Demand Estimation When There Are Unobservable Substitutions Amongst Choice Alternatives
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Demand Estimation When There are Unobservable Substitutions Amongst Choice Alternatives
Accurate estimates of the future demand and the substitution probabilities between products are important inputs for retail assortment optimization. However, these quantities are difficult to estimate as the estimation involves understanding and modeling of consumer's choice behavior when a complete choice set is available as well as when the choice set is incomplete (i.e., their response to out-of-stock situations). In this paper, we propose a prospect theory based reference dependent preference structure for consumer choice and use the information available in store scanner sales and inventory data to estimate both the true demand for the products as well as the substitution probabilities between products. We use a combination of theoretical arguments, simulations, and empirical analysis to establish that the proposed reference dependent logit (RDL) model yields robust and efficient estimates. We also compare the performance of RDL against the multinomial logit, two models that use exogenous substitution probabilities, and experts' opinions regarding what the true substitution probabilities could be.
Discrete Choice Modelling and Air Travel Demand
In recent years, airline practitioners and academics have started to explore new ways to model airline passenger demand using discrete choice methods. This book provides an introduction to discrete choice models and uses extensive examples to illustrate how these models have been used in the airline industry. These examples span network planning, revenue management, and pricing applications. Numerous examples of fundamental logit modeling concepts are covered in the text, including probability calculations, value of time calculations, elasticity calculations, nested and non-nested likelihood ratio tests, etc. The core chapters of the book are written at a level appropriate for airline practitioners and graduate students with operations research or travel demand modeling backgrounds. Given the majority of discrete choice modeling advancements in transportation evolved from urban travel demand studies, the introduction first orients readers from different backgrounds by highlighting major distinctions between aviation and urban travel demand studies. This is followed by an in-depth treatment of two of the most common discrete choice models, namely the multinomial and nested logit models. More advanced discrete choice models are covered, including mixed logit models and generalized extreme value models that belong to the generalized nested logit class and/or the network generalized extreme value class. An emphasis is placed on highlighting open research questions associated with these models that will be of particular interest to operations research students. Practical modeling issues related to data and estimation software are also addressed, and an extensive modeling exercise focused on the interpretation and application of statistical tests used to guide the selection of a preferred model specification is included; the modeling exercise uses itinerary choice data from a major airline. The text concludes with a discussion of on-going customer modeling research in aviation. Discrete Choice Modelling and Air Travel Demand is enriched by a comprehensive set of technical appendices that will be of particular interest to advanced students of discrete choice modeling theory. The appendices also include detailed proofs of the multinomial and nested logit models and derivations of measures used to represent competition among alternatives, namely correlation, direct-elasticities, and cross-elasticities.
Quantifying Consumer Preferences
Author: Daniel Slottje
language: en
Publisher: Emerald Group Publishing
Release Date: 2009-05-21
Demand studies and understanding consumer behavior remain two of the most important areas of analysis by practicing applied economists and econometricians. This book presents research on the estimation of demand systems and the measurement of consumer preferences.