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DRU: Designing Resilience for Communities at Risk: Decision Support for Collective Action under Stress

$734,995FY2007SBENSF

University Of Pittsburgh, Pittsburgh PA

Investigators

Abstract

This project addresses the problem of collective action in communities exposed to continuing risk. Mobilizing coordinated action across a diverse community to reduce loss of lives, property, and maintain continuing operations in the face of emerging danger is a task common to all regions of the world. Recent disasters, such as the 2005 hurricanes on the Gulf Coast and the 2004 Sumatran Earthquake and Tsunami, illustrate the difficulty of this task, despite existing disaster plans and policies. The mobilization of collective action is a long-standing problem in organizational theory, involving individual, group, and organizational decision processes that are often in conflict. This research goes beyond the standard organizational approaches to solve the problem of collective action by integrating a technical information infrastructure to extend human problem solving capacity. This research will test a socio-technical model of decision support that enables human managers to address complex challenges under stressful conditions more effectively than organizational strategies alone. The investigators anticipate that the findings will demonstrate more creative and effective human decision making capacity, as technical means of decision support offer more focused, timely, valid information to a broader range of decision makers operating in a region exposed to risk. The project team will test their conceptual framework in a non-Western setting to explore the same processes of human decision making under risk. Findings from this study will inform the global discussion of disaster risk reduction, mitigation, and decision making under uncertainty. These findings will contribute to self organizing processes of risk management for underserved groups as well as communities exposed to continuing risk in western and non-Western cultures. The findings will offer a means of enabling communities to assess, manage, and reduce risk more effectively on a daily basis, while building effective relationships with wider networks of resources and support to counter extreme events. It will build on human capacity for learning and contribute to more effective reduction of risk.

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