IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v49y2015i4p1559-1571.html
   My bibliography  Save this article

Diffusion of innovations in dense and sparse networks

Author

Listed:
  • Mario Eboli

Abstract

This paper puts forward a comparison of the performance of sparsely and densely connected social networks in promoting the diffusion of innovations of uncertain profitability. To this end, we use a threshold model of innovation diffusion, based on a classic model of adoption of innovations via imitation by Jensen (Int. J. Ind. Organ. 6:335–350, 1988 ), to evaluate the probability of diffusion of an innovation in three classes of networks: the circular, the star-shaped and the complete networks. We find that, if agents hold a low prior confidence in the profitability of an innovation, then complete networks and star networks with informed agents (i.e., with agents who are aware of the structure of the network and use this information rationally) perform better than circles and than stars with myopic agents. The converse is true for innovations accompanied by initial high expectations about their profitability. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Mario Eboli, 2015. "Diffusion of innovations in dense and sparse networks," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1559-1571, July.
  • Handle: RePEc:spr:qualqt:v:49:y:2015:i:4:p:1559-1571
    DOI: 10.1007/s11135-014-0069-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11135-014-0069-9
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11135-014-0069-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kevin F. McCardle, 1985. "Information Acquisition and the Adoption of New Technology," Management Science, INFORMS, vol. 31(11), pages 1372-1389, November.
    2. Jackson, Matthew O. & Wolinsky, Asher, 1996. "A Strategic Model of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 71(1), pages 44-74, October.
    3. Gabrielle Demange & Wooders Myrna, 2005. "Group Formation in Economics: Networks, Clubs and Coalitions," Post-Print halshs-00576778, HAL.
    4. Jensen, Richard, 1988. "Information capacity and innovation adoption," International Journal of Industrial Organization, Elsevier, vol. 6(3), pages 335-350.
    5. Venkatesh Bala & Sanjeev Goyal, 2000. "A Noncooperative Model of Network Formation," Econometrica, Econometric Society, vol. 68(5), pages 1181-1230, September.
    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. Ellison, Glenn, 1993. "Learning, Local Interaction, and Coordination," Econometrica, Econometric Society, vol. 61(5), pages 1047-1071, September.
    8. Reinganum, Jennifer F., 1985. "A two-stage model of research and development with endogenous second-mover advantages," International Journal of Industrial Organization, Elsevier, vol. 3(3), pages 275-292, September.
    9. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
    10. Lamberson PJ, 2010. "Social Learning in Social Networks," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 10(1), pages 1-33, August.
    11. Demange,Gabrielle & Wooders,Myrna (ed.), 2005. "Group Formation in Economics," Cambridge Books, Cambridge University Press, number 9780521842716.
    12. Hojman, Daniel A. & Szeidl, Adam, 2008. "Core and periphery in networks," Journal of Economic Theory, Elsevier, vol. 139(1), pages 295-309, March.
    13. Ellison, Glenn & Fudenberg, Drew, 1993. "Rules of Thumb for Social Learning," Journal of Political Economy, University of Chicago Press, vol. 101(4), pages 612-643, August.
    14. Schelling, Thomas C, 1969. "Models of Segregation," American Economic Review, American Economic Association, vol. 59(2), pages 488-493, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cai, Yuzhuo, 2023. "Towards a new model of EU-China innovation cooperation: Bridging missing links between international university collaboration and international industry collaboration," Technovation, Elsevier, vol. 119(C).

    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. Sommarat Chantarat & Christopher Barrett, 2012. "Social network capital, economic mobility and poverty traps," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 10(3), pages 299-342, September.
    2. Hellmann, Tim & Staudigl, Mathias, 2014. "Evolution of social networks," European Journal of Operational Research, Elsevier, vol. 234(3), pages 583-596.
    3. Kets, W., 2008. "Networks and learning in game theory," Other publications TiSEM 7713fce1-3131-498c-8c6f-3, Tilburg University, School of Economics and Management.
    4. Ana Mauleon & Huasheng Song & Vincent Vannetelbosch, 2010. "Networks of Free Trade Agreements among Heterogeneous Countries," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 12(3), pages 471-500, June.
    5. Edward L. Glaeser & Jose Scheinkman, 2000. "Non-Market Interactions," NBER Working Papers 8053, National Bureau of Economic Research, Inc.
    6. Olivier Tercieux & Vincent Vannetelbosch, 2006. "A characterization of stochastically stable networks," International Journal of Game Theory, Springer;Game Theory Society, vol. 34(3), pages 351-369, October.
    7. Philippe Bich & Lisa Morhaim, 2020. "On the Existence of Pairwise Stable Weighted Networks," Mathematics of Operations Research, INFORMS, vol. 45(4), pages 1393-1404, November.
    8. AJ Bostian & David Goldbaum, 2016. "Emergent Coordination among Competitors," Working Paper Series 36, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    9. Corbae, Dean & Duffy, John, 2008. "Experiments with network formation," Games and Economic Behavior, Elsevier, vol. 64(1), pages 81-120, September.
    10. Edward Cartwright, 2002. "Learning to play approximate Nash equilibria in games with many players," Levine's Working Paper Archive 506439000000000070, David K. Levine.
    11. PAPACCIO, Anna, 2013. "Bilateralism and Multilateralism: a Network Approach," CELPE Discussion Papers 125, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    12. Francesco Feri & Miguel Meléndez-Jiménez, 2013. "Coordination in evolving networks with endogenous decay," Journal of Evolutionary Economics, Springer, vol. 23(5), pages 955-1000, November.
    13. Michel Grabisch & Agnieszka Rusinowska & Xavier Venel, 2019. "Diffusion in countably infinite networks," Documents de travail du Centre d'Economie de la Sorbonne 19017, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    14. Simon Weidenholzer, 2010. "Coordination Games and Local Interactions: A Survey of the Game Theoretic Literature," Games, MDPI, vol. 1(4), pages 1-35, November.
    15. Carrillo, Juan & Gaduh, Arya, 2012. "The Strategic Formation of Networks: Experimental Evidence," CEPR Discussion Papers 8757, C.E.P.R. Discussion Papers.
    16. Page Jr., Frank H. & Wooders, Myrna, 2007. "Networks and clubs," Journal of Economic Behavior & Organization, Elsevier, vol. 64(3-4), pages 406-425.
    17. Syngjoo Choi & Edoardo Gallo & Shachar Kariv, 2015. "Networks in the laboratory," Cambridge Working Papers in Economics 1551, Faculty of Economics, University of Cambridge.
    18. Lippert, Steffen & Spagnolo, Giancarlo, 2011. "Networks of relations and Word-of-Mouth Communication," Games and Economic Behavior, Elsevier, vol. 72(1), pages 202-217, May.
    19. Jean-François Caulier & Michel Grabisch & Agnieszka Rusinowska, 2015. "An allocation rule for dynamic random network formation processes," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 60(2), pages 283-313, October.
    20. Falk Armin & Kosfeld Michael, 2012. "It's all about Connections: Evidence on Network Formation," Review of Network Economics, De Gruyter, vol. 11(3), pages 1-36, September.

    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:spr:qualqt:v:49:y:2015:i:4:p:1559-1571. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.