Mobile Phone Service Provider- Uses and Problem

AbstractIn India there is an increasing convergence in perception about institutional structure, instrument and communication strategy in selecting a particular service. The Government’s dream of providing ‘urban service to rural areas will come true only if certain hindrances are removed. The education level of most of the cellular phone user is at least the matriculation. Income level of most of the cellular phone user is higher than the national per capita income. The cellular phone user show significant variation in respect of age, education, income, occupation, and residence. This study focuses on problems faced by the consumer and service expected from mobile service provider.

KEY WORDS : User, Service, Problem, Instrumentation, Communication

Introduction

India is competing for global leadership, and within a few decades the effort will become reality. Indian technological developments have largely been insulated from episode of global technological inconsistencies, and over the year, India has built resilience to shocks and now less vulnerable to output volatility. Technological level and education standard are steadily growing, and almost all the state governments and central government are heading toward a breakthrough in the field of communication technology. This will make the way for advanced consumer satisfaction in all the fields. There is an increase convergence in perception, institutional structure, choice of instrument and communication strategy in telecom policy making. The government’s dream of providing ‘urban service to rural areas’ will come true only if certain hindrances are removed.

This study is done during the month of March and April, 2009 in urban city of Tamil Nadu to understand the consumer preference for cellular preference for cellular phone services and problem they are facing. In depth study was undertaken to analyze preference pattern, problem of cellular phone services.

Objectives

To know how much people are aware about the mobile service they are using. To know which age people is maximum using mobile phone. To know how brand ambassador is affecting the people’s choice of selecting

mobile phone service. To know which channel is better for sales and advertisement. To know what are the basic problem peoples are facing in mobile service

Literature Review

In India cellular phone service provider are facing high competition. There are ten service provider who are providing service in India. Due to this they have to different every time to maintain their customer loyalty.

Roni Peleg(2003)- Major problem people are facing is connectivity problem. Mobile is very important part of peoples life, and they are so much depend on it for their daily routine and some other wok like consulting Physician.

Eric Ford in his research (2005) the major problem service provider are facing is arrangement of towers to get maximum profit.

Andrews, Edmund. L (The New York Times, 2006) Customer is more concerning about new service like TV in mobile phone, and many providers are also thinking about it. So to maintain their customer loyalty service provider should focus on better connectivity, with availability of recharge coupon, more advertisement, good scheme and should accurate in the choice of brand ambassador.

Andrews, Edmund L (2006) The Federal Communications Commission is expected to rule soon on whether to allow Fleet Call Inc to provide a new form of mobile telephone service. The ruling, should it be in favor of the company, will have far reaching effects on the cellular industry. Currently, regulations only allow two cellular companies to operate in a single city. The ruling would allow private radio service companies that cater to taxi fleets and delivery services, for example, to provide mobile telephone services to individuals. The FCC is said to be in favor of the scheme as this would open up the market to greater competition. The new services may have some drawbacks when compared to regular cellular systems and may turn out to be no cheaper, but critics of the current system claim that the competition factor alone should reduce market prices. Fleet Call would initially set up networks in only six major cities.

Sunitha, N.R. Ambedkar (2008) everyday cellphone service providers are growing like mushrooms after rain providing reliable facilities for customers to meet their budget. In view of the growing demand, service providers require the services of various local agents all over the world. The service providers must delegate the power to these agents to execute the services and monitor their performance. If found efficient the agents can continue to operate else they may need to be revoked.

S.A. Pandya ,Rajput (2008) Mobile networks reuse frequency bands based on a color map to increase the capacity of the network. A handoff should occur when a mobile unit moves from the influence of one base station with weaker signal into another's that has stronger

signal. Handoff behavior of all units is an important factor in quality of service of a mobile phone service. Handoff decisions, also called mobility decisions, are made by mobile phone based on the observed power from base stations. Premature, delayed or exceedingly sensitive decisions are considered poor decisions. Excessive poor decisions result in

degradation of service quality in otherwise a healthy mobile system.

