An empirical study on demographic factors influencing consumers’ usage of social media

 

Dr. Viral Bhatt1, Dipanti Joshi2

1Director, SAL Institute of Management, Ahmedabad, Gujarat

2Assistant Professor, SAL Institute of Management, Ahmedabad, Gujarat

*Corresponding Author Email:

 

ABSTRACT:

Considering other demographic factors like age, occupation, income, the researcher has selected four major social media: facebook, twitter, linkedin and google+. The researcher has studied the demographic factors influencing the usage of social media. Most of the people in this age group between 15 to 35 are using facebook for general purpose while for the corporate relations, achievement, status, looking for better opportunities, they are using linked. Twitter is the game of professionals who have achieved the heights in their careers. In the recent past, google+ has also become popular since the youth of Ahmedabad have started using it meaningfully and smartly.

 

KEYWORDS: Empirical study, Demographic factors, Consumer, Social media

 

 


INTRODUCTION:

Social media has made a vital impact on different aspects of society over the past few years especially in the way people communicate and share information. Through video sharing sites, wikis, forums, etc., social networking sites (SNS) provide an active, free and open platform for grabbing knowledge and connecting socially to any interested user regardless of their socio-demographic characteristics such as age or gender Huang, Hood, and Yoo, Osatuyi, (2013). Furthermore, this platform provides the perfect medium for personalized informal learning in the domains that the user is interested in, and increases the motivation to continue the learning process (Bull et al., 2008). For ease of understanding the influence of social media landscape, the total time spent on it has been calculated and further it is projected in comparison to many other regular activities.

 

 (http://www.businessinsider.com/how-much-time-do-people-spend-on-facebook-per-day-2016-4) Kalpana Chauhan and Anandan Pillai (2011) initiated an attempt to simplify the role of content strategy followed by leading higher education institutes who have created brand community on social media in India to make people aware about the same.

 

Social media usage has increased in areas such as: health, shopping, education, social networking, marketing etc. Demographic factors like age, income, gender, occupation etc have a huge impact on the usage pattern of social media. show that the teenagers usually use the Internet for social networking and communication. In this context, analyzing the purposes of Internet usage of the high school students, the relationship between these purposes and the demographic variables, and determining important factors affecting the purposes of social media usage are the objectives of this research. The main objective of research answering the following research question: “What are the demographic factors affecting social media usage?” (https://www.researchgate.net/publication/320556687_Factors_affecting_the_use_of_social_media_in_the_learning_process) Ruchi Sachdev (2015) discusses the role of social media in today’s society in terms of it play more of a positive or a negative role for the masses. Reynol Junco (2017) has studied the relationship between multiple indices of facebook usage and its relationship with academic performance of students in the United States.Ruth N. Bolton, A. Parasuraman, Ankie Hoefnagels and co-authors (Jan 2013) have studied the generation Y and how they use the social media. Wexlr Lisa, Aline Gubrim, Megan gifin and Gloria Diflvo (2015) have studied the role of digital world for promoting positive youth development and showing the reasons for living in northwest Alaska.

 

The role of the Internet and smartphone has been increasing in the daily life of many people around the globe and the studies on the Internet widely use individuals’ demographic characteristics in explaining the nature of usage. For example, in an earlier study, Taylor, Zhu, Dekkers and Marshall (2003) claimed that Internet usage pattern may have different dispersions for different gender groups out of total population who uses smartphones. Kalmus, Realo and Siibak (2011) age, income level, education level are the significant predictors of adoption and usage patterns of social media. On the other hand, the nature of Internet has changed drastically with the increasing popularity of social media especially during the last few yearsThis scenario has attracted the attention of higher education institutions. More specifically, Calisir, Atahan and Saracoglu (2013) pointed that differences may be significantly explained by the demographic characteristics for the adoption and usage pattrens of Social Network Sites (SNS), which means demographic characteristics should be taken into consideration, as the nature and consequences of SNS usage could be potentially different for different demographic groups.

