MOBILE PHONE SERVICES IN RURAL INDIA: ITS … Mobile Phone Services... · India is the second largest mobile market in the ... low tariffs and low handset prices. Indian ... 66 million

SAMZODHANA – “Journal of Management Research”

ISSN 2347 - 4270

Vol 6 Issue 1, April 2016

An International, Double-Blind Peer-Reviewed, Open-Access Journal

www.eecmbajournal.in 87

MOBILE PHONE SERVICES IN RURAL INDIA: ITS GROWTH AND USERS’

SATISFACTION

Dr. B. ANGAMUTHU M.Com, MPhil, Ph.D.

Assistant Professor of Commerce,

Kovai Kalaimagal College of Arts and Science,

Vellimalaipattinam, Narasipuram (po), Thondamuthur (via),

Coimbatore – 641 109, Tamilnadu, India

E-mail: [email protected]

Abstract

India is the second largest mobile market in the world. The rapid growth and

use of mobile phones has made the telecom companies like BSNL, Idea, Reliance,

Bharat, Vodafone, Airtel, Aircel, MTNL, etc. more conscious to provide world class and

best facilities to their customers in order to maintain their market. Also, these telecom

companies are coming up with new ideas and methodology to provide new and easy

services to their customers. This current research aims to measure the growth of mobile

phone services in the rural India and analyze the satisfaction level of mobile phone

users in the rural areas. Secondary data as regards mobile phone subscriber base has

been used for measuring the growth of mobile phone services during the study periods

from 2006-2007 to 2015-2016. It is reported that the rural subscriber base is steadily

increasing year by year and this study predicted that mobile phone subscribers in rural

areas has crossed to 532 million at the end of 31st March 2020 with compound annual

growth of 5% over the year 2015-2016. Self-designed questionnaire has been used to

collect data from various villages in Thondamuthur block of Coimbatore South Taluk,

Tamil Nadu. Multi-stage sampling technique is the most appropriate for the current

study. It is reported that 79.84% of the respondents are highly satisfied about mobile

phone services in the rural areas. The chi-square analysis reported that there is no

significant association between gender, age group, education, occupation, period of


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mobile phone usage of the respondents and their satisfaction level towards mobile

phone services.

Keywords: Mobile phone, Cell phone, Mobile technology, Rural areas, Mobile Services

Introduction and Execution of the Study

Mobile technology has very quickly become common among the people. There

were times when an individual dreamt of having own mobile phone as it was expensive

at the beginning. But as the world is getting advanced day-by-day, mobile and cell

phones technology is now the most common department of the advanced technology.

The mobile subscriptions across the world equal to the global population of 7.3 billion.

Among this growth, India and China alone constitute more than 2 billion mobile

subscriptions in the world. India continues to be one of the fastest growing major

telecom markets in the world. Over the last few years, the Indian government continued

its commitment to opening up the market to more competition and investment. This has

resulted in, among other things, low tariffs and low handset prices. Indian cellular

services are among the least expensive in the world. Early 2016, India has wireless

subscriber base 1026.66 million and the private companies held 91.38% market share of

the mobile phone subscribers whereas BSNL and MTNL, the two Public Sector Units

access service providers, had only a market share of 8.62%. According to TRAI reports

at the end of February 2016, India has 587.55 million urban and 439.11 million rural

mobile subscribers. The rural subscriber base accounts for 42.7% of all mobile

subscribers. As an affordable and accessible means of communication, both men and

women are realizing the potential of this technology to create economic opportunities

and strengthen social networks in rural areas. The mobile telephone is no longer just an

audio communication tool but capable of providing additional integrated functions.

Further, Mobile telephony effectively reduces the "distance" between individuals and

institutions, making the sharing of information and knowledge easier and more

effective. Mobile phones are the success story of bridging the rural digital divide,


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bringing tangible economic benefits and acting as agents of social mobilization through

improved communication.

Major players in Mobile Phone Service in India

The major players like Bharti Airtel (24.22%), Vodafone (19.16%), Idea

(17.01%), Reliance (9.93%) and BSNL (8.26%) has been contributing 78.58% market

share in the mobile phone service.

