Impact and Effectiveness of Social Media Advertising on Young

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IMPACT AND EFFECTIVENESS OF SOCIAL MEDIA ADVERTISING ON YOUNG WORKING WOMEN’S BUYING BEHAVIOUR WITH REFERENCE TO CONSUMER ELECTRONICS - A STUDY OF SELECTED CITIES IN MAHARASHTRA AND GUJARAT.

THESIS SUBMITTED TO D.Y.PATIL UNIVERSITY, DEPARTMENT OF BUSINESS MANAGEMENT IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF

DOCTOR OF PHILOSOPHY IN BUSINESS MANAGEMENT SUBMITTED BY MS. SHALAKA AYAREKAR (ENROLLMENT NO. DYP-PhD-116100013)

RESEARCH GUIDE DR. R. GOPAL DIRECTOR AND HEAD OF DEPARTMENT D.Y.PATIL UNIVERSITY, DEPARTMENT OF BUSINESS MANAGEMENT SECTOR 4, PLOT NO. 10, C.B.D. BELAPUR, NAVI MUMBAI - 400614. FEBRUARY 2015

Impact and effectiveness of social media advertising on young working women’s buying behaviour with

reference to consumer electronics – A study of

selected cities in Maharashtra and Gujarat.

DECLARATION

I hereby declare that the thesis entitled “Impact and effectiveness of Social media advertising on young working women’s buying behaviour with reference to consumer electronics – A study of selected cities in Maharashtra and Gujarat” submitted for the Award of Doctor of Philosophy in Business Management at the

D.Y.Patil University, Department of Business Management is my original work and the thesis has not formed the basis for the award of any degree, associate-ship, fellowship or any other similar titles.

The material borrowed from other sources and incorporated in the thesis has been duly acknowledged.

I understand that I myself could be held responsible and accountable for plagiarism, if any, detected later on.

The research papers published based on the research conducted out of an in the course of the study are also based on the study and not borrowed from other sources.

Place : Navi Mumbai Signature of the candidate

Date : Enrollment No.: DYP-PhD-116100013

CERTIFICATE

This is to certify that the thesis entitled “Impact and effectiveness of social media advertising on young working women’s buying behaviour with reference to consumer electronics - A study of selected cities in Maharashtra and Gujarat” and submitted by

Ms. Shalaka Ayarekar is a bonafide research work for the award of the Doctor of

Philosophy in Business Management at the D.Y.Patil University Department Of

Business Management in partial fulfilment of the requirements for the award of the

Degree of Doctor of Philosophy in Business Management and that the thesis has not formed the basis for the award previously of any degree, diploma, associate-ship, fellowship or any other similar title of any University or Institution.

Also certified that the thesis represents an independent work on the part of the candidate.

Place : Navi Mumbai.

Date :

Signature of the Head of the Department Signature of the Guide

ACKNOWLEDGEMENT

I am grateful to D.Y.Patil University, Department of Business Management for having given me an opportunity of career enhancement by carrying out the current research work.

I am extremely thankful to my guide, mentor, philosopher Dr. R. Gopal for having guided me with his valuable inputs and extending all his support throughout my research work. Without his able and valuable guidance and support this would not have been possible.

I would also like to thank my colleagues, the IT Lab staff especially Mr. Sandeep

Surve, librarian Ms. Vanda Salgaonkar and the administration staff for helping me wherever needed.

I would also like to thank Prof. Dr. Pradip Manjrekar, for his guidance.

I sincerely thank my mother, father and brother for their limitless support and for always being a source of encouragement to me.

Lastly I also thank everyone who have been directly and indirectly instrumental in the completion of my dissertation.

Place : Navi Mumbai.

Date : Signature of the candidate

CONTENTS

Chapter Section Title Page No.

List of Tables 10

List of Figures 35

List of Abbreviations 36

Executive Summary 37

1 Introduction 58

1.1 Concept of Social Media, Advertising, 58 Advertising on Social Networking sites and Consumer Behaviour

1.2 Origin Of Social Media 60

1.3 Popularity of Social Media 60

1.4 Advertising 61

1.5 Social Media Advertising 62

1.6 Consumer Buying Behaviour 65

1.7 Online Consumer’s Buying Behaviour 67

1.8 Women and Social Network Sites(SNSs) 68

1.9 Consumer Electronics and Social Media 68

2 Review of Literature 71

2.1 Literature Gap 100

3 Objectives, Hypothesis and Research 101 Methodology

3.1. Statement of the Problem 101

3.2. Objectives of Study 102

3.3. Hypothesis 102

3.4. Research Methodology 104

3.4.1. Type of Study 104

3.4.2. Data Collection 104

3.4.3. Pilot Study 105

3.4.4. Reliability 105

3.4.5. Questionnaire 105

3.4.6. Size and Design of Sample 107

3.4.7.a. Sampling Technique 107

3.4.7.b. Sample Size Calculation 107

3.4.8. Variables of the study 108

3.4.9. Definition of the Variables 109

3.5. Limitations of the Study 111

3.6. Utility of the study 111

3.7. Theoretical Model 111

3.8. Analysis of Data 112

4 Typical Aspects of Social Media and Social 113 Networking sites

4.1 Typical Aspects of Social Media 113

4.2 Social Networking Sites 114

4.2.1. Face-book 114

4.2.1.1. Origin of Facebook 114

4.2.1.2. Number of Users on Facebook 115

4.2.1.3. Face book’s Revenue 115

4.2.1.4. Advantages of Facebook 115

4.2.1.5. Disadvantages of Facebook 117

4.2.2. Twitter 118

4.2.2.1. Origin of Twitter 118

4.2.2.2. Number of Users on Twitter 120

4.2.2.3. Revenue of Twitter 121

4.2.2.4. Advantages of Twitter 121

4.2.2.5. Disadvantages of Twitter 122

4.2.3. LinkedIn 122

4.2.3.1 Origin of LinkedIn 122

4.2.3.2 Status of LinkedIn Today 122

4.2.3.3. Revenue of LinkedIn 123

4.2.3.4. Benefits LinkedIn Brings for Business 123

4.2.4. YouTube 125

4.2.4.1. Origin of YouTube 125

4.2.4.2. Number of users accessing YouTube 126

4.2.5. RSS 126

4.2.5.1. Working of RSS 126

4.2.5.2. Benefits of RSS 127

4.2.6. SlideShare 127

4.2.6.1. Users of Slideshare 128

4.2.7. Myspace 128

4.2.8. Friendster 128

5 Consumer Electronics Companies and their 129 presence on Social Media

5.1 Global Players 129

5.1.1 Samsung 129

5.1.2. Apple 130

5.1.3. Sony 130

5.1.4 Hewlett-Packard 132

5.1.5 LG 135

5.2 Indian Players 136

5.2.1 Hindustan Computers Limited (HCL) 136

5.2.2 TCS 136

5.2.3 Wipro 137

6 Study of Consumer Electronics Market 138

6.1. Market Research and Market Share of Global 138

Consumer Electronics Industry

6.1.1 Geographic trends in Global Consumer 140 Electronics Markets

6.1.2 Trends based on product preferences in Global 140 Consumer Electronics Market

6.2 Market Share of Indian Consumer Electronics 140 Industry

7 Data Analysis and Findings 142

7.1 Tabulation and Statistical Analysis of Data 142

7.2 Summary of the Analysis 184

7.3 Summary of Hypothesis 207

8 Conclusion 213

9 Recommendation and Suggestion 225

9.1 Recommendation and Suggestion 225

9.2 Future scope of research 226

Annexure 227

1 Bibliography 227

1.1 Webliography 234

2 Questionnaire 236

3 Descriptive Analysis (SPSS Output) 244

4 Inferential Analysis in Detail 306

LIST OF TABLES

Table No. Title Page No. 3.1. Table showing details of questionnaire 106 3.2. Table on Chosen Sample Size 108

3.3. Table showing the variables of the study 108

4.1. Table showing the number of users on Twitter 120

4.2 Table showing the year-wise revenue of Twitter 121 7.1.1. Table showing the number of young working women 143 accessing or using social networking sites in Mumbai, Nashik and Surat. 7.1.2. Table showing the number of young working women 144

accessing or using “Facebook” in Mumbai, Nashik and

Surat.

7.1.3. Table Showing the frequency with which the young 146

working women access SNS in a week in Mumbai,

Nashik and Surat.

7.1.4. Table Showing the time the young working women 147

spend each time they access Facebook in Mumbai,

Nashik and Surat.

7.1.5. Table Showing whether the young working women 148

share their opinion about a particular product or

service with your family or friends by writing reviews

or blogs in Mumbai, Nashik and Surat.

7.1.6. Table Showing the number of times the young working 150

women provided online rating in one year in Mumbai,

Nashik and Surat.

7.2.1.1.m.a. Table Relationship between consumer buying 152

behaviour with the factor of social media

advertisement i.e positive reactions/feelings towards

advertisements displayed on SNS in Mumbai.

7.2.1.1.m.b. Table of Symmetric Measures to show how much 153 relationship exists in between consumer buying behaviour and the factor of social media advertising i.e positive reactions/feelings towards advertisements displayed on SNS in Mumbai. 7.2.1.1.n.a. Table Relationship between consumer buying 154 behaviour with the factor of social media advertisement i.e positive reactions/feelings towards advertisements displayed on SNS in Nashik. 7.2.1.1.n.b. Table of Symmetric Measures to determine how much 155 relationship exists in between consumer buying behaviour and the factor of social media advertising i.e positive reactions/feelings towards advertisements displayed on SNS in Nashik. 7.2.1.1.s.a. Table Relationship between consumer buying 156 behaviour with the factor of social media advertisement i.e positive reactions/feelings towards advertisements displayed on SNS in Surat. 7.2.2.1.m.a. Table Relationship between online purchase 158 behaviour with the factor of social media advertising i.e positive reactions/feelings towards the advertisements displayed on SNS in Mumbai. 7.2.2.1.n.a. Table Relationship between online purchase 159 behaviour with the factor of social media advertising i.e positive reactions/feelings towards the advertisements displayed on SNS in Nashik.

7.2.2.1.n.b. Table of Symmetric Measures to determine how much 160 relationship exists in between online purchase behaviour and factor of social media advertising i.e positive reactions/feelings towards the advertisements displayed on SNS in Nashik. 7.2.2.1.s.a. Table Relationship between online purchase 161 behaviour with the factor of social media advertising i.e positive reactions/feelings towards the advertisements displayed on SNS in Surat. 7.2.2.1.s.b. Table of Symmetric Measures to determine how much 162 relationship exists in between online purchase behaviour and factor of social media advertising i.e positive reactions/feelings towards the advertisements displayed on SNS in Surat. 7.2.3.1.m.a. Table Relationship between complex buying 163 behaviour with the factor i.e. “positive reactions/feelings towards advertisements displayed on it” of social media advertising in Mumbai. 7.2.3.1.m.b. Table of Symmetric Measures to determine how much 164

relationship exists between complex buying behaviour

and the factor i.e. “positive reactions/feelings towards

advertisements displayed on it” of social media

advertising in Mumbai.

7.2.3.1.n.a. Table Relationship between complex buying 165 behaviour with the factor i.e. “positive reactions/feelings towards advertisements displayed on it” of social media advertising in Nashik. 7.2.3.1.n.b. Table of Symmetric Measures to determine how much 166 relationship exists between complex buying behaviour and the factor i.e. “positive reactions/feelings towards advertisements displayed on it” of social media

advertising in Nashik. 7.2.3.1.s.a. Table Relationship between complex buying 167 behaviour with the factor i.e. “positive reactions/feelings towards advertisements displayed on it” of social media advertising in Surat. 7.2.3.1.s.b. Table of Symmetric Measures to determine how much 168 relationship exists between complex buying behaviour with the factor i.e. “positive reactions/feelings towards advertisements displayed on it” of social media advertising in Surat. 7.2.4.1.m. Table showing relationship between all the factors of 169 habitual buying behaviour and all the factors of social media advertising in Mumbai. 7.2.4.1.n. Table showing relationship between all the factors of 170

habitual buying behaviour and all the factors of

social media advertising in Nashik.

7.2.4.1.s. Table showing relationship between all the factors of 171

habitual buying behaviour and all the factors of

social media advertising in Surat.

7.3.1.m.a. Table of Model Summary for Mumbai 173

7.3.1.m.b. Table for Anova to determine the level of significance 173

of R2

7.3.1.m.c. Table for significance of Coefficients 175

7.4.m.1. Table Showing effectiveness of SNSs in terms of 176

Audience in Mumbai

7.4.m.2. Table Showing effectiveness of SNSs in terms of 177

Targeting consumers in Mumbai.

7.4.m.3. Table Showing effectiveness of SNSs in terms of more 178

followers due to acquaintances in Mumbai.

7.4.m.4. Table Showing effectiveness of SNSs in terms of more 178

unknown followers in Mumbai.

7.5.I.m. Table Relationship between qualification of young 180

working women and impact of social media advertising

in Mumbai .

7.5.II.s.a. Table Relationship between annual income of young 181

working women and impact of social media advertising

in Surat.

7.5.II.s.b. Table To determine how much relationship exists 181

between annual income of young working women and

impact of social media advertising in Surat.

7.5.III.n.a. Table Relationship between occupation of young 182

working women and impact of social media advertising

in Nashik.

7.5.III.n.b. Table To determine how much relationship exists 183

between occupation of young working women and

impact of social media advertising in Nashik.

7.6 Tabular representation of details of Analysis and 184

results.

7.7 Tabular representation showing Hypothesis 207

(Accepted/Rejected).

10.1.1. Education 244

10.1.2. Annual income 244

10.1.3. Occupation 245

10.1.4. Place 245

10.2.1. Frequency of accessing internet 246

10.2.2. Table showing number of women using social 246

networking sites.

10.2.2.1. Table showing number of women who use facebook. 247

10.2.2.2. Table showing number of women who use Twitter. 247 10.2.2.3. Table showing number of women who use LinkedIn. 248 10.2.2.4. Table showing number of women who use other SNSs. 248 Table showing the frequency of using SNS within a 249

10.2.5. week among working women.

10.2.5.1. Table showing the number of women not using SNS 250 because they are not interested. 10.2.5.2. Table showing the number of women not using SNS 250

because of security concerns.

10.2.5.3. Table showing the number of women not using SNS 251

because of Non Availability of Enough time.

10.2.5.4. Table showing the number of women not using SNS 251 because they prefer face to face interactions 10.2.5.5. Table showing the number of women not using SNS 252

because of Lack of computer skills.

10.2.5.6. Table showing the number of women not using SNS 252 because they Prefer to use phone for interaction. 10.2.6.1. Table showing the time spent by working women for 253

using Facebook each time they access SNS.

10.2.6.2. Table showing the time spent by working women for 253 using LinkedIn each time they access SNS. 10.2.6.3. Table showing the time spent by working women for 254

using Twitter each time they access SNS.

10.2.6.4. Table showing the time spent by working women for 255 using other SNS(other than facebook, twitter & LinkedIn) each time they access SNS. 10.2.7. Table showing the number of women who have 255

increased, decreased or spent about the same amount

of time using the social networking site compared to

last year.

10.2.8. Table showing the number of women who think the 256

time that they are spending currently on the social

networking sites for product information search, is

about right, too much or not enough.

10.2.9. Table showing the number of women who in the next 257

twelve months will be increasing, decreasing or

spending the same amount of time using social

networking sites for product information search

compared to the last year.

10.2.10. Table showing the number of women who share their 257 opinion about a particular product or service with your family or friends by writing reviews or blogs. 10.2.11. Table showing the number of women who share their 258

feedback about a particular product or service with

the organization/company.

10.2.12. Table showing the number of women who visit 258

company website and provide a particular rating for a

particular product or service.

10.2.13. Table showing the number of times women have you 259 provided online rating in one year for a particular product or service. 10.2.14. Table showing whether working women send the 260

company link of their favourite brand to their family

and friends.

10.3.1. Table showing the number of women who have 260 purchased consumer electronic items through social media. 10.3.2. Table showing the list of reasons due to which women 261

purchased consumer electronic items through social

media.

10.3.3.1. Table showing the number of women providing online 262

rating to music players.

10.3.3.2. Table showing the number of women providing online 262

rating to Television set.

10.3.3.3. Table showing the number of women providing online 263

rating to Video Recorder.

10.3.3.4. Table showing the number of women providing online 263

rating to DVD Players.

10.3.3.5. Table showing the number of women providing online 264 rating to Digital Cameras. 10.3.3.6. Table showing the number of women providing online 264

rating to Personal computers/Laptops.

10.3.3.7. Table showing the number of women providing online 265

rating to Telephone Instruments.

10.3.3.8. Table showing the number of women providing online 265

rating to Mobile Phones.

10.3.3.9. Table showing the number of women providing online 266

rating to Video Games Console

10.3.3.10. Table showing the number of women providing online 266 rating to Camcorders 10.3.4. Table showing the number of women who read blogs 267

or online reviews about a product or service before

making buying decision

10.4.1. Table showing the number of women who are 267 personally involved in making a buying decision. 10.4.2. Table showing the number of women who think there 268

is any difference between the products of different

brands.

10.4.3. Table showing the women’s opinion towards the price 268

of the branded product.

10.4.4. Table showing women’s perception regarding the time 269

consumed in taking the buying decision, about a

particular product whose advertisement they have

viewed on any social networking sites.

10.5.1. Table showing the type of product information search 270

conducted on social media by women before actual

buying.

10.5.2. Table showing how frequently the women pay 271

attention to the advertisements of consumer electronic

products on social networking sites

10.5.3. Table showing the amount of time and efforts the 272

women spend on researching for the product

information on the network before actual online

purchase.

10.5.4. Table showing the number of online electronic stores 273 visited on an average by women before making the buying decision. 10.5.5.a. Table showing the number of women who consider the 273

Physical Appearance of the product while taking the

buying decision of consumer electronic product

through a social networking site .

10.5.5.b. Table showing the number of women who consider 274 the feature of Availability of a variety of functions in the product while taking the buying decision of consumer electronic product through a social networking site . 10.5.5.c. Table showing the number of women who consider the 275

price of the product while taking the buying decision of

consumer electronic product through a social

networking site .

10.5.5.d. Table showing the number of women who consider the 275 quality of the product while taking the buying decision of consumer electronic product through a social networking site . 10.5.5.e. Table showing the number of women who consider the 276

popularity of the product while taking the buying

decision of consumer electronic product through a

social networking site .

10.5.5.f. Table showing the number of women who consider the 277

Association with a particular brand for the product

while taking the buying decision of consumer

electronic product through a social networking site .

10.5.5.g. Table showing the number of women who consider 277

none of the mentioned features of the product while

taking the buying decision of consumer electronic

product through a social networking site .

10.5.6. Table showing the number of women who compare 278

different electronic products available in retail store by

physically visiting the stores in the market before

making a final online purchase.

10.6.1. Table showing the number of women who buy the 279 product because they buy it regularly 10.6.2. Table showing the number of women who buy the 280

product because they think that the product is best fit

for them.

10.7.1. Table showing the number of women who buy the 280

product because they wanted to try out a different

variety of product, belonging to a different brand .

10.7.2. Table showing the number of women who like to buy a 281

new variety of product belonging to a new brand; each

time they make a purchase-decision after viewing an

advertisement on social networking site

10.7.3. Table showing the number of women who agree that 282

the different brands of the same product serve, one

and the same purpose

10.8.1. Table showing the number of women who agree that 283

taking a buying decision of an expensive electronic

product is difficult and needs a lot of thinking.

10.8.2. Table showing the number of women who agree that 284

taking a buying decision of an expensive electronic

product is time consuming.

10.8.3. Table showing the number of women who agree that 284 they have the feeling of anxiety that whether their purchase decision is correct. 10.9.1. Table showing the number of women who agree that 285 they had no plans of buying any consumer electronic products when they logged on a social networking site. 10.9.2. Table showing the number of women who agree that 286 the advertisement of the product on the social networking site provokes their purchase intentions. 10.9.3. Table showing the number of women who agree that at 287 times they buy a product just because they find the discount scheme displayed in the advertisement on the social networking site interesting and not available in the retail stores. 10.10.1.A Table showing the number of women liking anyone 288 SNS from Facebook, Twitter and LinkedIn the most. 10.10.1.B. Table showing the number of women according to 288 whom the most useful SNS is anyone from Facebook, Twitter and LinkedIn. 10.10.1.C. Table showing the number of women according to 289 whom the most preferable SNS to use is anyone from Facebook, Twitter and LinkedIn.

10.10.1.D. Table showing the number of women according to 289 whom the most user-friendly SNS is anyone from Facebook, Twitter and LinkedIn. 10.10.1.E. Table showing the number of women according to 290 whom the most striking SNS is anyone from Facebook, Twitter and LinkedIn. 10.10.2.A. Table showing the Facebook ratings for having a large 290 number of groups (networks) available for any demographics you are looking for; for instance group of teenagers, group of kids etc provided by working women. 10.10.2.B. Table showing the Twitter ratings for having a large 291 number of groups (networks) available for any demographics you are looking for; for instance group of teenagers, group of kids etc provided by working women. 10.10.2.C. Table showing the LinkedIn ratings for having a large 292 number of groups (networks) available for any demographics you are looking for; for instance group of teenagers, group of kids etc. provided by working women. 10.10.3.A. Table showing the Facebook ratings according to the 293 way they are targeting the advertisements to specific group of audience provided by working women. 10.10.3.B. Table showing the Twitter ratings according to the 294 way they are targeting the advertisements to specific group of audience, provided by working women. 10.10.3.C. Table showing the LinkedIn ratings according to the 295 way they are targeting the advertisements to specific group of audience, provided by working women. 10.10.4.A. Table showing the number of women who select the 295 site having more followers due to acquaintances 10.10.4.B. Table showing the number of women who select the 296

site having more unknown . 10.11.1.A.1. Table showing the number of women who have 297 positive reactions/feelings towards advertisements displayed on Facebook. 10.11.1.A.2. Table showing the number of women who have 297 positive reactions/feelings towards advertisements displayed on Twitter. 10.11.1.A.3. Table showing the number of women who have 298 positive reactions/feelings towards advertisements displayed on LinkedIn. 10.11.1.B.1. Table showing the number of women who think 298

advertisements displayed on Facebook are appealing.

10.11.1.B.2. Table showing the number of women who think 299 advertisements displayed on Twitter are appealing. 10.11.1.B.3. Table showing the number of women who think 299 advertisements displayed on LinkedIn are appealing. 10.11.1.C.1. Table showing the number of women who find the 300 visuals and slogans of the advertisements displayed on Facebook memorable. 10.11.1.C.2. Table showing the number of women who find the 300 visuals and slogans of the advertisements displayed on Twitter memorable. 10.11.1.C.3. Table showing the number of women who find the 301 visuals and slogans of the advertisements displayed on LinkedIn memorable. 10.11.1.D.1. Table showing the number of women who find the 302 product advertisement displayed on Facebook memorable. 10.11.1.D.2. Table showing the number of women who find the 302 product advertisement displayed on Twitter memorable. 10.11.1.D.3. Table showing the number of women who find the 303

product advertisement displayed on LinkedIn memorable. 10.11.1.E.1. Table showing the number of women who trust the 303 product advertisement displayed on Facebook. 10.11.1.E.2. Table showing the number of women who trust the 304 product advertisement displayed on Twitter. 10.11.1.E.3. Table showing the number of women who trust the 304 product advertisement displayed on LinkedIn. 10.11.2. Table showing the number of times the working 305 women have seen an advertisement for consumer electronics on SNS in the time they spend on Social networking site . 10.11.3. Table showing the number of working women who 306

were satisfied with the actual product which they

purchased after watching the advertisement on any of

the social networking sites.

10.12.1. Table Showing the frequency with which the young 307 working women access internet in Mumbai, Nashik and Surat. 10.12.4. Table Showing the number of young working women 309 accessing or using “Twitter” in Mumbai, Nashik and Surat. 10.12.5. Table Showing the number of young working women 310 accessing or using “LinkedIn” in Mumbai, Nashik and Surat. 10.12.6 Table Showing the number of young working women 311 accessing or using “Other SNSs” in Mumbai, Nashik and Surat. 10.12.8. Table Showing the number of young working women 312 not accessing SNS for the reason lack of interest in Mumbai, Nashik and Surat. Table Showing the number of young working women 313

10.12.9. not accessing SNS for the reason of security concerns in Mumbai, Nashik and Surat. 10.12.10. Table Showing the number of young working women 315 not accessing SNS for the reason of Non Availability of Enough time in Mumbai, Nashik and Surat. 10.12.11. Table Showing the number of young working women 316 not accessing SNS for the reason of more Prefering face to face interactions in Mumbai, Nashik and Surat. 10.12.12. Table Showing the number of young working women 317 not accessing SNS for the reason of Lack of computer skills in Mumbai, Nashik and Surat. 10.12.13. Table Showing the number of young working women 319 not accessing SNS for the reason of Prefering to use phone for interaction in Mumbai, Nashik and Surat. 10.12.15. Table Showing the time the young working women 320 spend each time they access LinkedIn in Mumbai, Nashik and Surat. 10.12.16. Table Showing the time the young working women 321 spend each time they access Twitter in Mumbai, Nashik and Surat. 10.12.17. Table Showing the time the young working women 322 spend each time they access Other SNS in Mumbai, Nashik and Surat. 10.12.18. Table Showing whether the young working women has 323 increased or decreased the time they spend using SNS in Mumbai, Nashik and Surat. 10.12.19. Table Showing whether the amount of time spent by 325 young working women for product information search is right, too much or not enough the time they spent using SNS in Mumbai, Nashik and Surat. 10.12.20. Table Showing whether the young working women 326 will be increasing, decreasing or spending the same amount of time using social networking sites for

product information search as compared to the last year in Mumbai, Nashik and Surat. 10.12.22. Table Showing whether the young working women 328 share their feedback about a product or service with the organization /Company in Mumbai, Nashik and Surat. 10.12.23. Table Showing whether the young working women 329 visit company website and provide a particular rating for a particular product or service in Mumbai, Nashik and Surat. 10.12.25. Table Showing whether the young working women 331 send the company link of their favourite brand to their family and friends in Mumbai, Nashik and Surat. 10.13.1.2.m.a. Table Relationship between consumer buying 333 behaviour with the appealing factor of social media advertisement towards advertisements displayed on SNS in Mumbai. 10.13.1.2.m.b. Table of Symmetric Measures to determine how much 334 relationship exists in between consumer buying behaviour and the appealing factor of social media advertising towards advertisements displayed on SNS in Mumbai. 10.13.1.2.n.a. Table Relationship between consumer buying 335 behaviour with the appealing factor of social media advertisement towards advertisements displayed on SNS in Nashik. 10.13.1.2.s.a. Table Relationship between consumer buying 336 behaviour with the appealing factor of social media advertisement towards advertisements displayed on SNS in Surat. 10.13.1.3.m.a. Table Relationship between consumer buying 338 behaviour with the factor of memorable visuals and slogans of the advertisements displayed on SNS in

Mumbai. 10.13.1.3.n.a. Table Relationship between consumer buying 339 behaviour with the factor of memorable visuals and slogans of the advertisements displayed on SNS in Nashik. 10.13.1.3.s.a. Table Relationship between consumer buying 340 behaviour with the factor of memorable visuals and slogans of the advertisements displayed on SNS in Surat. 10.13.1.4.m.a. Table Relationship between consumer buying 342 behaviour with the attractive factor of the advertisements displayed on SNS in Mumbai. 10.13.1.4.n.a. Table Relationship between consumer buying 343 behaviour with the attractive factor of the advertisements displayed on SNS in Nashik. 10.13.1.4.s.a. Table Relationship between consumer buying 344 behaviour with the attractive factor of the advertisements displayed on SNS in Surat. 10.13.1.4.s.b. Table of Symmetric Measures to determine how much 345 relationship exists in between consumer buying behaviour and the attractive factor of social media advertisements displayed on SNS in Surat. 10.13.1.5.m.a. Table Relationship between consumer buying 346 behaviour with the trustworthiness factor of the advertisements displayed on SNS in Mumbai. 10.13.1.5.n.a. Table Relationship between consumer buying 348 behaviour with the trustworthiness factor of the advertisements displayed on SNS in Nashik. 10.13.1.5.s.a. Table Relationship between consumer buying 349 behaviour with the trustworthiness factor of the advertisements displayed on SNS in Surat. 10.13.1.5.s.b. Table of Symmetric Measures to determine how much 350 relationship exists in between consumer buying

behaviour and the attractive factor of social media advertisements displayed on SNS in Surat. 10.13.2.2.m.a. Table Relationship between online purchase 352 behaviour with the appealing factor of social media advertisements displayed on SNS in Mumbai. 10.13.2.2.n.a. Table Relationship between online purchase 353 behaviour with the appealing factor of social media advertisements displayed on SNS in Nashik. 10.13.2.2.n.b. Table of Symmetric Measures to determine how much 354 relationship exists in between online purchase behaviour and appealing factor of social media advertisements displayed on SNS in Nashik. 10.13.2.2.s.a. Table Relationship between online purchase 355 behaviour with the appealing factor of social media advertisements displayed on SNS in Surat. 10.13.2.2.s.b. Table of Symmetric Measures to determine how much 356

relationship exists in between online purchase

behaviour and appealing factor of social media advertisements displayed on SNS in Surat. 10.13.2.3.m.a. Table Relationship between online purchase 357 behaviour with the factor of social media advertising i.e memorable visuals and slogans of the advertisements displayed on SNS in Mumbai. 10.13.2.3.n.a. Table Relationship between online purchase 358 behaviour with the factor of social media advertising i.e memorable visuals and slogans of the advertisements displayed on SNS in Nashik. 10.13.2.3.n.b. Table of Symmetric Measures to determine how much 359 relationship exists in between online purchase behaviour with the factor of social media advertising i.e memorable visuals and slogans of the advertisements displayed on SNS in Nashik. 10.13.2.3.s.a. Table Relationship between online purchase 360

behaviour with the factor of social media advertising i.e memorable visuals and slogans of the advertisements displayed on SNS in Surat. 10.13.2.3.s.b. Table of Symmetric Measures to determine how much 361 relationship exists between online purchase behaviour with the factor of social media advertising i.e memorable visuals and slogans of the advertisements displayed on SNS in Surat. 10.13.2.4.m.a. Table Relationship between online purchase 362 behaviour with the attractive factor of social media advertising in Mumbai. 10.13.2.4.n.a. Table Relationship between online purchase 363 behaviour with the attractive factor of social media advertising in Nashik. 10.13.2.4.n.b. Table of Symmetric Measures to determine the 364 relationship between online purchase behaviour with the attractive factor of social media advertising in Nashik. 10.13.2.4.s.a. Table Relationship between online purchase 365 behaviour with the attractive factor of social media advertising in Surat. 10.13.2.4.s.b. Table of Symmetric Measures to determine the 366 relationship between online purchase behaviour with the attractive factor of social media advertising in Surat. 10.13.2.5.m.a. Table Relationship between online purchase 367 behaviour with the trust factor of social media advertising in Mumbai. 10.13.2.5.n.a. Table Relationship between online purchase behaviour 369 with the trust factor of social media advertising in Nashik. 10.13.2.5.s.a. Table Relationship between online purchase behaviour 370

with the trust factor of social media advertising in

Surat.