 

RESEARCH METHODOLOGY:

Objectives of the study:

The core objective of the study is to understand the difference among demographic factors with respect to social media influence in Ahmedabad city. To identify the factors of demographic that have an impact on usage pattern of social media.

 

Data collection:

Secondary Data collection:

In this research, the researcher has used many resources of secondary data collection. Recent newspapers, research journals, media websites, books, magazines, published research papers in the national and international journals have been referred for the secondary data. Recent cases involving use of social media have been taken from various English and Gujarati newspapers and online papers. Even some articles from the supplements of a newspaper have been discussed. Websites of media channels like Times of India, NDTV and Mint have been cited where n when content has been taken and various online dictionaries like Oxford and Cambridge have been referred to, to get the theoretical content and various definitions for many terms.

 

Primary data collection:

For collection of primary data, researcher has used structured questionnaire which consist of the parameters of social media influence on youngsters.

 

Sample frame:

With reference to collect the data, researcher has considered any male or female, falling in the age group of 15 to 35, resident of Ahmedabad city and using social media for the last 6 months.

 

Sample size:

1133 samples have been taken from various areas of Ahmedabad city.

 

Data Analysis:

Age * Influence of social media:

H0: There is no significant difference amongst various age group regarding the positive influence of social media

 

H1: There is significant difference amongst various age group regarding the positive influence of social media

 

Table 1. 1 Descriptive Statistics

Dependent Variable: SUMMATED_COMBINPOSITIVE

Age Group

Mean

Std. Deviation

N

15-20

42.0000

10.11691

234

21-25

39.8509

10.56275

523

26-30

39.8062

11.35577

227

31-35

35.6081

12.14069

148

Total

39.7314

10.99105

1132

 

This table 1.1 shows the descriptive statistics of overall changes in positive manners because of social media. Mean stands for the average value while standard deviation shows the fluctuations. Our objective is to check whether there is any significant difference amongst the various age values. The researcher has also evaluated whether the variance is homogeneous or not through the Levence’s Test.

 

Table 1.2 Levene's Test of Equality of Error Variancesa

Dependent Variable: SUMMATED_COMBINEDPOSITIVE

F

df1

df2

Sig.

9.106

3

1130

.000

Tests the null Hypothesis that the error variance of the dependent variable is equal across groups.

a. Design: Intercept + Q0.1

 

 

The Levene’s Test table indicated that F ratio between and within the sample is 9.106 it means variations between the samples is 9 times more than the variations within the samples. While significant value of the test is 0.00 which is less than 0.05, it indicates that there is a significant difference amongst the value of variance in different groups.


 

Table 1.3 ANOVA

Source

Type III Sum of Squares

df

Mean Square

F

Sig.

Corrected Model

3729.252a

3

1243.084

10.551

.000

Intercept

1425691.887

1

1425691.887

12100.762

0.000

Questions

3729.252

3

1243.084

10.551

.000

Error

132899.109

1128

117.818

 

 

Total

1923590.000

1132

 

 

 

Corrected Total

136628.360

1131

 

 

 

 


This is the vital part of one way ANOVA analysis and this will derive if there is significant difference amongst the group or not. So far as this content is concerned, the researcher has considered various age groups as a fixed factor and overall negative influences of social media on youth is considered as a dependent variable. For the age group, the value of F ratio is 10.551; it indicates that variations between the groups are multiple times more than the variations within the group. The value of significance is 0.0 which is less than 0.05, it indicates that Null Hypothesis cannot be accepted and in this case accept the alternative Hypothesis is accepted.


