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Prospect Theory
In the last half of the 20th century, a plethora of papers demonstrated that the expected utility model did not adequately explain the choices of experimental subjects facing risky choices. In a typical study, a subject chooses between a prospect (alternative involving more than one potential outcome) offering a 0.5 chance of gaining $10 and a 0.5 chance of losing $5, and a prospect offering a certain $3. In 1979, Daniel Kahneman and Amos Tversky proposed a general model, termed prospect theory, that captures the main features of the experimental results. Prospect theory predicts individuals’ choices when faced with well-defined prospects that include uncertain outcomes. The theory encompasses the results of a number of experiments in which individuals made such choices. Management papers have used prospect theory to explain a wide variety of managerial and organizational decisions. This entry examines the principles, extensions, and applications of prospect theory. A detailed description of the theory is followed by a section describing the roots of the theory and a later version of it, termed cumulative prospect theory. The entry concludes with a discussion of the application of prospect theory to strategic decision making.
Fundamentals
Prospect theory predicts individual decision making under risk. It originally applied to relatively simple problems with monetary outcomes, stated probabilities, and two prospects. Prospect theory conceptualizes choice using two phases. In the first, “editing” phase, the subject simplifies the prospects or prospects facing the decision maker. Then in the “evaluation” phase, the decision maker chooses between the prospects. As with many theories, we should view this theory as saying people act as if they operate according to these stages, not that they actually calculate in such stages.
The Editing Phase
The simplification of prospects in the editing phase occurs through four major operations: coding, combination, segregation, and cancellation. In coding, the subject subtracts a reference point from the gamble’s potential outcomes, making them into a series of gains or losses with respect to the reference point. The wording of the problem and the decision maker’s expectations can influence the reference point and, consequently, the coding of outcomes as gains or losses. Combination refers to the simplification of prospects by combining the probabilities associated with identical outcomes. Segregation refers to the simplification of prospects by separating out a riskless component from a risky component. While coding, combination, and segregation apply to each prospect separately, the final operation, cancellation, applies to a set of two or more prospects. Cancellation occurs when decision makers ignore components common to the prospects, discard common outcome probability pairs, round up probabilities or outcomes, or discard extremely unlikely or dominated outcomes.
While the editing phase simplifies the choice problem for the decision maker, it can also result in inconsistent preferences. For example, differences in presentation of the problem that do not influence the actual gambles can influence coding. Experiments often do this by changing the reference point without changing the probabilities or potential outcomes.
The Evaluation Phase
The evaluation phase begins with the decision maker implicitly assigning subjective values to the edited prospects (υ(x) and υ(y)), and transforming the prospect’s probabilities (p and q) into decision weights (π(p)). The subject multiplies the values of the prospects by the associated decision weights and sums over then-potential outcomes associated with a given prospect. The subject chooses the prospect with the highest sum (total Value, denoted by V).
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