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On the bias of intermittent demand estimates

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Cited by:

  1. Saskia Puspa Kenaka & Andi Cakravastia & Anas Ma’ruf & Rully Tri Cahyono, 2025. "Enhancing Intermittent Spare Part Demand Forecasting: A Novel Ensemble Approach with Focal Loss and SMOTE," Logistics, MDPI, vol. 9(1), pages 1-25, February.
  2. A A Syntetos & J E Boylan & J D Croston, 2005. "On the categorization of demand patterns," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(5), pages 495-503, May.
  3. A A Syntetos & J E Boylan & S M Disney, 2009. "Forecasting for inventory planning: a 50-year review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 149-160, May.
  4. Rob J. Hyndman & Lydia Shenstone, 2005. "Stochastic models underlying Croston's method for intermittent demand forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(6), pages 389-402.
  5. Mariusz Doszyn, 2020. "Accuracy of Intermittent Demand Forecasting Systems in the Enterprise," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 912-930.
  6. Wallström, Peter & Segerstedt, Anders, 2010. "Evaluation of forecasting error measurements and techniques for intermittent demand," International Journal of Production Economics, Elsevier, vol. 128(2), pages 625-636, December.
  7. Romeijnders, Ward & Teunter, Ruud & van Jaarsveld, Willem, 2012. "A two-step method for forecasting spare parts demand using information on component repairs," European Journal of Operational Research, Elsevier, vol. 220(2), pages 386-393.
  8. 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.
  9. Kourentzes, Nikolaos & Athanasopoulos, George, 2021. "Elucidate structure in intermittent demand series," European Journal of Operational Research, Elsevier, vol. 288(1), pages 141-152.
  10. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  11. Aiping Jiang & Qiuguo Chi & Junjun Gao & Maoguo Wu, 2019. "An Integrated Approach to Forecasting Intermittent Demand for Electric Power Materials," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1309-1335, April.
  12. van Wingerden, E. & Basten, R.J.I. & Dekker, R. & Rustenburg, W.D., 2014. "More grip on inventory control through improved forecasting: A comparative study at three companies," International Journal of Production Economics, Elsevier, vol. 157(C), pages 220-237.
  13. Kourentzes, Nikolaos, 2014. "On intermittent demand model optimisation and selection," International Journal of Production Economics, Elsevier, vol. 156(C), pages 180-190.
  14. R García-Flores & X Z Wang & T F Burgess, 2003. "Tuning inventory policy parameters in a small chemical company," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(4), pages 350-361, April.
  15. Lindsey, Matthew & Pavur, Robert, 2009. "Prediction intervals for future demand of existing products with an observed demand of zero," International Journal of Production Economics, Elsevier, vol. 119(1), pages 75-89, May.
  16. 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.
  17. Van der Auweraer, Sarah & Boute, Robert N. & Syntetos, Aris A., 2019. "Forecasting spare part demand with installed base information: A review," International Journal of Forecasting, Elsevier, vol. 35(1), pages 181-196.
  18. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2019. "Retail forecasting: research and practice," MPRA Paper 89356, University Library of Munich, Germany.
  19. Kostas Nikolopoulos & F. Petropoulos, 2015. "Forecasting, Foresight and Strategic Planning for Black Swans," Working Papers 15003, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
  20. Li, Chongshou & Lim, Andrew, 2018. "A greedy aggregation–decomposition method for intermittent demand forecasting in fashion retailing," European Journal of Operational Research, Elsevier, vol. 269(3), pages 860-869.
  21. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
  22. Nikolopoulos, Konstantinos I. & Babai, M. Zied & Bozos, Konstantinos, 2016. "Forecasting supply chain sporadic demand with nearest neighbor approaches," International Journal of Production Economics, Elsevier, vol. 177(C), pages 139-148.
  23. Syntetos, Aris A. & Boylan, John E., 2006. "On the stock control performance of intermittent demand estimators," International Journal of Production Economics, Elsevier, vol. 103(1), pages 36-47, September.
  24. Prak, Dennis & Rogetzer, Patricia, 2022. "Timing intermittent demand with time-varying order-up-to levels," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1126-1136.
  25. Syntetos, Aris A. & Zied Babai, M. & Gardner, Everette S., 2015. "Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping," Journal of Business Research, Elsevier, vol. 68(8), pages 1746-1752.
  26. Heinecke, G. & Syntetos, A.A. & Wang, W., 2013. "Forecasting-based SKU classification," International Journal of Production Economics, Elsevier, vol. 143(2), pages 455-462.
