# Multiattribute Utility Theory

Anonymous
timer Asked: Dec 17th, 2017
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Question description

I need help in summarizing the multiattribute utility theory paper in the attachment and the graph. Also to come uup with a new recommended approach.

Utility 1.0 0.5 Attribute level 0 Figure 1 - “Univariate utility-curve” 1 U2 GUF = αU1 + (1-α)U2 GUF = U1 + 0 . U2 Efficient frontier of decision maker 1 Efficient frontier of decision maker 2 U1 Figure 2 - Group-utililty-function characterization U2 GUF = βU1 + (1-β)U2 Efficient frontier of decision maker 2 Efficient frontier of decision maker 1 U1 Figure 3 - Group-utility-function characterization with proxy decision-maker efficient-frontier political states overall space capability National economy Mission cuticality Environment space/ground ratio Mission impact Maturity of mission Economic commitment Economic impact Launch priority Mission performance status Contribution to mission Level of Technology Expected remaining lifetime Satellite Utililty cost/domestic commitment Satellite Status Figure 4 - Model Criteria Figure 5 - Strategic equivalence 1.0 U A= U M= cost/domestic commitment 0.8 U 0 .7 U 0.7 A= 0.6 0.6 M= 0.6 U U A= M= 0.4 0.5 U U M= A= 0. 4 M= 0.4 U 0.2 0.5 .3 =0 UA 0.3 0 0.2 0.4 Satellite Status 0.6 0.8 1.0 Legend UA : Additive form UM : Multiplicative form

Fridah G
School: UIUC

Attached.

Last name 1
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Multiattribute Utility Theory
Staats and Chan make use of the multi-attribute utility theory (MAUT) in order to define
a mathematical illustration of a decision maker’s utility. The authors were concerned with
whether or not it is possible to substantially simplify the survey process of MAUT. This is
because survey instruments are usually so complex such that the decision makers get confused to
the level that their responses become inconsistent. As a result, such decision makers often tend to
leave the process with minute confidence in its validity. The authors make the survey simpler to
administer through elimination of the need to use lottery questions. Staats and Chan simplify the
survey instrument in three major ways that are centered primarily on eliminating the prerequisite
to use lottery questions in order to capture the preference structure of the decision makers.
The first simplification involves the use of Kirkwood's postulation of exponential
univariate function curves. This eliminates the need to use the fractile method that has been
under criticisms for its failure to provide consistent results (de Neufville, 1990). The authors then
reduce the quantity of pairwise comparisons that are needed so as to verify the utility
individuality through taking advantage of the "weak conditions” of Keeney and Raiffa.
According to Kee...

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Anonymous
Awesome! Exactly what I wanted.

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