Research Methodology

The study done in this research is of descriptive type where the 300 peoples were given the questionnaires to fill and then analyzing the results of the various responses given by the people with regard to the use and problem people are facing.

Various methods have been used in this study to find out the relationship between different variables. CHI SQUARE TESTS, ANOVA ONE WAY, KRUSKAL-WALLIS H-TEST, CORRELATION ANALYSIS has been used to find out these relationships between different variables according to the various responses given by the respondents.

Data Analysis & Interpretation

Correlation analysis

Relationship between age of people and frequency of recharge of sim by them.

1.000 .014

.014 1.000

. .808

.808 .

300 300

300 300

age

rchrgsim

age

rchrgsim

age

rchrgsim

PearsonCorrelation

Sig.(2-tailed)

N

age rchrgsim

Correlations

Inference- Value in this context is coming to be 0.014 which shows a low positive correlation between age and recharge sim by people.

Author also found that there is a low positive correlation between the ratio of advertisement of a Mobile service provider and customer intention to switch for another service provider.

Author also finds that there is a positive correlation between income of people and frequency of sim recharging by them. So more is the income more they will recharge.

Chi- square test

Association between liking of scheme by respondent provided by mobile service provider and frequency of sim recharge by respondent.

H0: There is no significant difference between schemes liking and frequency of sim recharge by customer.

300 100.0% 0 .0% 300 100.0%rchrgsim*schmulik

N Percent N Percent N Percent

Valid Missing Total

Cases

Case Processing Summary

Count

21 14 5 11 51

27 45 23 32 127

17 29 15 10 71

14 13 12 12 51

79 101 55 65 300

daily

1-10

10-20

20-30

rchrgsim

Total

lwdaily lwnyt freemsg lwstd

schmulik

Total

rchrgsim * schmulik Crosstabulation

14.266a

9 .113

14.359 9 .110

.504 1 .478

300

PearsonChi-Square

Likelihood Ratio

Linear-by-LinearAssociation

N of ValidCases

Value df

Asymp.Sig.

(2-sided)

Chi-Square Tests

0 cells (.0%) have expected count less than 5.The minimum expected count is 9.35.

a.

.022 .021 1.018 .309

.000 .000 .c

.c

.040 .039 1.018 .309

.015 .008 .143d

.016 .009 .103d

Symmetric

rchrgsimDependent

schmulikDependent

rchrgsimDependent

schmulikDependent

Lambda

GoodmanandKruskaltau

NominalbyNominal

ValueAsymp.

Std. Errora

Approx. Tb

Approx.Sig.

Directional Measures

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

.022 .021 1.018 .309

.000 .000 .c

.c

.040 .039 1.018 .309

.015 .008 .143d

.016 .009 .103d

Symmetric

rchrgsimDependent

schmulikDependent

rchrgsimDependent

schmulikDependent

Lambda

GoodmanandKruskaltau

NominalbyNominal

ValueAsymp.

Std. Errora

Approx. Tb

Approx.Sig.

Directional Measures

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null hypothesis.b.

Cannot be computed because the asymptotic standard error equals zero.c.

Based on chi-square approximationd.

.218 .113

.126 .113

.213 .113

300

Phi

Cramer's V

ContingencyCoefficient

Nominal byNominal

N of Valid Cases

ValueApprox.

Sig.

Symmetric Measures

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming thenull hypothesis.

b.

Inference:From the Chi-Square test output table, a significance level of 0.113 has been achieved. This mean the Chi-square test is showing significant association between two variables at 88.7% confidence level. Thus we can say that at 88.7% confidence level, SCHEME LIKE MOST and FREQUENTLY RECHARGE OF SIM BY CUSTOMER.

From Contingency coefficient of 0.213 it can be inferred that association between dependent independent variable is not significant as it is more closer to zero than One

From the lambda asymmetric value (with recharge sim dependent) of 0.000, it is not possible to predict relationship between scheme liking and recharge sim.

