USAGE PATTERN OF MOBILE PHONE SERVICE AND SOCIO-ECONOMIC STATUS OF THE CUSTOMER

454
Dr. S. Mythili and S. Chandrakala. “Usage Pattern of Mobile Phone Service and Socio-Economic
Status of the Customer” - (ICAM 2016)
USAGE PATTERN OF MOBILE PHONE SERVICE AND SOCIO-
ECONOMIC STATUS OF THE CUSTOMER
Dr. S. Mythili
Head of the Department
A.D.M. College for Women (Autonomous), Nagapattinam-611001
S. Chandrakala
Ph.D., Scholar (FT)
A.D.M. College for Women (Autonomous), Nagapattinam-611001
1. INTRODUCTION
Communication, as the transfer of information from person to person, is to reach out to people who are
close to you. It gives an opportunity to share your views with and how you miss a person and in a
business, it helps one to connect easily to his / her co-employees or boss. In the present modern
technological world, an individual can communicate anything to everything right from the place where
he/she stands either while riding vehicle or travelling in bus / train / air within a fraction of second at
quick speed with clear voice and without any disturbance. So, exchange of information becomes the
necessity of life to a common man and there are various means of communication on how you can
reach out to other people to communicate to communicate and one such means of communication is
mobile cell phone.
In the fast changing and competitive world, marked by hustle and bustle coupled with ceaseless
activities, mobile telecommunications have become increasingly needed services in a very limited
period. With the extensive use of mobile phones, the providing mobile phone services are now
recognized as the most competitive part of the telecommunications sector. Particularly in India, where
mobile telecommunication has penetrated at a very high rate during the past decade, it is necessary for
marketers to understand their customer needs and preferences in mobile phone services due to changes
in life-styles of the customers as well as continuous increase in their dependency on mobile phones to
carry out their day to day tasks.
Key words: Usage Pattern of Mobile Phone Services, Socio-Economic Characteristics,
Relationship between Internet Use and Mobile Net Connectivity.
Cite this Article: Dr. S. Mythili and S. Chandrakala. Usage Pattern of Mobile Phone Service
and Socio-Economic Status of the Customer. International Journal of Management, 7(2),
2016, pp. 454-463. http://www.iaeme.com/ijm/index.asp
2. OBJECTIVES OF THE STUDY
The present research work is undertaken with the following objectives:
 To study the usage pattern of mobile phone services as well as to evaluate relationship
between customers’ socio-economic characteristics and usage pattern and service oriented
factors influencing the users to choose mobile phone service providers.
INTERNATIONAL JOURNAL OF MANAGEMENT (IJM)
ISSN 0976-6502 (Print)
ISSN 0976-6510 (Online)
Volume 7, Issue 2, February (2016), pp. 454-463
http://www.iaeme.com/ijm/index.asp
Journal Impact Factor (2016): 8.1920 (Calculated by GISI)
www.jifactor.com
IJM
© I A E M E

International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 -
6510(Online), Volume 7, Issue 2, February (2016), pp. 454-463 © IAEME Publication
455
 To study the expected and perceived service quality of mobile phone service of BSNL in
Nagapattinam district.
 To analyze the relationship between customers’ socio-economic characteristics and
expected / perceived SQ of BSNL Mobile phone services.
3. METHODOLOGY
The present research work is mainly based on primary data. The secondary information obtained from
articles in journals, publications and books relevant for the research area is also used in the study. The
primary data are the opinion of the BSNL customers about their actual and expected service as well as
their opinion about factors for choosing BSNL service on ranks and about overall satisfaction with
various services. The socio-economic data of the customers also obtained. The respondents for the
sample are selected using simple random sampling technique among the population of BSNL
customers in Nagapattinam district
The distribution of the respondents by demographic characteristics is first provided in Table 1
Table 1 Distribution of Sample Respondents by Socio-Economic Characteristics
Socio-Economic Characteristics Number of Respondents % to Total
Sex
Male 303 60.6
Female 197 39.4
Age
<= 25 189 37.8
26 – 35 80 16.0
36 – 45 82 16.4
> 45 149 29.8
Education
Secondary 88 17.6
Degree 264 52.8
Post Graduates 148 29.6
Occupation
Student 189 37.8
Self-employed 90 18.0
Salaried 221 44.2
Place of Residence (Location)
Rural 282 56.4
Urban 218 43.6
Marital Status
Unmarried 223 44.6
Married 277 55.4
Family Income (Monthly)
Up to Rs.15000 138 27.6
Rs.15001-25000 103 20.6
Rs.25001-35000 84 16.8
> Rs.35000 175 35.0
Family Type
Joint 148 29.6
Nuclear 352 70.4
Total Sample 500 100.0
Source: Primary Data

