Disaster resilience and complex adaptive systems theory

Coetzee, Christo; Niekerk, Dewald van; Raju, Emmanuel

doi:10.1108/dpm-07-2015-0153

Cited by 77 publications

(60 citation statements)

References 57 publications

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“…Manyena (2006) argues that a holistic approach to systems theory can enhance understanding of disaster risk and social vulnerability to help build resilience [31]. Coetzee et al (2016) proposed that through the application of CAS, disaster resilience and its inherent dynamics can be better understood, which can provide effective tools for disaster risk governance and resilience construction in the future [32]. They proposed five CAS concepts that describe the system, which inform the conceptual framework in this paper [32]: (1) Non-linearity: the inputs into the system may have unexpected outputs, and a small input might have a large consequence; (2) Aggregation: in complex systems, individuals organize themselves into their own groups, through similar needs, practices and interests;…”

Section: Complex Adaptive System (Cas) Conceptual Frameworkmentioning

confidence: 99%

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Promoting Disaster Resilience: Operation Mechanisms and Self-Organizing Processes of Crowdsourcing

2020

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It is often difficult to realize effective governance and management within the inherent complexity and uncertainty of disasters. The application of crowdsourcing, through encouraging voluntary support from the general public, advances efficient disaster governance. Twelve international case studies of crowdsourcing and natural disaster governance were collected for in-depth analysis. Influenced by Complex Adaptive System theory, we explored the self-organizing operation mechanisms and self-organization processes of crowdsourcing within disaster governance. The self-organizing operation mechanisms of crowdsourcing are influenced by the multi-directional interaction between the crowdsourcing platform, the initiator (who commences the crowdsourcing process) and the contractor (who undertakes disaster reduction tasks). The benefits of crowdsourcing for governance structure and self-organization processes in natural disaster governance are reflected in three perspectives: strengthening communication and coordination, optimizing emergency decision-making, and improving the ability to learn and adapt. This paper discusses how crowdsourcing can promote disaster resilience from the perspective of the complex adaptive system to enrich the theoretical research on crowdsourcing and disaster resilience.Sustainability 2020, 12, 1862 2 of 14 enhancing community resilience. The research conducted by Baybay and Hindmarsh (2018) in coastal communities in the Philippines shows that community engagement can be increased by improving community activities, knowledge, skills, resources, and by adopting local culture and customs, which are crucial to promoting community resilience [4]. Traditional community engagement refers to offline action processes, while the Internet provides a new form of online community engagement. Crowdsourcing platforms, such as portals, social media, and online applications, have become effective tools for community engagement, by reducing the transaction costs associated with information search, analysis, and decision-making, as well as lowering resource costs (time, money, health, etc.) for civic engagement [5]. Crowdsourcing expands the boundaries of traditional community engagement, which is not limited by time or space, while people from all over the world can participate in specific actions online anytime and anywhere.The issue of how crowdsourcing promotes the self-organization process and builds disaster resilience is understudied. Existing research focuses on how crowdsourcing can be used to collect and analyze disaster data, as well as crowdsourcing's use in communication, loss assessment, and decision support. Research focuses on the functions of crowdsourcing at the technical level, but does not consider the interaction between different subjects in crowdsourcing from the perspective of disaster governance. Taking a tactical emphasis, many studies are based on a single case that focuses on how crowdsourcing can mitigate local problems caused by a specific disaster [6][7][8]. This paper analyses 1...

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Section: Complex Adaptive System (Cas) Conceptual Frameworkmentioning

confidence: 99%

“…The five CAS concepts proposed by Coetzee et al (2016) [32] can be used to explain the self-organizing processes in crowdsourcing.…”

Section: Crowdsourcing Structure and Self-organizing Processesmentioning

confidence: 99%

Promoting Disaster Resilience: Operation Mechanisms and Self-Organizing Processes of Crowdsourcing

2020

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“…Study of disasters reveals development of resilience abilities in populations facing disasters; such behaviours can be explained using applications of emergent system behaviour and Complex Adaptive Systems Theory which seeks to understand emergence within adaptive systems [14]. O'Sullivan et al [43] offer a framework for critical social infrastructure related to health and disaster resilience, which models culture and dynamic networks as impacting formal and informal structures, protocols, information and people-related aspects, which are considered micro-level inputs, and their influence on macro-level outputs such as connectedness and collaboration in relation to dynamic contexts, or states, situational awareness and adaptive response.…”

Section: Disaster Management and The Probabilistic Innovation Paradigmmentioning

confidence: 99%

Disaster management, crowdsourced R&D and probabilistic innovation theory: Toward real time disaster response capability

Callaghan

2016

International Journal of Disaster Risk Reduction

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a b s t r a c tGeneral agreement exists effective disaster management faces constraints related to knowledge sharing and a need for real-time research responses. Extreme case examples of disasters especially vulnerable to these challenges are global pandemics, or disease outbreaks, in which data required for research response are only available after the start of an outbreak. This paper argues the developing field of probabilistic innovation (innovation increasing probability of solving societal problems through radically increasing coordination of volumes of problem-solving inputs and analysis), and its methodologies, such as those drawing from crowdsourced R&D and social media, may offer useful insights into enabling real time research capabilities, with important implications for disaster and crisis management. Three paradigms of disaster research are differentiated, as literature is related to theory offered by post normal science, Kuhnian 'normal science' and Lakatosian 'structural science,' and the goal of achieving real time research problem solving capacity in disaster crisis situations. Global collaborative innovation platforms and large-scale investments in emerging crowdsourced R&D and social media technologies together with synthesis of appropriate theory may contribute to improved real time disaster response and resilience across contexts, particularly in instances where data required to manage response is only available after disasters unfold.

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“…The front line in theory development in the radical emergence paradigm has arguably been found in disaster-management literature, which has highlighted the potential of social media (Alexander 2014) and crowdsourcing (Callaghan 2016b) as well as the importance of complex adaptive systems (Coetzee, Van Niekerk & Raju 2016) and its emergent properties in solving research problems under intense time constraints.…”

Section: Emancipatory Science Contingent On Critical-theory Contributmentioning

confidence: 99%

Critical theory and contemporary paradigm differentiation

Callaghan

2017

Acta Commercii

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Disaster resilience and complex adaptive systems theory

Cited by 77 publications

References 57 publications

Promoting Disaster Resilience: Operation Mechanisms and Self-Organizing Processes of Crowdsourcing

Promoting Disaster Resilience: Operation Mechanisms and Self-Organizing Processes of Crowdsourcing

Disaster management, crowdsourced R&D and probabilistic innovation theory: Toward real time disaster response capability

Critical theory and contemporary paradigm differentiation

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