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Learning under Uncertainty

Networks in Crisis Management

Bibliographic Data

ID6361937
AuthorsDonald P Moynihan (0000-0003-4097-6908, corresponding author)
Year2008
Volume68
Issue2
Pages350-365
Publication date2008-02-08
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenuePublic Administration Review (JOURNAL)
Journal identifiersISSN: 0033-3352 • E-ISSN: 1540-6210
PublisherWiley (PUBLISHER • GB)
DOI10.1111/j.1540-6210.2007.00867.x
OpenAlexW2165416955
LanguageEN
Citations received112
References cited41

This article examines learning in networks dealing with conditions of high uncertainty. The author examines the case of a crisis response network dealing with an exotic animal disease outbreak. The article identifies the basic difficulties of learning under crisis conditions. The network 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, including virtual learning, learning forums, learning from the past, using information systems and learning from other network members. Most critically, the network used standard operating procedures to provide a form of network memory and a command and control structure to reduce the institutional and strategic uncertainty inherent in networks

Business · Control (management · Crisis management · Economics · Knowledge management · Learning network · Machine learning · Management · Management science · Network structure · Risk analysis (engineering · Variety (cybernetics · Artificial Intelligence · Complex Systems and Decision Making · Computer Science · Disaster Management and Resilience · Public Relations and Crisis Communication

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Unique citing works112
Citations per year5,33
Citation span2005 - 2026 (22)
Citation velocitycurrent
Highly citedYes
Citation typesNeutral: 112
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