Report from the 4th Workshop on Telecommunications Technoeconomics

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Market forecasts and business case modeling for 3G and wireless services in Europe

(Report from the 4th Workshop on Telecommunications Technoeconomics)

Dimitris Varoutas

University of Athens

Department of Informatics and Telecommunications, Panepistimiolopis, Athens, GREECE

Giovanni Gasbarrone

Dimitris Katsianis

University of Athens, GR

Evangelos Karathanos

University of Athens, GR

1.Subject Area – Objectives

Wireless services and applications are becoming more and more pervasive in the business and everyday life. Wireless access wherever we need: Home, Car, Office, Airport, Hotel as well as commercial areas. Bluetooth, Wireless Lan and HiperLan2 are changing our wireless market view. Over the next years, about 70 licenses for UMTS (Universal Mobile Telecommunication System) spectrum will be distributed in Europe, either through auctions or comparative hearings.

Now, more than ever, fixed and mobile operators are making critical decisions, which will shape their business over the next ten years. The main challenge is to maximize investment efficiency to provide wireless next-generation and mobile data services.

The main topics covered in this paper are related to applications /services market forecasts and evaluation issues. The scope of this paper is to provide current trends and tools to evaluate the future wireless market evolution in Europe.

The market assumptions are based on the future scenario taking in consideration the next generation wireless services. A smooth evolution is envisaged from 3G mobile generation to next 4G wireless wave: a learning process from the customers' side is highlighted and business visions are derived and crossed with other sources (ITU). The model outputs are market figures to be used as a starting point for evaluation. As a consequence this business evaluation tool may provide a better understanding on the future market demand.


Figure 1: Next generation technologies

A fundamental issue is to think long-term scenarios and to provide true market projections for the mobile next generation wave. To this purpose, specific tools and business models with a particular stress on the economics and revenues drivers have been developed and introduced ([1],[2])

The use of simulators will facilitate the understanding of the initial situation and its possible evolutions, as well the identification of the future economical potentialities.

Consultants predict major trends in wireless and mobile markets (e.g. they forecast mobile data growth and decreasing voice revenues). Available analysis provide us with medium term forecasts covering GPRS and UMTS growth until 2005. Forecasts are based on past experience and trends estimation. Beyond 2005, only rough estimations are available.

2.State of the Art in technoeconomics

Several activities for technoeconomic evaluation of existing and emerging mobile and fixed networks are spread across Europe. Here we described two of them as presented in the 4th Workshop on Telecommunications Technoeconomics, which organized from IST-TONIC project in Rennes, France during 14-15 May 2002 [3].

2.1IST-TONIC Methodology

EU IST-TONIC [1] project is a precursor in the investigation of the economic side of network deployments and the forecast of demand for mobile and fixed services.

The techno-economic modeling was carried out using the TONIC tool, which has been developed by the IST-TONIC project using the TERA tool [4] as the basis. This tool is an implementation of the techno-economic modeling methodology developed by a series of EU co-operation projects in the field. The tool has been extensively used for several techno-economic studies [5][6][7] among major European telecom organizations and academic institutes.

Figure 2 – Techno-economic Methodology from IST-TONIC project [1]

The base of the model’s operation is a database, where the cost figures of the various network components are reposited. These figures are constantly updated with data gathered from the biggest European telecommunication companies. The database outputs the cost evolution of the components over time. A dimensioning model is used to calculate the number of network components as well as their cost, for the set of services and the network architectures defined. Finally the future market penetration of these services and the tariffs associated with them, which have been calculated through market forecasts and benchmarking, are inserted into the tool. All these data are forwarded into the financial model of the tool that calculates revenues, investments, cash flows and other financial results for the network architectures for each year of the study period. An analytical description of the methodology and the tool can be found in [8].

2.2Marketing Forecasting Model: Methodology assessments

The purpose of this market model is to construct a system that can provide with preliminary market forecasts for a range of major telecommunication businesses. The model is able to provide market forecasts for a range of wireless telecommunication businesses including 3G, existing wireless as well as new opportunities to form part of the overall business plan. The business model tool provides good results based on the input information. However, high quality and reliable results will require intervention from a skilled analyst to input and interpret other factors such as likely competitive environment - therefore the user will need to be highly skilled in understanding telecommunications markets

Figure 3: Marketing Forecasting Model [2]
The market model development involves several stages [2]:

  • collection of basic macro economics data such as GDP and population

  • understanding and calculating the relationships between different variables e.g. GDP and wireless market figures (user, and revenues) ;

  • collecting and interpreting benchmark competitive environment e.g. wireless market share

  • constructing a model to draw on the macro data to calculate forecast the various elements of the revenue using the relationships and competitive environment analysis

  • Pricing reduction and volume increase follow the basic demand elasticity laws. Therefore, higher customers' base will reflect an additional increase in volumes and consequent additional revenues.