  27. F R Johnston & E A Shale & S Kapoor & R True & A Sheth, 2011. "Breadth of range and depth of stock: forecasting and inventory management at Euro Car Parts Ltd," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 433-441, March.
  28. Muñoz Negrón, David F. & Muñoz Medina, Diego F., 2009. "Bayesian Forecastings For Automobile Parts Using Stochastic Simulation," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 14(27), pages 7-20.
  29. Houxiang Wang & Haitao Liu & Songshi Shao & Zhihua Zhang, 2024. "Methodology of Shipboard Spare Parts Requirements Based on Whole Part Repair Strategy," Mathematics, MDPI, vol. 12(19), pages 1-25, September.
  30. A A Syntetos & M Z Babai & Y Dallery & R Teunter, 2009. "Periodic control of intermittent demand items: theory and empirical analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(5), pages 611-618, May.
  31. Prak, Dennis & Teunter, Ruud & Babai, Mohamed Zied & Boylan, John E. & Syntetos, Aris, 2021. "Robust compound Poisson parameter estimation for inventory control," Omega, Elsevier, vol. 104(C).
  32. Ye, Yuan & Lu, Yonggang & Robinson, Powell & Narayanan, Arunachalam, 2022. "An empirical Bayes approach to incorporating demand intermittency and irregularity into inventory control," European Journal of Operational Research, Elsevier, vol. 303(1), pages 255-272.
  33. Price, Ilan & Fowkes, Jaroslav & Hopman, Daniel, 2019. "Gaussian processes for unconstraining demand," European Journal of Operational Research, Elsevier, vol. 275(2), pages 621-634.
  34. Theodorou, Evangelos & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2025. "Forecast accuracy and inventory performance: Insights on their relationship from the M5 competition data," European Journal of Operational Research, Elsevier, vol. 322(2), pages 414-426.
  35. Boylan, John E. & Babai, M. Zied, 2016. "On the performance of overlapping and non-overlapping temporal demand aggregation approaches," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 136-144.
  36. Zied Babai, M. & Syntetos, Aris A. & Teunter, Ruud, 2010. "On the empirical performance of (T, s, S) heuristics," European Journal of Operational Research, Elsevier, vol. 202(2), pages 466-472, April.
  37. Syntetos, Aris A. & Boylan, John E., 2010. "On the variance of intermittent demand estimates," International Journal of Production Economics, Elsevier, vol. 128(2), pages 546-555, December.
  38. Ciancimino, Elena & Cannella, Salvatore & Canca Ortiz, José David & Framiñán Torres, José Manuel, 2009. "Análisis multinivel de cadenas de suministros: dos técnicas de resolución del efecto bullwhip // Supply Chain Multi-level Analysis: Two Bullwhip Dampening Approaches," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 8(1), pages 7-28, December.
  39. Zhou, Chenxi & Viswanathan, S., 2011. "Comparison of a new bootstrapping method with parametric approaches for safety stock determination in service parts inventory systems," International Journal of Production Economics, Elsevier, vol. 133(1), pages 481-485, September.
  40. Zied Babai, Mohamed & Syntetos, Aris & Teunter, Ruud, 2014. "Intermittent demand forecasting: An empirical study on accuracy and the risk of obsolescence," International Journal of Production Economics, Elsevier, vol. 157(C), pages 212-219.
  41. J E Boylan & A A Syntetos & G C Karakostas, 2008. "Classification for forecasting and stock control: a case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(4), pages 473-481, April.
  42. Tratar, Liljana Ferbar, 2010. "Joint optimisation of demand forecasting and stock control parameters," International Journal of Production Economics, Elsevier, vol. 127(1), pages 173-179, September.
  43. Kamal Sanguri & Kampan Mukherjee, 2021. "Forecasting of intermittent demands under the risk of inventory obsolescence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1054-1069, September.
  44. Teunter, Ruud H. & Syntetos, Aris A. & Zied Babai, M., 2011. "Intermittent demand: Linking forecasting to inventory obsolescence," European Journal of Operational Research, Elsevier, vol. 214(3), pages 606-615, November.
  45. Nikolaos Kourentzes & Dong Li & Arne K. Strauss, 2019. "Unconstraining methods for revenue management systems under small demand," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(1), pages 27-41, February.
  46. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
  47. G. Peter Zhang & Yusen Xia & Maohua Xie, 2024. "Intermittent demand forecasting with transformer neural networks," Annals of Operations Research, Springer, vol. 339(1), pages 1051-1072, August.
  48. Hu, Qiwei & Boylan, John E. & Chen, Huijing & Labib, Ashraf, 2018. "OR in spare parts management: A review," European Journal of Operational Research, Elsevier, vol. 266(2), pages 395-414.
