A STUDY ON THE INFLUENCE OF PERSONAL VALUES ON THE SHOPPING STYLES OF YOUNG ADULTS TOWARDS PURCHASE OF APPARELS IN CITY, , 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 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 PAGE TITLE NO. NO.

1 INTRODUCTION 01

2 PROFILE OF THE STUDY AREA AND LEADING 30 APPAREL RETAILERS IN BANGALORE, INDIA

3 REVIEW OF LITERATURE AND DESIGN OF THE 50 STUDY

4 PERSONAL VALUES AND SHOPPING STYLES 101

5 ANALYSIS & INTERPRETATION OF DATA 119

6 FINDINGS, SUGGESTIONS & CONCLUSION 217

BIBLIOGRAPHY vi

APPENDIX

LIST OF TABLES

TABLE PAGE TITLE NO 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 138 Conscious style 19 Hierarchy of items under Brand Conscious/Price Equals 139 Qualitystyle 20 Hierarchy of items under Novelty and Fashion 139 Consciousstyle 21 Hierarchy of items under Recreational and Shopping 140 Consciousstyle 22 Hierarchy of items under Price Conscious/Value for money 141 style 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

i TABLE PAGE TITLE NO 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 150 Shopping Styles 31 Relationship between the value Simplicity and Shopping 151 Styles 32 Relationship between the value Warm Relationships with 152 Others and Shopping Styles 33 Relationship between the value Self-Fulfillment and 153 Shopping Styles 34 Relationship between the value Being Well Respected and 154 Shopping Styles 35 Relationship between the value Fun and Enjoyment of life 155 and Shopping Styles 36 Relationship between the value Security & Comfort and 156 Shopping Styles 37 Relationship between the value Self Respect and Shopping 157 Styles 38 Relationship between the value Sense of Accomplishment 158 and Shopping Styles 39 Relationship between the value Being Independent and 159 Shopping Styles 40 Summary of Goodness-of-fit measures for the ‘Consumer 162 Style Inventory’ used in the study - CSI 41 Relative Chi Square (CMIN/df) (Chi-square/Degrees of 163 freedom) - CSI 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 168 Coefficient Alpha for Shopping Styles - CSI 46 Summary of Goodness-of-fit measures for the ‘Value – 170 Shopping Style’ measurement model - VSM

ii TABLE PAGE TITLE NO NO 47 Relative Chi Square (CMIN/df) (Chi-square/Degrees of 171 freedom) - VSM 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 175 adults towardsapparels 52 Influence of values on the ‘Perfectionist/High Quality 177 Conscious’ shopping style 53 Influence of values on the ‘Brand Conscious/Price Equals 178 Quality’ shopping style 54 Influence of values on the ‘Novelty and Fashion Conscious’ 179 shopping style 55 Influence of values on the ‘Recreational and Shopping 180 Conscious’ shopping style 56 Influence of values on the ‘Price Conscious/Value for money’ 181 shopping style 57 Indicating influence of values on the 182 ‘Impulsiveness/Careless’ shopping style 58 Influence of values on the ‘Confused by Overchoice’ 183 shopping style 59 Influence of values on the ‘Habitual/Brand Loyal’ shopping 184 style 60 Squared multiple correlations (R squared values) for 185 Shopping Styles 61 Nature of Influence of Values on the Perfectionist/High 186 Quality Conscious Shopping Style 62 Nature of Influence of Values on the ‘Brand 187 Consciousness/Price Equals Quality’Shopping Style 63 Nature of Influence of Values on the ‘Novelty and Fashion 188 Conscious’Shopping Style 64 Nature of Influence of Values on the ‘Recreational and 189 Shopping Conscious’ Shopping Style 65 Nature of Influence of Values on the ‘Price Conscious/Value 190 for Money’ Shopping Style

iii TABLE PAGE TITLE NO NO 66 Nature of Influence of Values on the 191 ‘Impulsiveness/Careless’Shopping Style 67 Nature of Influence of Values on the ‘Confused by 192 Overchoice’ Shopping Style 68 Nature of Influence of Values on the ‘Habitual/Brand Loyal’ 193 Shopping Style 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 199 Levels 72 ANOVA Indicating differences in shopping styles across 201 education level of young adults 73 Differences in mean for shopping styles across Regions 203 74 ANOVA Indicating differences in mean for shopping styles 204 across Regions 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 208 across Regional Background 78 ANOVA showing Value Orientations of Young Adults across 209 Regional Background 79 Differences in Mean for level of influence of individual 210 Values across Gender 80 t Test for Level of Influence of individual Values across 211 Gender 81 Differences in Mean for level of influence of individual 213 Values across Regional Background 82 ANOVA showing level of influence of individual Values 215 across Regional Background

iv

LIST OF FIGURES

FIGURE PAGE TITLE NO 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 174 Model Fit.

v 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.

1 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

2 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.

3 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

4 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 0-14 years: 29.3% (male 187,386,162/female 165,345,284)

(2012 est.) 15-24 years: 18.2% (male 116,019,042/female 103,660,359) 25-54 years: 40.2% (male 249,017,538/female 235,042,251) 55-64 years: 6.8% (male 41,035,270/female 40,449,880) 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.

5 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 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

6 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

7 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

8 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

9 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.

10 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 ème students for apparel products. 6 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.

11 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

12 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.

13 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

14 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.

15 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.

16 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

17 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.

18 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.

19 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

20 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

21 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

H4 There is no significant difference in the shopping styles of young adults towards purchase of apparels across education levels.

H5 There is no significant difference in the shopping styles of young adults towards purchase of apparels across regional background.

22 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 towards External Values, Internal Interpersonal Values and Internal 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/

23 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.

24 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 consumersெ decision-making styles. Journal of Consumer Affairs, 20 (2), 267-279.

25 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

26 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)

27 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

28 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.

29 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

30 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 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 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

31 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 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 , all date from the Chola era.

A succession of South Indian dynasties ruled the region of Bangalore until in 1537 A. D., KempéGowdƗ—a feudatory ruler under the — established a mud fort considered to be the foundation of modern Bangalore. Following transitory occupation by the MarƗthƗs 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

32 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

33 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 , 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 and .

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: Sex Ratio in Karnataka 1000 males for Hindu - 83%, every 968 females Muslim - 11%, Christian - 4%, Jains - 0.78% and Buddhist - 0.73%

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

34 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: Sex Ratio in Bangalore 1000 males for Hindu –79.4%, every 908 females Muslim – 13.4%, Christian –5.8%, Jains –1.1% [Provisional population totals census of India 2011 Govt of India]

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%).

35 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

36 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 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 , 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

37 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

38 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 . 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.

39 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 , 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,

40 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

41 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: , Bommasandra, , , 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

42 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/

43 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

44 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

45 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.

46 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

47 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

48 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

49 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.

50 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.

51 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.

52 (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.

53 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

54 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.

55 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.

56 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.

57 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.

58 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.

59 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.

60 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.

61 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.

62 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.

63 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.

64 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

65 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.

66 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.

67 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.

68 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.

69 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. øúletmeAraúWÕrmalarÕDergisi,2(3), 45-62 pp. 114ChienHou, Zhung-Hsien Lin. (2011) Shopping Styles Of Working Taiwanese Females.

70 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.

71 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.

72 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.

73 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.

74 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.

75 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.

76 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.

77 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.

78 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.

79 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.

80 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.

81 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.

82 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.

83 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.

84 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.

85 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.

86 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). .com.

87 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 , South 438 Bangalore 2 Esteem Mall Hebbal, North Bangalore 321 3 Rajaji Nagar, West 345 Bangalore 4 Phoenix Market City Whitefield, East 374 Bangalore 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.

88 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.

89 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

90 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.

91 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

92 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

93 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

94 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

95 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.

96 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

97 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: ȝ1 = ȝ2

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: ȝ1ȝ2

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"

98 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.

99 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.

100 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

101 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

102 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

103 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:

x RVS -Rokeach Value Survey (1973) x VALS -Values and Lifestyles (1978) x LOV - List of Values – Kahle (1983) x 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

104 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/

105 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.

106 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

107 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.

108 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.

109 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.

110 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 DamirAniü, 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.

111 TABLE: 07

DESCRIPTION OF CONSUMER DECISION-MAKING STYLE/ TRAITS

No. Decision-making Style / Trait Characteristics 1 Perfectionist, high-quality A characteristic measuring the degree to which conscious a consumer searches carefully and systematically for the best quality in products 2 Brand consciousness, “price Measuring a consumer’s orientation to buying equals quality” 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 A characteristic measuring the degree to which conscious a consumer finds shopping a pleasant activity and shops just for the fun of it. 5 Price conscious/value for the A characteristic identifying those with money consciousness 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

112 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.

113 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. *

114 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.

115 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.

116 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.

117 ‘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:

PERSONAL VALUES SHOPPING STYLES

1. Self-respect, 1. Perfectionist, high quality conscious consumer 2. Security, 2. Brand conscious, “price equals 3. Warm relationships with others, quality” consumer 4. Self fulfillment, 3. Novelty-fashion conscious consumer 5. A sense of accomplishment, 4. Recreational and hedonistic 6. Being respected, shopping consciousness 7. A sense of belonging, INFLUENCE 5. Price conscious, “value for money” consumer 8. Fun and enjoyment of life, 6. Impulsive, careless consumer 9. Simplicity 7. Confused by overchoice 10. Being Independent consumer 8. Habitual, brand loyal consumer

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).

118 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

119 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

GENDER OF RESPONDE Female NTS 0% 45.6% Male 54.4%

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%).

120 TABLE: 10 Education Level of Respondents

Education Level Frequency Percent UG 1131 76.5 PG 289 19.6 Others 58 3.9 [Diploma/PUC etc] TOTAL 1478 100

Source: Primary data

FIG.5

Educational Level of Respondents

3.9%

19.6% PG UG PG Others 76.5% UG

Source: Primary data

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.

121 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

Source: Primary data

FIG. 6 Regional Background of Respondents

80 71.2% 70 60 50 40 30 20 11.2% 10.6% 7% 10 0 South East North West

Source: Primary data

122 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.

123 TABLE:12

Reliability Statistics for List of Values

Scale: ALL VARIABLES

Reliability Statistics Cronbach's Alpha N of Items .903 10

Source: Primary data

Item-Total Statistics Scale Mean Scale Corrected Cronbach's if Item Variance if Item-Total Alpha if Item Deleted Item Deleted Correlation Deleted

1. Sense of Belonging 65.92 149.876 .609 .897

2.Simplicity 66.69 149.235 .607 .897

3. Warm Relationships with 66.50 147.728 .671 .893 others

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 66.37 146.658 .684 .892 accomplishment

10. Being Independent 66.29 146.827 .613 .897

Source: Primary data

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.

124 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

Source: Primary data

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-

125 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.

126 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

127 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.

