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Globalization and global risk: How risk analysis needs to be enhanced to be effective in confronting current threats

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  • Aven, Terje
  • Zio, Enrico

Abstract

In the last 20-30 years, technological innovation has enabled the advancement of industry at a global scale, giving rise to a truly global society, resting on an interdependent web of transnational technical, economic and social systems. These systems are exposed to scenarios of cascading outbreaks, whose impacts can ripple to very large scales through their strong interdependencies, as recently shown by the pandemic spreading of the Coronavirus. Considerable work has been conducted in recent years to develop frameworks to support the assessment, communication, management and governance of this type of risk, building on concepts like systemic risks, complexity theory, deep uncertainties, resilience engineering, adaptive management and black swans. Yet contemporary risk analysis struggles to provide authoritative societal guidance for adequately handling these types of risks, as clearly illustrated by the Coronavirus case. In this paper, we reflect on this situation. We aim to identify critical challenges in current frameworks of risk assessment and management and point to ways to strengthen these, to be better able to confront threats like the Coronavirus in the future. A set of principles and theses are established, which have the potential to support a common foundation for the many different scientific perspectives and ‘schools’ currently dealing with risk handling issues.

Suggested Citation

  • Aven, Terje & Zio, Enrico, 2021. "Globalization and global risk: How risk analysis needs to be enhanced to be effective in confronting current threats," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
  • Handle: RePEc:eee:reensy:v:205:y:2021:i:c:s0951832020307687
    DOI: 10.1016/j.ress.2020.107270
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    3. Jesse M. Keenan & Benjamin D. Trump & William Hynes & Igor Linkov, 2021. "Exploring the Convergence of Resilience Processes and Sustainable Outcomes in Post-COVID, Post-Glasgow Economies," Sustainability, MDPI, vol. 13(23), pages 1-12, December.
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    9. Lyu, Dongzhen & Niu, Guangxing & Liu, Enhui & Zhang, Bin & Chen, Gang & Yang, Tao & Zio, Enrico, 2022. "Time space modelling for fault diagnosis and prognosis with uncertainty management: A general theoretical formulation," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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