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The Mobile Communication in Sri Lanka- A Case Study

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					 The Mobile Communication in Sri Lanka
                A Case Study




MASTER OF BUSINESS ADMINISTRATION IN
    INFORMATION TECHONOLOGY




                Rajendram Ahilan
               Registartion No: 09/9053
   Department of Computer Science & Engineering
              University of Moratuwa
                    April 2009
DECLARATION

I certify that this report does not incorporate, without acknowledgment, any material
previously submitted for a Degree or Diploma in any Universities or Institutions and to
the best of my knowledge and belief, it does not contain any material previously
published or written by another person or myself. I also hereby consent for my report, if
accepted, to be made available for photocopying and for interlibrary loans, and for the
title and summary to be made available to outside organizations.




----------------------
Rajendram Ahilan                                                   Date:……/……/…..




                                                                                        i
ABSTRACT


The Mobile Communication is the technology that allows the user to be connected while
on the move from home, office car or even from the sea. The technology is rapidly
growing in developing countries like Sri Lanka. It is considered to be particularly
important for the development of the nation.


In Sri Lanka, Mobile Communication has been expanded from high class people to low
class people as well. Interestingly, while cost is an important factor for poor low
economic class people, they seem to spend a substantial amount of their income on
mobile phones.


We believe that identification of Mobile Communication’s influence in Sri Lankan
market place could not only be identified by the quantitative analysis of the a sample
collections with respect to the determinants, but also using the qualitative analysis.


This report discusses the analysis of the Mobile Communication in Sri Lankan market
place. It covers this from the background of telecommunication economy, introduction of
mobile communication in Sri Lanka, how and why it has captured the market place and
how it is being evolved.


Keywords
Mobile Communication, Economic Class, Quantitative Analysis, Qualitative Analysis




                                                                                         ii
ACKNOWLEDGEMENT

I am very much indebted and extremely grateful to Mr Sivakumar Kandiah of Informatics
International to providing his support in case study and quantitative analysis by providing
the data.


I am also thankful to Mohan and Ranjith for their support in case study.


I would like to extend my gratitude to numerous others who helped in various ways.


This is my first step towards heights in the field.




                                                                                        iii
TABLE OF CONTENTS


Declaration                                                            i
Abstract                                                               ii
Acknowledgement                                                        iii
List of Tables                                                         v
List of Figures                                                        v


Chapter 1- Introduction                                                1


Chapter 2- Mobile Communication in Sri Lanka                           3


Chapter 3 – Case Study and Quantitative Analysis of
Determinants of Growth in Mobile Telecommunication
Industry in Sri Lanka                                                  6
3.1 Overview                                                           6
3.2 Case Study 1- Ranjith, a three wheel driver- in low class          6
3.3 Case Study 2- Mohan, a business man- in middle calls               7
3.4 Case Study 3- Siva, Manager of a software company- in high class   8
3.5 Quantitative Analysis                                              9
       3.5.1 Model Extrapolation                                       10
                  3.5.1.1 Task 01: Descriptive Statistics              10
                  3.5.1.2 Discussions                                  15
                  3.5.2.1 Task 02: Correlation Matrix                  16
                  3.5.2.2 Discussions                                  17
                  3.5.3.1Task 03: Multiple Regression Model            18
                  3.5.3.2 Discussions                                  21

Chapter 4- Conclusion                                                  22




                                                                             iv
v
LIST OF TABLES
  • Table 3.1 : The correlation matrix among average out going call charges per
    month in Sri Lankan Rupees (LKR), income or salary of the customers per month
    in LKR, sex of the customer, average incoming calls’ duration per customer in
    minutes and age of the customer in 2009.
  • Table3.1.1 Descriptive Statistics of the column, average out going call charges
    per month in Sri Lankan Rupees (LKR) for female customers
  • Table3.1.2 Descriptive Statistics of the column, average out going call charges
    per month in Sri Lankan Rupees (LKR) for Male customers
  • Table3.2.1 Descriptive Statistics of the column, income or salary of the female
    customers per month in LKR
  • Table3.2.2 Descriptive Statistics of the column, income or salary of the male
    customers per month in LKR
  • Table3.3.1 Descriptive Statistics of the column, Average incoming calls’ duration
    per female customer in minutes
  • Table3.3.2 Average incoming calls’ duration per male customer in minutes
  • Table3.4.1 Descriptive Statistics of the column, Age of the female customer in
    2008
  • Table3.4.2 Age of the male customer in 2008
  • Table3.5 Descriptive Statistics for all the customers columns, Average out going
    call charges per month in Sri Lankan Rupees, Income or salary of the customers
    per month in LKR and Average incoming calls’ duration per customer in minutes.
  • Table3.6 The correlation matrix among average out going call charges per month
    in Sri Lankan Rupees (LKR), income or salary of the customers per month in
    LKR, sex of the customer, average incoming calls’ duration per customer in
    minutes and age of the customer in 2008.
  • Table 3.7 Excel output for the data set.




LIST OF FIGURES
      Figure 2.1: Sri Lankan Mobile Operator Market Share
      Figure 2.2: The Graph Showing the Growth of Penetration Rate in Each Year
      from 2004 to 2008
      Figure 2.3: The Graph Showing the Growth of Number of Subscribers in Each
      Year from 1990 to 2009
      Figure 3.1 Chart for the table 2.5




                                                                                   v
Chapter 1- Introduction

This report emanates from the island of Sri Lanka- the land like no other, lies in Indian
Ocean. It is to the southwest of the Bay of Bengal and to the southeast of the Arabian
Sea. The area of the island is 65,610 km2. Sri Lanka has a population of 19.8 million [1].

The island became a plantation economy, famous for production of essences, rubber and
tea (which remains a trademark national export), in the nineteenth and twentieth
centuries. Then the nation has moved steadily towards an industrial economy with the
development of food processing, textiles, finance and telecommunications and Sri Lanka
with an income per head of $1,350 [2], still lags behind some of its neighbors including
Maldives and Mauritius but is ahead of its giant neighbor India. Its economy grew by an
average of 5% during the 1990s during the 'War for Peace' era [2]. According to the Sri
Lankan central bank statistics, the economy was estimated to have grown by 7% last
year, although inflation had reached 20% [2].

“IT IS now the dominant technological item with which young people define themselves.
What sort you have, how you handle it and how you customise it says a great deal about
you. You may even have more than one: a commuter workhorse for use during the week,
and a sportier model for the weekend. Your car? No, your mobile phone. The similarities
                   between the two are striking—and informative.”
          (Phones are the new cars; Nov 30th 2006; From the Economic print edition)

The mobile telecommunication is defined as the technology that allows the user to be
connected while on the move from home, office car or even from the sea.