10.13.3.2.m.a. Table Relationship between complex buying behaviour 372 with the appealing factor of social media advertising in Mumbai. 10.13.3.2.n.a. Table Relationship between complex buying 373 behaviour with the appealing factor of social media advertising in Nashik. 10.13.3.2.n.b. Table of Symmetric Measures to determine how 374 much relationship exist between complex buying behaviour and the appealing factor of social media advertising in Nashik. 10.13.3.2.s.a. Table Relationship between complex buying behaviour 375 with the appealing factor of social media advertising in Surat. 10.13.3.2.s.b. Table of Symmetric Measures to determine how much 376 relationship exists between complex buying behaviour and the appealing factor of social media advertising in Surat. 10.13.3.3.m.a. Table Relationship between complex buying 377 behaviour with the memorable visuals and slogans factor of social media advertising in Mumbai. 10.13.3.3.m.b. Table of symmetric measures to determine how much 378 relationship exists between complex buying behaviour and the memorable visuals and slogans factor of social media advertising in Mumbai. 10.13.3.3.n.a. Table Relationship between complex buying behaviour 378

with the memorable visuals and slogans factor of social

media advertising in Nashik.

10.13.3.3.s.a. Table Relationship between complex buying behaviour 380

with the memorable visuals and slogans factor of social

media advertising in Surat.

10.13.3.4.m.a. Table Relationship between complex buying 381 behaviour with the attractive factor of social media advertising in Mumbai. 10.13.3.4.n.a. Table Relationship between complex buying 382 behaviour with the attractive factor of social media advertising in Nashik. 10.13.3.4.s.a. Table Relationship between complex buying 384 behaviour with the attractive factor of social media advertising in Surat. 10.13.3.4.s.b. Table of symmetric measures to determine how much 384 relationship exists between complex buying behaviour and the attractive factor of social media advertising in Surat. 10.13.3.5.m.a. Table Relationship between complex buying 385

behaviour with the trust factor of social media

advertising in Mumbai.

10.13.3.5.m.b. Table of symmetric measures to determine how much 386 relationship exists between complex buying behaviour and the trust factor of social media advertising in Mumbai. 10.13.3.5.n.a. Table Relationship between complex buying 387 behaviour with the trust factor of social media advertising in Nashik. 10.13.3.5.n.b. Table of symmetric measures to determine how much 388

relationship between complex buying behaviour and

the trust factor of social media advertising in Nashik.

10.13.3.5.s.a. Table Relationship between complex buying behaviour 389

with the trust factor of social media advertising in

Surat.

10.13.5.m. Table showing relationship between all the factors of 390 variety seeking buying behaviour and all the factors of social media advertising in Mumbai. 10.13.5.n. Table showing relationship between all the factors of 391 variety seeking buying behaviour and all the factors of social media advertising in Nashik. 10.13.5.s. Table showing relationship between all the factors of 392 variety seeking buying behaviour and all the factors of social media advertising in Surat. 10.13.6.m. Table showing relationship between all the factors of 394

Dissonance buying behaviour and all the factors of

social media advertising in Mumbai.

10.13.6.n. Table relationship between all the factors of 395 Dissonance buying behaviour and all the factors of social media advertising in Nashik. 10.13.6.s. Table showing relationship between all the factors of 396 Dissonance buying behaviour and all the factors of social media advertising in Surat. 10.13.7.m. Table showing relationship between all the factors of 397 Impulsive buying behaviour and all the factors of social media advertising in Mumbai. 10.13.7.n. Table showing relationship between all the factors of 398

Impulsive buying behaviour and all the factors of

social media advertising in Nashik.

10.13.7.s. Table showing relationship between all the factors of 399 Impulsive buying behaviour and all the factors of social media advertising in Surat. 10.14.n.a. Table of Model Summary for Nashik 400

10.14.n.b. Table of Anova to determine the level of significance 401

10.14.n.c. Table for significance of Coefficients 402

10.14.s.a. Table of Model Summary for Surat 404

10.14.s.b. Table of Anova to determine the level of significance of 404

10.14.s.c. Table for significance of Coefficients 405 10.15.1.n. Table Showing effectiveness of SNSs in terms of more 407

Audience groups in Nashik.

10.15.2.n. Table Showing effectiveness of SNSs in terms of 408 targeting consumers in Nashik. Table Showing effectiveness of SNSs in terms of more 408 10.15.3.n. followers due to acquaintances in Nashik. 10.15.4.n. Table Showing effectiveness of SNSs in terms of more 409 unknown followers in Nashik. 10.15.1.s. Table Showing effectiveness of SNSs in terms of more 409 Audience groups in Surat. 10.15.2.s. Table Showing effectiveness of SNSs in terms of 410 targeting consumers in Surat. 10.15.3.s. Table Showing effectiveness of SNSs in terms of more 410 followers due to acquaintances in Surat. 10.15.4.s. Table Showing effectiveness of SNSs in terms of more 411 unknown followers in Surat. 10.16.1.n.a. Table Relationship between qualification of young 412 working women and impact of social media advertising in Nashik. 10.16.1.n.b. Table To determine qualification group has more or 413 less impact of social media advertisement in Nashik. 10.16.1.s.a. Table Relationship between qualification of young 414 working women and impact of social media advertising in Surat. 10.16.1.s.b. Table To determine how much relationship exists 414 between qualification of young working women and impact of social media advertising in Surat.

10.16.2.m.a. Table Relationship between annual income of young 415 working women and impact of social media advertising in Mumbai. 10.16.2.n.a. Table Relationship between annual income of young 416 working women and impact of social media advertising in Nashik. 10.16.2.n.b. Table To determine how much relationship exists 417 between annual income of young working women and impact of social media advertising in Nashik. 10.16.3.m.a. Table Relationship between occupation of young 418 working women and impact of social media advertising in Mumbai. 10.16.3.s.a. Table Relationship between occupation of young 419 working women and impact of social media advertising in Surat.

LIST OF FIGURES

Figure No. Title Page No.

3.1 Theoretical Model of the Study 111

4.1 Revenue distribution of LinkedIn 123

5.1 Three Cs of E-marketing ecosystem at HP 134

6.1. Showing the Markets that will lead the growth in tech 138 sector in the year 2015.

List of Abbreviations

SNS – Social Networking Sites.

SM – Social Media.

IMC –Integrated Marketing Communications.

CRM – Customer Relationship Management.

FMCG – Fast moving consumer goods.

PR – Public Relations eWOM – electronic word of mouth

PCAP – perceived community attitude toward a product

MAU – Monthly active users

CAGR - Compounded Annual Growth Rate.

SG&A - sales, general and administrative

SERP - search engine ranking position

CPC - cost per click

EBITDA - Earnings before Interest, Taxes, Depreciation and Amortization

USD - US Dollar

MNC - Multi-national company

ASSOCHAM - The Associated Chamber of Commerce and Industry of India

Executive Summary

Social media has created a huge buzz in today’s world. It is very popular in the younger generations, but the middle and the older generations are also not untouched by the wave of social media. On domestic front it is used for interacting with friends and relatives and for the purpose of socialising. On professional front, it has been widely used for acquiring markets by new business ventures. Many established organizations are undergoing operational change in their traditional practices in order to adapt to this online environment for promoting their products and services globally.

Social media has been the most recent and booming technological innovations. It offers a wide range of benefits. Interest and curiosity to gain more knowledge in the field of social media has been the main ground for selecting the topic of Social media for the research purpose. Also much research has not been done on social media in the

Indian context and more precisely in Maharashtra, therefore Social Media has been selected as the topic for research.

In the first part of this study the various concepts are defined like the concept of social media, social media advertising, consumer buying behaviour etc. Moving ahead in the second part of the study, social media and advertising, social media and consumer behaviour, social media and consumer electronics, social media and women have been discussed in combination. The third part of the study has talked in detail about the different social media tools like Facebook, Twitter and LinkedIn which are the only tools considered for the purpose of this study from the large number of existing

SNSs. In the fourth part of the study the various promotional strategies adopted by the

37 leading players in the consumer electronics segment are discussed in detail. The fifth part of the study throws light on the objectives of the study.

The objectives of the study were :

1. To study the reason of online consumer’s Social Media usage.

2. To study the customers buying behaviour with respect to Social media advertising.

3. To study the impact of social media advertising on the buying behavior of young

working women for consumer electronics.

4. To study the effectiveness of Social Media tools like face book, twitter, LinkedIn

on the consumer behaviour.

5. To study the impact of social media advertising on working women belonging to

different demographic factors such as qualification, annual income, occupation and

place.

The Research Methodology Adopted:

Data Collection:

Primary data was collected by questionnaire survey method. Research instrument

is questionnaire, personal interviews. Single questionnaire was created and

administered in three cities. The target audience was working women in the age

group of 18-35 from Mumbai, Nashik and Surat in this study.

The cities in India have been classified on the basis of grading structure devised by

the government of India. According to this gradation, Mumbai belongs to Tier I

category of cities and Nashik and Surat belongs to Tier II category (source for

information on Tier I & II cities of India: www.maps ofindia.com). The

requirement of the study was comparison between the tier one and tier two cities

having different population sizes. Therefore based on convenience, Mumbai was

selected as a Tier I city or a Metro city with heterogeneous population of 12.7

million and Nashik as a tier II city having population approximately 1.5 million

from Maharashtra and Surat having population 4.5 million was selected from

Gujarat (source :Reports of Internet And Mobile Association of India [IAMAI] and

Internet Market Research Bureau [IMRB] ).

Pilot Study :

Pilot study was conducted and the questionnaire was first pre-tested on a sample of

100 respondents (working women in the age group of 18-35) from Mumbai city for

checking the reliability of the questionnaire.

Reliability

The Chronbach’s Alpha found out was 0.860. Any value of Cronbach’s Alpha above

0.6 shows that the scale is reliable.

Questionnaire

The questionnaire comprised of several sections relating to the various aspects of social media advertising, buying behaviour etc. Essentially it comprises of :

1. Demographic aspects - 4 questions.

2. Usage of social media - 14 questions.

3. Buying behaviour including Consumer buying behaviour, complex, habitual

buying behaviour etc. - 25 questions.

4. Effectiveness of social media and impact of social media advertising - 15

questions.

Size and Design of Sample

The study was conducted in two cities of Maharashtra (Mumbai & Nashik) and in one city of Gujarat (Surat). The sample unit is working women in the age group of 18-35 and having knowledge of internet.

Sampling Technique :

Random Sampling technique has been used for this study. In a Random sample from infinite population, selection of each item is controlled by the same probabilities and the successive selections are independent of one another. (C.R.Kothari, Research

Methodology Methods and Techniques)

Sample size Calculation :

Where,

n = Sample size

= critical value

 = Standard Deviation

E = Estimated margin of error

2 Z   2  2  1.9618.19 n    1271.78  E   1   

Round off sample size is required is 1272 respondents.

Table on Chosen Sample Size

Name of the Cities No. of Respondents Sr. No.

1 Mumbai 516

2 Nashik 359

3 Surat 397

TOTAL 1272

Variables of the study :

Dependent Variables - Buying Behaviour with respect to Social Media Advertising.

Independent Variables - Online Purchase Behaviour, Consumer Buying Behaviour,

Complex Buying Behaviour, Habitual Buying Behaviour, Variety Seeking Buying

Behaviour, Dissonance Buying Behaviour, Impulsive Buying Behaviour.

Description of the Variables :

1. Online Purchase Behaviour :

“Online Purchase Behaviour”, this variable primarily indicates the online

behaviour of the consumer from the purchase point of view. It throws light on

a couple of things related to the purchase taking place online through the

medium of social media, like involvement of the consumer while taking the

online purchase decision, to what extent the consumer thinks there is a

difference in the products of different brands available online, what does the

consumer think about the price of the product available on social media and

does the consumer think that the decision making process in case of online

products is time consuming.

2. Consumer Buying Behaviour :

“Consumer Buying Behaviour”, this variable focuses on the online behaviour

of the consumer from the reasons which lead to the purchase through social

media, point of view. It considers the reasons which lead to the purchase like

whether the consumer read the blogs / reviews or view the advertisement on

social media. It also studies the consumers behaviour by considering, to which

electronic products consumer has provided rating.

3. Complex Buying Behaviour :

Complex buying behaviour when the consumer is highly involved in the

buying then it is called complex buying behavior. In case of complex buying

behavior the consumer must collect proper information about the product

features and attributes.

4. Habitual Buying Behaviour :

In case of Habitual buying behavior there is low involvement of the consumer.

The consumer buys the product belonging to a particular brand which has been

regularly preferred by them because the consumer thinks that the product

belonging to a particular brand is best fit for them. The consumer buys the

product quickly.

5. Variety-Seeking Buying Behaviour :

Variety seeking buying behaviour takes place when the consumer has many

different product choices that serve the same purpose. In case of Variety-

Seeking Buying Behaviour Consumers generally buy different products

because they want to try out a new variety of product.

6. Dissonance Buying Behaviour :

In Dissonance buying behavior consumer is highly involved in the purchase.

Dissonance buying behavior occurs when the product which the consumer is

thinking of buying is expensive or there are no differences or a few differences

between the brands. The consumers experience a feeling of discomfort or

anxiety after the purchase of the product, because they fear that the expensive

product which they have bought should not be a failure.

7. Impulsive Buying Behaviour :

Impulsive buying behaviour takes place when the consumer makes an

unplanned purchase, provoked by seeing the product or upon exposure to a

lucrative advertisement or scheme.

Limitations of the Study:

The study was conducted based on the data collected from Mumbai, Nashik

and Surat and therefore findings of this study may not be applicable to other

countries of the world because of the socio-cultural and economic differences.

Utility:

The study would be very useful to markets who would now be able to use

social media as a platform for promoting their products and services.

Conclusion of the study :

The detailed research has lead to certain conclusions which are being discussed in this chapter.

Association between Positive reactions or feelings towards social media advertisements with consumer buying behaviour :

It has been concluded from the study that there is a strong positive association between the factor of social media advertising i.e. positive reactions/feelings with the consumer buying behaviour in Mumbai and Nashik. So if there is any increase in the positive reactions/feelings it will positively affect the consumer buying behaviour. However there is no association between the factor of social media advertising i.e. positive reactions/feelings with the consumer buying behaviour in Surat.

Association between appealing factor of social media advertisements with consumer buying behaviour :

It has been concluded from the study that there is a strong positive association between the appealing factor of social media advertising with the consumer buying behaviour in Mumbai. However there is no association between the appealing factor of social media advertising with the consumer buying behaviour in Nashik and Surat.

Association between memorable visuals and slogans factor of social media advertisements with consumer buying behaviour :

It has been concluded from the study that the memorable visuals and slogans factor of social media advertising and consumer buying behaviour are

44 independent of each other and there is no association between the memorable visuals and slogans factor of social media advertising with the consumer buying behaviour in Mumbai, Nashik and Surat.

Association between attractive factor of social media advertisements with consumer buying behaviour :

It has been concluded from the study that the attractiveness factor of social media advertising and consumer buying behaviour are dependent of each other and there is a strong association between the attractiveness factor of social media advertising with the consumer buying behaviour in Surat. However there is no association between the attractiveness factor of social media advertising with the consumer buying behaviour in Mumbai and Nashik and they are independent of each other.

Association between trustworthiness factor of social media advertisements with consumer buying behaviour :

It has been concluded from the study that the trustworthiness factor of social media advertising and consumer buying behaviour are dependent of each other and there is a strong association between the trustworthiness factor of social media advertising with the consumer buying behaviour in Surat. However there is no association between the trustworthiness factor of social media advertising and the consumer buying behaviour in Mumbai and Nashik and they are independent of each other.

Association between Positive reactions or feelings towards social media advertisements with online purchase behaviour :

It has been revealed from the study that there is an association between the factor of social media advertising i.e. positive reactions/feelings with the online purchase behaviour in Nashik and Surat. So if there is any change in the positive reactions/feelings it will lead to change in the online purchase behaviour. However there is no association between the factor of social media advertising i.e. positive reactions/feelings with the online purchase behaviour in Mumbai.

Association between appealing factor of social media advertising and online purchase behaviour :

It has been revealed from the study that there is an association between the appealing factor of social media advertising and the online purchase behaviour in Nashik and Surat. So if there is any change in the appealing factor of social media advertising it will lead to change in the online purchase behaviour.

However there is no association between the appealing factor of social media advertising and the online purchase behaviour in Mumbai.

Association between memorable visuals and slogans factor of social media advertising and online purchase behaviour :

46 to change in the online purchase behaviour. However there is no association between the memorable visuals and slogans factor of social media advertising and the online purchase behaviour in Mumbai.

Association between attractiveness factor of social media advertising and online purchase behaviour :

It has been revealed from the study that there is an association between the attractiveness factor of social media advertising and the online purchase behaviour in Nashik and Surat. So if there is any change in the attractiveness factor of social media advertising it will lead to change in the online purchase behaviour. However there is no association between the attractiveness factor of social media advertising and the online purchase behaviour in Mumbai.

Association between trustworthiness factor of social media advertising and online purchase behaviour :

It has been revealed from the study that there is no association between the trustworthiness factor of social media advertising and the online purchase behaviour in Mumbai, Nasik and Surat. The trustworthiness factor of social media advertising and the online purchase behaviour are independent of each other.

Association between Positive reactions or feelings towards social media advertisements with complex buying behaviour :

47 change in the positive reactions/feelings factor of social media advertising, it will lead to change in the complex buying behaviour.

Association between appealing factor of social media advertisements with complex buying behaviour :

It has been revealed from the study that there is a strong relationship between the appealing factor of social media advertising with complex buying behaviour in Nashik and Surat. So if there is any change in the appealing factor of social media advertising, it will lead to change in the complex buying behaviour. However there is no relationship between the appealing factor of social media advertising and complex buying behaviour in Mumbai and they are independent of each other.

Association between memorable visuals and slogans factor of social media advertisements with complex buying behaviour :

It has been revealed from the study that there is a strong relationship between the memorable visuals and slogans factor of social media advertising with complex buying behaviour in Mumbai. So if there is any change in the memorable visuals and slogans factor of social media advertising, it will lead to change in the complex buying behaviour. However there is no relationship between the memorable visuals and slogans factor of social media advertising and complex buying behaviour in Nashik and Surat.

Association between attractiveness factor of social media advertisements with complex buying behaviour :

It has been revealed from the study that there is a strong relationship between the attractiveness factor of social media advertising with complex buying behaviour in Surat. So if there is any change in the attractiveness factor of social media advertising, it will lead to change in the complex buying behaviour in Surat. However there is no relationship between the attractiveness factor of social media advertising and complex buying behaviour in Mumbai and Nashik and they are independent of each other.

Association between trustworthiness factor of social media advertisements with complex buying behaviour :

It has been revealed from the study that there is a strong relationship between the trustworthiness factor of social media advertising with complex buying behaviour in Mumbai and Nashik. So if there is any change in the trustworthiness factor of social media advertising, it will lead to change in the complex buying behaviour in Mumbai and Nashik. However there is no relationship between the trustworthiness factor of social media advertising and complex buying behaviour in Surat and they are independent of each other.

Relationship between all the factors of Habitual Buying Behaviour with all the factor of Social Media Advertisement in different cities :

From the study it has been concluded that all the factors of Social Media

Advertisement and all the factors of Habitual Buying Behaviour of young working women for consumer electronics in Mumbai are independent of each

49 other. However in Nashik and Surat, all the factors of Social Media

Advertisement and all the factors of Habitual Buying Behaviour of young working women for consumer electronics are dependent of each other.

Relationship between all the factors of Variety Seeking Buying Behaviour with all the factor of Social Media Advertisement in different cities :

It has been concluded from the study that all the factors of Social Media

Advertisement and all the factors of Variety Seeking Buying Behaviour of young working women for consumer electronics in Mumbai, Nashik and Surat are dependent of each other.

Relationship between all the factors of Dissonance Buying Behaviour with all the factor of Social Media Advertisement in different cities :

It has been concluded from the study that all the factors of Social Media

Advertisement and all the factors of Dissonance Buying Behaviour of young working women for consumer electronics in Mumbai are dependent of each other. However all the factors of Social Media Advertisement and all the factors of Dissonance Buying Behaviour of young working women for consumer electronics in Nashik and Surat are independent of each other.

Relationship between all the factors of Impulsive Buying Behaviour with all the factor of Social Media Advertisement in different cities :

It has been concluded from the study that all the factors of Social Media

Advertisement and all the factors of Impulsive buying behaviour of young working women for consumer electronics in Nashik and Surat are dependent of each other. However all the factors of Social Media Advertisement and all

50 the factors of Impulsive buying behaviour of young working women for consumer electronics in Mumbai are independent of each other.

Impact of Social Media advertising on different factors of buying behaviour of young working women for consumer electronics in Mumbai

From the study it has been concluded that in Mumbai, Social media advertising has a significant impact on the following factors of buying behaviour - Consumer Buying Behaviour, Complex buying behaviour,

Variety-seeking buying behaviour, Dissonance buying behaviour.

Impact of Social Media advertising on different factors of buying behaviour of young working women for consumer electronics in Nashik :

It has been revealed from the study that in Nashik, Consumer Buying

Behaviour and Variety - Seeking buying behaviour are the factors of buying behaviour which are significantly impacted by Social media advertising.

Impact of Social Media advertising on different factors of buying behaviour of young working women for consumer electronics in Nashik :

It has been revealed from the study that in Surat, Consumer Buying

Behaviour, Complex buying behaviour, Habitual buying behaviour,

Dissonance and Variety - Seeking buying behaviour are the factors of buying behaviour which are significantly impacted by Social media advertising.

Effectiveness of social media tools like Face book, Twitter , LinkedIn on the consumer Behaviour in Mumbai :

Audience:

From the research study it has been concluded that in Mumbai the young working women prefer most Face book, as the Social networking sites that have a large number of groups (networks) available for any demographics you are looking for; for instance group of teenagers, group of kids, youth, group of new moms, brides, sports fans, technology enthusiasts, entrepreneurs etc.

Face-book is followed by LinkedIn and Twitter is the least preferred site.

Targeting :

From the study it has been concluded that Face book is the most preferred

Social networking site that targets the advertisements to specific group of audience according to the young working women in Mumbai. Face book is followed by LinkedIn and the least preferred site for targeting the advertisements to specific group of audience is Twitter in Mumbai.

More followers due to acquaintances :

From the study it has been observed that in Mumbai, Face-book has more followers due to acquaintances, followed by Twitter and LinkedIn has the least number of followers due to acquaintances.

More Unknown followers :

From the study it has been observed that in Mumbai, Face-book has more unknown followers, followed by Twitter and LinkedIn has least number of unknown followers.

Effectiveness of social media tools like Face book, Twitter , LinkedIn on the consumer Behaviour in Nashik :

Audience:

From the study it is concluded that in Nashik, the young working women prefer most Face book, followed by Twitter and least preferred is LinkedIn as the Social networking sites that have a large number of groups (networks) available for any demographics; for instance group of teenagers, group of kids, youth, group of new moms, brides, sports fans, technology enthusiasts, entrepreneurs etc.

Targeting :

From the study it has been observed that in Nashik, the young working women prefer most Face book, followed by LinkedIn and least preferred is twitter as the social networking sites targeting the advertisements to specific group of audience.

More followers due to acquaintances :

From the study it has been observed that in Nashik a maximum number of young working women agreed that Face book has more number of followers

53 due to acquaintances, followed by Twitter and LinkedIn has the minimum number of followers due to acquaintances.

More Unknown followers :

From the research it has been revealed that in Nashik, a maximum number of young working women said that face book has more unknown followers, followed by Twitter and LinkedIn has minimum unknown followers.

Effectiveness of social media tools like Face book, Twitter , LinkedIn on the consumer Behaviour in Surat :

Audience :

From the study it has been observed that in Surat the young working women prefer Face book most, followed by Twitter and the least preferred is

LinkedIn, as the Social networking sites that have a large number of groups

(networks) available for any demographics; for instance group of teenagers, group of kids, youth, group of new moms, brides, sports fans, technology enthusiasts, entrepreneurs etc.

Targeting :

From the study it has been concluded that in Surat, the young working women prefer most Face book, followed by Twitter and least preferred is LinkedIn as the Social networking sites targeting the advertisements to specific group of audience.

More followers due to acquaintances :

From the study it has been observed that in Surat, maximum number of young working women said that Face book has more followers due to acquaintances, followed by Twitter and LinkedIn has least number of followers due to acquaintances.

More Unknown followers :

From the study it has been observed that in Surat, a maximum number of respondents said that LinkedIn has more unknown followers, followed by Face book and Twitter has minimum number of unknown followers.

Relationship between impact of social media advertising of young working women with their qualification in different cities :

From the study it has been concluded that in Mumbai qualification of the young working women does not have any effect on the impact of Social media advertising. However qualification of the young working women has a direct effect on the impact of social media advertising in Nashik and Surat. Social media advertising has more impact on non graduate young working women followed by post graduate and graduates in Nashik. While Social media advertising has more impact on non graduate young working women followed by graduates and post graduate in Surat.

Relationship between impact of social media advertising of young working women with their Annual Income in different cities :

From the study it has been observed that annual income of young working women does not have any relationship with the impact of social media

55 advertising in Mumbai. However in Nashik and Surat the annual income of young working women has a substantial relationship with the impact of social media advertising. From the findings of the study it has been observed that the impact of social media advertising is more observed on the young working women having annual income upto 3 lakhs followed by young working women in the income groups of 3.1- 5, 5.1 – 10 and above 10 lakhs in Nashik.

In surat the impact of social media advertising is found to be more on young working women having annual income upto 3 lakhs followed by young working women in the income groups of 3.1- 5, above 10 lakhs and minimum impact is observed on the young working women having annual income in the group of 5.1 – 10 lakhs.

Relationship between impact of social media advertising and the

Occupation of young working women in different cities :

From the study it has been concluded that Occupation of young working women does not have any effect on the impact of social media advertising in

Mumbai and Surat. However in Nashik, occupation of the young working women does affect the impact of social media advertising. The impact of social media advertising is more observed on business class women, followed by women doing service and finally the self-employed women.

Recommendations & Suggestions :

The consumer electronics segment has a large scope of penetrating in smaller cities like Nashik, where large market is still untapped. This gap should be bridged and the awareness of Social Media should be increased in smaller

56 cities, so that organizations can directly reach more and more consumers and can interact with them.

