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Diffusion of two brands in competition: Cross-brand effect

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  • Laciana, C.E.
  • Gual, G.
  • Kalmus, D.
  • Oteiza-Aguirre, N.
  • Rovere, S.L.

Abstract

We study the equilibrium points of a system of equations corresponding to a Bass based model that describes the diffusion of two brands in competition. To increase the understanding of the effects of the cross-brand parameters, we perform a sensitivity analysis. Finally, we show a comparison with an agent-based model inspired in the Potts model. Conclusions include that both models give the same diffusion curves only when the cross coefficients are not null.

Suggested Citation

  • Laciana, C.E. & Gual, G. & Kalmus, D. & Oteiza-Aguirre, N. & Rovere, S.L., 2014. "Diffusion of two brands in competition: Cross-brand effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 104-115.
    • Handle: RePEc:eee:phsmap:v:413:y:2014:i:c:p:104-115
    DOI: 10.1016/j.physa.2014.06.019
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    References listed on IDEAS

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    1. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
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    4. Laciana, Carlos E. & Rovere, Santiago L. & Podestá, Guillermo P., 2013. "Exploring associations between micro-level models of innovation diffusion and emerging macro-level adoption patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1873-1884.
    5. Laciana, Carlos E. & Rovere, Santiago L., 2011. "Ising-like agent-based technology diffusion model: Adoption patterns vs. seeding strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1139-1149.
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    7. Laciana, Carlos E. & Oteiza-Aguirre, Nicolás, 2014. "An agent based multi-optional model for the diffusion of innovations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 254-265.
    8. 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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    Cited by:

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