The mobile communication networks are rapidly growing in developing countries like Sri
Lanka. It is considered to be particularly important for the development of the nation.
There are several reasons why mobile communication is considered important for the
nation’s development. The reasons are listed below:
   1) The benefits such as mobility and security to owners [3].
   2) Due to mobile communication’s characteristics, it is good leapfrogger: no need to
       rely on physical infrastructure such as roads and phone wires.




                                           -1-
   3) It requires only the basic literacy, and therefore is accessible to a large segment of
       population.
   4) Mobiles enjoy the technical advantages that make them particularly attractive for
       development.
   5) In addition to voice communication, the mobile communication assists in transfer
       of data which can be used in the context of applications for the purposes of health,
       education, commerce or governance.


In order to achieve the above listed benefits, like most of the countries in the developing
world, Sri Lankans have started to skip fixed-line infrastructure. Hence, the need of fixed
line connection is reduced vastly. The service providers like Sri Lanka Telecom (Sri
Lanka’s National Telecom) have started to provide mobile telecommunication services.
Currently mobile communication is the predominant mode of communication in Sri
Lanka. At the beginning of the twenty-first century, island’s mobile telecommunication
industry with mobile phone services, started to grow with 0.5 million subscribers and just
in nearly 10 years it has risen to 10 million subscribers with triple-play services [4].
Triple-play consists of Telephone, Cable TV and internet.


This report is organized as follows: Chapter 2 discusses the introduction of mobile
communication in Sri Lankan market; chapter 3 encompasses qualitative and quantitative
analysis of determinants of growth in mobile telecommunication industry in Sri Lanka;
and finally chapter 4 concludes the report.




                                              -2-
Chapter 2- Mobile Communication in Sri Lanka


The mobile telecommunication has been introduced in Sri Lanka in 1989, with the aid of
join venture program. The first cellular operator in Sri Lanka is Celltel. When the Celltel
was being first started, most of the Sri Lankan haven’t even heard about “mobile
phones”. They curiously looked at those “brick sized” pocket radio type equipment
carried by the upper class society. This equipment was known as “Celltel” making the
word “Celltel” synonymous with “Mobile Phone”, and “Celltel number” synonymous
with “Mobile Phone Number”. Due to the marketing failure the Celltel turns into Tigo.
For the analysis of how the market pioneer got failed in the market place, Celltel will be a
good example (Another case study area).


The Sri Lankan mobile telecommunication market place became competence when the
other service providers like Mobitel, Call Link (Now Hutch) and Dialog Telecom came
into the market place. In the recent past Airtel owned by an Indian has been introduced to
the Sri Lankan market place. The below Figure 2.1 depicts the Sri Lankan mobile
operator market share in 2008. The Dialog is the market pioneer now with the country’s
largest mobile phone network [4].




          Figure 2.1: Sri Lankan Mobile Operator Market Share
                                  Source: TRC of SL [4]




                                           -3-
In 1995, there were more phone lines in the western province of the nation than in the
entire island. In year 2004, the penetration is almost 11.6. Now it is almost 50 [4]. Below
Figure 2.2 shows the penetration rate from 2004 to 2008.




Figure 2.2: The Graph Showing the Growth of Penetration Rate in Each
                              Year from 2004 to 2008
                                  Source: TRC of SL [4]
Till the beginning of the 21st century, there were only half a million subscribers. After
that within next 10 years it became 11 million subscribers [4]. Below figure 2.2 depicts
the relationship of number of subscriptions in each year from 1990 to 2009.




                                           -4-
 Figure 2.3: The Graph Showing the Growth of Number of Subscribers
                         in Each Year from 1990 to 2009
                                Source: TRC of SL[4]


Mobile Communication is not limited to cellular phones, but also the connectivity to the
world from a laptop. Using the technology of Wimax and Wifi a user can connect to the
world using his mobile note books. In Sri Lanka this service is mostly gained by the high
class people from the laptop.




                                          -5-
Chapter 3 – Case Study and Quantitative Analysis of Determinants of
Growth in Mobile Telecommunication Industry in Sri Lanka
It has been identified that the income per capita is one of the determinants of growth in
mobile telecommunication industry, in the world. Other than this age and gender are also the
other factors which determine the growth. The Case Study and Quantitative Analysis have
been conducted to identify the characteristics of these determinants in Sri Lankan market.
Three case studies have been conducted with three different economic class’s personals. This
is to identify the each Sri Lankan economic group’s people’s opinion about the mobile
communication. The quantitative analysis has been conducted in three phases: data collection
and reduction phase, Model building and evaluation phase and analysis phase. Only the main
findings of the analysis have been presented here.


In Sri Lanka, Mobile Communication has been expanded from high class people to low class
people as well. Interestingly, while cost is an important factor for poor low class people, they
seem to spend a substantial amount of their income on mobile phones. It ranged from 4-8%
in Sri Lanka [3]. The government of Sri Lanka also have known the usage of mobile phones
in low class people like farmers and initiated a pilot project via the organization called Givi
Gnana Seva in Dambulla in 2003 [3]. This is to provide independent price collection and
dissemination service. Even though the role of the mobile phone was minimal here, the
results of the introduction of mobile phone services to the farmers succeeded. The farmers of
77%, who used the services, felt it helped get accurate price information [3].


3.2 Case Study 1- Ranjith, A Three Wheel Driver- In Low Class
Ranjith is a 32- year old three wheel driver in the city of Colombo driving hired three-
wheeler. He earns about 20,000 rupees per month. He has studied up to the ordinary level in
one of the government free schools.




                                             -6-
Good for Business…
He has given his mobile number to his customers and they call him for the pick ups. He said
that the mobile phone is good for his business. He gets text messages as well from his
customers. He doesn’t reply them but he uses to get the messages after a ‘ring-cut’ (dial and
disconnect before the callee pickup the call) to see his customer’s status while waiting after
dropping the customer. The ring-cut is an activity followed by most of the Sri Lankan to
convey the signal without the charge.


Easy
“Even early days, before the mobile phones come to the cheaper market, I have given my
land line number to my customers and they used to call me for any hires. But I had to call my
home from telecommunication centers to ask my wife about any calls for the hire. It’s easy
now because, I don’t have to go and find the telecommunication centers now.”- Ranjith


Security
Ranjith’s wife feels that, she feels comfortable and secured when her husband with his
mobile phone. For any emergencies, when ever she hears about the bomb blasts she used to
call her husband to find out his status.


3.3 Case Study 2- Mohan, A Business Man- In Middle Class
Mohan is running a telecommunication centre. He has fixed phone lines in his centre and
earns by giving phone calls to his customer.


