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Article: Collective Dynamics of Hierarchical Networks

TitleCollective Dynamics of Hierarchical Networks
Authors
KeywordsDisaster response
Collective shared space
Hierarchical networks
Issue Date2015
PublisherCornell University Library.
Citation
arXiv:1503.08264 [cs.CY] How to Cite?
AbstractIn an increasingly complex, mobile and interconnected world, we face growing threats of disasters, whether by chance or deliberately. Disruption of coordinated response and recovery efforts due to organizational, technical, procedural, random or deliberate attack could result in the risk of massive loss of life. This requires urgent action to explore the development of optimal information-sharing environments for promoting collective disaster response and preparedness using multijurisdictional hierarchical networks. Innovative approaches to information flow modeling and analysis for dealing with challenges of coordinating across multi layered agency structures as well as development of early warnings through social systems using social media analytics may be pivotal to timely 2 responses to dealing with large scale disasters where response strategies need to be viewed as a shared responsibility. How do facilitate the development of collective disaster response in a multijurisdictional setting? How do we develop and test the level and effectiveness of shared multijurisdictional hierarchical networks for improved preparedness and response? What is the role of multi layered training and exercises in building the shared learning space for collective disaster preparedness and response? The aim of this is therefore to determine factors that may be responsible for affecting disaster response. It is shown here that changes to the interconnectedness of nodes in the network may have implications on the potential to preparedness and response. In this study, theory behind social network analysis is applied to a large-scale inter-organisational Disaster Response Network (DRN) for exploring correlation between network interconnectedness and response. We discover that the leadership and involvement displayed by organisations in multijurisdictional emergency response is not equal, and hypothesise the existence of a loose tiered structure that guides how interconnected an organisation should be. A model is presented as a theoretical means to confront the issues of disaster response. To test our hypotheses, we investigate survey data from state law enforcement, state emergency services and local law enforcement by performing agency-based (macro) and cross-agency (micro) analysis to identify attributes of each network and response. Results suggest that there is a positive correlation between network connectedness and potential to effective response as well as the concept of tiers within DRN may exist which can be characterized by the sub-network that an organisation associates with.
Persistent Identifierhttp://hdl.handle.net/10722/210828

 

DC FieldValueLanguage
dc.contributor.authorHossain, L-
dc.contributor.authorWigand, T-
dc.date.accessioned2015-06-23T05:56:01Z-
dc.date.available2015-06-23T05:56:01Z-
dc.date.issued2015-
dc.identifier.citationarXiv:1503.08264 [cs.CY]-
dc.identifier.urihttp://hdl.handle.net/10722/210828-
dc.description.abstractIn an increasingly complex, mobile and interconnected world, we face growing threats of disasters, whether by chance or deliberately. Disruption of coordinated response and recovery efforts due to organizational, technical, procedural, random or deliberate attack could result in the risk of massive loss of life. This requires urgent action to explore the development of optimal information-sharing environments for promoting collective disaster response and preparedness using multijurisdictional hierarchical networks. Innovative approaches to information flow modeling and analysis for dealing with challenges of coordinating across multi layered agency structures as well as development of early warnings through social systems using social media analytics may be pivotal to timely 2 responses to dealing with large scale disasters where response strategies need to be viewed as a shared responsibility. How do facilitate the development of collective disaster response in a multijurisdictional setting? How do we develop and test the level and effectiveness of shared multijurisdictional hierarchical networks for improved preparedness and response? What is the role of multi layered training and exercises in building the shared learning space for collective disaster preparedness and response? The aim of this is therefore to determine factors that may be responsible for affecting disaster response. It is shown here that changes to the interconnectedness of nodes in the network may have implications on the potential to preparedness and response. In this study, theory behind social network analysis is applied to a large-scale inter-organisational Disaster Response Network (DRN) for exploring correlation between network interconnectedness and response. We discover that the leadership and involvement displayed by organisations in multijurisdictional emergency response is not equal, and hypothesise the existence of a loose tiered structure that guides how interconnected an organisation should be. A model is presented as a theoretical means to confront the issues of disaster response. To test our hypotheses, we investigate survey data from state law enforcement, state emergency services and local law enforcement by performing agency-based (macro) and cross-agency (micro) analysis to identify attributes of each network and response. Results suggest that there is a positive correlation between network connectedness and potential to effective response as well as the concept of tiers within DRN may exist which can be characterized by the sub-network that an organisation associates with.-
dc.languageeng-
dc.publisherCornell University Library.-
dc.relation.ispartofarXiv-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectDisaster response-
dc.subjectCollective shared space-
dc.subjectHierarchical networks-
dc.titleCollective Dynamics of Hierarchical Networks-
dc.typeArticle-
dc.identifier.emailHossain, L: lhossain@hku.hk-
dc.identifier.authorityHossain, L=rp01858-
dc.description.naturepreprint-
dc.identifier.hkuros243373-
dc.publisher.placeNew York-

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