The Social networking sites like LinkedIn and Twitter can improve their advertising efficiency by enhancing features like targeting the advertisements to the right group of audience, introducing more groups for any demographics like group of engineers, manufacturers, entrepreneurs, doctors, youth, house wives etc., more user friendliness so that more and more audience are attracted towards them for socialising as well as accessing product information.

The study has revealed that the impact of social media advertising is more on undergraduates, business class and young working women having annual income around three lakhs. Therefore there is a need for the consumer electronics companies to find out the reasons for not accessing social media, among the young working women belonging to other educational, economic and occupational background and spreading awareness among them about the

Social Media tools and to reach out to them through social media in order to tap more consumers and increase the business. So consumer electronics segment should take social media to smaller cities and should work towards building trust in this less explored market.

Future Scope of Study :

The study today is applicable to working women in selected cities of

Maharashtra and Gujarat and to consumer electronics product segment. In future, the study can be carried out to the other areas of consumer markets and also to other cities of India. Additionally the study could also be extended to other group of women e.g. college students, house wives etc.

Chapter 1

Introduction

In the last few years, the trend in worldwide business has been the adoption of new marketing strategies that utilize the ever-advancing technology applications available today. One of the foremost technology application used in business promotion has been the use of social media. Social media has emerged as an Internet-based platform which is extremely dynamic and vibrant. It has proved to be an extremely useful platform where one person can communicate with hundreds or thousands of other people.

Indian context and more precisely in Maharashtra, therefore Social Media has been selected as the topic for research.

1.1 Concept of Social Media, Advertising, Advertising on Social Networking sites and Consumer Behaviour:

Concept of Social Media :

Social Media refers to a collection of social technologies which have enabled a revolution in user generated content, global community and publishing of consumer opinion. It can also be defined as a group of Internet-based applications that is built on

58 ideological and technological foundations of Web 2.0 and that allow the creation and exchange of User Generated Content (Andreas Kaplan and Michael Haenlein 2010).

Concept of Advertising :

Advertising is the non-personal communication of information usually paid for and usually persuasive in nature about products, services or ideas by identified sponsors through the various media (Bovee 1992,7).

Concept of Advertising on Social Networking sites:

The term Social Network Advertising is the advertising which is done online through

Social networking sites like Facebook, Friendster, twitter etc. It is a paid form of promotion of brand or product or service and require a properly planned communicative message and budget. This form of advertising is more customer centric and customers play a vital role in short or long communication because they are one who will decide the fate of the advertising communication. (P. Sri. Jothi, M.

Neelamalar and R. Shakthi Prasad, 2011)

Concept of Consumer Behaviour :

Blackwell (2001) defines consumer behaviour as the activities people undertake when obtaining, consuming and disposing of products and services. Consumer Behaviour is composed of five dimensions namely, perception, information/ learning, attitude, motivation and actual behaviour.

1.2 Origin Of Social Media :

In the year 1979, Usenet was created by Jim Ellis and Tom Truscott from Duke

University, a platform which allowed Internet users from across the world to post public messages. The period of Social Media started 20 years earlier when Bruce and

Susan Abelson founded “Open Diary” , a social networking site developed in the very initial years and which brought together all the online diary writers into one community. The term “weblog” was first used at the same time and was truncated to

“blog” a year later. The growing availability of high speed Internet access added to the popularity of the concept, leading to the formation of social networking sites like

MySpace(in 2003) and Facebook (in 2004) and coining of the term “Social Media”.

1.3 Popularity of Social Media:

There is a significant rise in the use of Social Media among Internet surfers. In 2007,

56% of Internet surfers used Social Media which grew in 2008 to almost 75% . The growth of Social Media was not limited to teenagers, members belonging to the age group of 35-44 years old, increasingly participate as joiners, spectators and critics.

The Universal McCann tracker study I which was conducted up to 2008, measured the usage of the main social platforms across the world among 17,000 active web users.

The number of surfers reading blogs increased from 54% to 77% globally in just two years. The number of surfers who had written and created blogs increased from 28% to 45%. The consumer-driven multimedia platforms such as video sharing, also increased from 32% in 2006 to 83% in 2008, making social media the fastest growing platform in the history. Asian internet users are the most active users of blogs, particularly South Korea and China, where blogs are accepted as a form of social community. The next most active users are in Latin America. The well established

60 web markets of the US and Europe demonstrate a slightly lower levels of adoption and a more passive approach towards creating and sharing content. However the

‘active participation rates’ are increasing rapidly (Tom Smith, 2010).

1.4 Advertising:

Our lives are governed by advertisements to a great extent. They have also become a vital element of the corporate world and large amount of money is being assigned by companies towards their advertising budget. Advertising has evolved to a great extent over the years. In today’s world a large gamete of choices are available to the

Advertisers, of the medium, through which they can advertise their product or service.

The medium of Advertising can be categorized into Print advertising, Guerrilla advertising, Broadcast advertising, Outdoor advertising, Public service advertising,

Product placement advertising, Cell phone and mobile advertising and Online advertising. When an advertisement is printed it is called as Print advertising like newspapers, magazines, booklets etc. Guerrilla advertising is a form of unconventional advertising which mainly involves creative ideas and it allows the consumers to interact or participate in the advertisement. It normally spreads through word of mouth and social media. Broadcast advertising takes place through television, radio and has the capability to reach the masses. Outdoor advertising is any type of advertising that reaches the consumer when he or she is out of the home e.g. Billboard, kiosks, trade shows etc. Public service advertising is advertising done for a social cause, primarily to educate and inform people and not for sale of products or services. Product placement advertising is the promotion of branded products or services in context with a movie or show. Mobile advertising is a comparatively new form of advertising and it is spreading rapidly with the help of face-book and twitter

61 applications over smart-phones. Online Advertising is another comparatively new form of advertising. When any advertisement is displayed over a website through internet it is called as online advertisement. It involves advertising through emails, search engines, social media advertising and many types of display advertising like banner advertising etc. Online advertising is a large business and is widely used across all industry sectors. It is growing extensively. This study focuses on Social

Media Advertising.

1.5 Social Media Advertising :

Media propagation has changed the ways in which advertising messages are delivered and received. Due to the high costs incurred in delivering a mass audience, advertisers are moving away from television and investing in alternate media, such as social network sites (SNSs), to reach their target customers. The emergence of Social Media has helped organisations in engaging in a direct, efficient, cost effective and timely end-consumer contact as compared to the traditional communication tools. Therefore

Social Media Advertising is more beneficial not only to large multinational firms, but also to small and medium sized companies, and even non profit and governmental agencies. “Marketing over conventional channels is four times more expensive than marketing over the Internet” (Verity and Hof,1994). Companies communicate with consumers through a wide range of online, word-of-mouth forums including blogs, company-sponsored discussion boards and chat rooms, consumer product or service rating websites and forums, internet discussion boards and forums, mo-blogs (sites containing digital audio, images, movies or photographs) and social networking websites to name a few. With the help of Social network sites (SNSs) consumers can actively interact with advertising like for instance SNS gives opportunity to the

62 consumers to “like” certain ads, follow ads on twitter, share them with friends and to know which friends like the ads. Many consumers are turning away from the traditional sources of advertising like radio, television, magazines, newspapers and are using Social Media more frequently to search information about products and make purchase decision. Therefore many researchers think that Social Media should be included as an integral part of the organization’s Integral Marketing

Communication strategy. Integral Marketing Communication (IMC) is an important principle organizations follow to communicate with their target markets. “Marketing on the internet known as the world wide web results in ten times as many units sold with one-tenth the advertising budget” (M. Potter, 1994)

The main benefit of selecting Social networking sites for advertisement is that the advertiser can use the user’s demographic information and target their advertisement appropriately.

On one hand Social media has given immense powers to the consumers which they have never experienced in the marketplace before; and on the other hand, the organizations have no direct control over the content, duration and frequency of the social media-based conversations.

The relationship between businesses and customers is changing with the introduction of Social Media. Various aspects of consumer behaviour are being influenced by

Social Media. The businesses are required to develop their marketing strategies in order to generate a genuine relationship with its customers. According to a study

Face-book had a higher amount of influence; than Twitter, on the buying behaviour of social media users. A variety of new ways and sources of online information, that are

63 created, circulated and used by consumers with the intention of educating each other about products, services, personalities and issues have been thrown open by Social

Media. Just as consumers are becoming social, the products they purchase and the organizations they interact with have to be social as well. The companies mere presence on the Face book or Twitter is not going to increase it’s turnover, the companies should use the Social networking sites to change the traditional purchasing process.

Sony made a lot of profit through its social media campaign that incentivised people to purchase their products. They offered to the Twitter users a chance to build a customised Sony Vaio Laptops alongwith a 10% discount. And it worked by increasing the company’s sales from Twitter for that period of $1.5 million. The prime objective of this Sony campaign was to achieve more sales by giving little bit extra to the users – by giving the consumers a customised laptop which will fit their requirement. The Twitter users felt privileged for getting the customised laptop according to their requirements and to get an extra discount of 10% which nobody else got. (Source : Evidence that Social Media Really Does Drive Sales; dated :

18/11/2014)

IBM raised millions of dollars using social media. According to Ed Linde II, Senior

Marketing Manager at IBM, they have been successful in increasing the sales by simply ‘listening for leads’.

Dell announced that it made a sale of $3 million in sales through their Twitter account in 2009.

There has been a dramatical shift in the online consumer’s buying behaviour that shows most of them prefer to buy through social media. It has been found that the users of Facebook and Twitter spend more money online than the average internet users. This is partly because companies are making it easier to buy through social networks and more online consumers have begun trusting in SN, social shopping or group buying.

1.6 Consumer Buying Behaviour :

Consumer buying behaviour is the way in which the consumers behave or react

while purchasing a product. Consumers buying behaviour is a long process in which

the consumer has to identify the product, study its features well which involves

minutely knowing its pros and cons, and finally deciding on whether to purchase it

or not. The consumers of products or services exhibit different types of consumer

buying behaviour. Following are the different types of consumer buying behaviours:

i. Complex buying behaviour :

This type of buying behaviour involves complete involvement of the buyer.

Complex buying behaviour is normally witnessed when the product which the

buyer wants to purchase is an expensive one, or carries itself with a great risk

factor or is not purchased very often. E.g. buying a laptop, house, television etc.

ii. Habitual buying behaviour :

In this buying behaviour the buyer purchases the product that he has been using

previously for a long time without thinking of switching to another brand. E,g.

Habitual buying behaviour can apply to products like sugar, bread etc.

iii. Dissonance reducing buying behaviour :

This type of buying behaviour is exhibited in case of products which are

expensive or has a risk involved in its purchase and when there are number of

brands that have very less or no difference. The consumers develop a sense of

discomfort after purchasing the product and fears if the product fails to perform

when a lot of money is spent in buying that product. E.g. buying a car, mobile etc. iv. Variety seeking buying behaviour :

This type of buying behaviour is seen when consumers have a many different

product choices that serve the same purpose. As the different brands of the same

product serve only one purpose the consumers my tend to tryout a different brand.

E.g. products like cooking oil, detergent which do not have much difference in the

different brands so the consumer may tryout different brands of these products

every time they want to purchase it. v. Impulsive Buying Behaviour :

This type of behaviour is exhibited by the buyer when he sees the product and

cannot resist from buying it. E.g. cloths, jewellery etc.

1.7 Online Consumer’s Buying Behaviour :

This research intends to study the impact of social media advertising on online consumer’s buying behaviour. The adoption of advanced technologies have changed the manner in which people buy a product or choose a service. The Consumer behaviour of online consumers is posing a great challenge to the marketing managers to develop the right digital (product promotion) strategy that meets the changing needs and retain the competitiveness in the marketplace. Various aspects of consumer behaviour including information acquisition, awareness, attitudes, opinions, purchase behaviour and post purchase communication and evaluation are influenced by Social

Media. Online consumers are unwilling to read large amounts of data. They prefer brief but complete information while seeking the key benefits of a product or service.

Integrated timesaving features like pop-up descriptions, photo galleries, product comparison etc. are always valued by the online consumers. Product/Service reviews are more preferred over automated recommendations. Buying decisions of consumer products, vacations and movies are more influenced by online information. It is very important for the organizations to know online customer’s expectations and reactions to advertisements, in order to attract and to retain them (online customers).

Knowledge of consumer behaviour is critical to develop an appropriate advertising strategy. It is very difficult to understand the consumers; rather it is a complex and multi-dimensional process. Consumers may say one thing and do another. They may respond positively to influences or advertisements and may change their mind at the last minute. Therefore gaining the correct knowledge about consumers is extremely important before planning an advertising strategy. This research tends to throw a light on the effect of Social media advertising on the various types of consumer buying

67 behaviours like Complex, Variety seeking, Impulsive, Habitual and Dissonance buying behaviour.

1.8 Women and Social Network Sites(SNSs):

Women are the driving force behind the SNSs and represent a proliferating portion of the SNS user population. SNSs have a majority of female users as compared to males. Women are using SNSs to connect with their old friends, make new ones, as well as maintain social ties with their family and friends across the globe using SNS.

The research suggests that the female user population of SNSs has increased since

2008, while the male user population is declining over the years. It is therefore important for academicians and practitioners to understand that women play a vital role in the propagation of SNSs.

1.9 Consumer Electronics and Social Media :

The consumer electronics sector can be called as an ice-breaker or the first mover in trying out the digital marketing techniques. Consumer electronics is among the most popular product categories that consumers purchase online (Nielson 2010).

A change has been observed in the advertising strategy of electronic items and the electronics manufacturers are now using and rather emphasising consumer’s experience for promoting the electronic products than the traditional product lead method of promotion. The competition in terms of price, loyalty has lead brands to find even more innovative and effective ways of engaging directly with the consumers. Social media has served as a crucial weapon in this battle. In the year

2007, Philips a well known brand in Consumer electronics, launched a universal

‘experiential website’ in order to change the traditional product-led approach to an

68 approach which makes consumers aware of the experiences of the people who have used the Philips products. This was a wider shift in the advertising strategy taken up by Philips even though their online sale was extremely good, around 70m products every year.

Matt McDowell, the marketing director of Toshiba states that Social media has provided a platform where organizations can give more contents about the product and answer more questions raised by the traditional media, specifically the TV.

According to him the medium of TV only raises questions in the minds of the consumers and causes a craving in people to want to know more. However digital medium provides a bridge from engagement and interest right through to purchase.

Social media has helped in giving a special element to the advertising campaigns; the element of personal touch or user friendliness. A survey by GfK Technology UK has shown that there has been an increase of nine points in the Consumer Confidence index for digital media. Therefore more and more organizations are directing a hefty chunk of their media budget towards digital marketing.

Digital Pioneers : According to Ruth Speakman, general manager at Sony Europe,

Sony was accidentally introduced to Social Media in 2005 when it was running a campaign to promote the Bravia LCD TV. The campaign was based on a TV advertisement however it took off in Social Media and this proved to be an eye opener for the company to the power of this platform.

A Space chair campaign was launched by Toshiba for promoting its new LED TV and this campaign was rooted in Social Media.

Panasonic also launched its first Facebook campaign to promote its latest compact digital camera, the Lumix ZX-1 with 8x optical zoom and got a very positive response.

Customer reviews and Online communities play a vital role in the customer-led promotion process. The consumers have a lot of questions which they ask through reviews and forums. The Online community has experts and customers, who build up a dialogue with consumers and answer their queries. Online videos are also becoming popular for educating consumers. Thus consumer electronics sector is efficiently merging the use of videos and social media, giving its brand’s otherwise complex products a platform where all its contents can be seen and directly read by the consumers. “The growth in online reviews, ratings and feedback forums puts power in the hands of consumers” (Robbie Tutt). The growth in digital marketing has provided new opportunities to new players and has lead to the ‘reinvention’ of the established ones and has resulted in a major shift in the market, with companies which understand and adopt digital marketing making comparatively more profits.

For the purpose of research, selected consumer electronic items have been taken into account such as music players, television set, video recorder, DVD players, digital cameras, personal computers/Laptops, telephone instruments, mobile phones, video games consoles, camcorders.

Chapter 2

Review of Literature

The whole essence of this study has been to study the impact of advertising done, using social media tools like face-book, twitter, LinkedIn, on consumer buying behaviour. The argument that Social Media played an influential role in shaping consumer perception and ultimately affected the buying behaviour of the consumers, has been given considerable attention. In order to get complete understanding of the theory and practice, various International as well as National Literature Review has been analyzed and reviewed.

1. Andreas M. Kaplan and Michael Haenlein (2010) in Users of the world, unite!

The challenges and opportunities of Social Media, has defined Social Media as a group of Internet-based applications that is built on ideological and technological foundations of Web 2.0 and that allow the creation and exchange of User Generated

Content. The writer of the paper has explained that although Social Media is a related concept, with Web 2.0 and User Generated Content and has evolved from the same, however it differs from them on technological and ideological grounds. The various types of Social Media tools or applications like Collaborative projects, blogs, content communities, social networking sites, virtual game worlds and virtual social worlds are explained in detail. The author says that today everything is about social media and that if you do not participate in Face-book, YouTube, Twitter you are no more a part of cyberspace. Social media is a tool through which businesses can directly contact the end-consumers, within short span of time and with great efficiency and that too at low cost as compared to other traditional media. This paper recommends

71 companies, for developing their own Social Media strategies in order to be a part of this new trend and gain more profits.

2. W. Glynn Mangold and David J. Faulds (2009) in Social Media : The new hybrid element of the promotion mix, argues that Social Media is a hybrid element of the promotion mix because in a traditional sense it enables companies to talk to their customers, while in a non-traditional sense it enables customers to talk directly to one another. The writers feel that Social Media being a hybrid element of the promotional mix, should be incorporated as an integral part of the company’s Integrated Marketing

Communication (IMC). When Procter and Gamble (P&G) or General Electric (GE) entered the arena of Social Media, they carefully framed their communications with the market place in order to consistently reflect their organizational values and they acknowledge the value of incorporating Social Media into their IMC strategies and promotional efforts.

The second promotion related role of Social media is : customers can use Social

Media to communicate with one another. The organization cannot control the content, timing, and frequency of the social media based conversations occurring between consumers. This stands in contrast to the traditional integrated marketing communications paradigm where organizations have a high degree of control over the customer’s communication. The Social Media has profoundly affected all aspects of consumer behaviour, and has bestowed consumers with power they have not previously experienced in the marketplace (Li & Bernhoff, 2008).

3.Tom Smith (2010) in The social media revolution, says that the impact of Social

Media is being felt across the globe. Social Media has changed the manner in which

72 the communication between the organizations and the customers were taking place; it has changed from talking through mass media to listening and conversing through social media. Since the consumer online is a commentator, reviewer and publisher, all the organizations have to stop talking and start listening to how they are perceived online. Listening is just the start, after listening, actively participating in the discussions with the consumers and engaging them is crucial. This engagement with the consumers online will be the key way for building long-term advocates of the brand, who not only purchase their products but also recommend them on and offline.

The writer then opines that there is a huge opportunity for research, as the need for research outputs and knowledge will shape the consumer opinion. Research and research companies have a great scope for research through Social Media and the research companies that evolve with Social Media can increasingly prosper. Research

Companies can evolve in various ways :

Build community : Consumers want to share views and opinion and communities should grab this opportunity and tap in. This means providing constant surveys, message boards, listening permanently and not occasionally, and making the conversation two-way by sharing results back with them.

Work with brands to build research communities: Research agencies and companies should work together and two-way research oriented portals should be implemented by organisations. Research agencies should constantly and carefully monitor the consumer’s conversations and help the organizations with the latest updates.

Widgitise : widgets or mini applications allow you to place your site or content in an external web environment. These offer a new way of building and maintaining research communities and distributing surveys.

Embrace social media platforms as research platforms: Sharing information, content, opinions through wikis, network sites, blogs, video sites, generates a large amount of data which can be very helpful for research. Therefore the social media platforms should be used as research platforms.

4.Yin, Sara (2008) in her research paper How Social Media and PR Connect, writes that with the emergence of Social Media, the whole communications landscape has transformed and the mass mobilizing power of Social Media is tremendous.

People think that Social Media is a threat to traditional PR and mainstream media, however Social media complements traditional PR and traditional PR will exist as an important component of any successful business. The PR and advertising agencies are all undergoing a change and are trying to evolve their strategy, physical structure and business models to be in tune with social media.

5. Áine Dunne, Margaret-Anne Lawlor, Jennifer Rowley (2010) in their study Young people’s use of online social networking sites-a uses and gratifications perspective have made an attempt to find out the reason behind young people’s use of social networking site with special reference to bebo. The results of the study indicate that the participants were using bebo for their personal motives and in order to maintain a certain persona and identity in social context. The impersonal nature of the

Social media has lead to facilitate the young people where they can negotiate the practicalities and forge the identities and maintain relationships.

6. Irene, falsePollach (Oct-Dec 2008) in their study on Media Richness in Online

Consumer Interactions : An Exploratory Study of Consumer-Opinion Web Sites have exclusively discussed on Consumer Opinion websites which provide opportunities to people to share their opinions or views about a product or service, read others opinions and also interact with other consumers. The writers have identified three major challenges which the consumer opinion websites face and they are i. quality of contributions ii. motivating users to participate iii. earning reader’s trust. The main objective of this article is to find out ways by which the quality of the contents of these websites is enhanced so that it becomes a useful source of information for the consumers as well as the companies. The conclusions drawn from the study shows that the consumer opinion websites are more influential and provide more valuable information when they separate the complex task of information search and dissemination from the simple task of social interaction, and support each task with appropriate levels of richness. The writers conclude that consumers should consider both positive and negative points about a product or service before stating their opinion.

7. Anil Bhatt (May 2012) in his paper on Blog Popularity And Activity On Social

Media : An Exploratory Research has made an attempt to find out the impact of some social media website’s popularity on ROI. Social media provides a global opportunity for brands to use them as an effective channel for marketing of products and services. However the effectiveness of any marketing channel is largely dependent on a very important entity the ROI. ROI is something that most marketers look at when one has to determine the effectiveness of any marketing channel. The study therefore examined ROI for weblogs and how their promotions through two highly popular social networking sites, namely Facebook and Twitter affects their

75 popularity and in turn increases their revenue through advertisements. Page views is a direct measure of the traffic a particular blog has and therefore a correlation between page views and Facebook fans and twitter fans was established to understand the effect of promotion of brands through social media. The findings of the study revealed a positive correlation across all blog categories and hence it was concluded that a positive change in Facebook followers and Twitter followers increases the number of page views. It was also found that the page views increased with the increase in time due to an increase in fans or followers.

8. Shahir Bhatt and Amola Bhatt (2012) in their research paper Factors influencing Online Shopping : An Empirical Study in Ahmedabad writes about the factors which influence the perceptions of consumers regarding online shopping.

The study has revealed ease/attractiveness of website, service quality of websites and website security as the three important factors which have prominently emerged from the study. The paper has proved that that these factors are related to specific type of consumers classified as occasional, frequent and regular consumers. The study shows that the regular buyers are most influenced by the ease/attractiveness and service quality of website, whereas the occasional buyers value website security to a greater extent.

9. Sheetal Thapar and Navneet Sharma (2013) in their study on role of social networking sites in some key cases throws a light on the growing popularity of social networking sites. The study showed that people have got their own media to raise their voice and stand for their rights. Author thinks that Social Media possess the character of true democratization of information. Study concludes that the participatory nature of Social Networking Sites cuts through caste and class barriers.

10. Ambrose Jagongo, Catherine Kinyua (2013) in their study The Social Media and Entrepreneurship Growth focused on the effect of social media on the growth of SMEs in Nairobi. The study established that social media tools offer greater market accessibility and CRM which in turn have a significant impact on the growth of SMEs. This study recommends that the policy makers should come up with favourable internet surfing rates and e-business policies to encourage the technological adoption that would grow the SME industry.

11. Venkatesh, R(2013), examines the possibilities of different sections of society following different trends of communication. This study talks about the usage of product promotion on social media, by the multinational companies in India especially in the FMCG sector.

12. The potential of Social networking sites in the field of education have been explored by Afendi Hamat, Mohamed Amin Embi, Haslinda Abu Hassan (2012) in the research paper “ The Use of Social Networking Sites among Malaysian university students”. The young adults most often use social media to interact and socialise with their peers. This study is conducted nationwide in Malaysia, where

SNSs are popular and very commonly used for interaction by the young adults, however there is very limited data available on the patterns of its use for the wider segment of the target population. The results show that the SNS has not penetrated completely i.e. 100% in Malaysia as was assumed earlier. The study also shows that the respondents are found to spend more time on interacting and socializing through

SNS than learning and they do not think that the use of SNS affects their academic performance. It has come out from the studies that the respondents are using SNS for the purpose of informal learning activities and nearly half i.e. 50.3% use it to get in touch with the lecturers for informal learning purpose.

13. Tool for collecting brand visibility information of brands present over social media have been identified by the authors Botha, E., Farshid, M., Pitt, L. (2011) in their research paper “How Sociable? An exploratory study of university brand visibility in social media”. Brands are using Social Media to acquire new customers and to retain the existing ones. Brands need to acquire information about their visibility on these social networking sites, as compared to the visibility of their competitors. This is an exploratory study that has been conducted on the South

African University brands. This study has identified, positioning of the brands over social media and the strategies followed by them to make themselves visible to the audience, as the tools for knowing the visibility of the brands. The findings of the study revealed that the South African University brands do not have a distinct position over social media, nor do they have effective strategies to engage their stakeholders.

The writers concluded that the institutions should have a fair attitude towards Social media, since social media is currently governing the internet and the media. The people who are managing these brands can see this as an opportunity to make the brand presence prominent.

14. Sunil Karve, Shilpa C. Shinde (March 2013) in their paper “Effectiveness of Social

Networking Sites (SNS)” have made an attempt to figure out the experiences of the internet users regarding social media and have also tried to find out the pattern of

SNS usage of the consumers. The writers state that social media has become so much popular, that it has surpassed the popularity of email, to become number four after search, portals and PC software applications. The tremendous increase in the amount of time people are spending using these SNS have changed the way people spend their time online and this affects the way people behave, interact and share in

78 their normal daily lives. This paper has tried to analyse the overall effectiveness of

SNS.

15. An effort has been made to know the awareness of social media with respect to business among teaching, non-teaching staff and students of a college by T. S.

Venkateswaran, B. Sowmya, R. Arun (July-Aug. 2012) in their research study

“Effective use of Social Websites towards business among academicians and students in Namakkal District”. The research intends to investigate the following :1.

Knowledge of business through social websites.2. Uses, impact and causes of social websites.3. Rating the various activities in Social websites.4. Impact of Social websites in future. The study lists the benefits of social websites for business: 1. To create brand awareness. 2. Utility of SNSs as a effective online reputation management tool. 3. For the purpose of recruiting. 4. To learn about new technologies and competitors. 5. As a lead generation tool to intercept potential prospects. The results of the study reveals that most of professionals and students are aware about business taking place through social networking sites, however most of them are not using it for the business purpose. Most of the respondents are using SNSs for socializing. Therefore the writers think that the social websites need to grab the professionals and students from rural areas to concentrate on business through Social websites.

16. The importance of Social media platform as a crucial tool for strategic marketing has been discussed by Efthymios Constantinides, Carlota Lorenzo Romero and

Miguel A. Gomez Boria (2009) in their research study “Social Media : A New

Frontier for Retailers?” This study has proposed a number new strategies for

79 retailers implementing which will not only help the retailers to survive, but create a competitive advantage and flourish in the new environment.

17. The rising significance of Virtual social worlds and how business can use their potentials has been discussed by Andreas Kaplan and Michael Heinlein (Nov.-Dec.

2009) in their research work “The fairyland of Second Life : Virtual social worlds and how to use them”. At the beginning this study the authors have discussed about the evolution of virtual social worlds and its history. Followed by how it fits in our time and lastly how they are different from other social media, such as content communities (e.g. YouTube), social networking sites and blogs (e.g. Facebook), collaborative projects (e.g. Wikipedia) and virtual game worlds. This study has thrown light on how businesses can make use of these virtual social worlds in the field of advertising and communication, virtual product sales (v-Commerce), human resource, marketing research and internal process management. Along with it this study has also discussed increasing linkages between the real and the virtual worlds, enforcement of law and order and transformation of virtual social business as business hubs or centres of the future.

18. Age differences have been considered in the perceptions of social communities held by people who were not participating in these comparatively new social spaces have been examined by Jae Eun Chung, Namkee Park,Hua Wang, Janet Fulk,

Margaret McLaughlin in their study “Age differences in perceptions of online community participation among non-users :An extension of the Technology

Acceptance Model”. With the help of Technology Acceptance Model (TAM) An effort has been made to investigate the factors that have an effect on future intention

80 of non users, to take part in online communities. The results of the study showed that perceived usefulness factor has a positive relationship with the behavioural intension.

