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Technology adoption and herding behavior in complex social networks

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Abstract

Using a simple computational model, we study consequences of herding behavior in population of agents connected in networks with different topologies: random networks, small-world networks and scale-free networks. Agents sequentially choose between two technologies using very simple rules based on the previous choice of their immediate neighbors. We show that different seeding of technologies can lead to very different results in the choice of majority of agents. We mainly focus on the situation where one technology is seeded randomly while the other is directed to targeted (highly connected) agents. We show that even if the initial seeding is positively biased toward the first technology (more agents start with the choice of the first technology) the dynamic of the model can result in the majority choosing the second technology under the targeted hub approach. Even if the change to majority choice is highly improbable targeted seeding can lead to more favorable results. The explanation is that targeting hubs enhances the diffusion of the firm’s own technology and halts or slows-down the adoption of the concurrent one. Comparison of the results for different network topologies also leads to the conclusion that the overall results are affected by the distribution of number of connections (degree) of individual agents, mainly by its variance.

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Bibliographic Info

Paper provided by Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies in its series Working Papers IES with number 2008/07.

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Length: 18 pages
Date of creation: May 2008
Date of revision: May 2008
Handle: RePEc:fau:wpaper:wp2008_07

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Keywords: technology adoption; simulation; networks; herding behavior;

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  1. Banerjee, Abhijit V, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, MIT Press, vol. 107(3), pages 797-817, August.
  2. Narduzzo, Alessandro & Warglien, Massimo, 1996. "Learning from the Experience of Others: An Experiment on Information Contagion," Industrial and Corporate Change, Oxford University Press, vol. 5(1), pages 113-26.
  3. 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.
  4. Floortje Alkemade & Carolina Castaldi, 2005. "Strategies for the Diffusion of Innovations on Social Networks," Computational Economics, Society for Computational Economics, vol. 25(1), pages 3-23, February.
  5. Katz, Michael L & Shapiro, Carl, 1986. "Technology Adoption in the Presence of Network Externalities," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 822-41, August.
  6. Sujoy Chakravarty, 2003. "Experimental Evidence on Product Adoption in the Presence of Network Externalities," Review of Industrial Organization, Springer, vol. 23(3_4), pages 233-254, December.
  7. Dosi, Giovanni & Ermoliev, Yuri & Kaniovski, Yuri, 1994. "Generalized urn schemes and technological dynamics," Journal of Mathematical Economics, Elsevier, vol. 23(1), pages 1-19, January.
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