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Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts

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Cited by:

  1. Barrow, Devon & Kourentzes, Nikolaos, 2018. "The impact of special days in call arrivals forecasting: A neural network approach to modelling special days," European Journal of Operational Research, Elsevier, vol. 264(3), pages 967-977.
  2. Salinas, David & Flunkert, Valentin & Gasthaus, Jan & Januschowski, Tim, 2020. "DeepAR: Probabilistic forecasting with autoregressive recurrent networks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1181-1191.
  3. Mohsen Sadegh Amalnick & Naser Habibifar & Mahdi Hamid & Mahdi Bastan, 2020. "An intelligent algorithm for final product demand forecasting in pharmaceutical units," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 481-493, April.
  4. Ulrich, Matthias & Jahnke, Hermann & Langrock, Roland & Pesch, Robert & Senge, Robin, 2022. "Classification-based model selection in retail demand forecasting," International Journal of Forecasting, Elsevier, vol. 38(1), pages 209-223.
  5. Svetunkov, Ivan & Chen, Huijing & Boylan, John E., 2023. "A new taxonomy for vector exponential smoothing and its application to seasonal time series," European Journal of Operational Research, Elsevier, vol. 304(3), pages 964-980.
  6. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
  7. Meeran, Sheik & Jahanbin, Semco & Goodwin, Paul & Quariguasi Frota Neto, Joao, 2017. "When do changes in consumer preferences make forecasts from choice-based conjoint models unreliable?," European Journal of Operational Research, Elsevier, vol. 258(2), pages 512-524.
  8. Pritularga, Kandrika F. & Svetunkov, Ivan & Kourentzes, Nikolaos, 2021. "Stochastic coherency in forecast reconciliation," International Journal of Production Economics, Elsevier, vol. 240(C).
  9. Kourentzes, Nikolaos & Athanasopoulos, George, 2019. "Cross-temporal coherent forecasts for Australian tourism," Annals of Tourism Research, Elsevier, vol. 75(C), pages 393-409.
  10. Ma, Shaohui & Fildes, Robert, 2021. "Retail sales forecasting with meta-learning," European Journal of Operational Research, Elsevier, vol. 288(1), pages 111-128.
  11. Villegas, Marco A. & Pedregal, Diego J., 2019. "Automatic selection of unobserved components models for supply chain forecasting," International Journal of Forecasting, Elsevier, vol. 35(1), pages 157-169.
  12. Athanasopoulos, George & Hyndman, Rob J. & Kourentzes, Nikolaos & Petropoulos, Fotios, 2017. "Forecasting with temporal hierarchies," European Journal of Operational Research, Elsevier, vol. 262(1), pages 60-74.
  13. Kourentzes, Nikolaos & Athanasopoulos, George, 2021. "Elucidate structure in intermittent demand series," European Journal of Operational Research, Elsevier, vol. 288(1), pages 141-152.
  14. Di Fonzo, Tommaso & Girolimetto, Daniele, 2024. "Forecast combination-based forecast reconciliation: Insights and extensions," International Journal of Forecasting, Elsevier, vol. 40(2), pages 490-514.
  15. Philippe St-Aubin & Bruno Agard, 2022. "Precision and Reliability of Forecasts Performance Metrics," Forecasting, MDPI, vol. 4(4), pages 1-22, October.
  16. Sagaert, Yves R. & Kourentzes, Nikolaos & De Vuyst, Stijn & Aghezzaf, El-Houssaine & Desmet, Bram, 2019. "Incorporating macroeconomic leading indicators in tactical capacity planning," International Journal of Production Economics, Elsevier, vol. 209(C), pages 12-19.
  17. 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.
  18. Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
  19. Vilkkumaa, Eeva & Liesiö, Juuso, 2022. "What causes post-decision disappointment? Estimating the contributions of systematic and selection biases," European Journal of Operational Research, Elsevier, vol. 296(2), pages 587-600.
  20. Victor Richmond R. Jose, 2017. "Percentage and Relative Error Measures in Forecast Evaluation," Operations Research, INFORMS, vol. 65(1), pages 200-211, February.
  21. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
  22. Aysun Kapucugil Ikiz & Gizem Halil Utma, 2023. "Combined Forecasts of Intermittent Demand for Stock-keeping Units (SKUs)," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 9(1), pages 1-31, June.
  23. Belvedere, Valeria & Goodwin, Paul, 2017. "The influence of product involvement and emotion on short-term product demand forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 652-661.
  24. Ma, Shaohui & Fildes, Robert, 2017. "A retail store SKU promotions optimization model for category multi-period profit maximization," European Journal of Operational Research, Elsevier, vol. 260(2), pages 680-692.
