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The Big Data Newsvendor: Practical Insights from Machine Learning

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Cited by:

  1. Jos'e-Manuel Pe~na & Fernando Su'arez & Omar Larr'e & Domingo Ram'irez & Arturo Cifuentes, 2023. "A Modified CTGAN-Plus-Features Based Method for Optimal Asset Allocation," Papers 2302.02269, arXiv.org, revised May 2024.
  2. 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.
  3. 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).
  4. Zhen-Yu Chen & Zhi-Ping Fan & Minghe Sun, 2023. "Machine Learning Methods for Data-Driven Demand Estimation and Assortment Planning Considering Cross-Selling and Substitutions," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 158-177, January.
  5. 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).
  6. 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.
  7. 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).
  8. Muñoz, M.A. & Pineda, S. & Morales, J.M., 2022. "A bilevel framework for decision-making under uncertainty with contextual information," Omega, Elsevier, vol. 108(C).
  9. Hamsa Bastani & Mohsen Bayati, 2020. "Online Decision Making with High-Dimensional Covariates," Operations Research, INFORMS, vol. 68(1), pages 276-294, January.
  10. Susan Athey & Stefan Wager, 2021. "Policy Learning With Observational Data," Econometrica, Econometric Society, vol. 89(1), pages 133-161, January.
  11. Felix Wick & Ulrich Kerzel & Martin Hahn & Moritz Wolf & Trapti Singhal & Daniel Stemmer & Jakob Ernst & Michael Feindt, 2021. "Demand Forecasting of Individual Probability Density Functions with Machine Learning," SN Operations Research Forum, Springer, vol. 2(3), pages 1-39, September.
  12. Francis de Véricourt & Georgia Perakis, 2020. "Frontiers in Service Science: The Management of Data Analytics Services: New Challenges and Future Directions," Service Science, INFORMS, vol. 12(4), pages 121-129, December.
  13. Tsan‐Ming Choi & Subodha Kumar & Xiaohang Yue & Hau‐Ling Chan, 2022. "Disruptive Technologies and Operations Management in the Industry 4.0 Era and Beyond," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 9-31, January.
  14. Yichun Hu & Nathan Kallus & Xiaojie Mao, 2022. "Fast Rates for Contextual Linear Optimization," Management Science, INFORMS, vol. 68(6), pages 4236-4245, June.
  15. Qi Feng & J. George Shanthikumar, 2022. "Developing operations management data analytics," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4544-4557, December.
  16. 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.
  17. van der Haar, Joost F. & Wellens, Arnoud P. & Boute, Robert N. & Basten, Rob J.I., 2024. "Supervised learning for integrated forecasting and inventory control," European Journal of Operational Research, Elsevier, vol. 319(2), pages 573-586.
  18. Bernardo K. Pagnoncelli & Domingo Ramírez & Hamed Rahimian & Arturo Cifuentes, 2023. "A Synthetic Data-Plus-Features Driven Approach for Portfolio Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 187-204, June.
  19. 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.
  20. Gao, Yuqiang & Wang, Zishuai & Wang, Kaihua & Zhang, Ruiai & Lu, Yuchen, 2023. "Effect of big data on enterprise financialization: Evidence from China's SMEs," Technology in Society, Elsevier, vol. 75(C).
  21. Tian, Xuecheng & Wang, Shuaian & Laporte, Gilbert & Yang, Ying, 2024. "Determinism versus uncertainty: Examining the worst-case expected performance of data-driven policies," European Journal of Operational Research, Elsevier, vol. 318(1), pages 242-252.
  22. 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.
  23. Yi Wang & Yafei Yang & Zhaoxiang Qin & Yefei Yang & Jun Li, 2023. "A Literature Review on the Application of Digital Technology in Achieving Green Supply Chain Management," Sustainability, MDPI, vol. 15(11), pages 1-18, May.
  24. Corredera, Alberto, 2022. "Prescriptive selection of machine learning hyperparameters with applications in power markets: retailer's optimal trading," DES - Working Papers. Statistics and Econometrics. WS 33693, Universidad Carlos III de Madrid. Departamento de Estadística.
  25. Mintz, Yonatan & Aswani, Anil & Kaminsky, Philip & Flowers, Elena & Fukuoka, Yoshimi, 2023. "Behavioral analytics for myopic agents," European Journal of Operational Research, Elsevier, vol. 310(2), pages 793-811.
  26. Gen Sakoda & Hideki Takayasu & Misako Takayasu, 2019. "Data Science Solutions for Retail Strategy to Reduce Waste Keeping High Profit," Sustainability, MDPI, vol. 11(13), pages 1-30, June.
  27. Corredera, Alberto & Ruiz, Carlos, 2023. "Prescriptive selection of machine learning hyperparameters with applications in power markets: Retailer’s optimal trading," European Journal of Operational Research, Elsevier, vol. 306(1), pages 370-388.
  28. 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.
