SIT Journal of Management Vol. 1. No. 1. June 2012. Pp ... · investment in the sector. Bharti...

SIT Journal of Management

Vol. 1. No. 1. June 2012. Pp. 122- 139

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Factors Affecting Brand Value of Bharti Airtel and Customers’ Perception

towards Selected Telecom Service Providers: An Empirical Study

Mrinal Kanti Das1

Abstract

India is potentially one of the most exciting GSM markets in the world with the increase in

population growing roughly at 1.7 percent a year. India's telecommunications market has

undergone steady liberalization since 1994 when the Indian government first sought private

investment in the sector. Bharti Airtel, Hutch, Idea, Aircel, Spice and MTNL are the main GSM

providers and Reliance Communications and Tata Indicom are the main CDMA providers in

India. This paper is an endeavor to study factors affecting brand value of Bharti Airtel and also to

study customers’ perception towards some selected telecom service providers. The results of the

study are based on survey of 104 retailers selected from Nadia district of West Bengal by using

convenience sampling technique. The study brings out several useful findings and the more

important among them are –customers’ perception is more favourable towards Bharti Airtel than

that of other telecom service providers in Nadia district, and factors affecting brand value of

Bharti Airtel are - Reverse Problem, Helpline Problem, Promotion Problem, Scheme Problem

and SIM Activation Problem. This study also establishes that there is significant influence of

different brands of mobile telecommunication services and different types of recharge voucher

on the sale of service product.

Keywords: Branding, Telecom Industry, Scaling, Factor Loading, Normal Distribution

1 Assistant Professor, Centre for Management Studies, JIS College of Engineering, Kalyani, India.

M: 9433710231, E-mail: [email protected]


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Introduction

India has become the fifth largest country in terms of telecommunications network in the world

and the second largest among the emerging economies of Asia. It has the fastest growing mobile

market in the stagnant global scenario. Recently, the Indian telecom industry is slated to an

estimated contribution of nearly 1% to India’s GDP. As on Apr 2007 India has 167 million

mobile phone subscribers. Out of this 125 million are GSM users and 41 million CDMA users.

BSNL, Bharti Airtel, Hutch, Idea, Aircel, Spice and MTNL are the main GSM providers in

India. Reliance Communications and Tata Indicom are the main CDMA providers in India. They

are classified in three heads:

State owned companies - BSNL and MTNL

Private Indian owned companies - Reliance Infocom and Tata Teleservices

Foreign invested companies - Vodafone-Essar, Bharti Tele-Ventures, Escotel, Idea

Cellular, BPL Mobile, and Spice Communications

Airtel is the fifth largest telecom operator in the world with over 243.336 million customers

across 20 countries as of March 2012. It is the largest cellular service provider in India, with over

183.3 million subscribers at the end of May 2012. Airtel is the third largest in-country mobile

operator by subscriber base, behind China Mobile and China Unicom. Bharti Airtel and

Vodafone top the list with 28.26% and 23.63% Market Shares in India. Vodafone grew at a

faster rate, with an increase of 1.50% compared to Airtel’s increase of 1.27%. State sector

incumbent BSNL managed to get 4th place (Source: www.pluggd.in).

This study examined factors affecting brand value of Bharti Airtel in Nadia district of West

Bengal and also developed an interval scale to ascertain customers’ attitude regarding telecom

services considered for this study. For this study, retailers’ survey was undertaken with 104

retailers of Nadia district. This study also reveals the impact of different types of recharge

voucher for different brands of mobile telecommunication services on the sale of company’s

products.


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Objectives of the Study

The following are the specific objectives of the study:

1) To identify factors affecting brand value of Bharti Airtel

2) To develop interval scale for ranking different brands of mobile telecommunication

services resorting to some statistical tools.

3) To ascertain the impact of types of recharge (Voucher Card & LSO) for different brands

of mobile telecommunication services on the sale of company’s product.

4) To know the monthly SIM activation of different brands of mobile telecommunication

services.