Bharti Airtel: The company has been established 7th

July’1995 as a Public Limited

Company, Headquartered in New Delhi and is a leading global telecommunications

company with operations presence in 20 countries across Asia and Africa. Moreover,

Bharti Airtel ranks amongst the top 4 mobile service providers globally in terms of

subscribers. In India, Bharti Airtel had 357 million customers across its operations at the

end of March 2016 and the company's product offerings include 2G, 3G and 4G

wireless services, mobile commerce, fixed line services, high speed broadband services,

etc. The company has its proportionate revenue touched with Rs. 2,50,000 million in the

FY 2015-2016.

Vodafone India: Vodafone India is a 100% subsidiary of Vodafone Group. It

commenced operations in 1994 when its predecessor Hutchison Telecom acquired the

cellular license for Mumbai. Brand Vodafone was launched in India in September 2007,

after Vodafone Plc. acquired a majority stake in Hutchinson Essar in May 2007. From a

single operation base with 31 million customers, the company has expanded its

operations across the country to cover all 22 telecom circles and given service to 180

million customers.

Bharat Sanchar Nigam Limited (BSNL): BSNL is the only service provider, making

focused efforts and planned initiatives to bridge the rural-urban digital divide in ICT

sector. In fact there is no telecom operator in the country to beat its reach with its wide

network giving services in every nook & corner of the country & operates across India

except New Delhi & Mumbai. BSNL was incorporated on 15th

September 2000. It took

over the business of providing of telecom services and network management from the

erstwhile Central Government Departments of Telecom Services (DTS) and Telecom


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Operations (DTO), with effect from 1st October’ 2000 on an going concern basis. It is

one of the largest and leading public sector units providing comprehensive range of

telecom services in India. Today, it has about 43.74 million line basic telephone

capacity, 8.83 million WLL capacity, 72.60 million GSM capacity, 37,885 fixed

exchanges, 68,162 GSM BTSs, 12,071 CDMA Towers, 197 Satellite Stations, 6,86,644

RKm. of OFC, 50,430 RKm. of microwave network connecting 623 districts, 7330

cities/towns and 5.8 lakhs villages.

Reliance Communications: Reliance Communications is India's foremost and truly

integrated telecommunications service provider. With over 150 million subscribers

across India, Reliance Mobile is India’s largest mobile service brand. Reliance Mobile

services now cover over 24,000 towns, 6 lakh villages, and still counting. Reliance

Communications corporate clientele includes over 39,000 Indian and multinational

corporations including small and medium enterprises and over 290 global, regional and

domestic carriers. Moreover, the company owns and operates the world's largest next

generation IP enabled connectivity infrastructure, comprising over 280,000 kilometers

of fibre optic cable systems in India, USA, Europe, Middle East and the Asia Pacific

region.

IDEA Cellular Network: Idea Cellular is an Aditya Birla Group Company, India's first

truly multinational corporation. Idea is the sixth largest mobile operator in the world. In

India, the company has subscriber base of over 165 million and is one of the top 3

mobile operators. Presently, the company has a deep rooted network across the length

and breadth of the country comprising of over 1,49,196 cell sites covering 7,513 towns

and 3,63,580 villages.

Statement of the Problem

Expansion of literacy rate, intervention of technology in democratization of the

market and growing role of women and children in purchase decisions of family have

helped marketers including mobile phone service provider to target greater surplus

income in the rural market more than in the urban market in recent years. This has

resulted into more players in the cell phone industry and the subscribers are provided


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with various innovations of cell phone services. But still the market for cell phone

services in rural areas has become very competitive due to poor area coverage, non-

existence of towers, over billing, abrupt call cuts, etc. The subscribers may be possible

to change their mobile phone service provider whenever they face such issues, retaining

their existing mobile number.

The above related issues raised the following questions in the minds of the

researcher. What is the level of growth on mobile phone services in rural India? What

are the factors that are responsible for discriminating the satisfaction level? Does an

association exist with regard to satisfaction level among various groups?