128 TABLE: 14

Reliability Statistics for Value Dimensions

Reliability Statistics

Cronbach's Alpha N of Items

.884 3

Source: Primary data

Item-Total Statistics

Scale Mean Scale Corrected Cronbach's if Item Variance if Item-Total Alpha if Deleted Item Deleted Correlation Item Deleted

External Values 14.6127 7.787 .772 .838

Internal Interpersonal 14.8100 7.366 .765 .846 Values

Internal Individual 14.7911 7.919 .790 .823 Values

Source: Primary data

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.

129 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 7.49 1.48070 respected, Security & comfort]

Internal Individual Values [Self-fulfillment, Self respect, A sense 7.31 1.44328 of accomplishment, Simplicity, Being Independent]

Internal Interpersonal Values [Warm relationships with others, fun 7.29 1.57839 and enjoyment of life]

Source: Primary data

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.

130 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.

131 TABLE: 16

Reliability Statistics for Consumer Style Inventory

Scale: All Variables

Reliability Statistics

Alpha N of Items

.787 24

Source: Primary data

Item-Total Statistics Scale Scale Corrected Cronbach's Mean if Variance if Item-Total Alpha if Item Item Item Deleted Correlation Deleted Deleted Getting very good quality of clothes is 74.04 106.046 .433 .774 very important to me. When it comes to purchasing clothes, I 73.92 105.325 .498 .771 try to get the very best or perfect choice. In general, I usually try to buy the best overall 74.18 106.217 .462 .773 quality of apparels. The well-known national brands are for 74.81 104.885 .472 .772 me. The more expensive brands are usually my 75.28 103.862 .478 .771 choices.

132 The higher the price of the apparel, the better 74.92 106.829 .311 .780 the quality. I usually have one or more outfits of the very 74.80 105.293 .449 .773 newest style. I keep my wardrobe up- to-date with the 75.07 104.006 .473 .771 changing fashions. Fashionable, attractive styling is very 74.71 104.082 .456 .772 important to me. Shopping for clothes is not a pleasant activity 74.49 111.759 .097 .793 to me. Going shopping for clothes is one of the 74.74 103.828 .403 .775 most enjoyable activities of my life. Shopping the stores for 74.50 111.057 .144 .789 clothes wastes my time. I buy most of my 74.75 112.262 .125 .789 clothes at sale prices. The lowest price outfits 75.25 116.826 -.090 .800 are usually my choice. I look carefully to find the best value for the 73.92 113.812 .059 .792 money. I should plan my shopping more 74.39 109.419 .237 .784 carefully than I do. I am impulsive when 74.64 107.818 .343 .778 purchasing clothes.

133 Often I make careless purchases of clothes I 74.82 107.902 .266 .783 later wish I had not. There are so many brands to choose from 74.57 105.414 .401 .775 that I often feel confused. Sometimes it is hard to choose which stores to 74.47 106.907 .345 .778 shop for clothes. The more I learn about apparel brands, the 74.58 106.763 .375 .777 harder it seems to choose the best. I have favourite brands 74.53 102.777 .507 .769 I buy over and over. Once I find a brand I 74.69 106.200 .362 .777 like, I stick with it. I go to the same stores 74.78 108.955 .236 .784 each time I shop.

Source: Primary data

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.

134 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

Source: Primary data

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).

135 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.

136 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.

137 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 Mean Std. Deviation Three-item alpha =0.752

When it comes to purchasing clothes, I try to get 3.95 .943 the very best or perfect choice.

Getting very good quality of clothes is very 3.82 .994 important to me.

In general, I usually try to buy the best overall 3.69 .920 quality of apparels.

Source: Primary data

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.

138 TABLE: 19

Hierarchy of items under Brand Conscious/Price Equals Quality style

Brand Conscious/Price Equals Quality Three-item alpha =0.695 Mean Std. Deviation

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 2.59 1.109 quality.

Source: Primary data

The above table describes the hierarchy of the individual items under the ‘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 Std. Mean Three-item alpha =0.749 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

Source: Primary data

139 The above table describes the hierarchy of the individual items under the ‘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. Mean Three-item alpha =0.675 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 3.13 1.269 activities of my life.

Source: Primary data

The above table describes the hierarchy of the individual items under the ‘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.

140 TABLE:22

Hierarchy of items under Price Conscious/Value for money style

Price Conscious/Value for money Mean Std. Deviation Three-item alpha =0.353

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

Source: Primary data

The above table describes the hierarchy of the individual items under the ‘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. Mean Three-item alpha =0.530 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 3.05 1.187 not.

Source: Primary data

141 The above table describes the hierarchy of the individual items under the ‘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 Mean Std. Deviation Three-item alpha =0.761

Sometimes it is hard to choose which stores to 3.40 1.092 shop for clothes.

There are so many brands to choose from that I 3.30 1.119 often feel confused.

The more I learn about apparel brands, the 3.29 1.039 harder it seems to choose the best.

Source: Primary data

The above table describes the hierarchy of the individual items under the ‘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.

142 TABLE:25

Hierarchy of items under Habitual/Brand Loyal style

Habitual/Brand Loyal Mean Std. Deviation Three-item alpha =0.680

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

Source: Primary data

The above table describes the hierarchy of the individual items under the ‘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.

143 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 Internal Internal External Interpersonal Individual values values values

Pearson Correlation 1 .701** .734** External values Sig. (2-tailed) .000 .000 N 1477 1477 1477

Pearson Correlation .701** 1 .728** Internal Interpersonal values Sig. (2-tailed) .000 .000 N 1477 1478 1478

Pearson Correlation .734** .728** 1 Internal Individual values Sig. (2-tailed) .000 .000 N 1477 1478 1478 **. Correlation is significant at the 0.01 level (2-tailed).

Source: Primary data

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.

144 TABLE:27

Intra-Correlations among individual Values

Correlations sense being security warm fun & self sense of being of Simplicity selfulillment well & relationships enjoyment respect accomplishment independent belong respected comfort Pearson 1 .444** .530** .450** .539** .445** .475** .486** .403** .338** Correlation sense of belong Sig. (2- .000 .000 .000 .000 .000 .000 .000 .000 .000 tailed) N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478 Pearson .444** 1 .575** .474** .479** .402** .389** .476** .444** .404** Correlation simplicity Sig. (2- .000 .000 .000 .000 .000 .000 .000 .000 .000 tailed) N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478 Pearson .530** .575** 1 .538** .538** .468** .455** .503** .464** .404** Correlation warm relation- Sig. (2- ships .000 .000 .000 .000 .000 .000 .000 .000 .000 tailed) N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478 Pearson .450** .474** .538** 1 .521** .499** .442** .548** .503** .465** Correlation selfulill-ment Sig. (2- .000 .000 .000 .000 .000 .000 .000 .000 .000 tailed) N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478 Pearson .539** .479** .538** .521** 1 .501** .526** .624** .540** .475** Correlation being well Sig. (2- respected .000 .000 .000 .000 .000 .000 .000 .000 .000 tailed) N 1477 1477 1477 1477 1477 1477 1477 1477 1477 1477 Pearson .445** .402** .468** .499** .501** 1 .506** .512** .499** .456** Correlation fun & Sig. (2- enjoyment .000 .000 .000 .000 .000 .000 .000 .000 .000 tailed) N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478 Pearson .475** .389** .455** .442** .526** .506** 1 .557** .488** .433** Correlation security & Sig. (2- comfort .000 .000 .000 .000 .000 .000 .000 .000 .000 tailed) N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478 Pearson .486** .476** .503** .548** .624** .512** .557** 1 .584** .535** Correlation self respect Sig. (2- .000 .000 .000 .000 .000 .000 .000 .000 .000 tailed) N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478 Pearson .403** .444** .464** .503** .540** .499** .488** .584** 1 .608** sense of Correlation accomplishmen Sig. (2- .000 .000 .000 .000 .000 .000 .000 .000 .000 t tailed) N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478 Pearson .338** .404** .404** .465** .475** .456** .433** .535** .608** 1 Correlation being Sig. (2- independent .000 .000 .000 .000 .000 .000 .000 .000 .000 tailed) N 1478 1478 1478 1478 1477 1478 1478 1478 1478 1478 **. Correlation is significant at the 0.01 level (2-tailed).

Source: Primary data

145 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 Brand Price Brand perfectionist novelty Recreational impulsive confused conscious conscious loyalty Pearson 1 .474** .397** .228** -.031 .178** .192** .319** Correlation Perfectionist, high- Sig. (2- quality conscious .000 .000 .000 .235 .000 .000 .000 tailed) N 1478 1477 1478 1478 1478 1475 1478 1478 Pearson .474** 1 .470** .089** -.075** .157** .193** .324** Correlation Brand consciousness, Sig. (2- “price equals quality” .000 .000 .001 .004 .000 .000 .000 tailed) N 1477 1477 1477 1477 1477 1474 1477 1477 Pearson .397** .470** 1 .221** -.034 .168** .201** .290** Correlation Novelty and fashion Sig. (2- conscious .000 .000 .000 .187 .000 .000 .000 tailed) N 1478 1477 1478 1478 1478 1475 1478 1478 Pearson .228** .089** .221** 1 -.109** .049 .071** .066* Correlation Recreational and Sig. (2- shopping conscious .000 .001 .000 .000 .058 .006 .011 tailed) N 1478 1477 1478 1478 1478 1475 1478 1478 Pearson -.031 -.075** -.034 -.109** 1 .151** .050 .068** Price conscious/value Correlation for the money Sig. (2- .235 .004 .187 .000 .000 .055 .009 consciousness tailed) N 1478 1477 1478 1478 1478 1475 1478 1478 Pearson .178** .157** .168** .049 .151** 1 .414** .159** Correlation Impulsiveness/Careless Sig. (2- .000 .000 .000 .058 .000 .000 .000 tailed) N 1475 1474 1475 1475 1475 1475 1475 1475 Pearson .192** .193** .201** .071** .050 .414** 1 .217** Correlation Confused by Sig. (2- Overchoice .000 .000 .000 .006 .055 .000 .000 tailed) N 1478 1477 1478 1478 1478 1475 1478 1478 Pearson .319** .324** .290** .066* .068** .159** .217** 1 Correlation Habitual/brand-loyal Sig. (2- .000 .000 .000 .011 .009 .000 .000 tailed) 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).

Source: Primary data

146 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

147 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.

148 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

Source: Primary data

Correlations

Overall values Overall shopping Styles

Pearson Correlation 1 .116**

Overall values Sig. (2-tailed) .000

N 1477 1473

Pearson Correlation .116** 1 Overall Shopping Sig. (2-tailed) .000 Styles N 1473 1474

**. Correlation is significant at the 0.01 level (2-tailed).

Source: Primary data

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.

