BazermanMoore

Lawsuit: You are being sued for $500,000 and estimate that you have a 50 percent chance
of losing the case in court (expected value ¼ –$250,000). However, the other side is willing
to accept an out-of-court settlement of $240,000 (expected value ¼ –$240,000). An
expected-value decision rule would lead you to settle out of court. Ignoring attorney’s
fees, court costs, aggravation, and so on, would you (a) fight the case, or (b) settle out of
court?
Most people would choose (a) in both cases, demonstrating that situations exist in
which people do not follow an expected-value decision rule. To explain departures
from the expected-value decision rule, Daniel Bernoulli (1738/1954) first suggested
replacing the criterion of expected monetary value with the criterion of expected utility.
Expected-utility theory suggests that each level of an outcome is associated with an
expected degree of pleasure or net benefit, called utility. The expected utility of an
uncertain choice is the weighted sum of the utilities of the possible outcomes, each
multiplied by its probability. While an expected-value approach to decision making
would treat $1 million as being worth twice as much as $500,000, a gain of $1 million
does not always create twice as much expected utility as a gain of $500,000. Most
individuals do not obtain as much utility from the second $500,000 as they did from
the first $500,000.
The reason for this has to do with the ‘‘declining marginal utility of gains’’: in other
words, the more we get of something, the less pleasure it provides us. For instance,
while winning half a million dollars is nice, and winning an entire million is nicer, winning
$1 million is not twice as nice as winning half a million. Likewise, the second lobster
tail in the two-lobster-tail dinner platter is tasty, but not as tasty as the first. Thus,
in terms of utility, getting $500,000 for sure is worth more to most people than a 50 percent
chance at $1 million.
We can also describe decisions that deviate from expected value according to their
implications about risk preferences. When we prefer a certain $480,000 over a 50 percent
chance of $1 million, we are making a risk-averse choice, since we are giving up
expected value to reduce risk. Similarly, in the Big Positive Gamble problem above,
taking the $10 million is a risk-averse choice, since it has a lower expected value and
lower risk. In contrast, fighting the lawsuit would be a risk-seeking choice, since it has a
lower expected value and a higher risk. Essentially, expected utility refers to the maximization
of utility rather than simply a maximization of the arithmetic average of the
possible courses of action. While expected utility departs from the logic of expected
value, it provides a useful and consistent logical structure—and decision researchers
generally view the logic of expected utility as rational behavior.
Now consider a second version of the Asian Disease Problem (Tversky &
Kahneman, 1981):
Problem 2. Imagine that the United States is preparing for the outbreak of an unusual
Asian disease that is expected to kill 600 people. Two alternative programs to combat the
disease have been proposed. Assume that the scientific estimates of the consequences of
the programs are as follows.
Program C: If Program C is adopted, 400 people will die.
Framing and the Reversal of Preferences 63