Towards a transdisciplinary approach to systemic risk detection

Conference Paper (2021)
Author(s)

Mark Wever (AgResearch, Lincoln)

Nel Wognum (TU Delft - Air Transport & Operations)

Munir Shah (AgResearch, Lincoln)

Niall O’Leary (Cork Institute of Technology)

Marius George Onofrei (Letterkenny Institute of Technology)

Research Group
Air Transport & Operations
Copyright
© 2021 Mark Wever, Nel Wognum, Munir Shah, Niall O'Leary, George Onofrei
DOI related publication
https://doi.org/10.3233/ATDE210076
More Info
expand_more
Publication Year
2021
Language
English
Copyright
© 2021 Mark Wever, Nel Wognum, Munir Shah, Niall O'Leary, George Onofrei
Research Group
Air Transport & Operations
Pages (from-to)
3-12
ISBN (electronic)
9781643682082
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Systemic risks are potentially harmful events, that could severely disrupt an entire industry or economy. Examples include the bankruptcy of keystone companies and biosecurity incursions. According to the United Nations, detecting and managing systemic risk represents one of the main challenges of the 21st century. Due to increasing complexity and interconnectedness of today's social-technological-biophysical systems, stakeholders relying on individual disciplines to systemic risk detection, or a combination of disciplines that are not well coordinated, will fail to promptly identify key early warning signals of threats. Our paper argues that transdisciplinary approaches are required to make comprehensive and integrative assessments of complex systems. To support stakeholders undertaking such assessments, we propose a framework that will assist them in: (1) better understanding their system and the risks to which it is exposed; (2) selecting complementary disciplines, theories and methods that are relevant to the system and risks in question; and (3) integrating knowledge from these different disciplines to detect a wide range of early warning signals of systemic risk. The framework can be used as a foundation to build transdisciplinary approaches to risk detection.