We consider a competitive version of the classical newsboy problem—in which a firm must choose an inventory or production level for a perishable good with random demand, and the optimal solution is a fractile of the demand distribution—and investigate the impact of competition upon industry inventory. A splitting rule specifies how initial industry demand is allocated among competing firms and how any excess demand is allocated among firms with remaining inventory. We examine the relation between equilibrium inventory levels and the splitting rule and provide conditions under which there is a unique equilibrium. Our most general result is that if all excess demand is reallocated, i.e., there is perfect substitutability, then competition never leads to a decrease in industry inventory.

The profitability of a new technology is rarely known with certainty at its announcement date. Consequently, prior to making an adoption decision it behooves the firm considering the adoption of this innovation to reduce the level of uncertainty associated with its profitability. The firm accomplishes this by sequentially gathering information, updating its prior estimate of profitability in a Bayesian manner. Quantifying the uncertainty regarding the innovation permits application of dynamic programming techniques: criteria are derived which tell the firm when to stop collecting information and make the adoption decision. It will be shown that it is optimal for the firm to continue to collect information until its estimate of profitability crosses one of two thresholds: upon crossing the upper threshold the firm adopts the technology, whereas the firm rejects the technology if the lower threshold is crossed. The model predicts that even the manager who behaves optimally will occasionally adopt unprofitable technologies and reject profitable ones.information systems, technology

Many firms in the oil and gas business have long used decision analysis techniques to evaluate exploration and development opportunities and have looked at recent development in option pricing theory as potentially offering improvements over the decision analysis approach. Unfortunately, it is difficult to discern the benefits of the options approach from the literature on the topic: Most of the published examples greatly oversimplify the kinds of projects encountered in practice, and comparisons are typically made to traditional discounted cash flow analysis, which, unlike the option pricing and decision analytic approaches, does not explicitly consider the uncertainty in project cash flows. In this paper, we provide a tutorial introduction to option pricing methods, focusing on how they relate to and can be integrated with decision analysis methods, and describe some lessons learned in using these methods to evaluate some real oil and gas investments.

In Markov models of sequential decision processes, one is often interested in showing that the value function is monotonic, convex, and/or supermodular in the state variables. These kinds of results can be used to develop a qualitative understanding of the model and characterize how the results will change with changes in model parameters. In this paper we present several fundamental results for establishing these kinds of properties. The results are, in essence, "metatheorems" showing that the value functions satisfy property P if the reward functions satisfy property P and the transition probabilities satisfy a stochastic version of this property. We focus our attention on closed convex cone properties, a large class of properties that includes monotonicity, convexity, and supermodularity, as well as combinations of these and many other properties of interest. Subject classifications: Dynamic programming: properties of stochastic models. Decision analysis: properties of sequential models. Area of review: Decision Analysis.

We model a situation in which two retailers consider launching an "Advance Booking Discount" (ABD) program. In this program, customers are enticed to precommit their orders at a discount price prior to the regular selling season. However, these precommitted orders are filled during the selling season. While the ABD program enables the retailers to lock in a portion of the customer demand and use this demand information to develop more accurate forecasts and supply plans, the ABD price reduces profit margin. We analyze the four possible scenarios wherein each of the two firms offer an ABD program or not, and establish conditions under which the unique equilibrium calls for launching the ABD program at both retailers.retailing, competition, pricing, inventory management