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The impact of aggregation level on forecasting performance

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  1. Florian Dandl & Michael Hyland & Klaus Bogenberger & Hani S. Mahmassani, 2019. "Evaluating the impact of spatio-temporal demand forecast aggregation on the operational performance of shared autonomous mobility fleets," Transportation, Springer, vol. 46(6), pages 1975-1996, December.
  2. Babai, Zied & Boylan, John E. & Kolassa, Stephan & Nikolopoulos, Konstantinos, 2016. "Supply chain forecasting: Theory, practice, their gap and the futureAuthor-Name: Syntetos, Aris A," European Journal of Operational Research, Elsevier, vol. 252(1), pages 1-26.
  3. Madhavi Latha Challa & Venkataramanaiah Malepati & Siva Nageswara Rao Kolusu, 2020. "S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.
  4. Spiliotis, Evangelos & Makridakis, Spyros & Kaltsounis, Anastasios & Assimakopoulos, Vassilios, 2021. "Product sales probabilistic forecasting: An empirical evaluation using the M5 competition data," International Journal of Production Economics, Elsevier, vol. 240(C).
  5. Marle, Franck & Vidal, Ludovic-Alexandre & Bocquet, Jean-Claude, 2013. "Interactions-based risk clustering methodologies and algorithms for complex project management," International Journal of Production Economics, Elsevier, vol. 142(2), pages 225-234.
  6. Spiliotis, Evangelos & Petropoulos, Fotios & Kourentzes, Nikolaos & Assimakopoulos, Vassilios, 2018. "Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption," MPRA Paper 91762, University Library of Munich, Germany.
  7. Moon, Seongmin & Hicks, Christian & Simpson, Andrew, 2012. "The development of a hierarchical forecasting method for predicting spare parts demand in the South Korean Navy—A case study," International Journal of Production Economics, Elsevier, vol. 140(2), pages 794-802.
  8. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael & Önkal, Dilek, 2019. "Judgmental adjustments through supply integration for strategic partnerships in food chains," Omega, Elsevier, vol. 87(C), pages 20-33.
  9. Rostami-Tabar, Bahman & Babai, Mohamed Zied & Ducq, Yves & Syntetos, Aris, 2015. "Non-stationary demand forecasting by cross-sectional aggregation," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 297-309.
  10. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
  11. Mohammad Shakeri & Jagadeesh Pasupuleti & Nowshad Amin & Md. Rokonuzzaman & Foo Wah Low & Chong Tak Yaw & Nilofar Asim & Nurul Asma Samsudin & Sieh Kiong Tiong & Chong Kok Hen & Chin Wei Lai, 2020. "An Overview of the Building Energy Management System Considering the Demand Response Programs, Smart Strategies and Smart Grid," Energies, MDPI, vol. 13(13), pages 1-15, June.
  12. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael, 2014. "Collaborative forecasting in the food supply chain: A conceptual framework," International Journal of Production Economics, Elsevier, vol. 158(C), pages 120-135.
  13. Babai, M. Zied & Ali, Mohammad M. & Nikolopoulos, Konstantinos, 2012. "Impact of temporal aggregation on stock control performance of intermittent demand estimators: Empirical analysis," Omega, Elsevier, vol. 40(6), pages 713-721.
  14. Chang, Suk-Gwon, 2015. "A structured scenario approach to multi-screen ecosystem forecasting in Korean communications market," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 1-20.
  15. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2019. "Retail forecasting: research and practice," MPRA Paper 89356, University Library of Munich, Germany.
  16. Ma, Shaohui & Fildes, Robert, 2020. "Forecasting third-party mobile payments with implications for customer flow prediction," International Journal of Forecasting, Elsevier, vol. 36(3), pages 739-760.
  17. Arunraj, Nari Sivanandam & Ahrens, Diane, 2015. "A hybrid seasonal autoregressive integrated moving average and quantile regression for daily food sales forecasting," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 321-335.
  18. Spiliotis, Evangelos & Petropoulos, Fotios & Kourentzes, Nikolaos & Assimakopoulos, Vassilios, 2020. "Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption," Applied Energy, Elsevier, vol. 261(C).
  19. Zotteri, Giulio & Kalchschmidt, Matteo, 2007. "Forecasting practices: Empirical evidence and a framework for research," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 84-99, July.
  20. Sbrana, Giacomo & Silvestrini, Andrea, 2013. "Forecasting aggregate demand: Analytical comparison of top-down and bottom-up approaches in a multivariate exponential smoothing framework," International Journal of Production Economics, Elsevier, vol. 146(1), pages 185-198.
  21. Kourentzes, Nikolaos & Petropoulos, Fotios, 2016. "Forecasting with multivariate temporal aggregation: The case of promotional modelling," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 145-153.
  22. Chen, Argon & Blue, Jakey, 2010. "Performance analysis of demand planning approaches for aggregating, forecasting and disaggregating interrelated demands," International Journal of Production Economics, Elsevier, vol. 128(2), pages 586-602, December.
  23. Shin-Lian Lo & Fu-Kwun Wang & James T. Lin, 2008. "Forecasting for the LCD monitor market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 341-356.
  24. Sali, Mustapha & Ghrab, Yahya & Chatras, Clément, 2023. "Optimal product aggregation for sales and operations planning in mass customisation context," International Journal of Production Economics, Elsevier, vol. 263(C).
  25. Michael R. Johnson & Hiten Naik & Wei Siang Chan & Jesse Greiner & Matt Michaleski & Dong Liu & Bruno Silvestre & Ian P. McCarthy, 2023. "Forecasting ward-level bed requirements to aid pandemic resource planning: Lessons learned and future directions," Health Care Management Science, Springer, vol. 26(3), pages 477-500, September.
  26. Wolters, Jannik & Huchzermeier, Arnd, 2021. "Joint In-Season and Out-of-Season Promotion Demand Forecasting in a Retail Environment," Journal of Retailing, Elsevier, vol. 97(4), pages 726-745.
  27. Zotteri, Giulio & Kalchschmidt, Matteo, 2007. "A model for selecting the appropriate level of aggregation in forecasting processes," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 74-83, July.
  28. Franck Marle & Hadi Jaber & Catherine Pointurier, 2019. "Organizing Project Actors for Collective Decision-Making about Interdependent Risks," Complexity, Hindawi, vol. 2019, pages 1-18, March.
  29. George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Anastasios Panagiotelis, 2023. "Forecast Reconciliation: A Review," Monash Econometrics and Business Statistics Working Papers 8/23, Monash University, Department of Econometrics and Business Statistics.
  30. Hakeem‐Ur Rehman & Guohua Wan & Raza Rafique, 2023. "A hybrid approach with step‐size aggregation to forecasting hierarchical time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 176-192, January.
  31. Haberleitner, Helmut & Meyr, Herbert & Taudes, Alfred, 2010. "Implementation of a demand planning system using advance order information," International Journal of Production Economics, Elsevier, vol. 128(2), pages 518-526, December.
  32. Poloni, Federico & Sbrana, Giacomo, 2015. "A note on forecasting demand using the multivariate exponential smoothing framework," International Journal of Production Economics, Elsevier, vol. 162(C), pages 143-150.
  33. Huber, Jakob & Stuckenschmidt, Heiner, 2021. "Intraday shelf replenishment decision support for perishable goods," International Journal of Production Economics, Elsevier, vol. 231(C).
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