  29. Sheng Liu & Long He & Zuo-Jun Max Shen, 2021. "On-Time Last-Mile Delivery: Order Assignment with Travel-Time Predictors," Management Science, INFORMS, vol. 67(7), pages 4095-4119, July.
  30. Viet Anh Nguyen & Fan Zhang & Shanshan Wang & Jose Blanchet & Erick Delage & Yinyu Ye, 2021. "Robustifying Conditional Portfolio Decisions via Optimal Transport," Papers 2103.16451, arXiv.org, revised Apr 2024.
  31. Shanshan Wang & Erick Delage, 2024. "A Column Generation Scheme for Distributionally Robust Multi-Item Newsvendor Problems," INFORMS Journal on Computing, INFORMS, vol. 36(3), pages 849-867, May.
  32. Ari Hyytinen & Petri Rouvinen & Mika Pajarinen & Joosua Virtanen, 2023. "Ex Ante Predictability of Rapid Growth: A Design Science Approach," Entrepreneurship Theory and Practice, , vol. 47(6), pages 2465-2493, November.
  33. Meng Qi & Ying Cao & Zuo-Jun (Max) Shen, 2022. "Distributionally Robust Conditional Quantile Prediction with Fixed Design," Management Science, INFORMS, vol. 68(3), pages 1639-1658, March.
  34. Yi‐Jen (Ian) Ho & Siyuan Liu & Jingchuan Pu & Dian Zhang, 2022. "Is it all about you or your driving? Designing IoT‐enabled risk assessments," Production and Operations Management, Production and Operations Management Society, vol. 31(11), pages 4205-4222, November.
  35. Xi Chen & Zachary Owen & Clark Pixton & David Simchi-Levi, 2022. "A Statistical Learning Approach to Personalization in Revenue Management," Management Science, INFORMS, vol. 68(3), pages 1923-1937, March.
  36. Justin Jia & Elena Katok, 2022. "Technical note: Sufficient operational statistics," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2429-2437, June.
  37. Tinglong Dai & Jing-Sheng Song, 2021. "Transforming COVID-19 vaccines into vaccination," Health Care Management Science, Springer, vol. 24(3), pages 455-459, September.
  38. Miguel Angel Muñoz & Pierre Pinson & Jalal Kazempour, 2023. "Online decision making for trading wind energy," Computational Management Science, Springer, vol. 20(1), pages 1-31, December.
  39. Rettinger, Moritz & Mandl, Christian & Minner, Stefan, 2024. "A data-driven approach for optimal operational and financial commodity hedging," European Journal of Operational Research, Elsevier, vol. 316(1), pages 341-360.
  40. 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.
  41. 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.
  42. Nam Ho-Nguyen & Fatma Kılınç-Karzan, 2022. "Risk Guarantees for End-to-End Prediction and Optimization Processes," Management Science, INFORMS, vol. 68(12), pages 8680-8698, December.
  43. Andrew Butler & Roy H. Kwon, 2021. "Integrating prediction in mean-variance portfolio optimization," Papers 2102.09287, arXiv.org, revised Nov 2022.
  44. Liu, Congzheng & Letchford, Adam N. & Svetunkov, Ivan, 2022. "Newsvendor problems: An integrated method for estimation and optimisation," European Journal of Operational Research, Elsevier, vol. 300(2), pages 590-601.
  45. Gah-Yi Ban, 2020. "Confidence Intervals for Data-Driven Inventory Policies with Demand Censoring," Operations Research, INFORMS, vol. 68(2), pages 309-326, March.
  46. João M. C. Sousa & Rodrigo Luís & Rui Mirra Santos & Luís Mendonça & Susana M. Vieira, 2024. "Fuzzy Multi-Item Newsvendor Problem: An Application to Inventory Management," Mathematics, MDPI, vol. 12(11), pages 1-17, May.
  47. Hongzhe Zhang & Xiaohang Zhao & Xiao Fang & Bintong Chen, 2024. "Proactive Resource Request for Disaster Response: A Deep Learning-Based Optimization Model," Information Systems Research, INFORMS, vol. 35(2), pages 528-550, June.
  48. Adam N. Elmachtoub & Paul Grigas, 2022. "Smart “Predict, then Optimize”," Management Science, INFORMS, vol. 68(1), pages 9-26, January.
  49. Velibor V. Miv{s}i'c & Georgia Perakis, 2019. "Data Analytics in Operations Management: A Review," Papers 1905.00556, arXiv.org.
  50. Schäfers, A. & Bougioukos, V. & Karamatzanis, G. & Nikolopoulos, K., 2024. "Prediction-led prescription: Optimal Decision-Making in times of turbulence and business performance improvement," Journal of Business Research, Elsevier, vol. 182(C).
  51. van Eekelen, Wouter, 2023. "Distributionally robust views on queues and related stochastic models," Other publications TiSEM 9b99fc05-9d68-48eb-ae8c-9, Tilburg University, School of Economics and Management.
  52. 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.
  53. Tsan-Ming Choi & Alexandre Dolgui & Dmitry Ivanov & Erwin Pesch, 2022. "OR and analytics for digital, resilient, and sustainable manufacturing 4.0," Annals of Operations Research, Springer, vol. 310(1), pages 1-6, March.