149 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 Sense of Shopping Styles Remark Belonging Pearson Correlation .109** **. Correlation is significant Perfectionist/High Sig. (2-tailed) .000 at the 0.01 level (2-tailed) Quality Conscious N 1478 Pearson Correlation -.013 Brand Consciousness Sig. (2-tailed) .628 /Price Equals Quality N 1477 Pearson Correlation -.018 Novelty and Fashion Sig. (2-tailed) .494 Conscious N 1478 Pearson Correlation .078** **. Correlation is significant Recreational and Sig. (2-tailed) .003 at the 0.01 level (2-tailed) Shopping Conscious N 1478 Pearson Correlation .036 Price Conscious/Value Sig. (2-tailed) .167 for the money N 1478 Pearson Correlation -.001 Impulsiveness/Careless Sig. (2-tailed) .960 N 1475 Pearson Correlation .003 Confused by Overchoice Sig. (2-tailed) .911 N 1478 Pearson Correlation .032 Habitual/Brand Loyalty Sig. (2-tailed) .221 N 1478 Source: Primary data

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.

150 TABLE: 31 Relationship between the value Simplicity and Shopping Styles

Correlations Shopping Styles Simplicity Remark ** Pearson Correlation .076 **. Correlation is Perfectionist/High Quality Sig. (2-tailed) .004 significant at the 0.01 Conscious N 1478 level (2-tailed).1 Pearson Correlation .003 Brand Consciousness/Price Sig. (2-tailed) .904 Equals Quality N 1477 Pearson Correlation -.021 Novelty and Fashion Sig. (2-tailed) .416 Conscious N 1478 Pearson Correlation .043 Recreational and Shopping Sig. (2-tailed) .095 Conscious N 1478 * Pearson Correlation .062 *. Correlation is Price Conscious/Value for Sig. (2-tailed) .017 significant at the 0.05 the money N 1478 level (2-tailed). Pearson Correlation .020 Impulsiveness/Careless Sig. (2-tailed) .446 N 1475 Pearson Correlation .047 Confused by Overchoice Sig. (2-tailed) .071 N 1478 ** Pearson Correlation .084 **. Correlation is Habitual/Brand Loyalty Sig. (2-tailed) .001 significant at the 0.01 N 1478 level (2-tailed).

Source: Primary data

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.

151 TABLE: 32

Relationship between the value Warm Relationships with Others and Shopping Styles

Correlations Shopping Styles Warm Remark Relationships with others Pearson Correlation .131** **. Correlation is Perfectionist/High Quality Sig. (2-tailed) .000 significant at the Conscious 0.01 level (2- N 1478 tailed). Brand Pearson Correlation -.012 Consciousness/Price Sig. (2-tailed) .654 Equals Quality N 1477 Pearson Correlation -.013 Novelty and Fashion Sig. (2-tailed) .623 Conscious N 1478 Pearson Correlation .092** **. Correlation is Recreational and Sig. (2-tailed) .000 significant at the Shopping Conscious 0.01 level (2- N 1478 tailed). Pearson Correlation .087** **. Correlation is Price Conscious/Value for Sig. (2-tailed) .001 significant at the the money 0.01 level (2- N 1478 tailed). Pearson Correlation .038 Impulsiveness/Careless Sig. (2-tailed) .141 N 1475 Pearson Correlation .048 Confused by Overchoice Sig. (2-tailed) .066 N 1478 Pearson Correlation .031 Habitual/Brand Loyalty Sig. (2-tailed) .232 N 1478 Source: Primary data

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.

152 TABLE:33

Relationship between the value Self-Fulfillment and Shopping Styles

Correlations Shopping Styles Self- Remark Fulfillment Pearson Correlation .050 Perfectionist/High Sig. (2-tailed) .055 Quality Conscious N 1478 Brand Pearson Correlation -.042 Consciousness/Price Sig. (2-tailed) .110 Equals Quality N 1477 Pearson Correlation .023 Novelty and Fashion Sig. (2-tailed) .369 Conscious N 1478 Pearson Correlation .051 Recreational and Sig. (2-tailed) .051 Shopping Conscious N 1478 Pearson Correlation .040 Price Conscious/Value Sig. (2-tailed) .123 for the money N 1478 Pearson Correlation -.055* *. Correlation is Sig. (2-tailed) .034 significant at the Impulsiveness/Careless 0.05 level (2- N 1475 tailed). Pearson Correlation .015 Confused by Overchoice Sig. (2-tailed) .553 N 1478 Pearson Correlation .014 Habitual/Brand Loyalty Sig. (2-tailed) .600 N 1478 Source: Primary data

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.

153 TABLE:34

Relationship between the value Being Well Respected and Shopping Styles

Correlations Shopping Styles Being Well Remark Respected Pearson Correlation .150** **. Correlation is Perfectionist/High Sig. (2-tailed) .000 significant at the Quality Conscious 0.01 level (2- N 1477 tailed). Brand Pearson Correlation .028 Consciousness/Price Sig. (2-tailed) .284 Equals Quality N 1476 Pearson Correlation .057* *. Correlation is Novelty and Fashion Sig. (2-tailed) .028 significant at the Conscious 0.05 level (2- N 1477 tailed). Pearson Correlation .099** **. Correlation is Recreational and Sig. (2-tailed) .000 significant at the Shopping Conscious 0.01 level (2- N 1477 tailed). Pearson Correlation -.006 Price Conscious/Value Sig. (2-tailed) .820 for the money N 1477 Pearson Correlation .004 Impulsiveness/Careless Sig. (2-tailed) .874 N 1474 Pearson Correlation .049 Confused by Overchoice Sig. (2-tailed) .061 N 1477 Pearson Correlation .080** **. Correlation is Sig. (2-tailed) .002 significant at the Habitual/Brand Loyalty 0.01 level (2- N 1477 tailed). Source: Primary data

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.

154 TABLE:35 Relationship between the value Fun and Enjoyment of life and Shopping Styles

Correlations Shopping Styles Fun and Remark Enjoyment of life

Pearson Correlation .172** **. Correlation is Perfectionist/High Quality Sig. (2-tailed) .000 significant at the Conscious 0.01 level (2- N 1478 tailed). Pearson Correlation .080** **. Correlation is Brand Consciousness/Price Sig. (2-tailed) .002 significant at the Equals Quality 0.01 level (2- N 1477 tailed). Pearson Correlation .121** **. Correlation is Novelty and Fashion Sig. (2-tailed) .000 significant at the Conscious 0.01 level (2- N 1478 tailed). Pearson Correlation .072** **. Correlation is Recreational and Shopping Sig. (2-tailed) .005 significant at the Conscious 0.01 level (2- N 1478 tailed). Pearson Correlation -.015 Price Conscious/Value for the money Sig. (2-tailed) .553 N 1478 Pearson Correlation .027 Impulsiveness/Careless Sig. (2-tailed) .297 N 1475 Pearson Correlation .075** **. Correlation is significant at the Confused by Overchoice Sig. (2-tailed) .004 0.01 level (2- N 1478 tailed). Pearson Correlation .072** **. Correlation is significant at the Habitual/Brand Loyalty Sig. (2-tailed) .006 0.01 level (2- N 1478 tailed). Source: Primary data

The above table indicates that there is a significant positive relationship 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.

155 TABLE:36 Relationship between the value Security & Comfort and Shopping Styles

Correlations Shopping Styles Security & Remark Comfort Pearson Correlation .115** **. Correlation is Perfectionist/High Sig. (2-tailed) .000 significant at the Quality Conscious 0.01 level (2- N 1478 tailed). Brand Pearson Correlation .011 Consciousness/Price Sig. (2-tailed) .665 Equals Quality N 1477 Pearson Correlation .054* *. Correlation is Novelty and Fashion Sig. (2-tailed) .038 significant at the Conscious 0.05 level (2- N 1478 tailed). Pearson Correlation .115** **. Correlation is Recreational and Sig. (2-tailed) .000 significant at the Shopping Conscious 0.01 level (2- N 1478 tailed). Pearson Correlation .029 Price Conscious/Value for the money Sig. (2-tailed) .267 N 1478 Pearson Correlation .016 Impulsiveness/Careless Sig. (2-tailed) .528 N 1475 Pearson Correlation .069** **. Correlation is Confused by Sig. (2-tailed) .008 significant at the Overchoice 0.01 level (2- N 1478 tailed). Pearson Correlation .064* *. Correlation is Habitual/Brand Sig. (2-tailed) .015 significant at the Loyalty 0.05 level (2- N 1478 tailed). Source: Primary data

The above table indicates that there is a significant positive relationship 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.

156 TABLE:37 Relationship between the value Self Respect and Shopping Styles

Correlations Shopping Styles Self Respect Remark Pearson Correlation .109** **. Correlation is Perfectionist/High Sig. (2-tailed) .000 significant at the Quality Conscious 0.01 level (2- N 1478 tailed). Brand Pearson Correlation -.036 Consciousness/Price Sig. (2-tailed) .171 Equals Quality N 1477 Pearson Correlation .027 Novelty and Fashion Sig. (2-tailed) .294 Conscious N 1478 Pearson Correlation .081** **. Correlation is Recreational and Sig. (2-tailed) .002 significant at the Shopping Conscious 0.01 level (2- N 1478 tailed). Pearson Correlation .020 Price Conscious/Value Sig. (2-tailed) .450 for the money N 1478 Pearson Correlation -.027 Impulsiveness/Careless Sig. (2-tailed) .295 N 1475 Pearson Correlation .006 Confused by Overchoice Sig. (2-tailed) .813 N 1478 Pearson Correlation .061* *. Correlation is Sig. (2-tailed) .019 significant at the Habitual/Brand Loyalty 0.05 level (2- N 1478 tailed). Source: Primary data

The above table indicates that there is a significant positive relationship between the 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.

157 TABLE:38 Relationship between the value Sense of Accomplishment and Shopping Styles

Correlations Shopping Styles Sense of Remark Accomplishment Pearson Correlation .150** **. Correlation Perfectionist/High Quality Sig. (2-tailed) .000 is significant at Conscious the 0.01 level N 1478 (2-tailed). Pearson Correlation .032 Brand Consciousness/Price Sig. (2-tailed) .219 Equals Quality N 1477 Pearson Correlation .074** **. Correlation Novelty and Fashion Sig. (2-tailed) .004 is significant at Conscious the 0.01 level N 1478 (2-tailed). Pearson Correlation .047 Recreational and Shopping Sig. (2-tailed) .073 Conscious N 1478 Pearson Correlation .051* *. Correlation is Price Conscious/Value for Sig. (2-tailed) .050 significant at the the money 0.05 level (2- N 1478 tailed). Pearson Correlation .020 Impulsiveness/Careless Sig. (2-tailed) .452 N 1475 Pearson Correlation .060* *. Correlation is Sig. (2-tailed) .021 significant at the Confused by Overchoice 0.05 level (2- N 1478 tailed). Pearson Correlation .046 Habitual/Brand Loyalty Sig. (2-tailed) .074 N 1478 Source: Primary data

The above table indicates that there is a significant positive relationship between the 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.

