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Discovery and Diffusion of Knowledge in an Endogenous Social Network

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  • Myong-Hun Chang
  • Joseph E Harrington Jr

Abstract

We explore the evolution of the structure and performance of a social network in a population of individuals who search for local optima in diverse and dynamic task environments. Individuals choose whether to innovate or imitate and, in the latter case, from whom to learn. The probabilities of these possible actions respond to an individual's past experiences using reinforcement learning. Among some of our more interesting findings is that a population's performance is not monotonically increasing in either the reliability of the communication network or the productivity of innovation.

Suggested Citation

  • Myong-Hun Chang & Joseph E Harrington Jr, 2002. "Discovery and Diffusion of Knowledge in an Endogenous Social Network," Economics Working Paper Archive 489, The Johns Hopkins University,Department of Economics.
    • Handle: RePEc:jhu:papers:489
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    References listed on IDEAS

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    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    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. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    4. Venkatesh Bala & Sanjeev Goyal, 2000. "A Noncooperative Model of Network Formation," Econometrica, Econometric Society, vol. 68(5), pages 1181-1230, September.
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    Cited by:

    1. Shelley D. Dionne & Hiroki Sayama & Francis J. Yammarino, 2019. "Diversity and Social Network Structure in Collective Decision Making: Evolutionary Perspectives with Agent-Based Simulations," Complexity, Hindawi, vol. 2019, pages 1-16, March.
    2. Robin Cowan & Nicolas Jonard & Jean-Benoit Zimmermann, 2007. "Bilateral Collaboration and the Emergence of Innovation Networks," Management Science, INFORMS, vol. 53(7), pages 1051-1067, July.
    3. Myong-Hun Chang & Joseph E. Harrington, 2013. "Individual Learning and Social Learning: Endogenous Division of Cognitive Labor in a Population of Co-evolving Problem-Solvers," Administrative Sciences, MDPI, vol. 3(3), pages 1-23, July.
    4. Myong-Hun Chang & Joseph E. Harrington, 2007. "Innovators, Imitators, and the Evolving Architecture of Problem-Solving Networks," Organization Science, INFORMS, vol. 18(4), pages 648-666, August.
    5. Gabriel Galand, 2009. "The Neutrality of Money Revisited with a Bottom-Up Approach: Decentralisation, Limited Information and Bounded Rationality," Computational Economics, Springer;Society for Computational Economics, vol. 33(4), pages 337-360, May.
    6. Gerald C. Kane & Maryam Alavi, 2007. "Information Technology and Organizational Learning: An Investigation of Exploration and Exploitation Processes," Organization Science, INFORMS, vol. 18(5), pages 796-812, October.
    7. Mooweon Rhee & Tohyun Kim, 2014. "Identity-based learning and segregation in social networks under different institutional environments," Computational and Mathematical Organization Theory, Springer, vol. 20(4), pages 339-368, December.
    8. Carlos Sáenz-Royo & Carlos Gracia-Lázaro & Yamir Moreno, 2015. "The Role of the Organization Structure in the Diffusion of Innovations," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-13, May.
    9. Joseph E. Harrington, Jr, 2005. "Innovators, Imitators, and the Evolving Architecture of Social Networks," Economics Working Paper Archive 529, The Johns Hopkins University,Department of Economics.

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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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