Learning Under Uncertainty: Networks in Crisis Management

La Follette School Working Paper No. 2005-028,

34 Pages Posted: 13 Dec 2005

See all articles by Donald P. Moynihan

Donald P. Moynihan

Georgetown University - McCourt School of Public Policy

Date Written: December 2005

Abstract

This paper examines the nature of learning in networks dealing with conditions of high uncertainty. I apply Koppenjan and Klijn's (2004) framework for understanding network uncertainty to an extreme example: an inter-organizational 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, and a command and control structure to reduce institutional and strategic uncertainty.

Keywords: crisis, emergency, learning, ambiguity, uncertainty

JEL Classification: d81, h11, h70, l22

Suggested Citation

Moynihan, Donald P., Learning Under Uncertainty: Networks in Crisis Management (December 2005). La Follette School Working Paper No. 2005-028, , Available at SSRN: https://ssrn.com/abstract=868712 or http://dx.doi.org/10.2139/ssrn.868712

Donald P. Moynihan (Contact Author)

Georgetown University - McCourt School of Public Policy ( email )

Old North, Suite 100
37th & O Streets NW
Washington, DC 20057
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
93
Abstract Views
668
PlumX Metrics