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Effects of correlation on intermittent demand forecasting and stock control

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  • Altay, Nezih
  • Litteral, Lewis A.
  • Rudisill, Frank

Abstract

This study investigates the effects of three different types of correlation on forecasting and stock control of intermittent demand items. Applying appropriate forecasting and stock control methods to theoretically generated compound Poisson demand data we show that correlation in intermittent demand does play a role in forecast quality and stock control performance. Negative autocorrelation levels lead to higher service levels than positive values, while cost does not significantly change. Our results also show that high intermittency levels intensify these changes in service level. We also show that cross-correlation produces results in the opposite direction of autocorrelation in size or intervals; that is, positive (negative) cross-correlation leads to higher (lower) service levels.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:proeco:v:135:y:2012:i:1:p:275-283
    DOI: 10.1016/j.ijpe.2011.08.002
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    6. Christopher A. Boone & Benjamin T. Hazen & Joseph B. Skipper & Robert E. Overstreet, 2018. "A framework for investigating optimization of service parts performance with big data," Annals of Operations Research, Springer, vol. 270(1), pages 65-74, November.
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    8. Kumar, Anupam & Evers, Philip T., 2015. "Setting safety stock based on imprecise records," International Journal of Production Economics, Elsevier, vol. 169(C), pages 68-75.
    9. 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).
    10. 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.

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