IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v72y2026i6p4597-4609.html

Balancing Power in Decentralized Governance: Quadratic Voting and Information Aggregation

Author

Listed:
  • Alon Benhaim

    (Department of Mathematics, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Brett Hemenway Falk

    (Computer and Information Science Department, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Gerry Tsoukalas

    (Questrom School of Business, Boston University, Boston, Massachusetts 02215)

Abstract

In decentralized governance, quadratic voting (QV)—where the cost of acquiring voting power is convex—optimally aggregates voter preferences, outperforming simpler linear voting (LV) mechanisms when voters have complete information. But what if they do not? We show that uncertainty not only breaks QV optimality but can also cause it to underperform LV. Intuitively, this is because cost convexity can disincentivize better-informed voters from adequately conveying their private information. The optimal mechanism varies with the distribution of stakes and information among voters, implying that QV’s known advantages in preference aggregation do not readily extend to common-value information aggregation settings.

Suggested Citation

  • Alon Benhaim & Brett Hemenway Falk & Gerry Tsoukalas, 2026. "Balancing Power in Decentralized Governance: Quadratic Voting and Information Aggregation," Management Science, INFORMS, vol. 72(6), pages 4597-4609, June.
    • Handle: RePEc:inm:ormnsc:v:72:y:2026:i:6:p:4597-4609
    DOI: 10.1287/mnsc.2024.08469
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2024.08469
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.2024.08469?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:inm:ormnsc:v:72:y:2026:i:6:p:4597-4609. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.