Learning Under Uncertainty: Networks in Emergency Management

39 Pages Posted: 13 Jan 2020

See all articles by Donald P. Moynihan

Donald P. Moynihan

Georgetown University - McCourt School of Public Policy

Date Written: September 01, 2005

Abstract

This paper examines the nature of learning in networks dealing with conditions of high uncertainty. I take Koppenjan and Klijn’s (2004) framework for understanding network uncertainty and apply it to an extreme example of uncertainty, an interorganizational crisis taskforce dealing with an exotic animal disease. The paper identifies the basic difficulties involved in learning under crisis conditions. The taskforce had to learn most of the elements taken for granted in more mature structural forms – the nature of the structural framework in which it was working, how to adapt that framework, the role and actions appropriate for each individual, and how to deal with unanticipated problems. The network pursued this learning in a variety of ways. Most critically, the taskforce used standard operating procedures to provide a form of network memory.

Suggested Citation

Moynihan, Donald P., Learning Under Uncertainty: Networks in Emergency Management (September 01, 2005). Available at SSRN: https://ssrn.com/abstract=3508156 or http://dx.doi.org/10.2139/ssrn.3508156

Donald P. Moynihan (Contact Author)

Georgetown University - McCourt School of Public Policy ( email )

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