Customer Choice Models vs. Machine Learning: Finding Optimal Product Displays on Alibaba
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Publication:5031014
DOI10.1287/opre.2021.2158zbMath1484.91212OpenAlexW3210418234MaRDI QIDQ5031014
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Publication date: 18 February 2022
Published in: Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1287/opre.2021.2158
Artificial neural networks and deep learning (68T07) Auctions, bargaining, bidding and selling, and other market models (91B26) Experimental work for problems pertaining to game theory, economics, and finance (91-05)
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Uses Software
Cites Work
- Unnamed Item
- High-dimensional Ising model selection using \(\ell _{1}\)-regularized logistic regression
- Assortment Optimization Under Variants of the Nested Logit Model
- Coordinating Inventory Control and Pricing Strategies for Perishable Products
- Estimating Primary Demand for Substitutable Products from Sales Transaction Data
- Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint
- Inventory Management of a Fast-Fashion Retail Network
- Dynamic Assortment with Demand Learning for Seasonal Consumer Goods
- Discrete Choice Methods with Simulation
- Revenue Management Under a General Discrete Choice Model of Consumer Behavior
- Centralized and Competitive Inventory Models with Demand Substitution
- Technical Note—An Expectation-Maximization Algorithm to Estimate the Parameters of the Markov Chain Choice Model
- Approximation Algorithms for Product Framing and Pricing
- Recommender Systems Handbook
- Coordinating Inventory Control and Pricing Strategies with Random Demand and Fixed Ordering Cost: The Finite Horizon Case
- Stochastic gradient boosting.
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