  49. Tian, Xin & Wang, Haoqing & E, Erjiang, 2021. "Forecasting intermittent demand for inventory management by retailers: A new approach," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
  50. K Nikolopoulos & A A Syntetos & J E Boylan & F Petropoulos & V Assimakopoulos, 2011. "An aggregate–disaggregate intermittent demand approach (ADIDA) to forecasting: an empirical proposition and analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 544-554, March.
  51. Murphy Choy & Michelle L. F. Cheong, 2011. "Identification of Demand through Statistical Distribution Modeling for Improved Demand Forecasting," Papers 1110.0062, arXiv.org.
  52. Kourentzes, Nikolaos, 2013. "Intermittent demand forecasts with neural networks," International Journal of Production Economics, Elsevier, vol. 143(1), pages 198-206.
  53. Prak, Derk & Teunter, Rudolf & Babai, M. Z. & Syntetos, A. A. & Boylan, D, 2018. "Forecasting and Inventory Control with Compound Poisson Demand Using Periodic Demand Data," Research Report 2018010, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  54. Hasni, M. & Aguir, M.S. & Babai, M.Z. & Jemai, Z., 2019. "On the performance of adjusted bootstrapping methods for intermittent demand forecasting," International Journal of Production Economics, Elsevier, vol. 216(C), pages 145-153.
  55. 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.
  56. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
  57. Ali Caner Türkmen & Tim Januschowski & Yuyang Wang & Ali Taylan Cemgil, 2021. "Forecasting intermittent and sparse time series: A unified probabilistic framework via deep renewal processes," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-26, November.
  58. Zhu, Sha & Jaarsveld, Willem van & Dekker, Rommert, 2020. "Spare parts inventory control based on maintenance planning," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
  59. Gutierrez, Rafael S. & Solis, Adriano O. & Mukhopadhyay, Somnath, 2008. "Lumpy demand forecasting using neural networks," International Journal of Production Economics, Elsevier, vol. 111(2), pages 409-420, February.
  60. Pierre Dodin & Jingyi Xiao & Yossiri Adulyasak & Neda Etebari Alamdari & Lea Gauthier & Philippe Grangier & Paul Lemaitre & William L. Hamilton, 2023. "Bombardier Aftermarket Demand Forecast with Machine Learning," Interfaces, INFORMS, vol. 53(6), pages 425-445, November.
  61. Ferbar Tratar, Liljana & Mojškerc, Blaž & Toman, Aleš, 2016. "Demand forecasting with four-parameter exponential smoothing," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 162-173.
  62. Pennings, Clint L.P. & van Dalen, Jan & van der Laan, Erwin A., 2017. "Exploiting elapsed time for managing intermittent demand for spare parts," European Journal of Operational Research, Elsevier, vol. 258(3), pages 958-969.
  63. Pinçe, Çerağ & Turrini, Laura & Meissner, Joern, 2021. "Intermittent demand forecasting for spare parts: A Critical review," Omega, Elsevier, vol. 105(C).
  64. Svetunkov, Ivan & Boylan, John Edward, 2017. "Multiplicative state-space models for intermittent time series," MPRA Paper 82487, University Library of Munich, Germany.
  65. Jože Martin Rožanec & Blaž Fortuna & Dunja Mladenić, 2022. "Reframing Demand Forecasting: A Two-Fold Approach for Lumpy and Intermittent Demand," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
  66. Syntetos, Aris A. & Boylan, John E., 2005. "The accuracy of intermittent demand estimates," International Journal of Forecasting, Elsevier, vol. 21(2), pages 303-314.
  67. Babai, M.Z. & Dallery, Y. & Boubaker, S. & Kalai, R., 2019. "A new method to forecast intermittent demand in the presence of inventory obsolescence," International Journal of Production Economics, Elsevier, vol. 209(C), pages 30-41.
  68. Petropoulos, Fotios & Makridakis, Spyros & Assimakopoulos, Vassilios & Nikolopoulos, Konstantinos, 2014. "‘Horses for Courses’ in demand forecasting," European Journal of Operational Research, Elsevier, vol. 237(1), pages 152-163.
  69. Teunter, Ruud & Sani, Babangida, 2009. "On the bias of Croston's forecasting method," European Journal of Operational Research, Elsevier, vol. 194(1), pages 177-183, April.
  70. Lolli, F. & Gamberini, R. & Regattieri, A. & Balugani, E. & Gatos, T. & Gucci, S., 2017. "Single-hidden layer neural networks for forecasting intermittent demand," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 116-128.