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According to the table, there are 500 customers of BSNL in the sample as respondents. Out of 500
respondents, male constitute 60.6 per cent and female 39.4 per cent. While age is up to 25 years for
37.8 per cent, it is between 26 – 35 years, 36-45 years and above 45 years for 16.0 per cent, 16.4 per
cent and 29.8 per cent of the respondents respectively. The graduates are more constituting 52.8 per
cent of the total sample followed by post graduates with 29.6 per cent and secondary educated with
17.6 per cent. By occupation, it is understood that 44.2 per cent of the sample belongs to salaried
group, 37.8 per cent as students / home makers and 18.0 per cent as employed.
The married group (55.4%) outnumbers the unmarried customer group (44.6%). By monthly
income of the family, those with income above Rs.35000 higher comprise 35.0 per cent of the total
sample followed by the respondents with income up to Rs.15000 (27.6%), Rs.15001-25000 (20.6%)
and those with income between Rs.25001-Rs.25000 (16.8%). Majority of the customers in the study
area are living in nuclear families (70.4%) and those from joint family’s amount to 148 out of 500
(29.6%).
The period of having mobile phone is explored by frequency distribution and percentage analysis
and results of which are exhibited in Table2. As per the table, more than 50 per cent (51.6%) of the
customers in the sample have stated that they use mobile phone for 4-9 years while the mobile phone is
used for more than 9 years by 37.6 per cent of the customers in the sample.
Table 2 Distribution of Respondents by Period of Having Mobile Phone
Period Number of Respondents % to Total
3 years 54 10.8
4 - 9 years 258 51.6
> 9 years 188 37.6
Only 10.8 per cent of the customers in the sample are found to have been using the communication
device for 3 years and below.
The relationship between customers’ socio-economic characteristics and period of having mobile
phones is explored by cross tabulation and chi-square analysis in order to expose the importance of
gender, age, education, occupation, area of residence, marital status, family income and family type in
determining the possession of mobile phones. The results of the analysis are displayed in Table 3. As
displayed in the table, more number male than female is found to be having the mobile for longer
periods (51.8% of male customers against 15.7 per cent of females have the device for more than 9
years) whereas number of female cases having the device for 9 years and below is more compared to
male counterparts. This difference is also found to be significant at 1 per cent level (χ2
= 74.29, p <
0.01).
Table.3 Relationship between Socio-Economic Characteristics and Period of Having Mobile Phones
Groups by Socio Economic Characteristics
Period (Years)
Chi-Square
3 4 – 9 > 9 All
Sex
Male
16 130 157 303 74.29**
(5.3) (42.9) (51.8) (100.0) df=2
Female
38 128 31 197
(19.3) (65.0) (15.7) (100.0)
Age
Up to 25 years
39 118 32 189
(20.6) (62.4) (16.9) (100.0)
26 – 35 years
7 45 28 80 91.87**
(8.8) (56.3) (35.0) (100.0) df=6
36 – 45 years
5 44 33 82
(6.1) (53.7) (40.2) (100.0)
Above 45 years
3 51 95 149
(2.0) (34.2) (63.8) (100.0)

