to test the structure of

decision-making styles of German shoppers and it’s use in segmenting consumers.

The authors concluded that consumers’ decision-making styles could be used as the

basis of segmenting consumers and it was likely that both specific needs and product

and service preferences are associated with these segments. Thus, further research is

required to determine to what extent purchase behavior differed at the product level,

87Mitchell, V.W. & Bates, L. (1998). UK Consumer Decision Making Styles. Journal of Marketing

Management, 14, 199-225 pp. 88Siu, N.Y.M. and Hui, A.S.Y. (2001). “Consumer Decision Making Styles In China: A Cross

Cultural Validation.” Asia Pacific Advances in Consumers Research, 4, 258-262 pp. 89Walsh, G., Thurau, T. H., Mitchell, V. W. and Widmann, K. P. (2001).“Consumers' Decision

Making Style as A Basis For Market Segmentation.” Journal of Targeting, Measurement And Analysis For Marketing, 10(2), 117-131 pp.

62

which would give more information on exactly what the identified segments could

look for in products to satisfy the differing needs.

Canabal (2002),90 the exploratory study investigated the decision-making

styles of young South Indian consumers. The data for the study were collected from

two institutions of higher education in the city of Coimbatore, India in the fall of

1995 utilizing the Consumer Style Inventory (CSI) and also adapted the conceptual

framework to determine applicability of the Consumer Styles Inventory. The results

of the study were compared to similar studies where data from the United States,

Korea and China were analyzed. Five reliable factors and their corresponding

decision - making styles were identified. The findings suggested that Indian

consumers’ impulsiveness were more related to indifference to brands rather than

carelessness of decision-making. The South Indian students tend to be mainly

perfectionists in their market decisions. They look for high quality products and they

also enjoy shopping. However, they can be confused by too many choices and to a

lesser degree these consumers tend to be brand conscious. The study also added a

new category, “dissatisfied/careless,” to reflect the findings.

Ng(2002),91 confirmed the eight-factor model of Sproles & Kendall (1986)

and two more decision-making characteristics were also found as part of the Chinese

Eleven-Factor Model of CSI. The additional factors were labelled as "Time-Energy

Conserving", "Store-Brand-Hopping Consumer", and "Shopping Indifference

Consumer". They thus established the generalizability and applicability of the CSI in

China setting. The study concluded that consumers’ decision-making styles and

profiling their buying characteristics not only determined the success of marketing

segmentation strategy in the real business world, but also improved the academic

research in consumer research discipline.

90Canabal , M. E. (2002). Decision making styles of young south Indian consumers: an exploratory

study. College Student Journal, 36(1). 91Ng, S. W.(2002). Profiling Chinese consumers stylesba cross-cultural generalizability study Of

consumers’ decision-making style. Asia Pacific Advances in Consumer Research ,5, 258- 264 pp.

63

Backwell & Mitchell (2003),92 examined the decision-making styles of adult

female Generation Y consumers in the UK. Five meaningful and distinct decision-

making groups were identified in the study: “recreational quality seekers”,

“recreational discount seekers”, “trend setting loyals”, “shopping and fashion

uninterested” and “confused time/money conserving”. In the further study on

decision-making styles of male consumers in the UK (2004), all of the original eight

traits plus four new traits namely; store-loyal/low-price seeking, time-energy

conserving, confused time restricted and store-promiscuity were also identified. The

study also demonstrated the potential of the CSI for segmenting markets as

meaningful and distinct groups of male consumers with different decision-making

styles. Later (2006), the study used a sample of 480 male and female undergraduate

students in UK, to compare their decision-making styles. They found that nine

decision-making styles were common to both genders. In addition, three new male

traits (store-loyal/low-price seeking, confused time-restricted and store-promiscuity)

and three new female traits (bargain seeking, imperfectionism and store loyal) were

also identified in the study.

Bao et.al, (2003),93 explored the effects of two cultural dimensions, face

consciousness and risk aversion, on consumers’ decision-making styles. Data from

China and the United States show that consumers in the United States differed from

their counterparts in China in decision-making styles. Face consciousness and risk

aversion appeared to contribute to such divergence. Thus, the exploratory study

stimulated scope for further research in order to identify more underlying

contributors rather than merely examining the cross national differences in consumer

decision-making styles.

Kamaruddin & Mokhlis (2003),94 together defined four social structural

variables (social class, gender, ethnicity, residence, and religion) and used it to

92Backwell, C., and Mitchell, V.W. (2003).“Generation Y Female Consumer Decision Making

Styles.”International Journal of Retail & Distribution Management, 3(2), 95-106 pp. 93Bao, Y., Kevin, Z. Z., and Su, C. (2003). “Face Consciousness and Risk Aversion: Do They Affect

Consumer Decision Making?” Psychology & Marketing, 20(8), 733-755 pp. 94Kamaruddin & Mokhlis (2003),Consumer socialization, social structural factors and decision-

making styles: a case study of adolescents in Malaysia. International Journal of Consumer Studies. Volume 27, Issue 2, pages 145–156 pp.

64

determine its influences on consumer decision-making styles. The CSI was

administered to adolescents in secondary schools. Multiple regression analysis

disclosed the differences in decision-making styles between males and females.

Thus, results showed that males tended to be more brand-conscious and females

tended to be more recreational shoppers. Adolescents in urban areas tended to be

more brand-conscious and novelty-conscious than rural adolescents.

Bae (2004),95 earlier studies focused only on general consumer's shopping

behaviors. The main purpose of the study was to apply a consumer decision-

making model based on Consumer Style Inventory (CSI), invented by Sproles and

Kendall (1986), to be more specific on the shopping styles involved in athletic

apparel and to examine whether specific shopping pattern differences existed

between selected university students in the United States and South Korea. As a

result, American and Korean college-aged consumers demonstrated different

shopping patterns on quality, recreation, confusion, fashion, impulse, price, and

brand consciousness.

Chase (2004),96 investigated the relationship between beginning college

students' self-reported mind styles, consumer decision-making styles, and shopping

habits. Three instruments were administered: the Gregorc Style Delineator(TM),

the Consumer Styles Inventory, and a Demographic Survey. Findings showed that

there is a significant relationship between gender and self-reported shopping habits.

Females tend to self-report purchases of clothing more frequently than males. And

as well, a Mann-Whitney Rank Sum Test showed that there was a significant

relationship between gender and the Recreational/Hedonistic consumer decision-

making style. Finally, concluding that females tend to be more recreational shoppers

than then males.

95Bae, S. (2004).Shopping pattern differences of physically active Korean and American university

consumers for athletic apparel. ProQuest, UMI Dissertations Publishing. 96Chase, M. W. (2004). The relationship between mind styles, consumer decision-making styles, and

shopping habits of beginning college students. ProQuest, UMI Dissertations Publishing.

65

Kwan et.al, (2004),97explored young Chinese consumers’ decision-making

behaviour towards casual wear purchase in Mainland China. The Consumer Style

Inventory (CSI), developed by Sproles and Kendall (1986) was adapted in the study

and was administered to 161 University students in Shanghai, Beijing and

Guangzhou in the Mainland. The results showed that six decision-making styles

(recreational and hedonistic consciousness, perfectionism consciousness, confused

by over-choice, habitual and brand loyalty, price and value consciousness and brand

and fashion consciousness) were found in the Mainland. Confirmatory Factor

Analysis (CFA) was first performed with AMOS program for testing the

applicability and appropriateness of Sproles and Kendall’s 8-factor structured

consumer decision-making style model in the study. The results of the CFA

disconfirmed the original structure of Sproles and Kendall’s model, as Goodness of

Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Root Mean Square

Residual (RMR) and Comparative Fit Index (CFI) were all fall out of their critical

values. This indicated that there was a bad fit between the original 8 factors

structured model and the data.

However, in the year (2006),98 similar study done subsequently, identified

that seven styles were valid for young clothing consumers in China. Significant

influence of demographic characteristics, such as gender, number of siblings and

birth order on several consumer decision-making styles were also identified. The

findings from the study gave valuable insights for academic practitioners and

clothing marketers into young Chinese consumers' decision-making practices in

terms of casual wear purchases. In addition, they also provided a basis for academic

practitioners for investigating consumer decision-making styles in a more

comprehensive manner.

97Kwan, C. Y., Yeung, K. W., & Au, K. F. (2004). Decision-making behaviour towards casual wear

buying: A study of young consumers in mainland China. Journal Of Management & World Business Research, 1(1).

98Kwan, C. Y. (2006). An investigation on the factors affecting young Chinese consumers' decision-making behaviour towards casual wear purchase. ProQuest, UMI Dissertations Publishing

66

Mitchell & Walsh (2004),99 compared the decision-making styles of male

and female shoppers in Germany. The researchers confirmed the construct validity

of all eight CSI factors for female shoppers and four of the factors for male

shoppers. It was subsequently concluded that male individuals were slightly less

likely to be perfectionists, somewhat less novelty and fashion conscious, and less

likely to be confused when making purchases than their female counterparts.

Wang et.al, (2004),100 studied the relationship between consumers’ decision-

making styles and their choice between domestic and imported brand clothing using

a sample of Chinese consumers. The results indicated that seven decision-making

styles together with other consumer behavioral characteristics can be used to

distinguish and profile consumers who preferred to buy domestic, imported or both

types of clothing. Empirical findings revealed that consumers who preferred to buy

imported brand clothing tend to have a unique lifestyle and shopping orientation that

differed from those who preferred domestic brand clothing. Conceptual

contributions and managerial implications were also discussed.

Akturan & Tezcan (2007),101 the study aimed at profiling young adults as

consumers through their decision-making styles for apparel products. The data was

collected from college students aged 18-24 by face-to-face interviews. The

consumer decision-making styles were measured by the CSI scale (Sproles and

Kendall, 1986) and 2 additional dimensions (shopping influences and reliance on

mass media) taken from Shopping Styles Dimensions (Tai, 2005). As a result of the

exploratory factor analysis six factors were identified. Finally, in order to classify

the respondents through the decision- making styles, cluster analysis was utilized.

The young consumers form a powerful consumer spending group and hence they

were the target group. These groups have their own consumption patterns, motives,

feelings and styles. They have been also nurtured by companies to cement loyalty so

99Bakewell, C. & Mitchell, V. W. (2004).Male consumer decision-making styles. International

Review of Retail, Distribution and Consumer Research, 14(2), 223-240 pp. 100Wang, C.L., Siu, N.Y.M. and Hui, A.S.Y. (2004). “Consumer Decision Making Styles On

Domestic And Imported Brand Clothing.” European Journal Of Marketing, 38(½), 239-252 pp.

101Akturan, U., Tezcan, N., (2007), “Profiling young adults: Decision-making styles of college students for apparel products”, in: 6eme Journees Normandes de Reserchesurla Consommation: Societeetconsommations, Groupe ESC Rouen, Rouen, 19-20 March, 2007.

67

that they would be valuable consumers later. They are also perceived as valuable

early adopters. Thus concluded that the companies need to understand the behaviors

of the target group as a consumer in order to get closer and establish a long term

relationship with them.

Ghodeswar (2007),102 investigated the decision-making style among

students of a Business School in India. Findings revealed seven decision-making

styles which were grouped into six factor structure. Price Consciousness was the

factor which was not confirmed in the study.

Hanzaee & Aghasibeig (2008),103 in an Iranian setting, indicated that

Generation Y male and female consumers differ in their decision-making styles.

However, of the 10-factor solution confirmed for males and 11-factor solution for

females, nine factors were found to be common to both genders. The researchers

regarded the similarity as a result of the changing gender roles in modern Iran.

Unal & Ercis (2008),104 attempted to study consumers’ decision-making

styles with the CSI approach. Males and females living in Erzurum, Turkey,

constituted the population of the study. How gender affected consumers’ decision-

making styles was analyzed in the study. The CSI dealt with the mental orientation

of consumers in making decisions and, therefore, focused on the cognitive and

effective orientations in consumer decision-making and identified eight mental

characteristics of consumer decision-making. According to the results concluded,

male and female consumers had different decision-making styles.

Patel (2008),105 investigated the consumers’ decision making styles in

shopping malls and studied variations in the consumer decision making styles across

different demographic variables. An attempt was made to profile the decision 102Ghodeswar, B. M. (2007). Consumer decision-making styles among Indian students. Alliance

Journal of Business Research, 3(spring), 36-48 pp. 103Hanzaee, K. & Aghasibeig, S. (2008). Generation Y female and male decision-making styles in

Iran: are they different? The International Review of Retail, Distribution and Consumer Research, 18 (5), 521–537 pp.

104UnalS., and Ercis A. (2008). “The Role Of Gender Difference In Determining The Style Of Consumer Decision Making.” Bogazici Journal, 22(1-2), 89-106 pp.

105Patel, V. (2008). “Consumer Decision Making Styles in Shopping Malls: An Empirical Study.” New Age Marketing: Emerging Realities, 627-637 pp.

68

making styles of Indian Consumers in shopping malls. Sproles and Kendall (1986)

identified nine decision making styles while in the study, researcher found only six

decision-making styles in Indian environment. Results showed that single consumers

are more price conscious than married consumers. Young consumers between the

age group of 11-20 years are most recreational in their shopping. Above all Indian

consumers are confused by over choice, novelty conscious, and variety seekers.

Yesilada & Kavas (2008),106 the study investigated whether the CSI could

be generalized to the female consumers living in TRNC. Findings of the study gave

some idea about the decision making styles of the Turkish Cypriots, which might be

of value for the retailers not only in the north, but also in the south of the island as

these consumers preferred to shop from the south as well. The results confirmed

three of the eight original decision making traits and identified five new ones two of

which are somewhat similar to the two original traits. Thus, the CSI’s

generalizability across cultures, have received only limited support from the current

study.

Boonlertvanich (2009),107adapted the Consumer Style Inventory (CSI), to

examine the consumer’s purchasing behaviour of digital still camera market in

Bangkok. Some factors other than the Consumer Style Inventory were added to

increase credibility of the study such as social influence, media influence and

lifestyles. It focused on the relationship among age, gender, income and other

factors with eight styles of consumer decision making. Finally, it was found that

genders had different tastes in their fashion, social habits, brand loyalty, lifestyle

consciousness and style of customers.

Kamaruddin & Kamaruddin (2009),108 the study investigated the Malays’

decision-making styles pertaining to shopping behavior. It also examined the

association between Malays’ cultural value orientations and their decision-making

106Yesilada, F., and Kavas, A. (2008). “Understanding The Female Consumers Decision Making

Styles.” Isletmefakultesidergisi, cilt, 9(2), 167-185 pp. 107Boonlertvanich, K. (2009). Consumer buying and decision making behavior of a digital camera in

Thailand. RU.Int. J. vol. 3(1). 108Kamaruddin, A.R., and Kamaruddin, K. (2009). “Malay Culture and Consumer Decision-Making

Styles: An Investigation On Religious And Ethnic Dimensions.” Journal Kemanusiaan, 14, 37-50 pp.

69

styles. The findings revealed that Malay consumers are quite incompetent in

handling product and market information, resulting in information overload and

confusion. Therefore, the results suggested that formal consumer education should

be introduced in secondary schools in developing knowledgeable and efficient

young consumers.

Mokhlis et.al, (2009),109 investigated the decision-making styles of young

Malay, Chinese and Indian consumers in Malaysia using Consumer Style Inventory

(CSI) developed by Sproles and Kendall (1986). It attempted at verifying the

generalizability of Sproles and Kendall’s CSI across three ethnic groups within a

Malaysian retail environment. However, the results revealed some interesting

patterns in the decision-making traits of young Malay, Chinese and Indian

consumers. Eight meaningful factors resulted for the Malay and Chinese samples,

and six for the Indian sample.Further (2010),110 gave aninsight into similarities and

differences in cognitive structure underlying consumers’ shopping styles. A total of

477 respondents were classified into three groups based on their religious

affiliations: Muslim, Buddhist and Hindu. Exploratory factor analyses were

employed to compare the shopping styles of these three religious micro-cultures.

The results indicated that interesting similarities and differences in consumer

shopping styles existed among the three religious micro-cultures.

Mokhlis & Salleh (2009),111 investigated the differing approaches of male

and female Malaysian consumers toward shopping and buying activities using

Sproles and Kendall’s (1986) Consumer Style Inventory (CSI) on a sample of 386

Malaysian males and females. Exploratory factor analysis was used to understand

the decision-making styles of both genders. Finally, the study revealed new traits for

male and female consumers that were in contrast with the original CSI factors. The

most important finding is that there is an indication of the generality of several

109Moklis, S., and Salleh, H. (2009). “Decision Making Styles Of Young Malay, Chinese And Indian

Consumers In Malaysia.” Asian Social Science, 5(12), 50-59 pp. 110Mokhlis, S., and Salleh, H. (2010). “Religious Contrasts In Consumer Shopping Styles: A Factor

Analytic Comparison.” Journal of Business Studies Quarterly, 2(1), 52-64 pp. 111Mokhlis, S., and Salleh, H. (2009). “An Investigation Of Consumer Decision Making Styles Of

Young Adults In Malaysia.” International Journal Of Business and Management,4(4), 140-148 pp.

70

consumer decision-making styles of young U.S. and Malaysian consumers. Thus,

the researchers suggested that there is reason for cautious optimism that the CSI has

elements of construct validity and has potential use across international populations.

Anic et.al, (2010),112 examined decision making styles among young-adult

consumers in the Republic of Macedonia using the Sproles and Kendall’s (1986)

CSI. Significant gender differences were found on four factors of consumer-decision

making styles (brand consciousness, novelty-fashion consciousness, recreational

hedonistic consumer and habitual, brand-loyal consumer). Cluster analysis was

employed to classify consumers according to their decision making styles. The

results showed that as compared to male consumers, females appeared to be less

brand conscious and less brand loyal, but more novelty and fashion conscious and

more interested in hedonistic shopping behaviour. The study further indicated that

male consumers and female consumers among the young-adult showed similarity

with respect to perfectionism, price consciousness, impulsiveness, and confused by

overchoice.

Mishra (2010),113 made use of Sproles and Kendall’s (1986) consumer

styles inventory (CSI) on a sample of 425 young-adult Indian consumers and

examined the generalizability of the scale. The study confirmed the applicability of

the original US characteristics as well as two new traits specific to the Indian

context. Thus, emerged from the study that the CSI is sensitive enough and is able to

assess cultural differences and produce sensible results for the research.

Hou & Lin (2011),114* investigated the shopping styles of working

Taiwanese females. Since Sproles and Kendall (1986) developed a consumer style

inventory (CSI) based on the assumption that consumer decision making style could

be divided into eight dimensions, therefore the study focused on the decision making

of students sample with a very few focused on the non-students sample. The most

important findings in the study is that there is an indication of the generality of

112Anic, I. D., Suleska, A. C., &Rajh, E. (2010). Decision-making styles of young-adult consumers

in the republic of macedonia. Ekonomskaistrazivanja, 23(4), 102-113 pp. 113 Mishra, A. A. (2010). Consumer Decision-Making Styles And Young-Adult Consumers: An

Indian Exploration. letmeAra rmalar Dergisi,2(3), 45-62 pp. 114ChienHou, Zhung-Hsien Lin. (2011) Shopping Styles Of Working Taiwanese Females.

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several working female decision making styles and the CSI has the potential use

across international population.

Radam et.al, (2011),115researched based on the Sproles and Kendall’s

(1986) Consumer Style Inventory (CSI). 200 Chinese consumers in Klang Valley

were selected as sample. Six reliable factors of consumer decision-making styles on

clothing were identified in the study. One of the key findings in the study is the

confirmation of majority of the Chinese consumers in Klang Valley were highly

concerned in price/value of money.

Vieira et.al, (2011),116examined the cross-cultural applicability of CSI scale

for profiling consumers’ decision-making style in Brazil. It was investigated with

the belief that decision-making styles, much like personality traits, are likely to be

largely independent of the culture and descriptive of a personal orientation. The

results showed that the eight factors structure existed such as: Perfectionism or

High-Quality; Brand Consciousness; Novelty-Fashion Consciousness; Recreational

and Hedonistic Shopping Consciousness; Price and Value for Money Shopping

Consciousness; Impulsiveness, Careless Consumer Orientation; Confusion from

over Choice of Brands, Stores and Consumer Information; and Habitual, Brand-

Loyal Orientation. The study concluded that the scale, as an overall, was suitable to

be used in Brazil.

STUDIES ON YOUNG ADULTS / YOUTH

Comegys & Brennan, (2003),117 investigated the online purchase behavior

of a key segment of the population, the “Next Generation” undergraduate college

aged student, from two of the countries the United States and Ireland. Researchers

analyzed how frequently students from each country interactively shop online, how

much they spend, what they buy, as well as analyzed whether the students from the

two countries under study approached the Buyer Decision Process differently in the

115Radam , A. P. A., Ali , M. H., & Leng, Y. S. (2011). Decision-making style of Chinese consumer

on clothing .The Journal of Global Business Management. 116Vieira, V. A., Slongo, L. A., and Torres, C. V. (2011). “Evaluating The Psychometric Properties of

Consumer Decision Making Style Instruments. 117Comegys, C., & Brennan, M. .L. (2003). Students’ online shopping behavior: A dual-country

perspective. Journal of Internet Commerce, 2(2), 69-89 pp.

72

use of the Internet. Thus, the results indicated and concluded that almost all college

students were found to use the Internet and they are an integral part of “Next

Generation”.

Jiyeon Kim, (2003)118. The purpose of this research was to examine the

relationship between college students’ apparel impulse buying behaviours and visual

merchandising. This study provides information as to why visual merchandising

should be considered an important component of a strategic marketing plan in

support of sales increase and positive store/company image. This study further

investigated some external factors that influence impulse buying behaviour. The

results proved that there were significant relationships between college students’

impulse buying behaviour and in-store form/mannequin display and promotional

signage. Even though the window display and floor merchandising did not appear to

significantly lead to college students’ impulse buying behaviour, the results still

suggested that these variables and consumers’ impulse buying behaviour are

significantly correlated.

Sullivan(2004),119 examined socioeconomic characteristics and motivational

factors related to shopping. Additional attitudes toward shopping, direct marketing,

and advertising were also analyzed. The study pointed out a little significant

difference between the two groups with the exception that the Internet shoppers

placed more value on convenience. However, minor differences were found between

education level and age. Thus, the results demonstrated that the internet buyers

lacked strong opinion with the exception of their desires, for convenience when the

shop.

Tremblay(2005),120 invested into the subject of impulse buying which has

been studied since the late 1980's mainly by two teams; one Canadian and one is

American. The Self-Completion Theory and the general literature on impulse

118Jiyeon Kim. (2003). College Students’ Apparel Impulse Buying Behaviors In Relation To Visual

Merchandising. Athens, Georgia. 119Sullivan, D. P. (2004).A profile of generation y online shoppers and its application to

marketing.ProQuest, UMI Dissertations Publishing. 120 Tremblay, A. J. (2005). Impulse buying behavior: Impulse buying behavior among college

students in the borderlands. ProQuest, UMI Dissertations Publishing.

73

purchasing provided the foundation for understanding the purchasing power of

college students in 2004. Therefore, it was observed that some main variables such

as gender, credit money, childhood experiences and obsessive-compulsive disorder

could help explain the high rates of impulse purchases among college students in

America.

Magie(2008),121 examined the fashion involvement of female and

male consumers, aged 13 to 18, residing in the United States and the relationships

among demographic characteristics, lifestyle, usages of fashion information sources,

apparel shopping orientations, patronage behaviours and fashion involvement.

Findings indicated that female teens have higher fashion involvement than male

teens, and lifestyle activities, shopping orientations, and patronage behaviours do

influence fashion involvement.

Szendrey(2008),122 examined the underlying familial/parental factors which

would increase degrees of frugality, an opposite behaviour to that of compulsive

buying. However, results indicated that the proposed model significantly predicted

the degree of undergraduate frugality and that the following four familial/parental

influences are conducive to raising more conscientious consumer- and consumption-

minded students: (1) the perceived degree of frugal behaviours of the family in

which a student was raised, measured by a newly developed scale (statistically

significant, positively related), (2) intergeneration communication relating to

consumer skills (statistically significant, positively related), (3) intangible family

resources such as time and attention, discipline, life skills and instruction, emotional

support and love, and role modelling and guidance (statistically significant,

positively related), and (4) family socioeconomic status including perceived family

financial status, parental education levels, and home ownership status (statistically

significant, negatively related).

121Magie, A. A. (2008). An analysis of lifestyle, shopping orientations, shopping behaviors and

fashion involvement among teens aged 13 to 18 in the United States .ProQuest, UMI Dissertations Publishing.

122Szendrey, J. M. (2008). An empirical consumer behavior study of familial/parental influences on the degree of frugality of undergraduate students. ProQuest, UMI Dissertations Publishing.

74

Bhawnani (2010),123 investigated on what excited the youth, grabs their

attention, interests and influences them. It aimed to capture key youth trends based

on factors such as: Lifestyle, Technology, Entertainment, Education, Career and

Culture. A small survey of youth in Urban India (Delhi) was conducted between the

age group of 16 to 25 years. It studied the lifestyle of youth, their perception and the

buying behaviour. Results showed that Indian youth profile were looking on more

towards factors such as: Freedom to pursue their talents, Fame, Success & Growth,

Fitness freaks, Showcase their strengths and Tech-savvy.

Hemalatha et al, (2010),124investigatedthe behaviour of youth in shopping

malls in a globalised economy. 19–25 years old constituted a bridge between

adolescents and adults when buying behavior is in transition. It would help retailers

to examine current and potential patrons, thereby providing guidance for store

design and marketing communications strategy. The most important factors for

visiting malls is social shopping, idea shopping, role shopping, adventure shopping,

value shopping, gratification shopping, shopping for stress relief, shopping to

alleviate a negative mood, and shopping as a special treat to oneself.

Saleem et al, (2010),125 determined the effect of factors like age, tendency to

spend, post purchase guilt, drive to spend compulsively, and feeling about shopping

and spending and dysfunctional spending on compulsive buying behaviour of youth

in Pakistan. Data was collected from college and university students from Lahore,

Islamabad and Bahawalpur of age 18 to 32 years. The compulsive buying scale

established by Edward (1993) was used to measure compulsive buying of youth in

Pakistan. Results showed that compulsive buyers generally tend to be younger and

also compulsive buyers are motivated by an internal trigger such as shopping and

spending.

123Bhawnani (2010). What all excites the Indian Youth now? 124Hemalatha, K. G., Jagannathan, L., &Ravichandran, K. (n.d.).Shopping behaviour in malls in

globalised economies. 125Saleem , S., Salaria, R., Megha, V. (2010). Few determinants of compulsive buying of youth in Pakistan.

75

4Ps B&M in association with Indian Council for Market Research

(ICMR) & Cvoter, (2011),126 researched to know the Indian youth inside out in

order to showcasean in-depth analysis of the Indian youth (in the age bracket of 18-

25 years) and its unique buying behaviour across product categories. The survey

included responses from 1,628 respondents belonging to 31 different Indian cities.

The target respondents were administered with a structured questionnaire and the

Survey had a good mix of working and non-working individuals. The process was

an attempt to understand the buying behaviour of the youth in categories like mobile

phones, gadgets, internet usage and apparels (especially casual wear). Thus, the

analysis of the survey represented the categorized and the cities’ different tier zones

to further understand the diversity of the Indian youth.

Ram Kulkarni and Dilip Belgaonkar. (2012).127 This paper reports the

results of a study of brand selection and loyalty within the 18–25 age groups of

Indian youth surveyed in Nashik city. The study explores brand loyalty behaviour

across different product categories, and investigates the dimensions that drive

loyalty behaviour within this age group. Finally, the study is concluded stating

Indian youth is more quality conscious, they prefer only brands those are time

tested, performing well and showing consistency in quality of the product. Indian

culture is reflecting in their purchase behaviour as they are more cost conscious and

their choice is utility oriented and not price oriented. They don’t go blindly behind

the brands therefore brands are trying to attract more youth consumer.

STUDIES ON APPARELS / CLOTHING BEHAVIOUR

Forsythe and Thomas (1989),128 conducted a study to find the preference

for natural, synthetic, or blended fibre contents or to link perceptions of fibres with

any particular market segment. The researchers examined fibre content preferences

and perceptions among female apparel consumers and the relationship between fibre

1264PS B&M - ICMR SURVEY, 2011. 127 Ram Kulkarni, Dilip Belgaonkar. (2012). Purchase Behavioral Trends and Brand Loyalty of

Indian Youth with Special Reference to Nashik City.International Conference on Humanity, History and Society.IPEDR vol.34 (2012) © (2012) IACSIT Press, Singapore

128Forsythe, S. M., & Thomas, J. B. (1989). Natural, synthetic, and blended fiber contents: An investigation of consumer preferences and perceptions. Clothing and Textiles Research Journal, 7(3), 60-64 pp.

76

content preference and perceptions and demographic variables. Thus, results from

the study indicated that female apparel shoppers had definite fibre content

preferences for various items of apparel; however, these preferences were not

generally related to demographic characteristics.

Shim et.al, (1989),129assessed the role of external variables on attitudes

toward imported and domestic apparel among college students. External variables

included demographics, clothing attitudes, students' self-perceptions, and level of

fashion involvement. The researchers found that the attitudes toward imported

clothing were influenced by the level of fashion involvement, the prestige clothing

attitude, the social activities clothing attitude, and social acceptance. The results also

indicated that students have more favourable attitude towards domestic apparel than

imported apparel.

Thomas et.al, (1991),130 investigated the underlying dimensions of apparel

involvement in consumers' purchase decisions. The researchers analyzed whether

the apparel involvement is composed of more than one dimension and also

determined whether there is any variation in apparel involvement dimensions with

the help of fibre information sources and demographics. The results from the study

indicated that apparel involvement is composed of more than one dimension and is

partially explained by fibre information sources. It was also found that one of the

two identified apparel involvement dimensions differed based on the consumer

demographic variables.

Huddlestonet.al,(1993),131 assessed whether apparel selection were the

predictors of female consumers' brand orientation. The criteria’s included quality

proneness, fibre consciousness, easy care preference and made in the USA. Data

was collected from 383 female consumers through mailed questionnaire regarding

129Shim, S., Morros, N. J., & Morgan, G. A. (1989). Attitudes toward imported and domestic apparel

among college students: The fishbein model and external variables. Clothing and Textiles Research Journal, 7(4), 8-18 pp.

130Thomas, J. B., Cassil, N. L., & Forsythe, S. M. (1991). Underlying dimensions of apparel involvement in consumers' purchase decisions. Clothing and Textiles Research Journal, 9 (3), 45-48 pp.

131Huddleston, P., Cassil, N. L., & Hamilton, L. K. (1993).Apparel selection criteria as predictors of brand orientation.Clothing and Textiles Research Journal, 12(1), 51-56 pp.

77

brand orientation and apparel selection criteria. The results from the study revealed

that quality proneness and made in the USA were predictors of brand orientation.

The researchers suggested that this would help in planning consumer programs and

as well helps retailers in planning product and promotion mixes, understanding

target consumers, and refining training programs.

