IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2202.00729.html
   My bibliography  Save this paper

The Impact of Connectivity on the Production and Diffusion of Knowledge

Author

Listed:
  • Gustavo Manso
  • Farzad Pourbabaee

Abstract

We study a social bandit problem featuring production and diffusion of knowledge. While higher connectivity enhances knowledge diffusion, it may reduce knowledge production as agents shy away from experimentation with new ideas and free ride on the observation of other agents. As a result, under some conditions, greater connectivity can lead to homogeneity and lower social welfare.

Suggested Citation

  • Gustavo Manso & Farzad Pourbabaee, 2022. "The Impact of Connectivity on the Production and Diffusion of Knowledge," Papers 2202.00729, arXiv.org.
  • Handle: RePEc:arx:papers:2202.00729
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2202.00729
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aoyagi, Masaki, 1998. "Mutual Observability and the Convergence of Actions in a Multi-Person Two-Armed Bandit Model," Journal of Economic Theory, Elsevier, vol. 82(2), pages 405-424, October.
    2. Darrell Duffie & Semyon Malamud & Gustavo Manso, 2009. "Information Percolation With Equilibrium Search Dynamics," Econometrica, Econometric Society, vol. 77(5), pages 1513-1574, September.
    3. Gustavo Manso, 2011. "Motivating Innovation," Journal of Finance, American Finance Association, vol. 66(5), pages 1823-1860, October.
    4. Bonatti, Alessandro & Hörner, Johannes, 2017. "Learning to disagree in a game of experimentation," Journal of Economic Theory, Elsevier, vol. 169(C), pages 234-269.
    5. Mira Frick & Yuhta Ishii, 2015. "Innovation Adoption by Forward-Looking Social Learners," Cowles Foundation Discussion Papers 1877, Cowles Foundation for Research in Economics, Yale University.
    6. Godfrey Keller & Sven Rady & Martin Cripps, 2005. "Strategic Experimentation with Exponential Bandits," Econometrica, Econometric Society, vol. 73(1), pages 39-68, January.
    7. Alexander Wolitzky, 2018. "Learning from Others' Outcomes," American Economic Review, American Economic Association, vol. 108(10), pages 2763-2801, October.
    8. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
    9. Dinah Rosenberg & Eilon Solan & Nicolas Vieille, 2007. "Social Learning in One-Arm Bandit Problems," Econometrica, Econometric Society, vol. 75(6), pages 1591-1611, November.
    10. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 595-621.
    11. Chamley, Christophe & Gale, Douglas, 1994. "Information Revelation and Strategic Delay in a Model of Investment," Econometrica, Econometric Society, vol. 62(5), pages 1065-1085, September.
    12. Rothschild, Michael, 1974. "A two-armed bandit theory of market pricing," Journal of Economic Theory, Elsevier, vol. 9(2), pages 185-202, October.
    13. Camargo, Braz, 2014. "Learning in society," Games and Economic Behavior, Elsevier, vol. 87(C), pages 381-396.
    14. Heidhues, Paul & Rady, Sven & Strack, Philipp, 2015. "Strategic experimentation with private payoffs," Journal of Economic Theory, Elsevier, vol. 159(PA), pages 531-551.
    15. William R. Kerr & Ramana Nanda & Matthew Rhodes-Kropf, 2014. "Entrepreneurship as Experimentation," Journal of Economic Perspectives, American Economic Association, vol. 28(3), pages 25-48, Summer.
    16. Sadler, Evan, 2020. "Innovation adoption and collective experimentation," Games and Economic Behavior, Elsevier, vol. 120(C), pages 121-131.
    Full references (including those not matched with items on IDEAS)

    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. Camargo, Braz, 2014. "Learning in society," Games and Economic Behavior, Elsevier, vol. 87(C), pages 381-396.
    2. Gomes, Renato & Gottlieb, Daniel & Maestri, Lucas, 2016. "Experimentation and project selection: Screening and learning," Games and Economic Behavior, Elsevier, vol. 96(C), pages 145-169.
    3. Wagner, Peter A. & Klein, Nicolas, 2022. "Strategic investment and learning with private information," Journal of Economic Theory, Elsevier, vol. 204(C).
    4. Simina Br^anzei & Yuval Peres, 2019. "Multiplayer Bandit Learning, from Competition to Cooperation," Papers 1908.01135, arXiv.org, revised Jan 2024.
    5. Keller, Godfrey & Novák, Vladimír & Willems, Tim, 2019. "A note on optimal experimentation under risk aversion," Journal of Economic Theory, Elsevier, vol. 179(C), pages 476-487.
    6. Farzad Pourbabaee, 2022. "Robust experimentation in the continuous time bandit problem," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 73(1), pages 151-181, February.
    7. Osnat Zohar, 2019. "Boom-Bust Cycles of Learning, Investment and Disagreement," Bank of Israel Working Papers 2019.06, Bank of Israel.
    8. Klein, Nicolas, 2013. "Strategic learning in teams," Games and Economic Behavior, Elsevier, vol. 82(C), pages 636-657.
    9. Daron Acemoglu & Asuman Ozdaglar & Sarath Pattathil, 2023. "Learning, Diversity and Adaptation in Changing Environments: The Role of Weak Links," Papers 2305.00474, arXiv.org.
    10. Farzad Pourbabaee, 2021. "Robust Experimentation in the Continuous Time Bandit Problem," Papers 2104.00102, arXiv.org.
    11. Bonatti, Alessandro & Hörner, Johannes, 2017. "Learning to disagree in a game of experimentation," Journal of Economic Theory, Elsevier, vol. 169(C), pages 234-269.
    12. Wuggenig, Mirjam, 2015. "Learning faster or more precisely? Strategic experimentation in networks," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113196, Verein für Socialpolitik / German Economic Association.
    13. Thomas, Caroline, 2019. "Experimentation with reputation concerns – Dynamic signalling with changing types," Journal of Economic Theory, Elsevier, vol. 179(C), pages 366-415.
    14. Chen, Chia-Hui & Ishida, Junichiro & Mukherjee, Arijit, 2023. "Pioneer, early follower or late entrant: Entry dynamics with learning and market competition," European Economic Review, Elsevier, vol. 152(C).
    15. Heidhues, Paul & Rady, Sven & Strack, Philipp, 2015. "Strategic experimentation with private payoffs," Journal of Economic Theory, Elsevier, vol. 159(PA), pages 531-551.
    16. 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.
    17. Francis Bloch & Simona Fabrizi & Steffen Lippert, 2015. "Learning and collusion in new markets with uncertain entry costs," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 58(2), pages 273-303, February.
    18. Rosenberg, Dinah & Solan, Eilon & Vieille, Nicolas, 2009. "Informational externalities and emergence of consensus," Games and Economic Behavior, Elsevier, vol. 66(2), pages 979-994, July.
    19. Johannes Hoelzemann & Nicolas Klein, 2021. "Bandits in the lab," Quantitative Economics, Econometric Society, vol. 12(3), pages 1021-1051, July.
    20. Matan Harel & Elchanan Mossel & Philipp Strack & Omer Tamuz, 2021. "Rational Groupthink," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(1), pages 621-668.
      • Matan Harel & Elchanan Mossel & Philipp Strack & Omer Tamuz, 2014. "Rational Groupthink," Papers 1412.7172, arXiv.org, revised Jun 2020.

    More about this item

    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:arx:papers:2202.00729. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.