Methodology

For this study five telecom service providers – Airtel, Vodafone, Docomo, Reliance Smart and

Uninor have been selected. This study is basically empirical in nature. As the study is

empirical in nature, primary data have been mainly used. Secondary data have also been

collected to know the telecommunication market practice in India. This study was carried out

on 104 retailers of different areas of Nadia district. For this survey convenience sampling

technique was used. A structured questionnaire was prepared and requisite information was

collected through personal interviews of retailers of telecommunication services. Data

collection period was limited to three months, from May to July 2011. To analyze data

collected for this study, Exploratory Factor Analysis, ANOVA, Paired Comparison Scale, and

Thurstone Case V Scale was administered. ANOVA was conducted using Excel and Factor

Analysis was conducted using SPSS 16.0.

Hypotheses for the Study

This study was conducted on the following lines of hypotheses:

H01: There is no significant influence of different brands of mobile telecommunication on the

sale of service products.

Ha1: There is significant influence of different brands of mobile telecommunication on the sale of

service products.


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H02: There is no significant influence of different types of recharge on the sale of service

products.

Ha2: There is significant influence of different types of recharge on the sale of service products.

Analysis, Results and Discussion

I. Reliability Measurement

Cronbach’s Alpha Scale was used as a measure of reliability and its estimated value is 0.785 that

reveals satisfactory level of scale reliability as satisfactory value is required to be more than 0.7

for the scale to be reliable.

Table 1: Reliability Statistics

Cronbach's Alpha N of Items

0.785 16

II. Identifying Factors affecting Brand Value of Bharti Airtel

To identify factors that affect brand value of Bharti Airtel, Exploratory Factor Analysis was

administered. The data was captured in a spreadsheet and transported to a software statistical

package (SPSS 16.0). The results of the factor analysis are shown below.

KMO and Bartlett's Test: The Kaiser-Meyer-Olkin measure of sampling adequacy was

adapted to test whether the partial correlations among items are small. Bartlett's test of sphericity

examines whether the correlation matrix is an identity matrix, which would indicate that the

factor model is inappropriate. The KMO measures the sampling adequacy which should be

greater than 0.5 for a satisfactory factor analysis to proceed further. Both tests (Table 2) give

satisfactory results.

Table 2: KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.644

Bartlett's Test of Sphericity Approx. Chi-Square 1136.596

df 120.000

Sig. .000


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In this study, questionnaire, designed for factor analysis, consisted of 16 statements and the

respondents were asked to indicate their degree of agreement with these on a seven point scale

(1=strongly disagree, 5=strongly agree). Table 3 reflects the statements used for factor analysis.

Table 3: Statements Related to the Factors affecting Brand Value of Bharti Airtel

Label Statements

S01 Once recharge by mistake to other number the recharged amount cannot be

reversed back which is termed as reverse problem

S02 Reverse problem leads to monetary loss to retailer

S03 Reverse problem affects profitability of Airtel heavily

S04 The sign boards and promotional instrument are not adequately distributed

S05 The brand name of Airtel is unable to occupy a distinct place in the minds of

buyers for improper visibility

S06 Promotional problem occurs after change of symbol

S07 Problems arising out of inadequate distribution of promotional instruments

affect the sale adversely

S08 Total number of activation decreases due to deactivation of SIM card after 2 to 3

days of activation of new connection

S09 The activation time is longer than that of other Telecom Services.

S10 Aged customers prefer Airtel SIM to young customers.

S11 There is no tariff cutter scheme like other connections

S12 Non availability of tariff cutter scheme heavily affects the sale to young

generation

S13 Less variety of Schemes is one of the reasons of less profitability and sale

S14 The Retailer and Customer Service Care Executives take long time to respond.

S15 The complaints of customers and retailers are not resolved as per requirement

S16 Customer care problem heavily affects the customer Service.


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Correlation Matrix: The correlation matrix was computed and examined. Correlation matrix

was constructed using primary data, which has been presented in Table 5. The correlation matrix

revealed that there is a strong positive correlation between the statements. These statements were

considered appropriate for factor analysis procedure.

Anti-Image Correlation Matrix: The anti-image correlation matrix contains the negative values

of the partial correlation coefficients. Most of the off-diagonal elements should be small in a

good factor model. Anti-image correlation matrix was developed and presented in Table 6. This

matrix shows that partial correlations among the statements are low. Similarly, most of the off

diagonal elements are small, indicating that real factors exist in the data, which is necessary for

factor analysis.


