IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v204y2024ics0040162524002130.html
   My bibliography  Save this article

Towards novel blockchain decentralised autonomous organisation (DAO) led corporate governance framework

Author

Listed:
  • Saurabh, Kumar
  • Rani, Neelam
  • Upadhyay, Parijat

Abstract

Decentralised autonomous organisation (DAO) powered by blockchain technologies has the potential to transform the organisational governance model with the foundations of algorithmic trust and democratic systems. DAO envisages a decentralised democratic organisation using software-based smart contracts to execute autonomous transactions with consensus among stakeholders. The study investigates the prospects of adopting DAO led corporate governance to manage agency (theory) problems in the light of institutional (theory) pressures. The paper depicts how algorithmic trust led corporate governance measures help any organisation follow policies, rules and regulations using DAO led corporate governance (DAOCG) framework. The authors mapped the constituents of agency theory, ethical decision-making, and institutional factors to propose the DAOCG framework. The DAOCG framework is assessed using a thematic analysis of 16 expert interviews with relevant experience from corporate governance and audit domains from varied industries across geographies. The research leveraged MAXQDA software to analyse interview transcripts and opinion codes. The framework helps to identify the core elements of DAO-led corporate governance (DAOCG) and provides the potential to study the theoretically sequenced practical constituents of corporate governance. The first-of-its-kind practical DAOCG framework can be used in the pursuits of digital transformation, business model innovation and social change.

Suggested Citation

  • Saurabh, Kumar & Rani, Neelam & Upadhyay, Parijat, 2024. "Towards novel blockchain decentralised autonomous organisation (DAO) led corporate governance framework," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:tefoso:v:204:y:2024:i:c:s0040162524002130
    DOI: 10.1016/j.techfore.2024.123417
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162524002130
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2024.123417?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:eee:tefoso:v:204:y:2024:i:c:s0040162524002130. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.