457
Period (Years)
Chi-Square
3 4 – 9 > 9 All
Education
Secondary
5 55 28 88
(5.7) (62.5) (31.8) (100.0)
Graduate
41 145 78 264 36.42**
(15.5) (54.9) (29.6) (100.0) df=4
Post Graduates
8 58 82 148
(5.4) (39.2) (55.4) (100.0)
Occupation
Home maker / Student
30 118 41 88
(15.9) (62.4) (21.7) (100.0)
Self-Employed
7 45 38 264 36.07**
(7.8) (50.0) (42.2) (100.0) df=4
Salaried
17 95 109 148
(7.7) (43.0) (49.3) (100.0)
Location
Rural
51 153 78 282
49.67**
(18.1) (54.3) (27.7) (100.0) df=2
Urban
3 105 110 218
(1.4) (48.2) (50.5) (100.0)
Marital
Status
Unmarried
41 137 45 282 61.48**
(18.4) (61.4) (20.2) (100.0) df=2
Married
13 121 143 218
(4.7) (43.7) (51.6) (100.0)
Table.3 Continued…ups by Socio Economic
Characteristics
Period (Years)
Chi-Square
3 4 – 9 > 9 All
FamilyIncome
(Month)
Up to Rs.15000
29 86 23 138
(21.0) (62.3) (16.7) (100.0)
Rs.15001-25000
3 75 25 103 99.19**
(2.9) (72.8) (24.3) (100.0) df=6
Rs.25001-35000
7 46 31 84
(8.3) (54.8) (36.9) (100.0)
> Rs.35000
15 51 109 175
(8.6) (29.1) (62.3) (100.0)
Family
Type
Joint
27 83 38 282 19.55**
(18.2) (56.1) (25.7) (100.0) df=2
Nuclear
27 175 150 218
(7.7) (49.7) (42.6) (100.0)
Total Sample
54 258 188 500
(10.8) (51.6) (37.6) (100.0)
Figures in brackets are percentages to Row total. NS – Not Significant
***Significant at 1% level
The number of cases who have mobile phones for more than 9 years increases with increase in age
levels (16.9% of up to 25 years, 35.0% of 26 – 35 years, 40.3% of 36-45 years and 63.8% of the total
customers aged above 45 years). This is vice versa for possession of mobile phones for less than 9
years. This observed differences in period having mobile phone by age levels of the customers differ
significantly (χ2
= 91.87, p < 0.01). Somewhat same trend as observed by age levels can also be
observed by educational status of the respondents. The period of having mobile phones increase with

458
increase in educational status and decrease with decrease in educational status. Moreover, the observed
relationship between education and period of having mobile phones is significant statistically (χ2
=
36.42, p < 0.01).
When compared by occupational levels, a significant difference in period of having mobile phones
is observed (χ2
= 36.07, p < 0.01). Between rural and urban groups, 50.5 per cent of the urban
customers against 27.7 per cent of the rural customers is found to be having the device for more than
nine years whereas period of having the mobile phones for 4-9 years is found with 54.3 per cent of the
rural group against 48.2 per cent of the urban group and this difference is also significant (χ2
= 49.67, p
< 0.01). The similar difference is observed for period of having mobile phones between unmarried and
married customers groups (χ2
= 61.48, p < 0.01).
By family income levels, the period of having mobile phones is found to differ significantly (χ2
=
99.19, p < 0.01). The period of having mobile phones for more than 9 years is found with 16.7 per cent,
24.3 per cent, 36.9 per cent and 62.3 per cent and the period of having mobile phone for 4-9 years is
found with 62.3 per cent, 72.8 per cent, 54.8 per cent and 29.1 per cent of the respondents belong to
families with income up to Rs.15000, between Rs.15001-Rs.25000, Rs.25001-Rs.35000 and above
Rs.35000 respectively. Between joint and nuclear family groups, having the device for more than 9
years is found among more number of nuclear family customers whereas the 18.2 per cent of join
family customers against 7.7 per cent of nuclear family customers; and 56.1 per cent of joint family
customers against 49.7 per cent of nuclear family groups have the device for up to 3 years and between
4-9 years respectively. This differences in mobile phone usage period differ significantly between joint
and nuclear family customer groups (χ2
= 19.55, p < 0.01). In sum, from the entire inference, it is found
that the socio-economic characteristics of the customers such as sex, age, education, occupation, area
of residence (location), marital status, family income and family type, are important in determining the
period of having mobile phone devices in Nagapattinam district.
The mobile phone brand mostly used by the respondents is evaluated by the frequency and
percentage distribution analysis of their opinion and the results of the analysis are shown in Table 4.
Table 4 Distribution of Respondents by Mobile Phone Brand
Mobile Brand Number of Respondents % to Total
Nokia 269 53.8
Samsung 94 18.8
Micromax 70 14.0
LG 16 3.2
Motorola 15 3.0
Sony Ericson 13 2.6
Others 23 4.6
Source: Primary Data.
As shown in the table, the Nokia brand mobile phones are mostly used brand among 53.8 per cent
of the respondents in the sample (269 out of 500). Next to this, Samsung brand mobile is used by 18.8
per cent followed by 14.0 per cent of the respondents with Micromax brand mobile phones. The other
brand mobile phones, such as LG, Motorola and Sony Ericson are found with 3.2 per cent, 3.0 per cent
and 2.6 per cent of the respondents respectively. The users of mobile phones brand other than
mentioned above is found among 4.6 per cent of the respondents. Overall, it is found that the Nokia
brand is mostly used mobile phone brand followed by Samsung among the mobile users of
Nagapattinam district.
Table 5 is reported with results of the analysis distributing the respondents based on their opinion
about internet use.

