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Modelling the Development of Supply-Restricted Telecommunications Markets


  • Islam, Towhidul
  • Fiebig, Denzil G


A large proportion of the world telecommunications market can be characterized as supply restricted. In ITU (1999) official waiting lists numbered about 50 million worldwide with an average waiting time of two years. More than 100 countries had not eliminated the waiting list for telephone connections and hence a supply restricted market prevailed in all of these countries. Only about 25 countries have succeeded in eradicating their waiting list for basic telephone service. In terms of the pattern of diffusion, the subscriber's flow from waiting applicants to adopters is controlled by supply restrictions adding an important dimension that needs to be addressed when modeling and forecasting demand. An empirical analysis of the diffusion of main telephones in 46 supply-restricted countries is presented to demonstrate the usefulness of a three-stage Bass model that has been proposed to capture the dynamics of supply restrictions. We also compare the forecasting ability of different approaches to estimation when panel data are available. Copyright © 2001 by John Wiley & Sons, Ltd.

Suggested Citation

  • Islam, Towhidul & Fiebig, Denzil G, 2001. "Modelling the Development of Supply-Restricted Telecommunications Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(4), pages 249-264, July.
  • Handle: RePEc:jof:jforec:v:20:y:2001:i:4:p:249-64

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    Cited by:

    1. Islam, Towhidul & Meade, Nigel, 2015. "Firm level innovation diffusion of 3G mobile connections in international context," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1138-1152.
    2. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - German National Library of Economics.
    3. Abualkhair, Ayman, 2007. "Electricity sector in the Palestinian territories: Which priorities for development and peace?," Energy Policy, Elsevier, vol. 35(4), pages 2209-2230, April.
    4. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
    5. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    6. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
    7. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
    8. Robert Bartels & Towhidul Islam, 2002. "Supply Restricted Telecommunications Markets: The Effect of Technical Efficiency on Waiting Times," Journal of Productivity Analysis, Springer, vol. 18(2), pages 161-169, September.
    9. Dalla Valle, Alessandra & Furlan, Claudia, 2014. "Diffusion of nuclear energy in some developing countries," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 143-153.
    10. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.

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