  • Mobile e-commerce revenue is calculated according to statistical calculation on country specific average revenue per user (ARPU). Higher confidence showed by customers and better perception of the technology increases volume traffic and size of transactions specific services.

  • Operator revenues are extrapolated by using linear mathematical functions for specific country mobile e-commerce revenues. The operative research calculation follows basic assumptions (e.g. operator shares will smoothly decrease over time as transport revenues decrease and reduction in margins increase due to stronger competition).

3.Approach for marketing forecasts modelling

3.1Overview of next generation wireless marketing forecasts tools

The next generation wireless business case relies on a wide range of market assumptions into the model as well as other analysis that is used to assist us in forecasting process. The next generation wireless business model is based on a number of modifications and extension to 3G marketing planning

The business model covers a wide range of areas including:

  • Demographic and macroeconomic forecast analysis in Europe (E.g. various economic and social factors including population composition & GDP/PPI)

  • Wireless customers traffic profile forecasts (based on statistics evaluation) (Voice and data ARPU)

  • Mobile E- Commerce (B2B, B2C, etc.)

  • Mobile games, gambling and entertainment

  • On-demand movies

  • Wholesale wireless services

  • Mobile Advertising content & distribution

  • Mobile Trading

3.2Overview of 4G business case: market assumptions

The main market assumptions are the following:

  • Mobile advertising will become more and more like information entertainment services, this will reflects an increasing traffic through to web sites and provide benefit to mobile operators trough IP services revenues.

  • Direct advertising revenues will be generated in a significant size in the medium term; the customer base growth follows 3G wave; non human users will gain increasing market share according new social & economic behaviour .

  • A learning process from the customers' side is highlighted and a consequent market boost is forecasted

  • Higher confidence gained by customers and better perception of the technology increase volume traffic and size of e-commerce transactions

  • The role of content providers and operators is to make alliances in marketing services (co branding process) and to share voice & data traffic or revenues. Multimedia terminal cost will be subsidised by traffic and services revenues.

  • Mobile e-commerce users

The forecast of overall mobile e-commerce users is taken as due proportion of mobile data users forecast available from statistical different sources, and managed by specific forecasting routine software on the global mobile market. The growth of mobile e-commerce in Europe is an average value measured according to linear functions of Internet & mobile CAGR in European countries.

  • Revenues estimation

We forecast mobile revenues by estimating the average revenue per subscriber in western European countries, and then multiply that estimation by the number of subscribers. Revenue per subscriber takes account of all revenues lines (e-commerce, gambling, advertising & trading and other value-added services).


4.1Market Sizing: demand forecast

Historical data on wireless data and benchmarking analysis of over 200 different countries have been used to estimate demand curves for a number of country groupings.

There are a number of factors, which affect the levels of demand. Examples of these include:

  • available investment by current and future operator(s)

  • fair interconnect regime

  • changing/alternative technology e.g. new wireless and radio technologies

  • price changes and price elasticity

The business model can be used to identify best-practice values, where possible, based on all relevant international benchmarks, on the effect these factors will have on the future demand for telecommunications services (e.g. a 50% reduction in prices will result in a 20% increase in volume).

Figure 4: 3G and beyond European market

4.23G financial perspectives in Europe [6]

A detailed technoeconomic analysis of 3G market in Europe has been already performed in ACTS-TERA and IST-TONIC project, based on TONIC tool. The techno-economic prospects for a newcomer and especially for an incumbent operator planning to deploy the UMTS technology are found to be quite positive (Figure 5) according to this study [6].

With four operators sharing the market, the customer base appears sufficient to achieve a positive NPV over the study period in all four cases. The IRR is higher than the 10% discount rate, which shows that the investment is sound over this period. Table 1 summarizes the economic results of the two basic scenarios (large and small country) for both the incumbent and new entrant.
Table 1: Summary of the economic results for operators with 25% end market share

Incumbent Small

Incumbent Large

Greenfield Small

Greenfield Large

NPV (M€)










Rest Value (M€)





Pay-back period





Number of customers 2009





Investments (M€)





Running costs (M€)





Investment per connected customer ()





ARPU per month over the study period (€)





Specifically, the following elements were identified to have major consequences on the profitability of this new business:

  • Regulatory decisions to promote competition.

