IDEAS home Printed from https://ideas.repec.org/p/gmf/wpaper/2011-20.html
   My bibliography  Save this paper

Fitting Broadband Diffusion by Cable Modem in Portugal

Author

Listed:
  • Rui Pascoal

    (Faculty of Economics University of Coimbra)

  • Jorge Marques

    (Faculty of Economics University of Coimbra)

Abstract

The purpose of this article is to described the evolution of the number of residential subscribers of broadband fixed access by cable modem, in Portugal, on the period from 2000–2009. The pattern of evolution is estimated by fitting several models to the series, namely the following: exponential, Gompertz, Logistic, Bass and Michaelis-Menten. We fit the models to the data by nonlinear least squares, except in the exponential model where the linear version is fitted by ordinary least squares, using the internet freely available program R. This comparative study is in line with many others on the diffusion of technological innovations in the telecommunications sector, where the point is finding out if there is an early or a late take-off phenomenon. The Michaelis-Menten model is introduced for the first time in this approach. It allows to predict the later evolution in the series and reveals a qualitatively different behavior.

Suggested Citation

  • Rui Pascoal & Jorge Marques, 2011. "Fitting Broadband Diffusion by Cable Modem in Portugal," GEMF Working Papers 2011-20, GEMF, Faculty of Economics, University of Coimbra.
    • Handle: RePEc:gmf:wpaper:2011-20
    as

    Download full text from publisher

    File URL: https://repec.uc.pt/gmf/wpaper/wpgemf/gemf_2011-20.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nunes, Flávio, 0. "Geographical gaps in the Portuguese broadband access. Rethinking the role of public funding after years of trade liberalisation," Telecommunications Policy, Elsevier, vol. 30(8-9), pages 496-515, September.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    3. V. Srinivasan & Charlotte H. Mason, 1986. "Technical Note—Nonlinear Least Squares Estimation of New Product Diffusion Models," Marketing Science, INFORMS, vol. 5(2), pages 169-178.
    4. Moon-Soo Kim & Ho Kim, 2004. "Innovation Diffusion Of Telecommunications: General Patterns, Diffusion Clusters And Differences By Technological Attribute," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 223-241.
    5. Kim, Moon-Soo & Kim, Ho, 2007. "Is there early take-off phenomenon in diffusion of IP-based telecommunications services?," Omega, Elsevier, vol. 35(6), pages 727-739, December.
    6. Botelho, Anabela & Pinto, L.C.Lígia Costa, 0. "The diffusion of cellular phones in Portugal," Telecommunications Policy, Elsevier, vol. 28(5-6), pages 427-437, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jha, Ashutosh & Saha, Debashis, 2020. "“Forecasting and analysing the characteristics of 3G and 4G mobile broadband diffusion in India: A comparative evaluation of Bass, Norton-Bass, Gompertz, and logistic growth models”," Technological Forecasting and Social Change, Elsevier, vol. 152(C).
    2. Gupta, Ruchita & Jain, Karuna, 2016. "Competition effect of a new mobile technology on an incumbent technology: An Indian case study," Telecommunications Policy, Elsevier, vol. 40(4), pages 332-342.
    3. Kim, Moon-Soo & Kim, Ho, 2007. "Is there early take-off phenomenon in diffusion of IP-based telecommunications services?," Omega, Elsevier, vol. 35(6), pages 727-739, December.
    4. Riikonen, Antti & Smura, Timo & Kivi, Antero & Töyli, Juuso, 2013. "Diffusion of mobile handset features: Analysis of turning points and stages," Telecommunications Policy, Elsevier, vol. 37(6), pages 563-572.
    5. Berrin Aytac & S. Wu, 2013. "Characterization of demand for short life-cycle technology products," Annals of Operations Research, Springer, vol. 203(1), pages 255-277, March.
    6. Yuri Peers & Dennis Fok & Philip Hans Franses, 2012. "Modeling Seasonality in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 351-364, March.
    7. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    8. Bacha, Radia & Gasmi, Farid, 2022. "The broadband diffusion process and its determinants in Algeria: A simultaneous estimation," TSE Working Papers 22-1309, Toulouse School of Economics (TSE).
    9. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    10. Kim, Namwoon & Srivastava, Rajendra K., 2007. "Modeling cross-price effects on inter-category dynamics: The case of three computing platforms," Omega, Elsevier, vol. 35(3), pages 290-301, June.
    11. Nigel Meade & Towhidul Islam, 1998. "Technological Forecasting---Model Selection, Model Stability, and Combining Models," Management Science, INFORMS, vol. 44(8), pages 1115-1130, August.
    12. Kivi, Antero & Smura, Timo & Töyli, Juuso, 2012. "Technology product evolution and the diffusion of new product features," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 107-126.
    13. Vakratsas, Demetrios & Kolsarici, Ceren, 2008. "A dual-market diffusion model for a new prescription pharmaceutical," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 282-293.
    14. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    15. Tunstall, Thomas, 2015. "Iterative Bass Model forecasts for unconventional oil production in the Eagle Ford Shale," Energy, Elsevier, vol. 93(P1), pages 580-588.
    16. Theoharakis, Vasilis & Vakratsas, Demetrios & Wong, Veronica, 2007. "Market-level information and the diffusion of competing technologies: An exploratory analysis of the LAN industry," Research Policy, Elsevier, vol. 36(5), pages 742-757, June.
    17. Marshall, Pablo & Dockendorff, Monika & Ibáñez, Soledad, 2013. "A forecasting system for movie attendance," Journal of Business Research, Elsevier, vol. 66(10), pages 1800-1806.
    18. Sang-Gun Lee & Eui-bang Lee & Chang-Gyu Yang, 2014. "Strategies for ICT product diffusion: the case of the Korean mobile communications market," Service Business, Springer;Pan-Pacific Business Association, vol. 8(1), pages 65-81, March.
    19. Franses, Ph.H.B.F., 2009. "Forecasting Sales," Econometric Institute Research Papers EI 2009-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Liu, Xueying & Madlener, Reinhard, 2019. "Get Ready for Take-Off: A Two-Stage Model of Aircraft Market Diffusion," FCN Working Papers 15/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).

    More about this item

    Keywords

    Broadband; Technological Innovations; Diffusion Growth Models; Nonlinear Least Squares;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    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:gmf:wpaper:2011-20. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sofia Antunes (email available below). General contact details of provider: https://edirc.repec.org/data/cebucpt.html .

    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.