Bad for Business
Mohan says that after the people has started to use mobile phones, he is not getting the
customers into his centre. In the early days he used to have about thirty to fifty customers per
day. Now it has been reduced to ten to twenty. He further said that, “Now everybody has a
mobile phone. They can make calls easily at lower cost. I lost my business because of this”.
He agrees with the advantages of the mobile phones, considering other factors such as easy
and security. He also has a mobile phone.




                                               -7-
Bad for Culture
Mohan complains that his daughter gets nuisance calls to her mobile. “Even though she says
that it’s unknown calls, I suspect that it should be from her boy friend. I wanted to get the
mobile from her, but couldn’t do that because of I wanted to have the update of her activities
time to time.” Mohan first started complaining about the mobile phone and then finished
saying that he needs it anyhow.


3.4 Case Study 3- Siva, Manager of a software company- in high class
Siva is a manager of a software company, managing his team of people who develop
software for mobile telecommunications.


My life is with Mobile telecommunication
“I’m eating because of the mobile communications. We have to evolve with the new
technology changes. There is no end for mobile telecommunication industries including the
software providers for telecommunications in this world because Mobile Communication has
captured its market place. If your business is down because of mobile phones, it’s your
mistake that you didn’t evolve with the technology changes.” Siva said this when he refutes
the Mohan’s statement.


From the above three case studies we can understand that, in Sri Lanka, mobile
telecommunication is not only a service that is being consumed by the Sri Lankan, but also it
is with their life. It has moved to all the economic classes of Sri Lanka. In Sri Lanka, mobile
phones and the connections are being given for cheaper rates than the fixed lines. It will need
to wait for longer to get the fixed line connections than a connection to mobile phones. There
could be advantages and disadvantages of mobile communications, but it’s like their partner
now.




                                             -8-
3.5 Quantitative Analysis
If you are finding difficulties in understanding some of the below statistical analysis, then
you can ignore the statistics sections and go to Main Findings.


The quantitative analysis has been conducted to identify the determinants: income, age and
gender, of mobile communication market place in Sri Lanka. The results of this analysis can
be used to identify the characteristics of the market place. In the first phase: ‘Data collection
Phase’, proper and correct data should be collected. This was the most challenging part for
me since the data are collected from four databases of four provinces: Western, Central,
Southern and Eastern, mobile customers. The data are indirect.


The ‘Data Reduction Phase’, since the data is collected from the database this phase has been
made easy by SQL queries. All the controls applied for the data are simply forced by the
SQL queries and filtered accurate data are collected (Assumed that computer wont make
mistakes).




                                              -9-
3.5.1 Model Extrapolation

Results
3.5.1.1 Task 01: Descriptive Statistics
Objective:                Describing a large collection of measurements with a few key
                          summary values.
Note:                     The Sample data collected for the analysis can be found in
                          Appendix A of this document.

Tables 3.1.1 and 3.1.2 show the descriptive statistics of the dependent variable; average out
going call charges per month in Sri Lankan Rupees (LKR) for customers who are females
and males respectively.

    Average out                             Average out going
 going call charges                          call charges per
  per month in Sri                         month in Sri Lankan
  Lankan Rupees                              Rupees (LKR)-
  (LKR)-Females                                   Males

Mean                           1102.949   Mean                         4349.173
Standard Error                 103.5504   Standard Error                347.815
Median                           816.19   Median                         2985.5
Mode                              575.5   Mode                         14207.74
Standard Deviation             1704.655   Standard Deviation           3950.419
Sample Variance                2905850    Sample Variance             15605811
Kurtosis                       50.48438   Kurtosis                     3.589771
Skewness                       6.761399   Skewness                     1.944908
Range                             15490   Range                        20104.25
Minimum                             203   Minimum                           287
Maximum                           15693   Maximum                      20391.25
Sum                            298899.1   Sum                          561043.3
Count                               271   Count                             129
Confidence                                Confidence
Level(95.0%)                    203.869   Level(95.0%)                688.2114

 Table3.1.1 Descriptive Statistics of      Table3.1.2 Descriptive Statistics of
 the column, average out going call        the column, average out going call
 charges per month in Sri Lankan           charges per month in Sri Lankan
 Rupees    (LKR)      for     female       Rupees (LKR) for Male customers
 customers


The ratio of female to male calls (ages>21) was 446.04(95% confidence interval [CI]
=203.869 to 688.2114). Therefore call rates about males were much higher than about
females. Since the number of females (271) in the data set is much higher than the males’


                                            - 10 -
count, the standard error of the statistics for males is much higher than the other. I couldn’t
avoid this situation; count of females>count of males) due to the authentication required from
the officials of the company where I got the data set.


The mean shows males are paying more than 3 times of amount for their out going call
charges than females. Since the skewness for both are getting positive values (6.761399 and
1.944908), it indicates that data are skewed right and the right tails is much longer relative to

the left tail for female data set than males. There fore the data are not normal. Positive
kurtosis indicates a “peaked” distribution for both the data. Please be informed that no
transformation done to make data normal and all the further forecasting done using this.


Tables 3.2.1 and 3.2.2 show the descriptive statistics of one of the independent variables;
Income or salary of the female and male customers per month in LKR

 Income or salary of                            Income or salary
      the female                                   of the male
    customers per                                customers per
   month in LKR                                  month in LKR

 Mean                           9132.841       Mean                        19922.48062
 Standard Error                 298.5368       Standard Error              812.4524735
 Median                            10000       Median                            20000
 Mode                               5000       Mode                              15000
 Standard Deviation             4914.535       Standard Deviation          9227.686265
 Sample Variance               24152658        Sample Variance              85150193.8
 Kurtosis                       5.460182       Kurtosis                    0.775235293
 Skewness                       1.697979       Skewness                     0.96232334
 Range                             35000       Range                             45000
 Minimum                            5000       Minimum                            5000
 Maximum                           40000       Maximum                           50000
 Sum                             2475000       Sum                             2570000
 Count                               271       Count                               129
 Confidence                                    Confidence
 Level(95.0%)                   587.7559       Level(95.0%)                1607.576005

   Table3.2.1 Descriptive Statistics of               Table3.2.2 Descriptive Statistics of
   the column, income or salary of the                the column, income or salary of the
   female customers per month in                      male customers per month in LKR
   LKR




                                             - 11 -
Same pattern of argument above is followed here as well for the variable Income or salary of
the female customers per month in LKR.
The ratio of female to male income (ages>21) was 1097.66 (95% confidence interval [CI]
=587.7559 to 1607.576005). Therefore income about males was much higher than about
females. Since the number of females (271) in the data set is much higher than the males’
count, the standard error of the statistics for males is much higher than the other.