  25. Gür Ali, Özden & Gürlek, Ragıp, 2020. "Automatic Interpretable Retail forecasting with promotional scenarios," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1389-1406.
  26. Ana Caroline Pinheiro & Paulo Canas Rodrigues, 2024. "Hierarchical Time Series Forecasting of Fire Spots in Brazil: A Comprehensive Approach," Stats, MDPI, vol. 7(3), pages 1-24, June.
  27. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
  28. Sroginis, Anna & Fildes, Robert & Kourentzes, Nikolaos, 2023. "Use of contextual and model-based information in adjusting promotional forecasts," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1177-1191.
  29. Hartzel, Kathleen S. & Wood, Charles A., 2017. "Factors that affect the improvement of demand forecast accuracy through point-of-sale reporting," European Journal of Operational Research, Elsevier, vol. 260(1), pages 171-182.
  30. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2019. "Retail forecasting: research and practice," MPRA Paper 89356, University Library of Munich, Germany.
  31. Victor Richmond R. Jose, 2017. "Percentage and Relative Error Measures in Forecast Evaluation," Operations Research, INFORMS, vol. 65(1), pages 200-211, February.
  32. Fildes, Robert & Petropoulos, Fotios, 2015. "Is there a Golden Rule?," Journal of Business Research, Elsevier, vol. 68(8), pages 1742-1745.
  33. Abolghasemi, Mahdi & Hurley, Jason & Eshragh, Ali & Fahimnia, Behnam, 2020. "Demand forecasting in the presence of systematic events: Cases in capturing sales promotions," International Journal of Production Economics, Elsevier, vol. 230(C).
  34. Fildes, Robert & Petropoulos, Fotios, 2015. "Simple versus complex selection rules for forecasting many time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1692-1701.
  35. Kshitij Sharma & Yogesh K. Dwivedi & Bhimaraya Metri, 2024. "Incorporating causality in energy consumption forecasting using deep neural networks," Annals of Operations Research, Springer, vol. 339(1), pages 537-572, August.
  36. Fildes, Robert & Petropoulos, Fotios, 2013. "An evaluation of simple forecasting model selection rules," MPRA Paper 51772, University Library of Munich, Germany.
  37. 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.
  38. Larissa Koupriouchina & Jean-Pierre van der Rest & Zvi Schwartz, 2023. "Judgmental Adjustments of Algorithmic Hotel Occupancy Forecasts: Does User Override Frequency Impact Accuracy at Different Time Horizons?," Tourism Economics, , vol. 29(8), pages 2143-2164, December.
  39. 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.
  40. Ma, Shaohui & Fildes, Robert & Huang, Tao, 2016. "Demand forecasting with high dimensional data: The case of SKU retail sales forecasting with intra- and inter-category promotional information," European Journal of Operational Research, Elsevier, vol. 249(1), pages 245-257.
  41. 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).
  42. Emrouznejad, Ali & Rostami-Tabar, Bahman & Petridis, Konstantinos, 2016. "A novel ranking procedure for forecasting approaches using Data Envelopment Analysis," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 235-243.
  43. Li, W. & Fok, D. & Franses, Ph.H.B.F., 2019. "Forecasting own brand sales: Does incorporating competition help?," Econometric Institute Research Papers EI2019-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  44. Philip Hans Franses, 2021. "Modeling Judgment in Macroeconomic Forecasts," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 401-417, December.
  45. Jože Rožanec & Elena Trajkova & Inna Novalija & Patrik Zajec & Klemen Kenda & Blaž Fortuna & Dunja Mladenić, 2022. "Enriching Artificial Intelligence Explanations with Knowledge Fragments," Future Internet, MDPI, vol. 14(5), pages 1-13, April.
  46. Yinuo Xu & Chunxiao Zhang & Wei Hou, 2022. "Modeling of Daytime and Nighttime Surface Urban Heat Island Distribution Combined with LCZ in Beijing, China," Land, MDPI, vol. 11(11), pages 1-21, November.
  47. Khosrowabadi, Naghmeh & Hoberg, Kai & Imdahl, Christina, 2022. "Evaluating human behaviour in response to AI recommendations for judgemental forecasting," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1151-1167.
  48. Athanasopoulos, George & Kourentzes, Nikolaos, 2023. "On the evaluation of hierarchical forecasts," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1502-1511.
  49. 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.
