no code implementations • 12 Oct 2023 • Hanzhao Wang, Xiaocheng Li, Kalyan Talluri
Discrete-choice models, such as Multinomial Logit, Probit, or Mixed-Logit, are widely used in Marketing, Economics, and Operations Research: given a set of alternatives, the customer is modeled as choosing one of the alternatives to maximize a (latent) utility function.
no code implementations • 10 Aug 2023 • Hanzhao Wang, Zhongze Cai, Xiaocheng Li, Kalyan Talluri
Discrete-choice models are used in economics, marketing and revenue management to predict customer purchase probabilities, say as a function of prices and other features of the offered assortment.
no code implementations • 19 Aug 2022 • Zhongze Cai, Hanzhao Wang, Kalyan Talluri, Xiaocheng Li
Choice modeling has been a central topic in the study of individual preference or utility across many fields including economics, marketing, operations research, and psychology.
no code implementations • 23 Jul 2022 • Hanzhao Wang, Xiaocheng Li, Kalyan Talluri
A number of products are sold in the following sequence: First a focal product is shown, and if the customer purchases, one or more ancillary products are displayed for purchase.
no code implementations • 25 Dec 2021 • Hanzhao Wang, Kalyan Talluri, Xiaocheng Li
In this paper, we show that UCB and Thompson sampling-based pricing algorithms can achieve an $O(d\sqrt{T}\log T)$ regret upper bound without assuming any statistical structure on the covariates $x_t$.