Lee&Burns (1993),132 examined the relationships between the criteria that

individuals used in the purchase of clothing and the individual traits of public and

private self-consciousness between two cultural groups namely United States and

Korea. Researchers explored the importance of criteria used in the purchase of

clothing, private and public self-consciousness, and demographic characteristics. It

was also found that a significant interaction effected between self-consciousness and

cultural group for the importance of brand name as a clothing purchase criterion.

The results from the study indicated that there is a significant relationship between

the trait of public self-consciousness and the importance of fashion and

attractiveness as clothing purchase criteria in both cultural groups.

Shim and Kotsiopulos (1993),133 analyzed the typology of apparel shopping

orientation segments among female consumers. The researchers segmented female

apparel shoppers into unique apparel shopping orientation groups and developed a

profile for each segment with respect to information sources, importance of store

attributes, lifestyle activities, patronage behaviour, and demographics. The results

indicated that shopping orientations are a base for segmenting female apparel

shoppers and these groups are unique in consumer buying characteristics. The

characteristics included three factors of information sources (Store Fashion

Service/Promotion, Fashion Publications, and Mass Media) and also five factors of

importance of store attributes (Store Personnel, Visual Image of Store, Customer

Service, Easy Access, and Brand/Fashion).

132Lee, M., & Burns, L. D. (1993). Self-consciousness and clothing purchase criteria of korean and

united states college women. Clothing and Textiles Research Journal, 11(4), 32-40 pp. 133Shim, S., &Kotsiopulos, A. (1993). A typology of apparel shopping orientation segments among

female consumers. Clothing and Textiles Research Journal, 12(1), 73-85 pp.

78

Hines & O'Neal (1995),134 assessed how consumers evaluated clothing

quality by examining the cognitive structure that existed between the evaluated

criteria used to judge quality and personal values. It was also found that consumers

evaluated quality by using attributes that they associated with social, psychological,

economic, physiological, and aesthetic consequences. Results from the study

indicated that for this group of consumers, the concept of perceived clothing quality

included a number of associated concepts at various levels of abstraction. The

researchers finally suggested that a proper study should be carried out to assess how

consumers’ evaluated quality and to include factors other than physical attributes.

Fairhurst et.al, (1996),135 assessed apparel retail buyers' perceptions about

the importance and satisfaction with services available at market shows. Researchers

measured manufacturers’ sales representatives’ perceptions of the importance of the

market services. Data was collected from 161 apparel retail buyers and 146

manufacturers’ sales representatives who attended a local Midwest market show.

The results from the study revealed that apparel retail buyers and manufacturers’

sales representatives differed regarding the importance of five market show services.

As compared to retail buyers, manufacturers’ sales representatives attributed more

importance to help for new retailers, show books, and timing of the markets

Beaudoin et.al., (1998),136 investigated whether females fashion leaders and

fashion followers differed in the attitudes towards buying imported and domestic

apparel products. Data was collected from a sample of 283 female consumers

between 18 and 25 years of age through mailed questionnaire. Results showed that

fashion followers have the same overall attitude toward buying American or

imported apparel. However, fashion leaders have significantly more positive attitude

towards followers for buying imported apparel than buying domestic apparel.

134Hines, J. .D., & O'Neal, G. S. (1995). Underlying determinants of clothing quality: The consumers'

perspective. Clothing and Textiles Research Journal, 13(4), 227-233 pp. 135Fairhurst, A. E., Lennon, S. J., & Yu, H. (1996). Retail buyers' and manufacturers' sales

representatives' perceptions of market show services in small apparel markets. Clothing and Textiles Research Journal, 14(3), 161-168 pp.

136Beaudoin, P., Moore, M. A., & Goldsmith, R. E. (1998). Young fashion leaders’ and followers’ attitudes toward American and imported apparel. Journal of Product & Brand Management.7 (3), 193-207pp.

79

Gaal & Burns (2001),137 conducted a study to identify and clarify important

yet inadequate information in a catalogue’s apparel descriptions, and tested if

clarifications of the descriptions altered consumers’ perceived ability to evaluate the

garments and the degree of perceived risk associated with purchasing the garments.

The researchers conducted an experiment to test whether the changes made to the

descriptions influenced consumers’ perceived ability to evaluate the garments, as

well as consumers' perceived risk associated with purchasing the garments. Thus,

results indicated that changes made regarding the fabric/fibre content increased

participants' perceived ability to evaluate the garments, whereas changes made

regarding the sizing/fit did not. However it did not support the notion that type of

change would alter the degree of perceived risk associated with purchasing the

garments.

Asma Kiran, Ayesha Riaz & Niaz Hussain Malik, (2002)138 Investigated

and explained the factors responsible for the change in clothing patterns of the

adolescent girls, that are yet not clearly defined but are un-ignorable. In order to find

out the affect of various factors likesocial status, education, mass media and peer

pressure on the clothing patterns of young girls, a survey was conducted in the

University of Agriculture Faisalabad by distributing a comprehensive questionnaire

among 102 students of B.Sc. Home Economics classes. Results clearly indicated that

friends, family’s socio-economic status, changing trends and education were the

most important responsible factors. It was also revealed that the adolescent girls

were more impressed by the T.V., fashion shows and magazines while brining

change in their clothing patterns.

Xu & Paulins (2005),139 studied the college students’ attitudes and

behavioral intention of shopping online for apparel products by using the theory of

reasoned action. The results from the study showed that the students, in general, had

137Gaal, B., & Burns, L. D. (2001). Apparel descriptions in catalogs and perceived risk associated

with catalogpurchases .Clothing and Textiles Research Journal, 19(1), 22-30 pp. 138Asma Kiran, Ayesha RiazAndNiaz Hussain Malik. (2002). Factors Affecting Change In The

Clothing Patterns of the Adolescent Girls.International Journal Of Agriculture & Biology 1560–8530/2002/04–3–377–378 pp.

139Xu, Y. &Paulins, V.A. (2005). College students’ attitudes toward shopping online for apparel products: Exploring a rural versus urban campus. Journal of Fashion Marketing & Management 9(4), 420-433 pp.

80

positive attitudes toward shopping online for apparel products and intended to shop

more online for apparel products and had more positive attitudes than those who did

not have the intentions. Internet usage, employment status, and card access had

significantly influenced on students’ attitudes toward online shopping for apparel

products.

Comegys et.al, (2006),140 investigated the online purchase behaviour of

university students, from Finland and USA. The research was carried out to find

whether online shoppers from the two countries approached the consumer buying

decision process differently over time. The results from the study indicated that

online shopping has increased in popularity among both male and female portions of

the target groups in Finland, and more so in the USA. The study found that in both

Finland and USA affordable broadband connections was the main reason that made

people to take online purchase decisions. Thus, the results indicated that it was

worthwhile for e-marketers to keep the customers satisfied. If the e-marketer

satisfied the customer, that customer is a prime candidate for a repurchase. So the e-

marketer who effectively served, satisfied, and delighted the online buyers would

enjoy repeated patronage.

Kim & Jin (2006),141 examined virtual communities of consumption hosted

by companies that sell apparel products. The researcher tried to present a general

overview of the characteristics of virtual communities hosted by apparel retailers.

The results from the study indicated that apparel retailers selling casual merchandise

to the young teen’s market had the strongest representation. Therefore, the study

suggested that the virtual communities should be given more importance by

marketers because it helps them in consumer research and feedback.

Park & Stoel (2006),142 examined the effects of brand familiarity, the

number of pieces of product information presented on a web site, and previous

140Comegys, C., Hannula, M., &Vaisanen, J. (2006).Longitudinal comparison of Finnish and US

online shopping behavior among university students: The five-stage buying decision process. Journal of Targeting, Measurement and Analysis for Marketing, 14(4), 336-356 pp.

141Kim, H.S. & Jin, B. (2006).Exploratory study of virtual communities of apparel retailers .Journal of Fashion marketing and Management.10(1).41-55 pp.

142Park, J. &Stoel, L. (2006).Effect of brand familiarity, experience and information on online apparel purchase. International Journal of Retail & Distribution Management.33 (2), 148-160 pp.

81

online apparel shopping experience on perceived risk and purchase intention. The

results from the study indicated that there is a significant effect of brand familiarity

and previous experience on perceived risk and purchase intention, and no effect of

amount of information on perceived risk and purchase intention. Thus the study

suggested that internet retailers should capitalize on the power of their brand names

to gain advantage.

Cowart & Goldsmith (2007),143 investigated the motivational factors for

online apparel consumption using the Consumer Styles Inventory. Data from a

sample of 357 US college students showed that quality consciousness, brand

consciousness, fashion consciousness, hedonistic shopping, impulsiveness and brand

loyalty were positively correlated with online apparel shopping. Price sensitivity

was negatively correlated with online spending. The findings revealed that

impulsive shoppers spend more for apparel online in a typical month and spend

more time online than other consumers. These findings could lead one to infer that a

substantial number of online apparel purchases are unplanned and precipitous.

Inglessis (2008),144 explored how Hispanic women (living in the United

States) of different levels of acculturation communicated their individual, social and

cultural identities through clothing and appearances. The study demonstrated that,

when it comes to clothing and appearance, Hispanic women have more

commonalities than differences. The values and beliefs are learned early on from

their mothers and maintained through constant interaction with the Hispanic culture

through friends and families. Hispanic cultural values drive theway Hispanic women

communicate, attractiveness, ethnicity and social class. Finally, the study illustrated

the interconnection between the different aspects of the adoption of clothes by

pointing out sensorial experience, fit, and interpersonal influence as the major

drivers of adoption among Hispanic women.

143Cowart, K. O., & Goldsmith, R. E. (2007).The influence of consumer decision-making styles on

online apparel consumption by college students. International Journal of Consumer Studies, 31(6), 639-647 pp.

144Inglessis, M. G. (2008). Communicating through clothing: The meaning of clothing among hispanic women of different levels of acculturation. ProQuest, UMI Dissertations Publishing.

82

Reiley (2008),145 examined the relationship between the desire for a unique

appearance and sources of clothing acquisition- vintage or new clothing. Subjects

were 97 female college students within the age group of 18-25 years, who

purchased clothing from vintage and/or new clothing sources. The survey included

the “desire for unique consumer products” (DUCP) scale developed by Lynn and

Harris (1997a) with eight statements on a 5-point scale. The outcome was that

regular vintage wearers did have a higher desire for unique consumer products

according to the DUCP scale than the new clothing wearers. The regular vintage and

new clothing wearers with high DUCP scores used a greater variety of unique pieces

from different clothing sources and put them together in unexpected ways to create a

unique appearance. Therefore, concluded that those with similar high DUCP scores

created an appearance that was more unique than the wearers with low DUCP

scores.

Zeng (2008),146 investigated Chinese college online apparel shoppers’

decision-making styles and their online apparel shopping behaviours. It explored the

relationships between the decision-making characteristics and the related online

apparel shopping behaviours and consumptions. The results demonstrated that some

of the characteristics of the CSI were related to the frequency of buying apparel

online, and the dollar amount spent online for apparel purchasing. The findings

showed that recreational consciousness, hedonistic consciousness, brand

consciousness, habitual consciousness and brand-loyalty consciousness have

significant correlations with the frequency of online apparel purchases. However,

only brand conscious and habitual conscious, brand-loyalty conscious are

significantly correlated with the amount of money spent online for apparel purchases

by Chinese college students.

145Reiley, K. J. W. (2008). Definitions of uniqueness in terms of individual appearance: Exploring

vintage clothing and new clothing wearers. ProQuest, UMI Dissertations Publishing 146Zeng, Y. (2008). An investigation of decision making style of Chinese college student online

apparel shoppers.Thesis, B.A. Wuhan University Of Science And Engineering, China,, Retrieved from http://etd.lsu.edu/docs/available/etd-11052008 123052/ unrestricted/ Zengthesis.pdf.

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Mandloi (2010),147 ascertained the buying decision-making styles of Indian

shoppers in Indore shopping malls, so as to provide information to marketers

interested in the decision-making profile of Indian consumers and thus enabling

them to build their marketing efforts accordingly. Results showed that the main

influencing factor which influenced and affected the respondents in order to make

buying decision from shopping malls is brand consciousness. Demographic

variables like age and gender also influenced the customer choices and buying

decision-making style of Indian shoppers.

Meenakshi & Arpita (2010),148 examined the Indian youth's need for

uniqueness (NFU) and their attitudes towards luxury brand as an expression

of individuality. It was apparent that while the NFU is not very high amongst the

Indian youth, luxury brands do symbolize status and individuality to them and serve

a value-expressive function.

Noh &Lee (2011),149 analysed the effects of brand difference on

multichannel apparel shopping behaviors in a multichannel environment. The

researcher investigated the effect of brand difference on the path parameters in the

Structural Equation Model developed by Noh in a multichannel shopping context.

The results revealed that the Structural Equation Model developed by Noh needs to

be applied to each brand separately. Therefore, the researchers suggested that

multiple-group causal models need to be applied to a research dealing with several

groups, such as a research regarding cross-national consumer behaviors that are

important to global marketers.

147Mandloi, M. (2010).A study on buying decision making style of Indian shoppers in Indore

shopping malls. 148Meenakshi, H., &Arpita, K. (2010). Need for uniqueness and consumption behaviour for luxury

brands amongst Indian youth. International Journal of Indian Culture and Business Management, 3(5).

149Noh, M., & Lee, E. J. (2011).Effect of brand difference on multichannel apparel shopping behaviors in a multichannel environment. International Journal of Business and Social Science, 2(18), 24-32 pp.

84

Padmanabhan, Parvathi(2012),150 conducted a study that examined how

young Indian professionals make decisions about apparel products considering the

myriad of options that are now available to them in the marketplace. In this study, a

qualitative approach was used to understand the role of brands in the decision-

making process of young, urban Indian consumers. Data collection took place in

Bangalore, a large city in the South of India. Thirty-four males and females between

the ages of 22 and 35 participated in the study. In addition, consumption behaviours

of young consumers in three shopping malls in and around Bangalore were

observed.

ZeenatIsmail, Sarah Masood and Zainab Mehmood Tawab (2012)151,

conducted a study in order to determine the consumer preferences of global brands

instead of local ones. It is also designed to find out the buying behaviour patterns of

young Pakistani consumers. Consumer evaluates products based on information

cues, which are intrinsic and extrinsic. A number of factors affect the consumer

purchase decisions. The results suggest that most important factors that influence a

consumer’s final decision are the price and quality of the product in question. Since

the consumers usually associate the price of the brand with its quality, a brand

priced too low is generally perceived as a low quality product. Similarly, a product

priced too high may not be affordable by many. Other factors that have an impact on

the consumer preferences are: consumer ethnocentrism, country of origin, social

status, price relativity with the competing brands and family and friends. The

research was conducted in Karachi and the samples selected included 200 people of

age 16-24. The data collected for the research was through a questionnaire and was

conducted in two popular shopping malls of the city and two universities since the

target audience was largely the youth. Calculations were then analyzed and

interpreted using a percentage of respondents and through frequency distribution

tables and charts.

150Padmanabhan, Parvathi. (2012), Foreign Apparel Brands and the Young Indian Consumer: An

Exploration of the Role of Brand in the Decision-Making Process. Directed by Dr. Nancy Hodges.165 pp.

151ZeenatIsmail , Sarah Masood and ZainabMehmoodTawab (2012), Factors Affecting Consumer Preference of International Brands over Local Brands. 2nd International Conference on Social Science and Humanity, IPEDR vol.31 (2012) © (2012) IACSIT Press, Singapore.

85

Lawan and Zanna (2013)152, in their study titled ‘Evaluation of Socio-

Cultural Factors Influencing Consumer Buying Behaviour of Clothes’ assessed the

cultural factors influencing consumer buying behaviour of clothes in Borno State,

Nigeria. The study was specifically carried out to examine the cultural, economic as

well as personal factors influencing clothes buying behaviour. Findings revealed a

highly significant influence of cultural factors on consumer buying behaviour. The

study concluded that culture, either acting independently or in conjunction with

economic and personal factors significantly influences buying behaviour of clothes.

It was recommended that marketing managers should take cognizance of the fact

that socio-cultural factors are some of the fundamental determinants of a person’s

want and behaviour and should therefore be considered when designing clothes for

their markets.

RESEARCH GAP AND DIMENSIONS OF THE PRESENT STUDY

The review based on available literatures at international and national level

has provided an incentive to think on various levels about the present study. It has

shed light on the problem focussed and helped to determine the scope of the study.

The studies on psychographic / values discussed above have mostly explored

the validity and the applicability of the values scales. A couple of studies have

recommended the psychographic approach to market segmentation and have

profiled the segments based on life –style or values. Very Few studies have

attempted to study the relationship between values and consumer behaviour. Only

one study has been conducted in India using the LOV to examine the frequent

clothing purchase behavior of undergraduate urban college-goers in Kolkata, India

(Roy S., Goswami P., 2007). However, the study assessed the value-psychographic

traits-clothing (VPC) purchase behavior hierarchy and did not employ the consumer

Styles Inventory.

152Lawan A. Lawan, Ramat Zanna (2013), Evaluation of Socio-Cultural Factors Influencing

Consumer Buying Behaviour of Clothes in Borno State, Nigeria; International Journal of Basic and Applied Science, Vol 01, No. 03, Jan 2013, pp. 519-529 pp.

86

The review of literature on the Consumer Styles Inventory Many revealed

that many studies have been conducted using the Sproles and Kendall Consumer

Styles inventory, but most of them were done abroad. Further, most of the studies

were undertaken to study the applicability and the generalizability of the CSI in

different countries. Some studies used the CSI to establish gender differences in

consumer decision-making styles. Two distinct studies in India investigated the

decision-making styles of youth, one on the South Indian college-going consumers

in Coimbatore by Canabel, (2002) and Ghodeswar (2007)investigated the decision-

making style among students of a Business School in Mumbai, India. Neither of

these studies used the LOV to explore the influence of values.

The young adult segment has gained considerable importance in the area of

consumer behaviour research. Many studies have been conducted in India on the

youth to understand their diversity and profile youth behaviour based on what

interests’ them and grabs their attention. Studies have attempted to understand their

interests and what influences them, their fashion involvement and their behaviour of

in shopping malls. No study has been conducted to study the values perceived by

them and its influence on their buying behaviour.

The studies on apparels/clothing behaviour predominantly investigated the

clothing patterns among young people, their attitudes towards imported and

domestic apparels, apparel shopping orientation among consumers, how consumers

evaluated clothing quality, factors responsible for the change in clothing patterns,

shopping online for apparel products, and the evaluation of socio-cultural factors

influencing consumer buying behaviour of clothes.

The literatures on psychographics indicate the importance and need for

psychographic segmentation, the studies on CSI indicate its applicability and

generalizability and usefulness in understanding consumer shopping styles, the

literature on youth revealed the need for more specific and in-depth studies to

understand the most promising target group of consumers in India, the young adults,

due to its demographic dividend and the literature on clothing behaviour point that

clothing is an important channel for self expression among the young adults.

87

Summing up, no study has been undertaken so far in Bangalore, India, to

profile the young adults in the age group of 18 – 25 years based on their shopping

styles and explore the influence of personal values on their shopping styles for

apparels.

RESEARCH DESIGN

This study throws insight upon the influence of values on the buying

behaviour of young adults towards apparels. Information regarding the personal

values that are important to the target market would be valuable in the development

of advertising campaigns and other marketing strategies. To date, however, few

studies have been available for bringing to light how consumer choices are

influenced by personal values. It is expected that such a psychographic analysis will

give a more fine tuned and accurate results on young adults buying behaviour than a

general study on youth.

SAMPLE SIZE, SAMPLING TECHNIQUE AND SAMPLE SELECTION

The respondents for the study consist of young adults as defined by the UN

and as defined by India Youth Policy 2010, in the age group of 18-25 years.

Sample size plays an important role in the estimation and interpretation of

results of studies adopting Structural Equation Modelling (SEM). According to

Fidell153 The minimum sample required for adopting any statistical tool should be

greater than or equal to 8k+50, where k = the number of items involved in the

questionnaire. The questionnaire administered by the researcher in this study

included 10 items on ‘Values’ and 24 statements on ‘Shopping Styles’ adding up to

a total of 34 items. Therefore, solving for n, n = 8 (34) + 50 = 322. The total sample

for the present study was 1478 respondents who were young adults in the age group

18-25 years residing in Bangalore.

Non-probability sampling methods such as judgemental and convenient

sampling methods were adopted to select the respondents for the study. Judgmental

153Tabachnick, Linda S. Fidell. (2003). Using Multivariate Statistics (6th Edition). Amazon.com.

88

sampling method was adopted to identify to whom the questionnaire should be

administered. One criteria adopted in the study to select respondents was that they

should be in the age group of 18 – 25 years. Convenient sampling was adopted to

administer the questionnaire to young adult visitors to malls in Bangalore. The

selection of malls was based on the presence of branded apparel retails outlets in

these malls and their proximity to colleges. Many college students and working

people in the age group of 18-25 frequently visit these malls for purchase of

apparels.

The following four popular malls located in prominent locations representing

the four zones in Bangalore city were identified as the data collection points:

TABLE 05

DATA COLLECTION LOCATIONS AND NUMBER OF RESPONDENTS

S.NO MALL LOCATION / AREA No. of Respondents

1 Forum Mall Koramangala, South

Bangalore

438

2 Esteem Mall Hebbal, North Bangalore 321

3 Orion Mall Rajaji Nagar, West

Bangalore

345

4 Phoenix Market City Whitefield, East

Bangalore

374

Total 1478

The study mainly focused on the college-going student population because

the Sproles & Kendall Consumer Style Inventory was meant to be used for the

student population. The original study by Sproles & Kendall154 administered the

Consumer Style Inventory to 482 youth in the United States. The subjects were all

154Sproles, G.B., Kendall, E.L., (1986), “A methodology for profiling consumer decision making

styles”, The Journal of Consumer Affairs, 20 (2): 67-79 pp.

89

high school students in home economics classes. Halfstrom, et.al,155 identified

decision-making styles of young consumers in Korea and administered the CSI to

310 college students in Korea. Lysonski et.al,156 conducted the study with

undergraduate business students in four countries to investigate the applicability of

the Consumer Styles Inventory. Fan &Xiao,157 administered the Consumer Styles

Inventory to see if the consumer decision-making styles could be generalised to

Chinese college students. Canabal (2002),158 investigated the decision -making

styles of young South Indian consumers with data collected from two institutions of

higher education in the city of Coimbatore, India. Ghodeswar,159 investigated the

decision-making style among students of a Business School in India.

PILOT STUDY AND RELIABILITY TEST

A pilot study was conducted on 30 respondents in October 2012. Reliability

test using Cronbach’s coefficient alpha was used to test the reliability of the scales

and assess the internal consistency of individual constructs, subscales and overall

scale. The rule of thumb is that the coefficient alpha must be above 0.7 for the scale

to be reliable.160 The reliability for the present study was significant (Cronbach

Alpha .737). The main study was conducted from November 2012.

155Halfstrom, J. L., Chae, J. S., and Chung, Y. S. (1992). “Consumer Decision Making Styles:

Comparison Between United States and Korean Young Consumers.” Journal of Consumer Affairs, 26(1), 1-11 pp.

156Lysonski, S., Durvasula, S. and Zotos, Y. (1996), “Consumer Decision-Making Styles: A

Multicountry investigation”, European Journal of Marketing, Vol. 30, No. 12, pp. 10-21. 157Jessie X. Fan, Jing J. Xiao (1998), Consumer Decision-Making Styles of Young-Adult Chinese

consumers. Journal of Consumer Affairs. Volume 32, Issue 2, pages 275–294, Winter 1998. 158Canabal , M. E. (2002). Decision making styles of young south Indian consumers: an exploratory

study. College Student Journal, 36(1). 159Ghodeswar, B. M. (2007). Consumer decision-making styles among Indian students. Alliance

Journal of Business Research, 3(spring), 36-48 pp. 160Nunnally, J. C. (1978). Psychometric Theory. Second edition. New York, NY: McGraw-Hill. And, Hair Jr, JF, Anderson, RE, Tatham, RL and Black WC (1998) Multivariate data analysis

fourth edition. Prentice-Hall: London.

90

DATA COLLECTION

Primary data for the study has been collected using a questionnaire

developed by the researcher incorporating two validated tools, one to measure the

independent variable ‘values’ using the LOV - List of Values – Kahle (1983), and

the second to measure the dependent variable ‘Shopping Styles’- using Consumer

Styles Inventory: CSI- (Sproles and Kendall 1986; Sproles and Sproles 1990).

The questionnaire has three sections:

o The first section investigates the demographic profile of the young

adults,

o The second section consists of the modified version of Kahle’s LOV

[List of Values, 1983]

o The third section consists of the adapted version of Sproles & Kendall’s

CSI -Consumer Style Inventory, 1986.

Data collection was spread over a period of five months, from November

2012 to March 2013. Data was collected with the help of research assistants working

in the same department and institution of the researcher. The questionnaire was

given to respondents after enquiring their age and their willingness to participate in

the survey. Respondents were asked to state whether they were studying in

Bangalore in Under Graduate courses, Post Graduate courses or with other

qualifications. The education level of the respondents was also used as parameter to

obtain the demographic profile of the respondents and as a variable for testing

hypothesis.

The questionnaire was administered to a sample of 1600 male and female

young adults falling in the age group of 18-25 years who visited the four malls. Of

the 1600 questionnaires distributed, 1478 questionnaires were deemed valid for data

analysis yielding a response rate of 92%. Such a response rate was considered

sufficient for statistical reliability and generalisability,161 and more satisfactory when

compared with previous research works on consumer decision-making styles. The

161Tabachnick, Linda S. Fidell. (2001). Using Multivariate Statistics (6th Edition). Amazon.com

91

purpose for selecting such a large sample was to reduce the effect of non-sampling

errors.

The sample for the study consists of 54.4 per cent male and 45.6 per cent

female respondents. The respondents were from different regions with diverse

backgrounds ranging from urban to rural which also reflect their differences in

socio-economic status.

Research papers, journals and text books, internet based research libraries

Ebsco Host, SSRN, Jstor were also used extensively for the purpose of this study.

This study is also backed with extensive review of previous literatures under each

variable category of the study, namely Values, Young Adults, and Shopping Style.

PERIOD OF THE STUDY

Data collection for the study commenced in November 2012 and extended

till March 2013. Data analysis and interpretation was done in April & May 2013.

FRAME WORK OF ANALYSIS

The design of analysis of the data to establish the findings to the research

objectives is presented in a sequential manner as described below:

a) General Descriptive analysis based on demographic variables such

gender, educational level and regional back ground of respondents.

This is presented in tables indicating frequencies and percentages and

depicted in bar/pie diagrams. Under descriptive analysis, no attempt

was made to analyze the age of the respondents as it has been

reported that differences in attitudes and behaviour of adolescents

and youth under reference for this study is not due as much to age as

to education cohort.162 It was therefore assumed that no significant

difference would result from analysing differences in the age of the

respondents. 162Haytko, D. L. & Baker, J. (2004). It’s all at the mall: exploring adolescent girl’s experiences.

Journal of Retailing, 80(1), 67-83 pp.

92

b) Descriptive analysis for List of Values, Value dimensions and Shopping

Styles presented in tables indicating Mean and Standard Deviations in

descending order.

c) Reliability tests for List of Values and Shopping Styles indicating

Cronbach alpha.

d) Correlation analysis for testing relationship of overall values to shopping

styles, individual values to shopping styles, value dimensions to

shopping styles. Inter-correlations among values and among shopping

styles are also studied.

e) Structural Equation Modelling, Confirmatory Factor Analysis (CFA),

Goodness of Fit Measures (GFM), Multiple Regressions and Path

analysis for confirming the consumer shopping styles with the original

CSI constructs and testing the ‘Value Shopping-style Model’.

f) Testing of Hypotheses using ANOVA and t-test to study differences in

shopping styles, differences in value orientations and level of influence

of values, based on demographic segmentation variables such as gender,

education level, regional background of respondents, etc.

Description of Statistical Tools Employed

The data was processed and tabulated using Microsoft Excel 2007 and SPSS

version 19. Data analysis was performed by using software packages - IBM SPSS

(Statistical package for Social Sciences) version 19 and AMOS version 16.0.

Statistical Package for the Social Sciences (SPSS)

SPSS program is one of the most widely used tool for analysis within the

social sciences research and has the advantage of wide range of supporting

documentation and text books available to guide the researcher. First, a coding sheet

was prepared for all the questions in the questionnaire and the data was fed in SPSS

data editor. SPSS version 19 was used for all the non-specialist statistical analysis

such as general descriptive analysis, reliability tests, correlation analysis, T-test and

93

ANOVA. The SPSS provides features for descriptive and inferential statistical

analysis.

Analysis of Moment Structures (AMOS)

Analysis of Moment Structures (AMOS) version 16.0, a leading SEM

software package, was used in this study. AMOS is a user friendly software and

widely used within the social sciences research. It is one of the most common

covariance-based Structural Equation Modelling (SEM) techniques. The diagrams in

AMOS are much clearer compared to other software packages. AMOS also has wide

range of supporting documents to guide the researcher. The study used AMOS to

test the confirmation of original factors, model testing and path analysis.

Descriptive statistics

Descriptive statistics was used to compute mean, standard deviation and

percentages. Summary of the data was done using measures of central tendency and

measures of variation. Measures of central tendency included mean and measures of

variation included standard deviation. Mean and standard deviation provided a basic

descriptive feel of the distribution of data (response) for different variables in the

study.

Karl Pearson’s Coefficient of Correlation

Correlation is a statistical analysis that defines the variation in one variable by

the variation in another, without establishing a cause-and-effect relationship.

The coefficient of correlation is a measure of the strength of the relationship

between the variables; that is, how well changes in one variable can be predicted by

changes in another variable.

When using SPSS for Pearson correlation coefficient, the descriptive output

tells us about each set of data (i.e., the mean, standard deviation, and number of

values for each variable), and the correlation matrix in the output tells us how the

data are related. To ascertain if the correlation is statistically significant, the row

labeledsig should be referred. The value in this row is the probability of the null

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hypothesis being true. For a two-tailed correlation test, the probability of the null

hypothesis (i.e., that there is no relationship between the variables) being true, sig

value should be less than the preset level of significance (typically 0.01 or 0.05). In

such a case, we can reject the null hypothesis and conclude that the relationship

between the variables is statistically significant.

In addition to using the sig value to determine whether to reject or retain the

null hypothesis, there is also another visual indication of statistical significance on

the output. By default, SPSS "flags" (marks) significant relationships with asterisks.

If the sig value is below the preset criterion of significance, SPSS will put asterisks

next the correlation value. Pearson’s correlation coefficient was used to study the

relationship between personal values and shopping styles of young adults.

