||We develop a structural demand model that endogenously captures the effect of out-of-stocks
on customer choice by simulating a time-varying set of available alternatives. Our
estimation method uses store-level data on sales and partial information on product
availability. Our model allows for flexible substitution patterns, which are based
on utility maximization principles and can accommodate categorical and continuous
product characteristics. The methodology can be applied to data from multiple markets
and in categories with a relatively large number of alternatives, slow-moving products,
and frequent out-of-stocks (unlike many existing approaches). In addition, we illustrate
how the model can be used to assist the decisions of a store manager in two ways.
First, we show how to quantify the lost sales induced by out-of-stock products. Second,
we provide insights on the financial consequences of out-of-stocks and suggest price
promotion policies that can be used to help mitigate their negative economic impact,
which run counter to simple commonly used heuristics. © 2010 INFORMS.