The mean shows males are getting more than double amount as their salary than females.
Since the skewness for both are getting positive values (1.697979 and 0.96232334), it indicates
that data are skewed right and the right tails is much longer relative to the left tail for male
data set than females. There fore the data are not normal. Positive kurtosis indicates a
“peaked” distribution for both the data. For this variable’s data it seems that data are
normally distributed than the previously discussed dependent variable (AVG out going call
charges).


Tables 3.3.1 and 3.3.2 show the descriptive statistics of one of the independent variables:
average incoming calls’ duration per customer who are female and male respectively in
minutes
 Average incoming calls’                               Average incoming calls’
   duration per female                                   duration per male
  customer in minutes                                   customer in minutes

 Mean                           5583.155               Mean                         6727.38
 Standard Error                 141.0337               Standard Error               221.739
 Median                             5888               Median                          6574
 Mode                               6000               Mode                            9790
 Standard Deviation             2321.708               Standard Deviation         2518.471
 Sample Variance                 5390328               Sample Variance             6342696
 Kurtosis                       -0.01214               Kurtosis                   -0.70503
 Skewness                       -0.07505               Skewness                   -0.38494
 Range                              9805               Range                           9558
 Minimum                             200               Minimum                          450
 Maximum                           10005               Maximum                        10008
 Sum                             1513035               Sum                           867832
 Count                               271               Count                            129
 Confidence Level(95.0%)        277.6656               Confidence Level(95.0%)    438.7485

 Table3.3.1 Descriptive Statistics of                  Table3.3.2 Average incoming
 the column, Average incoming                          calls’ duration per male customer in
 calls’ duration per female customer                   minutes
 in minutes
                                              - 12 -
The ratio of female to male incoming call duration (min) (ages>21) was 1097.66 (95%
confidence interval [CI] =277.6656 to 438.7485). Therefore incoming call duration about
males was much higher than about females. Since the number of females (271) in the data set
is much higher than the males’ count, the standard error of the statistics for males is much
higher than the other.


The mean says incoming call duration of the male and female differs only by 17 hours
approximately, per month. Since the skewness for both are getting negative values(-0.07505
and -0.38494), it indicates that data are skewed left and the left tails is much longer relative to

the right tail for female data set than males. There fore the data are not normal. Negative
kurtosis indicates a “flat” distribution for both the data. For this variable’s data it seems that
data are normally distributed than the previously discussed dependent variable (AVG out
going call charges) and independent variable (Salary).


Tables 3.4.1 and3.4.2 show the descriptive statistics of one of the independent variables; age
of the female and male customers respectively in 2008


  Age of the female                                Age of the male
  customer in 2005                                customer in 2005

 Mean                     32.17712               Mean                    35.64341
 Standard Error           0.729056               Standard Error          1.016089
 Median                         27               Median                        34
 Mode                           22               Mode                          27
 Standard Deviation       12.00177               Standard Deviation      11.54055
 Sample Variance          144.0426               Sample Variance         133.1844
 Kurtosis                 1.088291               Kurtosis                -0.16722
 Skewness                  1.39671               Skewness                 0.71189
 Range                          45               Range                         45
 Minimum                        21               Minimum                       21
 Maximum                        66               Maximum                       66
 Sum                          8720               Sum                         4598
 Count                         271               Count                        129
 Confidence                                      Confidence
 Level(95.0%)             1.435357               Level(95.0%)            2.010506


Table3.4.1 Descriptive Statistics              Table3.4.2 Age of the male
of the column, Age of the female               customer in 2008
customer in 2008

                                              - 13 -
The ratio of female to male incoming call duration (min) (ages>21) was 1.722 (95%
confidence interval [CI] =1.435357 to 2.010506). Therefore age about males was little higher
than about females. Since the number of females (271) in the data set is much higher than the
males’ count, the standard error of the statistics for males is higher than the other.


The mean says ages of the male and female are almost similar. Since the skewness for male
is getting positive value (1.39671) and the other is getting negative value, it indicates that data
are skewed right for females and the left for males. There fore the data are not normal.
Negative kurtosis indicates a “flat” distribution for males’ data.




                    Average out      Income       Average
                    going call       or salary    incoming
                    charges per      of the       calls’
                    month in Sri     customers    duration
                    Lankan           per          per
                    Rupees           month in     customer
                    (LKR)            LKR          in minutes
 Mean                    2154.781       12612.5        5954.655
 Standard Error          152.2522      415.8132        122.1361
 Median                  1099.525         10000            6000
 Mode                    14207.74          5000            6000
 Standard
 Deviation               3045.045      8316.264        2442.722
 Sample Variance          9272299     69160244         5966891
 Kurtosis                11.13949      2.895237        -0.38195
 Skewness                3.195082      1.573173        -0.12444
 Range                   20188.25         45000            9808
 Minimum                      203          5000             200
 Maximum                 20391.25         50000           10008
 Sum                     861912.5       5045000        2381862
 Count                        400           400             400
 Confidence
 Level(95.0%)            299.3168     817.4585         240.1107

 Table3.5 Descriptive Statistics for all the customers columns, Average out going call
 charges per month in Sri Lankan Rupees, Income or salary of the customers per
 month in LKR and Average incoming calls’ duration per customer in minutes.




                                              - 14 -
          14000
          12000
                                                                 AVG Out Going Call
          10000                                                  Charges(LKR)
            8000                                                 Income or Salary

            6000                                                 Average Incoming
                                                                 calls' duration(mins)
            4000
            2000
                  0
                         Mean       SE         Standard CI
                                               Deviation

                           Figure 3.1 Chart for the table 2.5


Most of the people who are getting more than 10,000 rupees are having a mobile and
reaching 2000 LKR out going charges (without rentals). The customers are getting more
(even more than double) numbers of incoming calls than out going calls made.


3.5.1.2 Discussions
Summary of main findings
According to the table 3.1.1 and 3.1.2 out going calls are mostly made by males than females
and both the people are getting similar amount of incoming calls. But mobile
telecommunications revenue is mainly based on the out going call charges. Therefore males
should be the targeted customer group. The promotions, advertisements and the like should
mainly attract the males. And the people who are in thirties should be mainly targeted (See
table 3.4.1 and 3.4.2)


By comparing the incoming and outgoing calls’ behaviors of males and females, we can
come to an assumption that, females are receiving the calls that are made by males. The


                                           - 15 -
difference in salaries (males>females) also could be a factor for the difference in out going
calls made.


The mobile telecommunications can also try this to increase their income. That is the table
3.5 shows customers are getting more (even more than double) numbers of incoming calls
than out going calls made. Therefore they can decrease applicable out going call charge and
slight increment of incoming call charge. This could extend their popularity while keeping
the current revenue in constant. This will lead to increase the subscribers’ amount.



