Dynamic Pricing with Demand Learning Emerging Topics and State of the Art
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| Publication date | 2022 |
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| Book title | The Elements of Joint Learning and Optimization in Operations Management |
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| Series | Springer Series in Supply Chain Management |
| Pages (from-to) | 79-101 |
| Number of pages | 23 |
| Publisher | Cham: Springer |
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| 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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