158 TABLE:39 Relationship between the value Being Independent and Shopping Styles

Correlations Being Shopping Styles Remark Independent Pearson Correlation .083** **. Correlation Perfectionist/High Sig. (2-tailed) .001 is significant at Quality Conscious the 0.01 level N 1478 (2-tailed). Brand Pearson Correlation .022 Consciousness/Price Sig. (2-tailed) .397 Equals Quality N 1477 Pearson Correlation .051 Novelty and Fashion Sig. (2-tailed) .052 Conscious N 1478 Pearson Correlation .017 Recreational and Sig. (2-tailed) .509 Shopping Conscious N 1478 Pearson Correlation .031 Price Conscious/Value Sig. (2-tailed) .229 for the money N 1478 Pearson Correlation .015 Impulsiveness/Careless Sig. (2-tailed) .571 N 1475 Pearson Correlation .016 Confused by Sig. (2-tailed) .546 Overchoice N 1478 Pearson Correlation .033 Habitual/Brand Sig. (2-tailed) .208 Loyalty N 1478

Source: Primary data

The above table indicates that there is a significant positive relationship 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.

159 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

160 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.

161 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 Ȥ2 (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

Source: Primary data

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)

162 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

Source: Primary data

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.

163 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

NFI RFI IFI TLI Model CFI Delta1 rho1 Delta2 rho2

Default model .855 .806 .877 .834 .876

Saturated model 1.000 1.000 1.000

Independence model .000 .000 .000 .000 .000

Source: Primary data

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.

164 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.

165 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

Source: Primary data

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

166 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)

LO HI Model RMSEA PCLOSE 90 90

Default model .057 .054 .060 .000

Independence model .140 .137 .142 .000

Source: Primary data

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

167 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

Average Variance Construct Shopping Styles Explained Validity (Convergent 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

Source: Primary data

168 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

169 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 Ȥ2(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

Source: Primary data

170 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

Source: Primary data

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)

NFI RFI IFI TLI Model CFI Delta1 rho1 Delta2 rho2

Default model .723 .683 .753 .715 .751

Saturated model 1.000 1.000 1.000

Independence model .000 .000 .000 .000 .000

Source: Primary data

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

171 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

Source: Primary data

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

Independence model .121 .119 .123 .000

Source: Primary data

172 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).

173 FIG.7

PATH DIAGRAM INDICATING THE VALUE – SHOPPING STYLE MODEL FIT

1 1 S19 e19 1 1 e3 S1 Confused by OverchoiceS20 e20 1 1 e2 S2 1 Perfectionist/High Quality Conscious 1 S21 e21 e1 S3 1 1 S22 e22 1 1 Habitual/Brand LoyalS23 l e23 e6 S4 1 1 S24 e24 e5 S5 1 Brand Conscious/Price Equals Quality 1 e4 S6 1 V1 e25 1 V2 e26 1 1 1 V3 e27 e9 S7 e41 1 1 1 V4 e28 e8 S8 1 Novelty and Fashion Conscious 1 1 V5 e29 e7 S9 values 1 V6 e30 1 V7 e31 1 V8 e32 1 1 e12 S10 V9 e33 1 1 e11 S11 1 Recreational and Shopping Conscious V10 e34 1 e10 S12

1 e15 S13 1 e14 S14 1 Price Conscious/Value for money 1 e13 S15

1 e18 S16 1 e17 S17 1Impulsiveness/Careless 1 e16 S18

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.

174 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 <--- values .209 .027 7.878 .000 Conscious Habitual/Brand Loyal <--- values .101 .026 3.810 .000 Confused by Overchoice <--- values .121 .033 3.690 .000 Brand Conscious/Price Equals <--- values .072 .022 3.213 .001 Quality Novelty and Fashion Conscious <--- values .148 .029 5.116 .000 Recreational and Shopping <--- values .128 .033 3.823 .000 Conscious Price Conscious/Value for money <--- values .006 .010 .594 .552 Impulsiveness/Careless <--- values .056 .025 2.224 .026 Source: Primary data

175 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’.

176 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 <--- Simplicity -.012 .011 -1.116 .264 Conscious Perfectionist/High Quality Warm Relationships <--- .035 .011 3.033 .002 Conscious With Others Perfectionist/High Quality <--- Self-Fulfillment -.031 .011 -2.801 .005 Conscious Perfectionist/High Quality <--- Being Well Respected .029 .012 2.471 .013 Conscious Perfectionist/High Quality Fun And Enjoyment of <--- .056 .011 5.105 .000 Conscious Life Perfectionist/High Quality <--- Security & Comfort .010 .012 .839 .402 Conscious Perfectionist/High Quality <--- Self-Respect .002 .012 .181 .856 Conscious Perfectionist/High Quality A Sense of <--- .053 .011 4.640 .000 Conscious Accomplishment Perfectionist/High Quality <--- Being Independent -.011 .010 -1.065 .287 Conscious 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.

177 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 <--- Sense Of Belonging -.008 .010 -.746 .455 Equals Quality

Brand Conscious/Price <--- Simplicity .007 .010 .661 .509 Equals Quality

Brand Conscious/Price Warm Relationships <--- -.005 .010 -.512 .609 Equals Quality With Others

Brand Conscious/Price <--- Self-Fulfillment -.029 .010 -2.800 .005 Equals Quality

Brand Conscious/Price Being Well- <--- .026 .011 2.355 .019 Equals Quality Respected

Brand Conscious/Price Fun And Enjoyment <--- .052 .010 5.010 .000 Equals Quality Of Life

Brand Conscious/Price <--- Security & Comfort .000 .011 .030 .976 Equals Quality

Brand Conscious/Price <--- Self-Respect -.039 .011 -3.417 .000 Equals Quality

Brand Conscious/Price A Sense Of <--- .016 .010 1.533 .125 Equals Quality Accomplishment

Brand Conscious/Price <--- Being Independent .006 .009 .598 .550 Equals Quality Source: Primary data

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.

178 TABLE:54 Influence of values on the ‘Novelty and Fashion Conscious’ shopping style

Shopping Style Values Estimate S.E. C.R. P

Novelty and Fashion Sense Of <--- -.026 .013 -1.942 .052 Conscious Belonging

Novelty and Fashion <--- Simplicity -.023 .013 -1.818 .069 Conscious

Novelty and Fashion Warm Conscious <--- Relationships -.017 .014 -1.265 .206 With Others

Novelty and Fashion <--- Self-Fulfillment -.006 .013 -.459 .646 Conscious

Novelty and Fashion Being Well- <--- .032 .014 2.294 .022 Conscious Respected

Novelty and Fashion Fun And <--- .065 .013 5.027 .000 Conscious Enjoyment Of Life

Novelty and Fashion Security & <--- .024 .014 1.761 .078 Conscious Comfort

Novelty and Fashion <--- Self-Respect -.006 .014 -.449 .654 Conscious

Novelty and Fashion A Sense Of <--- .026 .013 1.911 .056 Conscious Accomplishment

Novelty and Fashion <--- Being Independent .004 .012 .363 .717 Conscious Source: Primary data

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.

179 TABLE:55

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

Shopping Style Values Estimate S.E. C.R. P

Recreational and Sense Of <--- .007 .015 .462 .644 Shopping Conscious’ Belonging Recreational and Being Well- <--- .028 .016 1.717 .086 Shopping Conscious’ Respected Recreational and A Sense Of <--- -.001 .016 -.087 .931 Shopping Conscious’ Accomplishment Recreational and <--- Simplicity -.020 .015 -1.371 .170 Shopping Conscious’ Recreational and Fun And <--- .000 .015 .032 .975 Shopping Conscious’ Enjoyment Of Life Recreational and <--- Being Independent -.028 .014 -2.030 .042 Shopping Conscious’ Recreational and Security & <--- .058 .016 3.552 .000 Shopping Conscious’ Comfort Recreational and Warm Shopping Conscious’ <--- Relationships With .031 .016 1.985 .047 Others Recreational and <--- Self-Fulfillment .004 .015 .290 .772 Shopping Conscious’ Recreational and <--- Self-Respect .002 .017 .099 .921 Shopping Conscious’ 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.

180 TABLE:56

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

Shopping Style Values Estimate S.E. C.R. P

Price Conscious/Value for <--- Sense Of Belonging .003 .006 .505 .613 money Price Conscious/Value for <--- Simplicity -.003 .005 -.528 .598 money Price Conscious/Value for Warm Relationships <--- .026 .008 3.364 .000 money With Others Price Conscious/Value for <--- Self-Fulfillment .002 .006 .304 .761 money Price Conscious/Value for Being Well- <--- -.026 .008 -3.334 .000 money Respected Price Conscious/Value for Fun And Enjoyment <--- -.015 .006 -2.393 .017 money Of Life Price Conscious/Value for <--- Security & Comfort .002 .006 .262 .794 money Price Conscious/Value for <--- Self-Respect .003 .006 .524 .600 money Price Conscious/Value for A Sense Of <--- .013 .006 2.115 .034 money Accomplishment Price Conscious/Value for <--- Being Independent .002 .005 .337 .736 money Source: Primary data

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.

181 TABLE:57 Indicating influence of values on the ‘Impulsiveness/Careless’ shopping style

Shopping Style Values Estimate S.E. C.R. P

Impulsiveness/Careless <--- Sense Of Belonging -.002 .012 -.148 .882

Impulsiveness/Careless <--- Simplicity .013 .012 1.126 .260

Impulsiveness/Careless Warm Relationships <--- .035 .013 2.697 .007 With Others

Impulsiveness/Careless <--- Self-Fulfillment -.041 .012 -3.258 .001

Impulsiveness/Careless <--- Being Well-Respected -.010 .013 -.784 .433

Impulsiveness/Careless Fun And Enjoyment Of <--- .010 .012 .829 .407 Life

Impulsiveness/Careless <--- Security & Comfort .011 .013 .883 .377

Impulsiveness/Careless <--- Self-Respect -.012 .013 -.923 .356

Impulsiveness/Careless A Sense Of <--- .016 .012 1.299 .194 Accomplishment

Impulsiveness/Careless <--- Being Independent .007 .011 .611 .541

Source: Primary data

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.

182 TABLE:58

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

Shopping Style Values Estimate S.E. C.R. P

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 <--- .022 .016 1.378 .168 With Others

Confused by Overchoice <--- Self-Fulfillment -.021 .015 -1.423 .155

Confused by Overchoice <--- Being Well-Respected .008 .016 .503 .615

Confused by Overchoice Fun And Enjoyment of <--- .038 .015 2.562 .010 Life

Confused by Overchoice <--- Security & Comfort .041 .016 2.539 .011

Confused by Overchoice <--- Self-Respect -.030 .017 -1.801 .072

Confused by Overchoice A Sense of <--- .033 .016 2.110 .035 Accomplishment

Confused by Overchoice <--- Being Independent -.018 .014 -1.334 .182

Source: Primary data

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.

