IDEAS home Printed from https://ideas.repec.org/p/zbw/fisisi/s122011.html
   My bibliography  Save this paper

Uncertainty in diffusion of competing technologies and application to electric vehicles

Author

Listed:
  • Plötz, Patrick

Abstract

The diffusion of innovations is an important process and its models have applications in many fields, with particular relevance in technological forecast. The logistic equation is one of most important models in this context. Extensions of this approach as the Lotka-Volterra model have been developed to include the effect of mutual influences between technologies such as competition. However, many of the parameters entering this description are uncertain, difficult to estimate or simply unknown, particularly at early stages of the diffusion. Here, a systematic way to study the effect of uncertain or unknown parameters on the future diffusion of interacting innovations is proposed. The input required is a general qualitative understanding of the system: is the mutual influence positive or negative and does it apply symmetrically to either technology? Since the parameters enter the problem via a set of coupled non-linear differential equations, the approach proposed here goes beyond simple Monte-Carlo-like methods where the result is an explicit function of the parameters. The methodology is developed in detail and applied the case of three types of upcoming electric vehicle propulsion technologies. The findings indicate that competition between electric vehicles and mild hybrid vehicles implies a slow decline of the latter. The approach can easily be generalised to include other initial conditions, more technologies or other technological areas to find stable results for future market evolution independent of specific parameters.

Suggested Citation

  • Plötz, Patrick, 2011. "Uncertainty in diffusion of competing technologies and application to electric vehicles," Working Papers "Sustainability and Innovation" S12/2011, Fraunhofer Institute for Systems and Innovation Research (ISI).
  • Handle: RePEc:zbw:fisisi:s122011
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/52728/1/676492940.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. M. Potters & J. P. Bouchaud & L. Laloux, 2005. "Financial Applications of Random Matrix Theory: Old Laces and New Pieces," Papers physics/0507111, arXiv.org.
    2. Laurent Laloux & Pierre Cizeau & Jean-Philippe Bouchaud & Marc Potters, 1999. "Random matrix theory," Science & Finance (CFM) working paper archive 500052, Science & Finance, Capital Fund Management.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Assaf Almog & Ferry Besamusca & Mel MacMahon & Diego Garlaschelli, 2015. "Mesoscopic Community Structure of Financial Markets Revealed by Price and Sign Fluctuations," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-16, July.
    2. Pierre-Alain Reigneron & Romain Allez & Jean-Philippe Bouchaud, 2010. "Principal Regression Analysis and the index leverage effect," Papers 1011.5810, arXiv.org, revised Feb 2011.
    3. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2018. "Collective behavior of cryptocurrency price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 499-509.
    4. Gautier Marti & Frank Nielsen & Philippe Donnat & S'ebastien Andler, 2016. "On clustering financial time series: a need for distances between dependent random variables," Papers 1603.07822, arXiv.org.
    5. Vincent Tan & Stefan Zohren, 2020. "Estimation of Large Financial Covariances: A Cross-Validation Approach," Papers 2012.05757, arXiv.org, revised Jan 2023.
    6. Assaf Almog & Ferry Besamusca & Mel MacMahon & Diego Garlaschelli, 2015. "Mesoscopic Community Structure of Financial Markets Revealed by Price and Sign Fluctuations," Papers 1504.00590, arXiv.org.
    7. Gorban, Alexander N. & Smirnova, Elena V. & Tyukina, Tatiana A., 2010. "Correlations, risk and crisis: From physiology to finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3193-3217.
    8. Sebastien Valeyre, 2020. "Refined model of the covariance/correlation matrix between securities," Papers 2001.08911, arXiv.org.
    9. Fabio Caccioli & Imre Kondor & Matteo Marsili & Susanne Still, 2016. "Liquidity Risk And Instabilities In Portfolio Optimization," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(05), pages 1-28, August.
    10. Sebastien Valeyre & Denis Grebenkov & Sofiane Aboura & Francois Bonnin, 2016. "Should employers pay their employees better? An asset pricing approach," Papers 1602.00931, arXiv.org, revised Oct 2016.
    11. Raphael Douady & Antoine Kornprobst, 2018. "An Empirical Approach To Financial Crisis Indicators Based On Random Matrices," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(03), pages 1-22, May.
    12. Svensson, Jens, 2007. "The asymptotic spectrum of the EWMA covariance estimator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 621-630.
    13. Emmanuelle Jay & Thibault Soler & Jean-Philippe Ovarlez & Philippe de Peretti & Christophe Chorro, 2019. "Robust covariance matrix estimation and portfolio allocation: the case of non-homogeneous assets," Post-Print halshs-02372443, HAL.
    14. Nguyen, Q. & Nguyen, N.K.K., 2019. "Composition of the first principal component of a stock index — A comparison between SP500 and VNIndex," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    15. George Barnes & Sanjaye Ramgoolam & Michael Stephanou, 2023. "Permutation invariant Gaussian matrix models for financial correlation matrices," Papers 2306.04569, arXiv.org.
    16. Emmanuelle Jay & Thibault Soler & Eugénie Terreaux & Jean-Philippe Ovarlez & Frédéric Pascal & Philippe De Peretti & Christophe Chorro, 2019. "Improving portfolios global performance using a cleaned and robust covariance matrix estimate," Documents de travail du Centre d'Economie de la Sorbonne 19022, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    17. Linda Margarita Medina Herrera & Ernesto Armando Pacheco Velazquez, 2013. "Spectral Analysis And Networks In Financial Correlation Matrices, Analisis Espectral Y Redes En Matrices De Correlacion Financiera," Revista Internacional Administracion & Finanzas, The Institute for Business and Finance Research, vol. 6(6), pages 15-28.
    18. Paolo Giudici & Gloria Polinesi & Alessandro Spelta, 2022. "Network models to improve robot advisory portfolios," Annals of Operations Research, Springer, vol. 313(2), pages 965-989, June.
    19. Galazka, Marek, 2011. "Characteristics of the Polish Stock Market correlations," International Review of Financial Analysis, Elsevier, vol. 20(1), pages 1-5, January.
    20. Coronado Ramírez Semei Leopoldo & Porras Serrano Jesús & Sandoval Bravo Salvador, 2013. "Aplicación de bicorrelación cruzada al rendimiento diario del precio del café," Contaduría y Administración, Accounting and Management, vol. 58(1), pages 117-129, enero-mar.

    More about this item

    Keywords

    diffusion of innovations; logistic equation; competition; electric vehicles; Monte Carlo methods;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:fisisi:s122011. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/isfhgde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.