The ease of use factor did not play a significant role in predicting the perceived usefulness. The study also found out that there exists a negative relationship between the factors age and internet efficiency; age and perceived quality of online community websites. The writers concluded by stating that age does not change the relationships between perceived usefulness, ease of use and intention to participate in online communities.

19. The effect of the News feed privacy outcry on user behaviour changes has been examined by Christopher M. Hoadley, Heng Xu, Joey J. Lee, Mary Beth Rosson in their research “Privacy as information access and illusory control : The case of the Facebook News feed privacy outcry”. A survey was conducted on 172 current

Facebook users in one of the large universities of US in order to determine the reasons and the extent to which the users were upset and to investigate the influence of the

News feed privacy outcry on the user behaviour changes. The results showed that an easy access to information and an unreal loss of control which was alerted by the introduction of News feed features stimulates, privacy and security concerns among users.

20. The impact of cultural orientation of American, Chinese and Turkish non-profit organization’s behaviour and communication patterns in the social media space has been examined by Richard D. Waters & Kevin D. Lo (2012) in their research study

“Exploring the impact of Culture in Social Media Sphere : A content analysis of non-profit organization’s use of facebook”. A content analysis of 225 non-profit organization’s Facebook profiles was carried out for the research purpose. Particularly

81 the study has focused on the ways in which the organizations disclose information about themselves and about those who manage their Facebook presence, ways of promoting the organizational accomplishments and news, and engaging with the stakeholders in relation to their context, performance and collectivist/individualist natures, respectively. The findings of the study showed mixed support for the impact of traditional cultural expectations, thus suggesting that global connectivity of social media may be contributing to blurred cultural boundaries in favor of virtual culture that promoted the global community.

21. The usage of social media among the destination marketing organizations (DMO) of the top 10 most visited countries by international tourists has been examined by

Stephanie Hays, Stephen John Page & Dimitrios Buhalis (2012) in their research study “ Social Media as a destination marketing tool: its use by national tourism organisations”. Social media are gaining more importance in the marketing strategies of DMOs as it helps in seeking greater value in the way marketing budgets are spent.

Social media offers DMOs with global audience at limited costs. The writer has made an attempt to determine the impact and usage of social media marketing strategies and has developed a model of best practices for the national tourism organizations to learn from. The findings show that the social media usage among the top DMOs is still experimental and the strategies differs extensively.

22. The usage of social media and customer centric management systems and its contribution to firm-level capability of social customer relationship management

(CRM) has been investigated by Kevin J. Trainor, James (Mick) Andzulis, Adam

Rapp, Raj Agnihotri (June 2014) in their research work “Social media technology usage and customer relationship performance : A capabilities-based examination

82 of social CRM”. This paper has made an attempt to conceptualize and measure the capabilities of social CRM. The second important contribution of this paper is exploring how social CRM capabilities are influenced by customer centric management systems and social media technologies. The results suggests that social media technologies and customer centric management systems had a positive relation with the customer relationship performance.

23. The social media presence and social media metrics of Indian IT companies namely Infosys, Wipro, TCS and HCL has been discussed by Ramulu Bhukya (2012) in the research paper “ Presence of Indian Big IT Brands on Social Media : an

Empirical Study”. The data for this study has been collected from the respective brand’s social media websites and analyzed on a 5 point scale. The research findings shows that HCL and Infosys have high scores of 3.75 points for their social media presence and have their brand accounts on 7 social network sites each. Next with score of 1.75 and presence on 7 SNS is Wipro followed by TCS with score of 1.25 and social media presence on 6 SNS. de Vries et.al. (2012) conducted a study on 355 brand posts from 11 international brands spread across six categories of products and the result shows that positioning the brand post on top of the brand fan page helps in increasing and enhancing the popularity of the brand post. The author opines that the

SNS are free to join because if they are not free they will not expand and earn money from the brand or customer driven advertisements. According to the Social Media

Benchmark survey conducted by http://business.com, 2948 businesses were undergoing the process of decentralization of marketing plan. Among them 1,197 maintained a company profile on one or more SNSs, 80% maintained a presence on

Facebook while 56% maintained an account on Twitter. Social media has opened the doors of global markets and Infosys, Wipro, HCL and TCS are now preparing to

83 compete with the global biggies. Already Indian companies have labour availability at a comparatively much lower costs as compared to the global companies which is one advantage that the Indian companies have in their favour. However value created in the fields of brand, intellectual property will take these Indian companies to new heights. Accordingly these tech companies are working aggressively over budgets for marketing globally, enhancing global positioning and brand valuations.

24. Whether integrated marketing communication is a new horizon or a beginning of another failed marketing communications in marketplace experiencing economic turmoil, has been examined by Philip J. Kitchen & Don E. Schultz (2009) in their research work “IMC: New horizon/false dawn for a marketplace in turmoil”.

The writers argue for a totally new opinion for IMC going forward to match the economic realities faced by the organizations. IMC will be driven by marketplace, customer, technological changes enhanced by globalization and a shift of marketplace power to consumers, all heavily influenced by the current economic conditions.

25. Wright, Elizabeth; Khanfar, Nile M (Nov. 2010) in “The lasting effects of

Social Media Trends on Advertising” has explored that there is no use investing millions in traditional methods of advertising because people find new ways to block or get away from these advertisements. The key is to target the right people with the right messages. In order to do this, the marketers should focus on Connectors(are the ones that move and steer people into directions and avenues of interest to them) ,

Mavens(are the ones who want to know the best deals and tell everyone about it) and salespeople(who have the ability to convince and sell new ideas). The connectors, mavens and salespeople have the ability to give a high return on investment, since by targeting them the organization can acquire high sales just by targeting a small group

84 of people. Thus targeting the right people not only brings down the organization’s advertising expenses but also drastically improves their marketing productivity. Social

Media makes it very easy for any organization to connect with these connectors, mavens and salespeople. It is very important to use holistic, comprehensive relationship marketing strategy to target these people, since they are key drivers in influencing the consumers buying decision. The idea of relationship marketing is to

“build mutually satisfying long-term relationships with the key constituents in order to earn and retain their business”(Keller & Kotier,2009,p.20). To build and sustain such a relationship, marketers must understand and respond to customer needs and goals. Marketers are using tailored social networking forums to reach the consumers in a more personalised way. Marketers are finding that interactive and targeted marketing are the key to success and are far more beneficial than the traditional advertising.

26. Integrated Marketing Communications (IMC) must be used in social marketing is proposed by Jacinta Hawkins, Sandy Bulmer and Lynne Eagle (2011) in their research work “Evidence of IMC in social marketing”. This research study has given evidence of IMC being successfully incorporated in the commuication of school-based health promotion activities within schools that promotes health. The findings of the research reveals that IMC principles are successfully communicted and forms part of the HPS(health promoting school) policy of promoting health. This research throws light on how IMC can and should be used in social marketing. This research has provided insights for social marketing practitioners to improvise on the communication efforts.

27. Tan, Wei Jia; Kwek, Choon Ling; Li, Zhongwei (March 2013) in paper “The

Antecedents of Effectiveness Interactive Advertising in the Social Media”, have

85 tried to find out consumer’s attitude towards interactive advertising and its impact on purchase intention. Through their study the writers have made an attempt to share some understandings and opinions with advertisers and companies on the measurement of effectiveness, which they can consider when placing an interactive advertising. In the literature review the writers states the following factors as the determinants of the effectiveness of interactive advertising: Attitude towards

Advertising, Attitude towards Advertised Brand, Purchase Intention, Time of exposure to advertisement(Yang, 1996). The results of the study reveals that, there is a positive relation between attitude towards advertisement and purchase intention to effectiveness of interactive advertising. Thus the writers concluded saying traditional advertising could be used, but interactive advertising measures should be an add on.

28. Thirushen Naidoo (November 2011) in his research paper “The effectiveness of advertising through the social media in Gauteng” has made an attempt to investigate the effectiveness of advertising through the medium of social media and has focused mainly on Facebook. The author states that social media marketing explores and utilizes the social aspect of the web and is therefore able to connect and interact on a much more personalised manner than the traditional marketing. The study reveals brand engagement, brand attitude, brand image and consumer engagement as the factors contributing to the effectiveness of advertising. The paper also talks about brands having strong market presence automatically getting more attention from consumers on Social media. The author concludes that inorder to be effective, a brand needs to be established and must have strong brand reputation. The advertisements on Facebook serve to supplement the brand and does not put the brand up the rank in terms of its reputation.

29. A study has been conducted on social networking sites like Facebook, Twitter and

Orkut by authors P. Sri Jothi, M. Neelamalar and R. Shakthi Prasad (March

2011) in their research paper “Analysis of social networking strategy in developing brand communication”, with the primary objective of determining the effectiveness of brand communication strategy in advertising products and promoting brands on social networking sites. The various reasons for social media being a widely used platform, for advertising compared to the other traditional advertising mediums have been discussed. The various ways that are being provided by social media platform for its users to communicate with each other and interact with the brand are discussed like chat, messaging, video, email, voice chat, file-sharing, blogging and discussion groups. According to the writers views, the marketing communications are becoming personal, interesting, interactive and social. Findings of the study suggest that social media advertising has its impact on 70% of the users and half of them access these ads i.e. games, quiz, events etc. It was found that the interaction is more in the display banner advertisements in Face book and Orkut. Every Social networking site has a unique communication strategy and user interaction. Face book promote and allows user interactions, Twitter feeds posts relating the brand and Orkut promote through click ads and promotional brand pages. Face shows accessibility because of its huge popularity and Twitter gives more importance to the text. The writers concluded by stating that Social networking sites have the scope to grow big for highly targeted marketing and advertising. Social networking sites presents enormous opportunities to build the brands and have become a branding hub.

30. The characteristics of online marketing strategies used by E-entrepreneurs have been explored by S. Vivin. Richard, Ms. Sri. Jothi (Aug. 2012) in the research study “ A study on online marketing strategies used by E-Entrepreneurs in

India”. The study has analysed E-Entrepreneurs like www. Amazon.com, www.

Flipkart.com, www. Naptool.com etc. for the purpose of studying the nature and extent of marketing strategies used by successful online Entrepreneurs. SNSs apart from being a fantastic medium of communication and interaction, keeps the customers informed of the consumer market as well. Through this paper the writers have voiced their view that there is a need to analyze and research the needs of the customers who come online to fulfil their requirements. Internet has given an opportunity to entrepreneurs to market their products and services across the globe and has opened the doors of such a gigantic market, that their sales force cannot even think of identifying. The online companies can engage in online promotional activities through effective online marketing strategies to enhance their offerings in the online markets.

Advertising on the internet not only provides the information about the offerings but it also encourages innovation. The study concluded by revealing the results which stated that Social media marketing is one of the best online marketing strategies that has been used by the E-Entrepreneurs. The results also revealed that the International players like e.Bay.com, Amazon.com are well ahead in customer relationship building and management and in the online marketing strategies. Indian brands are identifying the strategies which the international websites use to improve the website and are trying to build their brand identity.

31. The Mass media advertising is coming to an end and its chances of recovery are grim, this has been talked about by Ronald T. Rust and Richard W. Oliver (June

2013) in their research “The Death of Advertisng”. In this paper the authors have expressed their opinion about the traditional advertising business being directly hit by direct marketing. The reasons for the diminishing business of traditional advertising has been attributed to the arrival of new technologies that have empowered the

88 consumers. A new market has evolved which is more in capacity, interactive and multimedia in place of the traditional mass media. This new media advertising results in more producer-consumer interactions.

32. Work on building systems that would help in recognizing the spam blogs, finding opinion on topics, identifying communities of interest, deriving trust relationships and detecting influential bloggers with the help of models of blogosphere have been elaborately explained by Tim Finin, Anupam Joshi, Pranam Kolari, Akshay Java,

Anubhav Kale, and Amit Karandikar (2008) in their study “The information ecology of social media and online communities”. Social media systems such as photo- and link-sharing sites like YouTube etc., weblogs, online forums are estimated to generate one third of the new web contents. One prominent feature that distinguishes the “web 2.0” sites from the other web pages is that they are interlinked with other forms of network data. Their standard hyperlinks are enriched by social networks, comments, trackbacks, advertisement, tags, resource description framework

(RDF) data and metadata. The writers conclude by stating that as the internet evolves, it changes the way in which the people interact with it as content providers or content consumers and the results will be more interesting mixture of underlying networks - network of individuals, groups, opinions, beliefs, documents, advertisements and scams. These interwoven networks will pose new opportunities and challenges for extracting information and knowledge from them.

33. Many online social networks fail to generate sustainable revenues from advertising, even though the usage activity is high. The means of harnessing effective advertising strategies in online social networks has been discussed by Florian Probst

(2011) in his research work “ Predicting User’s future level of communication

89 activity in online social networks : A first step towards more advertising effectiveness”. To enable effectiveness of advertising strategies, identifying a user who can influence a large number of friends or acquaintances is essential. In this regards, the user’s future level of online communication activity in online social network plays an important role. High online activity in the past does not guarantee high level of the future online activity. The means of predicting user’s future level of communication activity are required. Therefore the writers have proposed a probability based model that has been developed to primarily forecast the purchasing behaviour of the consumers resulting from the user’s communication activity on online social networks.

34. Applying Anthropological theories into the social marketing practices has been advocated by the authors Guang Tian, Luis Borges (2012) in their study “The effectiveness of social marketing mix strategy : Towards an Anthropological

Approach”. The author has described social marketing as a new science that seeks to improve the overall life quality of human beings by adopting marketing strategies and skills without aiming for making profits. Although the basic concepts of social marketing and commercial marketing are similar, however their principles differ in various fields. The author feels that the social marketers should become aware of the anthropological aspect of social marketing and about the differences between the social and commercial marketing theories. Social marketers should be able to apply anthropological theories and methods into social marketing practice.

35. Discussing the impact of social media on marketing has been the main goal of this study “Impact of Social Media on Marketing” by Rajiv Kaushik (March 2012).

Different media of marketing before social media revolution have been discussed,

90 followed by the evolution of Social media. The impact of social media on marketing is discussed in detail with the help of standard metrics like online advertising, public relations and search engine optimization. The paper has also discussed the concerns and criticism of social media. Some of the important concerns were if the customers post comments or tweets in haste it can cause severe damage to the brand image. If the consumers find the brand’s social networking activity intrusive then there is a high risk of losing the consumer. Since marketers are directly dealing with the public, they cannot lurk behind the scene, but have to become more accountable for the brand. The growing popularity of social media can lead to social media overtaking to other functional areas of marketing. Social media is building a bridge between the marketers and the consumers through continuous engagement, building trust and targeting the right audience at the right time and in real-time.

36. Simona Vinerean, Iuliana Cetina, Luigi Dumitrescu & Mihai Tichindelean

(June,2013) in their exploratory research work The Effects of Social Media

Marketing on Online Consumer Behaviour, have tried to determine the students pattern of using social media and social networking sites in relation to their reactions to the advertisements on social media, where they have the freedom to choose the information they engage with. The aim of this research paper is to empirically investigate what type of social media users, have a positive outlook regarding advertising on social networking sites. This study has contributed to the existing knowledge, of consumer behaviour in an online environment and on developing positive reactions to online advertisements and have also presented new ways to classify the online consumers, which served as a basis for psychographic segmentation, based on respondents online activities. The authors concluded stating that in order to be successful in the social media environment, companies must

91 undergo continuous online marketing research and should be sensitive to the changes in consumer behaviour patterns and should be able to identify new areas of customer interest.

37. Logan, Kelty; Bright, Laura F; Gangadharbatla, Harsha (2012) in paper

Facebook versus television : advertising value perceptions among females the writers compared the perceptions of female students regarding value of advertising on social network sites and value of advertising on television. Advertising trustworthiness-The study shows that consumers have become more concerned about the factualness or trustworthiness of advertising content. It was found out that consumer-generated product recommendations are more recommended than marketer- generated product recommendations. Involvement-SNSs provide an involving environment for advertisers. The users of Social networking sites involve in brand related activities and are therefore more engaged than consumers who simply read, listen or watch advertisements about a brand. Advertising effectiveness measures-It was found out that the advertisements having an element of entertainment and information in them are more accepted advertisements on SNSs. The results indicated that the young adults crowd(19-24) are more inclined towards informativeness than entertainment and young female participants are more engaged by entertaining advertisements on SNSs. Therefore it was concluded that informativeness and entertainment play a significant role in assessing advertising value whereas irritation did not play a significant role in assessing the advertising value.

38. Garima Gupta (January-June 2013) in the research paper Assessing the

Influence of Social Media on Consumer’s Purchase Intentions has made an attempt to determine the impact of social media on product evaluation and the resulting decision-making process of Indian consumers. The results are supportive of

92 the fact that social media does affect purchase intentions. More Specifically, there is a positive and strong impact of three factors namely peer communication, perceived product informativeness and the level of product involvement on consumers purchase intentions in the context of social media. The author concludes that as the products offered online cannot be examined, perceived information on social media and its spread through communication among peer groups facilitates consumer’s evaluation and purchase related decision.

39. Boris Bartikowski, Gianfranco Walsh in their research paper Attitude contagion in consumer opinion platforms: posters and lurkers have tried to explain how consumer’s perception about product reviews affect the product and brand attitudes and in turn affect the consumer’s buying decision. This study also reveals how the consumer product reviews affect the brand-related attitudes of posters than lurkers.

40. O’Brien, Clodagh (2011) in their research paper “The emergence of the social media empowered consumer” has thrown a light upon the various platforms that has an impact on traditional relationship marketing concepts and how this has resulted in raising consumer expectations of the conventional business. This study also talks about areas like word of mouth and consumer empowerment and emphasises the areas of potential development in theory and practice as a result of social media empowerment. The author in this study has expressed his views about social media and CRM. He says that Social media has completely changed the manner in which communication takes place thereby giving a new dynamics to the human relationships. The organizations which are accepting social media must also accept that they are losing the element of control to the consumers. For most of the businesses social media has gained a lot of importance in establishing their web

93 presence overtaking the company website and email communication programme. This has completely changed the manner in which the organizations are interacting with their consumers and how they are implementing the customer relationship management strategies. The main difference between the traditional CRM and social

CRM is that the social CRM is more customer oriented and it involves customers proactively. The author also talks about word of mouth marketing that empowers the organization and not the consumer.

41. falseDiffley, Sarah; Kearns, James, Bennett, William; Kawalek, Peter (2011) in their research paper Consumer Behaviour in Social Networking Sites:

Implications for Marketers have made an attempt to investigate whether social networking sites (SNSs) can be used as an effective tool of marketing and whether it can engage the consumers to participate in marketing on SNSs. The authors write that companies need to undertake a different approach that will attract consumers rather than pushing marketing messages on them. If marketing messages are pushed onto the consumers it will result in adverse reaction and the consumers will express their dissatisfaction when they are communicating over SNS. This will have a negative effect on the company and put an end to the potential of SNS to be used as a marketing tool. This paper talks about developing the correct approach in using SNSs as a marketing tool. In this paper the authors have drawn a conclusion that companies need to work towards having a ‘friendship’ based approach with the consumers and need to build relationships with them in order to have the SNSs act as a Marketing tool for the companies.

42. The factors which affect shopping attitude on social networking sites are identified by Jugal Kishor and Prof. V. K. Singh (August 2014) in their study “An

94 empirical study on shopping tendency through social networking sites (SNSs)”.

Different methods of payment used for shopping through SNSs are focused in this study. This research study has revealed that social networking sites have different targest consumers and factors; and have correlated these factors. The nature of the study is exploratory since it focuses on new idea of virtual shopping through SNSs.

The writers opine that patrons who vary in age all through the 30s are captivating the targets for sellers of goods and accommodations. The writer further states that due to the unique characteristics of gregarious networks the items that are sold on the gregarious networking sites can vary from the items that are being sold on other virtual sites. The internet sites largely sell authentic items i.e. the items (goods or accommodation) that can be used offline, irrespective of whether they are bought online or offline, such as books, flight tickets, furniture, apparel etc. The gregarious networks not only sell authentic items but they additionally sell virtual items i.e. the items (good or accommodations) whose use and purchase are constrained by exacting webspace, such as homepage outline, avatars, implicit gifts, music that can be utilised only on concrete websites etc. The findings of the study shows that time spent on social destinations is a differentiating element that influence the disposition to looking for things on a long range interpersonal communication. The apparent fit is the strongest factor that influence the shopping intensions on social destinations. The study found out that the individuals who regularly use long range informal communication locales usually accept more extra offers. Therefore the informal community clients hesitate to shop on interpersonal communication locales. It has been discovered through this study that different age groups have association with the

SNS shopping variable. From the managerial viewpoint the study reveals that the target consumers and the features of SNSs should differ according to the product type

95 if SNSs look forward to expand their businesses to include the shopping services.

That is younger people with positive perceptions of usefulness, ease of use and security of shopping services on SNSs.

43. An attempt is being made to examine how social relationship factors relate with eWOM being transmitted via social networking sites by Shu-Chuan Chu, Yoojung

Kim(2011) in their study “Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites”. As more and more marketers incorporates Social media in their promotional activities, there is a need to investigate the determinants that impact the consumers engagement in eWOM via social networks. eWOM is based on three aspects : opinion seeking behaviour, opinion giving behaviour and opinion passing behaviour. Opnion seekers depend on others advice to make purchase decision. Opinion givers exert a great influence on others opinions. Opinion passers helps in the flow of information. Literature review has revealed four social relationship variables - tie strength, homophily, trust and interpersonal influence. Interpersonal influence is further divided into normative influence and informational influence. The results indicate that tie strength, trust, normative and informational influence had a positive relationship with all types of eWOM behaviours. However homophily had a negative relationship with the eWOM behaviour.

44. The theory of ‘factors affecting the shopping attitude on social networking site differ with change in the type of product’ has been explored by Jiyoung Cha (2009) in their research work “Shopping on Social networking websites ; Attitudes toward real versus virtual items”. The study is based on two types of products which are present on social networking sites: Real products and Virtual products. The

96 study reveals that usefulness, age, ease of use, security and fit play a significant role in determining the attitude for shopping real products. On the other hand gender, social networking site experience, ease of use and fit influence the attitudes for shopping virtual products.

45. The factors affecting consumer’s attitudes towards marketing through the medium of social media have been discussed by Erkan Akar & Birol Topcu (March 2011) in their study “An examination of the factors influencing consumer’s attitudes towards social media marketing”. Consumer communities on social media are new marketplaces for marketers. The goal of this research is to identify the factors that affect the consumer’s attitude towards marketing on a social media platform.

46. The brand communities based on social networking sites influence the elements of customer centric model and brand loyalty has been talked about by Michel Laroche,

Mohammad Reza Habibi, Marie-Odile Richard (Feb. 2013) in their research work

“To be or not to be in social media : How brand loyalty is affected by social media?”. The study has aimed to show how brand communities based on social media influence the elements of customer centric model (i.e. the relationships between focal customer and brand, product, company and other customers) and brand loyalty. An empirical study was conducted on 441 respondents through survey method. The results of the study revealed that brand communities present on social media have a positive effect on customer-product, customer-brand, customer- company and customer-other customer relationships, these in turn have positive effect on brand trust and trust has positive effect on brand loyalty. The study found that brand trust plays an intermediary role in converting the effects of relationships in brand community to brand loyalty.

47. Examining the young social media user’s responses towards social media advertising has been focused by Shu-Chuan Chu, Sara Kamal & Yoojung Kim

(May 2013) in their research work “ Understanding consumer’s responses toward social media advertising and purchase intention towards luxury products. The popularity of Social media as an advertising platform is increasing with the users interacting with each other and with the brand. In the same time period the online luxury market experienced enormous growth due to rising number of users in the age group of 18-35 and belonging to affluent background. This research focused on determining young social media user’s belief, attitudes and behavioral response towards social media advertising. Brand consciousness and awareness was found to have its effect on user’s attitudes towards social media advertising, which eventually affects their behavioral response towards social media advertising and ultimately affects purchase intention of luxury products.

48. Smith, Nicola (Nov 2009) in their research paper “Consumer electronics vertical Focus : The heights of invention” has stated that consumer electronics sector has been the first sector in experimenting and trying out the different techniques of digital marketing. The various product promotional campaigns taken up on the Social Media by the digital pioneers like Sony, Toshiba, Samsung, Panasonic and the overwhelming responses they received online form a part of this paper. It has been put forth by the writers that the key challenge faced by the consumer electronics brands has been to effectively communicate the complexity of their products to a wide audience and through digital marketing they have overcome this challenge and therefore they are turning to digital marketing. Online video and Social Media (Social media includes Consumer reviews, online communities and forums) have been cited as the greatest opportunities by the consumer electronics brands. The brands can

98 directly open a dialogue with the consumer, understand the consumer’s needs, answer their questions, get feedback and have a friendly engagement with the consumer; all because of Social Media.

49. A detailed understanding of the relationship between social media and viral

marketing has been provided by Andreas M. Kaplan and Michael Haenlein

(May-June 2011) in their research work “Two hearts in three quarter time : How

to waltz the social media/viral marketing dance”. Viral marketing has been

defined as the electronic word of mouth in which some marketing messages relating

to the product, or brand is transmitted in an exponentially growing way through

social media applications. This study has considered three conditions which need to

be fulfilled to create an epidemic of viral marketing. These three conditions are

giving the right message to the right messengers in the right environment. For any

business there are two main reasons of using the social media platform - 1.

Marketing. 2. Customer service.

50. The future possibility and the prospects of connecting consumer electronics to

the web through open API’s has been endeavoured by the writers Mariana Baca

and Henry Holtzman (2008) in their research work “Television meets Facebook :

Social Networks through Consumer Electronics”. The project consist of an IP

enabled digital video recorder in the form of advance cable television set-top box

connected to Facebook social network. The objective of this project are : a. How can

the omnipresent consumer electronics work together in a simple way, b. How can

the data available on social networking application diffuse in useful ways into the

participant’s real lives and c. How can these systems accomplish these tasks

seamlessly without adding time or complexity to the user’s experience. The results

of this project are the user can now watch on his TV, the media that his friends

enjoy, as well as his own explicitly requested recordings, through the system of

ratings the user can use her DVR’s enhanced interface to post back on social

network what shows have been liked by them. The user’s profile box in Facebook is

going to be the main tool for sharing the user’s upcoming viewing schedule. The

information on their profile affects their viewing habits, therefore users will be more

conscious with whom they add in their friend network and what information they

provide through their profiles. The integration of consumer electronics and social

networking is expected to benefit the content producers and distributors through the

automation of word-of-mouth (WOM) recommendation. This project is also

expected to help the users in finding the appealing new content faster than they

would otherwise, help users in sharing contents and experiences more easily and

will help the content distributors track content distribution in a social network

directly into consumer electronics.

2.1 Literature Gap

From the literature review specific to Social Media it was found out that there is no study in Maharashtra which talks about the role of social media in shaping the consumer’s perception and thus influencing their buying behaviour.

Also, even though many people use Social media for buying consumer electronics however no major study has been conducted on role of social media with respect to consumer electronics segment in Maharashtra as well as Gujarat.

There has been no study conducted so far on Social Media with special reference to young working women of Maharashtra and Gujarat.

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Chapter 3

Objectives, Hypothesis and Research Methodology

3.1 Statement of the Problem :

Social Media is a Buzz word today. It is extremely popular not only among the youth but people belonging to higher age groups also seem to be catching up with this new technological advancement to a great extent. Businesses are extensively making use of Social media in framing their marketing strategies. The main goal of this study has been to study the impact of social media and how it influences consumer’s perception in turn to affect their buying behaviour. This study would be able to bring out whether advertising on social media does influence the consumer’s buying behaviour so that companies can decide whether to continue with traditional marketing practices or whether to incorporate social media in their marketing strategies.

It has been revealed from the literature review that there has been no study conducted so far on Social Media front of cities in both states, Maharashtra and Gujarat in the consumer electronics segment. Therefore this study was conducted with the aim of comparing the results and findings of the research in the two states.

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3.2 Objectives of Study:

Based on the Literature Review and the gap identified from the Literature Review the objectives of the study were framed, which are as follows:

1. To identify the Social Media Usage by young working women in different cities.

2. To study the customers buying behaviour with respect to Social media advertising.

3. To study the impact of social media advertising on the buying behavior of young

working women for consumer electronics.

4. To study the effectiveness of Social Media tools like face book, twitter, LinkedIn

on the consumer behaviour.

5. To study the impact of social media advertising on working women belonging to

different demographic factors such as qualification, annual income, occupation and place.

3.3 Hypothesis :

From the Objectives of the study the following Hypothesis were formed:

H01: There is no specific reason of consumer’s social media usage.

H11: There is a specific reason of consumer’s social media usage.

H02: There is no significant difference in buying behaviour of customer with respect to social media advertising.

H12: There is a significant difference in buying behaviour of customer with respect to social media advertising.

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H03 : There is no significant impact of social media advertising on young working women’s buying behaviour.

H13 : There is a significant impact of social media advertising on young working women’s buying behaviour.

