Presented to the Faculties of the University of Pennsylvania in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy 2011

R E TA I L D E M A N D M A N A G E M E N T : F O R E C A S T I N G , A S S O R T M E N T P L A N N I N G A N D P R I C I N G Ramnath Vaidyanathan Marshall Fisher In the first part of the dissertation, we focus on the retailer’s problem of forecasting demand for products in a category (including those that they have never carried before), optimizing the selected assortment, and customizing the assortment by store to maximize chain-wide revenues or profits. We develop algorithms for demand forecasting and assortment optimization, and demonstrate their use in practical applications. In the second part, we study the sensitivity of the optimal assortment to the underlying assumptions made about demand, substitution and inventory. In particular, we explore the impact of choice model mis-specification and ignoring stock-outs on the optimal profits. We develop bounds on the optimality gap in terms of demand variability, in-stock rate and consumer heterogeneity. Understanding this sensitivity is key to developing more robust approaches to assortment optimization. In the third and final part of the dissertation, we study how the seat value perceived by consumers attending an event in a stadium, depends on the location of their seat relative to the field. We develop a measure of seat value, called the Seat Value Index (SVI), and relate it to seat location and consumer characteristics. We apply our