459
Table 5 Distribution of Respondents by Internet Use
Internet Use Number of Respondents % to Total
Yes 423 84.6
No 77 15.4
As per the table, 84.6 per cent of the respondents have stated to be using internet in their mobile
phone and only 15.4 per cent of the respondents are not using such service. So, it is concluded the
internet usage through mobile phones is very high among the customers in Nagapattinam district.
The relationship between internet use and socio-economic status of the respondents is explored
statistically using cross tabulation and chi-square analysis. Table 6 is reported with the results of the
analysis.
Table 6 Relationship between Socio-Economic Characteristics and Internet Use
Internet Use
Chi-Square
Yes No All
Sex
Male
300 3 303 122.57**
(99.0) (1.0) (100.0) df=1
Female
123 74 197
(62.4) (37.6) (100.0)
Age
Up to 25 years
126 63 189
(66.7) (33.3) (100.0)
26 – 35 years
73 7 80 76.83**
(91.3) (8.8) (100.0) df=3
36 – 45 years
78 4 82
(95.1) (4.9) (100.0)
Above 45 years
146 3 149
(98.0) (2.0) (100.0)
Education
Secondary
74 14 88
(84.1) (15.9) (100.0)
Graduate
215 49 264 6.05*
(81.4) (18.6) (100.0) df=2
Post Graduates
134 14 148
(90.5) (9.5) (100.0)
Occupation
Home maker / Student
126 63 189
(66.7) (33.3) (100.0)
Self-Employed
87 3 90 75.14**
(96.7) (3.3) (100.0) df=2
Salaried
210 11 221
(95.0) (5.0) (100.0)
Location
Rural
232 50 282 2.70
(82.3) (17.7) (100.0) df=1
Urban
191 27 218
(87.6) (12.4) (100.0)
Marital
Status
Unmarried
157 66 223 62.27**
(70.4) (29.6) (100.0) df=1
Married
266 11 277
(96.0) (4.0) (100.0)