Structural Equation Modelling (SEM)

Structural Equation Modelling (SEM) is a multivariate statistical

methodology, which takes a confirmatory approach to the analysis of a structural

theory. Structural Equation Modelling is confirmatory process, since it commences

with the specification of a model. It is a multivariate analysis method based on

fitting and testing multiple regression equation as specified by the model. SEM is a

set of techniques which allows examination of relationships between one or multiple

independent variable and one or more dependent variables.163 Though there are

many ways to describe SEM, it is most commonly thought of as a hybrid between

some form of Analysis of Variance (ANOVA)/Regression and some form of Factor

Analysis. In general, it can be remarked that SEM allows one to perform some type

of multilevel Regression/ ANOVA on factors. Structural Equation Modelling

combines two approaches: the predictive approach of econometrics, coupled with

the psychometric approach of inferring latent variables from multiple observed

variables.164 It essentially seeks to answer research questions by combining multiple

regression analysis of factors with exploratory factor analysis. A researcher proposes

a hypothesized series of relationships between the variables under investigation (the 163Tabachnick, Linda S. Fidell. (2001). Using Multivariate Statistics (6th Edition). Amazon.com 164 Chin, W. W. (1998b). The partial least squares approach to structural equation modelling. In G. A.

Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Mahwah, NJ: Lawrence Erlbaum Associates, Inc

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model) and Structural Equation Modelling enables the reasonableness of t

relationships implied by the model to be assessed. In the present study structural

equation modelling was used to test the Value – Shopping Style Model

(Measurement).

Confirmatory Factor Analysis (CFA)

Confirmatory Factor Analysis (CFA) which is a part of the Structural

Equation Modelling (SEM) techniques can be used to estimate a measurement

model that specifies the relationship between observed indicators and their

underlying latent constructs. The measurement model specifies how latent constructs

are measured by the observed variables. CFA is often used to confirm a factor

structure known beforehand as is the case with the constructs in the study.

In statistics, CFA is a special form of factor analysis. It is used to test

whether measures of a construct are consistent with the researcher’s understanding

of the nature of that construct (factor). In contrast to exploratory factor analysis,

where all loadings are free to vary, CFA allows for the explicit constraint of certain

loadings to be zero. CFA assesses the fit of the model. Model fit measures could be

then obtained to assess how well the proposed model captured the covariance

between all the items on the test. If the fit is poor, it may be due to some items

measuring multiple factors. It might also be that some items within a factor are more

related to each other than others.

Goodness of Fit Measures (GFM)

“Goodness of fit measures” was used to test the appropriateness of the

structural model using the Amos 16.0 software. The overall fit of a model in

Structural Equation Modelling can be assessed using a number of fit indices. There

is a broad consensus that no single measure of overall fit should be relied on

exclusively and a variety of different indices should be consulted.165 There are

several indicators of Goodness-of-fit and most structural equation modelling

scholars recommend evaluating the models by observing more than one of these 165Tanaka, 1993. Tanaka, J.S. (1993). Multifaceted conceptions of fit in structural equation models. In

K.A. Bollen, & J.S. Long (eds.), Testing structural equation models. Newbury Park, CA: Sage

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indicators.166 Dozens of statistics, besides the value of the discrepancy function at its

minimum, have been proposed as measures of the merit of a mode. Choice of

Goodness-of-fit indexes should be based on careful consideration of critical factors

like sample size, estimation procedure, model complexity and/or violation of the

underlying assumptions of multivariate normality and variable independence.

Validity Measures

The Confirmatory Factor analysis is executed to test the validity of the

instruments through content validity, convergent validity, discriminant validity and

criterion related validity. Content validity refers to the degree which an instrument

covers the meaning of the concepts included in a particular research. For this study,

the content validity of the proposed instrument is adequate enough because the

instrument has been carefully constructed, validated and refined, supported by an

extensive literature review.

Construct validity: Construct validity is the extent to which a set of

measured variables actually represent the theoretical latent construct that they are

designed to measure.167To assess the construct validity of the scale, exploratory and

confirmatory factor analytic procedures were applied.

Convergent validity: Convergent validity is the extent to which indicators

of a specific construct ‘converge’ or share a high proportion of variance in common.

Convergent validity identifies the proportion of variance for each factor. To assess

this, standardized factor loadings in the measurement model were examined,

composite or construct reliability (CR) and average variance extracted (AVE) was

computed.

Construct Reliability (CR) = {(sum of standardized loadings)2} / {(sum of

standardized loadings)2 + (sum of indicator measurement errors)}

166Hu &Bentler (1999).Cutoff criteria for fit indexes in covariance structure analysis: Coventional

criteria versus new alternatives, Structural Equation Modeling, 6(1), 1-55 pp. 167Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E. &Tatham, R. L. (2005).Multivariate data

analysis (6th Ed.). Upper Saddle River, NJ: Prentice Hall.

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Multiple Regression and Path Analysis

Regression analysis involves identifying the relationship between a

dependent variable and one or more independent variables. A model of the

relationship is hypothesized, and estimates of the parameter values are used to

develop an estimated regression equation. Various tests are then employed to

determine if the model is satisfactory. If the model is deemed satisfactory, the

estimated regression equation can be used to predict the value of the dependent

variable, given the values for the independent variables.

Path analysis, an extension of multiple regression, lets us look at more than

one dependent variable at a time and allows for variables to be dependent with

respect to some variables and independent with respect to others. Structural equation

modelling extends path analysis by looking at latent variables. A multiple regression

model is drawn as a path analysis.

In addition to being thought of as a form of multiple regression focusing on

causality, path analysis can be viewed as a special case of structural equation

modelling (SEM) – one in which only single indicators are employed for each of the

variables in the causal model. That is, path analysis is SEM with a structural model,

but no measurement model. Other terms used to refer to path analysis include causal

modelling, analysis of covariance structures, and latent variable models.

t Statistic for Equality of Variances

The t-test is used for testing differences between two means. In order to use a

t-test, the same variable must be measured in different groups, at different times, or

in comparison to a known population mean. Comparing a sample mean to a known

population is an unusual test that appears in statistics books as a transitional step in

learning about the t-test. The more common applications of the t-test are testing the

difference between independent groups or testing the difference between dependent

groups.

The independent t-test, also called the two sample t-test or student's t-test, is

an inferential statistical test that determines whether there is a statistically significant

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difference between the means in two unrelated groups. A t-test for independent

groups is useful when the researcher's goal is to compare the difference between

means of two groups on the same variable. "Independent groups" means that the

groups have different people in them and that the people in the different groups have

not been matched or paired in any way. A t-test for related samples or a t-test for

dependent means is the appropriate test when the same people have been measured

or tested under two different conditions or when people are put into pairs by

matching them on some other variable and then placing each member of the pair into

one of two groups.

The null hypothesis for the independent t-test is that the population means

from the two unrelated groups are equal: H0: 1 = 2

In most cases, we are looking to see if we can show that we can reject the

null hypothesis and accept the alternative hypothesis, which is that the population

means are not equal: HA: 1 2

This requires the setting of a significance level (alpha) that allows us to

either reject or accept the alternative hypothesis. Most commonly, this value is set at

0.05.

"Levene's Test for Equality of Variances" is a test of the homogeneity of

variance assumption. The output in SPSS begins with the means and standard

deviations for the two variables which is key information that will need to be

included in any related research report. The "Mean Difference" statistic indicates the

magnitude of the difference between means. When combined with the confidence

interval for the difference, this information can make a valuable contribution to

explaining the importance of the results. When the value for F is large and the P-

value is less than 0.05, it indicates that the variances are heterogeneous which

violates a key assumption of the t-test.

The first format for "Equal" variances is the standard t-test taught in

introductory statistics. This is the test result that should be reported in a research

report under most circumstances. The second format reports a t-test for "Unequal"

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variances. This is an alternative way of computing the t-test that accounts for

heterogeneous variances and provides an accurate result even when the homogeneity

assumption has been violated (as indicated by the Levene test). It is rare that one

needs to consider using the "Unequal" variances format because, under most

circumstances, even when the homogeneity assumption is violated, the results are

practically indistinguishable. The output for both formats shows the degrees of

freedom (df) and probability (2-tailed significance). As in all statistical tests, the

basic criterion for statistical significance is a "2-tailed significance" less than 0.05.

Levene's test is used to assess the homogeneity of variance between sets of

scores. It tests the null hypothesis that "there is no significant difference between the

two population variances". A basic assumption underlying the use of parametric

tests such as the t-test or Analysis of Variance is that the variance (degree of spread)

for scores for each variable or condition must be roughly equal. Levene's and some

other tests are used to examine if this is the case.

If the Levene's test produces a non significant result (i.e. p is greater than

0.05), then one should use the "Equal variances are assumed" output. However, if

the Levene's test produces a significant result (i.e. p is less than 0.05) then one

should use the lower line that is labelled "Equal variances are not assumed". In this

case, the result is based on a correction for the lack of homogeneity of variance.

The Levene's test allows researchers to check for equality of variance. If the

spread of the data in the two different groups is different (unequal variances) then,

the Levene's test will reveal this difference in the output. SPSS will generate output

for two different t-tests: equal variances assumed and equal variances NOT

assumed. If the Levene's test is SIGNIFICANT, it means the variances are NOT

equal, so the results of the equal variances NOT assumed should be considered.

If the Levene's test is NOT significant, then the results of the equal variances

assumed t-test should be considered.

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ANOVA

The ANOVA is a statistical technique which compares different sources of

variance within a data set. The purpose of the comparison is to determine if

significant differences exist between two or more groups. The ANOVA test is used

to determine the impact independent variables have on the dependent variable in a

regression analysis.

The one-way analysis of variance (ANOVA) is used to determine whether

there are any significant differences between the means of two or more independent

(unrelated) groups.

Like the t-test, the ANOVA calculates the ratio of the actual difference to the

difference expected due to chance alone. This ratio is called the F ratio and it can

be compared to an F distribution, in the same manner as a t ratio is compared to a t

distribution. For an F ratio, the actual difference is the variance between groups,

and the expected difference is the variance within groups.

In the ANOVA setting, the observed variance in a particular variable is

partitioned into components attributable to different sources of variation. In its

simplest form, ANOVA provides a statistical test of whether or not the means of

several groups are equal, and therefore generalizes t-test to more than two groups.

Doing multiple two-sample t-tests would result in an increased chance of

committing a type I error. For this reason, ANOVAs are useful in comparing

(testing) three or more means (groups or variables) for statistical significance.

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CHAPTER IV

PERSONAL VALUES AND SHOPPING STYLES

In this study a ‘Value Shopping Style Model’ is proposed and tested. The

model has been developed on a three-fold phase involving an extensive review of

theory relating to consumer behaviour, review of past studies in the related area that

used value scales and consumer styles inventory, and personal interaction with

apparel manufacturers and marketers.

Theoretical Background of Consumer Behaviour

Consumer behaviour is “the study of individuals, groups, or organizations

and the processes they use to select, secure, use, and dispose of products, services,

experiences, or ideas to satisfy needs and the impacts that these processes have on

the consumer and society.”168

Insight into customer buying behaviour or consumer decision-making

process leads to a better development of an effective marketing strategy.

Understanding buying-related decision-making behaviour of consumers is important

for companies’ strategic marketing activities. Effective communication with

different consumer segments can be made by understanding the psychological

processes that affect consumer behaviour.

A marketer can rarely satisfy everyone in a market. Not everyone likes the

same toothpaste, beverage, automobile, TV channel, mobile handset and perfume.

Therefore, marketers identify and profile distinct groups of buyers who might prefer

or require different products and marketing mixes. Market segmentation is an

essential part of the marketing process. It allows firms to allocate their market into

groups that have the same characteristics which are relevant for decision making in

the marketing strategy.

168Hawkins and Mothersbaugh.(2013). Consumer Behavior. Chapter 1

102

The different types of market segmentation are demographic segmentation,

where marketers divide the market into smaller segments based on gender, age,

marital status, income, family size, occupation, education, religion, race, and

nationality. Geographic segmentation refers to the segmentation of the market

according to geographic criteria such as Nations, States, Regions, Countries, Cities

or Zip codes. Psychographic segmentation is where consumers are divided

according to their lifestyle, attitudes, interests, personality, values and social class.

Behavioural Segmentation is where the segmentation is based on benefits that are

required, purchase occasion, purchase behaviour, usage and perception and beliefs

of consumers.

For many years, demographic segmentation is the basis in which marketers

used to target consumers. Though demographic still continues to be the most

preferred and easier approach to segmentation, researchers have established that

they do not provide a complete understanding of the individual consumer. The basic

difference between the two types is that while demographics segment consumers

based on their similarities, psychographics segment consumers based on their

individual differences. Demographics help to make an initial step into market sizing

and segmentation. Whereas, psychographics helps to understand the psychology of

how a person makes decisions, and their own self-image.

The consumers in the same demographic segment possess divergent

psychographic makeup. Thus, psychographic segmentation allows the marketer to

look at consumers as real people or entities. The demographic and psychographic

approaches are highly complementary and work best together. People hailing from

the same sub-culture, social class and even occupation follow quite different

lifestyles.

Psychographic segmentation offers many benefits to marketers. Besides the

most obvious benefit of increased sales; it also increases the brand value of the

company in the eyes of the customer, provides greater usefulness of the product for

the customer and better inputs for the design of new products that the customer will

like. It also results in lesser amount of money spent on marketing as it is approaches

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a more specific group. Marketers find it easier to target a specific type of customer

base and derive effective and efficient marketing strategies. A greater degree of

customer satisfaction and customer loyalty leads to higher amount of customer

retention. Psychographics also enables strategic positioning of new products,

repositioning of existing products, develop new product concepts and create new

product opportunities in specific fields.

Psychographics has proven to be a very useful tool for organisations in their

marketing research. It identifies target markets that could not be isolated using only

demographic variables. Psychographics are designed to measure the consumer's

pre-disposition to buy a product and the factors that influence and stimulate buying

behaviour. Researchers have often paid their attention towards psychographics

because of the limitations encountered in demographics. An advantage of

psychographics is that it describes segments in terms that are directly relevant to

advertisement campaign and market planning decisions of organisations.

Psychographic segmentation suffers from the drawbacks of any priori169

segmentation. The most serious problem is that consumers are constantly changing,

so the segmentation framework needs to be changed in order to keep up the pace.

People’s attitudes and circumstances change quickly and it is difficult for fixed

segmentation frameworks to reflect this accurately. On the other hand, behavioural

based schemes can capture the results of these changes as they affect buying

patterns, allowing the marketer to respond.

There are reliability problems in psychographic segmentation. Firstly, there

are no standardized methods to evaluate the stability of the results of psychographic

techniques and uncertainty in this area weakens predictive power. Therefore, it will

create doubts regarding the reliability of the targeted segment and market. The main

problem is that psychographics attempt to measure intangible and diffuse concepts.

Values and attitudes are not easy to measure as every single person has a different

169Meaning: -relating to or denoting reasoning or knowledge which proceeds from theoretical deduction rather than from observation or experience:http://www.oxforddictionaries.com

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personality and consequently have different opinions and interests.170 However,

behavioural segmentation is not practical in every market and priori methods such as

psychographic segmentation become the only practical approach.

VALUE SCALES

Values scales are psychological inventories used to determine the values that

people endorse in their lives. They facilitate the understanding of both work and

general values that individuals uphold. Most scales have been normalized and can

therefore be used cross-culturally for vocational, marketing, and counselling

purposes, yielding unbiased results. Values scales are used by psychologists,

political, economists, and others interested in defining values, determining what

people value, and evaluating the ultimate function or purpose of values. While there

are a large number of different instruments developed and used over time, there are

few most commonly used social value classification systems in marketing research.

The most widely used value scales are:

RVS -Rokeach Value Survey (1973)

VALS -Values and Lifestyles (1978)

LOV - List of Values – Kahle (1983)

SVI - Schwartz's Value Inventory (1992)

A brief description of these prominent and widely used values scales used in

consumer behaviour studies are presented here.

RVS -Rokeach Value Survey (1973)171

Milton Rokeach, a prominent social psychologist, created the Rokeach Value

Survey (RVS), which has been in use for more than 30 years. The instrument

contains two sets of values each representing 18 individual items - Terminal

Values refer to desirable end-states of existence. These are the goals that a person

would like to achieve during his or her lifetime. These values vary among different 170Mary Anne Winslow. (2008). Market segmentation - Psychographic method; Article Source:http://EzineArticles.com. 16 Rokeach, M. (1973).The nature of human values. New York: The Free Press

105

groups of people in different cultures. Instrumental Values refer to preferable modes

of behaviour. These are the means of achieving the terminal values.

The value survey asks subjects to rank the values in order of importance to

them. The actual directions are as follows: “Rank each value in its order of

importance to you. Study the list and think of how much each value may act as a

guiding principle in your life. The Rokeach Value Survey has been extensively used

in empirical research work by psychologists, sociologists and marketers.

Rokeach Value List consists of:

Terminal values: True Friendship, Mature Love, Self-Respect, Happiness,

Inner Harmony, Equality, Freedom, Pleasure, Social Recognition, Wisdom,

Salvation, Family Security, National Security, A Sense of Accomplishment, A

World of Beauty, A World at Peace, A Comfortable Life, An Exciting Life.

Instrumental values: Cheerfulness, Ambition, Love, Cleanliness, Self-

Control, Capability, Courage, Politeness, Honesty, Imagination, Independence,

Intellect, Broad-Mindedness, Logic, Obedience, Helpfulness, Responsibility,

Forgiveness.

VALS -Values and Lifestyles172

VALS (“Values, Attitudes and Lifestyles”) is a proprietary research

methodology used for psychographic market segmentation. VALS was developed in

1978 by social scientist and consumer futurist Arnold Mitchell and his colleagues at

SRI International. It was immediately embraced by advertising agencies, and is

currently offered as a product of SRI's consulting services division. VALS draws

heavily on the work of Harvard sociologist David Riesman and psychologist

Abraham Maslow. Both public television and radio of United States track customer

loyalty using the VALS Psychographic segmentation system developed by SRI

Consulting (Susan Myrland). The basic tenet of VALS is that people express their

personalities through their behaviours. VALS specifically defines consumer

172http://www.strategicbusinessinsights.com/vals/

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segments on the basis of those personality traits that affect behaviour in the

marketplace. VALS uses psychology to analyze the dynamics underlying consumer

preferences and choices.

However, it should be noted that VALS is a proprietary tool and use of

VALS is restricted to permissions and applicable only within The US.

The VALS segments are as follows:

1. Innovators – Sophisticated, high self esteem, upscale; and image is important

to them.

2. Thinkers – Conservative, practical, income allows many choices; and these

people look for value.

3. Achievers – Goal oriented lifestyle; image is very important to them.

4. Experiencers – Like “cool stuff,” like excitement and variety, and they spend

a high proportion of income on fashion.

5. Believers – Conservative; they like familiar and established brands.

6. Strivers – Trendy and fun loving, money defines success; they are concerned

about the opinion of others.

7. Makers – Practical people, do it yourself, unimpressed by material

possessions; they prefer value to luxury.

8. Survivors – Few resources, buy at a discount, very modest market; they have

little motivation to buy.

Schwartz's Value Inventory (SVI)173

Shalom Schwartz (1992, 1994) used his 'Schwartz Value Inventory' (SVI)

with a wide survey of over 60,000 people to identify common values that acted as

‘guiding principles for one’s life’. Schwartz identified and validated 10 value

domains or distinct value groups with a total of 56 or 57 values included in them.

Values are rated by participants of the survey according to the importance of values

for them. The domains represent either individualistic or collective values, or a

173 Schwartz, S. H. (1992). Universals in the content and structure of values: Theory and empirical

tests in 20 countries. In M. Zanna (Ed.).Advances in experimental social psychology (Vol. 25) (pp. 1-65). New York: Academic Press.

107

combination of them, and are viewed in a framework of four dimensions - openness

to change, self-enhancement, conservation and self-transcendence.

Schwartz Value Inventory assesses for the following values:

Achievement: Personal success through the demonstration of competence in

accordance with society's standards, e.g., ambition.

Benevolence: Preservation and enhancement of the welfare of others in one's

immediate social circle, e.g., forgiveness.

Conformity: Restraint of actions that violate social norms or expectations, e.g.,

politeness.

Hedonism: Personal gratification and pleasure, e.g., enjoyment of food, sex, and

leisure.

Power: Social status, prestige, dominance, and control over others, e.g., wealth.

Security: Safety, harmony, and stability of society, e.g., law and order.

Self-direction: Independent thought and action, e.g., freedom.

Stimulation: Excitement, novelty, and challenge in life, e.g., variety.

Tradition: Respect for and acceptance of one's cultural or religious customs, e.g.,

religious devotion.

Universalism: Understanding, appreciating, and protecting all people and nature,

e.g., social justice, equality, environmentalism.

LOV - List of Values – Kahle (1983)174

The list of values (LOV) is a widely used scale for the measurement of values in

a variety of consumer behaviour contexts. Kahle has suggested that the instrument is

a widely accepted measure for cross-cultural comparison of values. Developed at the

174William O. Bearden, Richard G. Netemeyer. (1999). Handbook of Marketing Scales.Multi-Item

Measures for Marketing and Consumer Behavior Research

108

University of Michigan Survey Research Centre, the LOV is based on the theoretical

contributions Abraham Maslow, Milton Rokeach and Feather.175The LOV items

were derived by culling the values from a much larger pool of values to the nine

LOV items. Initiated by the work of Veroffet al., it was further developed by Lynn

Kahle to address the limitations of the Rokeach Value Survey (RVS) and provide a

more parsimonious measurement of personal values. Kahle first used the LOV scale

in America with 2264 adult respondents. Subsequent research has confirmed the

reliability and validity of the LOV and applied it to many specific consumer

behaviours, including opinion leadership, gift giving, and conformity in dress,

advertising preferences and sports participation.

The List of Values (LOV) typology draws a distinction between external and

internal values, and it notes the importance of interpersonal relations in value

fulfillment, as well as personal factors (i.e., self-respect, self-fulfillment) and a

personal factors (i.e., fun, security, excitement) in value fulfillment. In essence, the

LOV measures those values that are central to people in living their lives,

particularly the values of life’s major roles (i.e., marriage, parenting, work, leisure,

and daily consumptions). The LOV is most closely tied to social adaptation and

many studies suggest that the LOV is related to and/or predictive of consumer

behaviour and related activities.176

The LOV is composed of nine values that can be scored in a number of

ways. Each value can be evaluated on 9- or 10-point scales (very unimportant to

very important), or the values can be rank ordered from most to least important.

Also, some combination of the two methods can be used where each value is rated

on 9- or 10-point scales and then subjects are asked to circle the one or two values

that are most important to them in living their daily lives. The original List of

Values: LOV177 developed by Kahle (1983) consists of the following values:

175Rokeach, Milton J. (1973). The Nature of Human Values, New York: Free Press. Maslow,

Abraham H. (1954), Motivation and Personality, New York: Harper. Feather, Norman T. (1975), Values in Education and Society, New York: Free Press.

176Homer, Pamela and Lynn R. Kahle (1988).A structural equation analysis of the value-attitude-behavior hierarchy.Journal of Personality and Social Psychology, 54, 638–46.

177Kahle, Lynn R. ed. (1983).Social Values and Social Change: Adaptation to Life in America. New York, NY: Praeger Publishers.

109

Table 06

List of Values: LOV (Original)

Kahle 1983

The following are a list of ‘values’ that some people look for or want out of

life. Please study the list carefully and then; Rate each value on how important it is

in your daily life, where 1= least important and 9= very Important.

1(L) 2 3 4 5 6 7 8 9(H)

1. Sense of Belonging

2. Excitement

3. Warm Relationships with others

4. Self-fulfillment

5. Being Well-respected

6. Fun and enjoyment of life

7. Security & Comfort

8. Self-respect

9. A sense of accomplishment

In the original study using LOV by Kahle (1983), only 2% of the sample

endorsed “excitement” as their top value, therefore subsequently, excitement was

collapsed into the “fun and enjoyment in life” category. Kahle’s List of Values does

not dictate that respondents be given definitions of the values which they are asked

to reflect upon. Without a descriptor to establish a common approach to each value,

each respondent to the LOV may not be rating the same set of values. They may be

rating their own subjective interpretations of them instead. The implications are

potentially important because, if certain values have multiple interpretations, the

classification of individuals into value segments on the basis of the single most

important value may be misleading.

110

Giving due consideration to the above two shortcomings of the original

LOV, the scale has been adapted to suit the specific requirements of the present

study which are stated as follows:

a) To remove the value “excitement” as it could be mis-interpreted by

the age group under reference and also because it is similar to the

value “fun & enjoyment in life” as suggested by Kahle.178

b) To add two additional values that are relevant for the study and that

would have a bearing on the manner a person dresses and hence

would have an impact on the clothing purchase decision. The values

added are: ‘Simplicity’ and ‘Being Independent’.

c) To add a descriptor to establish a common approach to each value in

order to avoid subjective/multiple interpretations

THE CONSUMER STYLES INVENTORY [CSI] SPROLES & KENDALL

1986179

A consumer decision-making style is defined as a mental orientation

characterizing a consumer’s approach to make choices. It is a basic consumer

personality, similar to the concept of personality in psychology.180The examination

ofthe decision-making construct can be categorised into three major approaches: the

psychographic/lifestyle approach,181 the consumer typology approach,182 and the

consumer characteristics approach.183 Among these three approaches, the consumer

characteristics approach has been widely acknowledged by consumer researchers as

the most explanatory and powerful construct because it focuses on the cognitive and

affective aspects of consumer behaviour. This approach deals with consumers’

general predisposition towards the act of shopping and describesthe mental

178Kahle, Lynn R. ed. 1983.Social values and social change: adaptation to life in America. New York,

NY: Praeger Publishers. 179Sproles, G.B., Kendall, E.L., (1986), “A methodology for profiling consumer decision making

styles”, The Journal of Consumer Affairs, 20 (2): 67-79 180Sproles G.B. & Kendall, E.L. (1986).A methodology for profiling consumers’ decision-making

styles.Journal of Consumer Affairs, 20 (2), 267-279. 181 Wells, W.D. (1975). Psychographics: A review. Journal of Marketing Research, 11 (May), 196-213. 182Kenson, K. M. (1999). A profile of apparel shopping orientation segments among male consumers.

Unpublished MA, thesis, California State University Long Beach. 183Sproles, E. K. &Sproles, G. B. (1990). Consumer decision-making styles as a function of

individual learning styles. Journal of Consumer Affairs, 24 (1), 134-147.

111

orientation of consumers in their decision-making process.184The underlying idea is

that consumers engage in shopping with certain fundamental decision-making

styles.185

Sproles and Kendall conceptualized the Consumer StylesInventory (CSI),

which is an early attempt to systematically measure shopping orientationsusing

decision-making orientations. One of the most important assumptions of this

approachis that each individual consumer has a specific decision-making style

resulting from acombination of their individual decision making dimensions.

Decision making styles are very important to marketers who want to expand their

products or services into new and overseas markets because, if they can comprehend

the different cultures of these markets, they can easily target their products, services,

locations and promotional efforts according to the types of consumers and identify

the differences and similarities of consumer decision making between different

countries.186

Sproles and Kendall used data from samples of young consumers in the

United States to measure basic characteristics of consumer decision-making styles.

They developed and validated a Consumer Styles Inventory (CSI) for this purpose.

This model has been used internationally by many great researchers to identify the

different shopping characteristics or decision-making styles of consumers. There

have been a substantial number of studies designed to investigate consumer

behaviour.Based on his review of previous literature, Sproles187 initially identified

50 items relating to consumers’ cognitive and affective orientation towards shopping

activities. Subsequently the inventory was refined and a more parsimonious scale

consisting of 40 items was developed. The Consumer Style Inventory (CSI) that

they have developed consists of eight mental consumer style characteristics. Specific

descriptions were given for each style by the authors. 184Lysonski, S., Durvasula, S. &Zotos, Y. (1996). Consumer decision-making styles: a multi-country

investigation. European Journal of Marketing, 30 (12), 10-21. 185SafiekMokhlis and HayatulSafrahSalleh, (2009). Consumer decision-making styles in Malaysia:

An exploratory study of gender differences. European Journal of Social Sciences – Volume 10, Number 4

186Ivan DamirAni , Anita CiunovaSuleska, Edo Rajh. (2010). Decision-making styles of young-adult Ekonomskaistraživanja, Vol. 23, No. 4 (102-113)103

187Sproles, E. K. & Sproles, G. B. (1990). Consumer decision-making styles as a function of individual learning styles. Journal of Consumer Affairs, 24 (1), 134-147.

112

TABLE: 07

DESCRIPTION OF CONSUMER DECISION-MAKING STYLE/ TRAITS

No. Decision-making Style / Trait Characteristics

1 Perfectionist, high-quality

conscious

A characteristic measuring the degree to which

a consumer searches carefully and

systematically for the best quality in products

2 Brand consciousness, “price

equals quality”

Measuring a consumer’s orientation to buying

the more expensive, well-known brands in the

belief that the higher price of a product is an

indicator of better quality.

3 Novelty and fashion conscious A characteristic identifying consumers who

appear to like new and innovative products and

gain excitement from seeking out new things.

4 Recreational and shopping

conscious

A characteristic measuring the degree to which

a consumer finds shopping a pleasant activity

and shops just for the fun of it.

5 Price conscious/value for the

money consciousness

A characteristic identifying those with

particularly high consciousness of sale prices

and lower prices in general.

6 Impulsiveness/Careless A characteristic identifying those who tend to

buy in the spur of the moment and appear

unconcerned about how much they spend (or

getting “best buys”).

7 Confused by Overchoice A characteristic identifying those consumers

who perceive too many brands and stores from

which to choose, experiencing information

overload in the market.

8 Habitual/brand-loyal A characteristic indicating consumers who

have favourite brands and stores, who have

formed habits in choosing these repetitively. Source: Sproles& Kendall, 1986; Sproles and Sproles 1990

113

The 40-item Consumer Style inventory (CSI) was tested on a sample of 482

individuals of the US youth population. The subjects were all high school students in

home economics classes. Also for each style, a three-item short form of the scale

is available (i.e., 24 items total). All items are scored on 5-point Likert- type scales

ranging from strongly disagree to strongly agree. Item scores are summed within

each style separately to create composite scores for each style.

