IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/102538.html
   My bibliography  Save this paper

The speed of innovation diffusion in social networks

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/102538/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Timothy Conley & Udry Christopher, 2001. "Social Learning Through Networks: The Adoption of New Agricultural Technologies in Ghana," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 668-673.
    2. Itai Arieli & H. Peyton Young, 2016. "Stochastic Learning Dynamics and Speed of Convergence in Population Games," Econometrica, Econometric Society, vol. 84, pages 627-676, March.
    3. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    4. Blume Lawrence E., 1993. "The Statistical Mechanics of Strategic Interaction," Games and Economic Behavior, Elsevier, vol. 5(3), pages 387-424, July.
    5. Benjamin Golub & Matthew O. Jackson, 2012. "How Homophily Affects the Speed of Learning and Best-Response Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(3), pages 1287-1338.
    6. Burke, Mary A. & Fournier, Gary M. & Prasad, Kislaya, 2010. "Geographic variations in a model of physician treatment choice with social interactions," Journal of Economic Behavior & Organization, Elsevier, vol. 73(3), pages 418-432, March.
    7. Hans-Peter Kohler & Jere Behrman & Susan Watkins, 2001. "The density of social networks and fertility decisions: evidence from south nyanza district, kenya," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 43-58, February.
    8. Arieli, Itai & Young, H. Peyton, 2016. "Stochastic learning dynamics and speed of convergence in population games," LSE Research Online Documents on Economics 68715, London School of Economics and Political Science, LSE Library.
    9. Vega-Redondo,Fernando, 2007. "Complex Social Networks," Cambridge Books, Cambridge University Press, number 9780521674096, January.
    10. Munshi, Kaivan, 2004. "Social learning in a heterogeneous population: technology diffusion in the Indian Green Revolution," Journal of Development Economics, Elsevier, vol. 73(1), pages 185-213, February.
    11. Mary A. Burke & Gary M. Fournier & Kislaya Prasad, 2007. "The Diffusion of a Medical Innovation: Is Success in the Stars?," Southern Economic Journal, John Wiley & Sons, vol. 73(3), pages 588-603, January.
    12. Amitabh Chandra & Douglas O. Staiger, 2007. "Productivity Spillovers in Health Care: Evidence from the Treatment of Heart Attacks," Journal of Political Economy, University of Chicago Press, vol. 115(1), pages 103-140.
    13. Vega-Redondo,Fernando, 2007. "Complex Social Networks," Cambridge Books, Cambridge University Press, number 9780521857406, January.
    14. Ellison, Glenn & Fudenberg, Drew & Imhof, Lorens A., 2016. "Fast convergence in evolutionary models: A Lyapunov approach," Journal of Economic Theory, Elsevier, vol. 161(C), pages 1-36.
    15. Munshi, Kaivan & Myaux, Jacques, 2006. "Social norms and the fertility transition," Journal of Development Economics, Elsevier, vol. 80(1), pages 1-38, June.
    16. Elchanan Mossel & Allan Sly & Omer Tamuz, 2015. "Strategic Learning and the Topology of Social Networks," Econometrica, Econometric Society, vol. 83(5), pages 1755-1794, September.
    17. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    18. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    19. Jackson, Matthew O. & Watts, Alison, 2002. "The Evolution of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 106(2), pages 265-295, October.
    20. ,, 2013. "A general framework for rational learning in social networks," Theoretical Economics, Econometric Society, vol. 8(1), January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Delia Coculescu & M'ed'eric Motte & Huy^en Pham, 2023. "Opinion dynamics in communities with major influencers and implicit social influence via mean-field approximation," Papers 2306.16553, arXiv.org.
    2. Julian Hidalgo & Michelle Sovinsky, 2023. "Internet (Power) to the People: How to Bridge the Digital Divide," CRC TR 224 Discussion Paper Series crctr224_2023_461, University of Bonn and University of Mannheim, Germany.
    3. Sawa, Ryoji & Wu, Jiabin, 2023. "Statistical inference in evolutionary dynamics," Games and Economic Behavior, Elsevier, vol. 137(C), pages 294-316.
    4. Chellig, Jordan & Durbac, Calina & Fountoulakis, Nikolaos, 2022. "Best response dynamics on random graphs," Games and Economic Behavior, Elsevier, vol. 131(C), pages 141-170.