183 TABLE:59

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

Shopping Style Values Estimate S.E. C.R. P

Habitual/Brand Loyal Sense Of <--- -.005 .012 -.393 .694 Belonging

Habitual/Brand Loyal <--- Simplicity .032 .012 2.691 .007

Habitual/Brand Loyal Warm <--- Relationships With -.016 .012 -1.270 .204 Others

Habitual/Brand Loyal <--- Self-Fulfillment -.022 .012 -1.841 .066

Habitual/Brand Loyal Being Well- <--- .018 .013 1.380 .168 Respected

Habitual/Brand Loyal Fun And <--- .017 .012 1.494 .135 Enjoyment of Life

Habitual/Brand Loyal Security & <--- .009 .013 .705 .481 Comfort

Habitual/Brand Loyal <--- Self-Respect .022 .013 1.663 .096

Habitual/Brand Loyal A Sense of <--- .001 .012 .120 .904 Accomplishment

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’.

184 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.

185 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

INFLUENCE OF VALUES

Shopping Style Negative Positive Influence No Influence Influence

Perfectionist/High x Fun and x Self-Ful- x Security and Quality Conscious Enjoyment of fillment Comfort Life x Self –Respect x A Sense of x Simplicity Accomplishment x Being x Warm Independent Relationships with Others x Being Well- Respected x Sense of Belonging Source: Primary data; Ref. Table 52

186 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

INFLUENCE OF VALUES Shopping Style Positive Negative Influence No Influence Influence Brand x Fun and x Self-Fulfillment x A Sense of Conscious/ Price Enjoyment of x Self –Respect Accomplishment Equals Quality Life x Warm Relationships x Being Well- with Others Respected x Sense of Belonging x Security and Comfort x Simplicity x Being Independent Source: Primary data; Ref. Table 53

187 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

INFLUENCE OF VALUES

Shopping Style Negative Positive Influence No Influence Influence

Novelty and x Fun and x A Sense of Fashion Conscious Enjoyment of Accomplishment Life x Warm x Being Well- Relationships with Respected Others x Sense of Belonging x Self-Fulfillment x Security and Comfort x Self –Respect x Simplicity x Being Independent Source: Primary data; Ref. Table 54

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

188 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

INFLUENCE OF VALUES Shopping Style Negative Positive Influence No Influence Influence Recreational and x Security and x Being x Fun and Shopping Comfort Independ Enjoyment of Life Conscious x Warm ent x Being Well- Relationships Respected with Others x A Sense of Accomplishment x Sense of Belonging x Self-Fulfillment x Self –Respect x Simplicity Source: Primary data; Ref. Table 55

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.

189 TABLE:65

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

INFLUENCE OF VALUES

Shopping Style Negative Positive Influence No Influence Influence

Price x Warm x Fun and x Security and Conscious/Value Relationships Enjoymen Comfort for money with Others t of Life x Being Independent x A Sense of x Being x Sense of Accomplishment Well- Belonging Respected x Self-Fulfillment

x Self –Respect x 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.

190 TABLE:66

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

INFLUENCE OF VALUES

Shopping Style Positive Negative No Influence Influence Influence

Impulsiveness/ x Warm x Self- x A Sense of Careless Relationships Fulfillment Accomplishment

with Others x Fun and Enjoyment of Life

x Being Well- Respected

x Security and Comfort

x Being Independent

x Sense of Belonging

x Self –Respect

x 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.

191 TABLE:67

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

INFLUENCE OF VALUES Shopping Negative Style Positive Influence No Influence Influence

Confused by x Security and x Being Well- Overchoice Comfort Respected

x Fun and x Being Independent

Enjoyment x Sense of Belonging of Life x Self –Respect x A Sense of x Self-Fulfillment Accomplish ment x Warm Relationships with Others

x Simplicity

Source: Primary data; Ref. Table 58

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.

192 TABLE:68

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

INFLUENCE OF VALUES Shopping Positive Negative Style No Influence Influence Influence

Habitual/Brand x Simplicity x Being Well- Loyal Respected x Being Independent x Sense of Belonging x Self –Respect x Self-Fulfillment x Warm Relationships with Others x Fun and Enjoyment of Life x A Sense of Accomplishment x 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.

193 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.

194 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.

195 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

Std. Std. Error Gender Mean Deviation Mean Male 3.7954 .80470 .02838 Perfectionist/High Quality Conscious Female 3.8510 .74784 .02887 Male 2.9505 .87289 .03078 Brand Conscious/Price Equals Quality Female 2.7597 .86069 .03325 Male 2.9838 .88212 .03111 Novelty and Fashion Conscious Female 3.0333 .89071 .03441 Male 2.9619 .84678 .02986 Recreational and Shopping Conscious Female 3.6682 .93933 .03626 Male 3.2488 .68814 .02427 Price Conscious/Value for money Female 3.1967 .61998 .02393 Male 3.2313 .76945 .02714 Impulsiveness/Careless Female 3.2837 .79139 .03055 Male 3.3118 .87650 .03091 Confused by Overchoice Female 3.3465 .91153 .03519 Male 3.2454 .90339 .03186 Habitual/Brand Loyal Female 3.1396 .87259 .03369 Source: Primary data

196 TABLE:70 t test for shopping styles across gender

Levene's Test for Equality of Variances

Sig. F Sig. t df (2-tailed)

Perfectionist/High Equal variances 3.224 .073 -1.364 1473 .173 Quality Conscious assumed Equal variances -1.373 1456.060 .170

not assumed Brand Conscious/Price Equal variances .001 .974 4.204 1472 .000 Equals Quality assumed Equal variances 4.210 1431.280 .000

not assumed Novelty and Fashion Equal variances .671 .413 -1.068 1472 .286 Conscious assumed Equal variances -1.067 1419.489 .286

not assumed Recreational and Equal variances 18.634 .000 - 1473 .000 Shopping Conscious assumed 15.176 Equal variances - 1363.642 .000

not assumed 15.035 Price Conscious/Value Equal variances 8.510 .004 1.512 1473 .131 for money assumed Equal variances 1.527 1464.381 .127

not assumed Impulsiveness/Careless Equal variances .129 .719 -1.283 1473 .200 assumed Equal variances -1.280 1411.277 .201

not assumed Confused by Equal variances .944 .331 -.744 1473 .457 Overchoice assumed Equal variances -.741 1404.957 .459

not assumed Habitual/Brand Loyal Equal variances 1.598 .206 2.276 1473 .023 assumed Equal variances 2.283 1442.027 .023

not assumed Source: Primary data

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).

197 The gender differences in shopping styles indicated above are summarized as under:

Recreational Habitual brand- Gender Brand conscious shopper 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.

198 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 DamirAniü, 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

95% Confidence Interval Std. Std. for Mean Mean Deviation Error Lower Upper Bound 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

199 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

200 TABLE:72 ANOVA Indicating differences in shopping styles across education level of young adults

ANOVA Sum of Mean

Squares df Square F Sig. Perfectionist/ Between .684 3 .228 .375 .771 High Quality Groups Conscious Within 895.135 1475 .609

Groups Total 895.819 1478 Brand Between 2.290 3 .763 1.003 .390 Conscious/ Groups Price Equals Within 1118.429 1475 .761

Quality Groups Total 1120.720 1473 Novelty and Between .109 3 .036 .046 .987 Fashion Groups Conscious Within 1156.388 1475 .787

Groups Total 1156.496 1478 Confused by Between 1.457 3 .486 .530 .662 Overchoice Groups Within 1347.941 1475 .916

Groups Total 1349.399 1478 Recreational Between 3.841 3 1.280 2.966 .031 and Shopping Groups Conscious Within 634.931 1475 .432

Groups Total 638.772 1478 Price Between 2.086 3 .695 1.144 .330 Conscious/ Groups Value for Within 893.952 1475 .608

money Groups Total 896.037 1478 Impulsiveness/ Between .665 3 .222 .278 .841 Careless Groups Within 1173.369 1475 .798

Groups Total 1174.034 1478 Habitual/Brand Between 5.049 3 1.683 2.126 .095 Loyal Groups Within 1164.540 1475 .792

Groups Total 1169.589 1478 Source: Primary data

201 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.

202 TABLE:73 Differences in mean for shopping styles across Regions

95% Confidence Std. Interval for Mean Mean Std. Error Deviation Lower Upper Bound Bound Perfectionist/ High North .0811128 .93654793 .07887156 -.0748206 .2370461 Quality Conscious 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 Brand South -.0126457 .99254229 .03064512 -.0727784 .0474871 Conscious/Price 1.03727296 .08099741 .0442459 .3641249 Equals Quality East .2041854 West -.0160948 .96014072 .09414954 -.2028182 .1706286 Total .0043238 .99921781 .02616866 -.0470084 .0556561 North -.1273052 1.06371860 .08958127 -.3044122 .0498018 Novelty and Fashion South .0156108 .99117243 .03060282 -.0444389 .0756606 Conscious East .1151740 .98540984 .07694758 -.0367685 .2671166

West -.1018932 1.00617703 .09866378 -.2975695 .0937831 Total .0046073 .99976265 .02618292 -.0467530 .0559675 Confused by North -.0726794 1.03308571 .08700151 -.2446860 .0993273 Overchoice 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 Recreational and South -.0220780 1.00890181 .03115022 -.0832019 .0390459 Shopping Conscious East -.0114369 .96498795 .07535290 -.1602306 .1373568 West .0879494 1.02807708 .10081125 -.1119859 .2878847 Total .0013821 1.00158731 .02623071 -.0500719 .0528360 Price North -.1171347 .98750845 .08316321 -.2815528 .0472834 Conscious/Value South .0640978 .92970993 .02870514 .0077717 .1204239 for money East -.1492174 1.03861140 .08110192 -.3093633 .0109285

West -.2330703 1.44573512 .14176599 -.5142297 .0480891 Total .0013797 .99726207 .02611744 -.0498521 .0526115 Impulsiveness/Care North -.0026552 .93768136 .07896702 -.1587773 .1534668 less 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 Source: Primary data

203 TABLE:74 ANOVA Indicating differences in mean for shopping styles across Regions

ANOVA Sum of Mean Df F Sig. Squares Square Perfectionist/High Between 6.753 3 2.251 2.255 .080 Quality Conscious Groups Within 1451.289 1475 .998

Groups Total 1458.042 1478 Brand Conscious/Price Between 8.068 3 2.689 2.703 .044 Equals Quality Groups Within 1446.654 1475 .995

Groups Total 1454.722 1478 Novelty and Fashion Between 5.765 3 1.922 1.926 .123 Conscious Groups Within 1450.543 1475 .998

Groups Total 1456.308 1478 Between 5.423 3 1.808 1.800 .145 Confused by Groups Overchoice Within 1459.809 1475 1.004

Groups Total 1465.232 1478 Recreational and Between 3.608 3 1.203 1.199 .309 Shopping Conscious Groups Within 1458.021 1475 1.003

Groups Total 1461.629 1478 Price Conscious/Value Between 15.543 3 5.181 5.255 .001 for money Groups Within 1433.490 1475 .986

Groups Total 1449.033 1478 Impulsiveness/Careless Between 2.042 3 .681 .677 .566 Groups Within 1462.380 1475 1.006

Groups Total 1464.421 1478

Habitual/Brand Loyal Between 4.018 3 2.009 2.537 .079 Groups 1165.572 1475 .792 Within 1169.589 1478 Groups Total Source: Primary data

204 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.