In order to find out the answers for the above raised issues the researcher has

undertaken this research work.

Objectives of the study

To find out the growth of mobile phone services in rural India.

To assess & analyze the satisfaction level of mobile phone users in rural areas

To explore the responsible factors on determinants of satisfaction level among

the users of mobile phone service

Hypotheses of the study

Null hypothesis: There is a slow growth of mobile phone services in rural India.

Null hypothesis: There is no significant association of satisfaction level among

various groups of respondents.

Methods and Materials

This empirical and analytical research used both secondary and primary data.

The secondary data related to mobile phone subscriber base helps to measure the growth

of mobile phone services in rural India and the related statistics have been collected

from official records of TRAI (Telecom Regulatory Authority of India) during the

periods of 2006-2007 to 2015-2016 (Upto February). The self-designed questionnaire

has been used to collect primary data from five villages in Thondamuthur Block of


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Coimbatore South Taluk. Totally, 250 questionnaires were distributed, 241 responses

were obtained from the respondents but based on the application of Discriminant function

only 124 responses were used for final study. Five villages, namely, Molapalayam,

Vadivelampalayam, Nathegoundenpudur, Naraseepuram and Ikkarai Boluvampatti were

selected using multi-stage sampling technique. Moreover, the researcher is familiar with

the selected villages. The primary data were collected during the period from

November’ 2015 to January’ 2016. The statistical tools like Trend analysis, Mean,

Compound Annual Growth Rate, Chi-square analysis and Discriminant function were

used to draw the conclusion.

Review of Literature

Arvind and Claudia Kubowicz (2013) in their study explored the switching

behavior of mobile service customers in the USA with a focus on service quality,

innovation and lock-in strategies as deterrents of switching. Chaitanya (2013) has

investigated customers' choice for the mobile phones with a right blend of features and

price. A survey conducted among 214 Indian undergraduate student mobile phone users

reveal their criteria for selecting mobile phone with maximum features and an

affordable price. Feature-wise comparison is also made between mobile phones of most

preferred companies. Mobile handset manufacturers and network providers can

implement customers' feedback and suggestions to improve their products or services.

Dhevika et al (2013) studied brand switching among cellular network service users and

found that users’ satisfaction is the main influencing factor for brand switching. Juha

(2008) investigated customers' intentions to purchase mobile communications services

and how these intentions are affected by the customers' price perceptions in the Finnish

mobile services market. The author indicated that there is a significant and positive

relationship that exists between customers' price perceptions and their purchase

intentions, and that the formation of price perceptions is significantly influenced by

satisfaction with pricing and services. Ramakrishnan et al (2008) aimed to address the

significance of product attributes in brand switching behaviour through multi-

dimensional scaling and results suggest that a set of product attributes trigger the


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intention to switch the current brand. Vijayakumar (2006) reported that the satisfaction

derived by the subscribers of Airtel Network has been influenced by the clarity of

signals, availability of plan options, low call charges and activation formalities. Revathy

et al (2005) found that the factors like lower service charges offered by Department of

Telecommunications (DOT) than other private players, convenience of contact,

accessibility, improvement of own business/profession, prestige and status symbol as

the influencing factors for the possession of cell phone connections. Nadine (2002) in

her study revealed that the various punctual reasons that motivate the use of the mobile

phone (such as, its functionality, its cost, its ease of access), as well as the type of

communications placed from a mobile phone. These reasons and communication types

all concur to make this device the support of fluid and flexible social interactions and

coordination. As to text messaging, it is considered as a medium in its own right, whose

use is largely governed by emerging social conventions. Oliver (1981) defined customer

satisfaction as the summary psychological state resulting when the emotion surrounding

disconfirmed expectations is coupled with the consumer’s prior feelings about the

consumption experience.

Analysis and Interpretation

Growth of Mobile Phone service in the Rural India

The growth of mobile phone services in rural areas can be measured through the

mobile phone subscriber base since 2006-2007 and it is discussed in brief. For this

purpose, the researcher has applied appropriate statistical tools. They are

Mean: The value is obtained by adding together all the items in the ‘X’ series

and then dividing the total number of observations (N). It can be find out through the

equation of ∑Х/N.