 

Table 1.4 Multiple Comparisons

Dependent Variable: SUMMATED_COMBINEDNEGATIVE Tukey HSD

(I) Age Group

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval

Lower Bound

Upper Bound

15-20

21-25

2.1491

.85368

.058

-.0473

4.3455

26-30

2.1938

1.01120

.132

-.4078

4.7955

31-35

6.3919*

1.13999

.000

3.4589

9.3249

21-25

15-20

-2.1491

.85368

.058

-4.3455

.0473

26-30

.0447

.86273

1.000

-2.1750

2.2644

31-35

4.2428*

1.01062

.000

1.6426

6.8429

26-30

15-20

-2.1938

1.01120

.132

-4.7955

.4078

21-25

-.0447

.86273

1.000

-2.2644

2.1750

31-35

4.1981*

1.14678

.001

1.2476

7.1486

31-35

15-20

-6.3919*

1.13999

.000

-9.3249

-3.4589

21-25

-4.2428*

1.01062

.000

-6.8429

-1.6426

26-30

-4.1981*

1.14678

.001

-7.1486

-1.2476

Based on observed means.

 The error term is Mean Square(Error) = 117.818.

*. The mean difference is significant at the .05 level.

 


By analyzing the Tukey multiple comparisons, We can find the mean difference of 21 to 25 is  2.14 and significant value is 0.058 similarly for 26 to 30, it is 2.19 and significant value is 0.132, which is more than 0.05, it indicates that these two categories are not significantly different in terms of average value for overall positive changes occurring because of the social media. While analyzing the Tukey multiple comparison for the  various age groups of 21 to 25, the mean difference of 15 to 20 is -2.14 and significant value is 0.58, similarly for 26 to 30, the mean difference is 0.0447 and the significant difference is 1.00; with the age group 31-35, the mean difference is 4.24 and the significant difference is 0.0.By analyzing  the Tukey multiple comparisons, the mean difference of 15 to 20 is -2.19 and significant value is 0.132, similarly for 21 to 25, it is -0.044 and significant value is 1.00, which is quite more than 0.05, indicating that these two categories are similar in terms of average value for overall positive changes occurring because of the social media. 31 to 35: Considering the mean differences and the significant values of the age groups of 15 to 29, 21 to 25 and 26 to 30 in the Tukey multiple comparisons the mean differences -6.39, -4.24 and -4.19 and the significant differences 0.0, 0.0 and 0.001, all of these are less than 0.05, indicating that all of these categories are similar in terms of influences of social media.

 

Income * Influence of social media:

H0: There is no significant difference amongst various income groups regarding social positive influence of social media.

 

H1: There is significant difference amongst various income groups regarding social positive influence of social media.

 

 

 

 

 

 

Table 1.5 Descriptive Statistics

Dependent Variable: SUMMATED_SOCIALPOSITIVE

Family Income

Mean

Std. Deviation

N

Less than 2 lac

29.4045

4.99485

267

Between 2.1 lac- 5 lac

30.4609

4.61404

447

5.1 lac – 10 lac

30.8157

4.56837

293

10 lac p.a – to 20 lac

30.4896

5.08040

96

More than 20 lac

31.1034

6.96596

30

Total

30.3224

4.82783

1133

 

This table shows the descriptive statistics of Social influences of social media with reference to various young social media users across various family incomes. Mean stands for the average value while standard deviation shows the fluctuations. Our objective is to check whether there is any significant difference amongst the various values of annual family income. The researcher also evaluated whether the variance is homogeneous or not through the Levence’s Test.

 

Table 1.6 Levene's Test of Equality of Error Variancesa

Dependent Variable: SUMMATED_SOCIALPOSITIVE

F

df1

df2

Sig.

4.394

4

1127

.002

Tests the null Hypothesis that the error variance of the dependent variable is equal across groups.

a. Design: Intercept + Q0.11

 

The Levene’s Test table indicated that F ratio between and within the sample is 4.394 it means variations between the samples is four times more than the variations within the samples. While significant value of the test is 0.002 which is less than 0.05, it indicates that there is significant difference amongst the value of variance in different groups. By analyzing  the descriptive statistics, the highest fluctuations is 6.96 in the group no 5 for the income group of more than 5 lacs while the smallest variations is 4.56 in the range of 5.1 to 10.


Table 1.7 ANOVA

Source

Type III Sum of Squares

df

Mean Square

F

Sig.

