Natural Hazards

, Volume 39, Issue 2, pp 309–327 | Cite as

Inter-organizational coordination in extreme events: The World Trade Center attacks, September 11, 2001

  • Louise K. ComfortEmail author
  • Naim Kapucu
Research Article


This paper addresses the problem of inter-organizational coordination in response to extreme events. Extreme events require coordinated action among multiple actors across many jurisdictions under conditions of urgent stress, heavy demand and tight time constraints. The problem is socio-technical in that the capacity for inter-organizational coordination depends upon the technical structure and performance of the information systems that support decision making among the participating organizations. Interactions among human managers, computers and organizations under suddenly altered conditions of operation are complex and not well understood. Yet, coordinating response operations to extreme events is an extraordinarily complex task for public and nonprofit managers. This paper will analyze the interactions among public, private and nonprofit organizations that evolved in response to the 11 September 2001 attacks, examining the relationships among organizations in terms of timely access to information and types of supporting infrastructure.

The performance of the inter-organizational system is examined in the context of the events of 11 September 2001 from the theoretical perspective of complex adaptive systems. A model of auto-adaptation is proposed for implementation to improve inter- organizational performance in extreme events. This model is based on the concept of individual, organizational and collective learning in environments exposed to recurring risk, guided by a shared goal. Such a model requires public investment in the development of an information infrastructure that can support the intense demand for communication, information search, exchange and feedback that characterizes an auto-adaptive system.


Auto-adaptation Sensemaking Extreme events Emergency response Organizational learning Complex adaptive systems 


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Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  1. 1.Graduate School of Public and International AffairsUniversity of PittsburgUSA
  2. 2.Department of Public Administration, College of Health and Public AffairsUniversity of Central FloridaUSA

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