205 TABLE:75 Differences in Mean for Value Orientations across Gender

Group Statistics

Std. Std. Gender N Mean Error Deviation Mean Male 804 7.2852 1.52137 .05365 External values Female 673 7.7439 1.39110 .05362 Internal interpersonal Male 804 7.1853 1.62115 .05717 values Female 674 7.4206 1.51712 .05844 Internal individual Male 804 7.1823 1.48065 .05222 values 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 Sig. F Sig. t df (2-tailed) Equal variances 5.315 .021 -5.999 1475 .000 assumed External values Equal variances not -6.047 1463.517 .000 assumed Equal variances 5.032 .025 -2.861 1476 .004 Internal interpersonal assumed values Equal variances not -2.878 1458.239 .004 assumed Equal variances 3.908 .048 -3.775 1476 .000 Internal individual assumed values Equal variances not -3.797 1458.891 .000 assumed Source: Primary data

206 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 towards External Values, Internal Interpersonal Values and Internal 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.

207

TABLE:77

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

95% Confidence Std. Std. Interval for Mean N Mean Deviation Error Lower Upper Bound Bound

North 141 7.5934 1.28365 .10810 7.3797 7.8071

South 1052 7.4591 1.52981 .04717 7.3666 7.5517

External values 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 Internal interpersonal East 165 7.2121 1.59568 .12422 6.9668 7.4574 values 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 Internal East 165 7.2242 1.49972 .11675 6.9937 7.4548 individual values West 104 7.6250 .89342 .08761 7.4513 7.7987

Total 1463 7.3185 1.43455 .03751 7.2450 7.3921 Source: Primary data

208 TABLE:78

ANOVA showing Value Orientations of Young Adults across Regional Background

ANOVA Sum of Mean df F Sig. Squares Square Between 17.910 3 5.970 2.767 .041 Groups External values Within 3145.812 1458 2.158 Groups Total 3163.722 1461 Between 10.753 3 3.584 1.455 .225 Groups Internal Within interpersonal values 3593.263 1459 2.463 Groups Total 3604.016 1462 Between 19.194 3 6.398 3.122 .025 Groups Internalindividual Within values 2989.494 1459 2.049 Groups Total 3008.688 1462 Source: Primary data

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.’

209 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 Std. Std. Error Gender N Mean Deviation Mean Male 804 7.55 1.862 .066 Sense Of Belonging Female 674 7.94 1.721 .066 Male 804 6.84 1.910 .067 Simplicity Female 674 7.11 1.767 .068 Male 804 6.98 1.820 .064 Warm Relationships Female 674 7.35 1.729 .067 Male 804 7.08 1.916 .068 Self fulfillment Female 674 7.45 1.795 .069 Male 804 7.17 1.888 .067 Being Well Respected Female 673 7.58 1.609 .062 Male 804 7.39 1.958 .069 Fun & Enjoyment Female 674 7.49 1.820 .070 Male 804 7.13 1.901 .067 Security & Comfort Female 674 7.70 1.712 .066 Male 804 7.53 1.863 .066 Self Respect Female 674 7.93 1.644 .063 Sense Of Male 804 7.22 1.861 .066 Accomplishment Female 674 7.35 1.769 .068 Male 804 7.25 2.069 .073 Being Independent Female 674 7.49 1.854 .071 Source: Primary data

210 TABLE:80

t Test for Level of Influence of individual Values across Gender

Levene's Test for Equality of Variances Sig. F Sig. t df (2-tailed) Equal variances 12.850 .000 -4.114 1476 .000 assumed sense of belong Equal variances not -4.143 1462.013 .000 assumed Equal variances 7.445 .006 -2.811 1476 .005 assumed simplicity Equal variances not -2.831 1461.739 .005 assumed Equal variances .912 .340 -4.012 1476 .000 warm assumed relationships Equal variances not -4.030 1453.209 .000 assumed Equal variances 2.595 .107 -3.875 1476 .000 assumed self fulillment Equal variances not -3.898 1457.916 .000 assumed Equal variances 12.969 .000 -4.389 1475 .000 being well assumed respected Equal variances not -4.452 1474.520 .000 assumed Equal variances 4.937 .026 -.988 1476 .323 fun & assumed enjoyment Equal variances not -.994 1460.441 .320 assumed

211 Equal variances 11.182 .001 -5.946 1476 .000 security & assumed comfort Equal variances not -6.001 1468.399 .000 assumed Equal variances 14.736 .000 -4.399 1476 .000 assumed self respect Equal variances not -4.447 1472.046 .000 assumed Equal variances 1.483 .223 -1.321 1476 .187 sense of assumed accomplishment Equal variances not -1.327 1452.952 .185 assumed Equal variances 8.266 .004 -2.298 1476 .022 being assumed independent Equal variances not -2.320 1469.475 .020 assumed Source: Primary data

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.’

212 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

95% Confidence Std. Std. Interval for Mean N Mean Deviation Error Lower Upper Bound Bound North 141 7.87 1.573 .132 7.60 8.13 South 1053 7.65 1.880 .058 7.53 7.76 sense of East 165 7.84 1.747 .136 7.57 8.10 belonging West 104 8.20 1.177 .115 7.97 8.43 Total 1463 7.73 1.801 .047 7.64 7.82 North 141 6.95 1.834 .154 6.65 7.26 South 1053 6.93 1.868 .058 6.81 7.04 simplicity 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 North 141 7.13 1.643 .138 6.85 7.40 South 1053 7.13 1.841 .057 7.02 7.24 warm East 165 7.13 1.668 .130 6.87 7.38 relationships West 104 7.51 1.421 .139 7.23 7.79 Total 1463 7.16 1.778 .046 7.06 7.25 North 141 7.36 1.790 .151 7.06 7.66 South 1053 7.24 1.921 .059 7.12 7.35 selfulillment 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

213 North 141 7.50 1.534 .129 7.25 7.76 South 1052 7.31 1.843 .057 7.20 7.42 being well East 165 7.39 1.731 .135 7.12 7.65 respected West 104 7.66 1.304 .128 7.41 7.92 Total 1462 7.36 1.771 .046 7.27 7.45 North 141 7.48 1.779 .150 7.19 7.78 South 1053 7.43 1.935 .060 7.32 7.55 fun & enjoyment 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 North 141 7.41 1.871 .158 7.10 7.72 South 1053 7.41 1.839 .057 7.29 7.52 security & East 165 7.10 1.993 .155 6.80 7.41 comfort West 104 7.75 1.335 .131 7.49 8.01 Total 1463 7.40 1.833 .048 7.30 7.49 North 141 7.99 1.384 .117 7.76 8.22 South 1053 7.68 1.826 .056 7.57 7.80 self respect 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 sense of East 165 7.17 1.857 .145 6.88 7.46 accomplishment West 104 7.54 1.284 .126 7.29 7.79 Total 1463 7.29 1.812 .047 7.19 7.38 North 141 7.90 1.518 .128 7.65 8.15 South 1053 7.27 2.036 .063 7.14 7.39 being East 165 7.26 2.042 .159 6.95 7.57 independent 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

214 TABLE:82

ANOVA showing level of influence of individual Values across Regional Background

ANOVA Sum of Mean Df F Sig. Squares Square Between 34.581 3 11.527 3.572 .014 Groups sense of belonging Within 4707.772 1459 3.227 Groups Total 4742.353 1462 Between 9.143 3 3.048 .896 .442 Groups simplicity Within 4961.637 1459 3.401 Groups Total 4970.779 1462 Between 14.013 3 4.671 1.479 .218 Groups warm relationships Within 4606.455 1459 3.157 Groups Total 4620.468 1462 Between 11.463 3 3.821 1.098 .349 Groups self fulfillment Within 5078.962 1459 3.481 Groups Total 5090.425 1462 Between 15.139 3 5.046 1.611 .185 Groups being well Within respected 4567.002 1458 3.132 Groups Total 4582.140 1461 Between 9.790 3 3.263 .911 .435 Groups fun & enjoyment Within 5228.846 1459 3.584 Groups Total 5238.636 1462

215 Between 27.323 3 9.108 2.721 .043 Groups security & comfort Within 4882.738 1459 3.347 Groups Total 4910.062 1462 Between 26.781 3 8.927 2.893 .034 Groups self respect Within 4502.758 1459 3.086 Groups Total 4529.539 1462 Between 12.306 3 4.102 1.250 .290 Groups sense of Within accomplishment 4788.265 1459 3.282 Groups Total 4800.571 1462 Between 74.390 3 24.797 6.442 .000 Groups being independent Within 5615.767 1459 3.849 Groups Total 5690.157 1462 Source: Primary data

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.’

216 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

217 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.

218 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.

219 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.

220 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,

221 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

222 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

223 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.

224 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.

225 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

226 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).

227 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.

228 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,

229 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

230 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,

231 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.

*****

232 BIBLIOGRAPHY

BOOKS

C.R.Kothari, Research Methodology Methods and Techniques, New Age International Pvt. Ltd, New Delhi, 2005

Foxall, G.R., Goldsmith, RE and Brown, S. (1998) Consumer Psychology for Marketing (2nd edition). International Thomson Business Press, London.

Indian Institute of Foreign Trade, Ready-made garment Industry in India, A Study of Problems and Prospects, New Delhi, 1998.

R. Panneerselvam, Research Methodology, Prentice Hall of India, New Delhi, 2004

S.L. Gupta Sumitra Pal, Consumer Behaviour, An Indian Perspective Text and Cases. Jain Book Depot, New Delhi, 2011.

S.P. Gupta: Statistical Methods, Sultan Chand Publishers, New Delhi. Edition 2003.

Schiffman, L.G. and Kanuk, L.L. (1987) Consumer Behavior (3rd Edition) Prentice- Hall International, Englewood Cliffs, N.J.

Saravanavel: Social Research, Himalaya Publishers, New Delhi, Edition 2000.

Wilkinson and Bhandarkan: Methodology and Techniques of Social Research, Himalaya Publishing House, sixteenth revised edition, Reprint, 2004.

William O. Bearden, Richard G. Netemeyer. (1999). Handbook Of Marketing Scales. Multi-Item Measures for Marketing and Consumer Behavior Research

Zikmund, W.G. & d'Amica, M. (1995) Effective Marketing: Creating and Keeping Customers South Western College Publishing, Cincinnati, Ohio.

vi AGENCY REPORTS

Hindustan Times Youth Survey 2011

4PS B&M - ICMR SURVEY, 2011.

