Some limits of revenue generation for mobile network operators

1. Some limits of revenue generation for mobile network operators Jari Veijalainen Jouni Markkula Univ. of Jyväskylä Finland email: veijalai@cs.jyu.fi, jouni.markkula@titu.jyu.fi

2. Contents • Introduction • The big picture • Some limits for the revenues • Conclusions

3. Introduction • Currently mobile Internet is advancing fast; in Japan NTT DoCoMo’s i-Mode and similar services of the other operators have gathered well over 30 million users and it is expected that the penetration will reach saturation in a few years; currently over 80 % of the wireless traffic is voice, but data traffic is increasing • Telecom industry estimates that in 2003 there will be over 500 million Internet-enabled terminals in use in the world • In Europe, many Mobile Network Operators (MNOs) paid huge license fees to the governments for 3G bandwidth; in Germany and GB ca. 600 €/inhabitant, Italy, NL, and France 200 €/inhabitant, in other countries 10-50 €/inh, except in Finland and Sweden zero euro • The above things raise many questions, such as, are there limits for the revenue generation of MNOs and which factors determine this? What happens in the European market as the costs in different countries are so different? how does the voice and data traffic and the respective revenues develop in the future? What is relationship to digi-TV and wireline Internet? What kind of charging schemes are appropriate?

4. The bigger picture: convergence of Internet and digital telecom networks PC PC Mobile terminal TV set IP Backbone Network Mobile NW Operator sphere E-commerce server CA server Service provider Server (e.g. GIS) Community server

5. Some measures for the big picture • there are about 700 GSM networks in 171 countries on earth and several other types of 2G networks (eg. CDMA-based); • GSM technology is truly global with its roaming capability and coverage • the number of digital telecom handsets will soon exceed 1 billion (this year 400 million handsets will be sold) and by 2005 perhaps 2 billions • of these hundred of millions are Internet-enabled( WWW or WAP) • There are over a hundred million of servers at the server side

6. Some concrete limits • Observed ARPUs for voice at NTT DoCoMo went from 10800 Y/(subs*month) in 3/98 down to 6940 Y/(subs*month) in 3/2002; • ARPU for the data traffic (after launching i-Mode) went from 120 to 1540 Y/(month*subs) • total ARPU decreased continuously since 3/1998 ending a 8480 Y(month*subs) • the number of spoken minutes increased from 155 min/(month*subs) to 189 in 3/2001 and decreased to 178 in 3/2002 • the revenue figures above are rather at the higher end in the world, so no MNO can expect to collect more revenues per customer from a large population than the above figures suggest

7. Notations for the overall model • N - Total number of wireless subscribers in the world (subscriber) • NO – Number of subscribers of an operator O (subscriber) • R – Total wireless revenue in the world (price unit / month). • RO – Revenues of operator O (price unit / month). • RS – Mean revenue generated by a subscriber (price unit / month). • C – Mean capacity of a wireless link (bytes /(month)). • L – number of parallel wireless up- and down links in the world • F – Monthly subscription fee (price unit / (month*subs)). • P – Price of a traffic unit (price unit / byte). • PD – Price of a data unit (price unit / byte). • PM – Price of a connection time unit ( price unit / min). • AS – Mean overall wireless traffic volume of a subscriber(byte/(month*subs). • DS – Mean wireless data traffic volume of a subscriber (byte /(month*subs)).

8. Notations for the overall model (cntnd) • MS – Mean connection time of a subscriber (min /(month*subsc)). • Mv – Mean voice connection time of a subscriber (min/(month*subs)) • Ti – User’s interacting time with terminal in using an application (min). • Tt – Data transfer time of an application (min). • I – Communication intensity of a service. • I = Tt/Ti .