460
Internet Use
Chi-Square
Yes No All
FamilyIncome
(Month)
Up to Rs.10000
112 26 138
(81.2) (18.8) (100.0)
Rs.10001-20000
95 8 103 6.66
(92.2) (7.8) (100.0) df=3
Rs.20001-30000
72 12 84
(85.7) (14.3) (100.0)
> Rs.30000
144 31 175
(82.3) (17.7) (100.0)
Family
Type
Joint
130 18 148
1.69
(87.8) (12.2) (100.0) df=1
Nuclear
293 59 352
(83.2) (16.8) (100.0)
Total Sample
423 77 500
(84.6) (15.4) (100.0)
Figures in brackets are percentages to Row total. NS – Not Significant
**Significant at 5% level; ***Significant at 1% level
As reported in the table, 99.0 per cent of male customers against 62.4 per cent females access
internet through their mobile phones. That is, internet usage through mobile device (phones) is more
among male customers compared to female counterparts. Further, the difference in the extent of using
internet through mobile phone among male group is significantly higher than that of female customers
of mobile phones (χ2
=122.57, p < 0.01). By age levels, it is understood that there is no much difference
in the extent of using internet among those who are aged above 26 years but the use of internet through
mobile device is found among 66.7 per cent against 33.3 per cent of non-users among those aged up to
25 years. This difference by age levels is found to be significant at 1 per cent level (χ2
=76.83, p < 0.01).
The significant difference in use of internet through mobile phone is observed by difference in
educational status also (χ2
=6.05, p < 0.05). When compared by occupational levels, it is understood that
use of internet through mobile device is less among home maker / student group (66.7%) compared to
that of those who are self-employed (96.7%) and salaried (95.0%); and this difference across three
occupational groups is significant (χ2
=75.14, p < 0.01). On the other hand, the internet use through
mobile device is similar between rural and urban groups, joint and nuclear families as well as across
respondent groups with all levels of family income (Chi-square values are not significant statistically).
At the same time, use of internet by mobile device is significantly higher among married than
unmarried customers (χ2
=62.27, p < 0.01). Putting all together, it is concluded that internet use through
mobile phone is significantly associated with sex, age, education, occupation and marital status among
customers in Nagapattinam district.
The results of the analysis identifying the relationship between internet use and mobile net
connectivity are exhibited in Table 7. As exhibited in the table, the internet use is very high among the
customers of 3G mobile net connectivity according to 93.7 per cent of the respondents’ opinion. Next
to this, 86.1 per cent of the both 2G/3G net connectivity, 72.6 per cent of 4G and 66.7 per cent of 2G
net connectivity customers use internet through their mobile phones. That is, internet use is less among
2G net connectivity customers.

461
Table 7 Relationship between Internet Use and Mobile Net Connectivity
Internet Use
Chi-Square
Yes No All
2G 54 27 81
(66.7) (33.3) (100.0)
3G 223 15 238 43.37**
(93.7) (6.3) (100.0) df=3
2G / 3G 93 15 108
(86.1) (13.9) (100.0)
4G 53 20 73
(72.6) (27.4) (100.0)
Total Sample
423 77 500
(84.6) (15.4) (100.0)
Source: Primary Data; **Significant at 1% level
The difference in internet use with respect to mobile net connectivity is significantly statistically
(χ2=43.37, p < 0.01). So, it is found that there is significant association between mobile net
connectivity and internet use among mobile phone users of Nagapattinam district.
Table 8 displays the results of the analysis distributing the respondents by type of connection.
Table 8 Distribution of Respondents by Type of Connection
Type of Connection Number of Respondents % to Total
Pre Paid 455 91.0
Post Paid 45 9.0
As displayed in the table, most of the mobile phone users have pre-paid connection as stated by
91.0 per cent of the sample respondents. The post-paid connections are found with little number of
customers in the study area. Hence, it is deduced the pre-paid connection is the mostly used type of
connection in Nagapattinam district.
The contribution of socio-economic characteristics of the mobile phone users on their selection of
connection type between pre-paid and postpaid is explored by relating the linear composite scores of
socio-economic variables with type of connection. For this purpose, linear discriminant analysis is
used.
The discriminant analysis is a multivariate technique used to identify a variable which has unique
discriminating power on the dependent in the presence of other variables in the independent set. That
is, this technique is used to identify the socio-economic factors that are associated with type of
connection used.
The discriminant analysis first provide the results of the Chi-square test of successive roots
(functions) to show which discriminant canonical function gives better discrimination. The number of
successive roots tested by the analysis is the number of groups in the dependent variable minus one. If
the number of groups or categories is three, the number of discriminant function produced and tested
by the discriminant analysis is two.
The discriminant analysis produces standardized coefficients and factor structure matrix for each
variable in the independent set. The standardized canonical coefficients are like standardized beta
coefficients in the multiple regression analysis, which are comparable across variables, help identify
the degree of predicting power. On the other hand, the structure matrix, which is the correlation
between discriminant function and each of the variables, help identify an extent of relationship between
a variable and discriminant function. That is, it helps identify the relative importance of each predictor
variable in discriminating the groups. The results of the discriminant analysis for average monthly
usage value and socio-economic status are tabulated in the tables from 9 to 11.