Corrected Model

325.204a

4

81.301

3.519

.007

Intercept

427064.342

1

427064.342

18485.925

0.000

Question

325.204

4

81.301

3.519

.007

Error

26036.107

1127

23.102

 

 

Total

1067179.000

1132

 

 

 

Corrected Total

26361.310

1131

 

 

 

 


This is the core part of one way ANOVA analysis and this will derive if there is significant difference amongst the group or not. Here the researcher has the model of test among the subject effects; as far as this content is concerned, the researcher has considered various income groups as a fixed factor and social positive influences of social media on youth is considered as a dependent variable. For the age group, the value of F ratio is 3.519, it indicates that variations between the group is multiple times more than the variations within the group. The value of significance is 0.007 which is less than 0.05, it indicates that Null Hypothesis cannot be accepted and in this case the researcher accepts the alternative Hypothesis. It indicates that there is a significant difference amongst the various age groups regarding overall changes in the various groups.

 

Gender * Influence of social media:

H0: There is no significant difference between male and female regarding overall Positive influence of social media.

 

H1: There is significant difference between male and female regarding overall Positive influence of social media.


 

Table 1.8

 

Independent Samples Test

 

 

Levene's Test for Equality of Variances

t-test for Equality of Means

 

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower

Upper

Summated_Combinedpositive

Equal variances assumed

17.990

.000

1.815

1129

.070

1.52718

.84152

-.12393

3.17830

Equal variances not assumed

 

 

1.901

1077.582

.058

1.52718

.80318

-.04879

3.10316

 


Considering the independent sample test table, the value F suggest 17.99 with significant value is 0.00, it indicates that Levance Test significant value which is less than 0.05, it indicates that there is no similarity in the variance between male and female. Considering the T value is 1.815, and significant two tailed value is 0.07, which is less than 0.05, so we reject null Hypothesis. It indicates that there is significant difference between male and female regarding the overall Negative influence Combined factors with respect to social media. The mean difference between the male and female is 1.52 for the sample size and it should lie between -0.12 and 3.17 for the entire population of the Ahmedabad city.

 

Educational Level * Influence of social media:

H0: There is no significant difference amongst various education levels regarding influence of social media.

H1: There is a significant difference amongst various education levels regarding influence of social media.

 

 

 

 

 

 

 

Table 1. 9 Descriptive Statistics

Dependent Variable: Overall_Influence_Combinepositive_Negative

Student

Mean

Std. Deviation

N

School Going

122.4341

18.32853

129

Under Graduate

116.4505

17.92803

404

Post Graduate

116.4928

18.91993

489

Higher Degree

117.1651

21.63267

109

Total

117.2202

18.85581

1131

 

This table shows the descriptive statistics of overall influences of social media with reference to various educational levels. Mean stands for the average value while standard deviation shows the fluctuations. Our objective is to check whether there is any significant difference amongst the various values of annual family income.


Table 1.10 Tests of Between-Subjects Effects

Dependent Variable: Overall_Influence_Combinepositive_Negative

Source

Type III Sum of Squares

df

Mean Square

F

Sig.

Corrected Model

4005.228a

3

1335.076

3.783

.010

Intercept

10411798.037

1

10411798.037

29500.669

0.000

Q0.4Edu

4005.228

3

1335.076

3.783

.010

Error

397756.952

1127

352.934

 

 

Total

15942342.000

1131

 

 

 

Corrected Total

401762.180

1130

 

 

 

a. R Squared = .010 (Adjusted R Squared = .007)

b. Computed using alpha = .05

 


This is the vital part of one way ANOVA analysis and this will derive if there is significant difference amongst the group or not. Here, the researcher has the model of test between the subject effects; as far as this content is concerned, the researcher has considered various educational groups as a fixed factor and overall changes is considered as a dependent variable. For the educational level group, the value of F ratio is 3.783, it indicates that variations between the group is multiple times more than the variations within the group. The value of significance is 0.010 which is less than 0.05, it indicates that Null Hypothesis cannot be accepted and in this case we accept the alternative Hypothesis.