9. 2 Theoretical limits: number of subscribers and overall revenues • (1) R = N*(F+AS*P) • Revenues increase with any individual factor or term increasing • Assuming e.g., N= 7*109,F = 3€/month*subs and AS*P = 30 € /month*subs we get R = 231*109 €/month, i.e. R ~ 2.8*1012 €/year. • More realistically if N = 2*109 ,then the maximal revenues of the combined wireless voice and data traffic would be ca. 0.56* 1012 €/year. • Notice that these figures do not include the actual wireless services, like Location-based Services or other M-commerce services

10. 2 Theoretical limits: bandwidth scarcity • (2) N*AS < L*C < Lmax* Cmax • The number of available simultaneous wireless links L times the capacity C per link must be bigger than number of bytes AS the N users will transmit monthly • L*C is in practice smaller than the theoretical maximum Lmax* Cmax obtained by maximally reusing the allocated finite bandwidth by setting up as many base stations as possible in every area of the world • Still, in some dense populated regions or uninhabited places the real capacity L*C can be too small for the demand; What restricts building the capacity are mostly cost factors when building up the system • In cities it is cheaper to build wireline capacity, in rural areas wireless

11. 3 Limiting factors for revenues in voice traffic • (3) R = Ng*(F+Mv*PM) • Mv(PM +x) <= Mv(PM) for all PM, x>0, I.e. the more expensive the spoken minute is, the less people tend to speak per month • Decreasing the price PM per connection minute does not increase R without bound; this is because people have a finite time Mmax they are ready to use for mobile phone calls • It is unclear how Mv will develop over time; there are arguments both for increasing Mv and for decreasing Mv • PM will most probably decrease over time due to competition and faster wireless technology • F is difficult to increase when once set – unless PM is set to zero • Thus, operator should attract more customers i.e. increase Ng ;should this not happen, revenues for transmission stagnate

12. 4 Limiting Factors in Data traffic • (4) R = N*(F+DS*PD) • Theoretically the limiting factor the number of bytes transferred DS per month; this is restricted by the wireless link capacity (up- and downlink having in this context the same capacity) • With the current wireless data tansfer tariffs the price is so high, however, that no user would transfer the maximum amount of data, but rather only a small fraction • However, if PD ->0 then this restriction does not apply, but we have the flat rate case; • In the latter case rather the capabilities of the terminal become crucial; can the terminal generate traffic alone, without continuous user interaction (and battery recharging)? If yes, then the link capacity can be fully used; if no then the time the user is willing to invest is crucial

13. 5 The data transmission intensity coefficient I • “data transmission intensity” coefficient I = Tt/Ti determines how long the terminal transmits data versus how long the user interacts with it per month. • For voice traffic terminals I = 1, whereas for the more complex terminals I can be anything above zero. This is because the user can load e.g. a game and play with it for long time in stand-alone mode – ( I ->0) or she can start an agent by pressing a button that scans hour after hour the Internet in order to find matching documents (I ->µ) • For the latter reason flat rate is probably not a good idea in 3G networks in the longer run; the clever terminal base is able to congest it badly

14. 6 Recent developments in convergence • Nokia and other companies try to push Open Mobile Architecture • www.nokia.com/oma • this concentrates especially on the data transmission part

15. Functional convergence on PTDs

16. Roaming heterogeneity:overcoming it an all levels

17. Technical enablers

18. Conclusions and further research • there are absolute limiting factors for the revenue generation, like the number of people in the world that are able and willing to take part in wireless communications, as well the ARPU affected by tariffs • If MNO would like to use only either volume-based or time-based charging then volume based is better, because it makes easier to increase capacity • Flat rate-based tariffs are probably not a viable solution when terminals become more sophisticated and the close tie between the time user spends interacting with the terminal and the time it transmits data becomes blurred: the terminals can generate very much traffic that leads to network congestion no matter how much capacity is offered

19. Conclusions and further research • user time is crucial for revenue generation of a MNO especially in the voice traffic but also in the data traffic • it requires more investigation how the user divides his or her time among different channels (TV, wireline Internet) and how they are interdependent in order to assess more exactly the limits