The original version on the Consumer Style Inventory is given below:

Table 08

Consumer Styles Inventory CSI (original constructs)

Sproles& Kendall (1986, 1990)

1) Perfectionist/High Quality Conscious (seven-item alpha = 0.74, three-item

alpha = 0.69)

1. Getting very good quality is very important to me.

2. When it comes to purchasing products, I try to get the very best or perfect choice.

3. In general, I usually try to buy the best overall quality.

4. I make a special effort to choose the very best quality products.

5. I really don’t give my purchases much thought or care. *

6. My standards and expectations for products I buy are very high.

7. I shop quickly, buying the first product or brand I find that seems good enough. *

2 Brand Consciousness/Price Equals Quality (six term alpha = 0.75, three –

item alpha=0.63)

1. The well-known national brands are for me.

2. The more expensive brands are usually my choices.

3. The higher the price of the product, the better the quality.

4. Nice department and specialty stores offer me the best products.

5. I prefer buying the best selling brands.

6. The most advertised brands are usually very good choices.

114

3) Novelty and Fashion Conscious (five-item alpha = 0.74, three-item alpha =

0.76)

1. I usually have one or more outfits of the very newest style.

2. I keep my wardrobe up-to-date with the changing fashions.

3. Fashionable, attractive styling is very important to me.

4. To get variety, I shop at different stores and choose different brands.

5. It’s fun to buy something new and exciting.

4 Recreational and Shopping Conscious (five-item alpha = 0.76, three-item

alpha = 0.71)

1. Shopping is not a pleasant activity to me. *

2. Going shopping is one of the most enjoyable activities of my life.

3. Shopping the stores wastes my time.*

4. I enjoy shopping just for the fun of it.

5. I make shopping trips fast. *

5) Price Conscious/Value for the money (alpha = 0.48)

1. I buy as much as possible at sale prices.

2. The lowest price products are usually my choice.

3. I look carefully to find the best value for the money.

6 Impulsiveness/Careless (five-item alpha = 0.48, three-item alpha = 0.41)

1. I should plan my shopping more carefully than I do.

2. I am impulsive when purchasing.

3. Often I make careless purchases I later wish I had not.

4. I take the time to shop carefully for best buys. *

5. I carefully watch how much I spend. *

115

7) Confused by Overchoice (four-item alpha = 0.55, three-item alpha = 0.51)

1. There are so many brands to choose from that I often feel confused.

2. Sometimes its hard to choose which stores to shop.

3. The more I learn about products, the harder it seems to choose the best.

4. All the information I get on the different products confuses me.

8) Habitual/Brand Loyalty (four-item alpha = 0.53, three-item alpha = 0.54)

1. I have favourite brands I buy over and over.

2. Once I find a product or brand I like, I stick with it.

3. I go to the same stores each time I shop.

I change brands I buy regularly. * Notes: * denotes items that require reverse scoring. Items scored on 5-point Likert-

type scales from strongly disagree to strongly agree.

For the purpose of this study the original Consumer Style Inventory was

adapted with the following modifications:

a) The three item short version of the Consumer Style Inventory – i.e.,

the 24 item inventory was used instead of the lengthy 40 item

inventory. This was done keeping in the mind the age group of

respondents who may not have the patience to fill up a lengthy

questionnaire.

b) The original 24 statements were partially re-worded to describe

shopping behaviour towards apparels. This was done to ensure that

every respondent gave his/her opinion for each statement with

apparels as the product to consider for purchase.

116

APPAREL MANUFACTURES/MARKETERS PERSPECTIVES ON THE

PROPOSED VALUE- SHOPPING STYLE MODEL OF THE STUDY

The researcher intended to confirm the appropriateness of the proposed

model directly from the apparel manufacturers, marketers and fashion designers to

ensure that the findings of the study benefit the target audience. A semi-structured

interview was conducted with a randomly selected group of ten individuals working

in Bangalore, comprising of Store Managers of leading apparel brands, fashion

designers in international brand companies and retail apparel marketers. The

summary of the discussion is presented below.

The target customers for most of the respondents were Men/Women/kids of

all age groups. The type of apparels they dealt in varied from Casual wear and

formal wear to all categories of apparels. All the respondents agreed that they design

clothes as per customer needs.

Primarily apparel marketers assess customer needs and preferences with the

help of Fashion/Trends magazines, whereas apparel manufacturers and fashion

designers also conduct their own research to assess their target customer needs and

preferences. While generally profiling young adult consumers for apparels, all the

respondents strongly agreed that young adult consumers are selective about the

clothes they wear; agreed that young adult consumers prefer good quality clothes

and are fashion conscious. They agreed that cultural background and value systems

affect young adults’ apparel buying behaviour. They neither agreed nor disagreed

that young adult consumers are highly brand conscious, are impulsive when

purchasing apparels and are brand loyal.

The modes of advertising that is most effective to reach young adult

consumers were: firstly, the television and secondly, the internet. However, they felt

that it depends on the retail model. If it’s an online retail model then the internet is

the best marketing tool. If it’s an offline retail model, then Television and Fashion

magazines would serve to be more appropriate for marketing. Hoardings and

Newspapers primarily create brand awareness.

117

Most of the manufacturers and marketers had done some research to study

the factors that influence buying behaviour of young adults for apparels. They

expressed that personal values affect the buying behaviour for apparels; however, a

few of them stated that it depends upon which tier/band of income & city were

targeted because values affect buying behaviours in Tier-II and Tier-III cities.

Fashion is the main consideration while selecting apparels by young adults.

All of them agreed that a model that studies the link between personal values and

buying behaviour for apparels would be very useful for the Indian market to help

them develop better marketing strategies.

The given inputs and the intense review of literatures in the related area

supported in developing the ‘Value – Shopping Style Model’ which is proposed

and tested in this study.

118

‘THE VALUE - SHOPPING STYLE MODEL’

Do values influence the Shopping styles of young adults for apparel

purchases? The study aims to establish this relationship by proposing ‘The Value –

Shopping Style Model’ illustrated in Fig. 3 below:

FIG. 3: ‘THE VALUE – SHOPPING STYLE MODEL’ - VSM

The model is proposed and tested to verify the validity of adding two new

values ‘Simplicity’ and ‘Being Independent’ which were not part of the original

LOV developed by Kahle (1983),and the confirmation of the Apparel Shopping

Constructs to the original CSI Constructs developed by Sproles & Kendall (1986).

PERSONAL VALUES

1. Self-respect,

2. Security,

3. Warm relationships with others,

4. Self fulfillment,

5. A sense of accomplishment,

6. Being respected,

7. A sense of belonging,

8. Fun and enjoyment of life,

9. Simplicity

10. Being Independent

SHOPPING STYLES

1. Perfectionist, high quality

conscious consumer

2. Brand conscious, “price equals

quality” consumer

3. Novelty-fashion conscious

consumer

4. Recreational and hedonistic

shopping consciousness

5. Price conscious, “value for

money” consumer

6. Impulsive, careless consumer

7. Confused by overchoice

consumer

8. Habitual, brand loyal consumer

INFLUENCE

119

CHAPTER 5

ANALYSIS AND INTERPRETATION OF DATA

INTRODUCTION

This chapter presents the statistical analysis of the data, its interpretation and

the results. The data is carefully processed, systematically classified, scientifically

analyzed, properly interpreted and rationally concluded and presented in the

following sections.

After the data had been collected, it was processed and tabulated using

Microsoft Excel 2007 and SPSS version 19 (Statistical package for Social Sciences).

The statistical tools employed were Frequency and Percentage distributions, Mean

and Standard Deviation, Cronbach Alpha for reliability. Pearson’s Coefficient of

Correlation was used to study the relationship between values and shopping styles.

The research hypotheses were tested using t statistic and ANOVA. The proposed

model was tested with Structural Equation Modeling using AMOS16. All measures

were subjected to Confirmatory Factor Analysis to provide support for the issues of

dimensionality, i.e., to find out if the dimensions manifested in the present study

conformed to the original model. To evaluate the fit of the models, Chi-square

Goodness of Fit Indices and RMSEA (Root Mean Square Error of Approximation)

were used.188 Regression Analyses were carried out to study the influence of values

on the shopping styles of young adults for apparels. The obtained results have been

presented and interpreted in this chapter.

188 Arbuckle and Wothke,1999

120

DESCRIPTIVE STATISTICS FOR DEMOGRAPHIC VARIABLES

The following section presents descriptive statistics for the demographic

variables such as gender, education level and regional background of the

respondents, in the form of frequency tables and pictorial representation.

TABLE:09 Gender of Respondents

Gender Frequency Percent

Male 804 54.4

Female 674 45.6

TOTAL 1478 100

Source: Primary data FIG.4

Gender of Respondents

Source: Primary data

The above table and figure indicate that total number of respondents for the

study were 1478, of which 804 (54.4%) were male respondents and 674 (45.6%)

were female respondents.

The demographic profile of the respondents for the study more or less

replicates the demographic profile of the population of Bangalore city. The Male :

Female gender ratio is 1000:968 (50.81% : 49.19%) in Karnataka, the ratio of male

and female respondents for the study is 804:674 (54% : 46%).

GENDER OF RESPONDE

NTS0%

Male54.4%

Female45.6%

121

TABLE: 10

Education Level of Respondents

Education Level Frequency Percent

UG 1131 76.5

PG 289 19.6

Others

[Diploma/PUC etc]

58 3.9

TOTAL 1478 100


FIG.5

Educational Level of Respondents


The above table reveals that 1131 (76.5%) of the respondents were college

going students doing Undergraduate courses, 289 (19.6%) were doing Postgraduate

courses and 58 (3.9%) were PUC or Diploma holders under the age of 25 years.

Bangalore being an important hub for higher learning institutions, the size of

the college-going young adults’ population is considerable. Hence the sample size of

1478 respondents is an ideal representation of this group to draw meaningful

conclusions about the population.

76.5%UG

19.6%PG

3.9%

UGPGOthers

122

The respondents of the study were representing 28 different states of India,

signifying diverse ethnic and cultural background. The respondents were re-grouped

according to the state of origin into four regions as North, South, East and West.

The states covered under the regions are:

Northern Region: Delhi, Haryana, Himachal Pradesh, Jammu & Kashmir, Punjab,

Uttar Pradesh

Southern Region: Karnataka, Tamil Nadu, Andhra Pradesh, Karnataka, Kerala

Eastern Region: Agartala, Assam, Sikkim, Bihar, Jharkand, Manipur, Megalaya,

Nagaland, West Bengal and Odisha

Western Region:Maharashtra, Goa, Gujarat, Madhya Pradesh and Rajasthan

TABLE 11 Regional Background of Respondents

Region Frequency Percent

South 1053 71.2

East 165 11.2

North 156 10.6

West 104 7.0

Total 1478 100


FIG. 6 Regional Background of Respondents


71.2%

11.2% 10.6% 7%

01020304050607080

South East North West

123

It was found that there were 1053 (71.2 %) respondents hailing from the

Southern part of India, 165 (11.2%) were hailing from the Eastern part, 156 (10.6 %)

respondents were hailing from the Northern part of India, 104 (7%) were hailing

from the Western part of India.

The above table confirms the fact that Bangalore is a cosmopolitan city with

influx of people from all over the country. The demographic profile of Bangalore

city shows that 88% of the population is from the southern states such as Tamil

Nadu, Kerala, Andhra and Karnataka.189This is clearly reflected through the higher

representation of respondents from Southern part of India in the sample of the study.

DESCRIPTIVE STATISTICS FOR INDEPENDENT VARIABLES

The independent variables of the study were personal values adapted from

Kahle’s List of Values (LOV, 1983). The original List of Values had nine values; it

has been modified to suit the requirements of the present study.

a) The value “excitement” found in the original LOV was removed as it

could be mis-interpreted by the age group under reference and also

because it is similar to the value ‘fun & enjoyment in life’.

b) Two values were added to the list that are relevant for the study and

that would have a bearing on the manner a person dresses and hence

would have an impact on the clothing purchase decision. The values

added are: ‘Simplicity’ and ‘Being Independent’. Thus, totally ten

values were used as the independent variables for this study.

To analyze the internal consistency of the independent variablesviz., The List

of Values, a reliability test was carried out and is presented below.

189Source: Bangalore City Development Plan JNNURM.

124

TABLE:12

Reliability Statistics for List of Values

Scale: ALL VARIABLES

Reliability Statistics

Cronbach's Alpha N of Items

.903 10


Item-Total Statistics

Scale Mean

if Item

Deleted

Scale

Variance if

Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if Item

Deleted

1. Sense of Belonging 65.92 149.876 .609 .897

2.Simplicity 66.69 149.235 .607 .897

3. Warm Relationships with

others 66.50 147.728 .671 .893

4. Self-fulfillment 66.40 146.436 .666 .893

5. Being Well-respected 66.30 145.827 .722 .890

6. Fun and enjoyment of life 66.21 147.035 .641 .895

7. Security & Comfort 66.26 148.205 .637 .895

8. Self-respect 65.94 145.643 .730 .889

9. A sense of

accomplishment 66.37 146.658 .684 .892

10. Being Independent 66.29 146.827 .613 .897


It was found that the List of Values (LOV) scale used for assessing the

values cherished by young adults in Bangalore was highly reliable with a

Cronbach’s Alpha value of 0.903.

125

Hierarchy of Values Important to Young Adults

The respondents were asked to rate the ten values on a 9 point scale

according to the level of importance of each value to them. A small descriptor was

provided for each value to establish a common approach to rate each value and

avoid subjective/multiple interpretations.

The following table presents the hierarchy of these values in terms of the

calculated mean values.

Objective 1: To identify the values which are perceived to be important among

young adults.

TABLE: 13

Hierarchy of Values Important to Young Adults

VALUES Mean Std. Deviation

Sense of Belonging 7.71 1.881

Self-respect 7.69 1.870

Fun and enjoyment of life 7.42 1.980

Security & Comfort 7.37 1.938

Being Independent 7.34 2.054

Being Well-respected 7.33 1.868

A sense of accomplishment 7.25 1.906

Self-fulfillment 7.23 1.958

Warm Relationships with others 7.13 1.870

Simplicity 6.94 1.925


The above table indicates that among the list of values that young adults

cherish, Sense of Belonging has the highest mean score 7.71, followed by Self-

126

respect which has a mean score of 7.69. Fun and enjoyment of life has a mean score

of 7.42 followed by Security & Comfort with a mean score of 7.37. The value

simplicity has the lowest mean score of 6.94.

The analysis of the perceived level of importance of values among young

adults revealed some very interesting aspects.

1) Among the list of values that young adults in the age group 18-25 perceive to

be important, ‘Sense of belonging’ was rated as the most important value

(mean score 7.71). The feeling that family and friends care about them is

very important to this age group. The institution of the family and the family

support system are the main drivers in life. When this basic feeling of

belonging is established and confirmed in life, it gives a secure feeling that

every challenge can be faced bravely.

2) The second important value for this segment is ‘Self- respect’ (mean score

7.69). Self-esteem, belief in one’s own worth, preserving self-image are very

important to the 18-25 age group of young adults who are predominantly

college going students doing under graduate/post graduate/professional

studies. Though they are mostly under the supervision of their parents, they

do not like to be treated like kids. They expect their parents, teachers and

colleagues to treat them with respect and are very sensitive about this. They

desire to stand up for their beliefs and values.

3) The third important value cherished by young adults is ‘Fun and enjoyment

of life’ (mean score 7.42). Seeking adventure, novelty and change and

enjoying food and leisure very clearly describes the general disposition of

the youth population. It is that phase of life where they lead a carefree life,

not bogged down with work or family responsibilities and seek fun and

enjoyment in all that they do. They also seek adventure in this phase. They

look for Novelty in everything and get bored with tradition. Change is

embraced easily and sought after in all that they do.

127

4) The fourth value cherished by this group is ‘Security & Comfort’ (mean

score 7.37). Safety and secure surroundings are perceived to be important for

the young adults to lead a carefree and happy life. The news items on

violence, terrorism, abduction, murder, rape, abuse and so on, which are

rampant all over India, gives them an insecure feeling.

5) ‘Being Independent’ was considered as the fifth important value (mean

score 7.34) by the respondents. Being self reliant and self-sufficient displays

the characteristic of the present day young generation. They are highly

technology savvy, have knowledge accessible at their finger-tips, and prefer

to work independently.

6) The value considered sixth important to young adults is ‘Being well

respected’ (mean score 7.33). Having social recognition, respect and

approval from others is important to this age group. The young adult

population seeks to be affiliated to groups or individuals who share their

ideals, likes and interests. Being identified as part of the group or at least in

general conforming to the standards of expectations of modern youth culture

is important to them.

7) Sense of accomplishment (mean score 7.25) is the seventh important value

for the young adult population. Being successful and doing something which

was never done before are attributes that can be associated with this age

group. They are go-getters and achievers and desire success in all their

endeavours.

8) Self fulfillment (mean score 7.23) is eighth in the value hierarchy for young

adults. Being creative, enjoying what is being done and achieving inner

harmony is preferred by this group. Satisfaction comes from being happy

with one-self and doing what is pleasing.

9) The value considered ninth important to young adults is ‘Warm

relationships with others’ (mean score 7.13). Maintaining cordial relations

with others is required but not very important to this age group. Being

128

independent is perceived to be more important than warm relationships

others.

10) The least important in the value hierarchy for young adults is ‘Simplicity’

(mean score 6.94). Being unassuming, straight forward, and down to earth

are not the preferred traits for this age group. On the contrary, they prefer to

have the best things in life, high quality items, latest in fashion and

technology. Young adults are attention seekers and love to flaunt and display

their skills, abilities and possessions and are seldom simple.

DESCRIPTIVE STATISTICS FOR VALUE DIMENSIONS

The study also analyses the values orientations of the respondents based on the

value categories mentioned by Kahle in his List of Values (1983). The list of values

is further grouped under three categories as External values, Internal Individual

values and Internal Inter-personal values. Understanding young adult population

based on their value orientations would facilitate apparel manufacturers, marketers

and fashion designers to further fine tune their marketing strategies and cater to this

population segment based on their psychographic attributes.

To analyze the internal consistency of the value dimensions a reliability test

was carried out and is presented below.

129

TABLE: 14

Reliability Statistics for Value Dimensions


Cronbach's Alpha N of Items

.884 3



Scale Mean

if Item

Deleted

Scale

Variance if

Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if

Item Deleted

External Values 14.6127 7.787 .772 .838

Internal Interpersonal

Values 14.8100 7.366 .765 .846

Internal Individual

Values 14.7911 7.919 .790 .823


It was found that the three dimensions of the value scale were highly reliable

with a Cronbach’s Alpha value of 0.884. This gives further scope to the study to

analyse the relationship and influence of the value dimensions on young adults.

130

The following table presents the hierarchy of value orientations in young

adults in terms of the calculated mean values.

TABLE: 15

Hierarchy of Value Orientations in Young Adults

Value Dimensions Mean Std. Deviation

External Values

[Sense of belonging, Being well

respected, Security & comfort]

7.49 1.48070

Internal Individual Values

[Self-fulfillment, Self respect, A sense

of accomplishment, Simplicity, Being

Independent]

7.31 1.44328

Internal Interpersonal Values

[Warm relationships with others, fun

and enjoyment of life]

7.29 1.57839


The above table indicates that most of the young adult respondents attach

greater importance to External values such as Sense of belonging, Being well

respected, Security & Comfort with a mean score of 7.49, followed by Internal

Individual values such as Self-fulfillment, Self respect, Sense of accomplishment,

Simplicity, Being Independent with a mean score of 7.31. Internal Interpersonal

values such as Warm relationships with others, fun and enjoyment of life with a

mean score of 7.29 was comparatively lower in their preference.

131

DESCRIPTIVE STATISTICS FOR DEPENDENT VARIABLES

The Dependent variables of the study were eight shopping styles. The

Consumer Styles Inventory conceptualized by Sproles and Kendall (1986) describes

eight mental orientation of consumers in their decision-making process viz.,

Perfectionist/high-quality conscious; Brand conscious/price equals quality; Novelty

and fashion conscious; Recreational & shopping conscious; Price conscious/value-

for-money; Impulsiveness/Careless; Confused by overchoice; and Habitual/brand-

loyal.

The original instrument had 40 items to measure general orientations towards

shopping. A three-item short form of the scale was also made available (i.e., 24

items total) by the original authors.

For the purpose of this study the original CSI was adapted with the following

modifications:

a) The three item short version of the CSI – i.e., the 24 item inventory was used

instead of the lengthy 40 item inventory. This was done keeping in the mind

the age group of respondents who may not have the patience to fill up a

lengthy questionnaire.

b) The original 24 statements were partially re-worded to describe shopping

behaviour towards apparels. This was done to ensure that every respondent

gave his/her opinion for each statement with apparels as the product to

consider for purchase.

To analyze the internal consistency of the Consumer Style Inventory used in

the study, a reliability test was carried out and is presented below.

132

TABLE: 16

Reliability Statistics for Consumer Style Inventory

Scale: All Variables


Alpha N of Items

.787 24



Scale

Mean if

Item

Deleted

Scale

Variance if

Item Deleted

Corrected

Item-Total

Correlation

Cronbach's

Alpha if Item

Deleted

Getting very good

quality of clothes is

very important to me.

74.04 106.046 .433 .774

When it comes to

purchasing clothes, I

try to get the very best

or perfect choice.

73.92 105.325 .498 .771

In general, I usually try

to buy the best overall

quality of apparels.

74.18 106.217 .462 .773

The well-known

national brands are for

me.

74.81 104.885 .472 .772

The more expensive

brands are usually my

choices.

75.28 103.862 .478 .771

133

The higher the price of

the apparel, the better

the quality.

74.92 106.829 .311 .780

I usually have one or

more outfits of the very

newest style.

74.80 105.293 .449 .773

I keep my wardrobe up-

to-date with the

changing fashions.

75.07 104.006 .473 .771

Fashionable, attractive

styling is very

important to me.

74.71 104.082 .456 .772

Shopping for clothes is

not a pleasant activity

to me.

74.49 111.759 .097 .793

Going shopping for

clothes is one of the

most enjoyable

activities of my life.

74.74 103.828 .403 .775

Shopping the stores for

clothes wastes my time. 74.50 111.057 .144 .789

I buy most of my

clothes at sale prices. 74.75 112.262 .125 .789

The lowest price outfits

are usually my choice. 75.25 116.826 -.090 .800

I look carefully to find

the best value for the

money.

73.92 113.812 .059 .792

I should plan my

shopping more

carefully than I do.

74.39 109.419 .237 .784

I am impulsive when

purchasing clothes. 74.64 107.818 .343 .778

134

Often I make careless

purchases of clothes I

later wish I had not.

74.82 107.902 .266 .783

There are so many

brands to choose from

that I often feel

confused.

74.57 105.414 .401 .775

Sometimes it is hard to

choose which stores to

shop for clothes.

74.47 106.907 .345 .778

The more I learn about

apparel brands, the

harder it seems to

choose the best.

74.58 106.763 .375 .777

I have favourite brands

I buy over and over. 74.53 102.777 .507 .769

Once I find a brand I

like, I stick with it. 74.69 106.200 .362 .777

I go to the same stores

each time I shop. 74.78 108.955 .236 .784


The Consumer Style Inventory scale used for identifying the shopping styles

of young adults were found to be highly reliable with an overall Cronbach’s Alpha

value of 0.787.

Segmenting Young Adults Based on Their Shopping Styles

The respondents were asked to score the 24 items of the CSI on 5-point Likert-

type scales ranging from strongly disagree to strongly agree.These24 items were

grouped under the eight shopping styles as prescribed by Sproles and Kendall. Each

style had three items under it. Item scores were summed within each style separately

to create composite scores for each style.

135

The respondents were segmented according to their preferred shopping style

based on the mean values for each shopping style. The results are presented in Table

14 given below:

Objective 2: To segment young-adult consumers based on their shopping styles

towards purchase of apparels.

TABLE: 17

Preferred Shopping Style of Young Adults

Shopping Style Mean Std. Deviation

Perfectionist/High Quality Conscious 3.8207 .77958

Confused by Overchoice 3.3276 .89247

Recreational and Shopping Conscious 3.2832 .95680

Impulsiveness/Careless 3.2551 .77968

Price Conscious/Value for money 3.2251 .65830

Habitual/Brand Loyal 3.1973 .89077

Novelty and Fashion Conscious 3.0063 .88608

Brand Conscious/Price Equals Quality 2.8637 .87226


The above table categorizes the entire respondent group of the study into

their preferred shopping style. The results indicate that Perfectionist/High Quality

consciousness (3.8207) was the predominant trigger for young adults in their

purchase-decisions for apparels followed by Confused by Overchoice (3.3276) and

Recreational and Shopping Conscious (3.2832). The Impulsive style had a mean of

3.2551 followed by Price conscious/value for money (3.2251). Brand loyalty had a

mean of (3.1973), Novelty and fashion conscious (3.0063) and the least preferred

shopping style was Brand conscious/price equals quality with a mean of (2.863).

136

The preferred shopping style of young-adult consumers revealed in the above

table is analyzed to describe their apparel shopping behavior.

1. Perfectionist/High Quality Conscious (mean 3.8207) is the predominant

style of young adults in their purchase-decisions for apparels. This group of

respondents seeks to maximize quality by choosing the best products. They

set high standards and have high expectations for the products they buy and

aim to get the best choice and value for money. Being higher in

perfectionism, these consumers could be expected to shop more carefully,

more systematically, or by comparison.

2. Confused by Overchoice (3.3276) is the second style prevalent among the

respondent group. Items loaded on this style suggest that these shoppers feel

confused and overloaded with information. They find it hard to choose the

best clothes or stores to shop. They feel the quantity of different consumer

brands is confusing. The amount of information available about these

different brands adds to confusion. Hence, this factor is named Confused by

Overchoice Consumer. They are aware of the many brands and stores from

which to choose and have difficulty making those choices.

3. Recreational and Shopping Conscious (3.2832) is the third preferred

shopping style of young adults. Items loading on this factor indicate that

shopping is an enjoyable and pleasant activity. Identified characteristics

show that they do not feel that shopping wastes time. Because shopping is

enjoyable, pleasant, fun filled activity.

4. The fourth preferred shopping style among young adults is the

Impulsiveness/Careless style with a mean of 3.2551. Items loaded in this

factor indicate that these shoppers are impulsive and careless in making their

purchases. They regret their impulsive shopping behaviour. Consumers who

score high on this factor tend to buy in the spur of the moment and later

regret their impulsive behaviour. They are also unconcerned about getting

best products by shopping as quickly as they can.

137

5. Price conscious/value for money (3.2251) ranked fifth as the preferred style

of young adults. Consumers of this characteristic look for sale prices and

generally appear to be conscious of lower prices. They tend to carefully

watch their spending and try to get the best value for the money spent on

apparels. This may also be due to the need to drive the maximum value for

their limited resources, which is also in line with theoretical economics as

reported by Schiffman and Kanuk (1997) that consumers, especially low

income earners are always economical in their purchase decision and always

consider functional (quality) aspect of a product in order to make a purchase

that is not just satisfactory but a perfect one (maximum value for money).

6. Habitual, Brand-Loyal Consumer (3.1973), is the sixth preferred shopping

style of young adults. This style reflects the characteristic of shoppers who

are habitual in buying same brands regularly. They have strong loyalty

towards the brands as well as stores. They appear to have favourite brands

and stores and to have formed habits in choosing these.

7. Novelty and fashion conscious (3.0063) is the seventh preferred style of

young adults. Items of this factor indicate that fashionable attractive styling

is important to them. These shoppers compare brands and take time to shop

carefully indicating that they are comparison shoppers. They usually have

one or more outfits of the newest style. They keep up to date with styles and

being in style is important to them.

8. The least manifested shopping style among the young adult respondent group

was Brand Consciousness/Price Equals Quality with a mean of (2.863).

This shopper style prefers buying the best selling and most expensive brands.

They buy the well known national and international brands and shop at nice

department or specialty stores. They tend to buy heavily advertised brands

and equate prices with quality. They tend to believe that a higher price means

better quality and appear to have positive attitudes toward department and

specialty stores. Brand name, quality and the price are the most important

purchasing criteria for these shoppers.

138

SHOPPING STYLE-WISE DESCRIPTIVE STATISTICS

The hierarchy of the three items within each shopping style is studied with

the help of their mean values to gain a deeper understanding of the characteristics of

the respondents who fall under this shopper segment.

In the following section the shopping style-wise mean and standard

deviations along with the Cronbach Alpha value for reliability and internal

consistency of the data is presented.

TABLE:18

Hierarchy of items under Perfectionist/High Quality Conscious style

Perfectionist/High Quality Conscious

Three-item alpha =0.752 Mean Std. Deviation

When it comes to purchasing clothes, I try to get

the very best or perfect choice.

3.95 .943

Getting very good quality of clothes is very

important to me.

3.82 .994

In general, I usually try to buy the best overall

quality of apparels.

3.69 .920


The above table describes the hierarchy of the individual items under the

‘Perfectionist/High Quality Conscious’ shopping style. It was found the

shopping attribute ‘When it comes to purchasing clothes, I try to get the very best

or perfect choice’ had the highest mean (3.95) followed by ‘Getting very good

quality of clothes is very important to me’ (3.82) and ‘In general, I usually try to

buy the best overall quality of apparels’ (3.69). This factor is considered highly

reliable with an alpha coefficient of 0.752. This is much higher than the three item

alpha 0.69 obtained in the Sproles and Kendall original study.

139

TABLE: 19

Hierarchy of items under Brand Conscious/Price Equals Quality style

Brand Conscious/Price Equals Quality


The well-known national brands are for me. 3.06 1.027

The more expensive brands are usually my choices 2.95 1.185

The higher the price of the apparel, the better the

quality.

2.59 1.109



‘Brand Conscious/Price Equals Quality’ shopping style. It was found that the

shopping attribute ‘The well-known national brands are for me’ had the highest

mean (3.06) followed by ‘The more expensive brands are usually my choices’ (2.95)

followed by ‘The higher the price of the apparel, the better the quality’ (2.59). This

factor is considered reliable with an alpha value of 0.695, which is higher than the

three-item alpha 0.63 obtained in the Sproles and Kendall original study.

TABLE:20

Hierarchy of items under Novelty and Fashion Conscious style

Novelty and Fashion Conscious

Three-item alpha =0.749 Mean

Std.

Deviation

Fashionable, attractive styling is very important to me. 3.16 1.128

I usually have one or more outfits of the very newest style. 3.07 1.028

I keep my wardrobe up-to-date with the changing fashions. 2.79 1.101


140


‘Novelty and Fashion Conscious’ shopping style. It was found the shopping

attribute ‘Fashionable, attractive styling is very important to me’ (3.16) had the

highest mean, followed by ‘I usually have one or more outfits of the very newest

style’ (3.07) followed by ‘I keep my wardrobe up-to-date with the changing

fashions’ (2.79). This factor is accepted to be highly reliable with an alpha value of

0.749, which is almost similar to the three-item alpha 0.76 obtained in the Sproles

and Kendall original study.

TABLE: 21

Hierarchy of items under Recreational and Shopping Conscious style

Recreational and Shopping Conscious


Std.

Deviation

Shopping for clothes is not a pleasant activity to me. 3.36 1.253

Shopping the stores for clothes wastes my time. 3.36 1.156

Going shopping for clothes is one of the most enjoyable

activities of my life.

3.13 1.269



‘Recreational and Shopping Conscious’ shopping style. It was found the

shopping attribute ‘Shopping for clothes is not a pleasant activity to me’ (3.36) and

‘Shopping the stores for clothes wastes my time’ (3.36) had higher means, followed

by ‘Going shopping for clothes is one of the most enjoyable activities of my life’

(3.13). This factor is accepted to be reliable with an alpha value of 0.675, which is

slightly lower than the three-item alpha 0.71 obtained in the Sproles and Kendall

original study.

141

TABLE:22

Hierarchy of items under Price Conscious/Value for money style

Price Conscious/Value for money


I look carefully to find the best value for the money. 3.94 .947

The lowest price outfits are usually my choice. 3.12 .992

I buy most of my clothes at sale prices. 2.61 1.045



‘Price Conscious/Value for money’ shopping style. It was found the shopping

attribute ‘I look carefully to find the best value for the money’ had the highest mean

(3.94), followed by ‘The lowest price outfits are usually my choice’ (3.12), followed

by ‘I buy most of my clothes at sale prices’ (2.61). This factor is the least reliable

with an alpha value of 0.353, which is lower than the three-item alpha 0.48 obtained

in the Sproles and Kendall original study.