Trend analysis: The foremost objective of least-square trend analysis is to

measure the changes of data/observation between the periods and prediction of future on

the basis of past experience. The present research work focuses on secular trend analysis

among different components, because it studies the movements of data either upward or

downward or constant direction over a period of time using linear trend by the method


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of least squares. This is the best method for obtaining the trend values.

It provides a convenient basis for obtaining the line of best fit in a series. The line of the

best fit is a line from which the sum of the deviations of various points on either side is

zero (actual values of Y from the computed values of Yc). Further the sum of the

squares of the deviations of the actual values of Y and computed values of Yc is least.

So, it is called the method of least squares and line obtained by this method is called the

line of best fit or straight line trend and it is derived from the equation of Yc = a + bx

Where,

Yc = Trend values for a period

a= Y intercept / trend value at origin when X = 0

b = the amount of change in trend value per unit (i.e., per year)

x = Time unit (i.e., per year)

The current study covered the following three things

Origin (Mid-year) – 2011-2012

X unit – one year

Y unit – Mobile phone subscription

Moreover, the values of two constants ‘a’ and ‘b’ are estimated by solving the

following two normal equations.

∑Y = Na + b∑X and ∑XY = a∑X + b∑X2

Compound Annual Growth Rate (CAGR) : The CAGR is calculated by taking

the nth

root of the total percentage growth rate, where ‘n’ is the number of years in the

period being considered.

CAGR=(Ending Value/Beginning Value) (1/# of years)

- 1

Table - 1: Growth of Mobile Phone Services in Rural India (in

millions)

Year Subscribers

Actual

growth

Growth rate (in

%)

2006-2007 33.14 - -

2007-2008 62.28 29.14 87.93


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2008-2009 111.63 49.35 79.24

2009-2010 190.88 79.25 70.99

2010-2011 273.54 82.66 43.30

2011-2012 323.27 49.73 18.18

2012-2013 342.5 19.23 5.95

2013-2014 371.78 29.28 8.55

2014-2015 414.18 42.4 11.40

2015-2016 439.11 24.93 6.02

Mean 45.11

Source: Reports from Telecom Regulatory Authority of India

It could be collected from the Table -1that the mobile phone services according to

subscriber base in rural areas has reached at 439.11 million compared to 414.18 during

the previous year (2014-2015) indicating an increase of 6.02% over the year of 2014-

2015 but 18.11% over the year of 2013-2014. Whereas, the additional mobile phone

subscription has been tremendous growth during the study periods which is proved that

maximum of 82.66 million in 2010-2011 and minimum subscription of 19.23 million

during 2012-2013. This is followed by average mobile phone subscription in the rural

areas shows that 45.11 million during ten years study period from 2006-2007 to 2015-

2016. Moreover, AGR shows over a period of ten years are depicted in Table - 1. It can

be seen that growth was found to be maximum (87.93%) in the year 2007-2008 and the

minimum growth rate (5.95%) was noticed in the year of 2012-2013. Further, the

comparison of actual growth of additional mobile subscriber base has been increasing

trend compared with its expected growth from 2009-2010 to 2011-2012 and 2014-2015

(Refer Figure -2). The growth of mobile phone services with respect to its subscriber base

expected to be 532.31 billion in 2019-2020 with added subscriber of 93.2 million in the

next four years (Refer - 3) with a CAGR of 5% over the year of 2015-2016.


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www.eecmbajournal.in

0

20

40

60

80

100

2007-2008 2008-2009 2009-2010 2010-2011 2011-2012 2012-2013 2013-2014 2014-2015 2015-2016

in m

illi

on

s

Figure - 2: Actual and Expected Growth of Mobile Phone Subscription (in millions)

Actual Expected


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www.eecmbajournal.in

33.14 62.28 111.63

190.88 273.54

323.27 342.5 371.78 414.18 439.11 467.35 492.35 514.01 532.31

0

100

200

300

400

500

600

in m

illi

on

s)

Figure - 3: Growth of Mobile Phone Services in Rural India from 2006 -2007 to 2019 - 2020


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Personal profile of the Respondents

Distribution of the sample respondents based on their gender, age group (in

years), education, occupation, family income (Rs. per month), period of mobile phone

usage and possession of mobile network is given in the table below.

