Identifying traces of resilient performance in incident management systems using episodes

Changwon Son, Jukrin Moon, Farzan Sasangohar, S. Camille Peres

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In order to cope with increasing complexity of catastrophic disasters, resilience is considered an essential capability of an incident management system (IMS). As resilience is manifested during systems operation, a naturalistic observational study was conducted to understand how resilient performance dynamically takes place in this domain. The study results were presented using the concept of episodes, each of which uncovers a trace of such resilient performance following an information input called an inject. The episode analysis also facilitated the identification of complex and dynamic interactions among human and technological agents to satisfy work demands, representing work-as-done (WAD) in large-scale emergency response operations.

Original languageEnglish (US)
Title of host publicationConference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2018
EditorsBrian Tomaszewski, Kees Boersma
PublisherInformation Systems for Crisis Response and Management, ISCRAM
Pages935-941
Number of pages7
ISBN (Electronic)9780692127605
StatePublished - 2018
Event15th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2018 - Rochester, United States
Duration: May 20 2018May 23 2018

Publication series

NameProceedings of the International ISCRAM Conference
Volume2018-May
ISSN (Electronic)2411-3387

Other

Other15th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2018
Country/TerritoryUnited States
CityRochester
Period5/20/185/23/18

Keywords

  • Cognitive Systems Engineering
  • Episode Analysis
  • Incident Management
  • Resilience Engineering

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Electrical and Electronic Engineering

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