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On the variance of intermittent demand estimates

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On the variance of intermittent demand estimates. / Syntetos, Aris A.; Boylan, John.
In: International Journal of Production Economics, Vol. 128, No. 2, 01.12.2010, p. 546-555.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Syntetos, AA & Boylan, J 2010, 'On the variance of intermittent demand estimates', International Journal of Production Economics, vol. 128, no. 2, pp. 546-555. https://doi.org/10.1016/j.ijpe.2010.07.005

APA

Syntetos, A. A., & Boylan, J. (2010). On the variance of intermittent demand estimates. International Journal of Production Economics, 128(2), 546-555. https://doi.org/10.1016/j.ijpe.2010.07.005

Vancouver

Syntetos AA, Boylan J. On the variance of intermittent demand estimates. International Journal of Production Economics. 2010 Dec 1;128(2):546-555. doi: 10.1016/j.ijpe.2010.07.005

Author

Syntetos, Aris A. ; Boylan, John. / On the variance of intermittent demand estimates. In: International Journal of Production Economics. 2010 ; Vol. 128, No. 2. pp. 546-555.

Bibtex

@article{cdc2485965af4d35ad8f21f2c9ca1aaf,
title = "On the variance of intermittent demand estimates",
abstract = "Intermittent demand occurs at random with many time periods showing no demand at all. Forecasting such demand patterns constitutes a challenging exercise because of the associated dual source of variation (demand intervals and demand sizes). Research in this area has developed rapidly in recent years with new results implemented into supply chain software solutions because of its practical implications. In an inventory context, both the accuracy of the forecasts and their variability (sampling error of the mean) have equal importance in terms of service level achievement and/or inventory cost minimisation. Although the former issue has been studied extensively (mainly building upon Croston{\textquoteright}s model, 1972) the latter has been largely ignored. The purpose of this paper is to analyse the most well-cited intermittent demand estimation procedures in terms of the variance of their estimates. Detailed derivations are offered along with a discussion of the underlying assumptions. As such, we hope that our contribution may constitute a point of reference for further analytical work in this area as well as facilitate a better understanding of issues related to modelling intermittent demands.",
keywords = "Intemittent demand, Forecasting, Supply chain management, Inventory management",
author = "Syntetos, {Aris A.} and John Boylan",
year = "2010",
month = dec,
day = "1",
doi = "10.1016/j.ijpe.2010.07.005",
language = "English",
volume = "128",
pages = "546--555",
journal = "International Journal of Production Economics",
issn = "0925-5273",
publisher = "Elsevier Science B.V.",
number = "2",

}

RIS

TY - JOUR

T1 - On the variance of intermittent demand estimates

AU - Syntetos, Aris A.

AU - Boylan, John

PY - 2010/12/1

Y1 - 2010/12/1

N2 - Intermittent demand occurs at random with many time periods showing no demand at all. Forecasting such demand patterns constitutes a challenging exercise because of the associated dual source of variation (demand intervals and demand sizes). Research in this area has developed rapidly in recent years with new results implemented into supply chain software solutions because of its practical implications. In an inventory context, both the accuracy of the forecasts and their variability (sampling error of the mean) have equal importance in terms of service level achievement and/or inventory cost minimisation. Although the former issue has been studied extensively (mainly building upon Croston’s model, 1972) the latter has been largely ignored. The purpose of this paper is to analyse the most well-cited intermittent demand estimation procedures in terms of the variance of their estimates. Detailed derivations are offered along with a discussion of the underlying assumptions. As such, we hope that our contribution may constitute a point of reference for further analytical work in this area as well as facilitate a better understanding of issues related to modelling intermittent demands.

AB - Intermittent demand occurs at random with many time periods showing no demand at all. Forecasting such demand patterns constitutes a challenging exercise because of the associated dual source of variation (demand intervals and demand sizes). Research in this area has developed rapidly in recent years with new results implemented into supply chain software solutions because of its practical implications. In an inventory context, both the accuracy of the forecasts and their variability (sampling error of the mean) have equal importance in terms of service level achievement and/or inventory cost minimisation. Although the former issue has been studied extensively (mainly building upon Croston’s model, 1972) the latter has been largely ignored. The purpose of this paper is to analyse the most well-cited intermittent demand estimation procedures in terms of the variance of their estimates. Detailed derivations are offered along with a discussion of the underlying assumptions. As such, we hope that our contribution may constitute a point of reference for further analytical work in this area as well as facilitate a better understanding of issues related to modelling intermittent demands.

KW - Intemittent demand

KW - Forecasting

KW - Supply chain management

KW - Inventory management

U2 - 10.1016/j.ijpe.2010.07.005

DO - 10.1016/j.ijpe.2010.07.005

M3 - Journal article

VL - 128

SP - 546

EP - 555

JO - International Journal of Production Economics

JF - International Journal of Production Economics

SN - 0925-5273

IS - 2

ER -