3.5.2.1Task 02: Correlation Matrix

Objective:              Investigating the relationships among average out going call
                        charges per month in Sri Lankan Rupees (LKR), income or salary
                        of the customers per month in LKR, sex of the customer, average
                        incoming calls’ duration per customer in minutes and age of the
                        customer in 2008 by examining the Correlation Matrix.




                                                            Average
                       Average out      Income             incoming
                        going call      or salary            calls’
                       charges per       of the             duration
                       month in Sri    customers              per      Age of
                         Lankan            per     Sex of customer       the
                         Rupees         month in     the       in    customer
                         (LKR)            LKR     customer minutes    in 2005
 Average out
 going call charges
 per month in Sri
 Lankan Rupees
 (LKR)                             1
 Income or salary
 of the customers
 per month in
 LKR                        0.602508            1
 Sex of the
 customer                   0.501287    0.607214            1
 Average
 incoming calls’            0.263806    0.270016      0.220708          1



                                             - 16 -
 duration per
 customer in
 minutes
 Age of the
 customer in 2008           0.086889    0.100107     0.136073   -0.02961          1

 Table3.6 The correlation matrix among average out going call charges per month in
 Sri Lankan Rupees (LKR), income or salary of the customers per month in LKR, sex
 of the customer, average incoming calls’ duration per customer in minutes and age of
 the customer in 2008.

The correlation matrix shows that the dependent variable average out going call charges per
month in Sri Lankan Rupees (LKR) has a moderate positive relation ship (0.602508) to the
independent variable income or salary of the customers per month in LKR and small relation
ship (0.501287) to the gender of the customer. The other two independent variables; average
incoming calls’ duration per customer in minutes and age of the customer in 2008 are having
weak relation ship to the dependent variable.


The independent variable income or salary of the customers per month in LKR has a
moderate positive relation ship (0.607214) to the independent variable Sex of the customer.


3.5.2.2 Discussions
Summary of main findings
The salary increments might increase the out going calls connected time. Telecommunication
companies can target the customer group who are earning higher salaries to increase their
income. This could be done by targeting the people who are holding credit cards. By
introducing new packages for the people who are having credit cards, this could be achieved.


The introduction of new packages targeting females with reduced income rates also could
attract female customers.




                                            - 17 -
3.5.3.1Task 03: Multiple Regression Model

                                      Investigating the relationships among the dependent variable
Objective:                            average out going call charges per month in Sri Lankan Rupees
                                      (LKR), and independent variables income or salary of the
                                      customers per month in LKR, sex of the customer, average
                                      incoming calls’ duration per customer in minutes and age of the
                                      customer in 2008 by examining the Correlation Matrix.


                        Scatter diagram for AVG Out Going Call Charges
                                           VS Salary

                        25000
   AVG Out Going Call
     Charges (LKR)




                        20000

                        15000
                                                                                  Series1
                        10000

                        5000
                           0
                                0   10000 20000 30000 40000 50000 60000
                                              Salary(LKR)


                                           Figure 3.1




                        Scatter diagram for AVG Out Going Call Charges
                                VS AVG Incoming calls duration

                        25000
   AVG Out Going Call
     Charges (LKR)




                        20000

                        15000
                                                                                  Series1
                        10000

                        5000
                           0
                                0   2000   4000   6000     8000     10000 12000
                                    AVG Incoming calls duration(min)


                                              Figure 3.2



                                                           - 18 -
                                         Scatter diagram for AVG Out Going Call Charges
                                                              VS Age

                                         25000
                    AVG Out Going Call




                                         20000
                         Charges




                                         15000
                                                                                                           Series1
                                         10000

                                         5000
                                               0
                                                   0              20         40           60        80
                                                                            Age


                                                                       Figure 3.3

                As mentioned, above the diagrams show that the dependent variable average out going call
                charges per month in Sri Lankan Rupees (LKR) has a moderate positive relation ship to the
                independent variable income or salary of the customers per month in LKR.
                Statistical model for multiple regressions could be explained by the population multiple
                regression function
                                    Y=b0+b1X1+b2X2…bkXk+ e
                                               Y is dependent variable
SUMMARY OUTPUT

      Regression Statistics
Multiple R         0.63319199
R Square          0.400932097
Adjusted R
Square            0.394865586
Standard Error     2368.75225
Observations                400

ANOVA
                                df                     SS                 MS                F       Significance F
Regression                                 4       1483307350          370826837.4       66.08941      9.02835E-43
Residual                                 395       2216339953          5610987.223
Total                                    399       3699647303

                  Coefficients                         Standard          t Stat         P-value      Lower 95%       Upper   Lower   Upper


                                                                                     - 19 -
                                    Error                                                        95%       95.0%      95.0%
Intercept       -1222.71037     474.1001622     -2.579012757       0.010269     -2154.785497   -290.635   -2154.79   -290.63
X Variable 1     0.16503918     0.018240164      9.048119525       6.68E-18      0.129179241   0.200899   0.129179   0.20089
X Variable 2    1325.588781     321.3948275      4.124486977       4.53E-05      693.7304737   1957.447   693.7305   1957.44
X Variable 3    0.121708874     0.050671464      2.401921397        0.01677      0.022089394   0.221328   0.022089   0.22132
X Variable 4    4.315582691     10.04242194      0.429735249       0.667623     -15.42769623   24.05886   -15.4277   24.0588
                                      bi where i=0 to k are regression coefficients
                                      Xi where i=1 to k are set of independent variables
                                      e is residual


                                          Table 3.7 Excel output for the data set.


               Here X Variable 1, 2, 3 and 4 are income or salary of the customers per month in LKR, sex
               of the customer, average incoming calls’ duration per customer in minutes and age of the
               customer in 2008 respectively.

               For the derived data set the estimated multiple regression equation is,

                                    Y= -12222.71+0.16X1+1325.58X2+0.12X3+4.31X4

               For the two values (0 and 1) of X2 the fitted equation becomes

                              Y= -12222.71+0.16X1+1325.58(0) +0.12X3+4.31X4 for females
               And
                              Y= -12222.71+0.16X1+1325.58(1) +0.12X3+4.31X4              for males

               The standard error of the estimate is

                      Sy.x’s=√ (SSE/ (n-k-1))

                               Here SSE is residual sum of squares, n number of observation and k is number
               of independent variable in the regression function

                               =√ (2216339953/ (400-4-1))
                               =2368.75
               It seems that average out going call charges are depended on some more independent factors.
               According to me those could be number of friends and family members, work type (busy
               hours) and the like. Unfortunately those details are not available in the data base where the
               data set is derived and only gathered from the questionnaires.




