Dynamic Pricing with Demand Learning Emerging Topics and State of the Art

Authors
Publication date 2022
Host editors
  • X. Chen
  • S. Jasin
  • C. Shi
Book title The Elements of Joint Learning and Optimization in Operations Management
ISBN
  • 9783031019258
  • 9783031019272
ISBN (electronic)
  • 9783031019265
Series Springer Series in Supply Chain Management
Pages (from-to) 79-101
Number of pages 23
Publisher Cham: Springer
Organisations
  • Faculty of Science (FNWI) - Korteweg-de Vries Institute for Mathematics (KdVI)
Abstract

Determining the right price is a fundamental business problem that can be addressed by data-driven methods. In this chapter, we discuss several pricing policies that learn the optimal price from accumulating sales data, both in parametric and nonparametric models, and both for single-product and multiple product settings. We also discuss possible future directions for research: product differentiation, online marketplaces, and Brownian approximations.

Document type Chapter
Language English
Published at https://doi.org/10.1007/978-3-031-01926-5_4
Other links https://www.scopus.com/pages/publications/85139069062
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