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

Giulia Datola, Marta Bottero, Elena De Angelis and Francesco Romagnoli

Ecological Modelling, 2022, vol. 465, issue C

Abstract: 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.

Keywords: Urban resilience; System Dynamics Model; Scenario simulation; Complex systems; Decision-Making support tool (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:465:y:2022:i:c:s0304380021003896

DOI: 10.1016/j.ecolmodel.2021.109851

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