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The speed of innovation diffusion in social networks

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  • Arieli, Itai
  • Babichenko, Yakov
  • Peretz, Ron
  • Young, H. Peyton

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, 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 (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

  • Arieli, Itai & Babichenko, Yakov & Peretz, Ron & Young, H. Peyton, 2020. "The speed of innovation diffusion in social networks," LSE Research Online Documents on Economics 102538, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:102538
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    File URL: http://eprints.lse.ac.uk/102538/
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    References listed on IDEAS

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    9. Marcel Fafchamps & Måns Söderbom & Monique van den Boogart, 2022. "Adoption with Social Learning and Network Externalities," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1259-1282, December.
    10. Rehse, Dominik & Tremöhlen, Felix, 2020. "Fostering participation in digital public health interventions: The case of digital contact tracing," ZEW Discussion Papers 20-076, ZEW - Leibniz Centre for European Economic Research.
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    12. Trieste, Leopoldo & Geisler, Elie & Turchetti, Giuseppe, 2022. "Columbus' egg and the engineer's effect in forecasting solutions adoption," Technological Forecasting and Social Change, Elsevier, vol. 183(C).

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    More about this item

    Keywords

    Innovation diffusion; social networks; speed of equilibrium convergence;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics

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