Original Research

A system dynamics approach for understanding community resilience to disaster risk

Onyekachi J. Onyeagoziri, Corrinne Shaw, Tom Ryan
Jàmbá: Journal of Disaster Risk Studies | Vol 13, No 1 | a1037 | DOI: https://doi.org/10.4102/jamba.v13i1.1037 | © 2021 Onyekachi J. Onyeagoziri, Corrinne Shaw, Tom Ryan | This work is licensed under CC Attribution 4.0
Submitted: 01 August 2020 | Published: 14 June 2021

About the author(s)

Onyekachi J. Onyeagoziri, Department of Mechanical Engineering, Faculty of Engineering and the Built Environment, University of Cape Town, Cape Town, South Africa
Corrinne Shaw, Department of Mechanical Engineering, Faculty of Engineering and the Built Environment, University of Cape Town, Cape Town, South Africa
Tom Ryan, Graduate School of Business, University of Cape Town, Cape Town, South Africa

Abstract

The Western Cape is a dynamic province that is disaster-prone, particularly the vulnerable urban communities in and around its environs. Such communities are more vulnerable to wildfire, flooding, pandemic, natural and human-made hazards because of poverty and, consequently, poor living conditions such as overcrowding and non-understanding of community resilience. The inability of these communities to understand community resilience and withstand adversities affects the sustainability of initiatives to develop them. This study aims to identify the mechanisms influencing the level of understanding of community resilience in a vulnerable community and to contribute to the understanding of community resilience to disaster risk. Fieldwork was conducted in an informal settlement in South Africa. The research study was conducted in two cycles of data collection and analysis. Data in the form of observation notes, document analysis and interviews were analysed using grounded-theory principles. Ten inter-related variables or mechanisms emerged from the analysis. The theoretical model consists of four reinforcing (R) feedback loops (R1, R2, R3 and R4), respectively, which explain how the understanding of community resilience in the informal settlement maps on to the relative achievement systems archetype. Negative reinforcing behaviour would explain the lack of understanding of community resilience, while positive reinforcing behaviour indicates how an understanding of community resilience develops. In addition, the variable with the leverage to improve the mechanisms influencing the understanding of community resilience was found to be the ‘level of public education and awareness’. The theory of how these variables behave in context was represented as a qualitative system dynamics model.

Keywords

disaster risk reduction; community resilience; grounded theory; system dynamics; informal settlements.

Metrics

Total abstract views: 4946
Total article views: 11787

 

Crossref Citations

1. Continuing from the Sendai Framework midterm: Opportunities for urban digital twins in disaster risk management
Edgardo Macatulad, Filip Biljecki
International Journal of Disaster Risk Reduction  vol: 102  first page: 104310  year: 2024  
doi: 10.1016/j.ijdrr.2024.104310

2. Participatory resilience: Surviving, recovering and improving together
Sachit Mahajan, Carina I. Hausladen, Javier Argota Sánchez-Vaquerizo, Marcin Korecki, Dirk Helbing
Sustainable Cities and Society  vol: 83  first page: 103942  year: 2022  
doi: 10.1016/j.scs.2022.103942

3. Building Urban Community Resilience against Hazards through Public-Private Partnerships: A Review of Critical Resilience Strategies
Robert Osei-Kyei, Godslove Ampratwum, Vivian W. Y. Tam, Ursa Komac, Timur Narbaev
Buildings  vol: 14  issue: 7  first page: 1947  year: 2024  
doi: 10.3390/buildings14071947

4. Impacts of resilience on food security in rural households of Iran under drought conditions using an extended sustainable livelihood framework
Mahsa Rajab-Kalantarzadeh, Moslem Savari
Results in Engineering  vol: 26  first page: 105145  year: 2025  
doi: 10.1016/j.rineng.2025.105145

5. Exploring the landscape of system dynamics archetypes: A systematic review
Marisa A. Sánchez
Systems Research and Behavioral Science  vol: 42  issue: 6  first page: 1618  year: 2025  
doi: 10.1002/sres.3066