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

  1. Lookup NU author(s)
  2. Seong Moon
  3. Dr Andrew Simpson
  4. Professor Christian Hicks
Author(s)Moon S, Simpson A, Hicks C
Publication type Article
JournalInternational Journal of Production Econonomics
ISSN (print)0925-5273
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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.
PublisherElsevier BV
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