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The Speed of Innovation Diffusion

Author

Listed:
  • Itai Arieli

    (Faculty of Industrial Engineering and Management, Technion–Israel Institute of Technology)

  • Yakov Babichenko

    (Faculty of Industrial Engineering and Management, Technion–Israel Institute of Technology)

  • Ron Peretz

    (Department of Economics, Bar Ilan University)

  • H. Peyton Young

    (London School of Economics and Nuffield College, University of Oxford)

Abstract

New ways of doing things often get started through the actions of a few innovators, then diffuse rapidly as more and more people come into contact with prior adopters in their social network. Much of the literature focuses on the speed of diffusion as a function of the network topology. In practice, however, the topology may not be known with any precision, and it is constantly in flux as links are formed and severed. Here we establish an upper bound on the expected waiting time until a given proportion of the population has adopted that holds independently of the network structure. Kreindler and Young [33, 2014] demonstrated such a bound for regular networks when agents choose between two options: the innovation and the status quo. Our bound holds for directed and undirected networks of arbitrary size and degree distribution, and for multiple competing innovations with different payoffs.

Suggested Citation

  • Itai Arieli & Yakov Babichenko & Ron Peretz & H. Peyton Young, 2018. "The Speed of Innovation Diffusion," Economics Papers 2018-W06, Economics Group, Nuffield College, University of Oxford.
    • Handle: RePEc:nuf:econwp:1806
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    References listed on IDEAS

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    1. Bilancini, Ennio & Boncinelli, Leonardo & Nax, Heinrich H., 2021. "What noise matters? Experimental evidence for stochastic deviations in social norms," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).

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