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Table 4: Total Variance Explained

Component Initial Eigen values Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %

1 4.141 25.882 25.882 4.141 25.882 25.882 2.815 17.593 17.593

2 2.700 16.875 42.757 2.700 16.875 42.757 2.708 16.924 34.517

3 2.506 15.661 58.418 2.506 15.661 58.418 2.631 16.445 50.962

4 1.661 10.383 68.801 1.661 10.383 68.801 2.153 13.457 64.419

5 1.219 7.616 76.417 1.219 7.616 76.417 1.920 11.998 76.417

6 .850 5.315 81.732

7 .672 4.202 85.933

8 .623 3.892 89.825

9 .447 2.793 92.619

10 .365 2.283 94.902

11 .243 1.519 96.421

12 .192 1.198 97.619

13 .162 1.015 98.634

14 .105 .659 99.293

15 .069 .434 99.726

16 .044 .274 100.000

Extraction Method: Principal Component Analysis.


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Table 5: Correlation Matrix

Correlation S01 S02 S03 S04 S05 S06 S07 S08 S09 S10 S11 S12 S13 S14 S15 S16

S01 1.000 .841 .939 .038 -.017 .124 .217 -.047 -.071 .159 .115 .070 .064 .118 .200 .257

S02 .841 1.000 .870 -.017 .021 .074 .096 -.044 -.023 -.032 .115 .110 .057 .158 .216 .273

S03 .939 .870 1.000 .030 -.031 .089 .144 -.015 -.060 .091 .125 .080 .076 .084 .176 .239

S04 .038 -.017 .030 1.000 .556 .668 .510 .143 .083 -.020 -.022 .000 .039 .334 .275 .257

S05 -.017 .021 -.031 .556 1.000 .401 .415 .176 .136 .172 .023 .021 .119 .332 .284 .290

S06 .124 .074 .089 .668 .401 1.000 .560 .195 .162 .191 .085 .226 .196 .292 .286 .278

S07 .217 .096 .144 .510 .415 .560 1.000 .179 .072 .110 .109 .017 .186 .249 .319 .304

S08 -.047 -.044 -.015 .143 .176 .195 .179 1.000 .825 -.070 .389 .149 .215 .203 .179 .150

S09 -.071 -.023 -.060 .083 .136 .162 .072 .825 1.000 -.007 .407 .175 .318 .171 .146 .151

S10 .159 -.032 .091 -.020 .172 .191 .110 -.070 -.007 1.000 .097 .140 .192 .107 .093 .091

S11 .115 .115 .125 -.022 .023 .085 .109 .389 .407 .097 1.000 .503 .606 -.120 -.053 .087

S12 .070 .110 .080 .000 .021 .226 .017 .149 .175 .140 .503 1.000 .405 -.126 -.119 -.027

S13 .064 .057 .076 .039 .119 .196 .186 .215 .318 .192 .606 .405 1.000 -.031 .050 .091

S14 .118 .158 .084 .334 .332 .292 .249 .203 .171 .107 -.120 -.126 -.031 1.000 .909 .815

S15 .200 .216 .176 .275 .284 .286 .319 .179 .146 .093 -.053 -.119 .050 .909 1.000 .802

S16 .257 .273 .239 .257 .290 .278 .304 .150 .151 .091 .087 -.027 .091 .815 .802 1.000


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Table 6: Anti-image Correlation Matrix

Anti-

image

Correlatio

n

S01 S02 S03 S04 S05 S06 S07 S08 S09 S10 S11 S12 S13 S14 S15 S16

S01 .713a -.182 -.728 .031 .108 .002 -.274 .109 -.061 -.223 -.059 .031 .097 -.062 .036 .028

S02 -.182 .667a -.469 .293 -.267 -.140 .040 .286 -.210 .418 -.101 -.106 .061 -.226 .088 .107

S03 -.728 -.469 .614a -.223 .109 .087 .196 -.289 .214 -.101 .102 .025 -.112 .258 -.136 -.161

S04 .031 .293 -.223 .573a -.438 -.555 -.156 .148 -.058 .349 -.120 .087 .082 -.283 .175 .148

S05 .108 -.267 .109 -.438 .684a .133 -.170 -.128 .053 -.299 .089 -.002 -.084 .015 .016 -.102

S06 .002 -.140 .087 -.555 .133 .687a -.283 -.074 -.026 -.254 .172 -.282 -.081 .075 -.061 -.067