H04 : There is no significant difference in effectiveness of different social media tools on consumer behaviour.

H14: There is a significant difference in effectiveness of different social media tools on consumer behaviour.

H05: There is no association between effect of social media advertising and education of respondent.

H15: There is an association between effect of social media advertising and education of respondent.

H06: There is no association between effect of social media advertising and income of respondent.

H16: There is an association between effect of social media advertising and income of respondent.

H07: There is no association between effect of social media advertising and occupation of respondent.

H17: There is an association between effect of social media advertising and occupation of respondent.

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3.4. Research Methodology

This chapter has been an over view of the research method used for this study and has include data collection, sample selection, type and contents of questionnaire, processing of data and finally interpretation of the data. Quantitative and Qualitative research approaches have been embraced for the purpose of research by this study.

3.4.1. Type of Study

The study has been conducted in two phases. Initially in Phase-I, Exploratory research has been conducted. For the same purpose formal interactions were conducted with those young working women who use online sites for buying consumer electronics products. After the interactions, the variables of the study had been identified and accordingly the questionnaire was prepared. In Phase-II, a Descriptive study had been conducted. The secondary data had been collected from various available resources.

Review of Literature from various published reports, research journals, reference books and online databases like Proquest, www.Googlescholar.com,www.Alexa.com, www.statista.com, www. Statisticbrain.com, www.econsultancy.com etc.

3.4.2 Data Collection

Primary data had been collected by questionnaire survey method. Research instrument that had been used for this research were questionnaire and personal interviews. A single questionnaire had been created and administered in three cities by the researcher. The target audience for this study were working women in the age group of 18-35 from Mumbai, Nashik and Surat.

The cities in India have been classified on the basis of grading structure devised by the government of India. According to this gradation, Mumbai belongs to Tier I

104 category of cities and Nashik and Surat belongs to Tier II category (source for information on Tier I & II cities of India: www.maps ofindia.com). The requirement of the study was comparison between the tier one and tier two cities having different population sizes. Therefore based on convenience, Mumbai was selected as a Tier I city or a Metro city with heterogeneous population of 12.7 million and Nashik as a tier II city having population approximately 1.5 million from Maharashtra and Surat having population 4.5 million was selected from Gujarat (source :Reports of Internet

And Mobile Association of India [IAMAI] and Internet Market Research Bureau

[IMRB] ).

3.4.3. Pilot Study

Pilot study was conducted and the questionnaire was first pre-tested on a sample of

100 respondents (working women in the age group of 18-35) from Mumbai city for checking the reliability of the questionnaire.

3.4.4. Reliability

The Chronbach’s Alpha found out was 0.860. Any value of Cronbach’s Alpha above

0.6 shows that the scale is reliable.

3.4.5. Questionnaire

The questionnaire comprised of questions pertaining to various sections mentioned below and each section had several questions related to the section to which it belongs to.

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Table 3.1 Showing details of Questionnaire

Section Name Questions Total

Number number of

questions

Sec. 1 Demographic information Education, Annual 4

Income, Occupation and

Place

Sec.2 Usage of Social Media. 1,2,3,4,5,6,7,8,9,10,11,12, 14

13,14.

Sec. 3 Consumer Buying Behaviour. 1,2,3,4 4

Sec. 4 Online Purchase Behaviour. 1,2,3,4 4

Sec. 5 Complex Buying Behaviour. 1,2,3,4,5,6 6

Sec. 6 Habitual Buying Behaviour. 1,2 2

Sec. 7 Variety Seeking Buying 1,2,3 3

Behaviour.

Sec. 8 Dissonance Buying 1,2,3 3

Behaviour.

Sec. 9 Impulsive Buying Behavior. 1,2,3 3

Sec. 10 Effectiveness of Social 1(A,B,C,D,E),2,3,4 8

Media.

Sec. 11 Impact of Social Media 1(A,B,C,D,E),2,3 7

Advertising.

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3.4.6. Size and Design of Sample

The study was conducted in two cities of Maharashtra (Mumbai & Nashik) and in one city of Gujarat (Surat). The sample unit is working women in the age group of 18-35 and having knowledge of internet.

3.4.7.a. Sampling Technique :

Random Sampling technique has been used for this study. In a Random sample from infinite population selection of each item is controlled by the same probabilities and the successive selections are independent of one another. (C.R.Kothari, Research

Methodology Methods and Techniques)

3.4.7.b. Sample size Calculation – The following formula was used for calculating the sample size.

Where, n = Sample size, = Standard Deviation, E = Estimated margin of error

= is known as the critical value. The critical value is = 1.96.

The margin of error = 1 and the standard deviation = 18.19. Using the formula for sample size, we can calculate :

2 Z   2  2  1.9618.19 n    1271.78  E   1   

Round off sample size required is 1272 respondents.

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3.2. Table on Chosen Sample Size

Place No. of Respondents Sr. No.

1 Mumbai 516

2 Nashik 359

3 Surat 397

TOTAL 1272

3.4.8. Variables of the study

3.3. Table showing the variables of the study

Dependent Variables Independent Variables

Buying Behaviour with respect to Online Purchase Behaviour Social Media Advertising. Consumer Buying Behaviour

Complex Buying Behaviour

Habitual Buying Behaviour

Variety Seeking Buying Behaviour

Dissonance Buying Behaviour

Impulsive Buying Behaviour

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3.4.9. Definition of the Variables :

1. Online Purchase Behaviour :

Online Purchase Behaviour variable primarily indicates the online behaviour

of the consumer from the purchase point of view. It throws light on a couple

of things related to the purchase taking place online through the medium of

social media, like involvement of the consumer while taking the online

purchase decision, to what extent the consumer thinks there is a difference in

the products of different brands available online, what does the consumer

think about the price of the product available on social media and does the

consumer think that the decision making process in case of online products is

time consuming.

2. Consumer Buying Behaviour :

Consumer Buying Behaviour variable focuses on the online behaviour of the

consumer from the reasons which lead to the purchase through social media,

point of view. It considers the reasons which lead to the purchase like whether

the consumer read the blogs / reviews or view the advertisement on social

media. It also studies the consumers behaviour by considering, to which

electronic products consumer has provided rating.

3. Complex Buying Behaviour :

Complex buying behaviour when the consumer is highly involved in the

buying then it is called complex buying behavior. In case of complex buying

behavior the consumer must collect proper information about the product

features and attributes.

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4. Habitual Buying Behaviour :

In case of Habitual buying behavior there is low involvement of the consumer.

The consumer buys the product belonging to a particular brand which has been

regularly preferred by them because the consumer thinks that the product

belonging to a particular brand is best fit for them. The consumer buys the

product quickly.

5. Variety-Seeking Buying Behaviour :

Variety seeking buying behaviour takes place when the consumer has many

different product choices that serve the same purpose. In case of Variety-

Seeking Buying Behaviour Consumers generally buy different products

because they want to try out a new variety of product.

6. Dissonance Buying Behaviour :

In Dissonance buying behavior consumer is highly involved in the purchase.

Dissonance buying behavior occurs when the product which the consumer is

thinking of buying is expensive or there are no differences or a few differences

between the brands. The consumers experience a feeling of discomfort or

anxiety after the purchase of the product, because they fear that the expensive

product which they have bought should not be a failure.

7. Impulsive Buying Behaviour :

Impulsive buying behaviour takes place when the consumer makes an

unplanned purchase, provoked by seeing the product or upon exposure to a

lucrative advertisement or scheme.

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3.5 Limitations of the Study :

The study was conducted based on the data collected from Mumbai, Nashik and Surat and therefore findings of this study may not be applicable to other cities in India and the world at large because of the socio-cultural and economic differences.

3.6 Utility of the study :

The study would be very useful to markets who would now be able to use social media as a platform for promoting their products and services.

3.7 Theoretical Model :

Figure 3.1 Theoretical Model of the Study

Online Purchase Behaviour Factors of Social

Media Consumer Buying Consumer Advertising Behaviour Buying Behaviour Age Complex Buying with respect to Behaviour Social Media Occupation Advertising Habitual Buying Education Behaviour

Annual Income Variety Seeking Place Buying Behaviour

Dissonance Buying Behaviour

Impulsive Buying Behaviour

Age : 18-35.

Occupation : Service, Business & Self-employed professionals. Education : Non-graduates, Graduates & Post Gadruates.

Annual Income : Up to Rs. 3 Lakhs, 3.1-5 Lakhs, 5.1-10 Lakhs & above 10 Lakhs.

Place : Mumbai, Nashik & Surat.

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3.8 Analysis of Data :

The data was analyzed in SPSS version 17 using different statistical tools viz:

1. Frequency Table With percentages 2. Analysis of Variance (ANOVA) 3. Chi-Square Test 4. Regression 5. Rank Order

The raw data has been collected from primary source i.e. with the help of questionnaire which consists of the question at two different level of measurements i.e. nominal and interval scale. To draw the logical inferences from the data descriptive and inferential statistics techniques had been used. The type of statistical techniques i.e. Bivariate analysis and Multivariate analysis has been used based upon the level of measurements of the questions pertaining to those variables. The

Multivariate procedures dealing with the analysis of variance were used to test and to draw the inference whether the samples have been drawn from more than two populations having the same mean; it helped the researcher to understand the perception of the responses for all the factors in more than two groups. Then in bivariate analysis, Chi square test has been used to find the association between the two qualitative variables. Frequency table with percentages has been used to identify the demographics and buying behaviour perception of young working women across different cities. Regression analysis has been used to determine the nature of relationship (functional relationship) between the variables of the study for forecasting or prediction. Rank Order has been used to determine which Social networking tool from Facebook, Twitter and LinkedIn is the most effective social networking tool. Rank Order correlation coefficient measures the strength of association between two ranked variables.

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Chapter 4

Typical Aspects of Social Media and Social Networking Sites

Electronic word of mouth is an important phenomenon of Social Media and it has the potential to take the products and the brand to new heights, as well as to ruin the existence of a product or a brand. Electronic word of mouth (eWOM) has been defined by Hennig- Thurau et al. (2004, p.13) as “any positive or negative statement made by potential, actual or former customers about a product or company, which is made available to a multitude of people and institutions via the internet”. Consumers very often refer to the eWOM as a source of information that gives them a large variety of opinions about the product or service or the company. Consumers find the eWOM as more persuasive, more trustworthy than the information direct from corporate sources. Yet eWOM can cause a threat to companies, since managers don’t have any control over the negative messages spread by the unsatisfied consumers.

Therefore it is very important for managers to effectively manage these eWOM so as to use them to promote the products and brands.

Social media management is a new area of management which has emerged with the growing success of social media and it is a kind of service which is associated with

Social Media. Organizations can efficiently manage their outbound and incoming online interactions along with the small business marketing activities with the help of

Social media management solutions. Social media management solutions helps in reorganising and fusing the organization’s conversations taking place when the organization interacts through different channels of Social media like - blogs, social networks like Twitter or Facebook, and other public and private Web communities

113 and sites. They also help the organizations to monitor and to know the people’s views and opinions about their business, products or services. Social media management helps in the automation of the process of delivering the outgoing messages through multiple social media outlets simultaneously and also enhances the organization’s social media presence across several social networking sites.

Social media management tools also facilitates organizations to integrate their social networking activities with other marketing programs which include other online activities, such as search engine marketing campaigns, Web sites, email marketing, contact management systems, as well as offline marketing, such as events or white paper.

4.2. Social Networking Sites :

4.2.1. Facebook

4.2.1.1. Origin of Facebook:

Face book was invented by a computer science student of Harvard University called

Mark Zukerberg in February 2004. Mark Zukerberg alongwith his classmates

Eduardo Saverin, Dustin Moskovitz, and Chris Hughes invented the Facebook.

Facebook was originally named as Facemash. Facemash was a software written by

Zukerberg when he was in his second year and it was a type of a game wherein the students who visited this website were able to see and compare two students identity photographs side-by-side which let them decide “Hot” or “not”. Mark Zukerberg tapped into the Harvard university’s security network and from there he csopied the student’s id images to populate Facemash. For the same Mark Zukerberg faced charges of breach of security system which were later on dropped. On 4 Frebruary

2004 Mark Zukerberg launched the website “TheFacebook”. The access to The

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Facebook site was at first restricted to Harvard students only. Zukerberg then took the help of his friends to make his site more popular : Eduardo Saverin worked on business, Dustin Moskovitz as a programmer, Andrew McCollum as a graphic artist, and Chris Hughes. Together the team expanded “TheFacebook” from Harvard’s campus to additional universities and colleges. In 2005 they purchased the domain name Facebook.com for $20,000 and within no time Mark Zukerberg became the world’s youngest multi-billionaire.

4.2.1.2. Number of Users on Facebook :

Active users are those users who have logged into Face book during the last 30 days.

In the second quarter of 2012, there were more than 1 billion monthly active users

(MAU). In the fourth quarter of 2013 the number of face book users had crossed 945 million mobile MAU. In the first quarter of 2014 Facebook had 1.28 billion monthly active users.

4.2.1.3. Face book’s Revenue: Facebook’s revenue grew from 153 million in 2007 to 7.87 billion US dollars in 2013.

4.2.1.4. Advantages of Facebook :

1. Facebook is free :

Facebook has provided free services to its users. This is the biggest advantage of

Facebook because anything which comes free is more powerful. Apart from that

Facebook is a well designed website and has the capability of engaging the users for longer time. In the recent days some paid services have been started by Facebook, but those paid services are not made compulsory for its users and the users are given the freedom to choose the right service.

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2. Facebook helps in Networking :

Facebook helps in connecting with old school friends, college friends and relatives.

Also facebook gives its users opportunities to make new friends from the different parts of the world. Facebook users can use facebook chat, poke, messages, group etc to connect with different people and improve their relationships with them. Therefore the users of facebook can take advantage of the various services provided by

Facebook and maintain their relationships. They can not only share videos and albums but also write blogs, articles and share it with their acquaintances.

3. Facebook facilitates Business :

Facebook has billions of users across the world, therefore it is the best place for businesses to promote their products or services. Using facebook, businesses can improve their brand value in the social media network. Businesses can direct their products or services through promotional campaigns to their target audience over

Facebook. For acquiring Business, organizations can make Facebook fan page of their brand or company.

4. Facebook video chat :

Facebook’s video chat tool allows its users to video chat with their friends and relatives. Facebook in partnership with skype has an in built video chat application which offers the service of video chatting to Facebook users.

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5. Facebook as image and video hosting site :

Facebook users can make albums of their images or collection of their videos on

Facebook and share it as public with their acquaintances or keep it private by using

Facebook privacy.

6. Facebook security :

Facebook has extremely high standard privacy policies and it provides high class security to the users account. It has kept the privacy settings very simple so that the users can easily use them to secure their account. Facebook is very strict as far as spammers are concerned. The users can hide the posts of the spammers, block the spammers or report the spammers to Facebook.

7. Free Gaming and app store on Facebook :

Free gaming services are provided by Facebook to its users, whereby the users can play free games with their friends. Also Facebook provides free app store where you can use thousands of Facebook application.

8.Facebook for news :

Facebook is also used by many users as a source of information and to know the news.

4.2.1.5. Disadvantages of Facebook :

Though Facebook has an array of benefits, it also has some disadvantages.

However the advantages of Facebook outpass the disadvantages.

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1.1.Fake profiles and ids :

Fake profiles is one of the biggest disadvantages of Facebook. Many people

create false id’s and fake profiles to cheat and trouble people they don’t like.

2.Addicting nature of Facebook :

Facebook is a well designed site with thousands of exiting and interesting

applications and services. It has the power to engage the user for long hours by

consuming their precious time. If the facebook is used to suffice the need, then it

is alright, however if one gets addicted to it, it consumes a lot of valuable time.

3.Privacy issues :

Many times due to lack of knowledge, many people don’t use the privacy features

which are offered by Facebook. This directly affects their personal information

which they provide to facebook to be accessed by anyone and for any purpose

causing serious problems.

4.2.2. Twitter :

4.2.2.1. Origin of Twitter :

Twitter is an innovation born out of necessity. Twitter is basically an sms mobile

phone-based communications platform, which eventually grew into a web

platform and it was founded by Jack Dorsey, Noah Glass, Biz Stone and Evan

Williams in 2006. This sms based platform was proposed by Jack Dorsey to co-

founder of Odeo, Evan Williams and Biz Stone during a brainstorming session at

Odeo which was a podcasting company. Evan Williams and Biz Stone asked

Jack Dorsey to go ahead and develop the twitter project. Noah Glass came up

118 with the name “twttr” earlier and later on it became popular with the name of

“twitter” which was also found out by Noah Glass. During the development and testing phase of twitter the podcasting company Odeo underwent a rough patch because Apple released its own podcasting platform which killed Odeo’s business model. The founders decided to buy their company back from the investors. Jack Dorsey, Biz stone, Evan Williams and other members of Odeo staff facilitated the buyback and by doing this they decided to acquire the rights to the Twitter platform. There is a controversy involved in the formation of

Obvious Corporation which was formed as a formality after the investor buyback of Odeo to house Twitter. The key members of the twitter development team were not brought on to the new company, specifically Noah Glass.

Twitter’s user base has grown at an astonishing rate to over 200 million active monthly users in six years and in March 2013, Jack Dorsey and Biz Stone were awarded the patent that secures the ownership of Twitter.

4.2.2.2. Number of Users on Twitter :

Table 4.1. Showing the Number of users on Twitter

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Twitter Company Statistics Data

Total number of active registered Twitter users 645,750,000

Number of new Twitter users signing up everyday 135,000

Number of unique Twitter site visitors every month 190 million

Average number of tweets per day 58 million

Number of Twitter search engine queries every day 2.1 billion

Percent of Twitter users who use their phone to tweet 43 %

Percent of tweets that come from third party 60% applicants

Number of people that are employed by Twitter 2,500

Number of active Twitter users every month 115 million

Percent of Twitters who don’t tweet but watch other 40% people tweet

Number of days it takes for 1 billion tweets 5 days

Number of tweets that happen every second 9,100

For the period, Twitter reported 241 million monthly active users. The service also reported monthly mobile active users of 184 million.

Source : www.techcrunch.com dated 28/11/2014

4.2.2.3. Revenue of Twitter :

Table 4.2 Showing the year-wise revenue of Twitter

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Twitter Annual Advertising Revenue Revenue

2013 $405,500,000

2012 $259,000,000

2011 $139,000,000

2010 $45,000,000

Source : www.statisticbrain.com dated 28/11/2014.

4.2.2.4. Advantages of Twitter :

1. Businesses can do Internet marketing free of cost by using Twitter wisely.

Twitter provides an excellent opportunity for the businesses to identify and to

understand the passion and interests of their target market. Businesses can

research their target markets by following their tweets.

2. Twitter can be used by businesses to understand the strategies of the

competitors by following their tweets.

3. Twitter allows individuals to efficiently network with large groups of people

and interact with their target markets effectively. Twitter helps in efficiently

directing the internet marketing campaigns to the relevant groups.

4. Twitter helps businesses in communicating instantly and directly with the

target market. It helps in gathering valuable feedback (real time intelligence)

from the target audience, in a very short span of time. Thus facilitating in

having a lasting relationship with the consumers.

4.2.2.5. Disadvantages of Twitter :

1. Twitter has a large number of spammers. Therefore its adivisible to filter out

the spammers from the lists frequently, to have a fair judgement of the target

market.

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2. It is very easy to get distracted from the purpose or objective as you get

involved in the communication or receive tweets from outside the business

interests. Therefore the individuals need to be focused on their business goals.

4.2.3. LinkedIn

4.2.3.1. Origin of LinkedIn :

LinkedIn is the oldest social networking site and it is older then YouTube,

Facebook and Twitter. LinkedIn started in the living room of the co-founder

Reid Hoffman and it was officially launched on 5 May 2003 with a goal of connecting world’s professionals and making them more productive and successful. Reid Hoffman had an excellent track record of working on the boards of Google, Ebay, PayPal. Along with Reid Hoffman, Allen Blue, Konstantin

Guericke, Eric Ly and Jean-Luc Vaillant are the inventers of LinkedIn.

LinkedIn has diversified business model with talent solutions, marketing solutions and premium subscription products.

4.2.3.2. Status of LinkedIn Today :

LinkedIn operates the world’s largest professional networks on the internet with more than 315 million users in over 200 countries. The professionals are joining the LinkedIn at the rate of more than 2 new member per second.

4.2.3.3. Revenue of LinkedIn :

LinkedIn has earned a total revenue of $534 Million in the second quarter of

2014.

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Figure 4.1 Revenue distribution of LinkedIn

Source : http://press.linkedin.com/about dated 20/10/2014

4.2.3.4. Benefits LinkedIn Brings for Business:

For business owners, account managers, business development managers and

anyone else who is in sales, these are the benefits LinkedIn can offer :

1. 1.Find Business Partners, Clients and Service Providers :

By giving simple searches you can connect with the experts, service providers

and prospective customers. If you want to recruit people, LinkedIn provides easy

access to potential candidates that fit in the required level of expertise. Business

can also post job ads. LinkedIn is the best solution where you can find

professionals according to your business requirement.

2. 2.Information Sharing :

LinkedIn is commonly used for knowledge sharing and the LinkedIn users can

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use their mailbox to pose questions to contacts and the multitude of groups on

LinkedIn serves as forums for discussions on variety of products and industry

related topics. LinkedIn Answers is the tool of LinkedIn which aims at providing

online information and idea-sharing.

3. 3. A Blog Promotional Tool :

LinkedIn users are able to add a blog or website to their individual profile in

order to give it exposure. LinkedIn is a great way to promote and share blogs.

4. 4. LinkedIn Recommendations :

Another tool that has been offered by LinkedIn is recommendation feature. Once

the products or services are there on any individual’s company profile,

recommendations can be requested from the customers regarding the product.

Recommendations means people talking about an individual or a product or a

service in Discussions, mentioning them as the expert in Answers or talking

about them outside of LinkedIn. Recommendations is the way to increase the

company’s trustworthiness and win new clients.

5. 5. LinkedIn for SEO :

LinkedIn’s profiles get a high PageRanking in google and this is a good way to

influence what people see when they search for an individual or his business.

LinkedIn allows an individual’s profile information to be available for search

engines to index. Going one step further LinkedIn now provides the facility to

share the content alike Facebook and Twitter and this activity is called as the

stimulator of search engine ranking positions (SERPs).

6. 6. Starting groups:

An excellent opportunity to network and grow the business is provided by the

Groups tool. Through this tool one can put the website link in the group profile

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for greater visibility and also include the website link in the group welcome

message and in each new discussion that is being created.

7. 7. Advertising :

LinkedIn has 120 million users global presence and excellent targeting

capabilities to attract the advertisers. LinkedIn has started a service called

“LinkedIn Ads” which has given an advertising opportunity to all it its users on a

cost per click (CPC) or impression basis (CPM).

4.2.4. Youtube :

4.2.4.1. Origin :

YouTube is the world’s most popular video site. In the year 2005 there were a

lot of content and photographs sharing sites and there were a lot of ways of

capturing photos. However there was not a single site through which one can

share the videos. That’s when Youtube was invented by Chad Hurley, Steve

Chen and Jawed Karim. Chad Hurley had studied design at Indiana University in

Pennsylvania and Steve Chen was a computer science student at the Illinois

University at Urbana Champaign. After graduation both of them started working

at Paypal in San Jose, California. In Feb. 2005 the logo and domain of YouTube

was registered by Hurley and three months later the beta test site

www.YouTube.com was launched in May 2005. YouTube received its funding

from Sequoia Capital in November 2005 and in the month of December 2005

YouTube officially became a corporation with its office in California. The first

video which flashed on the site was “Me at the zoo” which was a 19 seconds

long video. Google identified the growing potential in YouTube and YouTube

was acquired by Google for $1.65billion in October 2006. YouTube is spread

125 across 61 countries and 61 languages.

4.2.4.2. Number of Users accessing YouTube :

More than 1 billion users visit YouTube each month and more than 6 billion hours of video are watched every month on YouTube. 100 hours of video are uploaded to YouTube every minute.

4.5. RSS

Short form for Rich Site Summary or Really Simple Syndication. This service is an easy way to distribute the updates of websites to a large number of people. It is mostly used by those computer programs which organize the headlines and updates for easy reading.

4.2.5.1. Working of RSS

The author of the website maintains a list of notifications in a standard format on the website, which is called as the “RSS Feed”. People who are interested in knowing the latest information or updates can check this list. “RSS Aggregators” are specialised computer programs which access the RSS Feed of various websites of interest, on your behalf and organize the results. The RSS feed and

RSS aggregators together form the “RSS Readers”.

4.2.5.2. Benefits of RSS :

There are some websites whose content changes on an unpredictable schedule for e.g. product information pages, news sites, community and religious organization information pages, medical websites, websites of educational institutions and weblogs. Continuously scrutinizing each website for any updates

126 is very time consuming and tedious.

Earlier websites were emailing notifications to the users. But when there are notifications from many websites they are not organised and are mistaken for spam. RSS is a better way of receiving many updates and in an organized manner. RSS properly handles the updates of multiple websites and the results are presented in a well organized form.

4.2.6. SlideShare :

Slideshare is a web service meant for uploading presentations and sharing it with everyone, so that the presentations receives more views. It is the world’s largest community for uploading and sharing presentations. It supports all formats : ppt, pps, pptx, odp, pdf, doc, docx, odt, keynote and iWork pages. The presentations and documents can be linked with an individual’s LinkedIn account. One can incorporate YouTube videos in presentations and can also add audio. Slideshare is present on LinkedIn and Facebook. If the presentation is uploaded to anyone from Facebook, LinkedIn, Slideshare, then it shows up in all three instantly.

Looking at the potential Google bought Slideshare platform at $119 Million.

4.2.6.1. Users of Slideshare :

According to comScore, SlideShare had 29 million unique visitors. Users have uploaded 9 million presentations on SlideShare.

4.2.7. Myspace :

Myspace is a social networking site which allows its users to create web pages for the purpose of interacting with friends. Myspace allows its users to create blogs, upload photos and videos and design profiles to portray their talents and

127 interests. This site originated in the year 2003 and it became extremely popular among people. Myspace has helped many talented music artists and actors to kick start their flourishing careers.

4.2.8. Friendster :

Friendster is another social networking site used for interacting with friends. It came into existence in 2002, therefore it’s a predecessor to Myspace and

Facebook. Friendster at present, has closed its social networking services.

Friendster founder Jonathan Abrahams has entered into a new business of social news services, which is open to public and shares news and stories of successful tech companies.

Chapter 5

Consumer Electronics Companies and their presence on Social

Media

5.1. Global Players :

5.1.1. Samsung

Samsung has efficiently mastered the social care element not just by its social media presence, but by cleverly targeting their target consumers by its social

128 media campaigns. Samsung has a customer centric approach for its online advertising where the consumer’s needs, their issues, queries, feedback is given a lot of importance.

Samsung has successfully set an example of taking advantage of metrics powered digital and social strategy to have an overwhelming number of fans from the earlier 8 million to directly 25 million fans making it the number one brand in Europe. Samsung has achieved maximum global reach by creating its

Facebook brand page in 25 different languages for 28 countries taking itself to very corner of the globe. Samsung is very much happy with its strategy of localized campaigns.

Every week it has approximately 300,000 fans joining its fan list. This success of

Samsung Europe can be attributed to analytics driven understanding of consumers, developing localized campaigning strategy and engagement through quality creative content that supports two-way communications between

Samsung and its fans. Engaging, listening and responding to the consumers is of prime importance to Samsung. The main objective of their social media participation is creating the best social content, social advertising and segmentation and social care.

5.1.2. Apple

Apple has not made a direct appearance on Social media sites like Facebook and twitter which means that Apple does not have its own company page or Apple brand page on these social networking sites for their products. However it does have accounts on facebook and twitter for its services like itunes, iBook and App

129

Store. But all these accounts which Apple has for its services are not interactive and social. Apple does not make any attempt to respond to the consumers or does not participate in any discussions through these accounts. It simply pushes the marketing messages on to the consumers. Apple’s strategy was to become famous socially by remaining completely silent and let the rumors do the work of enhancing Public relations. Basically Apple wanted to create arouse excitement among people for its products. However Apple finally made its social media debut by creating its Apple brand page on Tumblr for promoting its iPhone5C. Apple selected Tumblr because it allows users to click on several short video animations with a short story and tagline in it. Apple’s strategy was to create a buzz by remaining silent and let the rumors do all the promotion work for it.

5.1.3. Sony

Sony adopts the policy of providing Social customer service which is delivering customer centric service through social media platform. According to social media management experts at Sony, there is no need to respond to every brand related query of the consumers that pops up in the social world, allowing the answers to the query to come from within the social media community.

The experts advocate that Sony’s social media strategy has been to identify the

Super Users (Super active sony fans) educate them, train them and allow them to respond to customer queries on behalf of Sony, to become social media moderators. The customer service provided through social media should be personal, helpful and chatty.

