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Conference Paper: Social network analysis of learning teams during emergency events

TitleSocial network analysis of learning teams during emergency events
Authors
KeywordsAdaptive Behavior
Emergency Management
Learning
Network Structure
Social Network Analysis
Issue Date2012
Citation
Frontiers in Artificial Intelligence and Applications, 2012, v. 238, p. 267-278 How to Cite?
AbstractUnderstanding factors that enhance or diminish learning and adaptability levels of individuals is instrumental in achieving individual and organizational performance goals. In this study, the effect of social network structure on learning attitudes of emergency personnel during an emergency event is investigated. Based on social network theories, and the social influence model of learning, a theoretical framework is proposed to investigate the effects of network structure on learning outcome of bushfire coordinating teams. To test our framework, we investigate social network data which has been extracted from the transcripts of the 2009 Victorian Bushfires Royal Commission report. Empirical results suggest that network structure of emergency personnel play a crucial role in the ability of those actors to engage in learning-related work activity. We infer that this will mean that these actors are better able to adapt and improvise in complex emergency events. We suggest that social network analysis may have a valuable part to play in the study of emergency events. By presenting a model of learning-related work activity, based on network structure, personnel within emergency services organizations can strengthen their capacity to be flexible and adaptable. © 2012 The authors and IOS Press.
Persistent Identifierhttp://hdl.handle.net/10722/194510
ISSN
2023 SCImago Journal Rankings: 0.281
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHamra, J-
dc.contributor.authorHossain, L-
dc.contributor.authorOwen, C-
dc.date.accessioned2014-01-30T03:32:40Z-
dc.date.available2014-01-30T03:32:40Z-
dc.date.issued2012-
dc.identifier.citationFrontiers in Artificial Intelligence and Applications, 2012, v. 238, p. 267-278-
dc.identifier.issn0922-6389-
dc.identifier.urihttp://hdl.handle.net/10722/194510-
dc.description.abstractUnderstanding factors that enhance or diminish learning and adaptability levels of individuals is instrumental in achieving individual and organizational performance goals. In this study, the effect of social network structure on learning attitudes of emergency personnel during an emergency event is investigated. Based on social network theories, and the social influence model of learning, a theoretical framework is proposed to investigate the effects of network structure on learning outcome of bushfire coordinating teams. To test our framework, we investigate social network data which has been extracted from the transcripts of the 2009 Victorian Bushfires Royal Commission report. Empirical results suggest that network structure of emergency personnel play a crucial role in the ability of those actors to engage in learning-related work activity. We infer that this will mean that these actors are better able to adapt and improvise in complex emergency events. We suggest that social network analysis may have a valuable part to play in the study of emergency events. By presenting a model of learning-related work activity, based on network structure, personnel within emergency services organizations can strengthen their capacity to be flexible and adaptable. © 2012 The authors and IOS Press.-
dc.languageeng-
dc.relation.ispartofFrontiers in Artificial Intelligence and Applications-
dc.subjectAdaptive Behavior-
dc.subjectEmergency Management-
dc.subjectLearning-
dc.subjectNetwork Structure-
dc.subjectSocial Network Analysis-
dc.titleSocial network analysis of learning teams during emergency events-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.3233/978-1-61499-073-4-267-
dc.identifier.scopuseid_2-s2.0-84879198578-
dc.identifier.volume238-
dc.identifier.spage267-
dc.identifier.epage278-
dc.identifier.isiWOS:000349033900023-
dc.identifier.issnl0922-6389-

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