IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v331y2026i1p260-277.html

Blockchain-enabled quality transparency and invoice tokenization in deep-tier supply chains

Author

Listed:
  • Guo, Penghui
  • Feng, Gengzhong
  • Wang, Kai
  • Wei, Liqun

Abstract

In hierarchical deep-tier supply chains, private quality information in the headstream’s raw materials and financial constraints in the midstream’s product procurement significantly restrict the downstream’s sales and market supply. To address these issues, downstream retailers can implement blockchain technology to trace and transparentize the headstream’s quality information across the chain and finance the midstream by digitizing accounts payable, i.e., invoice tokenization. To investigate how quality information and financing strategies interact, we formulate a multilevel Stackelberg game to analyze a deep-tier supply chain involving a retailer who may adopt blockchain, a tier-1 capital-constrained supplier, and a tier-2 supplier who privately owns quality information and can provide trade credit financing to the tier-1 supplier. Intuitively, blockchain benefits the retailer since transparentizing quality information can attract more purchases. However, we find that this may not be true, especially when the expected quality is relatively low. Interestingly, we find that merely using blockchain-enabled transparency decreases suppliers’ profits, but further incorporating invoice tokenization can benefit them, potentially achieving a triple-win result, although two suppliers’ interests may not always align. Finally, as the expected quality rises, equilibrium results move from trade credit under no blockchain (NT) to trade credit under blockchain-enabled transparency (BT) and then to blockchain-enabled transparency and invoice tokenization (BI) if the price of raw materials is high; otherwise, BI is more likely to be the equilibrium result. Our findings uncover how to utilize blockchain-driven traceability and invoice tokenization strategically.

Suggested Citation

  • Guo, Penghui & Feng, Gengzhong & Wang, Kai & Wei, Liqun, 2026. "Blockchain-enabled quality transparency and invoice tokenization in deep-tier supply chains," European Journal of Operational Research, Elsevier, vol. 331(1), pages 260-277.
  • Handle: RePEc:eee:ejores:v:331:y:2026:i:1:p:260-277
    DOI: 10.1016/j.ejor.2025.09.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221725007271
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2025.09.010?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

    for a different version of it.

    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:eee:ejores:v:331:y:2026:i:1:p:260-277. 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.elsevier.com/locate/eor .

    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.