facing outcomes involving chance; nonetheless, “this does not mean we cannot continue to learn by studying and modeling them separately” (pp. 149-150). And as we learn, developing newer and more accurate models, it is important that we have a good sense of when extant models can be appropriately applied. This paper discusses an experiment intended to determine whether there are circumstances in which the use of the standard expected utility model need not imply a tradeoff of descriptive validity for facility. Specifically, the experiment examines shared decision-making as a potential situation better suited for the expected utility framework. Choices between prospects with uncertain outcomes do not always confront individuals alone. Frequently, such decisions fall on organizations of people, like households choosing between health insurance plans. Sometimes people have organized for the very purpose of collectively making such decisions, like investment companies. Consequently, the modeling of preferences over probabilistic outcomes should look beyond individual behavior to consider shared preferences, which could be free of the cognitive biases shown to obfuscate expected utility maximization in individuals. That is, a pair of individuals making probabilistic decisions as though they were a single agent may behave more like an expected utility maximizer than an actual single agent. Since most multi-agent frameworks focus on games, it is important to ascertain the relative descriptiveness of standard expected utility as it applies to collaborative groups. For this reason, the simple experiment discussed here compares two-person collaborative pairs and solo individuals in terms of revealed consistency with the expected utility hypothesis. The measurement of comparison is a famous test of expected utility
Markowitz, Harry. 1954. “The Utility of Wealth,” The Journal of Political Economy, April 60(2): pp. 151-158. Marschak, Jacob. 1950. “Rational Behavior, Uncertain Prospects, and Measurable Utility,” Econometrica, April 18(2): pp. 111-141. Morrison, Donald. 1967. “On the Consistency of Preferences in Allais’ Paradox,” Behavioral Sciences, September 12(5), pp. 373-383. Moskowitz, Herbert. 1974. “Effects of Problem Representation and Feedback on Rational Behavior in Allais and Morlat-type Problems,” Decision Sciences, April 5(2): pp. 225-252. Raiffa, Howard. 1968. Decision Analysis: Introductory Lectures on Choices under Uncertainty. Reading, MA: Addison-Wesley. Savage, Leonard. 1954. The Foundation of Statistics. Mineola, NY: Dover. Slovic, Paul and Amos Tversky. 1974. “Who Accepts Savage’s Axiom?,” Behavioral Science, November 19(6): pp. 368-373. Tuthill, Jonathan and Darren Frechette. 2002. “Non-Expected Utility Theories: Weighted Expected, Rank Dependent, and, Cumulative Prospect Theory Utility,” Proceedings of the NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management. St. Louis, MO. Tversky, Amos and Daniel Kahneman. 1992. “Advances in Prospect Theory: Cumulative Representation of Uncertainty,” The Journal of Risk and Uncertainty, October (5)4: pp. 297-323. Von Neumann, John and Oskar Morgenstern. 1944. Theory of Games and Economic Behavior. Princeton, NJ: Princeton University Press. APPENDICES A1. Survey type #1; NSolo=46, NPair=48 In each part of this survey, there are two options (A and B). Each option represents a hypothetical lottery for small money amounts. Please circle the option you would prefer. PART ONE Option A: