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Diffusion of innovations in dense and sparse networks

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  • 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

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  • 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
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    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, January.
    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.
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    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).

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