Forecasting intermittent demand: a comparative study
R H Teunter () and
L Duncan ()
Additional contact information
R H Teunter: Lancaster University Management School
L Duncan: Lancaster University Management School
Journal of the Operational Research Society, 2009, vol. 60, issue 3, 321-329
Abstract:
Abstract Methods for forecasting intermittent demand are compared using a large data set from the UK Royal Air Force. Several important results are found. First, we show that the traditional per period forecast error measures are not appropriate for intermittent demand, even though they are consistently used in the literature. Second, by comparing the ability to approximate target service levels and stock holding implications, we show that Croston's method (and a variant) and Bootstrapping clearly outperform Moving Average and Single Exponential Smoothing. Third, we show that the performance of Croston and Bootstrapping can be significantly improved by taking into account that an order in a period is triggered by a demand in that period.
Keywords: forecasting; inventory; intermittent demand (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (46)
Downloads: (external link)
http://link.springer.com/10.1057/palgrave.jors.2602569 Abstract (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:pal:jorsoc:v:60:y:2009:i:3:d:10.1057_palgrave.jors.2602569
Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/41274
DOI: 10.1057/palgrave.jors.2602569
Access Statistics for this article
Journal of the Operational Research Society is currently edited by Tom Archibald and Jonathan Crook
More articles in Journal of the Operational Research Society from Palgrave Macmillan, The OR Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().