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The Data-Driven Newsvendor Problem: New Bounds and Insights

Citations

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Cited by:

  1. Jinzhi Bu & David Simchi-Levi & Li Wang, 2023. "Offline Pricing and Demand Learning with Censored Data," Management Science, INFORMS, vol. 69(2), pages 885-903, February.
  2. Jung, Seung Hwan & Yang, Yunsi, 2023. "On the value of operational flexibility in the trailer shipment and assignment problem: Data-driven approaches and reinforcement learning," International Journal of Production Economics, Elsevier, vol. 264(C).
  3. Janssen, Larissa & Claus, Thorsten & Sauer, Jürgen, 2016. "Literature review of deteriorating inventory models by key topics from 2012 to 2015," International Journal of Production Economics, Elsevier, vol. 182(C), pages 86-112.
  4. Shuaian Wang & Xuecheng Tian, 2023. "A Deficiency of the Predict-Then-Optimize Framework: Decreased Decision Quality with Increased Data Size," Mathematics, MDPI, vol. 11(15), pages 1-9, July.
  5. Huan Xu & Constantine Caramanis & Shie Mannor, 2016. "Statistical Optimization in High Dimensions," Operations Research, INFORMS, vol. 64(4), pages 958-979, August.
  6. Boxiao Chen & Xiuli Chao & Cong Shi, 2021. "Nonparametric Learning Algorithms for Joint Pricing and Inventory Control with Lost Sales and Censored Demand," Mathematics of Operations Research, INFORMS, vol. 46(2), pages 726-756, May.
  7. Satya S. Malladi & Alan L. Erera & Chelsea C. White, 2023. "Inventory control with modulated demand and a partially observed modulation process," Annals of Operations Research, Springer, vol. 321(1), pages 343-369, February.
  8. Boxiao Chen & Xiuli Chao & Hyun-Soo Ahn, 2019. "Coordinating Pricing and Inventory Replenishment with Nonparametric Demand Learning," Operations Research, INFORMS, vol. 67(4), pages 1035-1052, July.
  9. Thomas A. Weber, 2023. "Relatively robust decisions," Theory and Decision, Springer, vol. 94(1), pages 35-62, January.
  10. Gah-Yi Ban & Cynthia Rudin, 2019. "The Big Data Newsvendor: Practical Insights from Machine Learning," Operations Research, INFORMS, vol. 67(1), pages 90-108, January.
  11. Soham Ghosh & Sujay Mukhoti, 2023. "Non-parametric generalised newsvendor model," Annals of Operations Research, Springer, vol. 321(1), pages 241-266, February.
  12. Serrano, Breno & Minner, Stefan & Schiffer, Maximilian & Vidal, Thibaut, 2024. "Bilevel optimization for feature selection in the data-driven newsvendor problem," European Journal of Operational Research, Elsevier, vol. 315(2), pages 703-714.
  13. Pascal M. Notz & Richard Pibernik, 2022. "Prescriptive Analytics for Flexible Capacity Management," Management Science, INFORMS, vol. 68(3), pages 1756-1775, March.
  14. Gah-Yi Ban & Jérémie Gallien & Adam J. Mersereau, 2019. "Dynamic Procurement of New Products with Covariate Information: The Residual Tree Method," Manufacturing & Service Operations Management, INFORMS, vol. 21(4), pages 798-815, October.
  15. Karthik Natarajan & Melvyn Sim & Joline Uichanco, 2018. "Asymmetry and Ambiguity in Newsvendor Models," Management Science, INFORMS, vol. 64(7), pages 3146-3167, July.
  16. Yang, Ya & Chi, Huihui & Tang, Ou & Zhou, Wei & Fan, Tijun, 2019. "Cross perishable effect on optimal inventory preservation control," European Journal of Operational Research, Elsevier, vol. 276(3), pages 998-1012.
  17. Rui Wang & Xiao Yan & Chuanjin Zhu, 2023. "Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution," SAGE Open, , vol. 13(2), pages 21582440231, June.
  18. Eric W. K. See-To & Eric W. T. Ngai, 2018. "Customer reviews for demand distribution and sales nowcasting: a big data approach," Annals of Operations Research, Springer, vol. 270(1), pages 415-431, November.