 

Table 1. 11 Multiple Comparisons

Dependent Variable: Overall_Influence_Combinepositive_Negative Scheffe

(I) Student

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval

Lower Bound

Upper Bound

School Going

Under Graduate

5.9836*

1.89987

.020

.6645

11.3027

Post Graduate

5.9413*

1.85948

.017

.7352

11.1473

Higher Degree

5.2690

2.44415

.200

-1.5739

12.1119

Under Graduate

School Going

-5.9836*

1.89987

.020

-11.3027

-.6645

Post Graduate

-.0423

1.26307

1.000

-3.5786

3.4939

Higher Degree

-.7146

2.02769

.989

-6.3916

4.9623

Post Graduate

School Going

-5.9413*

1.85948

.017

-11.1473

-.7352

Under Graduate

.0423

1.26307

1.000

-3.4939

3.5786

Higher Degree

-.6723

1.98989

.990

-6.2434

4.8988

Higher Degree

School Going

-5.2690

2.44415

.200

-12.1119

1.5739

Under Graduate

.7146

2.02769

.989

-4.9623

6.3916

Post Graduate

.6723

1.98989

.990

-4.8988

6.2434

Based on observed means. The error term is Mean Square (Error) = 352.934.

*. The mean difference is significant at the .05 level.

 


If we analyse the Tukey multiple comparisons, the mean difference with under graduates is 5.98 and significant value is 0.09, which is more than 0.05, it indicates that these two categories are not significantly different in terms of average value for overall changes occurring because of the social media. After analyzing the Tukey multiple comparisons, the mean difference with school going students is -5.98 and significant value is 0.020 similarly for the post graduates, the it mean is -.0423, and significant value is 1.00, which is more than 0.05, it indicates that these two categories are not significantly different in terms of average value for overall changes occurring because of the social media. If we analyse the Tukey multiple comparisons, the mean difference with school going students is -5.94 and significant value is 0.017 similarly for the under graduates, the it mean is 0.0423, and significant value is 1.00, which is more than 0.05, it indicates that these two categories are not significantly different in terms of average value for overall changes occurring because of the social media. After analyzing the Tukey multiple comparisons, the mean difference with school going students is -5.26 and significant value is 0.200 similarly for the under graduates, the it mean is 0.71, and significant value is 0.989, which is more than 0.05, it indicates that these two categories are not significantly different in terms of average value for overall changes occurring because of the social media.

 

FINDING:

According to analysis the positive influence of the combined factors, male and female both genders have found to be having different in terms of influences. There can be multiple factors behind this difference of both the genders. Both the genders are motivated with different things respectively, have different aspirations, have differences in thought process and even there are differences found in brought up of both the genders in the society today. The values, mindsets, ambition, the influences etc usually differ and hence it is reflected in the research.

 

From analysis it is observed that there is significant difference amongst various age groups regarding overall influence of social media. In terms of being benefitted by using social media, the various age groups have different results on the positive side. The final result is quite evident considering the difference influencing factors like age, educational background, occupation etc differs a lot across the age groups.

 

There is significant difference amongst various income groups regarding social influence of social media. Individuals among the various income groups have different peer groups and the amount of participant and the amount of activity varies across the various income groups, which can be the reason for this finding.

 

Post Graduate and Higher Degree have proximate similarities in terms of Overall combined influence of social media. Both the post graduates and the individuals who are pursuing higher degree education have many similar opinions which may be the reason of their close similarity in the behavior with reference to the overall positive as well as influences of social media. Few of the aspects can be life cycle stage, similar age group, and financial independence

 

 

REFERENCE:

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Received on 31.10.2018         Modified on 19.01.2019

Accepted on 01.02.2019      ©AandV Publications All right reserved

Res.  J. Humanities and Social Sciences. 2019; 10(2): 709-714.

DOI: 10.5958/2321-5828.2019.00117.7