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

Lookup NU author(s): Seong Moon, Dr Andrew Simpson, Professor Christian Hicks


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

Publication metadata

Author(s): Moon S, Simpson A, Hicks C

Publication type: Article

Publication status: Published

Journal: International Journal of Production Econonomics

Year: 2013

Volume: 143

Issue: 2

Pages: 449-454

Print publication date: 25/02/2012

ISSN (print): 0925-5273

Publisher: Elsevier BV


DOI: 10.1016/j.ijpe.2012.02.016


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