  19. Xinqi Chen & Xingyu Bai & Zeyu Zheng & Nian Si, 2025. "Bias Analysis of Experiments for Multi-Item Multi-Period Inventory Control Policies," Papers 2501.11996, arXiv.org.
  20. Suhan Wu & Min Luo & Jingxia Zhang & Daoheng Zhang & Lianmin Zhang, 2022. "Pharmaceutical Supply Chain in China: Pricing and Production Decisions with Price-Sensitive and Uncertain Demand," Sustainability, MDPI, vol. 14(13), pages 1-28, June.
  21. Huber, Jakob & Müller, Sebastian & Fleischmann, Moritz & Stuckenschmidt, Heiner, 2019. "A data-driven newsvendor problem: From data to decision," European Journal of Operational Research, Elsevier, vol. 278(3), pages 904-915.
  22. Gah-Yi Ban, 2020. "Confidence Intervals for Data-Driven Inventory Policies with Demand Censoring," Operations Research, INFORMS, vol. 68(2), pages 309-326, March.
  23. Steffen Rebennack, 2022. "Data-driven stochastic optimization for distributional ambiguity with integrated confidence region," Journal of Global Optimization, Springer, vol. 84(2), pages 255-293, October.
  24. Adam Fleischhacker & Pak-Wing Fok & Mokshay Madiman & Nan Wu, 2023. "A Closed-Form EVSI Expression for a Multinomial Data-Generating Process," Decision Analysis, INFORMS, vol. 20(1), pages 73-84, March.
  25. van der Laan, Niels & Teunter, Ruud H. & Romeijnders, Ward & Kilic, Onur A., 2022. "The data-driven newsvendor problem: Achieving on-target service-levels using distributionally robust chance-constrained optimization," International Journal of Production Economics, Elsevier, vol. 249(C).
  26. Erkip, Nesim Kohen, 2023. "Can accessing much data reshape the theory? Inventory theory under the challenge of data-driven systems," European Journal of Operational Research, Elsevier, vol. 308(3), pages 949-959.
  27. Hao Yuan & Qi Luo & Cong Shi, 2021. "Marrying Stochastic Gradient Descent with Bandits: Learning Algorithms for Inventory Systems with Fixed Costs," Management Science, INFORMS, vol. 67(10), pages 6089-6115, October.
  28. Yinchu Zhu & Ilya O. Ryzhov, 2022. "Optimal data-driven hiring with equity for underrepresented groups," Papers 2206.09300, arXiv.org.
  29. Lin An & Andrew A. Li & Benjamin Moseley & R. Ravi, 2023. "The Nonstationary Newsvendor with (and without) Predictions," Papers 2305.07993, arXiv.org, revised Feb 2025.
  30. Xin, Linwei & Goldberg, David A., 2021. "Time (in)consistency of multistage distributionally robust inventory models with moment constraints," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1127-1141.
  31. Tian, Yu-Xin & Zhang, Chuan, 2023. "An end-to-end deep learning model for solving data-driven newsvendor problem with accessibility to textual review data," International Journal of Production Economics, Elsevier, vol. 265(C).
  32. Yang, Cheng-Hu & Wang, Hai-Tang & Ma, Xin & Talluri, Srinivas, 2023. "A data-driven newsvendor problem: A high-dimensional and mixed-frequency method," International Journal of Production Economics, Elsevier, vol. 266(C).
  33. Thais de Castro Moraes & Jiancheng Qin & Xue-Ming Yuan & Ek Peng Chew, 2023. "Evolving Hybrid Deep Neural Network Models for End-to-End Inventory Ordering Decisions," Logistics, MDPI, vol. 7(4), pages 1-18, November.
  34. Boxiao Chen & Xiuli Chao, 2020. "Dynamic Inventory Control with Stockout Substitution and Demand Learning," Management Science, INFORMS, vol. 66(11), pages 5108-5127, November.
  35. Zhi Chen & Weijun Xie, 2021. "Regret in the Newsvendor Model with Demand and Yield Randomness," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4176-4197, November.
  36. Zhichao Feng & Milind Dawande & Ganesh Janakiraman & Anyan Qi, 2023. "An Asymptotically Tight Learning Algorithm for Mobile-Promotion Platforms," Management Science, INFORMS, vol. 69(3), pages 1536-1554, March.
