Forecast accuracy, information technologies and the performance of inventory policies under multi-level rolling schedule environments
Dellaert, Nico and Jeunet, Jully (2002). Forecast accuracy, information technologies and the performance of inventory policies under multi-level rolling schedule environments. UNU-MERIT Research Memoranda. UNU-MERIT.
Document type:
Report
Collection:
-
Attached Files (Some files may be inaccessible until you login with your UNU Collections credentials) Name Description MIMEType Size Downloads rm2002-005.pdf PDF 
application/pdf 1.11MB -
Sub-type Working paper Author Dellaert, Nico
Jeunet, JullyTitle Forecast accuracy, information technologies and the performance of inventory policies under multi-level rolling schedule environments Series Title UNU-MERIT Research Memoranda Volume/Issue No. 5 Publication Date 2002 Publisher UNU-MERIT Language eng Abstract Our incentive is to study the behaviour of lot-sizing rules in a multi-level context when forecast demand is subject to changes within the forecast window. To our knowledges, only Bookbinder and Heath (1988) have proposed a lot-sizing study in a multi-echelon rolling schedule with probabilistic demands. But their simulation study was limited to two arborescent structures with 6 nodes. By means of an extensive simulation study we show that it is always worth decreasing the error magnitude. This should encourage companies to develop Electronic Data Interchange to ameliorate demand forecast. Although the presence or absence of forecast errors matters more than the error level, we show that lot-sizing rules exhibit significant differences in their behaviour as the level of error is augmented. This paper also provides a clear description of the rolling procedure when applied to general product structures, probabilistic demand within the forecast window and positive lead times. Copyright Year 2002 Copyright type All rights reserved -
Citation counts 
Search Google Scholar
Access Statistics: 354 Abstract Views, 128 File Downloads - Detailed Statistics Created: Fri, 13 Dec 2013, 12:42:53 JST