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Sequential market entries and competition modelling in multi-innovation diffusions

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  • Guseo, Renato
  • Mortarino, Cinzia
Abstract
The diffusion of innovations for simultaneous processes cannot take into account and properly explain systematic perturbations due to competition-substitution effects if they are examined one by one. A first aspect in simultaneous competing diffusions is the distinction between simultaneous market entries (synchronic competition) and sequential entries (diachronic competition). In the latter case, the beginning of competition may upset the first entrant’s diffusion. A second important aspect in multiple competition is represented by the choice to model the word-of-mouth effect either at the category level (balanced model) or at the brand level, separating the within-brand effect from the cross-brand one (unbalanced model). In this paper, balanced models are studied, and we propose a model that allows for a change in the parameter values of the first entrant as soon as the second one enters the market. The resulting differential system has a closed-form solution that enables, through sales data, an empirical validation of the assumptions underlying the model structure, improving the forecasting accuracy. An application to pharmaceutical drug competition is discussed.

Suggested Citation

  • Guseo, Renato & Mortarino, Cinzia, 2012. "Sequential market entries and competition modelling in multi-innovation diffusions," European Journal of Operational Research, Elsevier, vol. 216(3), pages 658-667.
    • Handle: RePEc:eee:ejores:v:216:y:2012:i:3:p:658-667
    DOI: 10.1016/j.ejor.2011.08.018
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    References listed on IDEAS

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    6. Guseo, Renato & Guidolin, Mariangela, 2010. "Cellular Automata with network incubation in information technology diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(12), pages 2422-2433.
    7. Krishnamoorthy, Anand & Prasad, Ashutosh & Sethi, Suresh P., 2010. "Optimal pricing and advertising in a durable-good duopoly," European Journal of Operational Research, Elsevier, vol. 200(2), pages 486-497, January.
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    Citations

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    Cited by:

    1. Porath, Daniel, 2016. "Size and dynamics of order-of-entry effects in pharmaceutical markets," UASM Discussion Paper Series 4/2016, University of Applied Sciences Mainz.
    2. Guidolin, Mariangela & Guseo, Renato, 2015. "Technological change in the U.S. music industry: Within-product, cross-product and churn effects between competing blockbusters," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 35-46.
    3. Guseo, Renato & Guidolin, Mariangela, 2015. "Heterogeneity in diffusion of innovations modelling: A few fundamental types," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 514-524.
    4. Mariangela Guidolin & Renato Guseo, 2020. "Has the iPhone cannibalized the iPad? An asymmetric competition model," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(3), pages 465-476, May.
    5. Semra Gunduc, 2021. "Diffusion of Innovation In Competitive Markets-A Study on the Global Smartphone Diffusion," Papers 2103.07707, arXiv.org.
    6. Furlan, Claudia & Mortarino, Cinzia, 2018. "Forecasting the impact of renewable energies in competition with non-renewable sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1879-1886.
    7. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    8. Fazıl Paç, M. & Savin, Sergei & Velu, Chander, 2018. "When to adopt a service innovation: Nash equilibria in a competitive diffusion framework," European Journal of Operational Research, Elsevier, vol. 271(3), pages 968-984.
    9. Claudia Furlan & Cinzia Mortarino & Mohammad Salim Zahangir, 2021. "Interaction among three substitute products: an extended innovation diffusion model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 269-293, March.
    10. Guidolin, Mariangela & Alpcan, Tansu, 2019. "Transition to sustainable energy generation in Australia: Interplay between coal, gas and renewables," Renewable Energy, Elsevier, vol. 139(C), pages 359-367.
    11. Guseo, Renato & Schuster, Reinhard, 2021. "Modelling dynamic market potential: Identifying hidden automata networks in the diffusion of pharmaceutical drugs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    12. Renato Guseo & Cinzia Mortarino, 2014. "Multivariate nonlinear least squares: robustness and efficiency of standard versus Beauchamp and Cornell methodologies," Computational Statistics, Springer, vol. 29(6), pages 1609-1636, December.
    13. Guseo, Renato, 2016. "Latent heterogeneity effects in modelling individual hazards: A non-proportional approach," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 89-93.
    14. Guseo, Renato & Mortarino, Cinzia & Darda, Md Abud, 2015. "Homogeneous and heterogeneous diffusion models: Algerian natural gas production," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 366-378.
    15. Shi, Xiaohui & Chumnumpan, Pattarin, 2019. "Modelling market dynamics of multi-brand and multi-generational products," European Journal of Operational Research, Elsevier, vol. 279(1), pages 199-210.
    16. Guidolin, Mariangela & Guseo, Renato, 2016. "The German energy transition: Modeling competition and substitution between nuclear power and Renewable Energy Technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1498-1504.

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