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  1. Computational and Mathematical Organization Theory
  2. Computational and Mathematical Organization Theory : Volume 9
  3. Computational and Mathematical Organization Theory : Volume 9, Issue 4, December 2003
  4. Supporting Learning in Evolving Dynamic Environments
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Computational and Mathematical Organization Theory : Volume 23
Computational and Mathematical Organization Theory : Volume 22
Computational and Mathematical Organization Theory : Volume 21
Computational and Mathematical Organization Theory : Volume 20
Computational and Mathematical Organization Theory : Volume 19
Computational and Mathematical Organization Theory : Volume 18
Computational and Mathematical Organization Theory : Volume 17
Computational and Mathematical Organization Theory : Volume 16
Computational and Mathematical Organization Theory : Volume 15
Computational and Mathematical Organization Theory : Volume 14
Computational and Mathematical Organization Theory : Volume 13
Computational and Mathematical Organization Theory : Volume 12
Computational and Mathematical Organization Theory : Volume 11
Computational and Mathematical Organization Theory : Volume 10
Computational and Mathematical Organization Theory : Volume 9
Computational and Mathematical Organization Theory : Volume 9, Issue 4, December 2003
Introduction: Learning in Dynamic, On-Line Environments
Learning in Dynamic Decision Making: The Recognition Process
Supporting Learning in Evolving Dynamic Environments
Learning to Ignore Online Help Requests
Computational and Mathematical Organization Theory : Volume 9, Issue 3, October 2003
Computational and Mathematical Organization Theory : Volume 9, Issue 2, July 2003
Computational and Mathematical Organization Theory : Volume 9, Issue 1, May 2003
Computational and Mathematical Organization Theory : Volume 8
Computational and Mathematical Organization Theory : Volume 7
Computational and Mathematical Organization Theory : Volume 6
Computational and Mathematical Organization Theory : Volume 5
Computational and Mathematical Organization Theory : Volume 4
Computational and Mathematical Organization Theory : Volume 3

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Supporting Learning in Evolving Dynamic Environments

Content Provider SpringerLink
Author Gibson, Faison P.
Copyright Year 2003
Abstract In dynamic decision environments such as direct sales, customer support, and electronically mediated bargaining, decision makers execute sequences of interdependent decisions under time pressure. Past decision support systems have focused on substituting for decision makers' cognitive deficits by relieving them of the need to explicitly account for sequential dependencies. However, these systems themselves are fragile to change and, further, do not enhance decision makers' own adaptive capacities. This study presents an alternative strategy that defines information systems requirements in terms of enhancing decision makers' adaptation. In so doing, the study introduces a simulation model of how decision makers learn patterns of sequential dependency. When a system was used to manage workflows in a way predicted by the model to enhance learning, decision makers in a bargaining experiment learned underlying patterns of sequential dependencythat helped them adapt to new situations. This result is rare if not unique in the study of dynamic decision environments. It indicates that a shift, away from substituting for short-term deficits and toward enhancing pattern learning, can substantially improve the effectiveness of decision support in dynamic environments. Based on the specific findings in this study, this shift has important implications for designing information system workflows and potential future applications in interface design.
Starting Page 305
Ending Page 326
Page Count 22
File Format PDF
ISSN 1381298X
Journal Computational and Mathematical Organization Theory
Volume Number 9
Issue Number 4
e-ISSN 15729346
Language English
Publisher Kluwer Academic Publishers
Publisher Date 2003-01-01
Publisher Place Boston
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Artificial Intelligence (incl. Robotics) Management Operation Research/Decision Theory Methodology of the Social Sciences Sociology
Content Type Text
Resource Type Article
Subject Applied Mathematics Computer Science Decision Sciences Computational Mathematics Modeling and Simulation
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