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Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping

Syntetos, Argyrios, Zied Babai, M. and Gardner, Everette S. 2015. Forecasting intermittent inventory demands: simple parametric methods vs. bootstrapping. Journal of Business Research 68 (8) , pp. 1746-1752. 10.1016/j.jbusres.2015.03.034

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Abstract

Although intermittent demand items dominate service and repair parts inventories in many industries, research in forecasting such items has been limited. A critical research question is whether one should make point forecasts of the mean and variance of intermittent demand with a simple parametric method such as simple exponential smoothing or else employ some form of bootstrapping to simulate an entire distribution of demand during lead time. The aim of this work is to answer that question by evaluating the effects of forecasting on stock control performance in more than 7,000 demand series. Tradeoffs between inventory investment and customer service show that simple parametric methods perform well, and it is questionable whether bootstrapping is worth the added complexity.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Business (Including Economics)
Uncontrolled Keywords: Inventory management; Operations forecasting; Time series methods; Intermittent demand
Publisher: Elsevier
ISSN: 0148-2963
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 1 February 2015
Last Modified: 01 Jul 2019 08:17
URI: http://orca.cf.ac.uk/id/eprint/73483

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