Note---Response to "Use of Sample Information in Stochastic Recourse and Chance-Constrained Programming Models": On the "Bayesability" of CCP's

Jagannathan's (Jagannathan, R. 1985. Use of sample information in stochastic recourse and chance-constrained programming models. Management Sci. 31 96--108.) invocation of a utility function for a chance-constrained programming problem [CCPP] produces a Bayesian utility maximation problem [BUMP] which is not equivalent to the given CCPP. Therefore, the nonanomalous behavior shown to characterize information value in the BUMP does not refute examples such as Blau's (Blau, R. A. 1974. Stochastic programming and decision analysis: An apparent dilemma. Management Sci. 21 271--276.).utility theory, chance-constrained programming, decision analysis

Note---Rolling Back Decision Trees Requires the Independence Axiom!

The Herstein--Milnor independence axiom is a necessary condition for recursion analysis of decisions in extensive (=tree) form.decision analysis foundations, independence axiom, sure-thing principle

Context-Dependent Choice with Nonlinear and Nontransitive Preferences.

This paper explores implications for one-stage and two-stage decision processes of a theory of choice tha t accommodates nontransitive preferences. It focuses on probabilistic convexification of finite base sets and on choice from convex sets. The one-stage formulation always has a maximally-preferred element in the convex set. Two-stage processes allow not only a holistic procedure for the entire problem, but also give rise to naive and sophisticated sequential procedures. All three have unambiguous solutions, but they can be radically different under intransitivities. The thre e two-stage solutions coincide when preferences are transitive. Copyright 1988 by The Econometric Society.