Provisional Population Totals Census Of India 2011 Govt Of India

Microsoft Advertising’s Pre Family Survey 2011

Retail perspectives from Deloitte, 2013

Indian Demographics Report 1998

Apparel in India, Euromonitor International. 2012

NATIONAL & INTERNATIONAL MAGAZINES/ JOURNALS AND WORKING PAPERS

Akturan, U., & Tezcan, N. (2007). Profiling young adults: Decision-making styles of college students for apparel products. Journees Normandes de Recherche sur la Consommation : Societe et consommations.

Allen, 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.

C.Anandan, C., Mohanraj. M.P. & 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.

Anic, I. D., Suleska, A. C., & Rajh, E. (2010). Decision-making styles of young- adult consumers in the Republic of Macedonia. Ekonomska istraživanja, 23(4), 102-113.

Arroba, T. (1977). Styles of decision making and their use: An empirical study. British Journal of Guidance and Counseling, 5(2), 149-158.

vii Asma Kiran et. Al; Factors Affecting Change in the Clothing Patterns of The Adolescent Girls; International Journal Of Agriculture & Biology 1560– 8530/2002/04–3–377–378

Backwell, C., and Mitchell, V.W. (2003). “Generation Y Female Consumer Decision Making Styles.” International Journal of Retail & Distribution Management, 3(2), 95-106.

Bae, S. (2004). Shopping pattern differences of physically active Korean and American university consumers for athletic apparel. ProQuest, UMI Dissertations Publishing.

Bao, 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.

Beaudoin, 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), 193-207.

Beatty, Sharon E., Lynn R. Kahle, Pamela Homer, and Shekhar Misra. (1985). Alternative measurement approaches to consumer values: The List of Values and the Rokeach Value Survey,” Psychology & Marketing, 2, 181–200.

Becker and Connor. (1981). Personal Values of the Heavy User of Mass Media. Journal of Advertising Research, 21, 37-43

Bhawnani (2010). What all excites the Indian Youth now?

Boonlertvanich, K. (2009). Consumer buying and decision making behavior of a digital camera in Thailand. RU. International. Journal. Vol. 3(1).

Canabal , M. E. (2002). Decision making styles of young south Indian consumers: an exploratory study. College Student Journal, 36(1).

viii Chase, M. W. (2004). The relationship between mind styles, consumer decision- making styles, and shopping habits of beginning college students. ProQuest, UMI Dissertations Publishing.

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

Comegys, C., & Brennan, M. . L. (2003). Students’ online shopping behavior: A dual-country perspective. Journal of Internet Commerce, 2(2), 69-89.

Comegys, 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.

Cowart, 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.

DeLace, Jessica. (2011). The Psychology and Behavior of Consumers in the Fashion Industry.

Devaraja. T.S. Indian Textile and Garment Industry- An Overview, University of Mysore Hassan, India

Diana Crane. (2000). Fashion and Its Social Agendas: Class, Gender and Identity in clothing. University of Chicago Press, 2000. 294 pp.

Durvasula, 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.

Elizabeth M Visser and Ronel du Preez. (2001). Apparel shopping orientation: Two decades of research ISSN 0378-5254. Journal of Family Ecology and Consumer Sciences. Vol 29.

ix Fairhurst, 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.

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

Forsythe, 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.

Fotopoulos, C., Athanasios, K., & Pagiaslis, A. (2011). Portrait value questionnaire's (pvq) usefulness in explaining quality food-related consumer behavior. British Food Journal, 113(2).

Foula Kopanidis. (2009). Towards the Development of a Personal Values Importance Scale (PVIS) - Application in Education. ANZMAC 2009.

Gaal, B., & Burns, L. D. (2001). Apparel descriptions in catalogs and perceived risk associated with catalog purchases . Clothing and Textiles Research Journal, 19(1), 22-30.

Ghodeswar, B. M. (2007). Consumer decision-making styles among Indian students. Alliance Journal of Business Research, 3(spring), 36-48.

Gosling et al.’s. (2002). Gosling, S. D., Ko, S. J., Mannarelli, T., & Morris, M. E. A Room with a Cue: Judgments of Personality Based on Offices and Bedrooms. Journal of Personality and Social Psychology, 82, 379-398.

Grant, 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

Hair, 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.

x Hair, J.F.; Ringle, C.M.; Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19 (2), 139-151.

Halfstrom, 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.

Hanzaee, 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

Hemalatha, K. G., Jagannathan, L., & Ravichandran, K. (n.d.). Shopping behaviour in malls in globalised economies. 3rd IIMA Conference on Marketing Paradigms for Emerging Economies

Haytko, D. L. & Baker, J. (2004). It’s all at the mall: exploring adolescent girl’s experiences. Journal of Retailing, 80(1), 67-83.

Hines, J. D., & O'Neal, G. S., (1995). Underlying determinants of clothing quality: The consumers' perspective. Clothing and Textiles Research Journal, 13(4), 227-233.

Holbrook, M. & Schindler, R. M. (1989). Some Explanatory Findings on the Development of Musical Tastes. Journal of Consumer Research, 16 (1), 119-124.

Hou, S.C., and Lin, Z.H. (2006). “Shopping Style of Working Taiwanese Females.” http://bai2006.atisr.org/CD/Papers/2006bai6305.doc accessed on May 15, 2011

Homer, 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.

xi Hu & Bentler (1999). Cutoff criteria for fit indexes in covariance structure analysis: Coventional criteria versus new alternatives, Structural Equation Modeling, 6(1), 1-55

Huddleston, 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.

Ian Spero, Merlin Stone, (2004). Agents of change: how young consumers are changing the world of marketing. Qualitative Market Research: An International Journal, Vol. 7 Iss: 2, pp.153 - 159

Inglessis, M. G. (2008). Communicating through clothing: The meaning of clothing among Hispanic women of different levels of acculturation. ProQuest, UMI Dissertations Publishing.

Ivan Damir Aniü, Anita Ciunova Suleska, Edo Rajh. (2010). Decision-making styles of young-adult Ekonomska istraživanja, Vol. 23, No. 4 (102-113)103

Jain, R., Singh, R., & Rankawat, K. (2011). General values and clothing behaviour of college going students. Studies on Home and Community Science, Vol.5, No.1, 2011, p. 13-14

Jaya Halepete, K.V. Seshadri Iyer. (2008). Multidimensional investigation of apparel retailing in India. Emerald 36.

Jessie 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.

Jiyeon Kim. (2003). College Students’ Apparel Impulse Buying Behaviors In Relation To Visual Merchandising, Research Thesis, Athens, Georgia.

J. M., & McQuarrie, E. F. (1988). Shortening the Rokeach value survey for use in consumer research. Advances in Consumer Research, 15, 381-386.

xii Kahle, Lynn R. ed. 1983. Social Values and Social Change: Adaptation to Life in America. New York, NY: Praeger Publishers.

Kamaruddin, 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.

Kaustav Sengupta. (2008) . INgene Insights Consultancy

Kaze, V., & Skapars, R. (2011). 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.

Kenson, K. M. (1999). A Profile of Apparel Shopping Orientation Segments among Male Consumers. Unpublished MA, thesis, California State University Long Beach.

Kevin Kuan-Shun Chiu (2008) The Role of Psychographic Approach in Segmenting Young Adults’ Buying Behavior for Athletic Footwear.

Kim, Y. (2002). The impact of personal value structures on consumer pro- environmental attitudes, behaviors, and consumerism: A cross-cultural study. ProQuest, UMI Dissertations Publishing.

Kim, H.S. & Jin, B. (2006). Exploratory study of virtual communities of apparel retailers. Journal of Fashion marketing and Management. 10(1). 41-55.

Kittichai, W (2005). A hierarchical model of values, price perception, ongoing search and shopping behaviors: A cross-cultural comparison. ProQuest, UMI Dissertations Publishing.

Kropp, 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.

xiii Kulkarni, R., Belgaonkar. D (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

Kwan, C. Y., Yeung, K.W., & Au, K.F. (2004). Decision-making behaviour toward casual wear buying: A study of young consumers in mainland China. Journal of Management & World Business Research, 1(1), 1-10.

Kwan, C. Y. (2006). An investigation on the factors affecting young Chinese consumers' decision-making behaviour towards casual wear purchase. ProQuest, UMI Dissertations Publishing.

Kwan, C.Y., Yeung, K.W., & Au, K.F. (2008). Relationship between consumer decision-making styles and lifestyle characteristics: Young fashion consumers in China. Journal of the Textile Institute, 99(3), 193-209.

Lawan 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

Laura P. Naumann. (2009). Express yourself: Manifestations of personality in clothing and appearance The University of Texas at Austin

Leslie, 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.

Linda B. Arthur. (1999). Religion, Dress and the Body [Paperback], Berg Publishers; ISBN-10: 1859732976 | ISBN-13: 978-1859732977

Lee, 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), 13-22.

xiv Lysonski, S., Durvasula, S. & Zotos, Y. (1996). Consumer Decision-Making Styles: A Multi-Country Investigation. European Journal of Marketing, 30 (12), 10-21.

Magie, 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.

Mathews, S., & Nagaraj, H. (2010). An analytical study of Vals on youth – Implication to marketers. Management Convergence, Vol 1, No 1

Mary Anne Winslow. (2008). Market Segmentation - Psychographic Method; Article Source: http://EzineArticles.com.

Meenakshi, H., & Arpita, K. (2010). Need for uniqueness and consumption behavior for luxury brands amongst Indian youth. International Journal of Indian Culture and Business Management, 3(5).

Mitchell, V.W. & Bates, L. (1998). UK Consumer Decision Making Styles. Journal of arketing Management, 14, 199-225.

Mitchell V, Walsh, G, Hennig-Thurau, T, Wiedmann, K-P (2001), 'Consumers' Decision Making Style as a Basis for Market Segmentation', Journal of Targeting, Measurement and Analysis for Marketing , 10(2), p.117-131.

Mishra, A.A. (2010). Consumer decision-making styles and young-adult consumers: An Indian exploration. øúletme AraúWÕrmalarÕ Dergisi, 2(3), 45-62.

Moschis, G. P. (1987). Consumer Socialization: A Life Cycle Perspective, Lexington, MA: Lexington Books.

Moklis, S., and Salleh, H. (2009). Decision making styles of young Malay, Chinese and Indian Consumers in Malaysia. Asian Social Science, 5(12), 50-59.

Mokhlis, 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. xv Mokhlis, S., and Salleh, H. (2010). Religious contrasts in consumer shopping styles: A Factor Analytic Comparison. Journal of Business Studies Quarterly, 2(1), 52-64.

Mandloi, M. (2010). A study on buying decision making style of Indian shoppers in Indore shopping malls.

Narang, 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.

Noble, s. M., et al. (2009). What drives college-age Generation Y consumers? Journal of Business Research 62, 617–628.

Noh, 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.

Ng, 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.

Nunnally, J. C. (1978). Psychometric Theory. Second edition. New York, NY: McGraw-Hill

Padmanabhan, Parvathi, Ph.D. (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.