S07 -.274 .040 .196 -.156 -.170 -.283 .716a -.201 .190 .022 -.009 .126 -.115 .230 -.209 -.124

S08 .109 .286 -.289 .148 -.128 -.074 -.201 .493a -.796 .233 -.261 -.023 .214 -.221 .053 .213

S09 -.061 -.210 .214 -.058 .053 -.026 .190 -.796 .567a -.114 .001 .061 -.229 .059 -.001 -.105

S10 -.223 .418 -.101 .349 -.299 -.254 .022 .233 -.114 .439a -.096 -.058 -.071 -.227 .106 .137

S11 -.059 -.101 .102 -.120 .089 .172 -.009 -.261 .001 -.096 .626a -.336 -.449 .251 -.036 -.292

S12 .031 -.106 .025 .087 -.002 -.282 .126 -.023 .061 -.058 -.336 .694a -.127 -.035 .094 .017

S13 .097 .061 -.112 .082 -.084 -.081 -.115 .214 -.229 -.071 -.449 -.127 .673a .061 -.125 .055

S14 -.062 -.226 .258 -.283 .015 .075 .230 -.221 .059 -.227 .251 -.035 .061 .627a -.740 -.471

S15 .036 .088 -.136 .175 .016 -.061 -.209 .053 -.001 .106 -.036 .094 -.125 -.740 .740a -.106

S16 .028 .107 -.161 .148 -.102 -.067 -.124 .213 -.105 .137 -.292 .017 .055 -.471 -.106 .795a

a. Measure of Sampling Adequacy (MSA)


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Table 7: Rotated Component Matrix

a

Statements Component Commonalities

1 2 3 4 5

S01 .948 .929

S02 .932 .886

S03 .965 .944

S04 .875 .792

S05 .685 .534

S06 .815 .720

S07 .748 .607

S08 .881 .845

S09 .851 .828

S10 .540 .549

S11 .745 .731

S12 .715 .551

S13 .777 .644

S14 .929 .932

S15 .916 .902

S16 .869 .832

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 7 iterations.

The Principal Components Analysis (PCA) method was selected after determining the

appropriateness of the data set. In factor analysis, only factors having eigen values greater

than 1.0 are retained, the other factors are not included in the model. It is observed from

the table 4 that eigen value greater than 1.0 result in five factors being extracted. From

the cumulative percentage of variance, it is evident that five factors accounted for

76.417% of the total variance. This is a pretty good bargain, and thus, five factors appear

to be reasonable in this situation. Table 4 also shows commonalities which provide

relevant information after the desired number of factors have been extracted.


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An important output from factor analysis is the rotated factor matrix. The factor matrix

contains the coefficients used to express the standardized variables in terms of the factors.

These coefficients, the factor loadings, represent the correlations between the factors and

the variables. A coefficient with large absolute value indicates that the factor and the

variables are closely related. The coefficients of the factor matrix can be used to interpret

the factors. Here varimax procedure is adopted for rotation which is an orthogonal

rotation method that minimizes the number of variables with high loadings on a factor,

thereby enhancing the interpretability of factors.

Table 8: Naming of the Factors affecting Brand Value of Bharti Airtel

Factor

No.

Name of

Factors Label Statements

Factor

Loading

1 Reverse

Problem

S1

Once recharge by mistake to

other number the recharged

amount cannot be reversed back .948

S2 Reverse problem leads to

monetary loss to retailer .932

S3 These problem affects

profitability of Airtel heavily .965

2 Helpline

Problem

S14 The Retailer and Customer

Service Care Executives take

long time to respond. .929

S15

The complaints of customers and

retailers are not resolved as per

requirement .916

S16 Customer care problem heavily

affects the customer Service. .869

3 Promotion S4 The sign boards and promotional

instruments are not adequately .875


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Problem distributed

S5

The brand name of Airtel is

unable to create a distinct place

in the minds of buyers for

improper visibility

.685

S6 Promotional problem occurs

after change of symbol .815

S7

Problems arising out of

inadequate distribution of

promotional instruments affect

the sale adversely

.748

4 Scheme

Problem

S10 Aged customers prefer Airtel

SIM to young customers. .540

S11 There is no tariff cutter scheme

like other connections .745

S12 Non availability of tariff cutter

scheme heavily affects the sale to

young generation .715

S13 Less variety of Schemes is one of

the reasons of less profitability

and sale .777

5

SIM

Activation

Problem

S8

Total number of activation

decreases due to deactivation of

SIM card after 2 to 3 day of

activation of new connection

.881

S9

The activation time is longer

than that of other Telecom

Services. .851


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(i) Factor 1: Reverse Problem: The three variables identified under Factor 1 are Once

recharge by mistake to other number the recharged amount cannot be reversed

back (factor loading = 0.948), reverse problem leads to monetary loss to retailer

