Utility Theories Measurements And Applications

The Conference on "Utility: Theories, Measurements, and Applications" met at the Inn at Pasatiempo in Santa Cruz, California, from June II to 15, 1989. The all-star cast of attendees are listed as authors in the Table of Contents of this book (see p. V), except for Soo Hong Chew and Amos Tversky. The purpose of the conference, and of National Science Foundation Grant No. SES-8823012 that supported it, was to confront proponents of new generalized theories of utility with leading decision analysts com mitted to the implementation, in practice, of the more traditional theory that these new theories reject. That traditional model is variously iden tified in this book as expected utility or subjectively expected utility maximization (EU or SEU for short) and variously attributed to von Neumann and Morgenstern or Savage. I had feared that the conference might consist of an acrimonious debate between Olympian normative theorists uninterested in what people actually do and behavioral modelers obsessed with the cognitive illusions and uninterested in helping people to make wise decisions. I was entirely wrong. The conferees, in two dramatic straw votes at the open ing session, unanimously endorsed traditional SEU as the appropriate normative model and unanimously agreed that people don't act as that model requires. (These votes had a profound impact on my thinking; detail about them and about that impact is located in Chapter 10.

In this volume we present some o~ the papers that were delivered at FUR-82 - the First International Con~erence on Foundations o~ Utility and Risk Theory in Oslo, June 1982. The purpose o~ the con~erence was to provide a ~orum within which scientists could report on interesting applications o~ modern decision theory and exchange ideas about controversial issues in the ~oundations o~ the theory o~ choice under un certainty. With that purpose in mind we have selected a mixture of applied and theoretical papers that we hope will appeal to a wide spectrum o~ readers ~rom graduate students in social science departments and business schools to people involved in making hardheaded decisions in business and government. In an introductory article Ole Hagen gives an overview o~ various paradoxes in utility and risk theory and discusses these in the light o~ scientific methodology. He concludes the article by calling ~or joint efforts to provide decision makers with warkable theories. Kenneth Arrow takes up the same issue on a broad basis in his paper where he discusses the implications o~ behavior under uncertainty for policy. In the theoretical papers the reader will ~ind attempts at de~initive Statements of the meaning o~ old concepts and suggestions for the adoption o~ new concepts. For instance, Maurice Allais discusses four di~ferent interpretations o~ the axioms o~ probability and explains the need ~or an empirical characterization o~ the concept of chance.

Decision Science and Technology is a compilation of chapters written in honor of a remarkable man, Ward Edwards. Among Ward's many contributions are two significant accomplishments, either of which would have been enough for a very distinguished career. First, Ward is the founder of behavioral decision theory. This interdisciplinary discipline addresses the question of how people actually confront decisions, as opposed to the question of how they should make decisions. Second, Ward laid the groundwork for sound normative systems by noticing which tasks humans can do well and which tasks computers should perform. This volume, organized into five parts, reflects those accomplishments and more. The book is divided into four sections: `Behavioral Decision Theory' examines theoretical descriptions and empirical findings about human decision making. `Decision Analysis' examines topics in decision analysis.`Decision in Society' explores issues in societal decision making. The final section, `Historical Notes', provides some historical perspectives on the development of the decision theory. Within these sections, major, multi-disciplinary scholars in decision theory have written chapters exploring some very bold themes in the field, as an examination of the book's contents will show. The main reason for the health of the Decision Analysis field is its close links between theory and applications that have characterized it over the years. In this volume, the chapters by Barron and Barrett; Fishburn; Fryback; Keeney; Moreno, Pericchi, and Kadane; Howard; Phillips; Slovic and Gregory; Winkler; and, above all, von Winterfeldt focus on those links. Decision science originally developed out of concern with real decision problems; and applied work, such as is represented in this volume, will help the field to remain strong.

This new monograph presents Dr. Luce's current understanding of the behavioral properties people exhibit (or should exhibit) when they make selections among alternatives and how these properties lead to numerical representations of those preferences. It summarizes, and places in historical perspective, the research Dr. Luce has done on utility theory for over 10 years. Included are axiomatic theoretical formulations, experiments designed to test individual assumptions, and analyses of the fit to bodies of data of numerical representations derived from the theory.

The first attempts to develop a utility theory for choice situations under risk were undertaken by Cramer (1728) and Bernoulli (1738). Considering the famous St. Petersburg Paradox! - a lottery with an infinite expected monetary value -Bernoulli (1738, p. 209) observed that most people would not spend a significant amount of money to engage in that gamble. To account for this observation, Bernoulli (1738, pp. 199-201) proposed that the expected monetary value has to be replaced by the expected utility ("moral expectation") as the relevant criterion for decision making under risk. However, Bernoulli's 2 argument and particularly his choice of a logarithmic utility function seem to be rather arbitrary since they are based entirely on intuitively 3 appealing examples. Not until two centuries later, did von Neumann and Morgenstern (1947) prove that if the preferences of the decision maker satisfy cer tain assumptions they can be represented by the expected value of a real-valued utility function defined on the set of consequences. Despite the identical mathematical form of expected utility, the theory of von Neumann and Morgenstern and Bernoulli's approach have, however, IFor comprehensive discussions of this paradox cf. Menger (1934), Samuelson (1960), (1977), Shapley (1977a), Aumann (1977), Jorland (1987), and Zabell (1987). 2Cramer (1728, p. 212), on the other hand, proposed that the utility of an amount of money is given by the square root of this amount.