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Marketing percolation

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Author Info

  • Goldenberg, J
  • Libai, B
  • Solomon, S
  • Jan, N
  • Stauffer, D
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    Abstract

    A percolation model is presented, with computer simulations for illustrations, to show how the sales of a new product may penetrate the consumer market. We review the traditional approach in the marketing literature, which is based on differential or difference equations similar to the logistic equation (Bass, Manage. Sci. 15 (1969) 215). This mean-field approach is contrasted with the discrete percolation on a lattice, with simulations of “social percolation” (Solomon et al., Physica A 277 (2000) 239) in two to five dimensions giving power laws instead of exponential growth, and strong fluctuations right at the percolation threshold.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0378437100002600
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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 284 (2000)
    Issue (Month): 1 ()
    Pages: 335-347

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    Handle: RePEc:eee:phsmap:v:284:y:2000:i:1:p:335-347

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

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    Cited by:
    1. B. M. Roehner, 2000. "Determining bottom price-levels after a speculative peak," Papers cond-mat/0009222, arXiv.org.
    2. R. D. Groot, 2004. "Levy distribution and long correlation times in supermarket sales," Papers cond-mat/0412163, arXiv.org.
    3. Martin Hohnisch & Sabine Pittnauer & Dietrich Stauffer, 2003. "Percolation-Based Model of New-Product Diffusion with Macroscopic Feedback Effects," Papers cond-mat/0308358, arXiv.org.
    4. Solomon Sorin & Golo Natasa, 2013. "Minsky Financial Instability, Interscale Feedback, Percolation and Marshall–Walras Disequilibrium," Accounting, Economics, and Law, De Gruyter, vol. 3(3), pages 167-260, October.
    5. Silverberg, G. & Verspagen, B., 2002. "A Percolation Model of Innovation in Complex Technology Spaces," Working Papers 02.12, Eindhoven Center for Innovation Studies.
    6. Andrea Ellero & Giovanni Fasano & Annamaria Sorato, 2008. "A Modified Galam's Model," Working Papers 180, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    7. Silverberg, Gerald, 2002. "The discrete charm of the bourgeoisie: quantum and continuous perspectives on innovation and growth," Research Policy, Elsevier, vol. 31(8-9), pages 1275-1289, December.
    8. Estrada, Fernando, 2011. "Theory of financial risk," MPRA Paper 29665, University Library of Munich, Germany.
    9. Silverberg, G. & Verspagen, B., 2003. "Brewing the future: stylized facts about innovation and their confrontation with a percolation model," Working Papers 03.06, Eindhoven Center for Innovation Studies.
    10. G. Yaari & D. Stauffer & S. Solomon, 2008. "Intermittency and Localization," Papers 0802.3541, arXiv.org, revised Mar 2008.
    11. Cantono, Simona, 2012. "Unveiling diffusion dynamics: an autocatalytic percolation model of environmental innovation diffusion and the optimal dynamic path of adoption subsidies," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201222, University of Turin.
    12. Silverberg,Gerald & Verspagen,Bart, 2002. "A Percolation Model of Innovation in Complex Technology," Research Memorandum 032, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    13. Martin Hohnisch & Sabine Pittnauer & Dietrich Stauffer, 2006. "A Percolation-Based Model Explaining Delayed Take-Off in New-Product Diffusion," Bonn Econ Discussion Papers bgse9_2006, University of Bonn, Germany.
    14. Estrada, Fernando, 2009. "Tamaño y Riesgo en los Mercados Financieros
      [Size and Risk in the Finanzal Markets]
      ," MPRA Paper 19267, University Library of Munich, Germany.
    15. 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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