(0.932), and reverse problem affects profitability of Airtel heavily (0.965). These

three variables reflect reverse problem; hence, this factor is collectively referred to

as “Reverse Problem”. These three variables together explain 17.593% of the total

variance through Factor 1, which is the highest among all the factors.

(ii) Factor 2: Helpline Problem: Factor 5 is a combination of three variables i.e., the

Retailer and Customer Service Care Executives take long time to respond (0.929),

the complaints of customers and retailers are not resolved as per requirement

(0.916), and Customer care problem heavily affects the customer Service (0.869).

These three variables are highly correlated with each other and together explain

16.924% of the variation. As these three variables are problems of helpline; hence,

the factor comprising of these four variables is named as “Helpline Problem”.

(iii) Factor 3: Promotion Problem: Factor 2 is a combination of four variables i.e., the

sign boards and promotional instrument are not adequately distributed (0.875), the

brand name of Airtel is unable to create a distinct place in the mind of buyer for

improper visibility (0.685), promotional problem occurs after change of symbol

(0.815) and problems arising out of inadequate distribution of promotional

instruments affect the sale adversely (0.748). These four variables are highly

correlated with each other and together explain 16.445% of the variation. As these

four variables reflect problems regarding promotion, the factor comprising these

four variables is named as “Promotion Problem”.

(iv) Factor 4: Scheme Problem: Four variables are included under Factor 4 - Aged

customers prefer Airtel SIM to young customers (0.540), there is no tariff cutter

scheme like other connections (0.745), non availability of tariff cutter scheme

heavily affects the sale to young generation (0.715) and less variety of Schemes is


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one of the reasons of less profitably and sale (0.777). This factor explains 13.457%

of the variation and is labeled as “Scheme Problem”.

(v) Factor 5: SIM Activation Problem: This factor explains 11.998% of the total

variance. Total number of activation decreases due to deactivation of SIM card

after 2 to 3 day of activation of new connection (0.881), and the activation time is

longer than that of other Telecom Services (0.851) are highly correlated with each

other. These two variables show problem of SIM activation; hence, this factor is

named as “SIM activation Problem”.

III. Construction of Interval Scale (Thurstone Case V Scale) to rank of Different

Brands of Telecommunication Services

Table 9: Observed proportions preferring Brand X (Column of the table) to Brand Y

(Row of table)

Brands

(Y)

Preferred Brands (Brand X)

Airtel Vodafone Docomo Smart Urinor

Airtel - 0.13 0.27 0.39 0.03

Vodafone 0.87 - 0.4 0.63 0.07

Docomo 0.73 0.6 - 0.66 0.03

Smart 0.61 0.37 0.34 - 0.04

Urinor 0.97 0.93 0.97 0.96 -

(Source: Primary Data)

For developing above paired-comparison scale (Table 9), two brands were chosen at a

time and the respondents were forced to answer one alternative in each of the ten cases as

the maximum number of paired comparison was ten for this study. Finally, the responses


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were aggregated. These observed proportions will tend to imply the distance between

different brands.

To determine if the data set is normal, Kolmogorov-Smirnov Z test was performed and

results show the data are normally distributed. Under the assumption of normality, these

proportions can be interpreted as the distance between those two brands. For the basic

Case V, the frequency dominance matrix is translated into proportions and interfaced

with the standard scores. The scale is then obtained as a left-adjusted column marginal

average of this standard score matrix (Thurstone, 1927b). Using these proportions as

probabilities, ordinates for each proportion were obtained from any normal distribution

table. These ordinates are symbolically represented as Z values. In general, Z values have

a symmetric pattern around zero. If the proportion is less than 0.5, the corresponding Z

value has negative sign, and conversely, if the proportion is greater than 0.5, the Z value

is positive. In the next table (Table 10) Z values have been summarized.

