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A population dependent diffusion model with a stochastic extension

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  • Michalakelis, C.
  • Sphicopoulos, T.

Abstract

Diffusion modeling is rather broad in nature, and is important in the areas of estimation and forecasting. Conventional models do not incorporate parameters that explicitly take into account the size of the population, or, equivalently, the size of the potential market. As a consequence, the models often fail to provide accurate forecasts, especially when the diffusion process is in the take-off stage. Furthermore, since diffusion is not a strictly deterministic process, forecasts should provide a measure of the underlying uncertainty of the process by incorporating a stochastic process into the formulation of the models.

Suggested Citation

  • Michalakelis, C. & Sphicopoulos, T., 2012. "A population dependent diffusion model with a stochastic extension," International Journal of Forecasting, Elsevier, vol. 28(3), pages 587-606.
    • Handle: RePEc:eee:intfor:v:28:y:2012:i:3:p:587-606
    DOI: 10.1016/j.ijforecast.2012.03.002
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    References listed on IDEAS

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    Cited by:

    1. Aggelos Skoufis & Georgios Chatzithanasis & Georgia Dede & Evangelia Filiopoulou & Thomas Kamalakis & Christos Michalakelis, 2023. "Technoeconomic assessment of an FTTH network investment in the Greek telecommunications market," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(2), pages 211-227, February.
    2. Aggelos Skoufis & Georgios Chatzithanasis & Georgia Dede & Thomas Kamalakis & Christos Michalakelis, 2020. "Technoeconomic analysis of a VDSL2/G.fast vectoring network: a case study from Greece," Netnomics, Springer, vol. 21(1), pages 83-101, December.
    3. Hattam, Laura & Greetham, Danica Vukadinović, 2018. "An innovation diffusion model of a local electricity network that is influenced by internal and external factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 353-365.
    4. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    5. Rządkowski Grzegorz & Sobczak Lidia, 2020. "A Generalized Logistic Function and its Applications," Foundations of Management, Sciendo, vol. 12(1), pages 85-92, January.

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