Retail Demand Management: Forecasting, Assortment Planning and Pricing

In the first part of the dissertation, we focus on the retailer\u27s 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 methodology to a proprietary dataset collected by a professional baseball franchise in Japan. Based on the observed heterogeneity in SVI, we provide segment-specific pricing recommendations to achieve a service level objective

A Demand Estimation Procedure for Retail Assortment Optimization with Results from Implementations

We consider the problem of choosing, from a set of N potential stock-keeping units (SKUs) in a retail category, K SKUs to be carried at each store to maximize revenue or profit. Assortments can vary by store, subject to a maximum number of different assortments. We view a SKU as a set of attribute levels and also model possible substitutions when a customer\u27s first choice is not in the assortment. We apply maximum likelihood estimation to sales history of the SKUs currently carried by the retailer to estimate the demand for attribute levels and substitution probabilities, and from this, the demand for any potential SKU, including those not currently carried by the retailer. We specify several alternative heuristics for choosing SKUs to be carried in an assortment. We apply this approach to optimize assortments for three real examples: snack cakes, tires, and automotive appearance chemicals. A portion of our recommendations for tires and appearance chemicals were implemented and produced sales increases of 5.8% and 3.6%, respectively, which are significant improvements relative to typical retailer annual comparable store revenue increases. We also forecast sales shares of 1, 11, and 25 new SKUs for the snack cake, tire, and automotive appearance chemical applications, respectively, with mean absolute percentage errors (MAPEs) of 16.2%, 19.1%, and 28.7%, which compares favorably to the 30.7% MAPE for chain sales of two new SKUs reported by Fader and Hardie (1996)

Measuring Seat Value in Stadiums and Theaters

We study how the seat value perceived by consumers attending an event in a theater/stadium depends on the location of their seat relative to the stage/field. We develop a measure of seat value, called the Seat Value Index, and relate it to seat location and consumer characteristics. We implement our analysis on a proprietary data set that a professional baseball franchise in Japan collected from its customers, and provide recommendations. For instance, we find that customers seated in symmetric seats on left and right fields might derive very different valuations from the seats. We also find that the more frequent visitors to the stadium report extreme seat value less often when compared with first-time visitors. Our findings and insights remain robust to the effects of price and game-related factors. Thus, our research quantifies the significant influence of seat location on the ex-post seat value perceived by customers. Utilizing the heterogeneity in seat values at different seat locations, we provide segment-specific pricing recommendations based on a service-level objective that would limit the fraction of customers experiencing low seat value to a desired threshold. Key words: seat value; empirical research; revenue management applications; customer behavior; ordinal logit model

Static and dynamic analysis of an aerofoil bladed disc using the concept of cyclic symmetry

Centrifugal fan impellers with aerofoil blades are analysed using the concept of cyclic symmetry. Impellers with single cover plate alone are considered. Both static and dynamic analyses are done and user-friendly programs for the design of these impellers are developed. In addition, parametric studies were also undertaken. Variations of maximum stress and the lowest frequency with the various values of both the outer diameter and thickness of the impeller plates was carried out, and the results plotted