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Related papers: Dynamic Pricing with Demand Covariates

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We consider dynamic pricing with covariates under a generalized linear demand model: a seller can dynamically adjust the price of a product over a horizon of $T$ time periods, and at each time period $t$, the demand of the product is…

Machine Learning · Computer Science 2023-11-14 Hanzhao Wang , Kalyan Talluri , Xiaocheng Li

Dynamic pricing of goods in a competitive environment to maximize revenue is a natural objective and has been a subject of research over the years. In this paper, we focus on a class of markets exhibiting the substitutes property with…

Machine Learning · Computer Science 2017-09-18 Paresh Nakhe

We consider a firm that sells a large number of products to its customers in an online fashion. Each product is described by a high dimensional feature vector, and the market value of a product is assumed to be linear in the values of its…

Computer Science and Game Theory · Computer Science 2017-04-26 Adel Javanmard

We consider a novel formulation of the dynamic pricing and demand learning problem, where the evolution of demand in response to posted prices is governed by a stochastic variant of the popular Bass model with parameters $\alpha, \beta$…

Machine Learning · Computer Science 2021-03-10 Shipra Agrawal , Steven Yin , Assaf Zeevi

We study contextual dynamic pricing problems where a firm sells products to $T$ sequentially-arriving consumers, behaving according to an unknown demand model. The firm aims to minimize its regret over a clairvoyant that knows the model in…

Machine Learning · Computer Science 2025-04-07 Zifeng Zhao , Feiyu Jiang , Yi Yu

We consider a periodical equilibrium pricing problem for multiple firms over a planning horizon of T periods. At each period, firms set their selling prices and receive stochastic demand from consumers. Firms do not know their underlying…

Computer Science and Game Theory · Computer Science 2024-06-07 Yongge Yang , Yu-Ching Lee , Po-An Chen

We consider price competition among multiple sellers over a selling horizon of $T$ periods. In each period, sellers simultaneously offer their prices (which are made public) and subsequently observe their respective demand (not made…

Machine Learning · Statistics 2026-05-08 Daniele Bracale , Moulinath Banerjee , Cong Shi , Yuekai Sun

We study the pricing problem faced by a firm that sells a large number of products, described via a wide range of features, to customers that arrive over time. Customers independently make purchasing decisions according to a general choice…

Machine Learning · Statistics 2018-01-03 Adel Javanmard , Hamid Nazerzadeh

Motivated by posted price auctions where buyers are grouped in an unknown number of latent types characterized by their private values for the good on sale, we investigate revenue maximization in stochastic dynamic pricing when the…

Machine Learning · Computer Science 2019-03-06 Nicolò Cesa-Bianchi , Tommaso Cesari , Vianney Perchet

Feature-based dynamic pricing is an increasingly popular model of setting prices for highly differentiated products with applications in digital marketing, online sales, real estate and so on. The problem was formally studied as an online…

Machine Learning · Computer Science 2021-10-26 Jianyu Xu , Yu-Xiang Wang

Recently, there is growing interest and need for dynamic pricing algorithms, especially, in the field of online marketplaces by offering smart pricing options for big online stores. We present an approach to adjust prices based on the…

Optimization and Control · Mathematics 2021-01-13 David Müller , Yurii Nesterov , Vladimir Shikhman

Price discrimination, which refers to the strategy of setting different prices for different customer groups, has been widely used in online retailing. Although it helps boost the collected revenue for online retailers, it might create…

Machine Learning · Computer Science 2023-07-31 Xi Chen , Jiameng Lyu , Xuan Zhang , Yuan Zhou

We consider dynamic pricing strategies in a streamed longitudinal data set-up where the objective is to maximize, over time, the cumulative profit across a large number of customer segments. We consider a dynamic model with the consumers'…

Machine Learning · Computer Science 2023-10-17 Rashmi Ranjan Bhuyan , Adel Javanmard , Sungchul Kim , Gourab Mukherjee , Ryan A. Rossi , Tong Yu , Handong Zhao

We study an online dynamic pricing problem where the potential demand at each time period $t=1,2,\ldots, T$ is stochastic and dependent on the price. However, a perishable inventory is imposed at the beginning of each time $t$, censoring…

Machine Learning · Statistics 2026-01-26 Jianyu Xu , Yining Wang , Xi Chen , Yu-Xiang Wang

We consider a dynamic pricing problem where customer response to the current price is impacted by the customer price expectation, aka reference price. We study a simple and novel reference price mechanism where reference price is the…

Machine Learning · Computer Science 2024-07-23 Shipra Agrawal , Wei Tang

The prevalence of e-commerce has made detailed customers' personal information readily accessible to retailers, and this information has been widely used in pricing decisions. When involving personalized information, how to protect the…

Cryptography and Security · Computer Science 2021-07-27 Xi Chen , David Simchi-Levi , Yining Wang

In contextual dynamic pricing, a seller sequentially prices goods based on contextual information. Buyers will purchase products only if the prices are below their valuations. The goal of the seller is to design a pricing strategy that…

Machine Learning · Statistics 2025-02-14 Matilde Tullii , Solenne Gaucher , Nadav Merlis , Vianney Perchet

Personalized pricing, which involves tailoring prices based on individual characteristics, is commonly used by firms to implement a consumer-specific pricing policy. In this process, buyers can also strategically manipulate their feature…

Machine Learning · Statistics 2024-06-27 Pangpang Liu , Zhuoran Yang , Zhaoran Wang , Will Wei Sun

In this paper, we study the contextual dynamic pricing problem where the market value of a product is linear in its observed features plus some market noise. Products are sold one at a time, and only a binary response indicating success or…

Machine Learning · Computer Science 2022-05-05 Jianqing Fan , Yongyi Guo , Mengxin Yu

This paper introduces a novel contextual bandit algorithm for personalized pricing under utility fairness constraints in scenarios with uncertain demand, achieving an optimal regret upper bound. Our approach, which incorporates dynamic…

Machine Learning · Statistics 2023-11-29 Xi Chen , David Simchi-Levi , Yining Wang
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