TABLE: 23

Hierarchy of items under Impulsiveness/Careless style

Impulsiveness/Careless


Std.

Deviation

I should plan my shopping more carefully than I do. 3.49 1.063

I am impulsive when purchasing clothes. 3.23 .989

Often I make careless purchases of clothes I later wish I had

not.

3.05 1.187


142


‘Impulsiveness/Careless’ shopping style. It was found that the shopping attribute

‘I should plan my shopping more carefully than I do’ had the highest mean (3.49),

followed by ‘I am impulsive when purchasing clothes’ (3.23), followed by ‘Often I

make careless purchases of clothes I later wish I had not’ (3.05). The above table

also indicates that the scale items were found moderately reliable with Cronbach’s

Alpha value 0.530. However, it is much higher than the three item alpha 0.51

obtained in the Sproles and Kendall original study.

TABLE:24

Hierarchy of items under Confused by Overchoice style

Confused by Overchoice


Sometimes it is hard to choose which stores to

shop for clothes.

3.40 1.092

There are so many brands to choose from that I

often feel confused.

3.30 1.119

The more I learn about apparel brands, the

harder it seems to choose the best.

3.29 1.039



‘Confused by Overchoice’ shopping style. It was found that the shopping attribute

‘Sometimes it is hard to choose which stores to shop for clothes’ had the highest

mean (3.40), followed by ‘There are so many brands to choose from that I often feel

confused’ (3.30), and followed by ‘The more I learn about apparel brands, the harder

it seems to choose the best’ (3.29). This factor is considered highly reliable with an

alpha of 0.761, which is much higher than the three item alpha 0.51 obtained in the

Sproles and Kendall original study.

143

TABLE:25

Hierarchy of items under Habitual/Brand Loyal style

Habitual/Brand Loyal


I have favourite brands I buy over and over. 3.33 1.149

Once I find a brand I like, I stick with it. 3.17 1.128

I go to the same stores each time I shop. 3.09 1.144



‘Habitual/Brand Loyal’ shopping style. It was found that the shopping attribute ‘I

have favourite brands I buy over and over’ had the highest mean (3.33), followed by

‘Once I find a brand I like, I stick with it’ (3.17), followed by ‘I go to the same

stores each time I shop’ (3.09). An alpha of 0.680 indicates that the reliability of this

factor is good. Compared to the three-item alpha 0.54 obtained in the Sproles and

Kendall original study indicates higher reliability of this factor in the present study.

144

INTRA-CORRELATION WITHIN VARIABLES

Intra – correlations within the variables of the study is calculated using Karl

Pearson’s Co-efficient of Correlation to ascertain the relationships among them.

TABLE:26

Intra-Correlations among Value Dimensions

Correlations

External

values

Internal

Interpersonal

values

Internal

Individual

values

External values

Pearson Correlation 1 .701** .734**

Sig. (2-tailed) .000 .000

N 1477 1477 1477

Internal

Interpersonal values

Pearson Correlation .701** 1 .728**

Sig. (2-tailed) .000 .000

N 1477 1478 1478

Internal Individual

values

Pearson Correlation .734** .728** 1

Sig. (2-tailed) .000 .000

N 1477 1478 1478

**. Correlation is significant at the 0.01 level (2-tailed).


The above table indicates that there is a significant positive correlation at

the 0.01 level among the value dimensions. This adds strength to the validity of the

scale used and its dimensionality. It also gives solid grounds for further analysis

using the scale.

145

TABLE:27

Intra-Correlations among individual Values

Correlations

sense

of

belong

Simplicity warm

relationships selfulillment

being

well

respected

fun &

enjoyment

security

&

comfort

self

respect

sense of

accomplishment

being

independent

sense of belong

Pearson

Correlation 1 .444** .530** .450** .539** .445** .475** .486** .403** .338**

Sig. (2-

tailed)

.000 .000 .000 .000 .000 .000 .000 .000 .000

N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478

simplicity

Pearson

Correlation .444** 1 .575** .474** .479** .402** .389** .476** .444** .404**

Sig. (2-

tailed) .000

.000 .000 .000 .000 .000 .000 .000 .000

N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478

warm relation-

ships

Pearson

Correlation .530** .575** 1 .538** .538** .468** .455** .503** .464** .404**

Sig. (2-

tailed) .000 .000

.000 .000 .000 .000 .000 .000 .000

N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478

selfulill-ment

Pearson

Correlation .450** .474** .538** 1 .521** .499** .442** .548** .503** .465**

Sig. (2-

tailed) .000 .000 .000

.000 .000 .000 .000 .000 .000

N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478

being well

respected

Pearson

Correlation .539** .479** .538** .521** 1 .501** .526** .624** .540** .475**

Sig. (2-

tailed) .000 .000 .000 .000

.000 .000 .000 .000 .000

N 1477 1477 1477 1477 1477 1477 1477 1477 1477 1477

fun &

enjoyment

Pearson

Correlation .445** .402** .468** .499** .501** 1 .506** .512** .499** .456**

Sig. (2-

tailed) .000 .000 .000 .000 .000

.000 .000 .000 .000

N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478

security &

comfort

Pearson

Correlation .475** .389** .455** .442** .526** .506** 1 .557** .488** .433**

Sig. (2-

tailed) .000 .000 .000 .000 .000 .000

.000 .000 .000

N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478

self respect

Pearson

Correlation .486** .476** .503** .548** .624** .512** .557** 1 .584** .535**

Sig. (2-

tailed) .000 .000 .000 .000 .000 .000 .000

.000 .000

N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478

sense of

accomplishmen

t

Pearson

Correlation .403** .444** .464** .503** .540** .499** .488** .584** 1 .608**

Sig. (2-

tailed) .000 .000 .000 .000 .000 .000 .000 .000

.000

N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478

being

independent

Pearson

Correlation .338** .404** .404** .465** .475** .456** .433** .535** .608** 1

Sig. (2-

tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000

N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478



146

The above table indicates that there is a significant positive correlation at

the 0.01 level among all the individual values. This adds strength to the validity of

the scale used and its dimensionality. It also gives solid grounds for further analysis

using the scale.

TABLE:28

Intra-Correlations among Shopping Styles

Correlations

perfectionist Brand

conscious novelty Recreational

Price conscious

impulsive confused Brand loyalty

Perfectionist, high-quality conscious

Pearson Correlation

1 .474** .397** .228** -.031 .178** .192** .319**

Sig. (2-tailed)

.000 .000 .000 .235 .000 .000 .000

N 1478 1477 1478 1478 1478 1475 1478 1478

Brand consciousness, “price equals quality”

Pearson Correlation

.474** 1 .470** .089** -.075** .157** .193** .324**

Sig. (2-tailed)

.000

.000 .001 .004 .000 .000 .000

N 1477 1477 1477 1477 1477 1474 1477 1477

Novelty and fashion conscious

Pearson Correlation

.397** .470** 1 .221** -.034 .168** .201** .290**

Sig. (2-tailed)

.000 .000

.000 .187 .000 .000 .000

N 1478 1477 1478 1478 1478 1475 1478 1478

Recreational and shopping conscious

Pearson Correlation

.228** .089** .221** 1 -.109** .049 .071** .066*

Sig. (2-tailed)

.000 .001 .000

.000 .058 .006 .011

N 1478 1477 1478 1478 1478 1475 1478 1478

Price conscious/value for the money consciousness

Pearson Correlation

-.031 -.075** -.034 -.109** 1 .151** .050 .068**

Sig. (2-tailed)

.235 .004 .187 .000

.000 .055 .009

N 1478 1477 1478 1478 1478 1475 1478 1478


Pearson Correlation

.178** .157** .168** .049 .151** 1 .414** .159**

Sig. (2-tailed)

.000 .000 .000 .058 .000

.000 .000

N 1475 1474 1475 1475 1475 1475 1475 1475


Pearson Correlation

.192** .193** .201** .071** .050 .414** 1 .217**

Sig. (2-tailed)

.000 .000 .000 .006 .055 .000

.000

N 1478 1477 1478 1478 1478 1475 1478 1478

Habitual/brand-loyal

Pearson Correlation

.319** .324** .290** .066* .068** .159** .217** 1

Sig. (2-tailed)

.000 .000 .000 .011 .009 .000 .000

N 1478 1477 1478 1478 1478 1475 1478 1478 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).


147

The above table indicates that there is a significant correlation at the

0.01level (2 tailed)among all the shopping styles and at the 0.05 level (2 tailed) for

the Recreational shopping conscious and Brand loyal shopping styles.

Perfectionist/ high-quality conscious shopping style is significantly

positively correlated at the 0.01 level with six other shopping styles - Brand

consciousness/price equals quality, Novelty and fashion conscious, Recreational and

shopping conscious, Impulsiveness/Careless, Confused by Overchoice, and

Habitual/brand-loyal. There is no significant correlation between the Perfectionist/

high-quality conscious shopping style and the Price conscious/value for the money

shopping style (p value >0.05).

Brand consciousness/price equals quality shopping style is significantly

positively correlated at the 0.01 level with all the other shopping styles -

Perfectionist/ high-quality conscious, Novelty and fashion conscious, Recreational

and shopping conscious, Impulsiveness/Careless, Confused by Overchoice, and

Habitual/brand-loyal shopping styles. There is a significant negative correlation

between the Brand consciousness/price equals quality shopping style and the Price

conscious/value for the money shopping style. This indicates that young adults are

willing to purchase good quality apparels by paying a high price for it. And that they

are more brand and quality conscious rather than being price conscious.

The Novelty and fashion conscious shopping style has a significant positive

correlation at the 0.01 level with all other shopping styles except the Price

conscious/value for the money shopping style. There is no significant correlation

between the Novelty and fashion conscious shopping style and the Price

conscious/value for the money shopping style (p value >0.05).

Recreational and shopping conscious shopping style has a significant

positive correlation at the 0.01 level with all the other shopping styles except the

Impulsiveness/Careless shopping style. There is a significant negative correlation

between the Recreational and shopping conscious shopping style and the Price

conscious/value for the money shopping style. This indicates that young adults who

consider shopping for apparels as a recreational activity are not worried about

148

spending money on apparel purchases. There is no significant correlation between

the Recreational and shopping conscious shopping style and the

Impulsiveness/Careless shopping style shopping style (p value >0.05).

Price conscious/value for the money shopping style has a significant positive

correlation at the 0.01 level with the Impulsiveness/Careless, and Habitual/brand-

loyal shopping styles. There is a significant negative correlation between the Price

conscious/value for the money shopping style and the Brand consciousness/price

equals quality and the Recreational and shopping conscious shopping styles as

indicated above. There is no significant correlation between the Price

conscious/value for the money shopping style and Perfectionist/ high-quality

conscious (p value >0.05), the Novelty and fashion conscious style (p value >0.05)

and Confused by Overchoice (p value> 0.05).

Impulsiveness/Careless shopping style has a significant positive correlation

at the 0.01 level with all the other shopping styles except the Recreational and

shopping conscious shopping style (p value >0.05).

Confused by Overchoice shopping style has a significant correlation at the

0.01 level with all the other shopping styles except the Price conscious/value for the

money shopping style (p value >0.05).

Habitual/brand-loyal shopping style has a significant correlation at the 0.01

levels with all the other shopping styles except Recreational and shopping conscious

shopping style. It is significantly correlated at the 0.05 level with the Recreational

and shopping conscious shopping style (p value <0.05).

INTER-CORRELATIONS BETWEEN VARIABLES

Inter-correlations between Values and shopping styles are calculated using

Karl Pearson’s Co-efficient of Correlation to ascertain the relationships between the

variables of the study.

149

TABLE:29

Correlation between Values and Shopping Styles

Descriptive Statistics

Mean Std. Deviation N

Overall values 7.3655 1.34154 1477

Overall Shopping Styles 3.2443 .44871 1474


Correlations

Overall values Overall

shopping

Styles

Overall values

Pearson Correlation 1 .116**

Sig. (2-tailed) .000

N 1477 1473

Overall Shopping

Styles

Pearson Correlation .116** 1


N 1473 1474



There is a significant positive correlation at the 0.01 level (2 tailed) among

the values and the shopping styles (p value <0.001). Values indicate a strong

relationship to the shopping styles of young adults.

150

Relationship between Individual Values and Shopping Styles

Objective- 3: To examine the relationship between values and shopping styles

of young adults towards purchase of apparels.

The results of the above analysis indicate that values and shopping styles are

significantly correlated. Further analysis is carried out to identify the relationship of

individual values to the eight dimensions of the shopping style inventory.

The results of Karl Pearson’s Co-efficient of correlation presented in the

following tables reveal the significant relationships between individual values and

specific shopping style.

TABLE: 30 Relationship between the value Sense of Belonging and Shopping Styles

Shopping Styles Sense of Belonging Remark


Pearson Correlation .109** **. Correlation is significant at the 0.01 level (2-tailed) Sig. (2-tailed) .000

N 1478

Brand Consciousness /Price Equals Quality

Pearson Correlation -.013 Sig. (2-tailed) .628 N 1477




Pearson Correlation .078** **. Correlation is significant at the 0.01 level (2-tailed) Sig. (2-tailed) .003

N 1478

Price Conscious/Value for the money

Pearson Correlation .036 Sig. (2-tailed) .167 N 1478

Impulsiveness/Careless Pearson Correlation -.001 Sig. (2-tailed) .960 N 1475

Confused by Overchoice Pearson Correlation .003 Sig. (2-tailed) .911 N 1478

Habitual/Brand Loyalty Pearson Correlation .032 Sig. (2-tailed) .221 N 1478


The above table indicates that there is a significant positive relationship at

the 0.01 level between the value ‘Sense of Belonging’ and the Perfectionist/High

Quality Conscious and Recreational and Shopping Conscious styles of young adults.

There were no significant relationships between the other shopping styles and Sense

of Belonging.

151

TABLE: 31 Relationship between the value Simplicity and Shopping Styles

Correlations Shopping Styles Simplicity Remark


Pearson Correlation .076** **. Correlation is significant at the 0.01

level (2-tailed).1 Sig. (2-tailed) .004 N 1478

Brand Consciousness/Price Equals Quality







Pearson Correlation .062* *. Correlation is significant at the 0.05

level (2-tailed). Sig. (2-tailed) .017 N 1478

Impulsiveness/Careless Pearson Correlation .020 Sig. (2-tailed) .446 N 1475


Habitual/Brand Loyalty Pearson Correlation .084** **. Correlation is

significant at the 0.01 level (2-tailed).

Sig. (2-tailed) .001 N 1478


The above table indicates that there is a significant positive relationship level

between the value ‘Simplicity’ and the Perfectionist/High Quality Conscious (p

value <0.01), Price Conscious/Value for the money (p value <0.05) and

Habitual/Brand Loyalty styles (p value <0.01) of young adults. There were no

significant relationships between the other shopping styles and Simplicity.

152

TABLE: 32

Relationship between the value Warm Relationships with Others and Shopping Styles

Correlations Shopping Styles Warm

Relationships with others

Remark


Pearson Correlation .131** **. Correlation is significant at the

0.01 level (2-tailed).


N 1478









N 1478





N 1478





The above table indicates that there is a significant positive relationship between the

value ‘Warm Relationships with others’ and the Perfectionist/High Quality

Conscious (p value <0.01), Recreational and Shopping Conscious (p value <0.01),

and Price Conscious/Value for the money shopping styles (p value <0.01) of young

adults. There were no significant relationships between the other shopping styles and

Warm Relationships with others.

153

TABLE:33

Relationship between the value Self-Fulfillment and Shopping Styles

Correlations Shopping Styles Self-

Fulfillment Remark












Pearson Correlation -.055* *. Correlation is significant at the



N 1475




The above table indicates that there is a significant negative relationship

between the value ‘Self-Fulfillment’ and the Impulsiveness/Careless shopping style

of young adults (Pearson’s correlation – 0.055 & p value<0.05). There were no

significant relationship between the other shopping styles and Self-Fulfillment.

Young adults who are self -satisfied and contented with their life do not need

any external motivations. They exhibit stable mindedness and are not impulsive

buyers.

154

TABLE:34

Relationship between the value Being Well Respected and Shopping Styles

Correlations Shopping Styles Being Well

Respected Remark





N 1477




Pearson Correlation .057* *. Correlation is significant at the



N 1477





N 1477





Habitual/Brand Loyalty




N 1477


The above table indicates that there is a significant positive relationship

between the value ‘Being Well Respected’ and the Perfectionist/High Quality

Conscious (p value <0.01), Novelty and Fashion Conscious (p value <0.05),

Recreational and Shopping Conscious (p value <0.01), and Habitual/Brand Loyalty

(p value<0.01) shopping styles of young adults. There were no significant

relationships between the other shopping styles and Being Well Respected.

155

TABLE:35 Relationship between the value Fun and Enjoyment of life and Shopping Styles

Correlations Shopping Styles Fun and

Enjoyment of life Remark




Sig. (2-tailed) .000 N 1478




Sig. (2-tailed) .002 N 1477




Sig. (2-tailed) .000 N 1478




Sig. (2-tailed) .005 N 1478




Confused by Overchoice Pearson Correlation .075** **. Correlation is

significant at the 0.01 level (2-

tailed).

Sig. (2-tailed) .004 N 1478

Habitual/Brand Loyalty Pearson Correlation .072** **. Correlation is

significant at the 0.01 level (2-

tailed).

Sig. (2-tailed) .006 N 1478



between the value ‘Fun and Enjoyment of life’ and the Perfectionist/High Quality

Conscious (p value <0.01), Brand Consciousness/Price Equals Quality (p value

<0.01), Novelty and Fashion Conscious (p value <0.01), Recreational and Shopping

Conscious (p value <0.01), Confused by Overchoice (p value <0.01) and

Habitual/Brand Loyalty (p value <0.01) shopping styles of young adults. There were

no significant relationships between the other shopping styles and Fun and

Enjoyment of life.

156

TABLE:36 Relationship between the value Security & Comfort and Shopping Styles

Correlations

Shopping Styles Security & Comfort

Remark




Sig. (2-tailed) .000 N 1478






Sig. (2-tailed) .038 N 1478




Sig. (2-tailed) .000 N 1478







Sig. (2-tailed) .008 N 1478




Sig. (2-tailed) .015 N 1478



between the value ‘Security & Comfort’ and the Perfectionist/High Quality

Conscious (p value <0.01), Novelty and Fashion Conscious (p value <0.05),

Recreational and Shopping Conscious (p value <0.01), Confused by Overchoice (p

value <0.01), and Habitual/Brand Loyalty (p value <0.05), shopping styles of young

adults. There were no significant relationships between the other shopping styles

and Security & Comfort.

157

TABLE:37 Relationship between the value Self Respect and Shopping Styles

Correlations

Shopping Styles Self Respect Remark





N 1478









N 1478



Impulsiveness/Careless Pearson Correlation -.027 Sig. (2-tailed) .295 N 1475






N 1478



value ‘Self Respect’ and the Perfectionist/High Quality Conscious (p value <0.01),

Recreational and Shopping Conscious (p value <0.01), and Habitual/Brand Loyalty

(p value <0.05) shopping styles of young adults. There were no significant

relationships between the other shopping styles and Self Respect.

158

TABLE:38 Relationship between the value Sense of Accomplishment and Shopping Styles

Correlations

Shopping Styles Sense of Accomplishment

Remark


Pearson Correlation .150** **. Correlation is significant at

the 0.01 level (2-tailed).


N 1478







N 1478







N 1478






N 1478




value ‘Sense of Accomplishment’ and the Perfectionist/High Quality Conscious

(p value <0.01), Novelty and Fashion Conscious (p value <0.01), Price

Conscious/Value for the money (p value 0.05), and Confused by Overchoice

(p value <0.05) shopping styles of young adults. There were no significant

relationships between the other shopping styles and Sense of Accomplishment.

159

TABLE:39 Relationship between the value Being Independent and Shopping Styles

Correlations

Shopping Styles Being Independent Remark





N 1478
















between the value ‘Being Independent’ and the Perfectionist/High Quality

Conscious shopping style (p value <0.011) of young adults. There were no

significant relationships between the other shopping styles and Being Independent.

160

STRUCTURAL EQUATION MODELING (SEM)

Structural Equation Modeling (SEM) is a multivariate statistical methodology,

which takes a confirmatory approach to the analysis of a structural theory. Structural

Equation Modeling is confirmatory process, since it commences with the

specification of a model. It is a Multivariate Analysis method based on fitting and

testing multiple regression equation as specified by the model. SEM is a set of

techniques which allows examination of relationships between one or multiple

independent variable and one or more dependent variables.190Though there are many

ways to describe SEM, it is most commonly thought of as a hybrid between some

form of Analysis of Variance (ANOVA)/Regression and some form of Factor

Analysis. In general, it can be remarked that SEM allows the researcher to perform

some type of multilevel Regression/ANOVA on factors. Structural Equation

Modeling combines two approaches: the predictive approach of econometrics,

coupled with the psychometric approach of inferring latent variables from multiple

observed variables. It essentially seeks to answer research questions by combining

multiple regression analysis of factors with exploratory factor analysis. A researcher

proposes a hypothesized series of relationships between the variables under

investigation (the model) and structural equation modeling enables the

reasonableness of t relationships implied by the model to be assessed. In the present

study structural equation modeling was used to test the Value – Shopping Style

Model (Measurement). The first part of structural equation modeling is confirmatory

factor analysis which measures the measurement model if it confirms to the original

model.

CONFIRMATORY FACTOR ANALYSIS (CFA)

Confirmatory Factor Analysis (CFA) which is a part of the Structural

Equation Modeling (SEM) techniques can be used to estimate a measurement model

that specifies the relationship between observed indicators and their underlying

latent constructs. The measurement model specifies how latent constructs are

190Tabachnick, Linda S. Fidell. (2001). Using Multivariate Statistics (6th Edition). Amazon.com

161

measured by the observed variables. CFA is often used to confirm a factor structure

known beforehand as is the case with the constructs in the study.

In statistics, CFA is a special form of factor analysis. It is used to test

whether measures of a construct are consistent with a researcher’s understanding of

the nature of that construct (factor). In contrast to exploratory factor analysis, where

all loadings are free to vary, CFA allows for the explicit constraint of certain

loadings to be zero. CFA assesses the fit of the model. Model fit measures could be

then obtained to assess how well the proposed model captured the covariance

between all the items on the test. If the fit is poor, it may be due to some items

measuring multiple factors. It might also be that some items within a factor are more

related to each other than others.

GOODNESS OF FIT MEASURES (GFM)

“Goodness of fit measures” was used to test the appropriateness of the

structural model using the Amos 16.0 software. The overall fit of a model in

structural equation modeling can be assessed using a number of fit indices. There is

a broad consensus that no single measure of overall fit should be relied on

exclusively and a variety of different indices should be consulted.191 There are

several indicators of Goodness-of-fit and most structural equation modeling scholars

recommend evaluating the models by observing more than one of these indicators.

Dozens of statistics, besides the value of the discrepancy function at its minimum,

have been proposed as measures of the merit of a mode. The choice of Goodness-of-

fit indexes should be based on careful consideration of critical factors like sample

size, estimation procedure, model complexity and/or violation of the underlying

assumptions of multivariate normality and variable independence.192The criteria for

ideal fit indices are relative independence of sample size, accuracy and consistency

to assess different models and ease of interpretation aided by a well-defined pre-set

191Tanaka, 1993. Tanaka, J.S. (1993). Multifaceted conceptions of fit in structural equation models. In

K.A. Bollen, & J.S. Long (eds.), Testing structural equation models. Newbury Park, CA: Sage 192Hu &Bentler (1999). Cutoff criteria for fit indexes in covariance structure analysis: Coventional

criteria versus new alternatives, Structural Equation Modeling, 6(1), 1-55.

162

range.193 The entire set of fit give a good sense of how the model fits the sample

data.

The overall fit of the proposed research model was significant as all measures

of fitness were at acceptable levels indicating the model fits the data well. Model fit

summary is presented in this section. The rule of thumb (to check the model fitness)

was referred from AMOS 16.0 User’s Guide.194

Confirmation of the dimensions of shopping styles among young adults with the

original Sproles& Kendall CSI (1986)

TABLE:40

Summary of Goodness-of-fit measures for the ‘Consumer Style Inventory’ used in the study

Model Fit Assessment Result

2 (chi-square) [CMIN] 1294.180

DF (Degrees of freedom) 224

p-value <.001

PGFI (Parsimony Goodness of Fit Index) .654

NFI (Normed Fit Index) .855

RFI (Relative Fit Index) .806

IFI (Incremental Fit Index) .877

TLI (Tucker-Lewis Coefficient) .834

CFI (Comparative Fit Index) .876

PRATIO (Parsimony Ratio) .747

NCP (Non centrality Parameter) 1070.180

RMSEA(Root Mean Square Error of Approximation) .057


193Marsh, H.W., Hau, K-T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis-

testing approaches to setting cutoff values for fit indexes and dangers of overgeneralizing Hu and Bentler’s (1999) findings. Structural Equation Modeling, 11, 320-341 pp.

194James L. Arbuckle. Amos ™ 16 User’s Guide. (2007)

163

Based on AMOS 16.0 User’s Guide, the measures- of -fit statistics given in

Table No. 37indicate an acceptable and adequate overall level of fit for the entire

sample.A detailed interpretation of each of the Goodness of Fit measures indicated

in the above table is given in the following tables.

TABLE:41

Relative Chi Square (CMIN/df) (Chi-square/Degrees of freedom)

Model NPAR CMIN DF P CMIN/DF

Default model 100 1294.180 224 .000 5.778

Saturated model 324 .000 0

Independence model 24 8943.902 300 .000 29.813


CMIN (X2) value is 0.1294.180, Degrees of freedom (df) is 224 and p value

is <.001 which means that the sample fits adequately to the hypothesized network of

relationships in the model. CMIN is the minimum value of the discrepancy C. DF is

the number of degrees of freedom for testing the model df = d = p – q where p is the

number of sample moments and q is the number of distinct parameters. P is the

probability of getting as large a discrepancy as occurred with the present sample

(under appropriate distributional assumptions and assuming a correctly specified

model). That is, P is a “p value” for testing the hypothesis that the model fits

perfectly in the population.

CMIN/DF is the minimum discrepancy divided by its degrees of freedom.

CMIN/DF is 5.77. Several writers have suggested the use of this ratio as a measure

of fit. Marsh and Hocevar195have recommended using ratios as low as 2 or as high as

5 to indicate a reasonable fit. The value reported as X2 is the minimum value of the

fitting function, and it is large compared to its df. X2 is quite sensitive to sample

size, and rejects for smaller and smaller discrepancies as the sample gets bigger. X2

195Marsh, Herbert W.; Hocevar, Dennis. (May 1985). Application of confirmatory factor analysis to

the study of self-concept: First- and higher order factor models and their invariance across groups. Psychological Bulletin, Vol 97(3), May 1985, 562-582. doi: 10.1037/0033-2909.97.3.562.

164

is probably less useful as an indicator than other model fit measures for this model

based on samples as large as this. Whenever the sample used is higher than 200, the

X2 test is not indicative of good or bad adjustment of the model to the data, since the

value of X 2 increase with the increase in sample size.196 This way, whenever the

sample is above 200, this test tends to reject all models, even when these present a

good adjustment. On the contrary, whenever the sample’s dimension is lower than

100, the test will tend to accept all models, even those that do not present an

adequate adjustment.

Comparisons to a Baseline Model

This set of goodness of fit measure compares the researcher’s model to the

fit of another model, usually the independence model. The independence model is

used as the baseline model in AMOS. The object of the exercise is to put the fit of

the proposed model into some perspective. Baseline comparison measures are

described below. The measures included are: Comparative fit index (CFI), Normed

fit index (NFI), Relative fit index (RFI), Incremental fit index (IFI), Tucker-Lewis

Index (TLI).

TABLE:42

Baseline Model

Model NFI Delta1

RFI rho1

IFI Delta2

TLI rho2 CFI

Default model .855 .806 .877 .834 .876

Saturated model 1.000

1.000

1.000

Independence model .000 .000 .000 .000 .000


196 Hair, J.F. Jr. , Anderson, R.E., Tatham, R.L., & Black, W.C. (1998). Multivariate Data Analysis, (5th Edition). Upper Saddle River, NJ: Prentice Hall.

165

Comparative fit index (CFI)

CFI (Comparative fit index) is 0.876 indicating a very good fit. Rule of

thumb: CFI values close to 1 indicate a very good fit.

Normed Fit Index (NFI)

Normed fit index (NFI) of the research model is 0.855 indicating good fit. As

per rule of thumb, models with overall fit indices of less than 0.9 can usually be

improved substantially.

Relative Fit Index (RFI)

Relative fit index (RFI) is 0.806 indicating again a very good fit. Rule of

thumb: RFI values close to 1 indicate a very good fit.

Incremental Fit Index (IFI)

Incremental fit index (IFI) is 0.877 indicating good fit. Rule of thumb: IFI

values close to 1 indicate a very good fit.

Tucker-Lewis Index (TLI)

TLI value is 0.834 which shows the proposed model has a very good fit. The

Tucker-Lewis197 coefficient was discussed by Bentler and Bonett, in the context of

analysis of moment structures and is also known as the Bentler-Bonett non-normed

fit index (NNFI).198 The typical range for TLI lies between 0 and 1, but it is not

limited to that range. TLI values close to 1 indicate a very good fit.

Parsimony Adjusted Measures

Parsimony adjusted measures are goodness-of-fit tests penalizing for lack of

parsimony. Parsimony measures lack of parsimony on the rationale that more

complex models will, all other things being equal, generate better fit than less

197L.R. Tucker and C. Lewis.(1973). A reliability coefficient for maximum likelihood factor

analysis.Psychometrika, pages 1–10, 1973. 198P.M. Bentler. (1990). Comparative fit indexes in structural models. Psychological Bulletin, pages

238–246 pp.

166

complex ones. Models with relatively few parameters (and relatively many degrees

of freedom) are sometimes said to be high in parsimony, or simplicity. Models with

many parameters (and few degrees of freedom) are said to be complex, or lacking in

parsimony. This use of the terms simplicity and complexity does not always

conform to everyday usage. While one can inquire into the grounds for preferring

simple, parsimonious models, there does not appear to be any disagreement that

parsimonious models are preferable to complex ones. Various parsimonious adjusted

measures considered here are: Parsimony Ratio (PRATIO), Parsimony Goodness-of-

Fit Index (PGFI).

TABLE:43

Parsimony-Adjusted Measures

Model PRATIO PNFI PCFI

Default model .747 .639 .654

Saturated model .000 .000 .000

Independence model 1.000 .000 .000


Parsimony Ratio (PRATIO)

PRATIO value is 0.747 which indicates that 74.7% of the number of

constraints in the independence model is being evaluated in the tested model. The

parsimony ratio expresses the number of constraints in the model being evaluated as

a fraction of the number of constraints in the independence model where d is the

degrees of freedom of the model being evaluated and is the degrees of freedom of

the independence model. The parsimony ratio is used in the calculation of PNFI and

PCFI.

