Riddalls, C.E. and Bennett, S. (2001) Quantifying Bounded Rationality: Managerial Behaviour and the Smith Predictor. Research Report. ACSE Research Report 784 . Department of Automatic Control and Systems Engineering
Abstract
The concept of bounded rationality in decision making and research on its relegation to aggregate system dynamics is examined. By recasting one such example of a dynamic system, the Beer Game, as a Smith predictor control system is derived. A stability analysis is then employed to support the and qualify the assertion that the level of bounded rationality can adversely affect the aggregate dynamic behaviour of such supply chains. The analytical basis of these calculations enables the qualification of the potential cost improvements resulting from more desirable supply chain dynamics. This approach is designed to inform the strategic investment decision to purchase computational aids in order to overcome the level of bounded rationality in the system.
Metadata
Item Type: | Monograph |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instance |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) > ACSE Research Reports |
Depositing User: | MRS ALISON THERESA BARNETT |
Date Deposited: | 05 Mar 2015 11:54 |
Last Modified: | 25 Oct 2016 05:17 |
Status: | Published |
Publisher: | Department of Automatic Control and Systems Engineering |
Series Name: | ACSE Research Report 784 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:83982 |