What Determines the Shape of the Probability Weighting Function Under Uncertainty?

Decision weights are an important component in recent theories of decision making under uncertainty. To better explain these decision weights, a two-stage approach has been proposed: First, the probability of an event is judged and then this probability is transformed by the probability weighting function known from decision making under risk. We extend the two-stage approach by allowing the probability weighting function to depend on the type of uncertainty. Using this more general approach, properties of decision weights can be attributed to properties of probability judgments and/or to properties of probability weighting. We present an empirical study that shows that it is indeed necessary to allow the probability weighting function to be source dependent. The analysis includes an examination of properties of the probability weighting function under uncertainty that have not been considered yet.

• 저널Management Science · 47(12) · 1712–1726
• 토픽Decision-Making and Behavioral Economics · General Decision Sciences
• DOI10.1287/mnsc.47.12.1712.10239
• 저자Michael Kilka, Martin Weber