Utility Theory For Decision Making

Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory. Features Covers approaches for making decisions under certainty, risk, and uncertainty Illustrates expected utility theory and its extensions Describes approaches to elicit the utility function Reviews classical and Bayesian approaches to statistical inference based on decision theory Discusses the role of causal analysis in statistical decision theory

In this valuable book, Paul Schoemaker summarizes recent experimental and field research that he and others have undertaken regarding the descrip tive validity of expected utility theory as a model of choice under uncer tainty. His principal message is that this paradigm is too narrow in its con ception and misses some of the important elements of a descriptive model of individual choice. In particular, Schoemaker calls attention to the impor tance of individual differences, task effects, and context effects as they influence behavior. The expected utility hypothesis has come under scrutiny in recent years from a number of different quarters. This book brings together these many studies and relates them to the large body of literature on individual de cision making under risk. Although this paradigm may be appropriate for describing behavior under many conditions of uncertainty, Schoemaker presents convincing evidence that it does not do well with respect to protec tion against low-probability events. For example, he shows that the insur ance purchase decision is influenced by the way information is presented to the client, as well as by the statistical knowledge of the respondents.

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.

One of the most important tasks faced by decision-makers in business and government is that of selection. Selection problems are challenging in that they require the balancing of multiple, often conflicting, criteria. In recent years, a number of interesting decision aids have become available to assist in such decisions. The aim of this book is to provide a comparative survey of many of the decision aids currently available. The first chapters present general ideas which underpin the methodologies used to design these aids. Subsequent chapters then focus on specific decision aids and demonstrate some of the software which implement these ideas. A final chapter provides a comparative analysis of their strengths and weaknesses.

This book is the second edition of Behavioral Decision Theory, published in 2014. The main approach and structure of this book have been retained in the new edition. However, this second edition provides a fresh overview of the idea of behavioral decision theory and related research findings such as theoretical and empirical discoveries of preference formation, time discounting, social interaction, and social decision making. The book covers a wide range from classical to relatively recent major studies concerning behavioral decision theory, which, in brief, is a general term for descriptive theories to explain the psychological knowledge related to people’s decision-making behavior. It is called a theory but is actually a combination of various psychological theories, for which no axiomatic systems—such as those associated with the utility theory widely used in economics—have been established. The utility theory is often limited to qualitative knowledge; however, as the studies of Nobel laureates H. A. Simon, D. Kahneman, and R. Thaler have suggested, the psychological methodology and knowledge of behavioral decision theory have been applied widely in such fields as economics, business administration, and engineering and are expected to become even more useful in the future. Research into people’s decision making represents an important part in those fields, various aspects of which overlap with the scope of behavioral decision theory. This theory is closely related to behavioral economics and behavioral finance, which have come into greater use in recent years. This book will appeal especially to graduate students, advanced undergraduate students, and researchers who are interested in decision-making phenomena.

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.

Human decision making involves problems which are being studied with increasing interest and sophistication. They range from controversial political decisions via individual consumer decisions to such simple tasks as signal discriminations. Although it would seem that decisions have to do with choices among available actions of any kind, there is general agreement that decision making research should pertain to choice prob lems which cannot be solved without a predecisional stage of finding choice alternatives, weighing evidence, and judging values. The ultimate objective of scientific research on decision making is two-fold: (a) to develop a theoretically sound technology for the optimal solution of decision problems, and (b) to formulate a descriptive theory of human decision making. The latter may, in tum, protect decision makers from being caught in the traps of their own limitations and biases. Recently, in decision making research the strong emphasis on well defined laboratory tasks is decreasing in favour of more realistic studies in various practical settings. This may well have been caused by a growing awareness of the fact that decision-behaviour is strongly determined by situational factors, which makes it necessary to look into processes of interaction between the decision maker and the relevant task environ ment. Almost inevitably there is a parallel shift of interest towards problems of utility measurement and the evaluation of consequences.