65
Views
1
CrossRef citations to date
0
Altmetric
Original Articles

The integrated use of information and stocks in the management of uncertain lumpy demand

&
Pages 220-233 | Published online: 19 Feb 2007
 

Abstract

This paper aims at presenting a new approach to the management of uncertain lumpy demand. After providing a comprehensive review of the related literature, a new approach is introduced here in order to reduce the need for stocks when coping with uncertain lumpy demand. The basic idea of this approach is that of exploiting available information within the company or within the company's supply chain, so as to minimize the impact of lumpy orders and reduce the need for stocks. Two theoretical models are presented here to address the trade-off between the benefit of the lower inventory level and the cost of the higher risk related to the anticipatory use of uncertain information: the first model treats the lumpy order quantity as deterministic, while the arrival of the order is considered as a stochastic event; the second model deals with the opposite situation, when the arrival of a lumpy order is certain, while the order quantity is uncertain. These new models turn out to have a relevant interpretative power, and seem useful in real-life management of lumpy demand, since they can boost running capital productivity resorting to information usually available within or around the company, although often not exploited.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 528.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.