Table 2: Personal profile of the respondents

Factor Character % of the

Respondents

Gender Male 68.05

Female 31.95

Age group (in years)

Upto 25 11.20

26 - 50 66.39

Above 50 22.41

Education

No formal education (I-VIII) 22.41

School level (IX - XII) 39.00

Higher education 29.88

Technical education

(Diploma/Polytechnic) 8.71

Occupation

Employees (Public/Private) 27.39

Businessman 46.47

Professional 15.35

Others (Student/Home makers

/Agricultural labourers etc) 10.79

Family Income (Rs.

Per annum)

Upto 1,00,000 37.76

1,00,001 - 2,00,000 37.76

Above 2,00,000 24.48

Period of mobile

phone usage (in

years)

Less than a year 28.22

1 - 3 56.43

3 - 5 Years 9.13

Above 5 years 6.22


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Possession of mobile

network

Aircel 10.37

Reliance 42.74

Airtel 14.94

Vodafone 16.60

BSNL 15.35

Source: Primary data

It could be understood from Table 2 that the majority (68.05%) of the

respondents is male and the remaining 31.95% are female. Then, nearly 2/3rd

of the

respondents belong to middle age group (26-50 years), 22.41% of the respondents

belong to the age group of above 50 years and the remaining 11.20% of the respondents

belong to young age groups (upto 25 years). Majority (39%) of the respondents have

completed school education compared to higher education (29.88%), no formal

education (22.41%) and technical education (8.71%). This is followed by nearly half of

the respondents being businessman and then 27.39% are employees of

government/private sector. Equal percentage (37.76%) of respondents’ family income is

upto Rs.1,00,000 and between Rs. 1,00,001 to Rs. 2,00,000. More than half of the

respondents (56.43%) have been used for mobile phone between 1 - 3 years and

majority (42.74%) of the respondents have reliance network compared to Aircel

(10.37%), Airtel (14.94%), Vodafone (16.60%) and BSNL (15.35%).

Satisfaction Level of Respondents

Distribution of the respondents based on their satisfaction level is given in figure

4 and it is concluded that nearly 8/10th

of the respondents have higher satisfaction about

mobile phone services.


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Satisfaction level of the Respondents towards various factors

Table 3 shows the average satisfaction of various parameters between low and

high satisfaction groups. Under higher satisfaction groups, mean score of all the

parameters except tariff rates comes out greater than 3.4 and it can be concluded that the

respondents are satisfied about various services provided by preferred service provider.

Under lower level satisfaction, the respondents are dissatisfied about various services

except schemes and offers provided by their chosen mobile phone service provider.

Moreover, the calculated value of ‘f’ comes out lesser than the one percent level of

significant and all the factors included in this study has highly correlated and also the

lambda value shows greater than 0.5 which is concluded that the satisfaction level of

each factor were correctly classified.

Table 3: Satisfaction level of the Respondents

Factors

Satisfaction level

Wilks'

Lamda

F (df 1,

122)

Lower Higher

Mean SD Mean SD

Schemes & offers (f1) 3.640 1.381 4.667 0.515 0.773 35.768**

Service quality (f2) 2.160 1.463 4.010 1.199 0.738 43.332**

Network quality (f3) 2.440 1.446 4.303 0.952 0.667 60.775**

Availability of dealers (f4) 1.320 0.627 3.980 1.178 0.507 118.481*

20.16

79.84

Figure - 4: Satisfaction level of the Respondents (in %)

Low High


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*

Free calls/SMS (f5) 2.560 1.446 4.273 1.048 0.729 45.268**

Value added services (f6) 2.040 1.172 3.444 1.287 0.832 24.580**

Customer care service (f7) 2.680 1.492 4.424 0.809 0.660 62.985**

Tariff rates (f8) 1.480 0.770 2.889 1.449 0.847 21.969**

Advertisements &

Communications (f9) 1.280 0.542 3.091 1.464 0.768 36.762**

*Significant @ 5% and **Significant @ 1% level

Highly satisfied ‘5’, Satisfied ‘4’, Neutral ‘3’, Dissatisfied ‘2’, Highly dissatisfied ‘1’


Responsible factors on determinants of satisfaction level of the Respondents

Discriminant model were used to study the satisfaction level among respondents.

