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Dynamic Pricing with an Unknown Demand Model: Asymptotically Optimal Semi-Myopic Policies

Citations

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Cited by:

  1. Yinchu Zhu & Ilya O. Ryzhov, 2023. "Semidiscrete optimal transport with unknown costs," Papers 2310.00786, arXiv.org, revised Nov 2023.
  2. Xi Chen & Jianjun Gao & Dongdong Ge & Zizhuo Wang, 2022. "Bayesian dynamic learning and pricing with strategic customers," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3125-3142, August.
  3. Sentao Miao & Xi Chen & Xiuli Chao & Jiaxi Liu & Yidong Zhang, 2022. "Context‐based dynamic pricing with online clustering," Production and Operations Management, Production and Operations Management Society, vol. 31(9), pages 3559-3575, September.
  4. Yiwei Chen & Cong Shi, 2023. "Network revenue management with online inverse batch gradient descent method," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2123-2137, July.
  5. Jianqing Fan & Yongyi Guo & Mengxin Yu, 2021. "Policy Optimization Using Semi-parametric Models for Dynamic Pricing," Papers 2109.06368, arXiv.org, revised May 2022.
  6. Bing Wang & Wenjie Bi & Haiying Liu, 2023. "Dynamic Pricing with Parametric Demand Learning and Reference-Price Effects," Mathematics, MDPI, vol. 11(10), pages 1-14, May.
  7. Virag Shah & Jose Blanchet & Ramesh Johari, 2019. "Semi-parametric dynamic contextual pricing," Papers 1901.02045, arXiv.org, revised Aug 2019.
  8. den Boer, Arnoud V., 2015. "Tracking the market: Dynamic pricing and learning in a changing environment," European Journal of Operational Research, Elsevier, vol. 247(3), pages 914-927.
  9. Xiao, Baichun & Yang, Wei, 2021. "A Bayesian learning model for estimating unknown demand parameter in revenue management," European Journal of Operational Research, Elsevier, vol. 293(1), pages 248-262.
  10. Peter Seele & Claus Dierksmeier & Reto Hofstetter & Mario D. Schultz, 2021. "Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing," Journal of Business Ethics, Springer, vol. 170(4), pages 697-719, May.
  11. Huashuai Qu & Ilya O. Ryzhov & Michael C. Fu & Eric Bergerson & Megan Kurka & Ludek Kopacek, 2020. "Learning Demand Curves in B2B Pricing: A New Framework and Case Study," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1287-1306, May.
  12. L. Jeff Hong & Chenghuai Li & Jun Luo, 2020. "Technical note: Finite‐time regret analysis of Kiefer‐Wolfowitz stochastic approximation algorithm and nonparametric multi‐product dynamic pricing with unknown demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(5), pages 368-379, August.
  13. Ningyuan Chen & Guillermo Gallego, 2018. "A Primal-dual Learning Algorithm for Personalized Dynamic Pricing with an Inventory Constraint," Papers 1812.09234, arXiv.org, revised Oct 2021.
  14. Renato Matta & Timothy J. Lowe, 2023. "Product price alignment with seller service rating and consumer satisfaction," Annals of Operations Research, Springer, vol. 320(2), pages 695-725, January.
  15. Yuqing Zhang & Neil Walton, 2019. "Adaptive Pricing in Insurance: Generalized Linear Models and Gaussian Process Regression Approaches," Papers 1907.05381, arXiv.org.
  16. Ruben Geer & Arnoud V. Boer & Christopher Bayliss & Christine S. M. Currie & Andria Ellina & Malte Esders & Alwin Haensel & Xiao Lei & Kyle D. S. Maclean & Antonio Martinez-Sykora & Asbjørn Nilsen Ris, 2019. "Dynamic pricing and learning with competition: insights from the dynamic pricing challenge at the 2017 INFORMS RM & pricing conference," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(3), pages 185-203, June.
  17. Thomas Loots & Arnoud V. den Boer, 2023. "Data‐driven collusion and competition in a pricing duopoly with multinomial logit demand," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1169-1186, April.
  18. Doan, Xuan Vinh & Lei, Xiao & Shen, Siqian, 2020. "Pricing of reusable resources under ambiguous distributions of demand and service time with emerging applications," European Journal of Operational Research, Elsevier, vol. 282(1), pages 235-251.
  19. Jianyu Xu & Yu-Xiang Wang, 2021. "Logarithmic Regret in Feature-based Dynamic Pricing," Papers 2102.10221, arXiv.org, revised Oct 2021.
  20. Woonghee Tim Huh & Michael Jong Kim & Meichun Lin, 2022. "Bayesian dithering for learning: Asymptotically optimal policies in dynamic pricing," Production and Operations Management, Production and Operations Management Society, vol. 31(9), pages 3576-3593, September.
  21. Jue Wang, 2021. "Optimal Bayesian Demand Learning over Short Horizons," Production and Operations Management, Production and Operations Management Society, vol. 30(4), pages 1154-1177, April.
  22. Ying Zhong & L. Jeff Hong & Guangwu Liu, 2021. "Earning and Learning with Varying Cost," Production and Operations Management, Production and Operations Management Society, vol. 30(8), pages 2379-2394, August.
  23. David Muller & Yurii Nesterov & Vladimir Shikhman, 2021. "Dynamic pricing under nested logit demand," Papers 2101.04486, arXiv.org.
  24. Baris Ata & Alexandre Belloni & Ozan Candogan, 2018. "Latent Agents in Networks: Estimation and Targeting," Papers 1808.04878, arXiv.org, revised Jan 2022.
  25. Gur, Yonatan & Macnamara, Gregory & Saban, Daniela, 2020. "On the Disclosure of Promotion Value in Platforms with Learning Sellers," Research Papers 3865, Stanford University, Graduate School of Business.
  26. Yonatan Gur & Gregory Macnamara & Ilan Morgenstern & Daniela Saban, 2019. "Information Disclosure and Promotion Policy Design for Platforms," Papers 1911.09256, arXiv.org, revised Dec 2022.
  27. Ruben van de Geer & Arnoud V. den Boer & Christopher Bayliss & Christine Currie & Andria Ellina & Malte Esders & Alwin Haensel & Xiao Lei & Kyle D. S. Maclean & Antonio Martinez-Sykora & Asbj{o}rn Nil, 2018. "Dynamic Pricing and Learning with Competition: Insights from the Dynamic Pricing Challenge at the 2017 INFORMS RM & Pricing Conference," Papers 1804.03219, arXiv.org.
  28. Boxiao Chen, 2021. "Data‐Driven Inventory Control with Shifting Demand," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1365-1385, May.
  29. Joon Suk Huh & Ellen Vitercik & Kirthevasan Kandasamy, 2024. "Bandit Profit-maximization for Targeted Marketing," Papers 2403.01361, arXiv.org.
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