Parsimony Goodness-of-Fit Index (PGFI)

The parsimony goodness of fit index is a variant of GFI. By arbitrary

convention, PGFI >.60 indicates good parsimonious fit, though some authors use the

167

more lenient >.50 criterion. The PGFI for the model is 0.654. A PGFI value that

exceeds 0.5 would indicate the model employed is a perfect fit to the data in the

study.The PGFI is a modification of the GFI that takes into account the degrees of

freedom available for testing the model.

TABLE:44

Root Mean Square Error of Approximation (RMSEA)

Model RMSEA LO 90

HI 90 PCLOSE

Default model .057 .054 .060 .000

Independence model .140 .137 .142 .000


RMSEA (root mean square error of approximation) value of .057 indicates

adequate fit. RMSEA is a popular measure of fit, partly because it does not require

comparison with a null model and does not require the author position as a plausible

model in which there is complete independence of the latent variables. It is one of

the fit indexes less affected by sample size. RMSEA has only recently been

recognized as one of the most informative criteria in covariance structure modelling.

The RMSEA takes into account the error of approximation in the population and

asks the question, “How well would the model, with unknown but optimally chosen

parameter values, fit the population covariance matrix if it were available?”. This

discrepancy, as measured by the RMSEA, is expressed per degree of freedom, thus

making the index sensitive to the number of estimated parameters in the model (i.e.,

the complexity of the model); values less than .05 indicate good fit, and values as

high as .08 represent reasonable errors of approximation in the population. RMSEA

values ranging from .08 to .10 indicate mediocre fit and those greater than 0.10

indicate poor fit.

The results of confirmatory factor analysis and goodness of fit test under the

Structural Equation Modeling Technique indicated in Table No. 37 show that the

values of NFI, CFI, RFI, IFI, TLI and RMSEA are values close to 1, within

168

acceptable ranges and shows that the proposed model indicates a good fit to the data.

It is concluded that the dimensions of shopping styles among young adults in

Bangalore city, confirms with the original Sproles & Kendall Consumer Styles

Inventory CSI (1986).

VALIDITY MEASURES

The confirmatory factor analysis has been executed to test the validity of the

instruments through content validity, convergent validity, discriminant validity and

criterion related validity. Content validity refers to the degree which an instrument

covers the meaning of the concepts included in a particular research. For this study,

the content validity of the proposed instrument is adequate enough because the

instrument has been carefully constructed, validated and supported by an extensive

literature review.

TABLE:45

Factors, standardized factor loading, AVE, CR and Coefficient Alpha for Shopping Styles

Shopping Styles Average Variance

Explained (Convergent Validity)

Construct Validity

Perfectionist/High Quality Conscious .55 .78

Confused by Overchoice .33 .50

Recreational and Shopping Conscious .60 .82

Impulsiveness/Careless .58 .80

Price Conscious/Value for money .56 .79

Habitual/Brand Loyal .42 .69

Novelty and Fashion Conscious .63 .83

Brand Conscious/Price Equals Quality .52 .77


169

Construct validity: Construct validity is the extent to which a set of

measured variables actually represent the theoretical latent construct they are

designed to measure. It is made up of four components: Convergent Validity,

Discriminant Validity, Nomological Validity and Face validity. To assess the

construct validity of the scale, exploratory and confirmatory factor analytic

procedures were applied.

Convergent validity: Convergent validity is the extent to which indicators

of a specific construct ‘converge’ or share a high proportion of variance in common.

Convergent validity identifies the proportion of variance for each factor. To assess

this, standardized factor loadings in the measurement model were examined,

composite or construct reliability (CR) and average variance extracted (AVE) was

computed.

Construct reliability: Is a measure of reliability and internal consistency

based on the square of the total of factor loadings for a construct.

Construct Reliability (CR) = {(sum of standardized loadings)2} / {(sum of

standardized loadings)2 + (sum of indicator measurement errors)}

CR values should be greater than 0.6 while AVE should be above 0.5. The

construct reliability estimates of the scale exceeded 0.6, indicating fair construct

reliability.

Discriminant Validity: The discriminant validity examines the extent to

which an independent variable is truly distinct from other independent variables in

predicting the dependent variable. It is the extent to which a construct is truly

distinct from other constructs. To substantiate the evidence of discriminant validity,

the values of average variance extracted (AVE) between dimensions were compared

to squared multiple correlations of the two.199 If within each possible pairs of

constructs, the shared variance observed is lower than the minimum of their AVEs,

then discriminant validity is evidenced.200 If all variance extracted (AVE) estimates

199Hair, J., Black, W., Babin, B., Anderson, R., and Tatham, R. (2006). Multivariate Data Analysis,

6th ed. Pearson Prentice Hall, Upper Saddle River, New Jersey 200Fornell&Larcker. (1981). Evaluating structural equation models with unobservable variables and

Measurement error.Journal of Marketing Research. 48: 39-50pp

170

are larger than the corresponding squared inter-construct correlation estimates (SIC)

then, the construct is said to have discriminant validity.

The convergent validity for the CSI scale was analysed and the values of the

standardized loading, AVE, CR and Coefficient Alpha are given in the above Table

42. The values support the internal consistency of the data.

MODEL TESTING

In this study a ‘Value Shopping Style Model’ (VSM) is proposed and tested

to investigate the primary research question, ‘Do values influence the Shopping

styles of young adults for apparel purchases’? Structural Equation Modeling output

results for the proposed model are presented in this section.

Objective 4 -To develop a ‘Value-Shopping Style Model’ and analyze the

influence of values on the shopping styles of young adults towards purchase of

apparels.

TABLE:46

Summary of Goodness-of-fit measures for the ‘Value – Shopping Style’ measurement model - (VSM)

Model Fit Assessment Result 2(chi-square) 3712.878

DF(Degrees of freedom) 519 p-value <.001 PGFI (Parsimony Goodness of Fit Index) 0.655 NFI (Normed Fit Index) 0.723 RFI (Relative Fit Index) 0.683 IFI (Incremental Fit Index) 0.753 TLI (Tucker-Lewis Coefficient) 0.715 CFI (Comparative Fit Index) 0.751 PRATIO (Parsimony Ratio) 0.872 NCP (Non centrality Parameter) 3193.878 RMSEA(Root Mean Square Error of Approximation) 0.065


171

A detailed interpretation of each of the Goodness of Fit measures indicated

in the above table is given in the following tables.

TABLE:47

Relative Chi Square (CMIN/df) (Chi-square/Degrees of freedom) (VSM)

Model NPAR CMIN DF P CMIN/DF

Default model 110 3712.878 519 .000 7.154

Saturated model 629 .000 0

Independence model 34 13427.685 595 .000 22.568


CMIN (X 2) value is 3712.878, Degrees of freedom (df) is 519 and p value is

<.001 which means that the sample fits adequately to the hypothesized network of

relationships in the model.

TABLE:48

Baseline Comparisons - (VSM)

Model NFI Delta1

RFI rho1

IFI Delta2

TLI rho2 CFI

Default model .723 .683 .753 .715 .751

Saturated model 1.000

1.000

1.000

Independence model .000 .000 .000 .000 .000


CFI (Comparative fit index) is 0.751 indicating a very good fit. Rule of

thumb: CFI values close to 1 indicate a very good fit. Normed fit index (NFI) of the

research model is 0.723, indicating a good fit. As per rule of thumb, models with

overall fit indices of less than 0.9 can usually be improved substantially. Relative fit

172

index (RFI) is 0.683 indicating again a very good fit. Rule of thumb: RFI values

close to 1 indicate a very good fit. Incremental fit index (IFI) is 0.753 indicating

good fit. Rule of thumb: IFI values close to 1 indicate a very good fit.TLI value is

0.715 which shows the proposed model has a very good fit. The typical range for

TLI lies between 0 and 1, but it is not limited to that range. TLI values close to 1

indicate a very good fit.

TABLE:49

Parsimony-Adjusted Measures - (VSM)

Model PRATIO PNFI PGFI

Default model .872 .631 .655

Saturated model .000 .000 .000

Independence model 1.000 .000 .000


PRATIO value is 0.872 which indicates that 87.2% of the number of

constraints in the independence model is being evaluated in the tested model. PGFI

>0.60 indicates good parsimonious fit, though some authors use the more lenient

>0.50 criterion. The Parsimony goodness-of-fit index is 0.655. This indicates that

the model employed is a perfect fit to the data in the study.

TABLE:50

Root Mean Square Error of Approximation (RMSEA) - (VSM)

Model RMSEA LO 90 HI 90 PCLOSE

Default model .065 .063 .067 .000



173

RMSEA value of 0.065 indicates reasonable fit. Rule of thumb: RMSEA

values less than 0.05 indicate good fit, and values as high as .08 represent reasonable

fit and RMSEA values ranging from 0.08 to 0.10 indicate mediocre fit and those

greater than 0.10 indicate poor fit.

To summarize the results, the values of NFI, CFI, RFI, IFI, and TLI are

values close to 1 and indicate a very good fit and the Root Mean Square Error of

approximation (RMSEA) value .065 is a reasonable fit. The results of Goodness of

Fit tests under the Structural Equation Modeling Technique indicate that the

proposed ‘Value – Shopping Style Model’ - (VSM) fits the data well.

Path Analysis and SEM are extensions of multiple regression, they rely very

heavily on pictures called path diagrams to visualize what’s going on. All of the

variables are represented by rectangles, and each path is represented by a straight

line with an arrow head at one end. The predictor variables are joined by curved

lines with arrow heads at both ends. The straight arrows are the paths, and the

curved ones represent the correlations among the variables. The circle with an

arrow pointing to the dependent variable is the error term, called the disturbance

term in PA and SEM and which is a part of every regression equation (and by

extension, part of every PA and SEM diagram).

174

FIG.7

PATH DIAGRAM INDICATING THE VALUE – SHOPPING STYLE MODEL FIT

As the measurement model proved to be a good fit, the researcher found

scope for testing the Structural Equation Model further using the Path Analysis. The

summary of the results are presented in the following sections.


S3e111 S2e2

1 S1e31


S6e411 S5e5

1 S4e61


S9e711 S8e8

1 S7e91


S12 e101 1 S11 e11

1 S10 e121


S15e1311 S14e14

1 S13e151


S18 e16 11 S17 e17

1 S16 e18 1

Confused by OverchoiceS19 e191 1

S20 e201

S21 e21 1

Habitual/Brand Loyal lS22 e221

1

S23 e231

S24 e241

values

V1 e25

1

1

V2 e261

V3 e271

V4 e281

V5 e291

V6 e301

V7 e311

V8 e321

V9 e331

V10 e341

e41 1

175

ANALYSIS OF INFLUENCE OF VALUES ON THE SHOPPING STYLES

The principal objective of this research work is to study the influence of

personal values on the young adults shopping styles for apparels in Bangalore City.

Path Analysis (Multiple Regression) was performed on the data, the results are

presented in the following tables.

Path analysis is an extension of Multiple Regression analysis that allows the

researcher to look at more than one dependent variable at a time and allows for

variables to be dependent with respect to some variables and independent with

respect to others. Structural equation modeling extends path analysis by looking at

latent variables.

H1 – There is no significant influence of values on the various shopping

styles of young adults towards purchase of apparels.

TABLE:51

Influence of overall values on the shopping styles of young adults towards apparels

CSI Scale Items

LOV Estimate S.E. C.R. P

Perfectionist/High Quality Conscious <--- values .209 .027 7.878 .000

Habitual/Brand Loyal <--- values .101 .026 3.810 .000

Confused by Overchoice <--- values .121 .033 3.690 .000

Brand Conscious/Price Equals Quality <--- values .072 .022 3.213 .001

Novelty and Fashion Conscious <--- values .148 .029 5.116 .000

Recreational and Shopping Conscious <--- values .128 .033 3.823 .000

Price Conscious/Value for money <--- values .006 .010 .594 .552

Impulsiveness/Careless <--- values .056 .025 2.224 .026 Source: Primary data

176

It was found that there is a significant influence of overall values on the

shopping styles of youth. The highest influence of values was on the

Perfectionist/High Quality Conscious style (P value <.001) followed by Novelty and

Fashion Conscious, Recreational and Shopping Conscious, Confused by

Overchoice, Habitual/Brand Loyal, Brand Conscious/Price Equals Quality and

Impulsiveness/Careless styles. There was no significant influence of values on the

Price Conscious/Value for money style. The table indicates that young adults in

Bangalore are not price conscious when it comes to apparel purchases.

As the above table indicates that values influence all the shopping styles

except the price conscious/value for money style, we reject the null hypothesis and

accept the alternate hypothesis ‘There is significant influence of overall values

on the shopping styles of young adults towards apparel purchases’.

177

Analyzing the Influence of values on the various dimensions of the

shopping style inventory:

H2 – There is no significant influence of values on the various dimensions of

the shopping styles of young adults towards purchase of apparels.

TABLE:52

Influence of values on the ‘Perfectionist/High Quality Conscious’ shopping style

Shopping Style Values Estimate S.E. C.R. P Perfectionist/High Quality Conscious <--- Sense of Belonging .025 .011 2.249 .025

Perfectionist/High Quality Conscious <--- Simplicity -.012 .011 -1.116 .264

Perfectionist/High Quality Conscious <--- Warm Relationships

With Others .035 .011 3.033 .002

Perfectionist/High Quality Conscious <--- Self-Fulfillment -.031 .011 -2.801 .005

Perfectionist/High Quality Conscious <--- Being Well Respected .029 .012 2.471 .013

Perfectionist/High Quality Conscious <--- Fun And Enjoyment of

Life .056 .011 5.105 .000

Perfectionist/High Quality Conscious <--- Security & Comfort .010 .012 .839 .402

Perfectionist/High Quality Conscious <--- Self-Respect .002 .012 .181 .856

Perfectionist/High Quality Conscious <--- A Sense of

Accomplishment .053 .011 4.640 .000

Perfectionist/High Quality Conscious <--- Being Independent -.011 .010 -1.065 .287 Source: Primary data

It was found that there was a significant influence of values, ‘Fun and

Enjoyment of life’ (p value <0.01), ‘A sense of accomplishment’ (p value <0.01),

‘Warm relationships with others’ (p value <0.01),‘Being well respected’ (p value

<0.05), and ‘Sense of belonging’ (p value <0.05), on the Perfectionist/High Quality

Conscious dimension of the shopping styles. Self-fulfillment had a negative

influence (p value <0.01). However, the values Simplicity, Security & Comfort,

Self-respect and Being independent did not have a significant influence on the

Perfectionist/High Quality Conscious shopping style.

178

TABLE:53

Influence of values on the ‘Brand Conscious/Price Equals Quality’ shopping style

Shopping Style

Values Estimate S.E. C.R. P

Brand Conscious/Price Equals Quality <--- Sense Of Belonging -.008 .010 -.746 .455

Brand Conscious/Price Equals Quality <--- Simplicity .007 .010 .661 .509

Brand Conscious/Price Equals Quality <--- Warm Relationships

With Others -.005 .010 -.512 .609

Brand Conscious/Price Equals Quality <--- Self-Fulfillment -.029 .010 -2.800 .005

Brand Conscious/Price Equals Quality <--- Being Well-

Respected .026 .011 2.355 .019

Brand Conscious/Price Equals Quality <--- Fun And Enjoyment

Of Life .052 .010 5.010 .000

Brand Conscious/Price Equals Quality <--- Security & Comfort .000 .011 .030 .976

Brand Conscious/Price Equals Quality <--- Self-Respect -.039 .011 -3.417 .000

Brand Conscious/Price Equals Quality <--- A Sense Of


Brand Conscious/Price Equals Quality <--- Being Independent .006 .009 .598 .550


It was found that there is a significant positive influence of the values Fun

and Enjoyment of Life(p value <0.01), and Being well respected(p value <0.05), on

the ‘Brand Conscious/Price Equals Quality’ dimension of the shopping style

inventory. Self-fulfillment (p value <0.01), and Self respect(p value <0.01), had

negative influence on ‘Brand Conscious/Price Equals Quality’ shopping style.

However, the values Sense of belonging, Simplicity, Warm Relationships, Security

& Comfort, A Sense of Accomplishment and Being independent did not have a

significant influence on the ‘Brand Conscious/Price Equals Quality’ shopping style.

179

TABLE:54 Influence of values on the ‘Novelty and Fashion Conscious’ shopping style

Shopping Style


Novelty and Fashion Conscious <--- Sense Of

Belonging -.026 .013 -1.942 .052

Novelty and Fashion Conscious <--- Simplicity -.023 .013 -1.818 .069

Novelty and Fashion Conscious <---

Warm Relationships With Others

-.017 .014 -1.265 .206

Novelty and Fashion Conscious <--- Self-Fulfillment -.006 .013 -.459 .646

Novelty and Fashion Conscious <--- Being Well-

Respected .032 .014 2.294 .022

Novelty and Fashion Conscious <--- Fun And

Enjoyment Of Life .065 .013 5.027 .000

Novelty and Fashion Conscious <--- Security &

Comfort .024 .014 1.761 .078

Novelty and Fashion Conscious <--- Self-Respect -.006 .014 -.449 .654

Novelty and Fashion Conscious <--- A Sense Of


Novelty and Fashion Conscious <--- Being Independent .004 .012 .363 .717


It was found that there is a significant influence of the values Fun and

enjoyment of life (p value <0.01), and Being Well-respected (p value <0.05), on the

‘Novelty and Fashion Conscious’ dimension of shopping style inventory. All the

other values did not have a significant influence on this dimension of shopping style

inventory.

180

TABLE:55

Influence of values on the ‘Recreational and Shopping Conscious’ shopping style

Shopping Style


Recreational and Shopping Conscious’ <--- Sense Of

Belonging .007 .015 .462 .644

Recreational and Shopping Conscious’ <--- Being Well-

Respected .028 .016 1.717 .086

Recreational and Shopping Conscious’ <--- A Sense Of

Accomplishment -.001 .016 -.087 .931

Recreational and Shopping Conscious’ <--- Simplicity -.020 .015 -1.371 .170

Recreational and Shopping Conscious’ <--- Fun And

Enjoyment Of Life .000 .015 .032 .975

Recreational and Shopping Conscious’ <--- Being Independent -.028 .014 -2.030 .042

Recreational and Shopping Conscious’ <--- Security &

Comfort .058 .016 3.552 .000

Recreational and Shopping Conscious’ <---


.031 .016 1.985 .047

Recreational and Shopping Conscious’ <--- Self-Fulfillment .004 .015 .290 .772

Recreational and Shopping Conscious’ <--- Self-Respect .002 .017 .099 .921 Source: Primary data

It was found that there is a significant positive influence of the values

Security and Comfort (p value <0.01), and Warm Relationships with others (p value

<0.05), on the ‘Recreational and Shopping Conscious’ dimension of shopping style

inventory. Being Independent (p value <0.05), had a negative influence, on the

‘Recreational and Shopping Conscious’ dimension of shopping style inventory. All

the other values did not have a significant influence on this dimension of shopping

style inventory.

181

TABLE:56

Influence of values on the ‘Price Conscious/Value for money’ shopping style

Shopping Style


Price Conscious/Value for money <--- Sense Of Belonging .003 .006 .505 .613

Price Conscious/Value for money <--- Simplicity -.003 .005 -.528 .598

Price Conscious/Value for money <--- Warm Relationships

With Others .026 .008 3.364 .000

Price Conscious/Value for money <--- Self-Fulfillment .002 .006 .304 .761

Price Conscious/Value for money <--- Being Well-

Respected -.026 .008 -3.334 .000

Price Conscious/Value for money <--- Fun And Enjoyment

Of Life -.015 .006 -2.393 .017

Price Conscious/Value for money <--- Security & Comfort .002 .006 .262 .794

Price Conscious/Value for money <--- Self-Respect .003 .006 .524 .600

Price Conscious/Value for money <--- A Sense Of


Price Conscious/Value for money <--- Being Independent .002 .005 .337 .736


It was found that there is a significant positive influence of the values Warm

Relationships with others (p value <0.01), and A sense of accomplishment (p value

<0.05), and a significant negative influence of the values Being Well-respected

(p value <0.01), and Fun and enjoyment of life (p value <0.05), on the ‘Price

Conscious/Value for money’ dimension of shopping style inventory. All the other

values did not have a significant influence on this dimension of shopping style

inventory.

182

TABLE:57 Indicating influence of values on the ‘Impulsiveness/Careless’ shopping style

Shopping Style


Impulsiveness/Careless <--- Sense Of Belonging -.002 .012 -.148 .882

Impulsiveness/Careless <--- Simplicity .013 .012 1.126 .260

Impulsiveness/Careless <---


.035 .013 2.697 .007

Impulsiveness/Careless <--- Self-Fulfillment -.041 .012 -3.258 .001

Impulsiveness/Careless <--- Being Well-Respected -.010 .013 -.784 .433


Fun And Enjoyment Of Life

.010 .012 .829 .407

Impulsiveness/Careless <--- Security & Comfort .011 .013 .883 .377

Impulsiveness/Careless <--- Self-Respect -.012 .013 -.923 .356


A Sense Of Accomplishment

.016 .012 1.299 .194

Impulsiveness/Careless <--- Being Independent .007 .011 .611 .541


It was found that there is a significant positive influence of the value Warm

Relationships (p value <0.01), with others and significant negative influence of the

value Self-fulfillment (p value <0.01), on the ‘Impulsiveness/Careless’ dimension of

the shopping inventory. All the other values did not have a significant influence on

this dimension of shopping style inventory.

183

TABLE:58

Influence of values on the ‘Confused by Overchoice’ shopping style

Shopping Style


Confused by Overchoice <--- Sense Of Belonging -.025 .015 -1.597 .110

Confused by Overchoice <--- Simplicity .024 .015 1.608 .108

Confused by Overchoice <---

Warm Relationships

With Others .022 .016 1.378 .168

Confused by Overchoice <--- Self-Fulfillment -.021 .015 -1.423 .155

Confused by Overchoice <--- Being Well-Respected .008 .016 .503 .615


Fun And Enjoyment of

Life .038 .015 2.562 .010

Confused by Overchoice <--- Security & Comfort .041 .016 2.539 .011

Confused by Overchoice <--- Self-Respect -.030 .017 -1.801 .072


A Sense of


Confused by Overchoice <--- Being Independent -.018 .014 -1.334 .182


It was found that there is a significant influence of the values Fun and

enjoyment of life (p value <0.01), Security & Comfort (p value <0.05), and A sense

of accomplishment (p value <0.05), on the ‘Confused by Overchoice’ dimension of

shopping styles inventory. All the other values did not have a significant influence

on this dimension of shopping style inventory.

184

TABLE:59

Influence of values on the ‘Habitual/Brand Loyal’ shopping style

Shopping Style


Habitual/Brand Loyal <--- Sense Of Belonging -.005 .012 -.393 .694

Habitual/Brand Loyal <--- Simplicity .032 .012 2.691 .007

Habitual/Brand Loyal <---


-.016 .012 -1.270 .204

Habitual/Brand Loyal <--- Self-Fulfillment -.022 .012 -1.841 .066

Habitual/Brand Loyal <--- Being Well-Respected .018 .013 1.380 .168

Habitual/Brand Loyal <--- Fun And Enjoyment of Life .017 .012 1.494 .135

Habitual/Brand Loyal <--- Security & Comfort .009 .013 .705 .481

Habitual/Brand Loyal <--- Self-Respect .022 .013 1.663 .096

Habitual/Brand Loyal <--- A Sense of Accomplishment .001 .012 .120 .904

Habitual/Brand Loyal <--- Being Independent -.002 .011 -.161 .872 Source: Primary data

It was found that there is a significant influence of the value Simplicity (p

value <0.01), on the ‘Habitual/Brand Loyal’ dimension of shopping style. The other

values did not have a significant influence on ‘Habitual/Brand Loyal’ style.

The above Tables 48 to 56 indicate that values influence all the dimensions

of the shopping styles inventory. Hence we reject the null hypothesis and accept

the alternate hypothesis ‘There is significant influence of values on the various

dimensions of the shopping styles of young adults towards purchase of

apparels’.

185

TABLE:60

Squared multiple correlations (R squared values) for Shopping Styles

Shopping Style Estimate

Confused by Overchoice .64

Recreational and Shopping Conscious .59

Novelty and Fashion Conscious .48

Habitual/Brand Loyal .42

Perfectionist/High Quality Conscious .34

Brand Conscious/Price Equals Quality .32

Impulsiveness/Careless .29

Price Conscious/Value for money .05 Source: Primary data

The overall model was significant. The independent variables (values)

explained 64% variation in Confused by Overchoice; 59% variation in Recreational

and Shopping Conscious; 48% variation in Novelty and Fashion Conscious; 42%

variation in Habitual/Brand Loyal; 34% variation in Perfectionist/High Quality

Conscious; 32% variation in Brand Conscious/Price Equals Quality; 29% variation

in Impulsiveness/Careless and 5% variation in Price Conscious/Value for money

style.

186

PROFILING THE YOUNG ADULT SHOPPER BASED ON PERSONAL

VALUES

The following consolidated tables reveal the nature of influence of values on

the various shopping styles of young adults. The nature of influence can be positive,

negative or neutral. A positive influence is when the variable is the underlying

motivation to act in a desired manner in tandem with the purpose. A negative

influence is when the variable is the motivation to act in a manner that is not in

favour of or is against the purpose. A neutral influence is when the variable does not

trigger any response or cause motivation to act in either manner.

Based on the findings of the nature of influence of values, a profile of the

young adult shopping behaviour for apparels can be developed.

TABLE:61

Nature of Influence of Values on the Perfectionist/High Quality Conscious Shopping Style

Shopping Style INFLUENCE OF VALUES

Positive Influence Negative Influence No Influence


Fun and Enjoyment of Life

A Sense of Accomplishment

Warm Relationships with Others

Being Well- Respected

Sense of Belonging

Self-Ful-fillment

Security and Comfort

Self –Respect Simplicity

Being Independent

Source: Primary data; Ref. Table 52

187

The Perfectionist/High Quality Conscious Shopping Style emerged as the

predominant style of young adults in their purchase-decisions for apparels as per the

mean and standard deviation scores. Values such as fun and enjoyment of life, sense

of accomplishment, warm relationship with others, being well respected and sense

of belonging were the cherished values of this shopper segment.

This group of respondents seeks to maximize satisfaction by

choosing the best quality products. Young adults seek fun and enjoyment of life,

love novelty and change in everything. They like to venture into new domains to

accomplish, and like to maintain cordial relations with family and peer group and

desire social recognition, respect and approval from others. They prefer to wear the

best quality apparels. Wearing high quality apparels adds to their image of being a

perfectionist. For them inter-personal and outer directed values bring in more

satisfaction, than internal individual value such as self-fulfillment (inner harmony)

which had a negative impact on this style segment. Being high in quality

consciousness, they are not simple in nature and self – worth and independence are

attributes that are already satisfied in being perfectionist. Hence values such as

security and comfort, self-respect, simplicity and independence did not have any

separate influence on their shopping style.

TABLE:62

Nature of Influence of Values on the ‘Brand Consciousness/Price Equals Quality’ Shopping Style



Brand Conscious/ Price Equals Quality



Self-Fulfillment Self –Respect



Sense of Belonging Security and Comfort Simplicity Being Independent


188

The Brand Consciousness/Price Equals Quality’ shopper segment considers

fun and enjoyment in life and being well respected as important values. They are

adventure seeking young adults who enjoy good food, leisure, novelty and change

and desire social recognition, respect and approval from others. They are brand

conscious and prefer to wear expensive branded clothes. Their image and status is

drawn from the expensive branded clothes they wear. They cherish inter-personal

and outer directed values higher rather than internal individual values such as like

self-fulfilment and self-respect which has a negative influence on this shopper

segment. All the other values do not influence the shopping style of this segment

while they shop for apparels.

TABLE:63

Nature of Influence of Values on the‘ Novelty and Fashion Conscious’ Shopping Style








Sense of Belonging

Self-Fulfillment Security and

Comfort Self –Respect Simplicity Being Independent


Young adults sporting the ‘Novelty and Fashion Conscious’ shopping style

cherish the values ‘Fun and enjoyment of life and Being Well-respected’ very

highly. They are similar to the brand conscious shopper in taste and love wearing

189

the latest fashion clothes. They are fun –loving and enjoy best things in life and are

attention seekers. Having social recognition and respect and approval from others is

important to this segment. They cherish inter-personal and outer directed values

higher rather than internal individual values.

All the other values did not have any significant influence on this shopper

segment.

TABLE:64

Nature of Influence of Values on the ‘Recreational and Shopping Conscious’ Shopping Style






Being Independent




Sense of Belonging

Self-Fulfillment Self –Respect Simplicity


It was found that there was a significant influence of the values Security and

Comfort, and Warm Relationships with others on the ‘Recreational and Shopping

Conscious’ shopping segment. Shopping is an enjoyable, fun filled activity and

pleasant activity for this group. They do not feel that shopping wastes their time.

They love to maintain good relations with others and go shopping with family and

friends just for the fun of it. They love to be associated with family and peer groups

and do not enjoy being independent which had a negative influence on this shopping

segment. All the other values did not have any significant influence on this shopper

segment.

190

TABLE:65

Nature of Influence of Values on the ‘Price Conscious/Value for Money’ Shopping Style

Shopping Style

INFLUENCE OF VALUES

Positive Influence Negative Influence

No Influence







Being Independent

Sense of Belonging

Self-Fulfillment

Self –Respect

Simplicity Source: Primary data; Ref. Table 56

Young adults embracing the Price Conscious/Value for Money’ shopping

style cherish the values Warm Relationships with others and a sense of

accomplishment highly. Getting best value for the money spent on apparels gives

them a sense of achievement. They share information about best buys with peer

group. The values Being Well-respected and Fun and enjoyment of life had negative

influence on this shopping segment. Internal directed values were more important to

this group than external directed values. This shopper segment seems conscious of

the things they buy and the amount they pay to procure the same. They are the

serious types who are not fun and enjoyment seekers and feel that respect is not

gained only from wearing high priced branded apparels. All the other values did not

have any significant influence on this shopper segment.

191

TABLE:66

Nature of Influence of Values on the ‘Impulsiveness/Careless’ Shopping Style

Shopping Style

INFLUENCE OF VALUES

Positive

Influence

Negative

Influence No Influence

Impulsiveness/

Careless Warm

Relationships

with Others

Self-

Fulfillment

A Sense of

Accomplishment

Fun and

Enjoyment of Life

Being Well-

Respected

Security and

Comfort

Being

Independent

Sense of

Belonging

Self –Respect

Simplicity Source: Primary data; Ref. Table 57

The Impulsiveness/Careless’ shopper segment considers Warm

Relationships with others as the important value to them. These shoppers are

impulsive and careless and tend to make unplanned purchases. They shop to please

others, even when they do not need. Self-fulfillment had a negative influence on

these shoppers indicating that they do not enjoy or approve what they do and regret

their impulsive behaviour. All the other values did not have any significant influence

on this shopper segment.