It is a statistical technique which allows to study the differences between two or more

groups with respect to several variables simultaneously and of classifying any object

into the group with which it is most closely associated and to infer the relative

importance of each variable used to discriminate between different groups and the

model is D = L1.f1 + L2.f2 +L3f3+L4f4+L5f5+L6f6 ……………….+ LK.fK,. The test

function was given below.

D= -6.868+0.352 f2+0.268 f3+0.473 f4+0.314 f5+0.283 f7+0.190 f9

% of variation explained: 100

Eigen value = 2.345

Wilks’ Lambda = 0.299

χ2

= 143.686** df = 6

Canonical correlation: 0.837

Classification of Respondents

Using the Discriminant function fitted and the observed predictor variables of

the respondents, the respondents are classified and the correct % of classification is

presented below:-


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Table 4: % of Correct Classification by using the Discriminant Function on

the Data

Satisfaction Low High

Low 25 0

High 0 99


From Table 4 it is observed that out of 25 respondents with lower satisfaction,

25 (100 %) were correctly classified; out of 99 respondents with higher satisfaction, 99

(100 %) were correctly classified Hence, the percentage of correct classification is

(124/124)*100 % or 100 % of original grouped cases are correctly classified. The

percent of correct classification of respondents using the observed observation clearly

indicates adequacy of the model in discriminating between the two groups namely,

lower and higher satisfaction towards mobile phone services. Moreover, the relative

importance of each predictor variable in discriminating between the two groups is

obtained and the results are presented below.

Table 5: Relative importance of Ratios in Discriminating between the satisfaction

groups

Factors Relative importance Rank

Service quality 17.23 II

Network quality 13.21 IV

Availability of dealers 33.29 I

Free calls/SMS 14.23 III

Customer care service 12.88 V

Advertisements & Communications 9.15 VI


Among the ratios under study, three variables namely, availability of dealers,

service quality of the service provider, and offering free calls/SMS are substantially


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important factors, in discriminating between groups of respondents namely with lower

satisfaction and with higher satisfaction.

Relationship of personal profile of the respondents and satisfaction level –

Application of chi-square analysis

The Chi-square test is an important test among the several tests of significance

developed by statisticians. It is statistically measured and used in the context of

sampling analysis for comparing an obtained variance to a theoretical variance. As a non–

parametric test, it can be used to evaluate the contingencies between two nominal measures. The

contingency may involve the comparison of two or more populations on a nominal

measure or two nominal variables. In the present study, the Chi-square test is used to

test the association between two attributes.

The chi-square statistic is carried out through the difference between the

observed and the expected frequencies in the cells of the contingency table using the

following formula.

χ2 = ∑ (Oi-Ej)

2 / EJ

Where,

χ2 = Pearson's Chi-square statistic

Oi = an observed frequency

Ei = an expected frequency

The table value of chi-square is calculated by (R-1) (C – 1) degree of freedom at

required percent level of significance whereas R and C denote Rows and Columns of the

contingency table. If the calculated χ2 value is greater than the table value, it is concluded

that there is a relationship between the two nominal measures and vice-versa.

Null Hypothesis (Ho): There is no significant association between gender, age

group, education, occupation, family income, period of mobile phone usage and

possession of mobile network of the respondents and their satisfaction level.

Alternate hypothesis (Ho1): There is a significant association between gender,

age group, education, occupation, family income, period of mobile phone usage and

possession of mobile network of the respondents and their satisfaction level.


