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Towards a Transdisciplinary Approach to Systemic Risk Detection

Authors: Mark Wever; Nel Wognum; Munir Shah; Niall O'Leary; George Onofrei;

Towards a Transdisciplinary Approach to Systemic Risk Detection

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.

Country
Netherlands
Keywords

Systemic risk, Risk detection, Transdisciplinary, Early warning systems

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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3
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