                                                               - 20 -
The coefficient of determination R² is given by

       R²=SSR/SST
               Where SSR is the variation explained by the predictor variables and SST is
       the total variation in response.
       =1483307350/3699647303
       =0.40
Here about 40% of the variation in average out going call charges is explained by the
regression, that is the relation of average out going call charges and income or salary of the
customers per month in LKR, sex of the customer, average incoming calls’ duration per
customer in minutes ,age of the customer in 2008. As I mentioned earlier there are other
factors those have the impact on the dependent variable here.


The F statistic and its p value clearly indicate the regression is significant.The regression
slope coefficient can be tested using the hypothesis test. In this case the large t statistics of
9.048119525 for income or salary of the customers per month in LKR variable X1 and its
small p value 6.68E-18 indicate coefficient of X1 is significantly different from zero (reject
H0:b1=0), Given the average incoming calls’ duration per customer in minutes variable X2
in the regression function, X1 can’t be dropped from the regression function. Similarly for
the big t value 4.124486977 for average incoming calls’ duration per customer in minutes and
its small p value indicate the coefficient of X2 is significantly different from zero(reject
H0:b2=0). Given X1 in the regression function, the X2 can’t be dropped from the regression
function. But except the others given the all three variables the variable age of the customer
in 2005 could be dropped and satisfies the hypothesis (reject H0:b4=0).


3.5.3.2 Discussions
Summary of main finding
As argued above it seems that average out going call charges are depended on some more
independent factors. According to me those could be number of friends and family members,
work type (busy hours) and the like. Unfortunately those details are not available in the data
base where the data set is derived and only gathered from the questionnaires.




                                             - 21 -
Chapter 4- Conclusion


The mobile communication technologies are rapidly growing in developing countries like
Sri Lanka. It is considered to be particularly important for the development of the nation.
At the beginning of the twenty-first century, island’s mobile telecommunication industry
with mobile phone services, started to grow with 0.5 million subscribers and just in
nearly 10 years, it has risen to 10 million subscribers [1].


In Sri Lanka, Mobile Communication has been expanded from high class people to low
class people as well. Interestingly, while cost is an important factor for poor low class
people, they seem to spend a substantial amount of their income on mobile phones.


The background of the mobile communication, its growth in Sri Lanka from the
introductory level, conducted Case Study and Quantitative Analysis to identify the
characteristics of these determinants in Sri Lankan mobile communication industry, are
also has been discussed in this report.




