 Comparison of a new bootstrapping method with parametric approaches for safety stock determination in service parts inventory systemsChenxi Zhou and S. Viswanathan International Journal of Production Economics, 2011, vol. 133, issue 1, 481-485 Abstract: In this paper, we address the problem of forecasting and managing the inventory of service parts where the demand patterns are highly intermittent. Currently, there are two classes of methods for determining the safety stock for the intermittent item: the parametric and bootstrapping approaches. Viswanathan and Zhou (2008) developed an improved bootstrapping based method and showed through computational experiments that this is superior to the method by Willemain et al. (2004). In this paper, we compare this new bootstrapping method with the parametric methods of Babai and Syntetos (2007). Our computational results show that the bootstrapping method performs better with randomly generated data sets, where there is a large amount of (simulated) historical data to generate the distribution. On the other hand, with real industry data sets, the parametric method seems to perform better than the bootstrapping method. Keywords: Forecasting; Intermittent; demand; Safety; stock; determination; Bootstrapping; Inventory; management (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:133:y:2011:i:1:p:481-485 Access Statistics for this article International Journal of Production Economics is currently edited by Stefan Minner More articles in International Journal of Production Economics from Elsevier |
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