Cramer’s V is coming to be 0 .126 which is less than 0.25. Therefore there is a low relationship between two variables.

It is also found by author that there is significant difference between mobile service people are using and use of advertisement media by MSP. So use of media has equal effect on people choice of service provider. Author also found that there is no significant difference Income of people choice of using particular mobile service.

ANOVA Variance between income of the Respondents and maximum recharge by them available in market

Ho: There is no significance difference between income of people and maximum recharge by them.

216 1.97 .75 5.10E-02 1.87 2.07 1 4

37 1.95 .88 .14 1.65 2.24 1 3

36 1.58 .73 .12 1.34 1.83 1 3

10 2.20 .79 .25 1.64 2.76 1 3

1 1.00 . . . . 1 1

300 1.92 .77 4.47E-02 1.84 2.01 1 4

student

selfemployement

<2 lakh

2-4

>4

Total

incomemaxrchrgN Mean

Std.Deviation Std. Error

LowerBound

UpperBound

95% ConfidenceInterval for Mean

Minimum Maximum

Descriptives

216 1.97 .75 5.10E-02 1.87 2.07 1 4

37 1.95 .88 .14 1.65 2.24 1 3

36 1.58 .73 .12 1.34 1.83 1 3

10 2.20 .79 .25 1.64 2.76 1 3

1 1.00 . . . . 1 1

300 1.92 .77 4.47E-02 1.84 2.01 1 4

student

selfemployement

<2 lakh

2-4

>4

Total

incomemaxrchrgN Mean

Std.Deviation Std. Error

LowerBound

UpperBound

95% ConfidenceInterval for Mean

Minimum Maximum

Descriptives

6.222 4 1.555 2.652 .033

173.015 295 .586

179.237 299

BetweenGroups

WithinGroups

Total

maxrchrg

Sum ofSquares df

MeanSquare F Sig.

ANOVA

Inference:

From F probability valve in the ANOVA table is less than 0.05. Hence we conclude that there is no significant relationship between income of people and maximum recharge by them.

Author also found that there is no significance difference between incomes of people and frequency of sim recharge by them. So more is the income of people more they will do recharge. Author also found that there is no significance difference between education of people and choice of brand ambassador. Hence choice of brand ambassador by people is depend on their education.

Kruskal Wallis Test

Association between between the brand association used by different mobile service provider and its impact on people while choosing mobile service provider

Ho: Irrespective of different brand ambassador using by service provider it has equal impact on people’s selection of mobile service provider.

100 164.95

68 133.57

89 142.01

43 161.24

300

brndambscrckt

othrsport

film

model

Total

mobserviN

MeanRank

Ranks

7.560

3

.056

Chi-Square

df

Asymp. Sig.

mobservi

Test Statisticsa,b

Kruskal WallisTest

a.

GroupingVariable:brndambs

b.

Inference:

The value is coming to be .056 which is more than .05. Therefore null hypothesis is accepted. Hence all ambassadors have equal impact on people’s selection of mobile service provider.

Author also found that Irrespective of presence of other service provider if recharge is easily available customer will continue the use of particular service. So if service provider wants that customer should continue the use of service they should make it sure that recharge coupon are available all the time.

Discriminant Analysis

300 100.0

0 .0

0 .0

0 .0

0 .0

300 100.0

Unweighted CasesValid

Missing orout-of-rangegroup codes

At least onemissingdiscriminatingvariable

Both missingorout-of-rangegroup codesand at leastone missingdiscriminatingvariable

Total

Excluded

Total

N Percent

Analysis Case Processing Summary

51 51.000

51 51.000

127 127.000

127 127.000

71 71.000

71 71.000

51 51.000

51 51.000

300 300.000

300 300.000

age

income

age

income

age

income

age

income

age

income

rchrgsimdaily

1-10

10-20

20-30

Total

Unweighted Weighted

Valid N (listwise)

Group Statistics

Analysis 1

Summary of Canonical Discriminant Functions

.011a 80.1 80.1 .102

.003a 19.9 100.0 .051

Function1

2

Eigenvalue% of

VarianceCumulative

%CanonicalCorrelation

Eigenvalues

First 2 canonical discriminant functions were used in theanalysis.

a.

