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Operationalising resilience: A methodological framework for assessing urban resilience through System Dynamics Model.

Authors :
Datola, Giulia
Bottero, Marta
De Angelis, Elena
Romagnoli, Francesco
Source :
Ecological Modelling. Mar2022, Vol. 465, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

• System Dynamics Model (SDM) for urban resilience assessment. • Multi-dimensional and comprehensive evaluation framework. • Literature review of SDM application in urban studies and urban resilience assessment. • Defining and describing urban elements through mathematical formulas. The global ambition of making cities resilient is leading to growing attention towards evaluation frameworks that can assess and communicate the performance of cities in terms of resilience. This perspective requires appropriate approaches and tools which consider complexity, multidimensionality and dynamic behaviour of urban resilience over time. In this context, the System Dynamics Model (SDM) is a suitable tool to analyse and evaluate urban resilience as part of its main characteristics. This paper firstly provides a literature review on the application of SDM in the field of urban resilience assessment in order to underline both the strengths and the weaknesses that characterise the implementations currently available in the literature. Secondly, the article proposes a methodological framework to build a comprehensive multidimensional SDM to assess urban resilience. The final part of the paper provides a specific literature review that collects in a single framework the existing applications of SDM that analyse and model urban resilience issues related to economic, social, environmental and infrastructure dimensions of urban systems. This review is helpful to understand how different urban elements can be characterised and described through mathematical equations. Thus, it provides a basis for a multidimensional SDM to assess urban resilience and identify the mutual interdependences among the considered urban variables. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03043800
Volume :
465
Database :
Academic Search Index
Journal :
Ecological Modelling
Publication Type :
Academic Journal
Accession number :
154892963
Full Text :
https://doi.org/10.1016/j.ecolmodel.2021.109851