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Risk Anal. 2018 Jun 20. doi: 10.1111/risa.13129. [Epub ahead of print]

Integrative Interdisciplinary Approaches to Critical Infrastructure Interdependency Analysis.

Abstract

There is a growing understanding that cross-sector risks faced by critical infrastructure assets in natural disasters require a collaborative foresight from multiple disciplines. However, current contributions to infrastructure interdependency analysis remain centered in discipline-specific methodologies often constrained by underlying theories and assumptions. This perspective article contributes to ongoing discussions about the uses, challenges, and opportunities provided by interdisciplinary research in critical infrastructure interdependency analysis. In doing so, several modes of integration of computational modeling with contributions from the social sciences and other disciplines are explored to advance knowledge that can improve the infrastructure system resilience under extreme events. Three basic modes of method integration are identified and discussed: (a) integrating engineering models and social science research, (b) engaging communities in participative and collaborative forms of social learning and problem solving using simulation models to facilitate synthesis, exploration, and evaluation of scenarios, and (c) developing interactive simulations where IT systems and humans act as "peers" leveraging the capacity of distributed networked platforms and human-in-the-loop architectures for improving situational awareness, real-time decision making, and response capabilities in natural disasters. Depending on the conceptualization of the issues under investigation, these broadly defined modes of integration can coalesce to address key issues in promoting interdisciplinary research by outlining potential areas of future inquiry that would be most beneficial to the critical infrastructure protection communities.

KEYWORDS:

Computational modeling; interdependent infrastructures; social science research; visualization techniques

PMID:
29924886
DOI:
10.1111/risa.13129

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