.987 3.870 6 .694

.997 .771 2 .680

Test ofFunction(s)1 through 2

2

Wilks'Lambda Chi-square df Sig.

Wilks' Lambda

1.347 -.455

-.638 1.271

age

income

1 2

Function

Standardized CanonicalDiscriminant Function Coefficients

.894* .449

.320 .947*

age

income

1 2

Function

Structure Matrix

Pooled within-groups correlationsbetween discriminating variablesand standardized canonicaldiscriminant functions Variables ordered by absolute sizeof correlation within function.

Largest absolute correlationbetween each variable andany discriminant function

*.

1.716 -.579

-.743 1.480

-2.865 -.849

age

income

(Constant)

1 2

Function

Canonical Discriminant FunctionCoefficients

Unstandardized coefficients

.179 -6.79E-02

-.102 -2.89E-02

1.504E-02 4.959E-02

5.353E-02 7.090E-02

rchrgsimdaily

1-10

10-20

20-30

1 2

Function

Functions at Group Centroids

Unstandardized canonicaldiscriminant functions evaluated atgroup means

Classification Statistics

300

0

0

300

Processed

Missing orout-of-rangegroup codes

At least onemissingdiscriminatingvariable

Excluded

Used in Output

Classification Processing Summary

.250 51 51.000

.250 127 127.000

.250 71 71.000

.250 51 51.000

1.000 300 300.000

rchrgsimdaily

1-10

10-20

20-30

Total

Prior Unweighted Weighted

Cases Used in Analysis

Prior Probabilities for Groups

12 34 0 5 51

13 102 3 9 127

13 51 1 6 71

8 36 2 5 51

23.5 66.7 .0 9.8 100.0

10.2 80.3 2.4 7.1 100.0

18.3 71.8 1.4 8.5 100.0

15.7 70.6 3.9 9.8 100.0

rchrgsimdaily

1-10

10-20

20-30

daily

1-10

10-20

20-30

Count

%

Originaldaily 1-10 10-20 20-30

Predicted Group Membership

Total

Classification Resultsa

40.0% of original grouped cases correctly classified.a.

Inference: Valve of wilks lambda ranges between 0 and 1 which is coming out to be0 .997 It means we cannot discriminate correctly between the grouping variable and the independent variableLevel of significance is coming out to be 69.40%. Two independent variables are income and ageFrom table it can be inferred that age is better predictor on frequently recharge of sim with a valve of 1.347

Discriminant function isY= -2.865+1.716 (age) - 0 .743 (income) Where Y is frequency of sim recharge by respondent.

Results andFindings It is found that ratio of students using mobile phone is more than any other. Majority of cellular phone user have studied more than metric levels. Income level of mobile phone users is higher than national per capita income. There is positive correlation between age and frequency of recharge, Ratio of

advertisement and loyalty of customer and Income of people and their frequency of recharging.

More frequently will be recharging if company will providing more better scheme. There is no much effect of advertisement on people’s choice of selecting mobile

service provider. There is no relation between people’s income and maximum recharge they do at a

time.

More the people are educated more they are concern about ambassador of service provider.

More is the income of people more frequently they will do recharge. If customer will feel any problem in getting recharge coupon, there is more

probability that they can switch to other service provider

ConclusionIn the era of information explosion, people are to be provided with quick and timely access to information. In India, there era ten cellular companies competing to provide efficient and quality services to customer. Government and private operators are competing at close margin and are trying to provide multiple valued added services to people hence the cellular operators should strive to provide cost effective quality equipment lesser charges for connectivity at various levels and connectivity based on consumer requirement this significance development in this field in the past ten years show that there is a very bright scope for expansion and modernization in cellular area with a very short span of time. Thus mobile phone service provider should rectify the problems faced by consumer to become a leading company in world.

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