  • Cost of licenses.

  • Tariffs of voice and data services.

  • Investment schedule.

Figure 5 - NPV – IRR – Payback Period for incumbent and newcomers for L-arge and S-mall European Countires

4.3A case study in Greece

IST-TONIC methodology has applied in the case of Greece. Based on the official data for the Greek market, announced by the operators (Figure 6), and assuming a subscription penetration of 120% until 2012, we can estimate the demand for mobile services in Greece (total population 11M).

Figure 6 – Number of Mobile Subscriptions in Greece

Based on these results and assuming that the percentage of subscribers holding more than one mobile station starts from 0% and saturates to 33%, the subscriber penetration has been estimated as well. For the estimation of both demand curves a logistic model with four parameters [9][10] was applied. The curves are illustrated in the diagram below.

Figure 7 – Mobile Subscriptions and Subscribers vs Year in Greece

The total subscriber penetration is split into three different mobile system generations, namely GSM or 2G, GPRS or 2.5G and UMTS or 3G. When the period of study starts in 2002 only GSM users are considered to be in the mobile market. Their number will constantly decrease until 2012 when they will totally disappear. The first GPRS users have been appeared in 2002. The saturation level for 2.5G is 40% for Greece and will be reached in 2007. Following that period there will be a decline in the demand down to the level of 25% until 2012. As for the UMTS users, they will appear at the end of 2003 and their number will increase to reach a percentage of 75% of the total mobile market in 2012 when the case study ends. A logistic model [9] was also applied to estimate the percentages for the different system generations for the years 2002 – 2012. The results are illustrated in the diagram below.

Figure 8 – Penetration Forecast for different Systems

Combining the results for the total mobile subscriber penetration and the market share of each of the mobile systems, the penetration forecast for these systems has been calculated.

Figure 9 – Mobile Subscriber Penetration Forecast

In order to achieve a better approach of the real market the subscribers have been divided in business and residential users based on the network usage and the services they use.

The following figure illustrates the investments, revenues and cash balance for the basic scenario.

Figure 10 - Investments, Revenues, Cash Balance for a 3G operator in Greece

The biggest amount of the investments is required in the first two years in order to install the UMTS BTSs in urban and suburban areas. Rural areas network implementation in 2006-2007 will call for substantial investments. The lowest point of the cash balance curve indicates the maximum need for funding. For the operator of our study this amount is €1.137 billion. The significant slope of the cash balance curve at the end of the period indicates good future earning potential.

The techno-economic prospects for an incumbent operator planning to build and operate a UMTS network in Greece are found to be encouraging, according to specific assumptions and scenarios. A more detailed analysis of 3G economics in Greece can be found in [6].


The technoeconomic analysis of 3G and 4G is mandatory for a 2G-like success story across Europe. The economic figures for these kinds of services are quite positive under specific circumstances. Tools and methodologies for market and business case modeling (presented in 4th Workshop on Telecommunication Technoeconomics) have been highlighted, in order to aware about this research area.


The authors would like to thank all the partners of IST-TONIC project for their useful support and discussions, as well as for the organization of the 4th Workshop on Telecommunications Technoeconomics, which gave the opportunity to exchange ideas and to prepare this paper.



  2. G. Gasbarrone, “Beyond third generation wireless communications The European market Business Case modelling”, 4th Workshop on Telecommunications Techno-Economics, Rennes – France, 14-15 May 2002



  5. D. Katsianis et al, “The financial perspective of the mobile networks in Europe”, IEEE Personal Commun. Mag., Dec. 2001 Vol 8, No 6, pp 58-64.

  6. D. Katsianis, et al.“3G economics in Greece from now to 2012 ” 4th Workshop on Telecommunications Techno-Economics, Rennes – France, 14-15 May 2002

  7. Th. Monath et al, “Economics of Ethernet based access networks for broadband IP services”, ISSLS 2002, 14 –17 April, 2002, Seoul

  8. L.A. Ims, “Broadband Access Networks Introduction strategies and techno-economic evaluation, Telecommunications Technology And Applications Series, Chapman & Hall 1998, ISBN 0 412 828200

  9. K. Stordahl, L. Rand, "Long term forecasts for broadband demand", Telektronikk, 95, (2/3), 1999.

  10. Kjell Stordahl, Leif Aarthun Ims, Marianne Moe, “Broadband market - the driver for network evolution”, Proc Networks 2000, Toronto, Canada, September 10-16, 2000.

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