IDEAS home Printed from https://ideas.repec.org/p/ver/wpaper/16-2014.html
   My bibliography  Save this paper

Instability And Network Effects In Innovative Markets

Author

Listed:
  • Paolo Sgrignoli

    (Department of Economics (University of Verona))

  • Elena Agliari

    (University of Parma)

  • Raffaella Burioni

    (University of Parma)

  • Augusto Schianchi

    (University of Parma)

Abstract

We consider a network of interacting agents and we model the process of choice on the adoption of a given innovative product by means of statistical mechanics tools. The modelization allows us to focus on the effects of direct interactions among agents in establishing the success or failure of the product itself. Mimicking real systems, the whole population is divided into two sub-communities called, respectively, Innovators and Followers, where the former are assumed to display more influence power. We study in detail and via numerical simulations on a random graph two different scenarios: no-feedback interaction, where innovators are cohesive and not sensitively affected by the remaining population, and feedback interaction, where the influence of followers on innovators is non negligible. The outcomes are markedly different: in the former case, which corresponds to the creation of a niche in the market, Innovators are able to drive and polarize the whole market. In the latter case the behavior of the market cannot be definitely predicted and become unstable. In both cases we highlight the emergence of collective phenomena and we show how the final outcome, in terms of the number of buyers, is affected by the concentration of innovators and by the interaction strengths among agents.

Suggested Citation

  • Paolo Sgrignoli & Elena Agliari & Raffaella Burioni & Augusto Schianchi, 2014. "Instability And Network Effects In Innovative Markets," Working Papers 16/2014, University of Verona, Department of Economics.
  • Handle: RePEc:ver:wpaper:16/2014
    as

    Download full text from publisher

    File URL: http://dse.univr.it/home/workingpapers/wp2014n16.pdf
    File Function: First version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. , & , & ,, 2014. "Dynamics of information exchange in endogenous social networks," Theoretical Economics, Econometric Society, vol. 9(1), January.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    3. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
    4. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    5. Peter M. DeMarzo & Dimitri Vayanos & Jeffrey Zwiebel, 2003. "Persuasion Bias, Social Influence, and Unidimensional Opinions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(3), pages 909-968.
    6. 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.
    7. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    8. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    9. Andrea Galeotti & Sanjeev Goyal, 2010. "The Law of the Few," American Economic Review, American Economic Association, vol. 100(4), pages 1468-1492, September.
    10. Galeotti, Andrea & Ghiglino, Christian & Squintani, Francesco, 2013. "Strategic information transmission networks," Journal of Economic Theory, Elsevier, vol. 148(5), pages 1751-1769.
    11. Galeotti, Andrea & Ghiglino, Christian & Squintani, Francesco, 2009. "Strategic Information Transmission in Networks," Economics Discussion Papers 2974, University of Essex, Department of Economics.
    12. Cerqueti, Roy & Tramontanta, Fabio & Ventura, Marco, 2012. "On the dynamics of innovators and imitators," MPRA Paper 38949, University Library of Munich, Germany.
    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. Syngjoo Choi & Edoardo Gallo & Shachar Kariv, 2015. "Networks in the laboratory," Cambridge Working Papers in Economics 1551, Faculty of Economics, University of Cambridge.
    2. Daron Acemoglu & Asuman Ozdaglar, 2011. "Opinion Dynamics and Learning in Social Networks," Dynamic Games and Applications, Springer, vol. 1(1), pages 3-49, March.
    3. , & , & ,, 2014. "Dynamics of information exchange in endogenous social networks," Theoretical Economics, Econometric Society, vol. 9(1), January.
    4. 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.
    5. Mercure, Jean-François, 2018. "Fashion, fads and the popularity of choices: Micro-foundations for diffusion consumer theory," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 194-207.
    6. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska & Emily Tanimura, 2015. "Strategic influence in social networks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01158168, HAL.
    7. Battiston, Pietro & Stanca, Luca, 2015. "Boundedly rational opinion dynamics in social networks: Does indegree matter?," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 400-421.
    8. H Peyton Young & Lucas Merrill Brown, 2016. "The Diffusion of a Social Innovation: Executive Stock Options from 1936," Economics Series Working Papers 777, University of Oxford, Department of Economics.
    9. 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.
    10. Zhu, Z.;, 2023. "The Value of Patients: Heterogenous Physician Learning and Generic Drug Diffusion," Health, Econometrics and Data Group (HEDG) Working Papers 23/12, HEDG, c/o Department of Economics, University of York.
    11. Jakob Grazzini & Domenico Massaro, 2021. "Dispersed information, social networks, and aggregate behavior," Economic Inquiry, Western Economic Association International, vol. 59(3), pages 1129-1148, July.
    12. Aymanns, Christoph & Georg, Co-Pierre, 2015. "Contagious synchronization and endogenous network formation in financial networks," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 273-285.
    13. Acemoglu, Daron & Ozdaglar, Asuman & ParandehGheibi, Ali, 2010. "Spread of (mis)information in social networks," Games and Economic Behavior, Elsevier, vol. 70(2), pages 194-227, November.
    14. Fang, Aili & Wang, Lin & Wei, Xinjiang, 2019. "Social learning with multiple true states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 375-386.
    15. , & ,, 2015. "Information diffusion in networks through social learning," Theoretical Economics, Econometric Society, vol. 10(3), September.
    16. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska & Emily Tanimura, 2018. "Strategic Influence in Social Networks," Mathematics of Operations Research, INFORMS, vol. 43(1), pages 29-50, February.
    17. Pradelski, Bary S.R., 2023. "Social influence: The Usage History heuristic," Mathematical Social Sciences, Elsevier, vol. 123(C), pages 105-113.
    18. Jonas Hedlund & Carlos Oyarzun, 2018. "Imitation in heterogeneous populations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(4), pages 937-973, June.
    19. Buechel, Berno & Hellmann, Tim & Klößner, Stefan, 2015. "Opinion dynamics and wisdom under conformity," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 240-257.
    20. Rusinowska, Agnieszka & Taalaibekova, Akylai, 2019. "Opinion formation and targeting when persuaders have extreme and centrist opinions," Journal of Mathematical Economics, Elsevier, vol. 84(C), pages 9-27.

    More about this item

    Keywords

    Innovation diffusion; Agent-based; Collective phenomena; Innovators; Random network;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

    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:ver:wpaper:16/2014. 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: Michael Reiter (email available below). General contact details of provider: https://edirc.repec.org/data/isverit.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.