                                            - 22 -
Appendix A
AVERAGE_OUT_G INCOME(LKR) SEX                   Incoming( Age
OING_CALL_CHAR                                   Minuits)
    GES(LKR)
                                SEX(M-1|F-0)
              10000      F                  0       5566        22
381.67        5000       F                  0       2000        29
1801.2        10000      F                  0       6122        24
1506.71       5000       F                  0       4002        30
2388.04       15000      M                  1       6004        35
1686.74       10000      F                  0       5333        23
1471.55       5000       F                  0       3000        45
1078.01       10000      F                  0       6098        24
1676.5        10000      F                  0       4998        35
5102.87       25000      M                  1       8090        38
666.95        5000       F                  0       2500        32
573.34        10000      F                  0       1201        40
4161.5        20000      M                  1       7658        27
401.23        10000      F                  0       3009        51
802.5         5000       F                  0       4002        22
656.1         5000       M                  1       3002        21
364           15000      F                  0       4320        25
2868          15000      M                  1       8765        32
2069          15000      M                  1       6574        41
1298.2        10000      F                  0       7659        26
967.5         5000       M                  1       3402        32
1676.5        20000      M                  1       5674        25
1906.77       10000      F                  0       8000        22
1364.23       15000      F                  0       5002        33
1142.25       10000      M                  1       7770        36
2285.56       5000       F                  0       3006        39
1326.5        10000      F                  0       4500        40
2676          15000      M                  1       3432        37
579.6         20000      F                  0       5888        21
217.33        5000       F                  0       1009        63
305.66        10000      F                  0       5460        26
2946.77       15000      M                  1       9008        25
5563.18       25000      M                  1       8790        34
3501          20000      M                  1       6005        43
954.5         10000      F                  0       5667        22
1652.92       5000       F                  0       6000        29
733.76        5000       M                  1       3000        26
562.39        40000      F                  0       4556        33
322.5         5000       F                  0       5000        26
1830.2        10000      F                  0       9990        45
720.5         5000       M                  1       3245        24
223           5000       F                  0        600        64
714.11        5000       F                  0       6000        21
1830.2        10000      M                  1       4000        27
1109          10000      F                  0       6000        27
619           5000       F                  0       5009        22
14914      40000   M   1    9008   53
20391.25   15000   M   1    8990   35
15825.25   40000   M   1    9786   37
8593       30000   M   1    9008   33
2895       15000   M   1    5908   49
844.52     5000    F   0    4000   35
1073       10000   F   0    6009   33
5513.41    25000   M   1    8970   62
1301.47    10000   F   0    4000   52
1472.5     15000   F   0    6009   34
1652.92    20000   M   1    7658   52
3533.44    20000   M   1    8765   32
2319.06    15000   M   1    3009   27
4747.99    20000   M   1   10000   52
1544.6     10000   F   0    3009   32
320.29     20000   F   0     800   65
2399.5     15000   M   1    7564   42
575.5      5000    F   0    6000   24
550.16     10000   F   0    3000   30
816.19     5000    F   0    6009   26
741.4      15000   F   0    3000   52
3410       20000   M   1    7665   33
3250.08    5000    F   0    6000   31
575.52     10000   F   0    8799   22
7759.75    30000   M   1   10005   33
580.16     5000    F   0    6009   24
433.8      15000   F   0    5009   29
203.5      5000    F   0     450   66
948.54     5000    F   0    5004   22
865        20000   F   0    4009   32
282        5000    F   0    6555   22
2176.17    15000   M   1    8000   44
575.5      5000    F   0    5667   34
336.5      10000   F   0    7757   27
5144       25000   M   1    9998   38
603        5000    F   0    4563   35
2081.08    15000   M   1    7568   42
2418.5     20000   M   1    6000   22
1965.5     10000   F   0    3002   23
756        15000   F   0    6004   23
567.45     5000    F   0    9790   44
832.75     5000    F   0    6003   55
1063.8     30000   M   1    6000   23
270        5000    F   0    4003   27
964.5      15000   F   0    1003   24
732        5000    F   0    7594   52
1410.77    10000   F   0     432   46
3222.5     20000   M   1    5009   22
1589.15    10000   F   0    6787   31
3207.76    5000    F   0    3440   55
681        20000   F   0    6000   25
916.5      5000    F   0    5435   23
3207.76    20000   M   1    9990   42
9131.6     30000   M   1   10000   48
329        5000    F   0     800   57
630.33     5000    F   0    7896   25
1133.8     10000   F   0    6098   37
383        5000    F   0     200   45
630        20000   M   1   10003   57
657        5000    F   0    8007   21
260        10000   F   0     600   65
602.5      20000   F   0    7002   25
262.8      5000    F   0    6008   24
1273.7     10000   F   0    8007   53
460.5      5000    F   0    5009   31
510.31     10000   F   0    6908   29
550.3      15000   F   0    3465   59
4539.86    20000   M   1    2300   27
1028.31    10000   F   0    5566   22
364.5      5000    F   0    2000   29
3044.8     20000   M   1    6122   32
3248.25    10000   M   1    4002   30
590.5      5000    F   0    6004   35
480        5000    F   0    5333   23
2427.83    15000   M   1    3000   45
463        5000    F   0    6098   24
447.5      15000   F   0    4998   35
4539.86    5000    F   0    8090   38
1385       10000   F   0    2500   32
3090.5     20000   M   1    1201   40
243        5000    F   0    7658   27
866.59     10000   F   0    3002   23
1623.62    10000   F   0    6004   23
4242.5     20000   M   1    9790   44
397.4      5000    F   0    6003   55
835.72     15000   F   0    3432   37
590.27     5000    F   0    5888   21
2251.2     15000   M   1    7658   27
1209.5     10000   F   0    3002   23
1266       15000   F   0    6004   23
5085.25    25000   M   1    9790   44
4848       20000   M   1    6000   31
14393.25   40000   M   1    8799   43
2690.25    15000   M   1   10005   33
320.21     50000   M   1    6009   24
8202.25    5000    M   1    5009   29
2436.25    15000   M   1     450   66
10245.5    40000   M   1    5004   22
555.19     5000    F   0    4009   32
680.58     10000   F   0    6555   22
11738.5    5000    F   0    8000   44
580        15000   F   0    5667   24
6326       30000   M   1    7757   27
290.5      5000    F   0    9998   25
1081       10000   F   0    4563   35
877        5000    F   0    7568   23
248        10000   F   0    6000   22
230        5000    F   0    6004   23
680.58     5000    F   0    9790   44
368.75     5000    F   0    6000   31
464.5      15000   F   0    8799   22
2214       15000   M   1   10005   33
1001.04    10000   F   0    6009   24
203        5000    F   0    5009   29
770.8      10000   F   0     450   66
871.5      15000   F   0    5004   22
995.76     5000    F   0    1009   63
602.97     5000    F   0    5009   31
2198.21    15000   M   1    6005   33
508.86     5000    F   0    4003   29
1129.52    10000   M   1    6054   26
2445.5     15000   M   1    8769   26
1043       10000   F   0    4535   26
3049.11    15000   M   1    9990   45
2379       15000   M   1    3440   55
847        10000   F   0    6000   25
628.75     5000    F   0    5435   23
869.64     15000   F   0    9990   42
4016       20000   M   1    7770   36
926.5      5000    F   0    3006   39
1684.5     10000   F   0    4500   29
854.25     5000    F   0    3432   37
332.89     10000   F   0    5888   21
1431.84    10000   F   0    7658   43
307        5000    F   0    5009   23
1223.27    10000   F   0    6005   33
377.88     5000    M   1    4003   53
210.27     5000    F   0     598   53
1078.7     10000   F   0    5004   26
741.84     5000    F   0    4535   26
2264.3     15000   M   1    9990   45
629        5000    F   0    6785   24
1019.5     10000   M   1    3000   43
14207.74   40000   M   1   10008   34
1113.11    5000    F   0    4000   27
14207.74   40000   M   1   10000   34
14207.74   10000   M   1    5009   22
806        5000    M   1    9008   21
547.26     10000   M   1    8970   23
353        5000    M   1     790   46
1386.31    10000   M   1    6009   34
14207.74   5000    F   0    7658   24
265.5      5000    F   0    8765   21
1789.6     10000   F   0    6004   33
778.05     5000    F   0    6000   22
1052.41    10000   F   0    3002   23
1231.74    15000   F   0    6004   23
10144.2    40000   M   1    9790   44
1052.41    10000   F   0    6003   55
1252.1     5000    F   0    3432   37
941.1      10000   F   0    5888   21
403.4      5000    F   0    4000   26
726.4      15000   F   0    4556   25
245        5000    F   0    5000   26
1454.5     10000   F   0    9990   45
240.3      5000    F   0    6000   24
1052.41    40000   M   1    9870   64
17942.25   40000   M   1   10003   43
1904.5     5000    F   0    4000   27
497.1      5000    F   0    6000   27
1389.5     10000   F   0    5009   22
1078.7     10000   F   0    3432   37
1364       15000   F   0    7896   21
4777       20000   M   1    7869   63
1117       10000   F   0    5460   26
209.5      5000    F   0    8000   24
14419.25   10000   F   0    3432   37
9907       30000   M   1    5888   21
220.2      20000   F   0    4000   26
282        5000    F   0    4556   25
1122       10000   F   0    5000   26
6415.5     30000   M   1    9990   45
291        15000   F   0    6000   24
230.06     5000    F   0    9870   64
1435.5     5000    F   0   10003   43
3323       20000   M   1    4000   27
564        5000    F   0    6000   27
410.83     15000   F   0    5009   22
533.5      5000    F   0    3432   37
2205.5     15000   M   1    7896   21
480.45     5000    F   0    7869   63
808.5      5000    F   0    5460   26
3425.25    20000   M   1    8000   24
354.8      5000    F   0    3002   21
1705.4     25000   F   0    4320   25
1706.5     10000   F   0    8765   32
761.4      5000    F   0    6574   41
525        15000   F   0    7659   26
244        5000    F   0    3402   32
614.5      15000   M   1    5674   25
595        5000    F   0    8000   22
341.06     10000   F   0    5002   33
517.92     5000    F   0    7770   36
3323       10000   F   0    3006   39
286        5000    F   0    4500   40
13555.83   40000   M   1    3432   37
715        5000    F   0    5888   21
1934       10000   F   0    1009   63
7638       30000   M   1    5460   26
5700       25000   M   1    8000   44
2892.5     15000   M   1    5667   34
2192.25    20000   M   1    7757   27
4347       20000   M   1    9998   38
1668.75    10000   F   0    9790   44
2365.75    15000   M   1    6003   55
2959.25    10000   M   1    6754   37
423.23     15000   M   1    6576   43
1558       10000   F   0    7658   27
402        5000    F   0    5436   23
2257       15000   M   1    6004   23
1345       10000   F   0    9790   31
1590.5     15000   F   0    6000   31
1529.67    10000   F   0    8799   43
845.75     5000    F   0   10005   33
8214       30000   M   1    6009   24
754        10000   F   0    5009   29
1826.5     10000   F   0     450   66
2500.2     15000   M   1    5004   22
1146.5     10000   F   0    4009   32
411.5      5000    F   0    6555   22
3504       20000   M   1    8000   44
356.3      15000   F   0    5667   24
4497.26    20000   M   1    7757   27
1703.13    15000   F   0    9998   25
1429.06    10000   F   0    4563   35
336.21     5000    F   0    7568   23
602.14     20000   F   0    6000   22
4420.46    20000   M   1    6004   23
515        5000    F   0    9790   22
252        15000   F   0    6000   31
538.5      5000    F   0    8799   22
1034       10000   F   0   10005   33
14127.25   40000   M   1   10008   33
1939.1     10000   F   0    5009   29
1645.73    15000   F   0     450   66
1362.96    10000   F   0    5004   22
699.32     5000    F   0    6759   22
5755.9     25000   M   1    7656   44
428.21     5000    F   0    6566   23
1386.88    10000   F   0    5655   33
3995.13    20000   M   1    7677   44
857.26     5000    F   0    4433   33
4182       20000   M   1    5665   43
704.31     5000    F   0    6000   22
3725.52    20000   M   1    6004   23
2129.6     15000   M   1    9790   22
1377.67    20000   F   0    6759   22
5767.15    25000   M   1    8990   43
2989.05    15000   M   1    3002   23
12291.77   40000   M   1    6004   23
908        5000    F   0    9790   44
999.37     10000   F   0    6003   55
209.08     5000    F   0    3432   37
527        10000   F   0    5888   21
392.54     5000    F   0    4000   26
2615.5     15000   M   1    4556   25
704        25000   F   0    5000   26
1182.96    10000   F   0    9990   45
2193.5     15000   M   1    6000   24
1730.25    20000   F   0    9870   64
526.8      5000    F   0   10003   43
2024       15000   M   1    4000   27
765.22     15000   F   0    6000   27
1610       10000   F   0    5009   22
466.65     5000    F   0    3432   37
1457       20000   F   0    7896   21
602        5000    F   0    7869   63
476.8      5000    F   0    5460   26
888.25     15000   F   0    8000   24
1211.82    10000   F   0    3432   37
6645.59    30000   M   1    5888   21
2985.5     15000   M   1    4000   26
1906.25    5000    F   0    4556   25
1591.98    10000   F   0    5000   26
2359.3     15000   M   1    9990   45
1061       15000   F   0    6000   24
863        5000    F   0    6754   37
1819.75    10000   F   0    6576   43
888        20000   F   0    6004   23
4404.25    20000   M   1    9008   57
442.64     5000    F   0    3002   23
254.48     15000   F   0    6004   23
914.5      5000    F   0    9790   44
1207.66    10000   F   0    6003   55
6119.75    30000   M   1    3432   37
1585.92    10000   F   0    5888   21
902.46     5000    F   0    4000   26
313.14     5000    F   0    4556   25
1333.5     10000   F   0    5000   26
833.6      5000    F   0    9990   45
244        10000   F   0    6000   24
1793       10000   F   0    9870   64
3534.5     20000   M   1   10003   43
1106.69    10000   F   0    4000   27
2428.44    20000   M   1    6000   27
2985       15000   M   1    5009   22
3149.57   20000   M   1    3432   37
907.99    5000    F   0    7896   21
2846      15000   M   1    7869   63
2741.25   10000   M   1    5460   26
1168      10000   F   0    8000   24
2732.91   15000   M   1    3432   37
268       5000    F   0    5888   21
645.5     15000   F   0    4000   26
912.9     5000    F   0    4556   25
831.39    5000    F   0    5000   26
1254      20000   F   0    9990   45
384.25    10000   F   0    6000   24
2194.2    15000   M   1    8799   43
862       15000   F   0   10005   33
304.5     5000    F   0    6009   24
1173.86   10000   F   0    5009   29
3260      20000   M   1     450   66
1112.5    10000   F   0    5004   22
286.2     5000    F   0    4000   28
432.4     5000    F   0    3002   23
1064      15000   F   0    6004   23
2671      15000   M   1    9790   44
362       10000   F   0    6000   31
1645.8    20000   F   0    8799   43
300.53    5000    F   0   10005   33
1043      5000    F   0    6009   24
769.16    15000   F   0    5009   29
365.32    10000   F   0     450   66
1696.3    20000   F   0    5004   22
826.52    10000   F   0    4009   32
15693     5000    F   0    6555   22
1089.51   10000   F   0    8000   44
3129.69   20000   M   1    5667   24
389.95    15000   F   0    7757   27
1277.87   10000   F   0    9998   25
435.5     5000    F   0    6759   22
766.26    5000    F   0    6000   22
1127      20000   M   1    3002   23
3652      10000   F   0    6004   23
5771.59   25000   M   1    9790   44
2335.04   15000   M   1    6003   55
1376.5    10000   F   0    6000   23
2032.18   15000   M   1    4003   27
247       15000   F   0    1003   24
1053.5    10000   F   0    7594   52
427.8     5000    F   0     432   46
287       5000    F   0    5009   22
REFERENCES


