IDEAS home Printed from https://ideas.repec.org/a/eee/telpol/v31y2007i1p31-44.html

Forecasting telecommunications data with linear models

Author

Listed:
  • Madden, Gary
  • Tan, Joachim

Abstract

For telecommunication companies to successfully manage their business, companies rely on mapping future trends and usage patterns. However, the evolution of telecommunications technology and systems in the provision of services renders imperfections in telecommunications data and impinges on a company's' ability to properly evaluate and plan their business. International Telecommunication Union (ITU) Recommendation E.507 provides a selection of econometric models for forecasting these trends. However, no specific guidance is given. This paper evaluates whether simple extrapolation techniques in Recommendation E.507 can generate accurate forecasts. Standard forecast error statistics--mean absolute percentage error (MAPE), median absolute percentage error and percentage better--show the ARIMA, Holt and Holt-D models provide better forecasts than a random walk and other linear extrapolation methods.

Suggested Citation

  • Madden, Gary & Tan, Joachim, 2007. "Forecasting telecommunications data with linear models," Telecommunications Policy, Elsevier, vol. 31(1), pages 31-44, February.
    • Handle: RePEc:eee:telpol:v:31:y:2007:i:1:p:31-44
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308596106000929
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Perambur Neelakanta & Raef Yassin, 2012. "Information theoretics-based technoeconomic forecasting: application to telecommunication service industry," Netnomics, Springer, vol. 13(1), pages 45-78, April.
    2. Paris A. Mastorocostas & Constantinos S. Hilas & Dimitris N. Varsamis & Stergiani C. Dova, 2016. "Telecommunications call volume forecasting with a block-diagonal recurrent fuzzy neural network," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 63(1), pages 15-25, September.
    3. Shagun Srivastava & Madhvendra Misra, 2014. "Developing Evaluation Matrix for Critical Success Factors in Technology Forecasting," Global Business Review, International Management Institute, vol. 15(2), pages 363-380, June.
    4. Mack, Elizabeth A. & Grubesic, Tony H., 2009. "Forecasting broadband provision," Information Economics and Policy, Elsevier, vol. 21(4), pages 297-311, November.
    5. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.

    More about this item

    Keywords

    ;

    JEL classification:

    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:telpol:v:31:y:2007:i:1:p:31-44. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/30471/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.