====== A Statistical Learning Approach to Personalization in Revenue Management ======

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===== 文献基本信息 =====

==== 标题 ====
A Statistical Learning Approach to Personalization in Revenue Management

==== 作者 ====
  - Xi Chen, New York University (NYU) - Leonard N. Stern School of Business
  - Zachary Owen, Massachusetts Institute of Technology (MIT) - Operations Research Center
  - Clark Pixton, Massachusetts Institute of Technology (MIT) - Operations Research Center
  - David Simchi-Levi, Massachusetts Institute of Technology (MIT) - School of Engineering


==== 出版年份 ====
2015

==== 来源 ====
SSRN

==== 关键词 ====
revenue management, statistical learning

==== 摘要 ====
We develop a general framework for modeling decision problems in which actions can be personalized by taking into account the information available to the decision maker. We demonstrate the application of our method to customized pricing and personalized assortment optimization. We show that learning under our model takes place reliably by establishing finite- sample convergence guarantees for model parameters which hold regardless of the number of customer types, which can be potentially uncountable. The parameter convergence guarantees are then extended to performance guarantees in decision problems. In particular, we provide high-probability bound on the gap between the expected revenue of the best action taken under the estimated parameters and the revenue generated by a decision-maker with full knowledge of the demand distribution. We conduct simulated experiments to demonstrate the performance of our method. We further test our method on real transaction data for airline seating reservations and show that effective customized pricing can increase revenue by at least 7% over the best single-price.

==== 引用方式 ====
Chen, Xi, Zachary Owen, Clark Pixton, and David Simchi-Levi. "A statistical learning approach to personalization in revenue management." Available at SSRN 2579462 (2015).

==== 链接 ====
  - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2579462
  - https://eyun.baidu.com/s/3ggpx5Gv

===== 评阅意见 =====

==== 文献简介 ====
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==== 文献评价 ====
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=== 创新性 ===
研究问题、建模、方法等


=== 相关性 ===
研究问题、发现


=== 严谨性 ===
适当的方法、分析的正确性等


==== 需改改进之处 ====
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==== 进一步研究的可能与方向 ====
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