SOURCES OF BIAS IN ASSESSMENT PROCEDURES FOR UTILITY FUNCTIONS

Abstract

INTRODUCTION The standard model of choice utilized by decision scientists in analyzing problems is expected utility (EU) theory. This model is presumed to be descriptive of people's basic preferences, while having normative implications for more complex problems. Recently, however, there has been an extensive literature which suggests that even basic choice is more complicated than utility theory suggests. (see for a review). In view of this, this chapter presents a framework for systematically investigating biases stemming from various information processing limitations. We define bias, for this purpose, as a violation of the EU axioms. The experimental data presented in this study, together with a large body of existing evidence, lead us to the conclusion that traditional EU theory may have to be modified if it is to serve as a descriptive and normative model of choice under uncertainty. Our analysis was, in part, motivated by a recent article of Fishburn and Kochenberger who analyzed 30 empirical utility functions published in earlier literature. These plotted utility functions were defined on net present values, returns on investments, or simply net monetary gain or loss. Some studies used business contexts, some personal and others both. Fishburn and Kochenberger (F–K) divided each graph into a below- and above-target segment, and fitted linear, power, and exponential functions separately to each subset of data.