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8/9/2019 Sks Presentation
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THE DIFFUSION OFMOBILE PHONES IN INDIA
-
Dr. Sanjay K. Singh
Department of Humanities and Social Sciences
Indian Institute of Technology Kanpur
INDIA
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Mobile is becoming the dominant means for accessingcommunications primarily because deploying mobilenetwork is not only more cost-efficient but also mobile
provides greater flexibility and convenience to its
subscribers than landline telephone.
Growth in telephone subscriber base in India
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Growth in mobile-density has been phenomenal during thelast 5 years or so. Mobile-density in the country hasincreased more than 23-fold from 0.35 in 2000-01 to 8.12 in
2005-06.
Teledensity in India from 1995-96 to 2005-06
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There has been 25-fold increase in mobile subscriber base ina span of just five years from 2000-01 to 2005-06. During thesame period, mobile-density has increased more than 23-fold
from 0.35 in 2000-01 to 8.12 in 2005-06.
Growth in Mobile Subscriber Base in India
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An effective management of mobile services requires anunderstanding of the factors that underlie the evolution of the market. Factors such as market potential and timingand speed of adoption are of great importance for telecomoperators for capacity planning. Understanding theevolution of mobile phone market and its likely futuretrend is equally important for policy makers.
The main objective of this study is to analyze thediffusion of mobile phones in India to inform the larger discussion of managing the communication services as
well as to assist analysts concerned about assessing theimpact of public policies in the evolution of telecomsector.
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E stimation of the future trend and analysis of the pattern and rate of adoption of mobile phones in India.
S pread of a successful innovation over time typically follows asigmoid or S -shaped curve. During an early phase of diffusion only afew members of the social system adopt the innovation whereas, over time, due to network consumption externality and dissemination of information, many people opt for innovation as the diffusion processunfold. Finally, during the maturing phase, the rate of diffusion goes
down when diffusion curve approaches a saturation level.
Therefore, it is hypothesized that the growth in mobile-densityover time follows a sigmoid curve. Among various functional forms that can describe sigmoid curves ( the logistic, Gompertz,
logarithmic logistic, log reciprocal, simple modified exponential,etc. ), the first two are the most widely used ones. Therefore, it is decided to use these two functions to model and forecast thedevelopment of mobile-density in India.
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The logistic model can be written as:
where Md t is mobile-density (no. of mobile phones per 100inhabitants), (time)t is value assigned to time at period t, Eis the saturation level and I t is an error term.
All the parameters: E, F and K are positive.
Md t ranges from a lower asymptote of 0 to the upper boundE as time ranges from -g to +g. Maximum growth rate (=
EF/4) occurs when Md t = E/2 (i.e., at half of the saturationlevel). Thus, the logistic curve is rotationally symmetricabout its inflection point (the point at which maximum rateof diffusion takes place).
t t
t ti ed I
K
!
))(exp(1(1)
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Similarly, the Gompertz model can be written as:
where all the variables and parameters have their previousmeaning and Lt is an error term.
Again, all the parameters: E, F and K are positive. In this case,maximum growth rate (= EF/e) occurs when Md t = E/e (i.e.,at 37% of the saturation level).
These two models are estimated using non-linear least square method once by assuming no restriction on thesaturation level and then by imposing restrictions on thesame. This is because there is no guarantee that the final estimate of the saturation level, E , will be close to the global optimum (Heij C. et al., 2004).
t t t ti ed L FK ! )))(exp(exp( (2)
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The shape of logistic and Gompertz curves
0
20
40
60
80
100
120
1 8 1 5
2 2
2 9
3 6
4 3
5 0ime
M o
b i l e
- d e n s i t y
Logist ic (a=120, b=0.6, g=8000)
Logist ic (a=120, b=0.6, g=5000)
Logist ic (a=120, b=0.5, g=8000)
Logist ic (a=120, b=0.5, g=5000)
ompertz (a=120, b=0.15, g=15)
ompertz (a=120, b=0.15, g=20)
ompertz (a=120, b=0.20, g=15)
ompertz (a=120, b=0.20, g=20)
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The saturation level of mobile-density for a country is likely to dependon whether it is an early adopter or a late adopter of telephones. Earlyadopters (developed countries) are expected to have lesser reliance on
mobile phones (due to high switching cost) whereas late adopters(developing countries) are expected to have lesser reliance on mainline telephones (due to high infrastructure cost).