    5. Ruoxi Ma & Shangguang Yang, 2023. "The Effect of Social Network on Controlled-Release Fertilizer Use: Evidence from Rice Large-Scale Farmers in Jiangsu Province, China," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
    6. Rehse, Dominik & Tremöhlen, Felix, 2022. "Fostering participation in digital contact tracing," Information Economics and Policy, Elsevier, vol. 58(C).
    7. Ryoji Sawa, 2022. "Statistical Inference in Evolutionary Dynamics," Working Papers e170, Tokyo Center for Economic Research.
    8. Gong, Qingbin & Diao, Xundi, 2023. "The impacts of investor network and herd behavior on market stability: Social learning, network structure, and heterogeneity," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1388-1398.
    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.
    11. Srinivas Arigapudi & Yuval Heller & Amnon Schreiber, 2023. "Heterogeneous Noise and Stable Miscoordination," Papers 2305.10301, arXiv.org.
    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. H Peyton Young & Itai Arieli & Yakov Babichenko & Ron Peretz, 2019. "The Speed of Innovation Diffusion in Social Networks," Economics Series Working Papers 884, University of Oxford, Department of Economics.
    3. Itai Arieli & Yakov Babichenko & Ron Peretz & H. Peyton Young, 2019. "The Speed of Innovation Diffusion in Social Networks," Economics Papers 2019-W07, Economics Group, Nuffield College, University of Oxford.
    4. Itai Arieli & Yakov Babichenko & Ron Peretz & H. Peyton Young, 2020. "The Speed of Innovation Diffusion in Social Networks," Econometrica, Econometric Society, vol. 88(2), pages 569-594, March.
    5. H Peyton Young & Lucas Merrill Brown, 2016. "The Diffusion of a Social Innovation: Executive Stock Options from 1936," Economics Series Working Papers 777, University of Oxford, Department of Economics.
    6. Camilo García-Jimeno & Angel Iglesias & Pinar Yildirim, 2018. "Women, Rails and Telegraphs: An Empirical Study of Information Diffusion and Collective Action," NBER Working Papers 24495, National Bureau of Economic Research, Inc.
    7. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    8. Daron Acemoglu & Munther A. Dahleh & Ilan Lobel & Asuman Ozdaglar, 2011. "Bayesian Learning in Social Networks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(4), pages 1201-1236.
    9. Hellmann, Tim & Staudigl, Mathias, 2014. "Evolution of social networks," European Journal of Operational Research, Elsevier, vol. 234(3), pages 583-596.
    10. Islam, Asadul & Ushchev, Philip & Zenou, Yves & Zhang, Xin, 2019. "The Value of Information in Technology Adoption," IZA Discussion Papers 12672, Institute of Labor Economics (IZA).
    11. Tsakas, Nikolas, 2017. "Diffusion by imitation: The importance of targeting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 139(C), pages 118-151.
    12. Matthew O. Jackson & Brian W. Rogers & Yves Zenou, 2016. "Networks: An Economic Perspective," Papers 1608.07901, arXiv.org.
    13. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications,, Elsevier.
    14. H Peyton Young, 2014. "The Evolution of Social Norms," Economics Series Working Papers 726, University of Oxford, Department of Economics.
    15. B Kelsey Jack, "undated". "Market Inefficiencies and the Adoption of Agricultural Technologies in Developing Countries," CID Working Papers 50, Center for International Development at Harvard University.
    16. Pongou, Roland & Serrano, Roberto, 2013. "Dynamic Network Formation in Two-Sided Economies," MPRA Paper 46021, University Library of Munich, Germany.
    17. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
    18. Pongou, Roland & Serrano, Roberto, 2016. "Volume of trade and dynamic network formation in two-sided economies," Journal of Mathematical Economics, Elsevier, vol. 63(C), pages 147-163.
    19. Fishman, Arthur & Fishman, Ram & Gneezy, Uri, 2019. "A tale of two food stands: Observational learning in the field," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 101-108.
    20. Nicholas Magnan & David J Spielman & Travis J. Lybbert & Kajal Gulati, 2013. "Leveling with Friends: Social Networks and Indian Farmers’ Demand for Agricultural Custom Hire Services," Working Papers id:5591, eSocialSciences.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ehl:lserod:102538. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.