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Table 6: Relationship of Personal profile of the respondents and Satisfaction level

Factor χ2 df Table value Result

Gender & Satisfaction level 2.143 1 3.84 Accept Ho and Reject

Ho1

Age group (in years) &

Satisfaction level 0.44 2 5.99

Accept Ho and Reject

Ho1

Education & Satisfaction level 3.667 3 7.81 Accept Ho and Reject

Ho1

Occupation & Satisfaction

level 1.222 3 7.81


Ho1

Family income (Rs. Per

annum) & satisfaction level 7.469* 2 5.99

Accept Ho1 and Reject

Ho

Period of mobile phone usage

(in years) & Satisfaction level 3.298 3 7.81


Ho1

Possession of mobile network

& Satisfaction level 10.697* 4 9.49

Accept Ho1 and Reject

Ho

* Sig. @ 5% and ** Sig. @ 1% level


Gender & Satisfaction level: Table 6 shows that the calculated value of χ2

is

2.143 which is lesser than the tabulated value of 3.84 at 5% significant level. Therefore,

accept the null hypothesis and reject the alternate hypothesis. Hence, it can be

concluded that there is no significant association between gender of the respondents and

their satisfaction level.

Age Group (in years) & Satisfaction level: It is obvious from table 6 that the

calculated value of χ2

comes out 0.440 which is lesser than tabulated value of 5.99 at 5%

significant level. Thus, accept the null hypothesis and reject the alternate hypothesis.

Finally, it can be concluded that there is no significant association between age group of

the respondents and their satisfaction level.


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Education & Satisfaction level: It could be collected from Table 6 that the

calculated value of χ2

comes out 3.667 which is lesser than tabulated value of 7.81 at 5%

significant level. So, accept the null hypothesis and reject the alternate hypothesis.

Therefore, it can be concluded that there is no significant association between education

of the respondents and their satisfaction level.

Occupation & Satisfaction level: Table 6 explains that the calculated value of

χ2

is 1.222 which is lesser than the tabulated value of 7.81 at 5% level of significance.

Therefore, accept the null hypothesis ad reject the alternate hypothesis. Hence, it can be

reported that there is no significant association between occupation of the respondents

and their satisfaction level.

Family Income (Rs. Per annum) & Satisfaction level: It is obvious from table

6 that the calculated χ2

value between family income of the respondents and their

satisfaction level is 7.469 which is greater than tabulated value of 5.99 at 5% level of

significance. So, accept the null hypothesis and it can be reported that there is a

significant association between family income of the respondents and their satisfaction

level.

Period of mobile phone usage (in years) & Satisfaction level: Table 6

explains that there is no significant association between period of mobile phone usage

of the respondents and their satisfaction level because the calculated value of χ2 (3.298)

is lesser than tabulated value (7.81) at 5% level of significance. Hence, accept the null

hypothesis and reject the alternate hypothesis.

Possession of mobile network & Satisfaction level: It is obvious from table 6

that calculated value of χ2

is 10.697 which is greater than tabulated value of 9.49 at 5%

significant level. Hence, accept the alternate hypothesis and it can be concluded that

there is a significant association between possession of mobile network of the

respondents and their satisfaction level.

Conclusion

From the study, we can observe that there is a rapid growth of mobile phone

subscription which shows yearly average mobile phone subscription in the rural areas


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crossed 45 million and totally, mobile phone services with respect to its subscriber base is

expected to be 532.31 billion in 2019-2020 with added subscriber of 93.2 million in

2019-2020. At present, 8/10th

of the mobile phone users in the rural areas are highly

satisfied with their preferred network. Availability of dealers, service quality and free

calls/SMS are substantially important factors on determination of satisfaction level of

the mobile phone users. Finally this study suggested that the Cell phone service

providers should try to reduce service charges for various value added services in order

to retain the existing customers and sustain growth.

References

1. Arvind, M., and Claudia Kubowicz, M., 2013. Exploring switching behavior of

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http://www.vodafone.in/

http://www.rcom.co.in/

http://www.ideacellular.com/

http://www.trai.gov.in/

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