Social network analysis of learning teams during emergency events
Hamra, J and Hossain, L and Owen, C, Social network analysis of learning teams during emergency events, Frontiers in Artificial Intelligence and Applications, 28-30 June 2012, Anavissos,Greece, pp. 267-278. ISSN 0922-6389 (2012) [Refereed Conference Paper]
Understanding 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.
Refereed Conference Paper
adaptive behavior, emergency management, learning; network structure, social network analysis, artificial intelligence, decision support systems, economic and social effects, emergency services, risk management, social networking (online), learning