Decision Analysis current issue

From the Editors ...

Tue, 15 Dec 2009 10:01:39 PST

This issue's "From the Editors" column is coauthored with all the associate editors to emphasize their major role in the leadership of the journal. Our first article is on "Proper Scoring Rules, Dominated Forecasts, and Coherence," by Mark J. Schervish, Teddy Seidenfeld, and Joseph B. Kadane. In the second article, Jason R. W. Merrick provides an overview of "Bayesian Simulation and Decision Analysis: An Expository Survey." Our third article, by Barry R. Cobb and Atin Basuchoudhary, is on "A Decision Analysis Approach to Solving the Signaling Game." The next article, by Robert T. Clemen and James E. Smith, is "On the Choice of Baselines in Multiattribute Portfolio Analysis: A Cautionary Note." In our final article, Russ Garber presents "An Interview with Ronald A. Howard."

Proper Scoring Rules, Dominated Forecasts, and Coherence

Schervish, M. J., Seidenfeld, T., Kadane, J. B. — Tue, 15 Dec 2009 10:01:39 PST

The concept of coherent probabilities and conditional probabilities through a gambling argument and through a parallel argument based on a quadratic scoring rule was introduced by de Finetti (de Finetti, B. 1974. The Theory of Probability. John Wiley & Sons, New York). He showed that the two arguments lead to the same concept of coherence. When dealing with events only, there is a rich class of scoring rules that might be used in place of the quadratic scoring rule. We give conditions under which a general strictly proper scoring rule can replace the quadratic scoring rule while preserving the equivalence of de Finetti's two arguments. In proving our results, we present a strengthening of the usual minimax theorem. We also present generalizations of de Finetti's fundamental theorem of probability to deal with conditional probabilities.

Bayesian Simulation and Decision Analysis: An Expository Survey

Merrick, J. R. W. — Tue, 15 Dec 2009 10:01:39 PST

The aim of this expository survey on Bayesian simulation is to stimulate more work in the area by decision analysts. We discuss the main areas of research performed thus far, including input analysis, propagation and estimation of output uncertainty, output analysis, making decisions with simulations, selecting the best simulated system, and applications of Bayesian simulation methods. Throughout, we offer avenues of future research in Bayesian simulation that may be of interest to decision analysts.

A Decision Analysis Approach to Solving the Signaling Game

Cobb, B. R., Basuchoudhary, A. — Tue, 15 Dec 2009 10:01:39 PST

Decision analysis has traditionally been applied to choices under uncertainty involving a single decision maker. Game theory has been applied to solving games of strategic interaction between two or more players. Building upon recent work of van Binsbergen and Marx (van Binsbergen, J. H., L. M. Marx. 2007. Exploring relations between decision analysis and game theory. Decision Anal. 4(1) 32–40), this paper defines a modified decision-theoretic approach to solving games of strategic interaction between two players. Using this method, the choices of the two players are modeled with separate decision trees comprised entirely of chance nodes. Optimal policies are reflected in the probabilities in the decision trees of each player. In many cases, the Nash equilibrium strategy for each player can be obtained by rolling back the opponent's decision tree. Results are demonstrated for the multistage signaling game, which is difficult to model using decision nodes to represent strategies, as in the approach of van Binsbergen and Marx.

On the Choice of Baselines in Multiattribute Portfolio Analysis: A Cautionary Note

Clemen, R. T., Smith, J. E. — Tue, 15 Dec 2009 10:01:39 PST

In multiattribute portfolio optimization, a decision maker must evaluate a number of projects on multiple dimensions and then select the set of projects that optimizes the portfolio's overall value. In this note, we discuss the importance of establishing an appropriate baseline score for not doing a project in multiattribute portfolio analysis. We believe that practitioners often implicitly assume that not doing a project results in the worst possible score on all attributes. We argue that this assumption is often inappropriate and may lead to incorrect recommendations.

An Interview with Ronald A. Howard

Garber, R. — Tue, 15 Dec 2009 10:01:39 PST

Ronald A. Howard has contributed substantially to defining the field of decision analysis since his first publication using that term in 1966 (Howard 1966). He has been a professor at the School of Engineering at Stanford since 1965, currently teaching an average of 450 students per year and having had 86 Ph.D. students in the last 44 years. In addition to numerous journal publications, Ron Howard has authored five books, including one very recent book on ethical decision making (Howard 1960, 1971; Howard and Matheson 1977, 1984; Howard and Korver 2008). He earned his Sc.D. in electrical engineering from the Massachusetts Institute of Technology (MIT) in 1958. Prior to joining the Stanford faculty, Howard was associate professor of electrical engineering, associate professor of industrial management, and associate director of the Operations Research Center at MIT. In 1986 he received the Frank P. Ramsey Award for "distinguished contributions in decision analysis." Professor Howard was also a cofounder of Strategic Decisions Group (a private consulting firm) and the Decision Education Foundation (a philanthropic educational foundation). Earlier this year I had the pleasure of interviewing Professor Howard to discuss his life and his experiences in academia and business, as well as his current directions.

About the Authors

Tue, 15 Dec 2009 10:01:39 PST

No abstract available.

Appreciation to Referees, 2009

Tue, 15 Dec 2009 10:01:39 PST

No abstract available.

INFORMS MEETING CALENDAR

Tue, 15 Dec 2009 10:01:39 PST

No abstract available.