The development of a classification model for predicting the performance of forecasting methods for naval spare parts demand

Seongmin Moon, Andrew Simpson and Christian Hicks

International Journal of Production Economics, 2013, vol. 143, issue 2, 449-454

Abstract: The performance of alternative forecasting methods that use hierarchical and direct forecasting strategies for predicting spare parts demand depends on the demand features. This paper uses data obtained from the South Korean Navy to identify the demand features of the spare parts that influence on the relative performance of the alternative forecasting methods. A logistic regression classification model for predicting the relative performance of the alternative forecasting methods for the spare parts demand by multivariate demand features was developed. This classification model minimised forecasting errors and inventory costs.

Keywords: Hierarchical forecasting; Spare parts demand; Non-normal demand; Classification; Logistic regression (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:143:y:2013:i:2:p:449-454

DOI: 10.1016/j.ijpe.2012.02.016

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