In past posts we have discussed or demonstrated how computational social science (CSS) (i.e. the study of social science through computational methods) and complexity theory can be utilized explore disasters or diseases but this has not really been  formalized.  To this end, Annetta Burger, William Kennedy and myself have a new review paper in Urban Science entitled “Organizing Theories for Disasters into a Complex Adaptive System Framework.” In the paper we review over a century of disaster research and demonstrate the properties and dynamics of complex adaptive systems in such studies and argue how complexity theory is integral to understanding human behavior in disasters by addressing the interactions across systems (i.e., physical, social, and individual systems). We discuss the characteristics of a complex adaptive system (e.g., heterogeneity, webs of connections, relationships and interactions, and adaptations arising from individual actions, decisions, and learning) and how such characteristics can be applied to disaster research and explore implications for future disaster research with an eye on sustainable and resilient cities. If this sounds of interest, and you want to find out more, below we provide the abstract to the paper and a  link to the the paper itself.

Abstract: Increasingly urbanized populations and climate change have shifted the focus of decision1makers from economic growth to the sustainability and resilience of urban infrastructure and communities, especially when communities face multiple hazards and need to recover from recurring disasters. Understanding human behavior and its interactions with built-environments in disasters requires disciplinary crossover to explain its complexity, therefore we apply the lens of complex adaptive systems (CAS) to review disaster studies across disciplines. Disasters can be understood to consist of three interacting systems: 1) the physical system, consisting of geological, ecological, and human-built systems; 2) the social system, consisting of informal and formal human collective behavior; and 3) the individual actor system. Exploration of human behavior in these systems shows that CAS properties of heterogeneity, interacting subsystems, emergence, adaptation, and learning are integral, not just to cities, but to disaster studies and connecting them in the CAS framework provides us with a new lens to study disasters across disciplines. This paper explores the theories and models used in disaster studies, provides a framework to study and explain disasters, and discusses how complex adaptive systems can support theory-building in disaster science for promoting more sustainable and resilient cities.

Keywords: Cities; Complex Adaptive Systems; Computational Social Science, Disasters; Human Behavior.

Framework for Understanding the Intersecting Complex Adaptive Systems of Disaster.

Full Reference:

Burger, A., Kennedy, W.G. and Crooks A.T. (2021), Organizing Theories for Disasters into a Complex Adaptive System Framework, Urban Science, 5(3), 61; https://doi.org/10.3390/urbansci5030061 (pdf)

In past posts we have discussed or demonstrated how computational social science (CSS) (i.e. the study of social science through computational methods) and complexity theory can be utilized explore disasters or diseases but this has not really been  formalized.  To this end, Annetta Burger, William Kennedy and myself have a new review paper in Urban Science entitled “Organizing Theories for Disasters into a Complex Adaptive System Framework.” In the paper we review over a century of disaster research and demonstrate the properties and dynamics of complex adaptive systems in such studies and argue how complexity theory is integral to understanding human behavior in disasters by addressing the interactions across systems (i.e., physical, social, and individual systems). We discuss the characteristics of a complex adaptive system (e.g., heterogeneity, webs of connections, relationships and interactions, and adaptations arising from individual actions, decisions, and learning) and how such characteristics can be applied to disaster research and explore implications for future disaster research with an eye on sustainable and resilient cities. If this sounds of interest, and you want to find out more, below we provide the abstract to the paper and a  link to the the paper itself.

Abstract: Increasingly urbanized populations and climate change have shifted the focus of decision1makers from economic growth to the sustainability and resilience of urban infrastructure and communities, especially when communities face multiple hazards and need to recover from recurring disasters. Understanding human behavior and its interactions with built-environments in disasters requires disciplinary crossover to explain its complexity, therefore we apply the lens of complex adaptive systems (CAS) to review disaster studies across disciplines. Disasters can be understood to consist of three interacting systems: 1) the physical system, consisting of geological, ecological, and human-built systems; 2) the social system, consisting of informal and formal human collective behavior; and 3) the individual actor system. Exploration of human behavior in these systems shows that CAS properties of heterogeneity, interacting subsystems, emergence, adaptation, and learning are integral, not just to cities, but to disaster studies and connecting them in the CAS framework provides us with a new lens to study disasters across disciplines. This paper explores the theories and models used in disaster studies, provides a framework to study and explain disasters, and discusses how complex adaptive systems can support theory-building in disaster science for promoting more sustainable and resilient cities.

Keywords: Cities; Complex Adaptive Systems; Computational Social Science, Disasters; Human Behavior.

Framework for Understanding the Intersecting Complex Adaptive Systems of Disaster.

Full Reference:

Burger, A., Kennedy, W.G. and Crooks A.T. (2021), Organizing Theories for Disasters into a Complex Adaptive System Framework, Urban Science, 5(3), 61; https://doi.org/10.3390/urbansci5030061 (pdf)