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A Generalized Logistic Function and its Applications

Author

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  • Rządkowski Grzegorz
  • Sobczak Lidia

    (Warsaw University of Technology, Faculty of Management, Warsaw, Poland)

Abstract

In the present article, we deal with a generalization of the logistic function. Starting from the Riccati differential equation with constant coefficients, we find its analytical form and describe basic properties. Then we use the generalized logistic function for modeling some economic phenomena.

Suggested Citation

  • Rządkowski Grzegorz & Sobczak Lidia, 2020. "A Generalized Logistic Function and its Applications," Foundations of Management, Sciendo, vol. 12(1), pages 85-92, January.
  • Handle: RePEc:vrs:founma:v:12:y:2020:i:1:p:85-92:n:7
    DOI: 10.2478/fman-2020-0007
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    References listed on IDEAS

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    1. 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.
    2. Qian, Lixian & Soopramanien, Didier, 2014. "Using diffusion models to forecast market size in emerging markets with applications to the Chinese car market," Journal of Business Research, Elsevier, vol. 67(6), pages 1226-1232.
    3. Yamakawa, Peter & Rees, Gareth H. & Manuel Salas, José & Alva, Nikolai, 2013. "The diffusion of mobile telephones: An empirical analysis for Peru," Telecommunications Policy, Elsevier, vol. 37(6), pages 594-606.
    4. Modis, Theodore, 2007. "Strengths and weaknesses of S-curves," OSF Preprints r5zk7, Center for Open Science.
    5. 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.
    6. Wu, Feng-Shang & Chu, Wen-Lin, 2010. "Diffusion models of mobile telephony," Journal of Business Research, Elsevier, vol. 63(5), pages 497-501, May.
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