Patel, V. (2008). “Consumer Decision Making Styles in Shopping Malls: An Empirical Study.” New Age Marketing: Emerging Realities, 627-637.

Park, 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.

xvi Radam. A., Ali, H. M., & Leng, Y. S. (n.d.). Decision-making style of Chinese consumer on clothing . University Putra Malaysia, The Journal of Global Business Management, 7(2).

Reiley, K. J. W. (2008). Definitions of uniqueness in terms of individual appearance: Exploring vintage clothing and new clothing wearers. ProQuest, UMI Dissertations Publishing.

Rebecca Garnett, B.S. (2010) .Examining The Effects of Psychographics, Demographics And Geographics On Time-Related Shopping Behaviors. University Of North Texas.

Rokeach, M. (1973). The Nature of Human Values. NY: The Free Press.Roper,

Roy, S., & Goswami, P. (2007). Structural equation modeling of value- psychographic trait-clothing purchase behavior: a study on the urban college- goers of India. Emerald Group Publishing Limited, 8(4), 269-277.

S. W. (2002). New age consumers: attitudes and values. Proquest, 121.

Safiek Mokhlis and Hayatul Safrah Salleh, (2009). Consumer Decision-Making Styles in Malaysia: An Exploratory Study of Gender Differences. European Journal of Social Sciences – Volume 10, Number 4

Saleem , S., Salaria, R., Megha, V. (2010). Few determinants of compulsive buying of youth in Pakistan.

Seo, J., Hathcote, J. and Sweaney, A. (2001). Casual wears shopping behavior of college men in Georgia, USA, Journal of Fashion Marketing and Management, 5(3), 208-222.

Schwartz. (1992). Universals in the Content and Structure of Values: Theoretical Advances and Empirical Tests in 20 Countries.Advances in experimental social psychology (Vol. 25) (pp. 1-65). New York: Academic Press.

xvii Shim, 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.

Shim, S., & Kotsiopulos, A. (1993). A typology of apparel shopping orientation segments among female consumers. Clothing and Textiles Research Journal, 12(1), 73-85.

Shim, S. (1996). Adolescent Consumer Decision Making Styles: The Consumer Socialization Perspective. Psychology & Marketing, 13(6), 547-569.

Shim, Soyeon and Jennifer L. Maggs. 2005. A psychographic analysis of college studentெs alcohol consumption: implications for prevention and consumer education. Family and Consumer Sciences Research Journal 33(3): 255-273.

Shrum, 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

Siu, 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.

Speer, T. (1998). College Come-Ons. American Demographics, 20 (3), 41-45.

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

Sproles, G.B., and Kendall, E.L. (1987). “A Short Test of Consumer Decision Making Styles.” The Journal of Consumer Affairs, 5, 7-14.

Sproles, 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.

xviii Srivatsa, H.S., Srinivasan. R. (2007). Banking Channel Perceptions; An Indian Youth perspective

Sullivan, D. P. (2004). A profile of generation y online shoppers and its application to marketing. ProQuest, UMI Dissertations Publishing.

Szendrey, J. M. (2008). An empirical consumer behavior study of familial/parental influences on the degree of frugality of undergraduate students. ProQuest, UMI Dissertations Publishing.

Tabachnick, Linda S. Fidell. (2001). Using Multivariate Statistics (6th Edition). Amazon.com

Tanaka, 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

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

Thomas, 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.

Thompson (2009), Interpreting Kahle’s List of Values: Being Respected, Security, and Self-fulfillment in Context. UW-L Journal of Undergraduate Research XI, 1-9.

Tremblay, A. J. (2005). Impulse buying behavior: Impulse buying behavior among college students in the Borderlands. ProQuest, UMI Dissertations Publishing.

Turk, J. L. and N. W. Bell. (1972). “Measuring Power in Families.” Journal of Marriage and theFamily 34:215-223.

xix Unal S., and Ercis A. (2008). “The Role of Gender Difference In Determining The Style of Consumer Decision Making.” Bogazici Journal, 22(1-2), 89-106.

Vieira, V. A., Slongo, L. A., and Torres, C. V. (2011). “Evaluating The Psychometric Properties of Consumer Decision Making Style Instruments” Retrieved from http://www.ead.fea.usp.br/semead/10semead/sistema/ resultado/TrabalhosPDF/277.pdf.

Vigaray, M. D. J., & Hota, M. (2008). Schwartz values, consumer values and segmentation: The Spanish fashion apparel case. Lille economie & management, 1-32.

Vikkraman. P; Sumathi. N. (2012). Purchase Behaviour in Indian Apparel Market: An Analysis International Journal of Business Economics & Management Research Vol.2 Issue 2, February 2012, ISSN 2249 8826

Vincent. 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

Vincent. 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.

Voices and Visons from India, 2004 © Commonwealth of Australia

Walsh, G., Mitchell, V.W., and Thurau, T. H. (2001). “German Consumer Decision Making Styles.” The Journal of Consumer Affairs, 35(1), 73-95.

Walsh, 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.

Wang, 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.

xx Warwick, J., P. Mansfield. (2000). Credit Card Consumers: College Students' Knowledge and Attitude. Journal of Consumer Marketing 17(7):617-626

Wells, W.D. (1975). Psychographics: A review. Journal of Marketing Research, 11 (May), 196-213.

Xu, 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.

Yesilada, F., and Kavas, A. (2008). “Understanding the Female Consumers Decision Making Styles.” Isletme fakultesi dergisi, cilt , 9(2), 167-185.

Zeenat Ismail , Sarah Masood and Zainab Mehmood Tawab (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.

Zeng, 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.

WEBSITES www.en.wikipedia.org www.zenithresearch.org.in http://www.ibef.org/industry/textiles.aspx, May 2013 http://www.researchandmarkets.com/reports/688195/textile_and_apparel_sector_in_ india http://yas.nic.in/ http://www.thefreedictonary.com

xxi unesco.org/new/en/social-and-human-sciences/themes/youth/youth-definition http://pitchonnet.com/blog/2012/08/21/how-well-do-indian-marketers-understand- the-Indian-youth/ Pallavi Srivastava and Arshiya Khullar http://www.atkearney.com/consumer-products-retail/global-retail-development- index/full-report/-/asset_publisher/oPFrGkbIkz0Q/content/2013-global- retail-development-index/10192#sthash.BiNogJzz.dpuf http://www.euromonitor.com/apparel-specialist-retailers-in-india/report http://www.ibef.org/industry/textiles.aspx, May 2013; and http://www.research andmarkets.com/reports/688195/textile_and_apparel_sector_in_india http://www.mudralifestyle.com/ http://www.indiainfoline.com http://www.arvindmills.com http://www.mywestside.com http://corporate.shoppersstop.com/corporate/history.aspx

xxii 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 Independence model .121 .119 .123 .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 Brand Conscious/Price <--> Conscious Equals Quality 0.648 0.419904 Perfectionist/High Quality Novelty and Fashion <--> Conscious Conscious 0.51 0.2601

Perfectionist/High Quality Recreational and Shopping <--> Conscious Conscious 0.313 0.097969 Perfectionist/High Quality Price Conscious/Value for <--> Conscious money 0.097 0.009409 Perfectionist/High Quality <--> Impulsiveness/Careless Conscious 0.288 0.082944 Perfectionist/High Quality <--> Confused by Overchoice Conscious 0.26 0.0676

Perfectionist/High Quality Habitual/Brand Loyal <--> Conscious 0.469 0.219961 Brand Conscious/Price Equals Novelty and Fashion <--> Quality Conscious 0.64 0.4096 Brand Conscious/Price Equals Recreational and Shopping <--> Quality Conscious 0.108 0.011664 Brand Conscious/Price Equals <--> Impulsiveness/Careless Quality 0.243 0.059049

Brand Conscious/Price Equals <--> Confused by Overchoice Quality 0.247 0.061009

Habitual/Brand Loyal Brand Conscious/Price <--> Equals Quality 0.523 0.273529

Recreational and Shopping Novelty and Fashion Conscious <--> 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

Novelty and Fashion Habitual/Brand Loyal <--> Conscious 0.449 0.201601 Recreational and Shopping Price Conscious/Value for <--> Conscious money 0.053 0.002809 Recreational and Shopping <--> Impulsiveness/Careless Conscious 0.071 0.005041 Recreational and Shopping <--> Confused by Overchoice Conscious 0.079 0.006241

Recreational and Shopping Habitual/Brand Loyal <--> 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

Price Conscious/Value for Habitual/Brand Loyal <--> 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

Perfectionist/High Quality Brand Conscious/Price <--> .231 .019 11.902 .000 Conscious Equals Quality

Perfectionist/High Quality Novelty and Fashion <--> .233 .020 11.849 .000 Conscious Conscious

Perfectionist/High Quality Recreational and Shopping <--> .154 .020 7.891 .000 Conscious Conscious

Perfectionist/High Quality Price Conscious/Value for <--> .053 .018 2.952 .003 Conscious money

Perfectionist/High Quality <--> Impulsiveness/Careless .113 .018 6.475 .000 Conscious

Perfectionist/High Quality <--> Confused by Overchoice .137 .019 7.174 .000 Conscious

Habitual/Brand Loyal Perfectionist/High Quality <--> .259 .023 11.394 .000 Conscious

Brand Conscious/Price Novelty and Fashion <--> .263 .023 11.651 .000 Equals Quality Conscious

Brand Conscious/Price Recreational and Shopping <--> .048 .016 2.915 .004 Equals Quality Conscious

Brand Conscious/Price <--> Impulsiveness/Careless .086 .016 5.416 .000 Equals Quality

Brand Conscious/Price <--> Confused by Overchoice .117 .018 6.548 .000 Equals Quality

Brand Conscious/Price Habitual/Brand Loyal <--> .261 .024 10.864 .000 Equals Quality

Estimate S.E. C.R. P

Novelty and Fashion Recreational and Shopping <--> .154 .022 6.965 .000 Conscious Conscious

Novelty and Fashion <--> Impulsiveness/Careless .120 .020 6.007 .000 Conscious

Novelty and Fashion Confused by Overchoice <--> .159 .022 7.174 .000 Conscious Habitual/Brand Loyal Novelty and Fashion <--> .286 .026 10.901 .000 Conscious Recreational and Shopping Price Conscious/Value for <--> .036 .023 1.528 .126 Conscious money Recreational and Shopping Impulsiveness/Careless <--> .035 .021 1.641 .101 Conscious Recreational and Shopping Confused by Overchoice <--> .052 .024 2.181 .029 Conscious Habitual/Brand Loyal Recreational and Shopping <--> .086 .026 3.303 .000 Conscious Price Conscious/Value for <--> Impulsiveness/Careless .099 .022 4.550 .000 money Price Conscious/Value for <--> Confused by Overchoice .065 .024 2.733 .006 money Price Conscious/Value for Habitual/Brand Loyal <--> .013 .026 .509 .611 money 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