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Inventory – forecasting: Mind the gap

Author

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  • Goltsos, T. .E.
  • Syntetos, A.
  • Glock, C. H.
  • Ioannou, G.

Abstract

No abstract is available for this item.

Suggested Citation

  • Goltsos, T. .E. & Syntetos, A. & Glock, C. H. & Ioannou, G., 2022. "Inventory – forecasting: Mind the gap," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 131494, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    • Handle: RePEc:dar:wpaper:131494
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/131494/
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    Citations

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    Cited by:

    1. Alexandra Birkmaier & Adhurim Imeri & Gerald Reiner, 2024. "Improving supply chain planning for perishable food: data-driven implications for waste prevention," Journal of Business Economics, Springer, vol. 94(6), pages 1-36, August.
    2. Lotte Hezewijk & Nico P. Dellaert & Willem L. Jaarsveld, 2025. "On non-negative auto-correlated integer demand processes," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 101(2), pages 135-161, April.
    3. Bergsma, Ritsaart & de Ruijt, Corné & Bhulai, Sandjai, 2025. "A systematic review of machine learning approaches in inventory control optimization," Operations Research Perspectives, Elsevier, vol. 15(C).
    4. Huosong Xia & Xiaoyu Hou & Justin Zuopeng Zhang & Mohammad Zoynul Abedin, 2025. "A new probability forecasting model for cotton yarn futures price volatility with explainable AI and big data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(1), pages 112-135, January.
    5. 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.
    6. Chen, Shan & Zhu, Meizhen & Han, Shuihua & Gupta, Shivam, 2026. "A deep fusion framework for end-to-end multi-product inventory optimization in e-commerce scenarios," International Journal of Production Economics, Elsevier, vol. 291(C).
    7. Bhavik Bharambe & Nishant Patil & Naman Kothari & Sandip Shingade & Sushila Shingade, 2026. "Efficient Supply Chains in Agriculture Through Cluster-Based Route Optimization," SN Operations Research Forum, Springer, vol. 7(1), pages 1-31, March.
    8. Joren Gijsbrechts & Heletjé Emily Van Staden, 2025. "Game—Where Did the Demand Go? Teaching Demand Censoring with the Newsvendor Challenge," INFORMS Transactions on Education, INFORMS, vol. 25(3), pages 257-264, May.
    9. De Bock, Koen W. & Coussement, Kristof & Caigny, Arno De & Słowiński, Roman & Baesens, Bart & Boute, Robert N. & Choi, Tsan-Ming & Delen, Dursun & Kraus, Mathias & Lessmann, Stefan & Maldonado, Sebast, 2024. "Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda," European Journal of Operational Research, Elsevier, vol. 317(2), pages 249-272.
    10. Motamedi, Maryam & Li, Na & Down, Douglas G., 2026. "Optimal ordering policy for perishable products by incorporating demand forecasts," European Journal of Operational Research, Elsevier, vol. 329(1), pages 124-137.
    11. Saravanan Kesavan & Tarun Kushwaha & Dayton Steele, 2026. "Profit Implications of Judgmental Adjustments to Forecast Inputs: Evidence from a Large-Scale Field Experiment," Management Science, INFORMS, vol. 72(1), pages 119-127, January.

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