[Sample B: Approval/Signature Sheet] - George Mason University
[Sample B: Approval/Signature Sheet] - George Mason University
[Sample B: Approval/Signature Sheet] - George Mason University
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Still using the attribute A3.3 Range as an example, it was clear that the DM‘s<br />
preferences increase in x, meaning that more range is better, thus the following points in<br />
the utility function could be derived:<br />
u (x0) = u (300) = 0<br />
u (x.25) = u(900) = 0.25<br />
u (x.5) = u(1800) = 0.5<br />
u (x.75) = u(2700) = 0.75<br />
u (x1) = u(4000) = 1<br />
A consistency check was performed by assessing the CE for (x.25, x.75). The result<br />
should be equal to u (x.5) = u (1800) = 0.5. In this example the DM was indifferent<br />
between the lottery and x.5, thus consistent with his preferences.<br />
The assessment procedure yielded a risk averse utility function, meaning that the<br />
CEs are less than the expected consequences of their respective lotteries, which means<br />
that the DM always prefers the expected consequences to run the risks involved with a<br />
lottery.<br />
Since the overall assessment involved the definition of five points, and no serious<br />
inconsistencies were identified in the DM‘s preferences, a three points curve was used to<br />
define the utility function -- the least preferred level of the sub-range, the most preferred<br />
level of the sub-range and the mid-preference level of the sub range (see fig. 28).<br />
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