A Comparative Empirical Study of Discrete Choice Models in Retail Operations

Management Science (forthcoming)

70 Pages Posted: 13 Mar 2018 Last revised: 6 Apr 2021

See all articles by Gerardo Berbeglia

Gerardo Berbeglia

University of Melbourne - Melbourne Business School

Agustín Garassino

Faculty of Exact and Natural Sciences, University of Buenos Aires

Gustavo Vulcano

Universidad Torcuato Di Tella - School of Business

Date Written: March 6, 2018

Abstract

Demand estimation is a fundamental task in retail operations and revenue management, providing the necessary input data for inventory control, assortment and price optimization models. The task is particularly difficult in operational contexts when product availability varies over time and customers may substitute. In addition to the classical multinomial logit (MNL) model and its variants (e.g., nested logit, mixed MNL), new demand models have been proposed (e.g., the Markov chain model) and others have been revisited (e.g., the rank-based and exponomial models). At the same time, new computational approaches were developed to ease the estimation function (e.g., column generation, EM algorithms).

In this paper, we conduct a systematic, empirical study of different demand models and estimation algorithms, spanning both maximum likelihood and least squares criteria. Through an exhaustive set of numerical experiments on synthetic and real data, we provide comparative statistics of the quality of the different choice models and estimation methods, and characterize operational environments suitable for different model/estimation implementations.

Keywords: discrete choice, revenue management, model estimation, consumer preferences

Suggested Citation

Berbeglia, Gerardo and Garassino, Agustín and Vulcano, Gustavo, A Comparative Empirical Study of Discrete Choice Models in Retail Operations (March 6, 2018). Management Science (forthcoming), Available at SSRN: https://ssrn.com/abstract=3136816 or http://dx.doi.org/10.2139/ssrn.3136816

Gerardo Berbeglia (Contact Author)

University of Melbourne - Melbourne Business School ( email )

200 Leicester Street
Carlton, Victoria 3053 3186
Australia

Agustín Garassino

Faculty of Exact and Natural Sciences, University of Buenos Aires ( email )

Pabellón 2, Piso 1
Buenos Aires, Buenos Aires 1428
Argentina

Gustavo Vulcano

Universidad Torcuato Di Tella - School of Business ( email )

Avda Figueroa Alcorta 7350
Buenos Aires, CABA 1428
Argentina

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