  54. 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.
  55. Soham Ghosh & Sujay Mukhoti, 2023. "Non-parametric generalised newsvendor model," Annals of Operations Research, Springer, vol. 321(1), pages 241-266, February.
  56. Hossein Abouee‐Mehrizi & Mahdi Mirjalili & Vahid Sarhangian, 2022. "Data‐driven platelet inventory management under uncertainty in the remaining shelf life of units," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3914-3932, October.
  57. Yinchu Zhu & Ilya O. Ryzhov, 2022. "Optimal data-driven hiring with equity for underrepresented groups," Papers 2206.09300, arXiv.org.
  58. Harun Avci & Kagan Gokbayrak & Emre Nadar, 2020. "Structural Results for Average‐Cost Inventory Models with Markov‐Modulated Demand and Partial Information," Production and Operations Management, Production and Operations Management Society, vol. 29(1), pages 156-173, January.
  59. Lin An & Andrew A. Li & Benjamin Moseley & R. Ravi, 2023. "The Nonstationary Newsvendor with (and without) Predictions," Papers 2305.07993, arXiv.org, revised Jul 2024.
  60. 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.
  61. Velibor V. Mišić & Georgia Perakis, 2020. "Data Analytics in Operations Management: A Review," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 158-169, January.
  62. Joaquin Gonzalez & Liliana Avelar Sosa & Gabriel Bravo & Oliverio Cruz-Mejia & Jose-Manuel Mejia-Muñoz, 2024. "Fog Computing and Industry 4.0 for Newsvendor Inventory Model Using Attention Mechanism and Gated Recurrent Unit," Logistics, MDPI, vol. 8(2), pages 1-14, June.
  63. Xiong, Xing & Li, Yanzhi & Yang, Wenguo & Shen, Huaxiao, 2022. "Data-driven robust dual-sourcing inventory management under purchase price and demand uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
  64. 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.
  65. Jun Li & Yizhe Huang & Yan‐Fu Li & Shuming Wang, 2023. "Redundancy allocation under state‐dependent distributional uncertainty of component lifetimes," Production and Operations Management, Production and Operations Management Society, vol. 32(3), pages 930-950, March.
  66. Notz, Pascal M. & Pibernik, Richard, 2024. "Explainable subgradient tree boosting for prescriptive analytics in operations management," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1119-1133.
  67. Huang, Di & Zhang, Jinyu & Liu, Zhiyuan & He, Yiliu & Liu, Pan, 2024. "A novel ranking method based on semi-SPO for battery swapping allocation optimization in a hybrid electric transit system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).
  68. Notz, Pascal M. & Wolf, Peter K. & Pibernik, Richard, 2023. "Prescriptive analytics for a multi-shift staffing problem," European Journal of Operational Research, Elsevier, vol. 305(2), pages 887-901.
  69. Christian Mandl & Selvaprabu Nadarajah & Stefan Minner & Srinagesh Gavirneni, 2022. "Data‐driven storage operations: Cross‐commodity backtest and structured policies," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2438-2456, June.
  70. Bingnan Yang & Xianhao Xu & Yeming Gong & Yacine Rekik, 2024. "Data-driven optimization models for inventory and financing decisions in online retailing platforms," Annals of Operations Research, Springer, vol. 339(1), pages 741-764, August.
  71. Junfei Huang & Avishai Mandelbaum & Petar Momčilović, 2022. "Appointment-driven service systems with many servers," Queueing Systems: Theory and Applications, Springer, vol. 100(3), pages 529-531, April.
  72. Pirayesh Neghab, Davood & Khayyati, Siamak & Karaesmen, Fikri, 2022. "An integrated data-driven method using deep learning for a newsvendor problem with unobservable features," European Journal of Operational Research, Elsevier, vol. 302(2), pages 482-496.
  73. Mengshi Lu & Zuo‐Jun Max Shen, 2021. "A Review of Robust Operations Management under Model Uncertainty," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1927-1943, June.
  74. Yunxiao Deng & Suvrajeet Sen, 2022. "Predictive stochastic programming," Computational Management Science, Springer, vol. 19(1), pages 65-98, January.
  75. Shaochong Lin & Youhua (Frank) Chen & Yanzhi Li & Zuo‐Jun Max Shen, 2022. "Data‐Driven Newsvendor Problems Regularized by a Profit Risk Constraint," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1630-1644, April.
  76. Yen, Benjamin P.-C. & Luo, Yu, 2023. "Navigational guidance – A deep learning approach," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1179-1191.
  77. John P. Saldanha & Bradley S. Price & Douglas J. Thomas, 2023. "A nonparametric approach for setting safety stock levels," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1150-1168, April.
  78. Pascal M. Notz & Richard Pibernik, 2022. "Prescriptive Analytics for Flexible Capacity Management," Management Science, INFORMS, vol. 68(3), pages 1756-1775, March.
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