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Supply chain forecasting when information is not shared

Citations

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Cited by:

  1. Yaniv Proselkov & Liming Xu & Alexandra Brintrup, 2026. "Modelling viable supply networks with cooperative adaptive financing," Papers 2601.13210, arXiv.org.
  2. Nassim Ghondaghsaz & Zarina Chokparova & Sven Engesser & Leon Urbas, 2022. "Managing the Tension between Trust and Confidentiality in Mobile Supply Chains," Sustainability, MDPI, vol. 14(4), pages 1-25, February.
  3. Roberto Dominguez & Salvatore Cannella & Borja Ponte & Jose M. Framinan, 2022. "Information sharing in decentralised supply chains with partial collaboration," Flexible Services and Manufacturing Journal, Springer, vol. 34(2), pages 263-292, June.
  4. Corey Ducharme & Bruno Agard & Martin Trépanier, 2024. "Improving demand forecasting for customers with missing downstream data in intermittent demand supply chains with supervised multivariate clustering," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1661-1681, August.
  5. Halina Brdulak & Anna Brdulak, 2021. "Challenges and Threats Faced in 2020 by International Logistics Companies Operating on the Polish Market," Sustainability, MDPI, vol. 13(1), pages 1-18, January.
  6. Rajaguru, Rajesh & Matanda, Margaret Jekanyika & Verma, Prikshat, 2023. "Information system integration, forecast information quality and market responsiveness: Role of socio-technical congruence," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
  7. Kang, Yanfei & Cao, Wei & Petropoulos, Fotios & Li, Feng, 2022. "Forecast with forecasts: Diversity matters," European Journal of Operational Research, Elsevier, vol. 301(1), pages 180-190.
  8. Mishra, Abhinay & Kundu, Tanmoy & Kapoor, Rohit & Goh, Mark, 2025. "Blockchain adoption in cross-border cold supply chains: Cost, Efficiency and Trust," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 201(C).
  9. Regina Frei & Lisa Jack & Sally‐Ann Krzyzaniak, 2020. "Sustainable reverse supply chains and circular economy in multichannel retail returns," Business Strategy and the Environment, Wiley Blackwell, vol. 29(5), pages 1925-1940, July.
  10. Dominguez, Roberto & Cannella, Salvatore & Barbosa-Póvoa, Ana P. & Framinan, Jose M., 2018. "Information sharing in supply chains with heterogeneous retailers," Omega, Elsevier, vol. 79(C), pages 116-132.
  11. Youssef Tliche & Atour Taghipour & Jomana Mahfod-Leroux & Mohammadali Vosooghidizaji, 2023. "Collaborative Bullwhip Effect-Oriented Bi-Objective Optimization for Inference-Based Weighted Moving Average Forecasting in Decentralized Supply Chain," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global Scientific Publishing, vol. 16(1), pages 1-37, January.
  12. Tliche, Y. & Taghipour, A. & Canel-Depitre, B., 2019. "Downstream Demand Inference in decentralized supply chains," European Journal of Operational Research, Elsevier, vol. 274(1), pages 65-77.
  13. Claire Y. T. Chen & Edward W. Sun & Ming-Feng Chang & Yi-Bing Lin, 2024. "Enhancing travel time prediction with deep learning on chronological and retrospective time order information of big traffic data," Annals of Operations Research, Springer, vol. 343(3), pages 1095-1128, December.
  14. Kogler, Christoph & Beiglböck, Alexander & Rauch, Peter, 2025. "An empirical study of the resilience in Austrian wood transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 191(C).
  15. Youssef Tliche & Atour Taghipour & Jomana Mahfod-Leroux & Mohammadali Vosooghidizaji, 2023. "Collaborative Bullwhip Effect-Oriented Bi-Objective Optimization for Inference-Based Weighted Moving Average Forecasting in Decentralized Supply Chain," Post-Print hal-04298705, HAL.
  16. Lu, Jizhou & Feng, Gengzhong & Shum, Stephen & Lai, Kin Keung, 2021. "On the value of information sharing in the presence of information errors," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1139-1152.
  17. Tliche, Youssef & Taghipour, Atour & Canel-Depitre, Béatrice, 2020. "An improved forecasting approach to reduce inventory levels in decentralized supply chains," European Journal of Operational Research, Elsevier, vol. 287(2), pages 511-527.
  18. Liu, Hao & Jiang, Wei & Feng, Gengzhong & Chin, Kwai-Sang, 2020. "Information leakage and supply chain contracts," Omega, Elsevier, vol. 90(C).
  19. Ducharme, Corey & Agard, Bruno & Trépanier, Martin, 2021. "Forecasting a customer's Next Time Under Safety Stock," International Journal of Production Economics, Elsevier, vol. 234(C).
  20. Wang, Jiao & Liu, Zhibing & Zhao, Ruiqing, 2019. "On the interaction between asymmetric demand signal and forecast accuracy information," European Journal of Operational Research, Elsevier, vol. 277(3), pages 857-874.
  21. Hosoda, Takamichi & Disney, Stephen M., 2018. "A unified theory of the dynamics of closed-loop supply chains," European Journal of Operational Research, Elsevier, vol. 269(1), pages 313-326.
  22. Hosoda, Takamichi & Disney, Stephen M. & Zhou, Li, 2021. "The yield rate paradox in closed-loop supply chains," International Journal of Production Economics, Elsevier, vol. 239(C).
  23. Schlaich, Tim & Hoberg, Kai, 2024. "When is the next order? Nowcasting channel inventories with Point-of-Sales data to predict the timing of retail orders," European Journal of Operational Research, Elsevier, vol. 315(1), pages 35-49.
  24. An, Min Jeong & Jung, Seung Hwan & Lee, Dong Hee, 2025. "Demand forecasting in micro-fulfillment centers using association rule-based machine learning," International Journal of Production Economics, Elsevier, vol. 290(C).
  25. Guojun Ji & Muhong Yu & Kim Hua Tan & Ajay Kumar & Shivam Gupta, 2024. "Decision optimization in cooperation innovation: the impact of big data analytics capability and cooperative modes," Annals of Operations Research, Springer, vol. 333(2), pages 871-894, February.
  26. Dominguez, Roberto & Cannella, Salvatore & Barbosa-Póvoa, Ana P. & Framinan, Jose M., 2018. "OVAP: A strategy to implement partial information sharing among supply chain retailers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 122-136.
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