Revenue management (RM) is the application of analytical methodologies and tools that
predict consumer behavior and optimize product availability and prices to maximize a firm's …

Choice models are widely applied in psychology, economics, transportation, marketing, and
operations studies. We review the existing developments on the modeling of consumers' …

In this paper, we consider the yet-uncharted assortment optimization problem under the
exponomial choice model, in which the objective is to determine the revenue-maximizing set …

Assortment optimization is a core topic of demand management that finds application in a
broad set of different areas including retail, airline, hotel, and transportation industries as …

Motivated by the successes of deep learning, we propose a class of neural network-based
discrete choice models, called RUMnets, inspired by the random utility maximization (RUM) …

Problem definition: This paper examines the impact of nonrandomness on random choice
models and studies various operations problems under the new discrete choice models …

Modeling decision behavior among multiple choices has been an active research area for
several decades. In this tutorial, we review the classic discrete choice models that are widely …

Understanding how consumers make choices is of paramount importance, as it offers
insights into consumer purchase behavior across multiple products, enables accurate …

Given data on the choices made by consumers for different offer sets, a key challenge is to
develop parsimonious models that describe and predict consumer choice behavior while …

We examine a firm's pricing decision when managing a broad product line with the goal of
optimally balancing the expected return on product investment with the revenue or profit risk …