  71. Leven, Erik & Segerstedt, Anders, 2004. "Inventory control with a modified Croston procedure and Erlang distribution," International Journal of Production Economics, Elsevier, vol. 90(3), pages 361-367, August.
  72. Aiping Jiang & Kwok Leung Tam & Xiaoyun Guo & Yufeng Zhang, 2020. "A new approach to forecasting intermittent demand based on the mixed zero‐truncated Poisson model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 69-83, January.
  73. Amniattalab, Ayda & Frenk, J.B.G. & Hekimoğlu, Mustafa, 2023. "On spare parts demand and the installed base concept: A theoretical approach," International Journal of Production Economics, Elsevier, vol. 266(C).
  74. R H Teunter & L Duncan, 2009. "Forecasting intermittent demand: a comparative study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(3), pages 321-329, March.
  75. A H C Eaves & B G Kingsman, 2004. "Forecasting for the ordering and stock-holding of spare parts," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(4), pages 431-437, April.
  76. Jakub Dyntar & Eva Kemrová & Ivan Gros, 2010. "Simulation approach in stock control of products with sporadic demand," Ekonomika a Management, Prague University of Economics and Business, vol. 2010(3).
  77. Zhu, Sha & Dekker, Rommert & van Jaarsveld, Willem & Renjie, Rex Wang & Koning, Alex J., 2017. "An improved method for forecasting spare parts demand using extreme value theory," European Journal of Operational Research, Elsevier, vol. 261(1), pages 169-181.
  78. Ferbar Tratar, Liljana, 2015. "Forecasting method for noisy demand," International Journal of Production Economics, Elsevier, vol. 161(C), pages 64-73.
  79. Wang, Wenbin & Syntetos, Aris A., 2011. "Spare parts demand: Linking forecasting to equipment maintenance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1194-1209.
  80. Kück, Mirko & Freitag, Michael, 2021. "Forecasting of customer demands for production planning by local k-nearest neighbor models," International Journal of Production Economics, Elsevier, vol. 231(C).
  81. Altay, Nezih & Litteral, Lewis A. & Rudisill, Frank, 2012. "Effects of correlation on intermittent demand forecasting and stock control," International Journal of Production Economics, Elsevier, vol. 135(1), pages 275-283.
  82. Bacchetti, Andrea & Saccani, Nicola, 2012. "Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice," Omega, Elsevier, vol. 40(6), pages 722-737.
  83. Petropoulos, Fotios & Kourentzes, Nikolaos & Nikolopoulos, Konstantinos, 2016. "Another look at estimators for intermittent demand," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 154-161.
  84. Syntetos, A.A. & Babai, M.Z. & Davies, J. & Stephenson, D., 2010. "Forecasting and stock control: A study in a wholesaling context," International Journal of Production Economics, Elsevier, vol. 127(1), pages 103-111, September.
  85. Nikolopoulos, Konstantinos, 2021. "We need to talk about intermittent demand forecasting," European Journal of Operational Research, Elsevier, vol. 291(2), pages 549-559.
  86. 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.
  87. Hasni, M. & Babai, M.Z. & Aguir, M.S. & Jemai, Z., 2019. "An investigation on bootstrapping forecasting methods for intermittent demands," International Journal of Production Economics, Elsevier, vol. 209(C), pages 20-29.
  88. E A Shale & J E Boylan & F R Johnston, 2006. "Forecasting for intermittent demand: the estimation of an unbiased average," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 588-592, May.
  89. Sharma, Pankaj & Kulkarni, Makarand S & Yadav, Vikas, 2017. "A simulation based optimization approach for spare parts forecasting and selective maintenance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 274-289.
  90. Teunter, Ruud & Sani, Babangida, 2009. "Calculating order-up-to levels for products with intermittent demand," International Journal of Production Economics, Elsevier, vol. 118(1), pages 82-86, March.
  91. Boylan, J.E. & Syntetos, A.A., 2007. "The accuracy of a Modified Croston procedure," International Journal of Production Economics, Elsevier, vol. 107(2), pages 511-517, June.
  92. Altay, Nezih & Rudisill, Frank & Litteral, Lewis A., 2008. "Adapting Wright's modification of Holt's method to forecasting intermittent demand," International Journal of Production Economics, Elsevier, vol. 111(2), pages 389-408, February.
  93. Gary Mitchell & Meike Niederhausen, 2010. "On Replenishing Items with Seasonal Intermittent Demand," American Journal of Economics and Business Administration, Science Publications, vol. 2(1), pages 90-102, March.
  94. Svetunkov, Ivan & Boylan, John E., 2023. "iETS: State space model for intermittent demand forecasting," International Journal of Production Economics, Elsevier, vol. 265(C).
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