[1]   National Anthems, "Sri Lanka," national-anthems.net, Jan. 18, 2008. [Online].
      Available: http://www.national-anthems.net/CE. [Accessed: Mar. 1, 2009].

[2]   Central Bank of Sri Lanka, "Statistics" cbsl.gov.lk, 2007. [Online]. Available:
      http://www.cbsl.gov.lk/info/08_statistics/statistics.htm. [Accessed: Mar. 1, 2009].

[3]   T. Rashid and L.Elder, “Mobile Phoned and Development: An Analysis of IDRC-
      Supported Projects,” EJISDC, vol. 36, no. 2, pp. 1-16, 2009

[4]   Telecommunications Regulatory Commission of Sri Lanka, "Statistics" trc.gov.lk,
      2009. [Online]. Available: http://www.trc.gov.lk/statistics.htm. [Accessed: Mar.
      1, 2009].

[5]   R.Jain and T.Sastry, “Socio-economic Impact of Rural Telecom: Implications for
      Policy, ” 1997

[6]   H.S.Dunn and H.L.Dunn, “Genderstanding Mobile Telephony: Woman, Men and
      their Use of Cellular Phones,” Teleuse at the Bottom of the Pyramid, November
      2007.




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Description: This report discusses the analysis of the Mobile Communication in Sri Lankan market place. It covers this from the background of telecommunication economy, introduction of mobile communication in Sri Lanka, how and why it has captured the market place and how it is being evolved.