  50. Costa, Marcelo Azevedo & Ruiz-Cárdenas, Ramiro & Mineti, Leandro Brioschi & Prates, Marcos Oliveira, 2021. "Dynamic time scan forecasting for multi-step wind speed prediction," Renewable Energy, Elsevier, vol. 177(C), pages 584-595.
  51. Wan, Xiang & Sanders, Nadia R., 2017. "The negative impact of product variety: Forecast bias, inventory levels, and the role of vertical integration," International Journal of Production Economics, Elsevier, vol. 186(C), pages 123-131.
  52. repec:wrk:wrkemf:33 is not listed on IDEAS
  53. Van Belle, Jente & Guns, Tias & Verbeke, Wouter, 2021. "Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains," European Journal of Operational Research, Elsevier, vol. 288(2), pages 466-479.
  54. Fildes, Robert & Goodwin, Paul & Önkal, Dilek, 2019. "Use and misuse of information in supply chain forecasting of promotion effects," International Journal of Forecasting, Elsevier, vol. 35(1), pages 144-156.
  55. Van den Broeke, Maud & De Baets, Shari & Vereecke, Ann & Baecke, Philippe & Vanderheyden, Karlien, 2019. "Judgmental forecast adjustments over different time horizons," Omega, Elsevier, vol. 87(C), pages 34-45.
  56. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
  57. Huang, Tao & Fildes, Robert & Soopramanien, Didier, 2014. "The value of competitive information in forecasting FMCG retail product sales and the variable selection problem," European Journal of Operational Research, Elsevier, vol. 237(2), pages 738-748.
  58. Kourentzes, Nikolaos & Barrow, Devon & Petropoulos, Fotios, 2019. "Another look at forecast selection and combination: Evidence from forecast pooling," International Journal of Production Economics, Elsevier, vol. 209(C), pages 226-235.
  59. Evangelos Spiliotis & Spyros Makridakis & Artemios-Anargyros Semenoglou & Vassilios Assimakopoulos, 2022. "Comparison of statistical and machine learning methods for daily SKU demand forecasting," Operational Research, Springer, vol. 22(3), pages 3037-3061, July.
  60. Fildes, Robert & Goodwin, Paul, 2021. "Stability in the inefficient use of forecasting systems: A case study in a supply chain company," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1031-1046.
  61. Huang, Tao & Fildes, Robert & Soopramanien, Didier, 2019. "Forecasting retailer product sales in the presence of structural change," European Journal of Operational Research, Elsevier, vol. 279(2), pages 459-470.
  62. Ji Wu & Xian Cheng & Stephen Shaoyi Liao, 2020. "Tourism forecast combination using the stochastic frontier analysis technique," Tourism Economics, , vol. 26(7), pages 1086-1107, November.
  63. Sasan Barak & Navid Parvini, 2023. "Transfer‐entropy‐based dynamic feature selection for evaluating Bitcoin price drivers," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(12), pages 1695-1726, December.
  64. Bentour, El Mostafa, 2015. "A ranking of VAR and structural models in forecasting," MPRA Paper 61502, University Library of Munich, Germany.
  65. George Athanasopoulos & Nikolaos Kourentzes, 2021. "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers 10/21, Monash University, Department of Econometrics and Business Statistics.
  66. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2022. "M5 accuracy competition: Results, findings, and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1346-1364.
  67. Ulrich, Matthias & Jahnke, Hermann & Langrock, Roland & Pesch, Robert & Senge, Robin, 2021. "Distributional regression for demand forecasting in e-grocery," European Journal of Operational Research, Elsevier, vol. 294(3), pages 831-842.
  68. Petropoulos, Fotios & Fildes, Robert & Goodwin, Paul, 2016. "Do ‘big losses’ in judgmental adjustments to statistical forecasts affect experts’ behaviour?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 842-852.
  69. George Athanasopoulos & Nikolaos Kourentzes, 2020. "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers 2/20, Monash University, Department of Econometrics and Business Statistics.
  70. Di Fonzo, Tommaso & Girolimetto, Daniele, 2023. "Cross-temporal forecast reconciliation: Optimal combination method and heuristic alternatives," International Journal of Forecasting, Elsevier, vol. 39(1), pages 39-57.
  71. Spiliotis, Evangelos & Nikolopoulos, Konstantinos & Assimakopoulos, Vassilios, 2019. "Tales from tails: On the empirical distributions of forecasting errors and their implication to risk," International Journal of Forecasting, Elsevier, vol. 35(2), pages 687-698.
  72. Ye, Lili & Xie, Naiming & Boylan, John E. & Shang, Zhongju, 2024. "Forecasting seasonal demand for retail: A Fourier time-varying grey model," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1467-1485.
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