Demand forecasting for companies with many branches, low sales numbers per product, and non-recurring orderings

We propose the new Top-Dog-Index to quantify the historic deviation of the supply data of many small branches for a commodity group from sales data. On the one hand, the common parametric assumptions on the customer demand distribution in the literature could not at all be supported in our real-world data set. On the other hand, a reasonably-looking non-parametric approach to estimate the demand distribution for the different branches directly from the sales distribution could only provide us wiWe propose the new Top-Dog-Index to quantify the historic deviation of the supply data of many small branches for a commodity group from sales data. On the one hand, the common parametric assumptions on the customer demand distribution in the literature could not at all be supported in our real-world data set. On the other hand, a reasonably-looking non-parametric approach to estimate the demand distribution for the different branches directly from the sales distribution could only provide us with statistically weak and unreliable estimates for the future demand.show moreshow less
Die Nachfrageschätzung spielt für Unternehmen eine immer größer werdende Rolle. Wir führen einen neuen Index für die Schätzung der Nachfrage anhand historischer Verkaufsinformationen ein.

Download full text files

Export metadata

  • Export Bibtex
  • Export RIS
  • frontdoor_exportcitavi

Additional Services

    Share in Twitter Search Google Scholar
Metadaten
Institutes:Mathematik
Author: Sascha Kurz, Jörg Rambau
Year of Completion:2006
SWD-Keyword:Operations Research; Revenue Management
Tag:Revenue Management
demand forecasting; revenue management
Dewey Decimal Classification:510 Mathematik
MSC-Classification:90B05 Inventory, storage, reservoirs
URN:urn:nbn:de:bvb:703-opus-4255
Document Type:Article
Language:English
Date of Publication (online):15.04.2008