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Strategies for the Diffusion of Innovations on Social Networks

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  • Floortje Alkemade

    ()

  • Carolina Castaldi

Abstract

We investigate the spread of innovations on a social network. The network consists of agents that are exposed to the introduction of a new product. Consumers decide whether or not to buy the product based on their own preferences and the decisions of their neighbors in the social network. We use and extend concepts from the literature on epidemics and herd behavior to study this problem. The central question of this paper is whether firms can learn about the network structure and consumer characteristics when only limited information is available, and use this information to evolve a successful directed-advertising strategy. In order to do so, we extend existing models to allow for heterogeneous agents and both positive and negative externalities. The firm can learn a directed-advertising strategy that takes into account both the topology of the social consumer network and the characteristics of the consumer. Such directed-advertising strategies outperform random advertising. Copyright Springer Science + Business Media, Inc. 2005

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Bibliographic Info

Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 25 (2005)
Issue (Month): 1 (February)
Pages: 3-23

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Handle: RePEc:kap:compec:v:25:y:2005:i:1:p:3-23

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Web page: http://www.springerlink.com/link.asp?id=100248
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Keywords: agents; learning; heterogeneous agents;

References

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  1. Bernheim, B Douglas, 1994. "A Theory of Conformity," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 102(5), pages 841-77, October.
  2. H Peyton Young, 2000. "The Diffusion of Innovations in Social Networks," Economics Working Paper Archive 437, The Johns Hopkins University,Department of Economics.
  3. Robin Cowan & William Cowan & G.M. Peter Swann, 2004. "Waves in consumption with interdependence among consumers," Canadian Journal of Economics, Canadian Economics Association, vol. 37(1), pages 149-177, February.
  4. M. E. J. Newman & D. J. Watts, 1999. "Scaling and Percolation in the Small-World Network Model," Working Papers, Santa Fe Institute 99-05-034, Santa Fe Institute.
  5. Joseph Farrell & Garth Saloner, 1986. "Installed Base and Compatibility, With Implications for Product Preannouncements," Working papers 411, Massachusetts Institute of Technology (MIT), Department of Economics.
  6. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-40, June.
  7. 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, University of Chicago Press, vol. 100(5), pages 992-1026, October.
  8. Cowan,Robin & Jonard,Nicolas, 1999. "Network Structure and the Diffusion of Knowledge," Research Memorandum 026, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
  9. Cowan, Robin & Cowan, William & Swann, Peter, 1997. "A model of demand with interactions among consumers," International Journal of Industrial Organization, Elsevier, Elsevier, vol. 15(6), pages 711-732, October.
  10. Ellison, Glenn, 1993. "Learning, Local Interaction, and Coordination," Econometrica, Econometric Society, Econometric Society, vol. 61(5), pages 1047-71, September.
  11. David, Paul A, 1985. "Clio and the Economics of QWERTY," American Economic Review, American Economic Association, vol. 75(2), pages 332-37, May.
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Cited by:
  1. Sorda, G. & Sunak, Y. & Madlener, R., 2013. "An agent-based spatial simulation to evaluate the promotion of electricity from agricultural biogas plants in Germany," Ecological Economics, Elsevier, vol. 89(C), pages 43-60.
  2. Pedro Campos & Pavel Brazdil & Isabel Mota, 2011. "Comparing Strategies of Collaborative Networks for R&D: an agent-based study," FEP Working Papers 405, Universidade do Porto, Faculdade de Economia do Porto.
  3. Floris J. Huétink & Alexander van der Vooren & Floortje Alkemade, 2009. "Initial infrastructure development strategies for the transition to sustainable mobility," Innovation Studies Utrecht (ISU) working paper series 09-05, Utrecht University, Department of Innovation Studies, revised Mar 2009.
  4. Delre, S.A. & Jager, W. & Bijmolt, T.H.A. & Janssen, M.A., 2007. "Targeting and timing promotional activities: An agent-based model for the takeoff of new products," Journal of Business Research, Elsevier, vol. 60(8), pages 826-835, August.
  5. Natalie Svarcova & Petr Svarc, 2008. "Technology adoption and herding behavior in complex social networks," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies 2008/07, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2008.
  6. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, Springer, vol. 20(3), pages 329-373, June.

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