IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1411.2167.html
   My bibliography  Save this paper

Comeback kids: an evolutionary approach of the long-run innovation process

Author

Listed:
  • Shidong Wang
  • Renaud Foucart
  • Cheng Wan

Abstract

We provide a theoretical framework to understand when firms may benefit from exploiting previously abandoned technologies and brands. We model for the long run process of innovation, allowing for sustainable diversity and comebacks of old brands and technologies. We present two extensions to the logistic and Lotka-Volterra equations, which describe the diffusion of an innovation. First, we extend the short-term competition to a long-term process characterized by a sequence of innovations and substitutions. Second, by allowing the substitutions to be incomplete, we extend the one-dimensional process to a tree-form multidimensional one featuring diversification throughout the long-term development.

Suggested Citation

  • Shidong Wang & Renaud Foucart & Cheng Wan, 2014. "Comeback kids: an evolutionary approach of the long-run innovation process," Papers 1411.2167, arXiv.org, revised Jul 2016.
    • Handle: RePEc:arx:papers:1411.2167
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1411.2167
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stoneman, P, 1981. "Intra-Firm Diffusion, Bayesian Learning and Profitability," Economic Journal, Royal Economic Society, vol. 91(362), pages 375-388, June.
    2. Karmeshu & Bhargava, S. C. & Jain, V. P., 1985. "A rationale for law of technological substitution," Regional Science and Urban Economics, Elsevier, vol. 15(1), pages 137-141, February.
    3. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
    4. L. Dean Hiebert, 1974. "Risk, Learning, and the Adoption of Fertilizer Responsive Seed Varieties," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 56(4), pages 764-768.
    5. Batten, David, 1982. "On the dynamics of industrial evolution," Regional Science and Urban Economics, Elsevier, vol. 12(3), pages 449-462, August.
    6. Jensen, Richard, 1982. "Adoption and diffusion of an innovation of uncertain profitability," Journal of Economic Theory, Elsevier, vol. 27(1), pages 182-193, June.
    7. Bruckner, E & Ebeling, W & Jimenez Montano, M.A. & Scharnhorst, A., 1996. "Nonlinear Stochastic Effects of Substitution--An Evolutionary Approach," Journal of Evolutionary Economics, Springer, vol. 6(1), pages 1-30, February.
    8. Champagnat, Nicolas, 2006. "A microscopic interpretation for adaptive dynamics trait substitution sequence models," Stochastic Processes and their Applications, Elsevier, vol. 116(8), pages 1127-1160, August.
    9. Parker, Philip M., 1994. "Aggregate diffusion forecasting models in marketing: A critical review," International Journal of Forecasting, Elsevier, vol. 10(2), pages 353-380, September.
    10. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    11. 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.
    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. Edouard Civel & Marc Baudry, 2018. "The Fate of Inventions. What can we learn from Bayesian learning in strategic options model of adoption ?," EconomiX Working Papers 2018-47, University of Paris Nanterre, EconomiX.
    2. Mira Frick & Yuhta Ishii, 2015. "Innovation Adoption by Forward-Looking Social Learners," Cowles Foundation Discussion Papers 1877, Cowles Foundation for Research in Economics, Yale University.
    3. Zhiling Guo & Jianqing Chen, 2018. "Multigeneration Product Diffusion in the Presence of Strategic Consumers," Information Systems Research, INFORMS, vol. 29(1), pages 206-224, March.
    4. Francesco Bogliacino & Giorgio Rampa, 2012. "Quality risk aversion, conjectures, and new product diffusion," Journal of Evolutionary Economics, Springer, vol. 22(5), pages 1081-1115, November.
    5. Richard A. Jensen, 2001. "Strategic Intrafirm Innovation Adoption and Diffusion," Southern Economic Journal, John Wiley & Sons, vol. 68(1), pages 120-132, July.
    6. Rui Leite & Aurora Teixeira, 2012. "Innovation diffusion with heterogeneous networked agents: a computational model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 125-144, October.
    7. Foucart, Renaud & Wan, Cheng & Wang, Shidong, 2018. "Innovations and technological comebacks," International Journal of Research in Marketing, Elsevier, vol. 35(1), pages 1-14.
    8. Kim, Tae-Kyun, 1989. "The factor bias of technical change and technology adoption under uncertainty," ISU General Staff Papers 1989010108000010138, Iowa State University, Department of Economics.
    9. Ferreira, Kevin D. & Lee, Chi-Guhn, 2014. "An integrated two-stage diffusion of innovation model with market segmented learning," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 189-201.
    10. Chen, Yanguang, 2014. "Urban chaos and replacement dynamics in nature and society," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 373-384.
    11. J. G. Smythe, 2002. "Reputation, public information, and physician adoption of an innovation," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 3(2), pages 103-110, June.
    12. Waters, James, 2013. "The influence of information sources on inter- and intra-firm diffusion: evidence from UK farming," MPRA Paper 50955, University Library of Munich, Germany.
    13. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
    14. Boerner, Lars & Severgnini, Battista, 2015. "Time for growth," LSE Research Online Documents on Economics 64495, London School of Economics and Political Science, LSE Library.
    15. Francesco Bogliacino & Giorgio Rampa, 2010. "Monopolistic competition and new products: a conjectural equilibrium approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(1), pages 55-76, June.
    16. Garth Heutel & Erich Muehlegger, 2015. "Consumer Learning and Hybrid Vehicle Adoption," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(1), pages 125-161, September.
    17. Bocquet, Rachel & Brossard, Olivier & Sabatier, Mareva, 2007. "Complementarities in organizational design and the diffusion of information technologies: An empirical analysis," Research Policy, Elsevier, vol. 36(3), pages 367-386, April.
    18. Franses, Philip Hans, 2021. "Modeling box office revenues of motion pictures✰," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    19. Julio A. Crego & Jin Huang, 2017. "Early Birds and Second Mice in the Stock Market," Working Papers wp2018_1717, CEMFI.
    20. Kenneth A. Baerenklau, 2005. "Toward an Understanding of Technology Adoption: Risk, Learning, and Neighborhood Effects," Land Economics, University of Wisconsin Press, vol. 81(1).

    More about this item

    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:arx:papers:1411.2167. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.