130

According to Nico Henderijckx European Forums Communities Manager, Sony:

1. The best support given to Sony users is by other users through their

community.

2. It follows the principle of allowing end users to help other users in social

customer service.

3. Sony keeps their ‘super’ fans i.e super active Sony fans passionate by

training them about the brand so that these super fans become the Social

media moderators for Sony.

4. Sony has been successful in achieving an 85% solve rate of the

complaints through peer-to-peer online support and it has been observed

that the complex problems are solved faster than the support line calls.

5. The moderators or the super fans are kept abreast with the latest product

knowledge through monthly training, online meetings, super user

conferences and insights on product launches. The top management

keeps the super fans passionate and motivated by meeting them and

explaining them the company’s goals and objectives.

6. The moderators are treated such that they feel special and are also given

incentives in the form of free products.

7. According to the latest statistics there has been an increase in the number

of British user’s interaction with brands over Twitter from 12% to 36%.

8. 65% people prefer social media than the call centers for solving their

customer queries and for customer service.

9. Social customer service is often used as a (di)stress channel i.e a back

channel to release customer’s frustration when other methods of contact

fail.

131

10. Social customer service is more profitable than marketing since 1%

increase in customer coming back to website generates 10% increase in

revenues.

5.1.4. Hewlett -Packard The growing effectiveness of digital media has changed the way marketers interact with customers. New age customers are informed and empowered. The challenge for organizations is to be a part of the customers’ conversations involving their product and to influence their choices. Hence, the adoption of digital channels such as social media, e-mail marketing and online search and display ads is growing steadily. What helps marketers get the most out of their digital marketing strategies is the ability to capture and mine data exhaustively and cost effectively through advanced analytics techniques. These techniques shed light on the effectiveness of all marketing activities, thus helping marketers fine-tune their strategy. In the long run, this enhances customer engagement, optimizes digital “marketing spend” [1] and has a direct impact on revenues.

Hewlett-Packard uses advanced analytics and operations research (O.R.) applications to drive its digital marketing strategies and overcome business challenges. HP’s in-house analytics team, Global Business Services Analytics

(GBS Analytics), directs this enterprise-wide analytics effort and plays a critical role in developing various advanced analytics solutions. These solutions leverage structured and unstructured data across billions of customers worldwide to improve the effectiveness of the e-marketing model across HP.

E-Marketing at HP

132

HP is at the centre stage of this digital revolution and has been making significant investments on digital channels to generate demand, engage customers and provide technical support. E-marketing at HP can be summarized into three broad themes – the three “Cs” of the e-marketing ecosystem:

1. Community deals with the aspect of engaging customers and creating awareness about HP products and services, leading to effective lead generation.

2. Content deals with the aspect of providing customized relevant content to customers and improving user experience.

3. Commerce deals with aspects of generating revenue through online commerce. (See Figure 5.1.)

Figure 5.1: Three Cs of E-marketing ecosystem at HP.

Multiple levers are available to grow the online business. These levers include:

133

 driving traffic by guiding customers to the right content;

 increasing conversion by offering relevant products at appropriate price

points;

 cross-sell and up-sell to increase basket size and improve margins; and

 increasing customer engagement to increase loyalty and repeat purchase.

HP deploys various analytical solutions to drive online commerce.

5.1.5. LG

LG intends to be present on Social media to create a closer connect with the consumers. The objective is to develop a bonding with the brand based on the likes and dislikes of consumers which will result in brand awareness and brand promotion.

According to LG facebook is a much broader engagement platform as compared to twitter. LG makes maximum use of Facebook platform for informing, engaging and entertaining the target audiences. Therefore LG undertakes a wide variety of initiatives related to product and technology news, contests, exploiting their sponsorships with respect to cricket and Formula One etc. Interaction levels are high here. LG’s activities on Twitter are limited in terms of content sharing and it is more often used as a platform for answering the grievances. Twitter’s role for brands should be to listen more than

134 talk; to solve problems and answer questions when asked.

According to LG the marketers must understand the consumer’s reason of joining a social community instead of bombarding its followers with the brand messages.

Therefore the content should be such that it helps people enjoy, connect with others and entertain them.

The Smartphone Idea Camp allows our consumers to showcase their creativity and talent and its an excellent way to gain inspiration from the imagination of the mobile phone users and the tech savvy crowd. Through this contest LG is in a better position to understand the demands and desires of the consumers and to know what exactly they are looking for in a product so that it can add value to their lives.

5.2. Indian Players :

5.2.1. Hindustan Computers Limited (HCL) :

HCL is an India based company which has a network of offices in 26 countries with 88,000 professionals of “ diverse nationalities”. HCL is exclusively using

Social Media for hiring people. In order to provide Human resources to employees, HCL has developed its own social network for internal use, called

Meme. The Meme platform has been used by the employees for connecting with

135 each other, for giving feedback and suggestions, for sharing photographs, for asking queries, for enabling support functions and staffing services. HCL’s social listening and analytics studies the consumer’s views and opinions, delivers competitive intelligence and product research and performs customer profiling, segmentation and influencer identification. HCL has a maximum social media presence with its company profiles being created on Facebook,

Twitter as well as LinkedIn, Flickr, Youtube, Google+ and Scribd.

5.2.2. TCS :

TCS is an Indian multinational Information Technology (IT) company offering it

IT and Business solutions and services and providing outsourcing service. In consumer electronics segment it focuses on audio, video and game console products. TCS has presence on six social networking sites Facebook, Twitter,

LinkedIn, RSS feed, Slideshare, Youtube. On a 5 point scale, TCS has a rating of 1.25 for its Social Media presence.

5.2.3. Wipro :

Wipro is extensively using the Social media platform for spreading the brand and reaching out to customers. When wipro decided to use social media platform in 2007, it considered social media as a business driver. A great deal of emphasis was laid on the importance of creating an experience for its users.

136

The MyWiproWorld is Wipro’s internal social media channel which allows its global employees to interact, engage, exchange ideas, innovations etc. Wipro has a Council for Industry research which comprises of technology, business experts along with academicians from institutes for analysing the market trends and meet the customers needs. This council generates insights for the business which help in formation of strategies. The digital team works in close collaboration with the Council for industry research team and internal marketing team to monitor the conversations getting exchanged over multiple channels and to drive the online conversations. The digital team increased the frequency of engagement on social platform by posting the daily updates on business insights, company events, job and other related areas.

The low cost, focused and high impact branding strategy of Wipro has taken it to new level. Wipro has its presence on Facebook, Twitter, LinkedIn, Slideshare and Youtube. Wipro is having 4 Facebook profiles (i.e. wipro.com, careers@Wipro, Xperience@Wipro and careers@Wipro BPO), 3 twitter profiles

(@Wipro, @Wiprocareers and @XperienceWipro), 1 LinkedIn, 1 YouTube accounts.

137

Chapter 5

Consumer Electronics Companies and their presence on Social

Media

5.1. Global Players :

5.1.1. Samsung

Samsung has efficiently mastered the social care element not just by its social media presence, but by cleverly targeting their target consumers by its social media campaigns. Samsung has a customer centric approach for its online advertising where the consumer’s needs, their issues, queries, feedback is given a lot of importance.

138

Facebook brand page in 25 different languages for 28 countries taking itself to very corner of the globe. Samsung is very much happy with its strategy of localized campaigns.

Every week it has approximately 300,000 fans joining its fan list. This success of

5.1.2. Apple

139 media debut by creating its Apple brand page on Tumblr for promoting its iPhone5C. Apple selected Tumblr because it allows users to click on several short video animations with a short story and tagline in it. Apple’s strategy was to create a buzz by remaining silent and let the rumors do all the promotion work for it.

5.1.3. Sony

The experts advocate that Sony’s social media strategy has been to identify the

According to Nico Henderijckx European Forums Communities Manager, Sony:

28. The best support given to Sony users is by other users through their

community.

29. It follows the principle of allowing end users to help other users in social

customer service.

30. Sony keeps their ‘super’ fans i.e super active Sony fans passionate by

training them about the brand so that these super fans become the Social

140

media moderators for Sony.

31. Sony has been successful in achieving an 85% solve rate of the

complaints through peer-to-peer online support and it has been observed

that the complex problems are solved faster than the support line calls.

32. The moderators or the super fans are kept abreast with the latest product

knowledge through monthly training, online meetings, super user

conferences and insights on product launches. The top management

keeps the super fans passionate and motivated by meeting them and

explaining them the company’s goals and objectives.

33. The moderators are treated such that they feel special and are also given

incentives in the form of free products.

34. According to the latest statistics there has been an increase in the number

of British user’s interaction with brands over Twitter from 12% to 36%.

35. 65% people prefer social media than the call centers for solving their

customer queries and for customer service.

36. Social customer service is often used as a (di)stress channel i.e a back

channel to release customer’s frustration when other methods of contact

fail.

37. Social customer service is more profitable than marketing since 1%

increase in customer coming back to website generates 10% increase in

revenues.

141 involving their product and to influence their choices. Hence, the adoption of digital channels such as social media, e-mail marketing and online search and display ads is growing steadily. What helps marketers get the most out of their digital marketing strategies is the ability to capture and mine data exhaustively and cost effectively through advanced analytics techniques. These techniques shed light on the effectiveness of all marketing activities, thus helping marketers fine-tune their strategy. In the long run, this enhances customer engagement, optimizes digital “marketing spend” [1] and has a direct impact on revenues.

E-Marketing at HP

1. Community deals with the aspect of engaging customers and creating awareness about HP products and services, leading to effective lead generation.

2. Content deals with the aspect of providing customized relevant content to

142 customers and improving user experience.

3. Commerce deals with aspects of generating revenue through online commerce. (See Figure 5.1.)

Figure 5.1: Three Cs of E-marketing ecosystem at HP.

Multiple levers are available to grow the online business. These levers include:

 driving traffic by guiding customers to the right content;

 increasing conversion by offering relevant products at appropriate price

points;

 cross-sell and up-sell to increase basket size and improve margins; and

 increasing customer engagement to increase loyalty and repeat purchase.

HP deploys various analytical solutions to drive online commerce.

143

5.1.5. LG

According to LG the marketers must understand the consumer’s reason of joining a social community instead of bombarding its followers with the brand messages.

Therefore the content should be such that it helps people enjoy, connect with others and entertain them.

The Smartphone Idea Camp allows our consumers to showcase their creativity

144 and talent and its an excellent way to gain inspiration from the imagination of the mobile phone users and the tech savvy crowd. Through this contest LG is in a better position to understand the demands and desires of the consumers and to know what exactly they are looking for in a product so that it can add value to their lives.

5.2. Indian Players :

5.2.1. Hindustan Computers Limited (HCL) :

HCL is an India based company which has a network of offices in 26 countries with 88,000 professionals of “ diverse nationalities”. HCL is exclusively using

Social Media for hiring people. In order to provide Human resources to employees, HCL has developed its own social network for internal use, called

Meme. The Meme platform has been used by the employees for connecting with each other, for giving feedback and suggestions, for sharing photographs, for asking queries, for enabling support functions and staffing services. HCL’s social listening and analytics studies the consumer’s views and opinions, delivers competitive intelligence and product research and performs customer profiling, segmentation and influencer identification. HCL has a maximum social media presence with its company profiles being created on Facebook,

Twitter as well as LinkedIn, Flickr, Youtube, Google+ and Scribd.

145

5.2.2. TCS :

TCS is an Indian multinational Information Technology (IT) company offering it

LinkedIn, RSS feed, Slideshare, Youtube. On a 5 point scale, TCS has a rating of 1.25 for its Social Media presence.

5.2.3. Wipro :

146 the online conversations. The digital team increased the frequency of engagement on social platform by posting the daily updates on business insights, company events, job and other related areas.

(@Wipro, @Wiprocareers and @XperienceWipro), 1 LinkedIn, 1 YouTube accounts.

147

Chapter 7

Data Analysis and Findings

7.1 Tabulation and Statistical Analysis of Data

The data collected from questionnaire were scored and tabulated into a master data sheet. The data was analyzed with the help of statistical package SPSS 17.

The mean scores arrived are put to various statistical analysis using various statistical tools in order to test the research hypothesis. The statistical tools applied included Chi-Square test, Regression, Anova, Rank Order Co-efficients etc.

The Data Analysis has been divided into :

i) Descriptive Analysis.

ii) Inferential Analysis.

(I) Descriptive Analysis - The descriptive analysis has been written in the

Annexure and can be referred to in the Annexure.

(II) Inferential Analysis - Exclusive analysis has been done for the purpose of

the research and the essence of the analysis has been presented in this

chapter.

148

Objective 1 – To identify the Social Media Usage by young working

women in different cities.-

1. USAGE OF SOCIAL MEDIA - DO YOU USE SOCIAL

NETWORKING SITES ?IN DIFFERENT CITIES -

Table 7.1.1. Showing the number of young working women accessing or

using social networking sites in Mumbai, Nashik and Surat.

USAGE OF

SOCIAL MEDIA -

DO YOU USE

SOCIAL

NETWORKING

SITES Total

YES NO YES

PLACE MUMBAI Count 459 57 516

% of Total 36.1% 4.5% 40.6%

SURAT Count 364 33 397

% of Total 28.6% 2.6% 31.2%

NASHIK Count 314 45 359

% of Total 24.7% 3.5% 28.2%

Total Count 1137 135 1272

% of Total 89.4% 10.6% 100.0%

Mumbai

149

It was found that out of total 516 respondents, 459 agreed that they use

social networking sites and 57 disagreed.

Surat

It was found that out of total 397 respondents, 364 agreed that they use

social networking sites and 33 disagreed.

Nashik

It was found that out of total 359 respondents, 314 agreed that they use

social networking sites and 45 disagreed.

2. USAGE OF SOCIAL MEDIA - WHICH OF THESE SOCIAL

NETWORKING SITES DO YOU USE- "Face book" –

Table 7.1.2. Showing the number of young working women accessing or

using “Facebook” in Mumbai, Nashik and Surat.

USAGE OF SOCIAL MEDIA -

WHICH OF THESE SOCIAL

NETWORKING SITES DO

YOU USE- "Face book" Total

Yes No Yes

PLACE MUMBAI Count 408 108 516

% of Total 32.1% 8.5% 40.6%

SURAT Count 334 63 397

% of Total 26.3% 5.0% 31.2%

NASHIK Count 279 80 359

% of Total 21.9% 6.3% 28.2%

Total Count 1021 251 1272

% of Total 80.3% 19.7% 100.0%

150

Mumbai

It was found that out of total 516 respondents, 408 agreed that they used Face

book and 108 disagreed.

Surat

It was found that out of total 397 respondents, 334 agreed that they used Face

book and 63 disagreed.

Nasik

It was found that out of total 359 respondents, 279 agreed that they used Face

book and 80 disagreed.

3. USAGE OF SOCIAL MEDIA - HOW OFTEN DO YOU USE SOCIAL

NETWORKING SITES LIKE FACE-BOOK, TWITTER, LINKEDIN -

151

Table 7.1.3. Showing the frequency with which the young working

women access SNS in a week in Mumbai, Nashik and Surat.

USAGE OF SOCIAL MEDIA - HOW OFTEN DO YOU USE

SOCIAL NETWORKING SITES LIKE FACE-BOOK,

TWITTER, LINKEDIN Total

4-5 2-3

DAYS DAY ONC

ALMOST / S A E A ALMOST

EVERYDA WEE WEE WEE RAREL NEVE EVERYDA

Y K K K Y R Y

PLAC MUMB Coun 291 116 47 28 16 18 516 E AI t

% of 22.9% 9.1% 3.7% 2.2% 1.3% 1.4% 40.6% Total

SURAT Coun 244 97 25 13 7 11 397 t

% of 19.2% 7.6% 2.0% 1.0% .6% .9% 31.2% Total

NASHIK Coun 172 79 27 24 23 34 359 t

% of 13.5% 6.2% 2.1% 1.9% 1.8% 2.7% 28.2% Total

Total Coun 707 292 99 65 46 63 1272 t

% of 55.6% 23.0% 7.8% 5.1% 3.6% 5.0% 100.0% Total

Mumbai

It was found that out of total 516 respondents, 291 agreed that they used social networking sites like Face book, Twitter, LinkedIn almost every day and 16 agreed that they used rarely.

152

Surat

It was found that out of total 397 respondents, 244 agreed that they used

social networking sites like Face book, Twitter, LinkedIn almost every day

and 7 agreed that they used rarely.

Nashik

It was found that out of total 359 respondents, 172 agreed that they used

social networking sites like Face book, Twitter, LinkedIn almost every day

and 23 agreed that they used rarely.

4. ROUGHLY HOW MUCH TIME DO YOU SPEND EACH TIME YOU

ACCESS THESE SOCIAL NETWORKING SITES - FACE BOOK –

Table 7.1.4. Showing the time the young working women spend each time

they access Facebook in Mumbai, Nashik and Surat.

ROUGHLY HOW MUCH TIME DO YOU SPEND

EACH TIME YOU ACCESS THESE SOCIAL

NETWORKING SITES - FACE BOOK Total

THAN 2

15 MIN. 30 MIN. HOUR HOURS HOURS

PLACE MUMBAI Count 159 111 127 80 39 516

% of Total 12.5% 8.7% 10.0% 6.3% 3.1% 40.6%

SURAT Count 125 82 109 60 21 397

% of Total 9.8% 6.4% 8.6% 4.7% 1.7% 31.2%

NASHIK Count 107 84 78 68 22 359

% of Total 8.4% 6.6% 6.1% 5.3% 1.7% 28.2%

Total Count 391 277 314 208 82 1272

% of Total 30.7% 21.8% 24.7% 16.4% 6.4% 100.0%

153

Mumbai

It was found that out of total 516 respondents, 159 spent 15 min of their time

on the social networking site Face book and 39 spent more than 2 hours.

Surat

It was found that out of total 397 respondents, 125 spent 15 min of their time

on the social networking site Face book and 21 spent more than 2 hours.

Nashik

It was found that out of total 359 respondents, 107 spent 15 min of their time

on the social networking site Face book and 22 spent more than 2 hours.

5. Do you share your opinion about a particular product or service with

your family or friends by writing reviews or blogs?

Table 7.1.5. Showing whether the young working women share their

opinion about a particular product or service with your family or friends

by writing reviews or blogs in Mumbai, Nashik and Surat.

Do you share your opinion about a

particular product or service with your

family or friends by writing reviews or

blogs? Total

Yes No

PLACE MUMBAI Count 285 231 516

% of Total 22.4% 18.2% 40.6%

SURAT Count 241 156 397

% of Total 18.9% 12.3% 31.2%

NASHIK Count 161 198 359

% of Total 12.7% 15.6% 28.2%

154

Total Count 687 585 1272

% of Total 54.0% 46.0% 100.0%

Mumbai

It was found that out of total 516 respondents, 285 agreed that they shared opinion about a particular product or service with your family or friends by writing reviews or blogs and 231 disagreed.

Surat

It was found that out of total 397 respondents, 241 agreed that they shared opinion about a particular product or service with your family or friends by writing reviews or blogs and 156 disagreed.

Nashik

It was found that out of total 359 respondents, 161 agreed that they shared opinion about a particular product or service with your family or friends by writing reviews or blogs and 198 disagreed.

155

6. How many times have you provided online rating in one year? –

Table 7.1.6. Showing the number of times the young working women

provided online rating in one year in Mumbai, Nashik and Surat.

How many times have you provided online rating in

one year? Total

over

none/don’t up to 10 11-20 21-50 50

rate times times times times

PLACE MUMBAI Count 259 212 35 8 2 516

% of Total 20.4% 16.7% 2.8% .6% .2% 40.6%

SURAT Count 265 119 6 3 4 397

% of Total 20.8% 9.4% .5% .2% .3% 31.2%

NASHIK Count 188 123 23 10 15 359

% of Total 14.8% 9.7% 1.8% .8% 1.2% 28.2%

Total Count 712 454 64 21 21 1272

% of Total 56.0% 35.7% 5.0% 1.7% 1.7% 100.0%

Mumbai

It was found that out of total 516 respondents, 2 said that they provided online

rating in one year over 50 times and 259 did not rate.

Surat

It was found that out of total 397 respondents, 4 said that they provided online

rating in one year over 50 times and 265 did not rate.

Nashik

156

It was found that out of total 359 respondents, 15 said that they provided online rating in one year over 50 times and 188 did not rate.

Objective 2 – To study the Different types of buying behaviour with respect to Social Media Advertising in different cities –

(I)To study the customer buying behaviour with respect to Social Media

Advertising in different cities – a) Relationship between consumer buying behaviour with the factor of

Social Media Advertisement i.e. “On social media do you have positive

reactions/feelings towards advertisements displayed on it” in different

cities –

(i) In Mumbai -

H0a :There is no association between the factor i.e. “On social media do

you have positive reactions/feelings towards advertisements displayed on

it” with Consumer buying behaviour of young working women for

consumer electronics in Mumbai.

H1a : There is association between the factor i.e. “On social media do

you have positive reactions/feelings towards advertisements displayed on

it” with Consumer buying behaviour of young working women for

consumer electronics in Mumbai

157

Chi-Square Tests

Table 7.2.1.1.m.a. Relationship between consumer buying behaviour

with the factor of social media advertisement i.e positive

reactions/feelings towards advertisements displayed on SNS in

Mumbai.

Asymp. Sig. (2-

Value Df sided)

Pearson Chi-Square 37.289(a) 8 .000

Likelihood Ratio 38.494 8 .000

Linear-by-Linear 16.218 1 .000 Association

N of Valid Cases 516

From the above table, it is observed that at 5 % level of significance p < α

(0.05), so the null hypothesis is rejected and alternative is accepted, so, we conclude that there is association between the factor i.e. “On social media do you have positive reactions/feelings towards advertisements displayed on it” with Consumer buying behaviour of young working women for consumer electronics in Mumbai. This means the factor i.e. “On social media do you have positive reactions/feelings towards advertisements displayed on it” with

Consumer buying behaviour of young working women in Mumbai for consumer electronics are dependent of each other. Further to check how

158 much association is existing between them we will use the Contingency

Coefficient Statistics.

Symmetric Measures

Table 7.2.1.1.m.b. Table of Symmetric Measures to show how much

relationship exists in between consumer buying behaviour and the

factor of social media advertising i.e positive reactions/feelings towards

advertisements displayed on SNS in Mumbai.

Approx.

Value Sig.

Nominal by Nominal Contingency .760 .000 Coefficient

N of Valid Cases 516

From the above table, it is observed that there is strong positive

reactions/feelings of young working women in Mumbai towards

advertisements displayed on social media for buying electronics products,

which will affect consumer buying behaviour by 76.0 %.

(ii)In Nashik -

H 0b :There is no association between the factor i.e. “On social media do

you have positive reactions/feelings towards advertisements displayed on

it” with Consumer buying behaviour of young working women for

consumer electronics in Nashik.

159

H1b : There is association between the factor i.e. “On social media do you have positive reactions/feelings towards advertisements displayed on it” with Consumer buying behaviour of young working women for consumer electronics in Nashik.

Chi-Square Tests

Table 7.2.1.1.n.a. Relationship between consumer buying behaviour with the factor of social media advertisement i.e positive reactions/feelings towards advertisements displayed on SNS in

Nashik.

Value Df Asymp. Sig. (2-sided)

Pearson Chi-Square 47.467(a) 3 .000

Likelihood Ratio 51.331 3 .000

Linear-by-Linear 19.337 1 .000 Association

N of Valid Cases 359

From the above table, it is observed that at 5 % level of significance p < α

(0.05), so the null hypothesis is rejected and alternative is accepted.

Therefore, we conclude that there is association between the factor i.e.

“On social media do you have positive reactions/feelings towards advertisements displayed on it” with Consumer buying behaviour of young working women for consumer electronics in Nashik. This means the factor i.e. “On social media do you have positive reactions/feelings towards advertisements displayed on it” with Consumer buying

160

behaviour of young working women in Nashik for consumer electronics

are dependent of each other. Further to check how much association

exists between them, we will use the Contingency Coefficient Statistics.

Symmetric Measures

Table 7.2.1.1.n.b. Table of Symmetric Measures to determine how

much relationship exists in between consumer buying behaviour and

the factor of social media advertising i.e positive reactions/feelings

towards advertisements displayed on SNS in Nashik.

Value Approx. Sig.

Nominal by Contingency .642 .000 Nominal Coefficient

N of Valid Cases 359

From the above table, it is observed that young working women in Nashik

are having very strong positive reactions /feelings towards advertisements

displayed on social media for buying electronics products which will affect

consumer buying behaviour by 64.2 %.

(iii) In Surat -

H0c : There is no association between the factor i.e. “On social media do

you have positive reactions/feelings towards advertisements displayed on

it” with Consumer buying behaviour of young working women for

consumer electronics in Surat.

H1c : There is association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it”

161

with Consumer buying behaviour of young working women for

consumer electronics in Surat

Chi-Square Tests

Table 7.2.1.1.s.a. Relationship between consumer buying behaviour

with the factor of social media advertisement i.e positive

reactions/feelings towards advertisements displayed on SNS in Surat.

Value Df Asymp. Sig. (2-sided)

Pearson Chi-Square 48.567(a) 3 .077

Likelihood Ratio 46.110 3 .000

Linear-by-Linear 10.219 1 .001 Association

N of Valid Cases 397

From the above table, it is observed that at 5 % level of significance p > α

(0.05), so the null hypothesis is accepted and alternative is rejected, so, we

conclude that there is no association between the factor i.e. “On social

media do you have positive reactions/feelings towards advertisements

displayed on it” with Consumer buying behaviour of young working

women for consumer electronics in Surat. This means the factor i.e. “On

social media do you have positive reactions/feelings towards

advertisements displayed on it” with Consumer buying behaviour of young

working women in Surat for consumer electronics are independent of each

other. So we can say that they do not have positive reactions/feelings

162

towards advertisements displayed on social media and there is no

association of the factor “On social media do you have positive

reactions/feelings towards advertisements displayed on it” with buying

behaviour of young working women in Surat for consumer electronics

which will not affect consumer buying behaviour.

In the same manner Relationship between consumer buying behaviour

with the various other factors of Social Media Advertisement like

appealing nature, memorable visuals and slogans, attractiveness and

trustworthiness has been studied one by one in different cities – Mumbai,

Nashik and Surat and the same can be referred in the Annexure.

(II)To study the online purchase behaviour with respect to Social Media

Advertising in different cities - a) Relationship between online purchase behaviour with the factor of Social

Media Advertisement i.e. “On social media do you have positive

reactions/feelings towards advertisements displayed on it” in different cities

–

(i) In Mumbai -

H0a : There is no association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it”

with online purchase behavior of young working women for consumer

electronics in Mumbai.

H1a : There is association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it”

163

with online purchase behavior of young working women for consumer

electronics in Mumbai

Chi-Square Tests

Table 7.2.2.1.m.a. Relationship between online purchase behaviour

with the factor of social media advertising i.e positive reactions/feelings

towards the advertisements displayed on SNS in Mumbai.

Value Df Asymp. Sig. (2-sided)

Pearson Chi-Square 53.365(a) 36 .031

Likelihood Ratio 48.137 36 .085

Linear-by-Linear .002 1 .964 Association

N of Valid Cases 516

From the above table, it is observed that at 5 % level of significance p > α

(0.05), so the null hypothesis is accepted and alternative is rejected and

therefore, we conclude that there is no association between the factor i.e.

“On social media do you have positive reactions/feelings towards

advertisements displayed on it” with online purchase behaviour of young

working women for consumer electronics in Mumbai. This means the factor

i.e. “On social media do you have positive reactions/feelings towards

advertisements displayed on it” with online purchase behaviour of young

working women in Mumbai for consumer electronics are independent of

each other. So, we can conclude that young working women in Mumbai do

not have positive reactions/feelings towards advertisements displayed on it.

164

So, it will not affect the online purchase behaviour of young working

women in Mumbai.

(ii) In Nashik -

H0b : There is no association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it”

with online purchase behaviour of young working women for consumer

electronics in Nashik

H1b : There is association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it”

with online purchase behaviour of young working women for consumer

electronics in Nashik

Chi-Square Tests

Table 7.2.2.1.n.a. Relationship between online purchase behaviour with

the factor of social media advertising i.e positive reactions/feelings

towards the advertisements displayed on SNS in Nashik.

Value Df Asymp. Sig. (2-sided)

Pearson Chi-Square 147.224(a) 24 .000

Likelihood Ratio 136.279 24 .000

Linear-by-Linear 13.059 1 .000 Association

N of Valid Cases 359

165

From the above table, it is observed that at 5 % level of significance p < α

(0.05), so the null hypothesis is rejected and alternative is accepted, therefore, we conclude that there is association between the factor i.e. “On social media do you have positive reactions/feelings towards advertisements displayed on it” with online purchase behaviour of young working women for consumer electronics in Nashik. This means the factor i.e. “On social media do you have positive reactions/feelings towards advertisements displayed on it” with online purchase behaviour of young working women in

Nashik for consumer electronics are dependent of each other. Further to check how much association exists the Contingency Coefficient Statistics is used.

