BISoN: Biologically-Inspired Social Network Framework for Coordinated and Adaptive Emergency Response

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Summary

Emergency preparedness and response coordination is a multi-organisational effort, where shared goals – warning, evacuation and recovery – are heavily interdependent. When an extreme event occurs, professionals from multiple organisations must respond to it by coordinating their respective knowledge, skills, and abilities to overcome problems generated by the crisis. This is a major challenge. A number of high-profile studies illustrate that coordination is often insufficient among responding government agencies, volunteers, businesses and humanitarian organisations Effective coordination of the emergency response effort depends strongly on the transfer, use, and quality of shared information about risks, vulnerabilities, and hazards among coordinating agencies. The traditional approaches to coordination were to delegate more authority to a single actor. The idea was to secure coordination by control from the top – a ‘coordination by command’ approach (Donini and Niland, 1994). This notion has been contentious mainly due to the difficulties of selecting a suitable governing body. Contemporary thinkers contend that it may be timely to consider whether an organisation should be reconceived as constituting a social network (Moore, Eng et al., 2003; Stephenson-Jr., 2004). A leading researcher in this field has argued that “coordination is multilayered, involving the orchestration of relationships not only at headquarters but also at the regional, national and field levels” (Minear, 2002). Hierarchical models of resource allocation and coordination emphasise the power and dependencies, which develop during inter-organisational transactions. Research within resource dependency has also argued that there is a positive association between organisations’ network centrality and their supposed influence in community affairs (Galaskiewicz, 1985).

Supervisor(s)

Professor Liaquat Hossain

Research Location

Civil Engineering

Program Type

Masters/PHD

Synopsis

It is no surprise that significant failures during recent high-profile crises have arisen from rapidly changing circumstances on the ground, and from the challenges of managing a dynamic situation across different response agencies that have distinct modes of operation. At the fundamental level, crisis response can be visualised as an interaction network with a flow of information between nodes, each representing an individual actor or agency. Observations of interaction networks in life, engineering, and the physical sciences suggest that the key functional properties of these networks are the flow of information they can support, the robustness of the flow to node failure, and the efficiency of the network (defined in terms of the time for information to pass between two points). Studies have shown that certain network designs perform better than others in each of these respects. This points to the premise that loosely knit collections of individuals constituting ad-hoc social networks have neither an overarching executive nor a hierarchical command and control structure tying them together. Rather, the connections among decision-makers at the different organisations form a network where all nodes have substantial autonomy with respect to their own social networks, telecommunications networks, resources, and decision-making. The Partner Organisation, the NSW State Emergency Service (SES) wants to join with the University of Sydney to create more effective, efficient and robust information network systems for decision-making during crisis events, and for post-crisis analysis. Our aim is to quantify existing structures and extending the analytical approaches to social network theory using structures inspired by biological networks.

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Keywords

response coordination, emergency preparedness, effective coordination of the emergency response, quantify existing structures, analytical approaches, social network theory, biological networks

Opportunity ID

The opportunity ID for this research opportunity is: 1352

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