IDEAS home Printed from https://ideas.repec.org/a/taf/tjmaxx/v13y2026i2p379-409.html

A method of tri-layer network modeling under strategic objectives for project portfolio risk assessment

Author

Listed:
  • Libiao Bai
  • Fang Li
  • Xuyang Zhao
  • Xixi Luo
  • Hongyu Zhu
  • Ziwen Zhang

Abstract

Risk assessment for project portfolio (PP) is pivotal in aligning strategic objectives (SOs) with organizational value propositions. Despite its significance, the impact of project portfolio risks (PPRs) on achieving SOs remains understudied, potentially causing inaccurate assessment. Applying a Bayesian network (BN) to model a tri-layer (PPR-PP-SO) network, this study bridges the gap and forges a direct connection between PPR assessments and SOs. Initially, the PPR criteria are determined, followed by constructing a BN structure to clarify relationships within the three-layer network. To mitigate data scarcity limitations in BN, Spherical Fuzzy Set and Dempster-Shafer theory are introduced to acquire tri-layer BN parameters. Utilizing propagation analysis of the tri-layer BN, the expected impact of risks on SOs is measured to reveal PPR criticality. A numerical example corroborates the model’s functionality and feasibility. The results indicate the criticality of one PPR varies substantially under different SOs, implying the importance of pinpointing critical risks specific to each SO.

Suggested Citation

  • Libiao Bai & Fang Li & Xuyang Zhao & Xixi Luo & Hongyu Zhu & Ziwen Zhang, 2026. "A method of tri-layer network modeling under strategic objectives for project portfolio risk assessment," Journal of Management Analytics, Taylor & Francis Journals, vol. 13(2), pages 379-409, April.
    • Handle: RePEc:taf:tjmaxx:v:13:y:2026:i:2:p:379-409
    DOI: 10.1080/23270012.2026.2652308
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23270012.2026.2652308
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/23270012.2026.2652308?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

    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:taf:tjmaxx:v:13:y:2026:i:2:p:379-409. 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 Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjma .

    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.