Symmetric Measures

Table 7.2.2.1.n.b. Table of Symmetric Measures to determine how much

relationship exists in between online purchase behaviour and factor of

social media advertising i.e positive reactions/feelings towards the

advertisements displayed on SNS in Nashik.

Approx.

Value Sig.

Nominal by Nominal Contingency .639 .000 Coefficient

N of Valid Cases 359

From the above table, it is observed that they are having very strong positive

/feelings of young working women in Nashik towards advertisements

166

displayed on social media for buying electronics products, which will affect

online purchase behaviour by 63.9 %.

(iii) In Surat -

H0c : There is no association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it” with

online purchase behavior of young working women for consumer electronics

in Surat.

H1c : There is association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it” with

online purchase behaviour of young working women for consumer

electronics in Surat.

Chi-Square Tests

Table 7.2.2.1.s.a. Relationship between online purchase behaviour with

the factor of social media advertising i.e positive reactions/feelings

towards the advertisements displayed on SNS in Surat.

Asymp. Sig.

Value Df (2-sided)

Pearson Chi-Square 83.531(a) 24 .000

Likelihood Ratio 79.912 24 .000

Linear-by-Linear 2.814 1 .093 Association

N of Valid Cases 397

From the above table, it is observed that at 5 % level of significance p < α

167

(0.05), so the null hypothesis is rejected and alternative is accepted, so, we

conclude that there is association between the factor i.e. “On social media do

you have positive reactions/feelings towards advertisements displayed on it”

with online purchase behaviour of young working women for consumer

electronics in Surat. This means the factor i.e. “On social media do you have

positive reactions/feelings towards advertisements displayed on it” with

online purchase behaviour of young working women in Surat for consumer

electronics are dependent of each other. Further to check how much

association is existing we will use the Contingency Coefficient Statistics.

Symmetric Measures

Table 7.2.2.1.s.b. Table of Symmetric Measures to determine how much

relationship exists in between online purchase behaviour and factor of

social media advertising i.e positive reactions/feelings towards the

advertisements displayed on SNS in Surat.

Approx.

Value Sig.

Nominal by Nominal Contingency .617 .000 Coefficient

N of Valid Cases 397

From the above table, it is observed that they are having very strong positive

reactions /feelings of young working women in Surat towards advertisements

displayed on social media for buying electronics products, which will affect

online purchase behaviour by 61.7 %.

In the same manner Relationship between online purchase behaviour with the

168

various other factors of Social Media Advertisement like appealing nature,

memorable visuals and slogans, attractiveness and trustworthiness has been

studied one by one in different cities – Mumbai, Nashik and Surat and the

same can be referred in the Annexure.

(III) Relationship between complex buying behaviour with the factor of Social

Media Advertisement i.e. “On social media do you have positive

reactions/feelings towards advertisements displayed on it” in different cities

–

i. In Mumbai -

H0a :There is no association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it” with

Complex buying behaviour of young working women for consumer

electronics in Mumbai.

H1a : There is association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it” with

Complex buying behaviour of young working women for consumer

electronics in Mumbai

Chi-Square Tests

Table 7.2.3.1.m.a. Relationship between complex buying behaviour with

the factor i.e. “positive reactions/feelings towards advertisements

displayed on it” of social media advertising in Mumbai.

Value Df Asymp. Sig. (2-sided)

Pearson Chi-Square 134.020(a) 48 .000

169

Likelihood Ratio 103.374 48 .000

Linear-by-Linear 19.801 1 .000 Association

N of Valid Cases 516

From the above table, it is observed that at 5 % level of significance p < α

(0.05), so the null hypothesis is rejected and alternative is accepted, so, we

conclude that there is association between the factor i.e. “On social media do

you have positive reactions/feelings towards advertisements displayed on it”

with Complex buying behaviour of young working women for consumer

electronics in Mumbai. This means the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it” with

Complex buying behaviour of young working women in Mumbai for

consumer electronics are dependent of each other. Further to check how

much association exists we will use the Phi & Cramer’s V Statistics.

Symmetric Measures

Table 7.2.3.1.m.b. Table of Symmetric Measures to determine how

much relationship exists between complex buying behaviour and the

factor i.e. “positive reactions/feelings towards advertisements displayed

on it” of social media advertising in Mumbai.

Value Approx. Sig.

Nominal Phi & by Cramer's V .610 .000

Nominal

170

N of Valid Cases 516

From the above table, it is observed that they are having very strong positive

reactions /feelings of young working women in Mumbai towards

advertisements displayed on social media for buying electronics products,

which will affect Complex buying behaviour by 61.0 %. ii. In Nashik -

H0b : There is no association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it” with

Complex buying behaviour of young working women for consumer

electronics in Nashik

H1b : There is association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it” with

Complex buying behaviour of young working women for consumer

electronics in Nashik

Chi-Square Tests

Table 7.2.3.1.n.a. Relationship between complex buying behaviour with

the factor i.e. “positive reactions/feelings towards advertisements

displayed on it” of social media advertising in Nashik.

Asymp. Value Sig. (2-

Df sided)

Pearson Chi-Square 179.455(a) 36 .000

Likelihood Ratio 186.883 36 .000

Linear-by-Linear 17.965 1 .000

171

Association

N of Valid Cases 359

From the above table, it is observed that at 5 % level of significance p < α

(0.05), so the null hypothesis is rejected and alternative is accepted, so, we conclude that there is association between the factor i.e. “On social media do you have positive reactions/feelings towards advertisements displayed on it” with Complex buying behaviour of young working women for consumer electronics in Nashik. This means the factor i.e. “On social media do you have positive reactions/feelings towards advertisements displayed on it” with

Complex buying behaviour of young working women in Nashik for consumer electronics because they are dependent of each other for. Further to check how much association is exist we will use the Phi & Cramer’s V

Statistics.

Symmetric Measures

Table 7.2.3.1.n.b. Table of Symmetric Measures to determine how much relationship exists between complex buying behaviour and the factor i.e.

“positive reactions/feelings towards advertisements displayed on it” of social media advertising in Nashik.

Value Approx. Sig.

Nominal Phi &

by Cramer's V .707 .000

Nominal

N of Valid Cases 359

172

From the above table, it is observed that there are having very strong positive

/feelings of young working women in Nashik towards advertisements

displayed on social media for buying electronics products, which will affect

Complex buying behaviour 70.7 %. iii. In Surat -

H0c : There is no association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it” with

Complex buying behaviour of young working women for consumer

electronics in Surat

H1c : There is association between the factor i.e. “On social media do you

have positive reactions/feelings towards advertisements displayed on it” with

Complex buying behaviour of young working women for consumer

electronics in Surat

Chi-Square Tests

Table 7.2.3.1.s.a. Relationship between complex buying behaviour with

the factor i.e. “positive reactions/feelings towards advertisements

displayed on it” of social media advertising in Surat.

Value Df Asymp. Sig. (2-sided)

Pearson Chi- 133.482(a) 36 .000 Square

Likelihood Ratio 116.736 36 .000

173

Linear-by-Linear 21.778 1 .000 Association

N of Valid Cases 397

From the above table, it is observed at 5 % level of significance p < α (0.05), so the null hypothesis rejected and alternative is accepted, so, we conclude that there is association between the factor i.e. “On social media do you have positive reactions/feelings towards advertisements displayed on it” with

Complex buying behaviour of young working women for consumer electronics in Surat. This means the factor i.e. “On social media do you have positive reactions/feelings towards advertisements displayed on it” with

Complex buying behaviour of young working women in Surat for consumer electronics because they are dependent of each other for. Further to check how much association is exist we will use the Phi & Cramer’s V Statistics.

Symmetric Measures

Table 7.2.3.1.s.b. Table of Symmetric Measures to determine how much

relationship exists between complex buying behaviour with the factor

i.e. “positive reactions/feelings towards advertisements displayed on it”

of social media advertising in Surat.

Value Approx. Sig.

Nominal by Phi & .658 .000 Nominal Cramer's V

N of Valid Cases 397

174

From the above table, it is observed that there are very strong positive

reactions/feelings of young working women in Nashik towards

advertisements displayed on social media for buying electronics products,

which will affect Complex buying behaviour 65.8 %.

In the same manner relationship between complex buying behaviour and

various other factors of social media advertisement like appealing nature,

memorable visuals and slogans, attractiveness and trustworthiness has been

studied one by one in different cities - Mumbai, Nashik and Surat and the

same can be referred in the Annexure.

IV) Relationship between all the factors of Habitual Buying Behaviour with all

the factor of Social Media Advertisement in different cities –

(i) In Mumbai –

H0a : All the factors of Social Media Advertisement and all the factors of

Habitual Buying Behaviour of young working women for consumer

electronics in Mumbai are independent of each other.

H1a : All the factors of Social Media Advertisement and all the factors of

Habitual Buying Behaviour of young working women for consumer

electronics in Mumbai are dependent of each other.

ANOVA

Table 7.2.4.1.m. showing relationship between all the factors of habitual

buying behaviour and all the factors of social media advertising in

175

Mumbai.

Sum of

Squares Df Mean Square F Sig.

Between Groups .595 6 .099 1.535 .165

Within Groups 32.869 509 .065

Total 33.464 515

From the above table, it is observed that p > α (0.05), so the null hypothesis is

accepted and alternative is rejected, so we can conclude that all the factors of

Social Media Advertisement and all the factors of Habitual Buying Behaviour

of young working women for consumer electronics in Mumbai are

independent of each other. So, we can say that social media advertisement

does not have any impact on Habitual Buying Behaviour of the young

working women in Mumbai.

(ii) In Nashik –

H0b : All the factors of Social Media Advertisement and all the factors of

Habitual Buying Behaviour of young working women for consumer

electronics in Nashik are independent of each other

H1b : All the factors of Social Media Advertisement and all the factors of

Habitual Buying Behaviour of young working women for consumer

electronics in Nashik are dependent of each other

ANOVA

Table 7.2.4.1.n. showing relationship between all the factors of habitual

buying behaviour and all the factors of social media advertising in

176

Nashik.

Sum of Mean

Squares Df Square F Sig.

Between Groups 51.632 17 3.037 11.927 .000

Within Groups 86.836 341 .255

Total 138.468 358

From the above table, it is observed that p < α (0.05), so the null hypothesis

is rejected and alternative is accepted, so we can conclude that all the factors

of Social Media Advertisement and all the factors of Habitual Buying

Behaviour of young working women for consumer electronics in Nashik are

dependent of each other. So, we can say that social media advertisements are

having impact on Habitual Buying Behaviour of the young working women

in Nashik.

(iii) In Surat –

H0c : All the factors of Social Media Advertisement and all the factors of

Habitual Buying Behaviour of young working women for consumer

electronics in Surat are independent of each other.

H1c : All the factors of Social Media Advertisement and all the factors of

Habitual Buying Behaviour of young working women for consumer

electronics in Surat are dependent of each other.

ANOVA

Table 7.2.4.1.s. showing relationship between all the factors of habitual

177

buying behaviour and all the factors of social media advertising in

Surat.

Sum of

Squares Df Mean Square F Sig.

Between Groups 1.554 6 .259 10.677 .000

Within Groups 9.460 390 .024

Total 11.014 396

From the above table, it is observed that p < α (0.05), so the null hypothesis is

rejected and alternative is accepted, so we can conclude that all the factors of

Social Media Advertisement and all the factors of Habitual Buying Behaviour

of young working women for consumer electronics in Surat are dependent of

each other. So, we can say that social media advertisements are having impact

on Habitual Buying Behaviour of the young working women in Surat.

In the same manner Relationship between all the factors of Social Media

Advertisements and all the factors of various consumer buying behaviours

like variety seeking buying behaviour, dissonance buying behaviour and

impulsive buying behaviours has been studied one by one in different cities –

Mumbai, Nashik and Surat and the same can be referred in the Annexure.

Objective 3 – To Study the impact of social media advertising on the

buying behaviour of young working women for consumer electronics in

all the cities – a) Impact of Social Media advertising on different factors of buying behaviour

of young working women for consumer electronics in Mumbai –

In the model, the dependent variable Y is Social Media Advertising whereas

178 independent variables X1, X2 ,...... , Xn are all buying Behaviours of young working women i.e. Online purchase behaviour, Consumer Buying

Behaviour, Complex Buying Behaviour, Habitual Buying Behaviour, Variety-

Seeking Buying Behaviour, Dissonance Buying Behaviour and Impulsive

Buying Behaviour. The estimated regression model is as follows:

Y (Social Media Advertising) = 1. 421+ (-0.045) Online purchase behaviour

+ (0.013) Consumer Buying Behaviour + (0.64) Complex Buying Behaviour

+ (-0.022) Habitual Buying Behaviour + (0.047) Variety-Seeking Buying

Behaviour + (0.038) Dissonance Buying Behaviour + (0.004) Impulsive

Buying Behaviour.

The results indicate that all the independent variables namely consumer buying behaviour, complex buying behaviour, variety-seeking buying behaviour, dissonance buying behaviour and impulsive buying behaviour have a positive impact on the Social Media Advertising. The independent variables namely Online purchase behaviour and Habitual Buying Behaviour have a negative impact on Social Media Advertising.

Model Summary

Table 7.3.1.m.a. Table of Model Summary for Mumbai

Adjusted R Std. Error of the

Model R R Square Square Estimate

1 .859(a) .737 .619 .68557

From the above it is observed, The R2 value for the model is 0.737 which indicates that 73.7 % of the variations in the Social Media Advertising are explained by Online purchase Behaviour, Consumer Buying Behaviour,

179

Complex Buying Behaviour, Habitual Buying Behaviour, Variety-Seeking

Buying Behaviour, Dissonance Buying Behaviour and Impulsive Buying

Behaviour. The significance of R2 is tested with the help of F statistic, which is shown in below table,

2 H0a : R is not statistically significant

2 H1a : R is statistically significant

ANOVA(b)

Table 7.3.1.m.b. Table for Anova to determine the level of significance of

Sum of Mean

Model Squares Df Square F Sig.

1 Regression 2.600 6 .433 12.584 .000(a)

Residual 17.529 509 .034

Total 20.129 515

From the above table it is observed that the , the p < (0.05) , so we reject null hypothesis and alternative hypothesis is accepted, so we conclude that that at

5% level of significance R2 is statistically significant .

The significance of the individual coefficients can be tested using t-statistic,

There is no significant impact of social media advertising on young working women’s buying behaviour in Mumbai.

There is significant impact of social media advertising on young working women’s buying behaviour in Mumbai.

180

Coefficients (a)

Table 7.3.1.m.c. Table for significance of Coefficients

Unstandardized Standardized

Model Coefficients Coefficients T Sig.

Std. Std.

B Error Beta B Error

1 (Constant) 1.421 .049 28.830 .000

Online

purchase -.045 .023 -.092 -1.947 .052

behaviour

Consumer

Buying 0.013 .088 0.044 -1.234 0.04

Behaviour

Complex

Buying .064 .012 .276 5.282 .000

Behaviour

Habitual -.022 .017 -.062 -1.272 .204 Buying

181

Behaviour

Variety

Seeking .047 .017 .139 2.780 .006 Buying

Behaviour

Dissonance

Buying .038 .015 .113 2.465 .014

Behaviour

Impulsive

Buying .004 .014 .013 .291 .771

Behaviour

From the above table at 5 % level of significance p > α (0.05), so the null hypothesis is accepted and alternative is rejected, so the coefficients of

Habitual, online purchase behaviour and Impulsive buying behaviour is not statistically significant. But the coefficients of Consumer Buying Behaviour,

Complex buying behaviour, Variety - Seeking buying behaviour, Dissonance buying behaviour is statistically significant. Therefore, we conclude that

Consumer Buying Behaviour, Complex buying behaviour, Variety - Seeking buying behaviour, Dissonance buying behaviour has a significant impact on influencing social media advertising amongst young working women in

Mumbai.

In the same manner impact of Social Media Advertising on different factors of buying behaviour of young working women for consumer electronics in

Nashik and Surat has been studied one by one and the same can be referred

182

to in the Annexure.

Objective 4 – To Study the effectiveness of social media tools like Face

book, Twitter , LinkedIn on the consumer Behaviour in different cities –

a) Effectiveness of social media tools like Face book, Twitter , LinkedIn on

the consumer Behaviour in Mumbai –

(i) Rank Order – Audience –

Table 7.4.m.1. Showing effectiveness of SNSs in terms of Audience in

Mumbai

Tota

Rank 1 2 3 4 5 6 7 8 9 10 l

Face 3726 31 19 15 20 25 33 81 106 66 120 book

20 19 28 45 74 75 102 62 54 37 3208 Twitter

LinkedI 3246 29 30 25 47 63 54 63 92 52 61 n

From the above table it was found that as an audience the young working

women prefer most Face book and least preferred is prefer Twitter as the

Social networking sites that have a large number of groups (networks)

available for any demographics you are looking for; for instance group of

teenagers, group of kids, youth, group of new moms, brides, sports fans,

technology enthusiasts, entrepreneurs etc in Mumbai.

(ii) Rank Order – Targeting –

183

Table 7.4.m.2. Showing effectiveness of SNSs in terms of Targeting

consumers in Mumbai.

Rank 1 2 3 4 5 6 7 8 9 10 Total

Face 3670 35 16 13 24 34 37 72 98 82 105 book

25 41 37 64 58 63 63 75 36 54 3047 Twitter

56 56 31 38 42 59 70 59 48 57 2941 LinkedIn

From the above table it was found that as an audience the young working

women in Mumbai prefer most Face book and least preferred is twitter as the

Social networking site that targets the advertisements to specific group of

audience in Mumbai.

(iii)Social Networking Site having more followers due to acquaintances (i.e.

friends and relatives) -

Table 7.4.m.3. Showing effectiveness of SNSs in terms of more followers

due to acquaintances in Mumbai.

184

Cumulative

Frequency Percent Valid Percent Percent

Valid Face book 430 83.3 83.3 83.3

Twitter 50 9.7 9.7 93.0

LinkedIn 36 7.0 7.0 100.0

Total 516 100.0 100.0

Out of the total 516 valid respondents, a maximum of 83.3 % agreed that

Face book more followers due to acquaintances and the minimum of 7.0 %

respondents said that LinkedIn has more followers due to acquaintance.

(iv) Social Networking Site having more unknown followers -

Table 7.4.m.4. Showing effectiveness of SNSs in terms of more unknown

followers in Mumbai.

Cumulative

Frequency Percent Valid Percent Percent

Valid Face book 258 50.0 50.0 50.0

Twitter 140 27.1 27.1 77.1

LinkedIn 118 22.9 22.9 100.0

Total 516 100.0 100.0

Out of the total 516 respondents, a maximum percentage of 50.0 % said that

face book has more unknown followers and minimum of 22.9 % said that

LinkedIn has more unknown followers.

In the same manner effectiveness of social media tools like Face book,

185

Twitter , LinkedIn on the consumer Behaviour for consumer electronics in

Nashik and Surat are studied one by one and the same can be referred to in

the Annexure.

In the same manner effectiveness of social media tools like Face book,

Twitter , LinkedIn on the consumer Behaviour of young working women for

consumer electronics in Nashik and Surat has been studied one by one and

the same can be referred to in the Annexure.

Objective 5- To study the impact of social media advertising on people

belonging to different demographic factors such as qualification, annual

income, occupation and place –

(I) Relationship between impact of social media advertising of young working

women with their qualification in different cities –

(a) In Mumbai –

H0a : Impact of social media advertising and the qualification of young

working women in Mumbai are independent of each other

H1a : Impact of social media advertising and the qualification of young

working women in Mumbai are dependent of each other

ANOVA

Table 7.5.I.m. Relationship between qualification of young working

women and impact of social media advertising in Mumbai .

Sum of Squares Df Mean Square F Sig.

186

Between Groups .085 2 .043 1.088 .338

Within Groups 20.044 513 .039

Total 20.129 515

From the above table, it is observed that p > α (0.05), so the null hypothesis is

accepted and alternative is rejected, so we can conclude that impact of social

media advertising and the qualification of young working women in Mumbai

are independent of each other. So, we can say that qualification of the young

working women in Mumbai has no effect on the impact of social media

advertising on young working woman’s buying behaviour in Mumbai.

In the same manner Relationship between impact of social media advertising

and the qualification of young working women in other cities like Nashik and

Surat has been studied one by one and the same can be referred to in the

Annexure.

(II) Relationship between impact of social media advertising of young working

women with their Annual Income in different cities –

(c)In Surat –

H0c : Impact of social media advertising and the Annual Income of young

working women in Surat are independent of each other

H1c : Impact of social media advertising and the Annual Income of young

working women in Surat are dependent of each other

ANOVA

Table 7.5.II.s.a. Relationship between annual income of young working

women and impact of social media advertising in Surat.

187

Sum of Squares Df Mean Square F Sig.

Between Groups 1.517 3 .506 21.306 .000

Within Groups 9.324 393 .024

Total 10.841 396

From the above table, it is observed that p < α (0.05), so the null hypothesis is rejected and the alternative is accepted, so we can conclude that impact of social media advertising and the Annual Income of young working women in

Surat are dependent of each other. So, we can say that social media advertisement has an impact on Annual Income of the young working women in Surat. So, which Annual Income group has more or less impact we can refer descriptive statistics table which is given below:

Descriptive

Table 7.5.II.s.b. To determine how much relationship exists between annual income of young working women and impact of social media advertising in Surat.

N Mean Std. Deviation

UPTO RS. 3 LAKHS 179 1.6752 .11972

3.1- 5 LAKHS 132 1.6535 .16214

5.1-10 LAKHS 64 1.5156 .18411

ABOVE 10 LAKHS 22 1.5242 .23842

Total 397 1.6339 .16546

From the above table, we observed that income group i.e. upto Rs. 3 lakhs earning of young working women are having more impact of social media advertising on buying behaviour followed by other income groups i.e. 3.1- 5, above 10 lakhs and 5.1 – 10 lakhs respectively.

188

In the same manner Relationship between impact of social media advertising

and the Annual Income of young working women in other cities like Mumbai

and Nashik has been studied one by one and the same can be referred to in

the Annexure.

(III) Relationship between impact of social media advertising of young working

women and their Occupation in different cities –

(b) In Nashik –

H0b : Impact of social media advertising and the Occupation of young

working women in Nashik are independent of each other

H1b : Impact of social media advertising and the Occupation of young

working women in Nashik are dependent of each other

ANOVA

Table 7.5.III.n.a. Relationship between occupation of young working

women and impact of social media advertising in Nashik.

Sum of Squares Df Mean Square F Sig.

Between Groups .280 2 .140 3.049 .049

Within Groups 16.342 356 .046

Total 16.622 358

From the above table, it is observed that p < α (0.05), so the null hypothesis is

rejected and alternative is accepted, so we can conclude that impact of social

media advertising and the Occupation of young working women in Nashik

are dependent of each other. So, we can say that social media advertisement

189 has an impact on Occupation of the young working women in Nashik. So, which Occupation group has more or less impact we can refer descriptive statistics table which is given below:

Descriptive

Table 7.5.III.n.b. To determine how much relationship exists between occupation of young working women and impact of social media advertising in Nashik.

N Mean Std. Deviation

SERVICE 283 1.6641 .21898

BUISNESS 55 1.7418 .20207

SELF- EMPLOYED PROFESSION 21 1.6857 .17530

Total 359 1.6773 .21548

From the above table, we observed that business class working women are having more impact of social media advertising on buying behaviour followed by service and self – employed professionals.

In the same manner Relationship between impact of social media advertising and the Occupation of young working women in other cities like Mumbai and

Surat has been studied one by one and the same can be referred to in the

Annexure.

190

7.2 Summary of the Analysis

7.6 Tabular representation of Summary of Analysis and results.

S. Objecti Hypothes Questionnaire Statis P- Result No ve is tical Va s of Sect Question Nos. . Test lue Testin ion Used g of Hypot hesis 1. To Nil Sect 1,2,3,4,5,6,7,8,9,1 Nil Nil Threw ion 0,11,12,13,14. light identify II on the Patter n of Social Social Media Media Usage Usage in 3 by differe nt young cities. workin g women in differe nt cities.

2. To 1. H0: Consumer buying Chi- 0.0 H0 behaviour / Squar 00 Reject study There is no Sect Section XI (1.A.) e test ed. ion

191 the associatio XI custom n between the factor ers i.e. buying positive behavi reactions/ feelings our towards with advertise respect ments displayed to with Social Consumer media buying adverti behaviour in sing. Mumbai.

2. H0: Consumer buying Chi- 0.0 H0 There is behaviour / Squar 00 Reject no Sect Section XI(1.A.) e test ed. ion associatio XI n between the factor i.e. positive reactions/ feelings towards advertise ments displayed with Consumer buying behaviour in Nashik.

3. H0: Consumer buying Chi- 0.0 H0 is There is behaviour / Squar 77 Accep no Sect Section XI (1.A.) e test ted. ion associatio XI n between the factor i.e.

192 positive reactions/ feelings towards advertise ments displayed with Consumer buying behaviour in Surat

4. H0: Consumer buying Chi- 0.0 H0 is There is behaviour / Squar 00 Reject no Sect Section XI (1.B.) e test ed. ion associatio XI n between the appealing factor of social media advertise ments with Consumer buying behavior in Mumbai.

5. H0: Consumer buying Chi- 0.0 H0 is There is behaviour / Squar 99 Accep no Sect Section XI( e test ted. ion 1.B.) associatio XI n between the appealing factor of social media advertise ments with

193

Consumer buying behavior in Nashik.

6. H0: Consumer buying Chi- 0.7 H0 is There is behaviour / Squar 77 Accep no Sect Section XI ( e test ted. ion 1.B.) associatio XI n between the appealing factor of social media advertise ments with Consumer buying behavior in Surat.

7. H0: Consumer buying Chi- 0.5 H0 is There is behaviour / Squar 66 Accep no Sect Section XI( e test ted. ion 1.C.) associatio XI n between the memorabl e visuals and slogans factor of social media advertise ments with Consumer buying behavior in Mumbai.

8. H0: Consumer buying Chi- 0.7 H0 is

194

There is behaviour / Squar 68 Accep no Sect Section XI( e test ted. associatio ion 1.C.) XI n between the memorabl e visuals and slogans factor of social media advertise ments with Consumer buying behavior in Nashik.

9. H0: Consumer buying Chi- 0.5 H0 is There is behaviour / Squar 66 Accep no Sect Section XI( e test ted. ion 1.C.) associatio XI n between the memorabl e visuals and slogans factor of social media advertise ments with Consumer buying behavior in Surat.

10. H0: Consumer buying Chi- 0.8 H0 is There is behaviour / Squar 11 Accep no Sect Section XI( e test ted. ion 1.D.) associatio

195 n between XI the attractive factor of social media advertise ments with Consumer buying behavior in Mumbai.

11. H0: Consumer buying Chi- 0.7 H0 is There is behaviour / Squar 66 Accep no Sect Section XI( e test ted. ion 1.D.) associatio XI n between the attractive factor of social media advertise ments with Consumer buying behavior in Nashik.

12. H0: Consumer buying Chi- 0.0 H0 is There is behaviour / Squar 0 Reject no Sect Section XI( e test ed. ion 1.D.) associatio XI n between the attractive factor of social media advertise ments

196 with Consumer buying behavior in Surat.

13. H0: Consumer buying Chi- 0.0 H0 is There is behaviour / Squar 89 Accep no Sect Section XI( e test ted. ion 1.E.) associatio XI n between the trustworth iness factor of social media advertise ments with Consumer buying behavior in Mumbai.

14. H0: Consumer buying Chi- 0.4 H0 is There is behaviour / Squar 44 Accep no Sect Section XI( e test ted. ion 1.E.) associatio XI n between the trustworth iness factor of social media advertise ments with Consumer buying behavior in Nashik.

15. H0: Consumer buying Chi- 0.0 H0 is

197

There is behaviour / Squar 00 Reject no Sect Section XI( e test ed. associatio ion 1.E.) XI n between the trustworth iness factor of social media advertise ments with Consumer buying behavior in Surat.

16. H0 : Online purchase Chi- 0.0 H0 is There is behaviour / Squar 31 Accep no Sect Section XI( e test ted. ion 1.A.) associatio XI n between the factor i.e. positive reactions/ feelings towards advertise ments displayed with online purchase behavior in Mumbai.

17. H0 : Online purchase Chi- 0.0 H0 is There is behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.A.) associatio XI n between

198 the factor i.e. positive reactions/ feelings towards advertise ments displayed with online purchase behavior in Nashik.

18. H0 : Online purchase Chi- 0.0 H0 is There is behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.A.) associatio XI n between the factor i.e. positive reactions/ feelings towards advertise ments displayed with online purchase behavior in Surat.

