| Literature DB >> 29694670 |
Igor Linkov1, Cate Fox-Lent1, Laura Read1, Craig R Allen2, James C Arnott3,4, Emanuele Bellini5, Jon Coaffee6, Marie-Valentine Florin7, Kirk Hatfield8, Iain Hyde9, William Hynes10, Aleksandar Jovanovic11, Roger Kasperson12, John Katzenberger4, Patrick W Keys13,14, James H Lambert15, Richard Moss16, Peter S Murdoch17, Jose Palma-Oliveira18, Roger S Pulwarty19, Dale Sands20, Edward A Thomas21, Mari R Tye22, David Woods23.
Abstract
Regulatory agencies have long adopted a three-tier framework for risk assessment. We build on this structure to propose a tiered approach for resilience assessment that can be integrated into the existing regulatory processes. Comprehensive approaches to assessing resilience at appropriate and operational scales, reconciling analytical complexity as needed with stakeholder needs and resources available, and ultimately creating actionable recommendations to enhance resilience are still lacking. Our proposed framework consists of tiers by which analysts can select resilience assessment and decision support tools to inform associated management actions relative to the scope and urgency of the risk and the capacity of resource managers to improve system resilience. The resilience management framework proposed is not intended to supplant either risk management or the many existing efforts of resilience quantification method development, but instead provide a guide to selecting tools that are appropriate for the given analytic need. The goal of this tiered approach is to intentionally parallel the tiered approach used in regulatory contexts so that resilience assessment might be more easily and quickly integrated into existing structures and with existing policies. Published 2018. This article is a U.S. government work and is in the public domain in the USA.Keywords: Business processes; disaster preparedness; policy analysis; resilience; risk analysis; systems analysis
Year: 2018 PMID: 29694670 DOI: 10.1111/risa.12991
Source DB: PubMed Journal: Risk Anal ISSN: 0272-4332 Impact factor: 4.000