  37. Wang Chi Cheung & David Simchi-Levi, 2019. "Sampling-Based Approximation Schemes for Capacitated Stochastic Inventory Control Models," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 668-692, May.
  38. Chao Fu & Weiyong Liu & Wenjun Chang, 2020. "Data-driven multiple criteria decision making for diagnosis of thyroid cancer," Annals of Operations Research, Springer, vol. 293(2), pages 833-862, October.
  39. Andrew F. Siegel & Michael R. Wagner, 2021. "Profit Estimation Error in the Newsvendor Model Under a Parametric Demand Distribution," Management Science, INFORMS, vol. 67(8), pages 4863-4879, August.
  40. Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Optimal Forecast Combination for Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202514, University of Kansas, Department of Economics, revised May 2025.
  41. Cao, Tiantian & Yang, Yi & Zhu, Han & Yu, Mingyue, 2025. "The big data newsvendor problem under demand and yield uncertainties," International Journal of Production Economics, Elsevier, vol. 279(C).
  42. Nir Halman, 2020. "Provably Near-Optimal Approximation Schemes for Implicit Stochastic and Sample-Based Dynamic Programs," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 1157-1181, October.
  43. Vishal Gupta & Nathan Kallus, 2022. "Data Pooling in Stochastic Optimization," Management Science, INFORMS, vol. 68(3), pages 1595-1615, March.
  44. Khouja, Moutaz & Li, Yuefeng & Zhou, Jing, 2023. "Nonlinear pricing for yield management and countering strategic consumer behavior," European Journal of Operational Research, Elsevier, vol. 307(1), pages 212-232.
  45. Soroush Saghafian & Brian Tomlin, 2016. "The Newsvendor under Demand Ambiguity: Combining Data with Moment and Tail Information," Operations Research, INFORMS, vol. 64(1), pages 167-185, February.
  46. Berndt Jesenko & Christian Schlögl, 2021. "The effect of web of science subject categories on clustering: the case of data-driven methods in business and economic sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6785-6801, August.
  47. Ren, Ke & Bidkhori, Hoda & Shen, Zuo-Jun Max, 2024. "Data-driven inventory policy: Learning from sequentially observed non-stationary data," Omega, Elsevier, vol. 123(C).
  48. Boxiao Chen & David Simchi-Levi & Yining Wang & Yuan Zhou, 2022. "Dynamic Pricing and Inventory Control with Fixed Ordering Cost and Incomplete Demand Information," Management Science, INFORMS, vol. 68(8), pages 5684-5703, August.
  49. Bai, Qingguo & Xu, Jianteng & Gong, Yeming & Chauhan, Satyaveer S., 2022. "Robust decisions for regulated sustainable manufacturing with partial demand information: Mandatory emission capacity versus emission tax," European Journal of Operational Research, Elsevier, vol. 298(3), pages 874-893.
  50. Wang, Wanpeng & Deng, Shiming & Zhang, Yuying, 2025. "Data-driven ordering policies for target oriented newsvendor with censored demand," European Journal of Operational Research, Elsevier, vol. 323(1), pages 86-96.
  51. Olivares-Nadal, Alba V., 2024. "Constructing decision rules for multiproduct newsvendors: An integrated estimation-and-optimization framework," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1021-1037.
  52. 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.
  53. David A. Goldberg & Martin I. Reiman & Qiong Wang, 2021. "A Survey of Recent Progress in the Asymptotic Analysis of Inventory Systems," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1718-1750, June.
  54. Liu, Congzheng & Zhu, Wenqi, 2024. "Newsvendor conditional value-at-risk minimisation: A feature-based approach under adaptive data selection," European Journal of Operational Research, Elsevier, vol. 313(2), pages 548-564.
  55. Cong Shi & Weidong Chen & Izak Duenyas, 2016. "Technical Note—Nonparametric Data-Driven Algorithms for Multiproduct Inventory Systems with Censored Demand," Operations Research, INFORMS, vol. 64(2), pages 362-370, April.
  56. Clausen, Johan Bjerre Bach & Larsen, Christian, 2025. "Using an iterative procedure of maximum likelihood estimations to solve the newsvendor problem with censored demand," Omega, Elsevier, vol. 133(C).
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