19. H0 : Online purchase Chi- 0.2 H0 is There is behaviour / Squar 52 Accep no Sect Section XI( e test ted. ion 1.B.) associatio XI n between the appealing factor of

199 the advertise ments displayed with online purchase behavior in Mumbai.

20. H0 : Online purchase Chi- 0.0 H0 is There is behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.B.) associatio XI n between the appealing factor of the advertise ments displayed with online purchase behavior in Nashik.

21. H0 : Online purchase Chi- 0.0 H0 is There is behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.B.) associatio XI n between the appealing factor of the advertise ments displayed with online

200 purchase behavior in Surat.

22. H0 : Online purchase Chi- 0.7 H0 is There is behaviour / Squar 96 Accep no Sect Section XI( e test ted. ion 1.C.) associatio XI n between the memorabl e visuals and slogans factor of the advertise ments with online purchase behavior in Mumbai.

23. H0 : Online purchase Chi- 0.0 H0 is There is behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.C.) associatio XI n between the memorabl e visuals and slogans factor of the advertise ments with online purchase behavior

201 in Nashik.

24. H0 : Online purchase Chi- 0.0 H0 is There is behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.C.) associatio XI n between the memorabl e visuals and slogans factor of the advertise ments with online purchase behavior in Surat.

25. H0 : Online purchase Chi- 0.5 H0 is There is behaviour / Squar 24 Accep no Sect Section XI( e test ted. ion 1.D.) associatio XI n between the attractive factor of the advertise ments with online purchase behavior in Mumbai.

26. H0 : Online purchase Chi- 0.0 H0 is There is behaviour / Squar 00 Reject no Sect Section XI (1.D.) e test ed.

202 associatio ion n between XI the attractive factor of the advertise ments with online purchase behavior in Nashik.

27. H0 : Online purchase Chi- 0.0 H0 is There is behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.D.) associatio XI n between the attractive factor of the advertise ments with online purchase behavior in Surat.

28. H0 : Online purchase Chi- 0.1 H0 is There is behaviour / Squar 46 Accep no Sect Section XI( e test ted. ion 1.E.) associatio XI n between the trustworth iness factor of the advertise ments

203 with online purchase behavior in Mumbai.

29. H0 : Online purchase Chi- 0.1 H0 is There is behaviour / Squar 17 Accep no Sect Section XI( e test ted. ion 1.E.) associatio XI n between the trustworth iness factor of the advertise ments with online purchase behavior in Nashik.

30. H0 : Online purchase Chi- 0.6 H0 is There is behaviour / Squar 65 Accep no Sect Section XI( e test ted. ion 1.E.) associatio XI n between the trustworth iness factor of the advertise ments with online purchase behavior in Surat.

204

31. H0: Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.A.) associatio XI n between the factor i.e. positive reactions/ feelings towards advertise ments displayed with Complex buying behaviour in Mumbai.

32. H0 : Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 00 Reject no Sect Section XI( 1.A.) e test ed. ion associatio XI n between the factor i.e. positive reactions/ feelings towards advertise ments displayed with Complex buying behaviour in Nashik.

33. H0 : Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 00 Reject no Sect Section XI( 1.A.) e test ed. ion associatio

205 n between XI the factor i.e. positive reactions/ feelings towards advertise ments displayed with Complex buying behaviour in Surat.

34. H0: Complex Buying Chi- 0.2 H0 is There is Behaviour / Squar 13 Accep no Sect Section XI( e test ted. ion 1.B.) associatio XI n between the appealing factor of the advertise ments displayed with Complex buying behaviour in Mumbai.

35. H0 : Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.B.) associatio XI n between the appealing factor i.e. of the advertise

206 ments displayed with Complex buying behaviour in Nashik.

36. H0 : Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.B.) associatio XI n between the appealing factor of the advertise ments displayed with Complex buying behaviour in Surat.

37. H0: Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.C.) associatio XI n between the memorabl e visuals and slogans factor of the advertise ments displayed with Complex buying behaviour

207 in Mumbai.

38. H0 : Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 97 Accep no Sect Section XI( e test ted. ion 1.C.) associatio XI n between the memorabl e visuals and slogans factor of the advertise ments displayed with Complex buying behaviour in Nashik.

39. H0 : Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 98 Accep no Sect Section XI( e test ted. ion 1.C.) associatio XI n between the memorabl e visuals and slogans factor of the advertise ments displayed with Complex buying behaviour in Surat.

40. H0: Complex Buying Chi- 0.7 H0 is

208

There is Behaviour / Squar 88 Accep no Sect Section XI( e test ted. associatio ion 1.D.) XI n between the attractive ness factor of the advertise ments displayed with Complex buying behaviour in Mumbai.

41. H0 : Complex Buying Chi- 0.1 H0 is There is Behaviour / Squar 22 Accep no Sect Section XI( e test ted. ion 1.D.) associatio XI n between the attractive ness factor of the advertise ments displayed with Complex buying behaviour in Nashik.

42. H0 : Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.D.) associatio XI n between the attractive

209 ness factor of the advertise ments displayed with Complex buying behaviour in Surat.

43. H0: Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.E.) associatio XI n between the trustworth iness factor of the advertise ments displayed with Complex buying behaviour in Mumbai.

44. H0 : Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 00 Reject no Sect Section XI( e test ed. ion 1.E.) associatio XI n between the trustworth iness factor of the advertise ments displayed

210 with Complex buying behaviour in Nashik.

45. H0 : Complex Buying Chi- 0.0 H0 is There is Behaviour / Squar 45 Accep no Sect Section XI ( e test ted. ion 1.E.) associatio XI n between the trustworth iness factor of the advertise ments displayed with Complex buying behaviour in Surat.

46. H0 : Sect Section XI Anova 0.1 H0 is All the ion (1.A,1.B,1.C,1.D,1 65 Accep factors of XI, .E) / Section VI ted. Sect (1,2.) Social ion Media VI Advertise ment and all the factors of Habitual Buying Behaviou r in Mumbai are independe nt of each other.

47. H0 : Sect Section XI Anova 0.0 H0 is All the ion (1.A,1.B,1.C,1.D,1 00 Reject

211 factors of XI, .E) / Section VI ed. Social Sect (1,2.) Media ion VI Advertise ment and all the factors of Habitual Buying Behaviou r in Nashik are independe nt of each other.

48. H0 : Sect Section XI Anova 0.0 H0 is All the ion (1.A,1.B,1.C,1.D,1 00 Reject factors of XI, .E) / Section VI ed. Sect (1,2.) Social ion Media VI Advertise ment and all the factors of Habitual Buying Behaviou r in Surat are independe nt of each other.

49. H0 : Sect Section XI Anova 0.0 H0 is All the ion (1.A,1.B,1.C,1.D,1 00 Reject factors of XI, .E) / Section VII ed. Sect (1,2,3). Social ion Media VII Advertise ment and all the factors of Variety

212

Seeking Buying Behaviou r in Mumbai are independe nt of each other.

50. H0 : Sect Section XI Anova 0.0 H0 is All the ion (1.A,1.B,1.C,1.D,1 00 Reject factors of XI, .E) / Section VII ed. Sect (1,2,3) Social ion Media VII Advertise ment and all the factors of Variety Seeking Buying Behaviou r in Nashik are independe nt of each other.

51. H0 : Sect Section XI Anova 0.0 H0 is All the ion (1.A,1.B,1.C,1.D,1 00 Reject factors of XI, .E) / Section VII ed. Sect (1,2,3) Social ion Media VII Advertise ment and all the factors of Variety Seeking Buying Behaviou r in Surat are

213 independe nt of each other.

52. H0 : Sect Section XI Anova 0.0 H0 is All the ion (1.A,1.B,1.C,1.D,1 00 Reject factors of XI, .E) / Section VIII ed. Sect (1,2,3). Social ion Media VIII Advertise ment and all the factors of Dissonan ce Buying Behaviou r in Mumbai are independe nt of each other.

53. H0 : Sect Section XI Anova 0.7 H0 is All the ion (1.A,1.B,1.C,1.D,1 78 Accep factors of XI, .E) / Section VIII ted. Sect (1,2,3). Social ion Media VIII Advertise ment and all the factors of Dissonan ce Buying Behaviou r in Nashik are independe nt of each other.

54. H0 : Sect Section XI Anova 0.2 H0 is All the ion (1.A,1.B,1.C,1.D,1 34 Accep

214 factors of XI, .E) / Section VIII ted. Social Sect (1,2,3). Media ion VIII Advertise ment and all the factors of Dissonan ce Buying Behaviou r in Surat are independe nt of each other.

55. H0 : Sect Section XI Anova 0.1 H0 is All the ion (1.A,1.B,1.C,1.D,1 28 Accep factors of XI , .E) / Section IX ted. Sect (1,2,3) Social ion Media IX Advertise ment and all the factors of Impulsive Buying Behaviou r in Mumbai are independe nt of each other.

56. H0 : Sect Section XI Anova 0.0 H0 is All the ion (1.A,1.B,1.C,1.D,1 00 Reject factors of XI , .E) / Section IX ed. Sect (1,2,3) Social ion Media IX Advertise ment and all the factors of

215

Impulsive Buying Behaviou r in Nashik are independe nt of each other.

57. H0 : Sect Section XI Anova 0.0 H0 is All the ion (1.A,1.B,1.C,1.D,1 00 Reject factors of XI, .E) / Section IX ed. Sect (1,2,3) Social ion Media IX Advertise ment and all the factors of Impulsive Buying Behaviou r in Surat are independe nt of each other.

3 Impact 1 Sect Section Regre 0.0 H0 is (i) H : ion XI(1.A,1.B,1.C,1. ssion 00 Reject of 0 Model is XI, D,1.E ) / Section ed. social not Sect III(1,2,3,4), statisticall ion Section media y fit. III, IV(1,2,3,4), adverti IV, Section V, V(1,2,3,4,5,6), sing on VI, Section VI(1,2), the VII, Section VII(1,2,3), VIII Section buying , IX. VIII(1,2,3), behavi Section IX(1,2,3) or of young workin g

216 women for consum er electro nics.

(ii) H0: all Regre the ssion coefficien ts of the study are not 0.0 H0 statisticall 52 Accep y ted significan t 0.0 H0 a. Online 4 Reject purchase ed behaviour b. 0.0 H0 Consumer 00 Reject Buying ed Behaviour

c. Complex 0.2 H0 Buying 04 Accep Behaviour ted d. Habitual Buying 0.0 H0 Behaviour 06 Reject e. Variety ed Seeking H0 Buying 0.0 Reject Behaviour 14 ed f.

Dissonanc e Buying H0 Behaviour 0.7 Accep g. 71 ted Impulsive Buying Behaviour

2. Sect Section Regre 0.0 H0 is (i) H0 ion XI(1.A,1.B,1.C,1. ssion 0 Reject :Model is XI, D,1.E ) / Section ed. Sect III(1,2,3,4), not ion Section

217 statisticall III, IV(1,2,3,4), y fit IV, Section V, V(1,2,3,4,5,6), VI, Section VI(1,2), VII, Section VII(1,2,3), VIII Section , IX. VIII(1,2,3), Section IX(1,2,3) (ii) H0: Regre all the ssion coefficien ts of the study are not statisticall 0.9 H0 y 13 Accep significan ted t 0.0 H0 a. Online 01 rejecte purchase d behaviour b. 0.1 H0 Consumer 60 Accep Buying ted Behaviour c. Complex 0.4 H0 Buying 56 Accep Behaviour ted d. Habitual Buying 0.0 H0 Behaviour 00 rejecte e. Variety d Seeking Buying 0.5 Ho Behaviour 22 Accep f. ted Dissonanc e Buying Behaviour 0.8 Ho g. 53 Accep Impulsive ted Buying Behaviour 3. Sect Section Regre 0.0 3.

(i) H0 : ion XI(1.A,1.B,1.C,1. ssion 0 (i) H0 : Model is XI, D,1.E ) / Section Model Sect III(1,2,3,4), not is not ion Section statisticall III, IV(1,2,3,4), statisti

218

y fit IV, Section cally V, V(1,2,3,4,5,6), fit VI, Section VI(1,2), VII, Section VII(1,2,3), VIII Section , IX. VIII(1,2,3), Section IX(1,2,3) (ii) H0: Regre all the ssion coefficien ts of the study are not statisticall 0.5 Ho y 77 Accep significan ted t 0.0 Ho a. Online 04 Reject purchase ed behaviour b. 0.0 Ho Consumer 25 Reject Buying ed Behaviour

c. Complex 0.0 H0 Buying 43 Reject Behaviour ed d. Habitual Buying 0.0 Ho Behaviour 01 Reject e. Variety ed Seeking Buying 0.0 Ho Behaviour 17 Reject f. ed Dissonanc e Buying Behaviour 0.3 Ho g. 91 Accep Impulsive ted Buying Behaviour

4. To Nil Sect Section Rank -- Faceb ion X(1.A,1B,1C,1D Order ook is study X ,1E, 2,3 & 4A,4B) and the the Frequ most ency effecti effectiv distrib ve in

219

eness of ution all 3 cities. Social It is Media follow ed by tools Twitte like r in some face cities book, and Linke twitter, dIn in Linked other cities. In on the consum er behavi our.

5. To 1. H0 : Sect Section XI (1,2,3) Anova 0.3 H0 is ion / Section I 38 Accep study Impact of social XI, (Education) ted. the Sect media ion impact advertisin I of g and the qualificati social on of media young adverti working women in sing on Mumbai workin are g independe women nt of each other. belongi ng to differe nt demogr aphic

220 factors such as qualific ation, annual income, occupa tion and place.

2. H0 : Sect Section XI (1,2,3) Anova 0.0 H0 is Impact of ion / Section I 01 Reject social XI, (Education) ed. Sect media ion advertisin I g and the qualificati on of young working women in Nashik are independe nt of each other.

3. H0 : Sect Section XI (1,2,3) Anova 0.0 H0 is Impact of ion / Section I 00 Reject social XI, (Education) ed. Sect media ion advertisin I g and the qualificati on of young working women in Surat are independe nt of each

221 other.

4. Impact Sect Section XI (1,2,3) Anova 0.7 H0 is of social ion / Section I (Annual 97 Accep media XI, income) ted. Sect advertisin ion g and the I Annual Income of young working women in Mumbai are independe nt of each other

5. Impact Sect Section XI (1,2,3) Anova 0.0 H0 is of social ion / Section I (Annual 29 Reject media XI, income) ed. Sect advertisin ion g and the I Annual Income of young working women in Nashik are independe nt of each other

6. Impact Sect Section XI (1,2,3) Anova 0.0 H0 is of social ion / Section I (Annual 00 Reject media XI, income) ed. Sect advertisin ion g and the I Annual Income of young working women in Surat are independe

222 nt of each other

7. Impact Sect Section XI (1,2,3) Anova 0.1 H0 is of social ion / Section I 28 Accep media XI, (Occupation) ted. Sect advertisin ion g and the I Occupatio n of young working women in Mumbai are independe nt of each other

8. Impact Sect Section XI (1,2,3) Anova 0.0 H0 is of social ion / Section I 49 Reject media XI, (Occupation) ed. Sect advertisin ion g and the I Occupatio n of young working women in Nashik are independe nt of each other

9. Impact Sect Section XI (1,2,3) Anova 0.0 H0 is of social ion / Section I 87 Accep media XI, (Occupation) ted. Sect advertisin ion g and the I Occupatio n of young working women in Surat are

223

independe nt of each other

7.3 Summery of Hypothesis :

7.7 Tabular representation showing Hypothesis (Accepted/Rejected).

Sr. H Hypotheis Accepted Sr. H Hypotheis Rejected No. 0 No. 0

1. H0c: There is no association 1. H0a: There is no association between the factor i.e. between the factor i.e. positive reactions/feelings positive reactions/feelings towards advertisements towards advertisements displayed with Consumer displayed with Consumer buying behaviour in Surat. buying behaviour in Mumbai.

2. H0b: There is no association 2. H0b: There is no association between the appealing factor between the factor i.e. of social media positive reactions/feelings advertisements with towards advertisements Consumer buying behavior displayed with Consumer in Nashik. buying behaviour in Nashik.

3. H0c: There is no association 3. H0a: There is no association between the appealing factor between the appealing factor of social media of social media advertisements with advertisements with Consumer buying behavior Consumer buying behavior in Surat. in Mumbai.

4. H0a: There is no association 4. H0c: There is no association between the memorable between the attractive factor visuals and slogans factor of social media of social media advertisements with

224

advertisements with Consumer buying behavior Consumer buying behavior in Surat. in Mumbai.

5. H0b: There is no association 5. H0c: There is no association between the memorable between the trustworthiness visuals and slogans factor factor of social media of social media advertisements with advertisements with Consumer buying behavior Consumer buying behavior in Surat. in Nashik.

6. H0c: There is no association 6. H0b : There is no association between the memorable between the factor i.e. visuals and slogans factor positive reactions/feelings of social media towards advertisements advertisements with displayed with online Consumer buying behavior purchase behavior in Nashik. in Surat.

7. H0a: There is no association 7. H0c : There is no association between the attractive factor between the factor i.e. of social media positive reactions/feelings advertisements with towards advertisements Consumer buying behavior displayed with online in Mumbai. purchase behavior in Surat.

8. H0b: There is no association 8. H0b : There is no association between the attractive factor between the appealing factor of social media of the advertisements advertisements with displayed with online Consumer buying behavior purchase behavior in Nashik. in Nashik.

9. H0a: There is no association 9. H0c : There is no association between the trustworthiness between the appealing factor factor of social media of the advertisements advertisements with displayed with online Consumer buying behavior purchase behavior in Surat. in Mumbai.

10. H0b: There is no association 10. H0b : There is no association between the trustworthiness between the memorable factor of social media visuals and slogans factor of advertisements with the advertisements with Consumer buying behavior online purchase behavior in in Nashik. Nashik.

225

11. H0a : There is no association 11. H0c : There is no association between the factor i.e. between the memorable positive reactions/feelings visuals and slogans factor of towards advertisements the advertisements with displayed with online online purchase behavior in purchase behavior in Surat. Mumbai.

12. H0a : There is no association 12. H0b : There is no association between the appealing factor between the attractive factor of the advertisements of the advertisements with displayed with online online purchase behavior in purchase behavior in Nashik. Mumbai.

13. H0a : There is no association 13. H0c : There is no association between the memorable between the attractive factor visuals and slogans factor of of the advertisements with the advertisements with online purchase behavior in online purchase behavior in Surat. Mumbai.

14. H0a : There is no association 14. H0a: There is no association between the attractive factor between the factor i.e. of the advertisements with positive reactions/feelings online purchase behavior in towards advertisements Mumbai. displayed with Complex buying behaviour in Mumbai.

15. H0a : There is no association 15. H0b : There is no association between the trustworthiness between the factor i.e. factor of the advertisements positive reactions/feelings with online purchase towards advertisements behavior in Mumbai. displayed with Complex buying behaviour in Nashik.

16. H0b : There is no association 16. H0c : There is no association between the trustworthiness between the factor i.e. factor of the advertisements positive reactions/feelings with online purchase towards advertisements behavior in Nashik. displayed with Complex buying behaviour in Surat.

17. H0c : There is no association 17. H0b : There is no association between the trustworthiness between the appealing factor factor of the advertisements i.e. of the advertisements

226

with online purchase displayed with Complex behavior in Surat. buying behaviour in Nashik.

18. H0a: There is no association 18. H0c : There is no association between the appealing factor between the appealing factor of the advertisements of the advertisements displayed with Complex displayed with Complex buying behaviour in buying behaviour in Surat. Mumbai.

19. H0b : There is no association 19. H0a: There is no association between the memorable between the memorable visuals and slogans factor of visuals and slogans factor of the advertisements displayed the advertisements displayed with Complex buying with Complex buying behaviour in Nashik. behaviour in Mumbai.

20. H0c : There is no association 20. H0c : There is no association between the memorable between the attractiveness visuals and slogans factor of factor of the advertisements the advertisements displayed with Complex displayed with Complex buying behaviour in Surat. buying behaviour in Surat.

21. H0a: There is no association 21. H0a: There is no association between the attractiveness between the trustworthiness factor of the advertisements factor of the advertisements displayed with Complex displayed with Complex buying behaviour in buying behaviour in Mumbai. Mumbai.

22. H0b : There is no association 22. H0b : There is no association between the attractiveness between the trustworthiness factor of the advertisements factor of the advertisements displayed with Complex displayed with Complex buying behaviour in Nashik. buying behaviour in Nashik.

23. H0c : There is no association 23. H0b : All the factors of Social between the trustworthiness Media Advertisement and all factor of the advertisements the factors of Habitual displayed with Complex Buying Behaviour in Nashik buying behaviour in Surat. are independent of each other.

24. H0a : All the factors of 24. H0c : All the factors of Social Social Media Advertisement Media Advertisement and all and all the factors of the factors of Habitual Habitual Buying Behaviour Buying Behaviour in Surat

227

in Mumbai are independent are independent of each of each other. other.

25. H0b : All the factors of 25. H0a : All the factors of Social Social Media Advertisement Media Advertisement and all and all the factors of the factors of Variety Dissonance Buying Seeking Buying Behaviour Behaviour in Nashik are in Mumbai are independent independent of each other. of each other.

26. H0c : All the factors of 26. H0b : All the factors of Social Social Media Advertisement Media Advertisement and all and all the factors of the factors of Variety Dissonance Buying Seeking Buying Behaviour Behaviour in Surat are in Nashik are independent independent of each other. of each other.

27. H0a : All the factors of 27. H0c : All the factors of Social Social Media Advertisement Media Advertisement and all and all the factors of the factors of Variety Impulsive Buying Seeking Buying Behaviour Behaviour in Mumbai are in Surat are independent of independent of each other. each other.

28. H0a: In Mumbai Online 28. H0a : All the factors of Social purchase behaviour is not Media Advertisement and all statistically significant. the factors of Dissonance Buying Behaviour in Mumbai are independent of each other.

29. H0a: In Mumbai Habitual 29. H0b : All the factors of Social Buying Behaviour is not Media Advertisement and all statistically significant. the factors of Impulsive Buying Behaviour in Nashik are independent of each other.

30. H0a: In Mumbai Impulsive 30. H0c : All the factors of Social Buying Behaviour is not Media Advertisement and all statistically significant. the factors of Impulsive Buying Behaviour in Surat are independent of each other.

31. H0b: In Nashik Online 31. H0a: In Mumbai Model is not purchase behaviour is not statistically fit. statistically significant.

32. H0b: In Nashik Complex 32. H0a: In Mumbai Consumer Buying Behaviour is not Buying Behaviour

228

statistically significant. is not statistically significant. 33. H0b: In Nashik Habitual 32. H0a: In Mumbai Complex Buying Behaviour is not Buying Behaviour is not statistically significant. statistically significant.

34. H0b: In Nashik Dissonance 33. H0a: In Mumbai Variety Buying Behaviour is not Seeking Buying Behaviour is statistically significant. not statistically significant.

35. H0b: In Nashik Impulsive 34. H0a: In Mumbai Dissonance Buying Behaviour is not Buying Behaviour is not statistically significant. statistically significant.

36. H0c: In Surat Online purchase 35. H0b :In Nashik Model is not behaviour is not statistically statistically fit. significant.

37. H0c: In Surat Impulsive 36. H0b: In Nashik Consumer Buying Behaviour is not Buying Behaviour is not statistically significant. statistically significant.

38. H0a : Impact of social media 37. H0b: In Nashik Variety advertising and the Seeking Buying Behaviour is qualification of young not statistically significant. working women in Mumbai are independent of each other.

39. H0a :Impact of social media 38. H0c : In Surat Model is not advertising and the Annual statistically fit Income of young working women in Mumbai are independent of each other.

40. H0a :Impact of social media 39. H0c: In Surat Consumer advertising and the Buying Behaviour is not Occupation of young statistically significant. working women in Mumbai are independent of each other.

41. H0c :Impact of social media 40. H0c: In Surat Complex Buying advertising and the Behaviour is not statistically Occupation of young significant. working women in Surat are independent of each other.

41. H0c: In Surat Habitual Buying Behaviour is not statistically significant.

42. H0c: In Surat Variety Seeking

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Buying Behaviour is not statistically significant.

43. H0c: In Surat Dissonance Buying Behaviour is not statistically significant.

44. H0b : Impact of social media advertising and the qualification of young working women in Nashik are independent of each other.

45. H0c : Impact of social media advertising and the qualification of young working women in Surat are independent of each other.

46. H0b :Impact of social media advertising and the Annual Income of young working women in Nashik are independent of each other

47. H0c :Impact of social media advertising and the Annual Income of young working women in Surat are independent of each other.

48. H0b :Impact of social media advertising and the Occupation of young working women in Nashik are independent of each other.

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Chapter 8

Conclusion

The growth of Social Media signifies the technological development of cities.

Women play an important role in taking the buying decision and they constitute

50% of the population. According to the IAMAI report the access rate of women accessing the social media is more as compared to that of men and it is increasing day by day. Therefore women have a prominent role to play as far as the consumer electronics market is concerned.

The detailed research has lead to certain conclusions which are being discussed in this chapter.

Association between Positive reactions or feelings towards social media advertisements with consumer buying behaviour :

Association between appealing factor of social media advertisements with consumer buying behaviour :

It has been concluded from the study that there is a strong positive association

231 between the appealing factor of social media advertising with the consumer buying behaviour in Mumbai. However there is no association between the appealing factor of social media advertising with the consumer buying behaviour in Nashik and Surat.

Association between memorable visuals and slogans factor of social media advertisements with consumer buying behaviour :

It has been concluded from the study that the memorable visuals and slogans factor of social media advertising and consumer buying behaviour are independent of each other and there is no association between the memorable visuals and slogans factor of social media advertising with the consumer buying behaviour in Mumbai, Nashik and Surat.

Association between attractive factor of social media advertisements with consumer buying behaviour :

Association between trustworthiness factor of social media advertisements with consumer buying behaviour :

It has been concluded from the study that the trustworthiness factor of social

232 media advertising and consumer buying behaviour are dependent of each other and there is a strong association between the trustworthiness factor of social media advertising with the consumer buying behaviour in Surat. However there is no association between the trustworthiness factor of social media advertising and the consumer buying behaviour in Mumbai and Nashik and they are independent of each other.

Association between Positive reactions or feelings towards social media advertisements with online purchase behaviour :

However there is no association between the factor of social media advertising i.e. positive reactions/feelings with the online purchase behaviour in Mumbai.

Association between appealing factor of social media advertising and online purchase behaviour :

It has been revealed from the study that there is an association between the appealing factor of social media advertising and the online purchase behaviour in

Nashik and Surat. So if there is any change in the appealing factor of social media advertising it will lead to change in the online purchase behaviour.

However there is no association between the appealing factor of social media advertising and the online purchase behaviour in Mumbai.

Association between memorable visuals and slogans factor of social media

233 advertising and online purchase behaviour :

It has been revealed from the study that there is an association between the memorable visuals and slogans factor of social media advertising and the online purchase behaviour in Nashik and Surat. So if there is any change in the memorable visuals and slogans factor of social media advertising it will lead to change in the online purchase behaviour. However there is no association between the memorable visuals and slogans factor of social media advertising and the online purchase behaviour in Mumbai.

Association between attractiveness factor of social media advertising and online purchase behaviour :

Association between trustworthiness factor of social media advertising and online purchase behaviour :

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Association between Positive reactions or feelings towards social media advertisements with complex buying behaviour :

It has been revealed from the study that there is a strong relationship between the factor of social media advertising i.e. positive reactions/feelings with online consumer behaviour in Mumbai, Nashik and Surat. So if there is any change in the positive reactions/feelings factor of social media advertising, it will lead to change in the complex buying behaviour.

Association between appealing factor of social media advertisements with complex buying behaviour :

It has been revealed from the study that there is a strong relationship between the appealing factor of social media advertising with complex buying behaviour in

Nashik and Surat. So if there is any change in the appealing factor of social media advertising, it will lead to change in the complex buying behaviour.

However there is no relationship between the appealing factor of social media advertising and complex buying behaviour in Mumbai and they are independent of each other.

Association between memorable visuals and slogans factor of social media advertisements with complex buying behaviour :

235 memorable visuals and slogans factor of social media advertising and complex buying behaviour in Nashik and Surat.

Association between attractiveness factor of social media advertisements with complex buying behaviour :

However there is no relationship between the attractiveness factor of social media advertising and complex buying behaviour in Mumbai and Nashik and they are independent of each other.

Association between trustworthiness factor of social media advertisements with complex buying behaviour :

Relationship between all the factors of Habitual Buying Behaviour with all the factor of Social Media Advertisement in different cities :

From the study it has been concluded that all the factors of Social Media

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Advertisement and all the factors of Habitual Buying Behaviour of young working women for consumer electronics in Mumbai are independent of each other. However in Nashik and Surat, all the factors of Social Media