J. Neil Bearden

Sequential Search with Multiattribute Options

We describe a search problem in which a decision maker (DM) must select among sequentially encountered options. Each option is described by multiple attributes, and the value of an option is given by a separable function of its attribute values. However, the attribute values are not known with certainty, and can only be ascertained in a predefined order, at some fixed cost. During the search the DM can choose to select an option, purchase information about an attribute value, reject (permanently) the current option and continue the search, or terminate the search and accept a status quo outcome. We introduce a threshold policy for this search process, and prove the optimality of this policy for separable value functions. We then furnish a dynamic programming procedure for prescribing an optimal policy for this problem. Finally, we derive analytic solutions to some special cases of the problem, and present a case study that demonstrates a possible use of the proposed approach.

Newsvendor Demand Chasing Revisited

Existing research on newsvendor behavior asserts that individuals engage in demand chasing---adjusting their order quantities towards prior demand. Several metrics have been used to identify this heuristic. By simulation, current metrics are shown to yield excessive false positives, indicating demand chasing when the true order generating process is independent of prior demand. A simple correlation measure does not suffer from this problem and is proposed here as an alternative to some of the more commonly used measures. This paper was accepted by Martin Lariviere, operations management.

On Optimal Satisficing: How Simple Policies Can Achieve Excellent Results

Herbert Simon introduced the notion of satisficing to explain how boundedly rational agents might approach difficult sequential decision problems. His satisficing decision makers were offered as an alternative to optimizers, who need impressive computational capacities in order to maximize their payoffs. In this chapter, we present a simplified sequential search problem for a satisficing decision maker, and show how to compute its optimal satisficing search policies. Our analyses provide bounds on the performance of satisficing search policies.

Entry Times in Queues with Endogenous Arrivals: Dynamics of Play on the Individual and Aggregate Levels

This chapter considers arrival time and staying out decisions in several variants of a queueing game characterized by endogenously determined arrival times, simultaneous play, finite populations of symmetric players, discrete strategy spaces, and fixed starting and closing times of the service facility. Experimental results show 1) consistent patterns of behavior on the aggregate level in all the conditions that are accounted for quite well by the symmetric mixed-strategy equilibrium of the stage game, 2) considerable individual differences in arrival time distributions that defy classification, and 3) learning trends across iterations of the stage queueing game in some of the experimental conditions. We propose and subsequently test a simple reinforcement-based learning model that, with a few exceptions, accounts for these major findings.

On the multi-attribute stopping problem with general value functions

We examine a sequential selection problem in which a single option must be selected. Each options value is a function of its attributes, whose precise values can be ascertained at a given cost. We prove the optimality of a threshold stopping rule for a general class of objective functions.