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Multi-attribute utility theory to assist top-level acquisition making

Authors: Goren, Ran;

Multi-attribute utility theory to assist top-level acquisition making

Abstract

Top-level acquisition decisions are complex and multi-objective. This implies difficulties in appropriately accounting for all relevant factors to select the best alternative. In addition, there are difficulties and deficiencies in the actual implementation of the decision process. The difficulties and deficiencies in the top-level acquisition decision-making are explored by this thesis. The thesis suggests improvements through intensive use of a quantitative, judgment-based decision technique derived from Multi-Attribute Utility Theory (MAUT). Emphasis is put on demonstrating MAUT's capability for incorporating subjective judgment, in order to reduce the existing doubts about its usefulness for top-level decision-making. The thesis recommends use of the MAUT procedure as the central tool for comprehensive evaluation of the decision alternatives. It argues that such use would solve some of the essential decision-making problems and in addition contribute to the quality and efficiency of the decision process.

Approved for public release; distribution is unlimited.

http://archive.org/details/multiattributeut1094520612

Colonel, Israeli Air Force

Keywords

Major-systems evaluation, DSARC, Acquisition decision-making, Multi-attribute utility theory (MAUT), Management

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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