462
Table 9 presents one discriminant function along with eigenvalues, canonical R, Wilks’ Lambda
and Chi-square values. The eigenvalue is nothing but the proportion of variance explained in the
canonical function. A large eigenvalue is associated with a strong function. A canonical R is a
correlation between the discriminant scores and the levels of the dependent variable.
There is only one discriminant function (as type of connection is two) with eigenvalue of 0.1295
and canonical correlation of 0.3386, which is significant at 1 per cent level (Wilks’ λ = 0.8854, χ2
=
60.14, p < 0.01). This indicates that there is significant difference in the linear combination of eight
socio-economic variables between pre-paid and post-paid users.
Table 9 Significance of the Discriminant Function Differentiating Respondents by Type of Connection
Based on Social Economic Variables
Function Eigenvalue
Canonical
R
Wilks’ Lambda Chi-Square df Level of Significance
0 0.1295 0.3386 0.8854 60.14 8 0.0000
*Significant at 5% level
Wilks’ Lambda indicates how good the power of the model in discriminating pre-paid users from
post-paid users. As the Wilks’ Lambda is 0.8854 (is not less but rather it is high), it is apparent that
11.46 per cent of the variation in discriminating the pre-paid users from post-paid users and vice versa
is accounted for by the socio-economic characteristics of mobile phone using customers.
Table 10 shows the group centroid, i.e., mean values on the discriminant function for respondent
group with pre and paid mobile connections.
Table 10 Mean Discriminant Scores (Centroid) for Respondent Groups with Pre and Post Connection
Type of Connection Canonical Function (0)
Pre Paid -0.1129
Post Paid 1.1429
From the means of discriminant scores, it is understood that the first function highly discriminates
the post-paid users (1.1429) from pre-paid user group (-0.1129) as the centroid values between two
category of the respondents is very apart from each other. The socio-economic variables that have
unique influence on type of connection is ascertained from standardized coefficients along with
structure coefficients. Table 11 reports the standardized coefficients and structure matrix for each one
of eight socio-economic variables in the independent set.
Table 11 Standardized and Structure Coefficients for SES Variables with Function Significantly
Discriminating Respondents by Type of Connection
SES Variables Standardized Coefficients Structure Coefficients
Sex -0.0163 -0.2285
Age -0.1314 0.3229
Education -0.0064 -0.0115
Occupation -0.1335 0.3467
Location -0.3034 -0.1813
Marital Status 0.9565 0.6446
Family Income -0.2485 -0.1694
Family Type -0.5792 -0.6410
From the perusal of the table, it becomes evident that the discriminant scores (linear composite
scores of socio-economic variables) of the function is mostly contributed by marital status and family
type. That is, the marital status and family type of the mobile phones customers are the dominant
factors in contributing the discriminant scores that differ between pre-paid and postpaid customer
groups. The same is reflected in the standardized coefficients also. From the observation of the

463
standardized coefficients, which are comparable across variables, it is apparent that the marital status
has very high power of group discrimination followed by family type negative sign of the coefficient.
While marital status has unique positive influence and family type has unique negative influence in
group discrimination. Relating the sign of the coefficients with that of group centroids, it is found that
use of post-paid mobile connection is significantly higher among married customers from joint families
whereas it is vice versa in respect of using pre-paid mobile connection.
4. CONCLUSION
In this chapter, an attempt has been made to empirically evaluate the respondents’ perception about
usage of BSNL mobile service and various aspects of mobile phones and mobile phone services along
with socio-economic characteristics as well as the effect of socio-economic characteristics on mobile
phone usage
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[2] Anderson CJ, Garbing WD (1998). “Structural equation modeling in practice: A review
and Recommended two step approach”, Psychol. Bull., 103(3): 411-423.
[3] Belk RW (1988). “Possessions and the Extended Self”. J. Consumer Res., 15: 139–168.
[4] Chauduri A, Holbrook MB (2001). “The chain of effects from brand trust and brand
affect to brand performance: the role of brand loyalty”. Mark. 65(2): 81–94.
[5] Doney PM, Cannon JP (1997). “An Examination of the Nature of Trust in Buyer-Seller
Relationships”. J. Mark., 61: 35–51.

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