192

TABLE:67

Nature of Influence of Values on the‘ Confused by Overchoice’ Shopping Style

Shopping

Style

INFLUENCE OF VALUES

Positive Influence Negative

Influence No Influence

Confused by

Overchoice

Security and

Comfort

Fun and

Enjoyment

of Life

A Sense of

Accomplish

ment

Being Well-

Respected

Being Independent

Sense of Belonging

Self –Respect

Self-Fulfillment

Warm Relationships

with Others

Simplicity


Young adults falling under the Confused by Overchoice’ segment are

influenced by the values Security & Comfort, Fun and enjoyment of life and A

Sense of Accomplishment. They love fun and adventure, enjoy good food and

leisure and doing new things. They are the easy –going type and find it hard to

choose the best clothes or stores to shop. They find the vast number of different

consumer brands confusing. This shopping style emerged as the second highly

prevalent style describing the young adult population under study. All the other

values did not have any significant influence on this shopper segment.

193

TABLE:68

Nature of Influence of Values on the ‘Habitual/Brand Loyal’ Shopping Style

Shopping Style

INFLUENCE OF VALUES

Positive Influence

Negative Influence No Influence


Simplicity Being Well- Respected

Being Independent Sense of Belonging Self –Respect Self-Fulfillment




Security and Comfort Source: Primary data; Ref. Table 59

Simplicity is the only value that influences the ‘Habitual/Brand Loyal’

shopper segment. They are unassuming, straight forward, and down to earth. They

do not flaunt and display their skills, abilities and possessions. As shoppers they are

habitual in buying same brands from the same or familiar stores. They appear to

have favourite brands and stores and to have formed habits in choosing these.

The discussions in this section on influence of values on shopping styles

suggest that values influence all the dimensions of the shopping styles inventory.

From the above tables we can identify the predominant values among the list of ten

values used in this study that influences the young adults shopping styles for

apparels.

194

Values such as ‘Fun and enjoyment of Life’ and ‘Warm Relationship with

others,’ have the highest positive influence on the shopping Styles of young adults

for apparels. They showed a positive influence on four shopping styles. Young

adults enjoy everything in life that brings in entertainment, joy and happiness and

love to share space with their family, friends and peer group. These values positively

influence them to be Perfectionists, High Quality and Brand conscious. They love

high quality branded apparels and prefer to sport the latest in fashion. They are also

recreational shoppers as it is a fun giving activity in the company of their family or

friends. Fun and enjoyment also leads to confusion in their minds when the choice

is many. And sometimes, warm relationship with others, such as parents/family also

makes them to be impulsive and price conscious consumers.

Values such as ‘Being Well Respected’ and ‘Sense of Accomplishment’

have the next level of positive influence on the shopping styles of young adults for

apparels. They showed a positive influence on three shopping styles. The value

‘Being well respected’ positively influence young adults to be perfectionists, brand

conscious and fashion conscious and gain the respect and admiration from social

groups. While the value ‘Sense of Accomplishment’ influences to them to derive a

satisfaction and a feeling of accomplishment when they purchase the best, high

quality apparels (perfectionist) or get want they want at the best price (value for

money). However being in the young adult group of 18-25 years, they are also

indecisive and fickle minded and hence confused with overchoice.

The values ‘Security and Comfort’, ‘Simplicity’ and ‘Sense of Belonging’

have comparatively lesser level of positive influence. They showed a positive

influence on either one or two shopping styles. The value Security and comfort

positively influences young adults to be recreational shoppers and also makes them

confused with the plethora of choices available in the apparel market. Simplicity

makes the shopper go only to the same store or buy the same brand that they are

comfortable with. They do not venture into new areas and are not influenced by

fashion or trends. Sense of belonging leads them to be perfectionist and highly

quality conscious. Wearing the perfect clothes connects them strongly to their family

or peer group.

195

The value Self-Fulfillment shows the highest level of negative influence

affecting three shopping styles. Self-fulfillment is a state of enjoying what is being

done and achieving inner harmony. Satisfaction comes from being happy with one-

self and doing what is pleasing. External motivations do not influence / affect them.

They do not desire external affirmations to be considered as perfectionist like being

brand conscious. They are responsible and shop only when there is a need, hence are

not impulsive or careless shoppers.

The values Self Respect and Being Independent do not show positive

influence on any shopping style for young adults for apparels. These values are

neutral in nature and do not influence most of the shopping styles for apparels.

196

TESTING OF HYPOTHESES BASED ON SHOPPING STYLES AND

DEMOGRAPHIC VARIABLES [GENDER, EDUCATION LEVEL AND

REGION]

In the following section the research hypotheses are tested using ANOVA

and t statistic. To study the differences in shopping styles and value perception and

orientation between male and female respondents, the t test was conducted. In order

to study the differences in shopping styles and value perception and orientations

among the regions, and education levels of respondents, ANOVA was performed.

The results are tabulated, presented and interpreted systematically.

Objective 5- To explore the differences in the shopping styles among young

adults across demographics such as gender, and educational levels and regional

background

H3 - There is no significant difference in the shopping styles of young adults towards

purchase of apparels across gender

TABLE:69

Differences in mean for shopping styles across gender

Gender Mean Std. Deviation

Std. Error Mean

Perfectionist/High Quality Conscious Male 3.7954 .80470 .02838 Female 3.8510 .74784 .02887

Brand Conscious/Price Equals Quality Male 2.9505 .87289 .03078 Female 2.7597 .86069 .03325

Novelty and Fashion Conscious Male 2.9838 .88212 .03111 Female 3.0333 .89071 .03441

Recreational and Shopping Conscious Male 2.9619 .84678 .02986 Female 3.6682 .93933 .03626

Price Conscious/Value for money Male 3.2488 .68814 .02427 Female 3.1967 .61998 .02393

Impulsiveness/Careless Male 3.2313 .76945 .02714 Female 3.2837 .79139 .03055

Confused by Overchoice Male 3.3118 .87650 .03091 Female 3.3465 .91153 .03519

Habitual/Brand Loyal Male 3.2454 .90339 .03186 Female 3.1396 .87259 .03369


197

TABLE:70 t test for shopping styles across gender

Levene's Test for Equality of Variances

F Sig. t df Sig. (2-tailed)


Equal variances assumed

3.224 .073 -1.364 1473 .173

Equal variances not assumed -1.373 1456.060 .170



.001 .974 4.204 1472 .000

Equal variances not assumed 4.210 1431.280 .000



.671 .413 -1.068 1472 .286




18.634 .000 -15.176

1473 .000

Equal variances not assumed -

15.035 1363.642 .000



8.510 .004 1.512 1473 .131


Impulsiveness/Careless Equal variances assumed

.129 .719 -1.283 1473 .200




.944 .331 -.744 1473 .457

Equal variances not assumed -.741 1404.957 .459

Habitual/Brand Loyal Equal variances assumed

1.598 .206 2.276 1473 .023



It was found that there was a significant difference in shopping styles across

gender (p<0.05) on three factors of consumer-decision making styles (brand

conscious, recreational-hedonistic consumer and habitual brand-loyal consumer).

198

The gender differences in shopping styles indicated above are summarized as

under:

Gender Brand conscious Recreational shopper

Habitual brand-loyal

Male High Low High

Female Low High Low Source: Primary data, Ref. Table 69 & 70

The Brand Conscious/Price Equals Quality factor had a significant difference

across gender. Male respondents were found to be more brand conscious than

female respondents.

The Recreational and Shopping Conscious factor had a significant difference

across gender. Female respondents had higher levels of Recreational and Shopping

Consciousness as compared to male respondents.

The Habitual/Brand Loyal factor had a significant difference across gender.

Male respondents had higher levels of brand loyalty compared to female

respondents.

As gender difference was significant for three shopping styles we reject the

null hypothesis and accept the alternate hypothesis ‘There is significant difference

in the shopping styles of young adults towards purchase of apparels across

gender.’

However, on the other five factors no significant differences (p>0.05) in

consumer decision styles between men and women were found. Those factors are:

perfectionist consumer, novelty and fashion conscious, price consciousness,

impulsive consumer, and confused by overchoice consumer. Both male and female

customers equally pay attention to quality, price, and variety of offered goods, latest

fashion and behave in the same way regarding impulsiveness in decision-making

process.

199

This study found statistically significant gender differences on three factors,

which is in line with most other research (Mitchell and Walsh, 2004). Female

consumer behaviour tends to be similar as indicated in Underhill’s study (1999).

This study further indicates that male consumers became similar like female

consumers among the young-adult consumers with respect to perfectionism, price

consciousness, impulsiveness, and confused by over choice. (Ivan DamirAni , Anita

CiunovaSuleska, Edo Rajh, 2010).

DIFFERENCES IN SHOPPING STYLES ACROSS EDUCATION LEVELS

The total sample for the study was 1478 respondents, which comprised of

76.5% college-going students doing Undergraduate courses, 19.6% doing

Postgraduate courses and 3.9% were working after PUC or Diploma courses.

ANOVA was performed to study the differences in the shopping styles for apparels

due educational background.

H4 - There is no significant difference in the shopping styles of young adults

towards purchase of apparels across education levels.

TABLE:71

Differences in mean for shopping styles across Education Levels

Mean Std. Deviation

Std. Error

95% Confidence Interval for Mean

Lower Bound

Upper Bound

Perfectionist UG 3.8112 .77087 .02279 3.7665 3.8559

PG 3.8628 .78790 .04643 3.7715 3.9542

Other 3.7907 .94847 .14464 3.4988 4.0826

Total 3.8207 .77958 .02030 3.7809 3.8605

Brand conscious UG 2.8523 .88414 .02615 2.8010 2.9036

PG 2.9010 .82917 .04886 2.8049 2.9972

Other 2.9186 .84545 .12893 2.6584 3.1788

200

Total 2.8637 .87226 .02272 2.8192 2.9083

Novelty UG 3.0067 .89750 .02655 2.9546 3.0588

PG 3.0035 .84389 .04973 2.9056 3.1013

Other 3.0155 .87576 .13355 2.7460 3.2850

Total 3.0063 .88608 .02308 2.9611 3.0516

Recreation UG 3.2791 .95519 .02824 3.2237 3.3345

PG 3.3206 .95314 .05616 3.2101 3.4311

Other 3.1395 1.02929 .15696 2.8228 3.4563

Total 3.2832 .95680 .02491 3.2343 3.3320

Priceconscious UG 3.2302 .64668 .01912 3.1927 3.2677

PG 3.2361 .67690 .03989 3.1576 3.3146

Other 3.0155 .80657 .12300 2.7673 3.2637

Total 3.2251 .65830 .01714 3.1915 3.2587

Impulsive UG 3.2646 .78377 .02317 3.2191 3.3100

PG 3.2494 .77214 .04550 3.1599 3.3390

Other 3.0426 .70250 .10713 2.8264 3.2588

Total 3.2551 .77968 .02030 3.2153 3.2950

Confusion UG 3.3198 .89553 .02648 3.2678 3.3717

PG 3.3426 .88253 .05200 3.2402 3.4449

Other 3.4341 .88949 .13565 3.1604 3.7079

Total 3.3276 .89247 .02324 3.2820 3.3732

Brandloyalty UG 3.1716 .90082 .02663 3.1194 3.2239

PG 3.3032 .86388 .05090 3.2030 3.4034

Other 3.1705 .75373 .11494 2.9386 3.4025

Total 3.1973 .89077 .02319 3.1518 3.2428 Source: Primary data

201

TABLE:72 ANOVA Indicating differences in shopping styles across education level of

young adults

ANOVA

Sum of Squares df

Mean Square F Sig.

Perfectionist/ High Quality Conscious

Between Groups

.684 3 .228 .375 .771

Within Groups

895.135 1475 .609

Total 895.819 1478 Brand Conscious/ Price Equals Quality

Between Groups

2.290 3 .763 1.003 .390

Within Groups

1118.429 1475 .761

Total 1120.720 1473 Novelty and Fashion Conscious

Between Groups

.109 3 .036 .046 .987

Within Groups

1156.388 1475 .787

Total 1156.496 1478 Confused by Overchoice

Between Groups

1.457 3 .486 .530 .662

Within Groups

1347.941 1475 .916

Total 1349.399 1478 Recreational and Shopping Conscious

Between Groups

3.841 3 1.280 2.966 .031

Within Groups

634.931 1475 .432

Total 638.772 1478 Price Conscious/ Value for money

Between Groups

2.086 3 .695 1.144 .330

Within Groups

893.952 1475 .608

Total 896.037 1478 Impulsiveness/Careless

Between Groups

.665 3 .222 .278 .841

Within Groups

1173.369 1475 .798

Total 1174.034 1478 Habitual/Brand Loyal

Between Groups

5.049 3 1.683 2.126 .095

Within Groups

1164.540 1475 .792

Total 1169.589 1478 Source: Primary data

202

It was found that there was a significant difference in the shopping styles

across education levels of respondents. PG students were more Recreational and

Shopping Conscious as compared to UG and others (p<0.05).As education level was

significant for Recreational and Shopping Conscious style we reject the null

hypothesis and accept the alternate hypothesis ‘There is significant difference in

the shopping styles of young adults towards purchase of apparels across

education levels.’

However, on the other seven factors no significant differences (p>0.05) in

consumer decision styles across education levels of young adults were found. Most

young adults in the reference age category behave similarly while purchasing

apparels. The less difference in the age of respondents is a rationale to support this

fact.

DIFFERENCES IN SHOPPING STYLES ACROSS REGIONS

H5 - There is no significant difference in the shopping styles of young

adults towards purchase of apparels across regional background.

203

TABLE:73 Differences in mean for shopping styles across Regions

Mean Std. Deviation Std. Error


Lower Bound

Upper Bound

Perfectionist/ High Quality Conscious

North .0811128 .93654793 .07887156 -.0748206 .2370461 South -.0437542 1.02012690 .03149680 -.1055582 .0180498 East .1522233 .98710796 .07708018 .0000189 .3044278 West .0224066 .87609373 .08590806 -.1479718 .1927850 Total -.0049152 1.00035740 .02619850 -.0563060 .0464756


North -.0868303 1.01382116 .08537914 -.2556294 .0819689 South -.0126457 .99254229 .03064512 -.0727784 .0474871 East .2041854 1.03727296 .08099741 .0442459 .3641249 West -.0160948 .96014072 .09414954 -.2028182 .1706286 Total .0043238 .99921781 .02616866 -.0470084 .0556561


North -.1273052 1.06371860 .08958127 -.3044122 .0498018 South .0156108 .99117243 .03060282 -.0444389 .0756606 East .1151740 .98540984 .07694758 -.0367685 .2671166 West -.1018932 1.00617703 .09866378 -.2975695 .0937831 Total .0046073 .99976265 .02618292 -.0467530 .0559675


North -.0726794 1.03308571 .08700151 -.2446860 .0993273 South .0304228 .99892801 .03084228 -.0300969 .0909424 East -.0012702 1.05728260 .08255990 -.1642950 .1617546 West -.1888453 .89458270 .08772105 -.3628193 -.0148713 Total .0012466 1.00282094 .02626302 -.0502708 .0527639


North .1269768 .96595287 .08134791 -.0338524 .2878060 South -.0220780 1.00890181 .03115022 -.0832019 .0390459 East -.0114369 .96498795 .07535290 -.1602306 .1373568 West .0879494 1.02807708 .10081125 -.1119859 .2878847 Total .0013821 1.00158731 .02623071 -.0500719 .0528360


North -.1171347 .98750845 .08316321 -.2815528 .0472834 South .0640978 .92970993 .02870514 .0077717 .1204239 East -.1492174 1.03861140 .08110192 -.3093633 .0109285 West -.2330703 1.44573512 .14176599 -.5142297 .0480891 Total .0013797 .99726207 .02611744 -.0498521 .0526115


North -.0026552 .93768136 .07896702 -.1587773 .1534668

South .0218628 1.02588209 .03167450 -.0402899 .0840154 East -.0715966 .97550983 .07617452 -.2220126 .0788195 West -.0821672 .88800130 .08707569 -.2548613 .0905269 Total .0015586 1.00254354 .02625575 -.67594 .406829


204

TABLE:74 ANOVA Indicating differences in mean for shopping styles across Regions

ANOVA

Sum of Squares Df Mean

Square F Sig.


Between Groups

6.753 3 2.251 2.255 .080

Within Groups

1451.289 1475 .998

Total 1458.042 1478 Brand Conscious/Price Equals Quality

Between Groups

8.068 3 2.689 2.703 .044

Within Groups

1446.654 1475 .995

Total 1454.722 1478 Novelty and Fashion Conscious

Between Groups

5.765 3 1.922 1.926 .123

Within Groups

1450.543 1475 .998

Total 1456.308 1478 Confused by Overchoice

Between Groups

5.423 3 1.808 1.800 .145

Within Groups

1459.809 1475 1.004

Total 1465.232 1478 Recreational and Shopping Conscious

Between Groups

3.608 3 1.203 1.199 .309

Within Groups

1458.021 1475 1.003

Total 1461.629 1478 Price Conscious/Value for money

Between Groups

15.543 3 5.181 5.255 .001

Within Groups

1433.490 1475 .986

Total 1449.033 1478 Impulsiveness/Careless Between

Groups 2.042 3 .681 .677 .566

Within Groups

1462.380 1475 1.006

Total 1464.421 1478


Between Groups Within Groups Total

4.018 1165.572 1169.589

3 1475 1478

2.009 .792

2.537 .079


205

The results indicate that there is a significant difference in shopping styles

across regional back ground of the respondents (p<0.05). Young adults from the

South were more ‘price conscious’ and perceived more value for money as

compared to other regions. Young adults from east were more ‘brand conscious’

compared to other regions.

As the regional background of young adults had a significant influence

on the Price Conscious/ Value for money and Brand Conscious/Price Equals Quality

shopping styles, we reject the null hypothesis and accept the alternate

hypothesis ‘There is significant difference in the shopping styles of young adults

towards purchase of apparels across regional background.’

TESTING OF HYPOTHESES BASED ON VALUES AND

DEMOGRAPHIC VARIABLES [GENDER, EDUCATION LEVEL AND

REGION]

Objective 6 - To explore the differences in value perception and value

orientation of young adults across demographics such as gender and regional

background

Gender based value orientations

H6 -There is no significant difference in the orientation of young adults

towards External Values, Internal Interpersonal Values and Internal Individual

Values across gender.

206

TABLE:75 Differences in Mean for Value Orientations across Gender

Group Statistics

Gender N Mean Std. Deviation

Std. Error Mean

External values Male 804 7.2852 1.52137 .05365

Female 673 7.7439 1.39110 .05362

Internal interpersonal values

Male 804 7.1853 1.62115 .05717

Female 674 7.4206 1.51712 .05844

Internal individual values

Male 804 7.1823 1.48065 .05222

Female 674 7.4656 1.38278 .05326 Source: Primary data

TABLE:76 t Test for Value Orientations across Gender

Levene's Test

for Equality of Variances


External values


5.315 .021 -5.999 1475 .000

Equal variances not assumed

-6.047 1463.517 .000



5.032 .025 -2.861 1476 .004


-2.878 1458.239 .004



3.908 .048 -3.775 1476 .000


-3.797 1458.891 .000


207

The above table indicates that there is significant difference in the orientation

towards the different category of values among male and female respondents

Female respondents were found to be with higher orientations towards

External Values such as Sense of belonging, Being well respected and Security &

comfort; Internal Interpersonal Values such as Warm relationships with others, fun

and enjoyment of life; and Internal Individual Values such as Self-fulfillment, Self

respect, A sense of accomplishment, Simplicity and Being Independent, than the

male respondents (p<0.01).

As there is a significant difference in the value orientations among male and

female respondents, we reject the null hypothesis and accept the alternate

hypothesis‘ There is significant difference in the orientation of young adults


Individual Values across gender.’

Region-wise value orientations of respondents

H7 - There is no significant difference in the orientation of young adults

towards External Values, Internal Interpersonal Values and Internal Individual

Values across regional background.

208

TABLE:77

Differences in Mean for Value Orientations of Young Adults across Regional

Background

N Mean Std. Deviation

Std. Error


Lower Bound

Upper Bound

External values

North 141 7.5934 1.28365 .10810 7.3797 7.8071

South 1052 7.4591 1.52981 .04717 7.3666 7.5517

East 165 7.4424 1.51200 .11771 7.2100 7.6748

West 104 7.8718 .88413 .08670 7.6999 8.0437

Total 1462 7.4995 1.47155 .03849 7.4241 7.5750


North 141 7.3050 1.38715 .11682 7.0740 7.5359

South 1053 7.2816 1.61777 .04985 7.1838 7.3794

East 165 7.2121 1.59568 .12422 6.9668 7.4574

West 104 7.5962 1.21894 .11953 7.3591 7.8332

Total 1463 7.2984 1.57007 .04105 7.2178 7.3789


North 141 7.5248 1.11958 .09429 7.3384 7.7112

South 1053 7.2754 1.49871 .04619 7.1848 7.3660

East 165 7.2242 1.49972 .11675 6.9937 7.4548

West 104 7.6250 .89342 .08761 7.4513 7.7987

Total 1463 7.3185 1.43455 .03751 7.2450 7.3921 Source: Primary data

209

TABLE:78

ANOVA showing Value Orientations of Young Adults across Regional Background

ANOVA

Sum of Squares df Mean

Square F Sig.

External values

Between Groups 17.910 3 5.970 2.767 .041

Within Groups 3145.812 1458 2.158

Total 3163.722 1461


Between Groups 10.753 3 3.584 1.455 .225

Within Groups 3593.263 1459 2.463

Total 3604.016 1462

Internalindividual values

Between Groups 19.194 3 6.398 3.122 .025

Within Groups 2989.494 1459 2.049


It was found that respondents from the Western Region display a higher

orientation towards both External Values and Internal Individual Values (p value

<0.05) compared to the other regions.

There is no significant difference in the orientation towards Internal

Interpersonal Values across regional back ground of the respondents.

As there is a significant difference in the value orientations among the

respondents from different regions, we reject the null hypothesis and accept the

alternate hypothesis ‘There is significant difference in the orientation of young

adults towards External Values, Internal Interpersonal Values and Internal

Individual Values across regional background.’

210

Level of Influence of individual values across gender of respondents

H8 - There is no significant difference in the level of influence of individual

values on young adults across gender.

TABLE:79

Differences in Mean for level of influence of individual Values across Gender Group Statistics

Gender N Mean Std. Deviation

Std. Error Mean

Sense Of Belonging Male 804 7.55 1.862 .066

Female 674 7.94 1.721 .066

Simplicity Male 804 6.84 1.910 .067

Female 674 7.11 1.767 .068

Warm Relationships Male 804 6.98 1.820 .064

Female 674 7.35 1.729 .067

Self fulfillment Male 804 7.08 1.916 .068

Female 674 7.45 1.795 .069

Being Well Respected Male 804 7.17 1.888 .067

Female 673 7.58 1.609 .062

Fun & Enjoyment Male 804 7.39 1.958 .069

Female 674 7.49 1.820 .070

Security & Comfort Male 804 7.13 1.901 .067

Female 674 7.70 1.712 .066

Self Respect Male 804 7.53 1.863 .066

Female 674 7.93 1.644 .063

Sense Of Accomplishment

Male 804 7.22 1.861 .066

Female 674 7.35 1.769 .068

Being Independent Male 804 7.25 2.069 .073

Female 674 7.49 1.854 .071 Source: Primary data

211

TABLE:80

t Test for Level of Influence of individual Values across Gender Levene's Test

for Equality of Variances


sense of belong


12.850 .000 -4.114 1476 .000


-4.143 1462.013 .000

simplicity


7.445 .006 -2.811 1476 .005


-2.831 1461.739 .005

warm relationships


.912 .340 -4.012 1476 .000


-4.030 1453.209 .000

self fulillment


2.595 .107 -3.875 1476 .000


-3.898 1457.916 .000

being well respected


12.969 .000 -4.389 1475 .000


-4.452 1474.520 .000

fun & enjoyment


4.937 .026 -.988 1476 .323


-.994 1460.441 .320

212

security & comfort


11.182 .001 -5.946 1476 .000


-6.001 1468.399 .000

self respect


14.736 .000 -4.399 1476 .000


-4.447 1472.046 .000

sense of accomplishment


1.483 .223 -1.321 1476 .187


-1.327 1452.952 .185

being independent


8.266 .004 -2.298 1476 .022


-2.320 1469.475 .020


The above table indicates that there is significant difference in the level of

influence of individual values among male and female respondents

Female respondents showed higher level of influence of eight values viz.

sense of belonging (p<0.01), simplicity (p<0.01), warm relationship with others

(p<0.01), self-fullfilment (p<0.01), being well respected (p<0.01), security and

comfort (p<0.01), self-respect (p<0.01), being independent (p<0.05).

Fun and enjoyment of life and sense of accomplishment(p>0.05), were the

only two values that did not reveal any significant difference in the level of

influence on male and female respondents.

As there is a significant difference in the level of influence of individual

values among male and female respondents, we reject the null hypothesis and

accept the alternate hypothesis ‘There is significant difference in the level of

influence of individual values on young adults across gender.’

213

Level of Influence of individual values across Regions

H9 - There is no significant difference in the level of influence of individual

values on young adults across regional background.

TABLE:81

Differences in Mean for level of influence of individual Values across Regional Background

N Mean Std. Deviation

Std. Error


Lower Bound

Upper Bound

sense of belonging

North 141 7.87 1.573 .132 7.60 8.13

South 1053 7.65 1.880 .058 7.53 7.76

East 165 7.84 1.747 .136 7.57 8.10

West 104 8.20 1.177 .115 7.97 8.43

Total 1463 7.73 1.801 .047 7.64 7.82

simplicity

North 141 6.95 1.834 .154 6.65 7.26

South 1053 6.93 1.868 .058 6.81 7.04

East 165 7.03 1.836 .143 6.75 7.31

West 104 7.22 1.607 .158 6.91 7.53

Total 1463 6.96 1.844 .048 6.87 7.06

warm relationships

North 141 7.13 1.643 .138 6.85 7.40

South 1053 7.13 1.841 .057 7.02 7.24

East 165 7.13 1.668 .130 6.87 7.38

West 104 7.51 1.421 .139 7.23 7.79

Total 1463 7.16 1.778 .046 7.06 7.25

selfulillment

North 141 7.36 1.790 .151 7.06 7.66

South 1053 7.24 1.921 .059 7.12 7.35

East 165 7.10 1.853 .144 6.82 7.39

West 104 7.49 1.344 .132 7.23 7.75

Total 1463 7.25 1.866 .049 7.16 7.35

214


North 141 7.50 1.534 .129 7.25 7.76

South 1052 7.31 1.843 .057 7.20 7.42

East 165 7.39 1.731 .135 7.12 7.65

West 104 7.66 1.304 .128 7.41 7.92

Total 1462 7.36 1.771 .046 7.27 7.45

fun & enjoyment

North 141 7.48 1.779 .150 7.19 7.78

South 1053 7.43 1.935 .060 7.32 7.55

East 165 7.30 1.901 .148 7.00 7.59

West 104 7.68 1.566 .154 7.38 7.99

Total 1463 7.44 1.893 .049 7.34 7.54

security & comfort

North 141 7.41 1.871 .158 7.10 7.72

South 1053 7.41 1.839 .057 7.29 7.52

East 165 7.10 1.993 .155 6.80 7.41

West 104 7.75 1.335 .131 7.49 8.01

Total 1463 7.40 1.833 .048 7.30 7.49

self respect

North 141 7.99 1.384 .117 7.76 8.22

South 1053 7.68 1.826 .056 7.57 7.80

East 165 7.56 1.865 .145 7.27 7.84

West 104 8.05 1.234 .121 7.81 8.29

Total 1463 7.73 1.760 .046 7.63 7.82


North 141 7.43 1.649 .139 7.15 7.70

South 1053 7.26 1.868 .058 7.15 7.37

East 165 7.17 1.857 .145 6.88 7.46

West 104 7.54 1.284 .126 7.29 7.79

Total 1463 7.29 1.812 .047 7.19 7.38

being independent

North 141 7.90 1.518 .128 7.65 8.15

South 1053 7.27 2.036 .063 7.14 7.39

East 165 7.26 2.042 .159 6.95 7.57

West 104 7.83 1.554 .152 7.52 8.13

Total 1463 7.37 1.973 .052 7.27 7.47 Source: Primary data

215

TABLE:82

ANOVA showing level of influence of individual Values across Regional Background

ANOVA

Sum of Squares Df Mean

Square F Sig.

sense of belonging

Between Groups 34.581 3 11.527 3.572 .014

Within Groups 4707.772 1459 3.227

Total 4742.353 1462

simplicity

Between Groups 9.143 3 3.048 .896 .442

Within Groups 4961.637 1459 3.401

Total 4970.779 1462

warm relationships

Between Groups 14.013 3 4.671 1.479 .218

Within Groups 4606.455 1459 3.157

Total 4620.468 1462

self fulfillment

Between Groups 11.463 3 3.821 1.098 .349

Within Groups 5078.962 1459 3.481

Total 5090.425 1462


Between Groups 15.139 3 5.046 1.611 .185

Within Groups 4567.002 1458 3.132

Total 4582.140 1461

fun & enjoyment

Between Groups 9.790 3 3.263 .911 .435

Within Groups 5228.846 1459 3.584

Total 5238.636 1462

216

security & comfort

Between Groups 27.323 3 9.108 2.721 .043

Within Groups 4882.738 1459 3.347

Total 4910.062 1462

self respect

Between Groups 26.781 3 8.927 2.893 .034

Within Groups 4502.758 1459 3.086

Total 4529.539 1462


Between Groups 12.306 3 4.102 1.250 .290

Within Groups 4788.265 1459 3.282

Total 4800.571 1462

being independent

Between Groups 74.390 3 24.797 6.442 .000

Within Groups 5615.767 1459 3.849


The above table indicates that there is significant difference in the level of

influence of individual values across regions. Young adults from the West showed a

higher level of influence by the values Sense of Belonging (p<0.05), Security and

comfort (p<0.05) and Self Respect (p<0.05), than the other regions. Young adults

from the North showed higher level of influence of the value Being

Independent(p<0.01).

As there is a significant difference in the level of influence of individual

values across respondents from different regions, we reject the null hypothesis and

accept the alternate hypothesis ‘There is significant difference in the level of

influence of individual values on young adults across regional background.’

217

CHAPTER 6

FINDINGS, SUGGESTIONS & CONCLUSION

The findings of the study are presented in the following sections:

1) The total number of respondents for the study were 1478 young adults, of

which 804 (54.4%) were male respondents and 674 (45.6%) were female

respondents. The demographic profile of the respondents for the study more

or less replicates the demographic profile of the population of Bangalore

city. The Male : Female gender ratio is 1000:968

2) It was found that most of the young adults in the age group 18-25 perceive,

‘Sense of belonging’ as the most important value (mean score 7.71). The

feeling that family and friends care about them is very important to this age

group. The institution of the family and the family support system are the

main drivers in life. When this basic feeling of belonging is established and

confirmed in life, it gives a secure feeling that every challenge can be faced

bravely.

3) Most of the young adult respondents attach greater importance to External

values such as Sense of belonging, Being well respected and Security &

comfort (Mean 7.49).