Teledensity and Percentage Share of Mobile in Selected Developed Countries
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Analysis reveals that the saturation level of mobile share in developedcountries could be anywhere between 50% and 70% whereas the samewould be between 80% and 90% for the developing countries.Assuming that the saturation level of teledensity could be anywhere
between 120 and 150 telephones per 100 inhabitants, the saturationlevel of mobile-density in developing countries is likely to be between100 and 120 mobile phones per 100 inhabitants.
Teledensity and Percentage Share of Mobile in Selected Developing Countries
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M odel estimationSince India is a late adopter of telephones, its saturation
level of mobile-density is likely to be between 100 and 120mobile phones per 100 inhabitants.
However, both logistic and Gompertz models are estimatedfor six different saturation levels (70, 80, 90, 100, 110 and120 mobile phones per 100 inhabitants) along with without
imposing any restriction on the same. The mean absolute percentage error (MAPE) for the last three observations isused to find out the most appropriate model and thesaturation level.
Annual data of mobile-density from 1995-96 to 2005-06 is
used for the estimation of the models.Data on mobile subscriber base and mobile-density is takenfrom Telecom Regulatory Authority of India (TR AI)
publications (www.trai.gov.in) and telecom sector databasefrom www.infraline.com.
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Estimation results (with t-statistic in parentheses ): According to both R 2 andMAPE, the Gompertz models fit the data better than the logistic ones. Asexpected, final estimate of the saturation level in the no restriction model doesnot seem to be globally optimal. It seems that the Gompertz model with the
saturation level of 120 mobile phones per 100 inhabitants is the best model todepict the diffusion of mobile phones in India.
Model Estimate
No restriction on the saturation level
ogistic (1) E = 18.9 (3.8), F = 0.7347 (11.0), K = 4331.2 (2.9); R 2
= 0.997; Adj. R 2
= 0.997; MAPE = 5.43
Gompertz (2) E = 217.9 (0.7), F = 0.1392 (3.1), K = 15.2 (8.7); R 2
= 0.997; Adj. R 2
= 0.997; MAPE = 4.70
Saturation level, E = 70
Logistic (1) F = 0.5970 (26.9), K = 5361.6 (4.3); R 2 = 0.995; Adj. R 2 = 0.996; MAPE = 5.12
Gompertz (2) F = 0.1954 (32.1), K = 18.6 (16.0); R 2
= 0.997; Adj. R 2
= 0.997; MAPE = 5.10
Saturation level, E = 80
Logistic (1) F = 0.5921 (26.6), K = 5895.6 (4.3); R 2 = 0.995; Adj. R 2 = 0.995; MAPE = 5.22
Gompertz (2) F = 0.1865 (32.6), K = 17.9 (17.0); R 2
= 0.997; Adj. R 2
= 0.997; MAPE = 5.04
Saturation level, E = 90
Logistic (1) F = 0.5883 (26.3), K = 6440.0 (4.3); R 2 = 0.995; Adj. R 2 = 0.995; MAPE = 5.30
Gompertz (2) F = 0.1793 (33.0), K = 17.4 (17.9); R 2
= 0.997; Adj. R 2
= 0.997; MAPE = 4.99
Saturation level, E = 100
Logistic (1) F = 0.5853 (26.1), K = 6991.4 (4.2); R 2 = 0.995; Adj. R 2 = 0.995; MAPE = 5.37
Gompertz (2) F = 0.1733 (33.2), K = 17.0 (18.6); R 2
= 0.997; Adj. R 2
= 0.997; MAPE = 4.94
Saturation level, E = 110
Logistic (1) F = 0.5828 (26.0), K = 7547.6 (4.2); R 2 = 0.995; Adj. R 2 = 0.995; MAPE = 5.42
Gompertz (2) F = 0.1683 (33.4), K = 16.6 (19.3); R 2
= 0.997; Adj. R 2
= 0.997; MAPE = 4.91
Saturation level, E = 120
Logistic (1) F = 0.5808 (25.8), K = 8107.2 (4.2); R 2 = 0.995; Adj. R 2 = 0.995; MAPE = 5.46
Gompertz (2) F = 0.1639 (33.6), K = 16.4 (19.9); R 2 = 0.997; Adj. R 2 = 0.997; MAPE = 4.88
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Assumptions and Projections of M obile-density in IndiaFurther analysis will primarily be based on the estimated Gompertzmodel at saturation level of 120 mobile phones per 100 inhabitants:
)(1639.04.16120
timeee Md
!
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Rate of growth of mobile-densityThe analysis reveals that the inflection point (the maximum growthrate point) of the curve will occur between 2011-12 and 2012-13
(when mobile-density will be around 45). During the year 2015-16,there will be 71 mobile phones for 100 people in the country. Analysisshow that the no. of mobile phones will exceed the no. of people inthe country by 2022-23.
