IDEAS home Printed from https://ideas.repec.org/a/taf/conmgt/v42y2024i4p346-365.html
   My bibliography  Save this article

Uncertainty network modeling method for construction risk management

Author

Listed:
  • Roope Nyqvist
  • Antti Peltokorpi
  • Olli Seppänen

Abstract

In recent decades, uncertainty management has increasingly elicited attention in construction management research due to increasing project complexity. However, existing management methods have not been able to solve the issues around risk and uncertainty, and regardless of the proposed network-based risk modeling approaches, there are insufficiencies in contemporary methods, such as their practical applicability. This study examined the current state and issues of uncertainty and risk management and proposed a novel uncertainty network model (UNM) as a solution. The uncertainty network model was designed and validated using design science methodology (DSM), drawing on literature and empirical data from interviews, questionnaires, case observations, and case testing. The UNM visually presents project risks, uncertainties, and their interconnections and criticality transforming project stakeholders’ tacit knowledge into an explicit, systematic representation of a project’s uncertainty and risk architecture. Applied to a real-world construction project, the model received positive feedback, demonstrating its effectiveness in enhancing practitioners’ understanding of networked risks and the potential to guide cost-effective risk-control activities by applying a systemic lens to project management. This practical validation showcases the model’s potential in addressing the shortcomings of existing methods and improving construction project risk management.

Suggested Citation

  • Roope Nyqvist & Antti Peltokorpi & Olli Seppänen, 2024. "Uncertainty network modeling method for construction risk management," Construction Management and Economics, Taylor & Francis Journals, vol. 42(4), pages 346-365, April.
  • Handle: RePEc:taf:conmgt:v:42:y:2024:i:4:p:346-365
    DOI: 10.1080/01446193.2023.2266760
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01446193.2023.2266760
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/01446193.2023.2266760?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.

    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:conmgt:v:42:y:2024:i:4:p:346-365. 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/RCME20 .

    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.