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Integrated Community Resilience, A Model Based Systems Engineering Approach
Author(s) -
McDermott Tom,
Nadolski Molly
Publication year - 2016
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2016.00155.x
Subject(s) - metamodeling , executable , sociotechnical system , community resilience , computer science , decision support system , resilience (materials science) , context (archaeology) , social capital , knowledge management , management science , process management , engineering , software engineering , artificial intelligence , sociology , geography , social science , physics , archaeology , redundancy (engineering) , thermodynamics , operating system
This paper presents a model‐based systems engineering framework used to integrate physical, socio‐ecological, and psychological factors of community resilience in urban areas. The research results represent the first year of a multi‐year project. However, both the modeling methodology and our approach to model social factors of community resilience are novel. We first applied a sociotechnical‐modeling framework to capture social factors of community sustainability and resilience in the context of urban infrastructure renewal. Two system constructs, standard of living and subjective well‐being, were linked to environmental, infrastructure, economic, and institutional factors to represent the human capital aspects of community resilience at multiple scales. The framework produced a system metamodel that was used to identify causal relationships between individual micro‐scale indicators of both infrastructure and social program development and the aggregate effects of human capital development. The system metamodel was then used to define an initial data model that will be used to structure an executable metamodel in later phases of research. The executable metamodel will support cross‐disciplinary modeling of the socio‐ecological (objective) and psychological (subjective) factors of community resilience. The long‐term goal is to define a full set of evaluation factors and computer based decision analysis tools that support macro‐scale decision criteria for social, behavioral, and economic decision‐making in complex urban infrastructures.