0.4 .1
36.5
43.7
50.
57.
64.7
71.0
0
10
20
30
40
50
60
70
0
2000-01 2005-06 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16
N o . o f m o b i l e p h o n e s p e r 1 0 0 i n h a b i t a n t s
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Note: Future population of India is taken from the United Nations PopulationDivision publication.
F uture M obile Subscriber Base in India
4
90
433
526
620
715
808
899
0
100
200
300
400
500
600
700
800
900
1000
2000-01 2005-06 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16
N o
o f
o b i l s b s r i b
s ( i
i l l i o n )
It is pr o j t d that al ost 350 illion n w obil s bs r i b s will
b add d b tw n 2005-06 and 2010-11 and o than 450 illionwill b add d b tw n 2010-11 and 2015-16
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E stimates of revenues collected by mobile operatorsand the government
Average Revenue per Mobile User per Month in India
Mobile operators¶ revenue depends on ARPU and no. of subscribers
Assuming that the ARPU will stabilize at around Rs. 300 per month by the year 2010-11, mobile operators¶ revenues during the year
2010-11 and 2015-16 have been estimated
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E stimates of M obile Operators¶ Revenueo. o
mobilesubscribers
(in million)
obile
A per year
( s.)
evenues
rommobile
services( s. in
billion)
G
( s. in billion atactor cost at
current prices)
obile
revenue as a percentage o
G
2005-06 90 4500 405 32000 1.32010-11 433 3600 1559 57600 2.72015-16 899 3600 3236 103680 3.1
apid increase in mobile subscriber base and mobile spending
will have equally important implications or the government revenue
particularly in the orm o regulatory charges (license fee includinguniversal service obligation and spectrum charges) and ser vice tax.
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E stimates of the Government¶s Revenue
Presently, on an average, annual direct regulatory charges faced
by the operators in India is around 13% [far more than that inPakistan (4.5%), Sri anka (0.3%), Malaysia (6.5%), and SouthAfrica (5%)]. If we include the education cess of 2% (of 12%),service tax burden on the sector would be 12.24% from thefinancial year 2006-07 onwards.
stimates of the Government¶s evenueate of
regulatory
charges
(%)
evenue from
regulatory
charges
( s. in billion
at current
prices)
ate of
service tax
(excluding
education
cess of 2%)
(%)
evenue from
service tax
( s. in billion at
current prices)
Total revenue
( s. in billion
at current
prices)
2005-06 13 53 10 41 942010-11 10 156 12 187 3432015-16 10 324 12 388 712
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Concluding Remarks
In this study, the growth of the mobile phone and mobile-
density in India has been analyzed using S -shaped growth curvemodels.
The result shows that the Gompertz model adequately describesthe path of mobile phone diffusion in India.
The analysis shows that the high growth phase of the diffusionof mobile phones will continue till 2012-13.
It is estimated that there will be 71 mobile phones per 100inhabitants in India at the end of year 2015-16. The number of mobile phones will exceed the number of people in the country
by 2022-23.
Total mobile phone demand is projected to increase from 90million in 2005-06 to 433 million in 2010-11 and nearly 900million in 2015-16.
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Concluding Remarks «.
Rapid growth in mobile subscriber base in the India will have
important implications for revenues collected by the operatorsand the government.
Revenue collected by the mobile operators is projected toincrease from Rs. 405 billion (1.3% of GDP) in 2005-06 to Rs.1559 billion (2.7% of GDP) in 2010-11 and Rs. 3236 billion
(3.1% of GDP) in 2015-16.
The government¶s revenue from regulatory charges and servicetax will increase substantially due to rapid increase in operators¶revenue.
Revenue from regulatory charges is expected to increase fromRs. 53 billion in 2005-06 to Rs. 156 billion in 2010-11 and Rs.324 billion in 2015-16. Revenue from service tax is projected toincrease from Rs. 41 billion in 2005-06 to Rs. 187 billion in2010-11 and Rs. 388 billion in 2015-16.
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Concluding Remarks «.
It is quite likely that the rapid expansion of mobile services will
provide economic, logistic and strategic challenges to theoperators.
As operators expand coverage into urban, semi-urban, and ruralareas, they will be confronted with the daunting tasks of developing a countrywide infrastructure and improving and
maintaining the quality of service.Mobile operators should be ready with contingency plans todeploy and operate infrastructure including customer care,
billing, applications, etc., faster than that they might haveinitially planned.
Infrastructure providers, handset suppliers, and vendors shouldalso be geared up to respond to such plans.
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THA NK S