Table 10: Thurstone Case V Scale

Brands (Y)

Preferred Brands (Brand X)

Airtel Vodafone Docomo Smart Uninor

Airtel - -1.13 -0.61 -0.28 -1.89

Vodafone 1.13 - -0.25 0.33 -1.48

Docomo 0.61 0.25 - 0.41 -1.88

Smart 0.28 -0.33 -0.41 - -1.75

Urinor 1.89 1.48 1.88 1.75 -

Total 4.11 0.27 0.61 2.21 -7

MEAN (Z) 0.82 0.05 0.12 0.44 -1.4

R*

(Case-V Scale

Value)

2.22 1.45 1.52 1.84 0


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RANK 1 4 3 2 5

Table 10 reflects that Airtel has been ranked first among five popular brands of mobile

telecommunication services considered for this study in Nadia district of West Bengal.

IV. Influence of different Brands of Mobile Telecommunication Services and

different types of Recharge Voucher on the sale of service product

Table 11: ANOVA Table

Source of

Variation SS DF MS F P-value F crit

Types of

recharge

4.28987E+11 1 4.28987E+11 18.82922 0.01226 7.708647

Brands 6.39092E+11 4 1.59773E+11 7.012805 0.042838 6.388233

Error 91132186000 4 22783046500

Total 1.15921E+12 9

As the critical value of F (4, 1) with = 0.05 is 7.7086 which is lesser than the calculated

value of F= 18.8292, we reject the null hypothesis that implies significant influence of

different types of recharge on the sale of service products.

On the other hand, it is found from the above table (Table 11) that the critical value of F

(4, 4) with = 0.05 is 6.3882 which is also lesser than the calculated value of F =

7.0128. So we have to reject the null hypothesis that indicates there is significant

influence of different brands of mobile telecommunication on the sale of service

products.


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V. Graphical Presentation of the Number of SIM activation per month

This study also presents number of SIM activation per month of different brands of

mobile telecommunication services (Figure 1). Figure 1 shows Airtel has got second

position and Reliance Smart has got first position in Nadia district. But customers’

perception shows different results where Airtel managed to get first position. This is due

to some attractive short term offers offered by Reliance Smart.

Figure 1: Number of SIM Activation per month

Conclusion

This study provides empirical evidence and has come up with more proof that perception

of the customers of Nadia district is more favourable towards Bharti Airtel than that of

other telecom service providers. The finding of this study has a significant relevance and

importance to management of the companies as well as academicians. This study has

proven that there is significant influence of different brands of mobile telecommunication

services and different types of recharge voucher on the sale of service products. This

study also discovered five factors that affect brand value of Bharti Airtel and these factors

are: Reverse Problem, Helpline Problem, Promotion Problem, Scheme Problem and SIM

Activation Problem. Thus, to sustain its position in the long run and to experience a

flourishing growth Bharti Airtel must consider factors affecting its brand value.

0

1000

2000

3000

4000

Number of SIM Activation

Airtel Vodafone Docomo Smart Uninor

Different Brands of Mobile Telecommunication


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Limitations of the Study

(a) The study covers a limited time period of three months starting from May, 2011 to

July, 2011. The results of this study are valid for this particular period and prediction

may not be reliable beyond this time period.

(b) This study is based on 104 retailers which may not represent the population and the

sampling technique used is convenience sampling, which has its own limitations.

(c) There may be errors due to biasness of the respondents.

(d) Lack of co-operation and support on the part of retailers may have been a major

constraint.

(e) The study was conducted in Nadia district, so the result of the study may not be

applicable to other areas.

Reference:

Thurstone, L. L. (1927b) “The method of paired comparisons for social values”, Journal

of Abnormal and Social Psychology, 21, 384-400.

Nargundkar, R. (2008), Marketing Research, Tata McGraw-Hill Education Pvt. Ltd.,

New Delhi, 3rd

Edn.

Bharti Airtel adds 2m mobile users in April'. The Times of India. 25 May 2012. Retrieved

25 May 2012.

http://www.airtel.in/QuarterlyResult/Quarterly_report_Q3_11 - accessed on 12/06/2012

http://www.apho2012india.org/about-the-hosts/about-india/communication - accessed on

14/06/2012

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