4) The results indicate that Perfectionist/High Quality Conscious (mean 3.8207)

is the predominant style of young adults in their purchase-decisions for

apparels. This group of respondents seeks to maximize quality by choosing

the best products. They set high standards and have high expectations for the

products they buy and aim to get the best choice and value for money. Being

higher in perfectionism, these consumers could be expected to shop more

carefully, more systematically, or by comparison.

5) The Perfectionist / high-quality conscious shopping style was found to be

significantly positively correlated at the 0.01 level with six other shopping

styles - Brand consciousness/price equals quality, Novelty and fashion

218

conscious, Recreational and shopping conscious, Impulsiveness/Careless,

Confused by Overchoice, and Habitual/brand-loyal. There is no significant

correlation between the Perfectionist/ high-quality conscious shopping style

and the Price conscious/value for the money shopping style (p value >0.05).

6) It was found there is significant positive correlation at the 0.01 level (2

tailed) among the values and the shopping styles (p value <0.001). This

indicates there is a strong relationship between values and shopping styles of

young adults.

7) The study found that the value ‘fun and Enjoyment of life’ showed the

maximum significant positive correlation to six shopping styles viz., the

Perfectionist/High Quality Conscious (p value <0.01), Brand

Consciousness/Price Equals Quality (p value <0.01), Novelty and Fashion

Conscious (p value <0.01), Recreational and Shopping Conscious (p value

<0.01), Confused by Overchoice (p value <0.01) and Habitual/Brand Loyalty

(p value <0.01) shopping styles of young adults. This indicates that young

adults are adventure seeking, and enjoy novelty and change. They are quality

and brand conscious. They are also recreational shoppers and are confused

with the choice of apparel brands available to them.

8) It was found there is significant relationship between the value ‘Sense of

Belonging’ and the Perfectionist/High Quality Conscious and Recreational

and Shopping Conscious styles of young adults.

9) It was found there is significant relationship between the value ‘Simplicity’

and the Perfectionist/High Quality Conscious, Price Conscious/Value for the

money and Habitual/Brand Loyalty styles of young adults.

10) It was found there is significant relationship between the value ‘Warm

Relationships with others’ and the Perfectionist/High Quality Conscious,

Recreational and Shopping Conscious, and Price Conscious/Value for the

money shopping styles of young adults.

219

11) It was found there is significant negative relationship between the value

‘Self-Fulfillment’ and the Impulsiveness/Careless shopping style of young

adults.

12) It was found there is significant relationship between the value ‘Being Well

Respected’ and the Perfectionist/High Quality Conscious, Novelty and

Fashion Conscious, Recreational and Shopping Conscious, and

Habitual/Brand Loyalty shopping styles of young adults.

13) It was found there is significant relationship between the value ‘Fun and

Enjoyment of life’ and the Perfectionist/High Quality Conscious, Brand

Consciousness/Price Equals Quality, Novelty and Fashion Conscious,

Recreational and Shopping Conscious, Confused by Overchoice and

Habitual/Brand Loyalty shopping styles of young adults.

14) It was found there is significant relationship between the value ‘Self

Respect’ and the Perfectionist/High Quality Conscious, Recreational and

Shopping Conscious, and Habitual/Brand Loyalty shopping styles of young

adults.

15) It was found there is significant relationship between the value ‘Sense of

Accomplishment’ and the Perfectionist/High Quality Conscious, Novelty and

Fashion Conscious, Price Conscious/Value for the money, and Confused by

Overchoice shopping styles of young adults.

16) It was found there is significant relationship between the value ‘Being

Independent’ and the Perfectionist/High Quality Conscious shopping style of

young adults.

17) It is found that the results of the Confirmatory Factor Analysis reports that

all partial squared correlation coefficients (R2) for all individual items in

each construct is more than 0.50. This clearly establishes the validity of the

measurement model.

220

18) The results of confirmatory factor analysis and goodness of fit test under the

Structural Equation Modeling Technique indicate that the dimensions of

shopping styles among young adults in Bangalore city, confirms with the

original Sproles & Kendall CSI (1986).

19) The proposed ‘Value - Shopping Style Model’ was tested using Structural

Equation Modelling technique (SEM). The overall fit of the proposed

research model was significant as all measures of fitness were at acceptable

levels indicating the model fits the data well.

Findings from Hypotheses Testing

20) It was found that there is significant influence of overall values on the

shopping styles of young adults towards purchase of apparels. The highest

influence of values was on the Perfectionist/High Quality Conscious style

(P value <.001), followed by Novelty and Fashion Conscious, Recreational

and Shopping Conscious, Confused by Overchoice, Habitual/Brand Loyal,

Brand Consciousness/Price Equals Quality and Impulsiveness/Careless

styles. There was no significant influence of values on the Price

Conscious/Value for the money style.

21) The study reveals that values influence all the dimensions of the shopping

styles inventory.

22) It was found that there is significant influence of values, ‘Fun and Enjoyment

of life’ (p value <0.01), ‘A sense of accomplishment’ (p value <0.01),

‘Warm relationships with others’ (p value <0.01), ‘Being well respected’

(p value <0.05), and ‘Sense of belonging’ (p value <0.05), on the

Perfectionist/High Quality Conscious dimension of the shopping styles.

Self-fulfillment had a negative influence (p value <0.01). However, the

values Simplicity, Security & Comfort, Self-respect and Being independent

did not have a significant influence on the Perfectionist/High Quality

Conscious shopping style.

221

The ‘Perfectionist/High Quality Conscious’ Shopping Style emerged as the

predominant style of young adults in their purchase-decisions for apparels as

per the mean scores, correlation and regression analysis. Values such as fun

and enjoyment of life, sense of accomplishment, warm relationship with

others, being well respected and sense of belonging were the cherished

values of this shopper segment. This group of respondents seeks to maximize

satisfaction by choosing the best quality products. Young adults seek fun and

enjoyment of life, love novelty and change in everything. They like to

venture into new domains to accomplish, and like to maintain cordial

relations with family and peer group and desire social recognition, respect

and approval from others. They prefer to wear the best quality apparels.

Wearing high quality apparels adds to their image of being a perfectionist.

For them inter-personal and outer directed values bring in more satisfaction,

than internal individual value such as self-fulfillment (inner harmony) which

had a negative impact on this style segment. Being high in quality

consciousness, they are not simple in nature and self – worth and

independence are attributes that are already satisfied in being perfectionist.

Hence values such as security and comfort, self-respect, simplicity and

independence did not have any separate influence on their shopping style.

23) It was found that there is significant positive influence of the values Fun and

Enjoyment of Life (p value <0.01), and Being well respected (p value <0.05),

on the ‘Brand Conscious/Price Equals Quality’ dimension of the shopping

style inventory. Self-fulfillment (p value <0.01), and Self respect (p value

<0.01), had negative influence on ‘Brand Conscious/Price Equals Quality’

shopping style. However, the values Sense of belonging, Simplicity, Warm

Relationships, Security & Comfort, A Sense of Accomplishment and Being

independent did not have a significant influence on the ‘Brand

Conscious/Price Equals Quality’ shopping style.

The ‘Brand Consciousness/Price Equals Quality’ shopper segment

considers fun and enjoyment in life and being well respected as important

values. They are adventure seeking young adults who enjoy good food,

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leisure, novelty and change and desire social recognition, respect and

approval from others. They are brand conscious and prefer to wear expensive

branded clothes. Their image and status is drawn from the expensive branded

clothes they wear. They cherish inter-personal and outer directed values

higher rather than internal individual values such as like self-fulfilment and

self-respect which has a negative influence on this shopper segment. All the

other values do not influence the shopping style of this segment while they

shop for apparels.

24) It was found that there is significant influence of the values Fun and

enjoyment of life (p value <0.01), and Being Well-respected (p value <0.05),

on the ‘Novelty and Fashion Conscious’ dimension of shopping style

inventory. All the other values did not have a significant influence on this

dimension of shopping style inventory.

Young adults sporting the ‘Novelty and Fashion Conscious’ shopping style

cherish the values ‘Fun and enjoyment of life and Being Well-respected’

very highly. They are similar to the brand conscious shopper in taste and

love wearing the latest fashion clothes. They are fun –loving and enjoy best

things in life and are attention seekers. Having social recognition and respect

and approval from others is important to this segment. They cherish inter-

personal and outer directed values higher rather than internal individual

values.

25) It was found that there is significant positive influence of the values Security

and Comfort (p value <0.01), and Warm Relationships with others (p value

<0.05), on the ‘Recreational and Shopping Conscious’ dimension of

shopping style inventory. Being Independent (p value <0.05), had a negative

influence, on the ‘Recreational and Shopping Conscious’ dimension of

shopping style inventory. All the other values did not have a significant

influence on this dimension of shopping style inventory.

The ‘Recreational and Shopping Conscious’ shopping segment considers

shopping is an enjoyable; fun filled activity and pleasant activity. They do

223

not feel that shopping wastes their time. They love to maintain good relations

with others and go shopping with family and friends just for the fun of it.

They love to be associated with family and peer groups and do not enjoy

being independent which had a negative influence on this shopping segment.

All the other values did not have any significant influence on this shopper

segment.

26) It was found that there is significant positive influence of the values Warm

Relationships with others (p value <0.01), and A sense of accomplishment (p

value <0.05), and a significant negative influence of the values Being Well-

respected (p value <0.01), and Fun and enjoyment of life (p value <0.05), on

the ‘Price Conscious/Value for money’ dimension of shopping style

inventory. All the other values did not have a significant influence on this

dimension of shopping style inventory.

Young adults embracing the Price Conscious/Value for Money’ shopping

style cherish the values Warm Relationships with others and a sense of

accomplishment highly. Getting best value for the money spent on apparels

gives them a sense of achievement. They share information about best buys

with peer group. The values Being Well-respected and Fun and enjoyment of

life had negative influence on this shopping segment. Internal directed values

were more important to this group than external directed values. This

shopper segment seems conscious of the things they buy and the amount they

pay to procure the same. They are the serious types who are not fun and

enjoyment seekers and feel that respect is not gained only from wearing high

priced branded apparels. All the other values did not have any significant

influence on this shopper segment.

27) It was found that there is significant positive influence of the value Warm

Relationships (p value <0.01), with others and significant negative influence

of the value Self-fulfillment (p value <0.01), on the

‘Impulsiveness/Careless’ dimension of the shopping inventory. All the

224

other values did not have a significant influence on this dimension of

shopping style inventory.

The Impulsiveness/Careless’ shopper segment considers Warm

Relationships with others as the important value to them. These shoppers are

impulsive and careless and tend to make unplanned purchases. They shop to

please others, even when they do not need. Self-fulfillment had a negative

influence on these shoppers indicating that they do not enjoy or approve

what they do and regret their impulsive behaviour. All the other values did

not have any significant influence on this shopper segment.

28) It was found that there is significant influence of the values Fun and

enjoyment of life (p value <0.01), Security & Comfort (p value <0.05), and

A sense of accomplishment (p value <0.05), on the ‘Confused by

Overchoice’ dimension of shopping styles inventory. All the other values

did not have a significant influence on this dimension of shopping style

inventory.

Young adults falling under the Confused by Overchoice’ segment are

influenced by the values Security & Comfort, Fun and enjoyment of life and

A Sense of Accomplishment. They love fun and adventure, enjoy good food

and leisure and doing new things. They are the easy –going type and find it

hard to choose the best clothes or stores to shop. They find the vast number

of different consumer brands confusing. This shopping style emerged as the

second highly prevalent style describing the young adult population under

study. All the other values did not have any significant influence on this

shopper segment.

29) It was found that there is significant influence of the value Simplicity (p

value <0.01), on the ‘Habitual/Brand Loyal’ dimension of shopping style.

The other values did not have a significant influence on ‘Habitual/Brand

Loyal’ style.

225

Simplicity is the only value that influences the ‘Habitual/Brand Loyal’

shopper segment. They are unassuming, straight forward, and down to earth.

They do not flaunt and display their skills, abilities and possessions. As

shoppers they are habitual in buying same brands from the same or familiar

stores. They appear to have favourite brands and stores and to have formed

habits in choosing these.

30) It is found from the study that the predominant values among the list of ten

values used in this study, that influences the young adults shopping styles for

apparels are Values such as ‘Fun and enjoyment of Life’ and ‘Warm

Relationship with others,’ which have the highest positive influence on the

shopping Styles of young adults for apparels. They showed a positive

influence on four shopping styles. Young adults enjoy everything in life that

brings in entertainment, joy and happiness and love to share space with their

family, friends and peer group. These values positively influence them to be

Perfectionists, High Quality and Brand conscious. They love high quality

branded apparels and prefer to sport the latest in fashion. They are also

recreational shoppers as it is a fun giving activity in the company of their

family or friends. Fun and enjoyment also leads to confusion in their minds

when the choice is many. And sometimes, warm relationship with others,

such as parents/family also makes them to be impulsive and price conscious

consumers.

31) The value Self-Fulfillment shows the highest level of negative influence

affecting three shopping styles viz., Perfectionist/High quality conscious,

Brand Conscious/Price equals quality and Impulsive/Careless shopping

styles.

32) The values Self Respect and Being Independent do not show positive

influence on any shopping style for young adults for apparels. These values

are neutral in nature and do not influence most of the shopping styles for

apparels.

226

33) The findings of the study indicate that there were significant gender

differences on three factors of consumer-decision making styles (brand

conscious, recreational-hedonistic consumer and habitual brand-loyal

consumer). The Brand Conscious/Price Equals Quality factor had a

significant difference across gender. Male respondents were found to be

more brand conscious than female respondents.

The Recreational and Shopping Conscious factor had a significant difference

across gender. Female respondents had higher levels of Recreational and

Shopping Consciousness as compared to male respondents.

The Habitual/Brand Loyal factor had a significant difference across gender.

Male respondents had higher levels of brand loyalty compared to female

respondents.

34) It was found that there is a significant difference (p<0.05) in the shopping

styles across education levels. PG students were more Recreational and

Shopping Conscious as compared to UG and others.

35) Young Adults from the South were more price-conscious and perceived

more value for money as compared to youth from other regions. Further,

young adults from east were more brand conscious compared to their peers

from other regions.

36) Female respondents were found to be with higher orientations towards

External Values such as Sense of belonging, Being well respected and

Security & comfort; Internal Interpersonal Values such as Warm

relationships with others, fun and enjoyment of life; and Internal Individual

Values such as Self-fulfillment, Self respect, A sense of accomplishment,

Simplicity and Being Independent, than the male respondents (p<0.01). The

study revealed that Value orientations are higher in women as compared to

men.

37) Female respondents showed higher level of influence of eight values viz.

sense of belonging (p<0.01), simplicity (p<0.01), warm relationship with

227

others (p<0.01), self-fullfilment (p<0.01), being well respected (p<0.01),

security and comfort (p<0.01), self-respect (p<0.01), being independent

(p<0.05). Fun and enjoyment of life and sense of accomplishment (p>0.05),

were the only two values that did not reveal any significant difference in the

level of influence on male and female respondents.

38) It was found that respondents from the Western Region display a higher

orientation towards both External Values and Internal Individual Values (p

value <0.05) compared to the other regions. There is no significant

difference in the orientation towards Internal Interpersonal Values across

regional back ground of the respondents.

39) Fun and enjoyment of life and sense of accomplishment, were the only two

values that did not reveal any significant difference in the level of influence

on male and female respondents.

40) Young adults from the West showed a higher level of influence by the values

Sense of Belonging (p<0.05), Security and comfort (p<0.05) and Self

Respect (p<0.05), than the other regions. Young adults from the North

showed higher level of influence of the value Being Independent (p<0.01).

228

SUGGESTIONS FOR APPAREL MANUFACTURERS AND FASHION

DESIGNERS

1) Manufacturers and Fashion designers should give utmost importance to the

quality aspects more than any other attribute of the apparel as quality is

considered as the most important criteria for purchase decision for apparels

by young adults.

2) The study revealed that young adults are perfectionists and besides being

quality conscious they also look for value for money in their purchase

decisions for apparels. This aspect should be factored into all product

development decisions for apparels.

3) Manufacturers and Fashion designers should endeavour to understand the

value systems of their target consumers. This calls for research on the ethnic

and cultural background and the value systems of the consumers. For this

purpose, they should conduct surveys with questionnaires that gather data to

understand the underlying values systems. The Value-Shopping Style model

presented through this study can be used by them as a tool to gather more

information about their target consumers.

4) Structured focus group interviews should also be conducted for different age

groups, ethnic groups, education levels and geographic regions to understand

the differences in values, beliefs, and customs that have a direct bearing on

their behaviour as a consumer.

5) Brands have to constantly keep pace with the speed of communication

among young adult peer groups on the latest trends and market environment

and strive to be part of their conversations. Young adults want better quality,

more value-for-money, superior experience and other value add. Though the

modern youth do not run after designer clothes, their wardrobes are up to

date. Most of them make additions to their wardrobes frequently to keep up-

to-date in fashion.

229

6) Brands should enhance their focus on the semi-urban youth market. They are

emerging as digital savvy and even the consumption pattern is growing

rapidly like in the metros. Hence brands should aim at reaching out the semi-

urban young population in a much bigger way by using a mix of various

marketing activities. However, the metro youth require a little more

sophisticated marketing strategy compared to their semi –urban counterparts.

SUGGESTIONS FOR APPAREL MARKETERS / RETAILS OUTLETS

1) There should be a paradigm shift in the mind set of marketers to consider

consumers as individuals with unique values and beliefs that determine their

buying behaviour. They should transcend from focusing on demographic

aspects and move to psychographic aspects.

2) Every group or society has a culture, and cultural influence on the buying

behaviour may vary greatly from place to place. International and National

marketers must understand the underlying culture in each of their markets

and adapt their marketing strategies accordingly.

3) Marketers should always try to study cultural shifts in order to discover new

products that might be the need of the market.

4) Marketers should highlight the quality features of the apparels in

advertisements to attract the attention of this consumer segment.

5) Marketers should frame their product and communication strategy in such a

way that it appeals to the Perfectionist and Quality Conscious young adult

population.

6) Marketers should understand the digital shift that is prevailing in the retail

environment and learn to communicate to the young adults using different

media. They should look at four mediums to connect with young people

namely; television & radio, social media, digital (mobile applications)

and real live space such as music concerts. Social media such as Face Book,

230

Twitter and YouTube is where the youth today interact actively most of the

time.

7) E-commerce can be used effectively to connect with the young adult

population. Marketers can offer additional services such as flexible payment

options, cash on delivery, and flexible return policy. Online shopping comes

with several benefits of shopping convenience, time saving, fuel saving

and privilege of being able to compare brands/styles/prices easily, through

the internet platform.

8) In the context of commercial communication with frequent apparel

purchasers, the marketer should also emphasize outer-directed values such as

‘Fun and enjoyment of Life’ and ‘Warm Relationship with Others’, rather

than inner-directed values such as Self-fulfillment, Self Respect, and Being

Independent. This is because consumers placing importance on outer-

directed values are more likely to be fashion-conscious and recreational than

consumers who give more importance to inner-directed values.

9) Marketers aware of the recreational shoppers among young Indians can

provide pleasant environments that will attract this type of consumer without

neglecting quality.

CONCLUSION

Several managerial implications might be derived from this study. Apparel

manufacturers, fashion designers and marketers might use the findings to segment

consumers according to the value-shopping style segments, to target and position

their products more effectively. Multi-national companies can use the findings of

this study to tailor their marketing strategies to specific characteristics of consumers

while entering the Indian market.

Personal Values may prove to be one of the most powerful explanations of,

and influences on, consumer behaviour. This research will contribute to the body of

consumer behaviour literature by investigating the influence of personal values on

the Consumer decision-making styles of young adults using the List of Values and

231

the Consumer Style Inventory. The study has high relevance from the Indian

context on several aspects due to the following reasons: The study focuses on the

youth population, which is the major demographic dividend of the entire population

of the country. This consumer segment is the trend setters for the others and also

they offer longevity of market. It makes a lot of sense to develop specific marketing

strategies for this segment that would be sustainable in the long run. The study

focuses on apparels which are the most frequently purchased items by young adults.

In India psychographic profiling of consumers is still in its stage of infancy.

The study focuses on values as the important psychographic variable that influences

shopping styles, especially for apparels. This knowledge helps marketers to predict

consumer behaviour more accurately than the other psychographic variables such as

attitudes, product attributes, product classification, and life style.

It is therefore concluded that personal values have significant influence on

the young adults shopping behaviour for apparels in Bangalore, India. The findings

of the present study are statistically relevant and can be used as basis for strategic

decisions-making by apparel manufacturers, fashion designers and marketers.

Findings of the study also contribute to knowledge and theory in the relevant area

and can be used as a model for further research.

SCOPE FOR FURTHER RESEARCH

The study was conducted in the city of Bangalore, and it can be extended to

other parts of the country to substantiate the findings and generalise the apparel

purchasing behaviour of young adults in India.

The age group of the respondents could also be expanded to include

consumers of other or all age groups.

Focussed studies can also be done on only either male or female consumers to

explore in depth the influence of values on their buying behaviour.

In the present study, influence of values on the apparels purchase behaviour is

studied. Other consumer items such as footwear, bags and other accessories,

232

perfumes, FMCG products, durable goods etc., could be considered and the general

values influencing the shopping behaviour could be identified.

The Value-Shopping Style model could be tested with other reference groups

and other consumer items.

The study revealed that the least manifested shopping style among the young

adult respondents in Bangalore is the Brand consciousness / Price equals quality

shopping style. This aspect alone could be researched to confirm its applicability in

other regions and age groups.

The study also revealed that the young adults are price conscious and seek

value for the price paid for the apparels. A further study could be undertaken to

validate this finding with young adult population of other states/regions.

*****

vi

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http://corporate.shoppersstop.com/corporate/history.aspx

QUESTIONNAIRE

A STUDY ON THE INFLUENCE OF PERSONAL VALUES ON THE

SHOPPING STYLES OF YOUNG ADULTS TOWARDS PURCHASE OF

APPARELS IN BANGALORE CITY, INDIA

Dear Sir / Madam,

This is an academic research study conducted as part of the PhD program of

Bharathidasan University, Trichy.

Psychographic variables are attributes relating to personality, values, attitudes,

interests, or lifestyles. Of these, Values have profound influence on consumer

behaviour. Values are the core principles that an individual upholds in life

which directs thought and drives action. This study aims to gain an insight into

the influence of values on the youth buying behaviour towards apparels. Studies

on consumer values would help marketers understand why consumers make the

choices they do and help them determine how to approach customers belonging to a

particular segment.

Your participation in the survey is very much appreciated and I assure you that the

information obtained in this study will be kept confidential and will be used only for

research purposes.

Yours Truly, Nithila Vincent Bangalore - 29

QUESTIONNAIRE No:____________

I. DEMOGRAPHIC DETAILS (PLEASE TICK)

a. Gender: Male (______) Female (______)

b. Age: 18-20 (______) 21-23 (______) 24-26 (______)

c. Educational Qualifications: UG (______) PG (______) Others (______)

d. Occupation: UG Student (______) PG student (______)

Private Employed (______) Government employed (______) Self

Employed (______)

e. Annual Income: Nil (_____) less than 50000 p.a (_____)

50,000-1,00,000 p.a (_____) 1 Lac – 3 Lakhs p.a (______)

3 Lakhs-5 Lakhs p.a (______) above 5 lakhs p.a (______)

f. Pocket Money Allowance: Nil (______) less than 500 per month

(______) 500-1000 per month (_____) 1000-3000 per month (_____)

3000-6000 per month (_____) >6000 per month (_____)

g. State of origin: _________________ Mother tongue: _______________

II SURVEY ON VALUES

The following are a list of ‘values’ that some people look for or want out of life. Please study the list carefully and then;

Rate each value on how important it is in your daily life. (1= least important and 9= very Important.. Please mark every item. 1(L) 2 3 4 5 6 7 8 9(H) 1. Sense of Belonging (Feeling that Family & friends care about me)

2. Simplicity (Being unassuming, straight forward, down to earth)

3. Warm Relationships with others (maintain cordial relations)

4. Self-fulfillment (Being creative, enjoy what I do, inner harmony)

5. Being Well-respected (Having social recognition, respect & approval by others)

6. Fun and enjoyment of life (Seeking adventure, Novelty & change, enjoying food & leisure)

7. Security & Comfort (Safety, secure surroundings)

8. Self-respect (Self-esteem, belief in one’s own worth, preserving self-image)

9. A sense of accomplishment (Being successful, doing something that I’ve never done before)

10. Being Independent (Self Reliant, Self Sufficient)

III. CONSUMER SHOPPING STYLES INVENTORY

The following statements describe consumer shopping styles. Please study the list carefully and then indicate your agreement ranging from ‘strongly disagree’ to ‘strongly agree’. Scale: 1- Strongly disagree, 2 – Disagree, 3 – Neither Agree nor Disagree, 4 – Agree, 5 – Strongly Agree

S.No 1 2 3 4 5

1 Getting very good quality of clothes is very important to me.

2 When it comes to purchasing clothes, I try to get the very best or perfect choice.

3 In general, I usually try to buy the best overall quality of apparels.

4 The well-known national brands are for me.

5 The more expensive brands are usually my choices.

6 The higher the price of the apparel, the better the quality.

7 I usually have one or more outfits of the very newest style.

8 I keep my wardrobe up-to-date with the changing fashions.

9 Fashionable, attractive styling is very important to me.

10 Shopping for clothes is not a pleasant activity to me.

11 Going shopping for clothes is one of the most enjoyable activities of my life.

12 Shopping the stores for clothes wastes my time.

13 I buy most of my clothes at sale prices.

14 The lowest price outfits are usually my choice.

15 I look carefully to find the best value for the money.

16 I should plan my shopping more carefully than I do.

17 I am impulsive when purchasing clothes.

18 Often I make careless purchases of clothes I later wish I had not.

19 There are so many brands to choose from that I often feel confused.

20 Sometimes it is hard to choose which stores to shop for clothes.

21 The more I learn about apparel brands, the harder it seems to choose the best.

22 I have favourite brands I buy over and over.

23 Once I find a brand I like, I stick with it.

24 I go to the same stores each time I shop.

Additional Goodness of Fit and Related Measures for the Value-Shopping Style Model

NCP

Model NCP LO 90 HI 90

Default model 3193.878 3004.174 3390.953 Saturated model .000 .000 .000

Independence model 12832.685 12458.923 13212.823

FMIN

Model FMIN F0 LO 90 HI 90

Default model 2.514 2.162 2.034 2.296

Saturated model .000 .000 .000 .000

Independence model 9.091 8.688 8.435 8.946

RMSEA

Model RMSEA LO 90 HI 90 PCLOSE

Default model .065 .063 .067 .000


AIC

Model AIC BCC BIC CAIC

Default model 3932.878 3938.218

Saturated model 1258.000 1288.534

Independence model 13495.685 13497.336

ECVI

Model ECVI LO 90 HI 90 MECVI

Default model 2.663 2.534 2.796 2.666

Saturated model .852 .852 .852 .872

Independence model 9.137 8.884 9.395 9.138

HOELTER

Model HOELTER .05 HOELTER .01

Default model 228 238

Independence model 72 75

Execution time summary

Minimization: 1.232

Miscellaneous: .094

Bootstrap: .000

Total: 1.326

Inter-construct correlations and Squared Inter-Construct Correlation estimates (SIC) .Correlations: (Group number 1 - Default model)

Shopping Styles

Shopping Styles Estimate SIC

Perfectionist/High Quality Conscious <--> Brand Conscious/Price

Equals Quality 0.648 0.419904

Perfectionist/High Quality Conscious <--> Novelty and Fashion

Conscious 0.51 0.2601

Perfectionist/High Quality Conscious <--> Recreational and Shopping

Conscious 0.313 0.097969

Perfectionist/High Quality Conscious <--> Price Conscious/Value for

money 0.097 0.009409

Perfectionist/High Quality Conscious <--> Impulsiveness/Careless 0.288 0.082944

Perfectionist/High Quality Conscious <--> Confused by Overchoice 0.26 0.0676

Habitual/Brand Loyal <--> Perfectionist/High Quality Conscious 0.469 0.219961

Brand Conscious/Price Equals Quality <--> Novelty and Fashion

Conscious 0.64 0.4096

Brand Conscious/Price Equals Quality <--> Recreational and Shopping

Conscious 0.108 0.011664

Brand Conscious/Price Equals Quality <--> Impulsiveness/Careless 0.243 0.059049

Brand Conscious/Price Equals Quality <--> Confused by Overchoice 0.247 0.061009


<--> Brand Conscious/Price Equals Quality 0.523 0.273529

Novelty and Fashion Conscious <--> Recreational and Shopping Conscious 0.271 0.073441

Novelty and Fashion Conscious <--> Impulsiveness/Careless 0.264 0.069696

Novelty and Fashion Conscious <--> Confused by Overchoice 0.261 0.068121

Habitual/Brand Loyal <--> Novelty and Fashion Conscious 0.449 0.201601

Recreational and Shopping Conscious <--> Price Conscious/Value for

money 0.053 0.002809

Recreational and Shopping Conscious <--> Impulsiveness/Careless 0.071 0.005041

Recreational and Shopping Conscious <--> Confused by Overchoice 0.079 0.006241

Habitual/Brand Loyal <--> Recreational and Shopping Conscious 0.125 0.015625

Price Conscious/Value for money <--> Impulsiveness/Careless 0.182 0.033124

Price Conscious/Value for money <--> Confused by Overchoice 0.089 0.007921

Habitual/Brand Loyal <--> Price Conscious/Value for money 0.017 0.000289

Impulsiveness/Careless <--> Confused by Overchoice 0.646 0.417316

Habitual/Brand Loyal <--> Confused by Overchoice 0.345 0.119025

Habitual/Brand Loyal <--> Impulsiveness/Careless 0.266 0.070756 Covariances among the Constructs

Estimate S.E. C.R. P


<--> Brand Conscious/Price Equals Quality

.231 .019 11.902 .000


<--> Novelty and Fashion Conscious

.233 .020 11.849 .000


<--> Recreational and Shopping Conscious

.154 .020 7.891 .000


<--> Price Conscious/Value for money

.053 .018 2.952 .003


<--> Impulsiveness/Careless .113 .018 6.475 .000


<--> Confused by Overchoice .137 .019 7.174 .000


<-->


.259 .023 11.394 .000



.263 .023 11.651 .000



.048 .016 2.915 .004





Habitual/Brand Loyal <--> Brand Conscious/Price Equals Quality

.261 .024 10.864 .000

Estimate S.E. C.R. P



.154 .022 6.965 .000




<--> Confused by Overchoice

.159 .022 7.174 .000



.286 .026 10.901 .000

Recreational and Shopping Conscious <-->


.036 .023 1.528 .126


<--> Impulsiveness/Careless

.035 .021 1.641 .101


<--> Confused by Overchoice

.052 .024 2.181 .029



.086 .026 3.303 .000





Habitual/Brand Loyal <--> Price Conscious/Value for money

.013 .026 .509 .611

Impulsiveness/Careless <--> Confused by Overchoice .339 .030 11.441 .000

Habitual/Brand Loyal <--> Impulsiveness/Careless .147 .025 5.941 .000

Habitual/Brand Loyal <--> Confused by Overchoice .254 .028 9.070 .000

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