The impact of lead time compression on demand forecasting risk and production cost: A newsvendor model

Ming Jian, Xin Fang, Liu-qian Jin and Azamat Rajapov

Transportation Research Part E: Logistics and Transportation Review, 2015, vol. 84, issue C, 61-72

Abstract: Short lead time reduces the exposure of demand forecasting risk, but an additional production cost is incurred to pay it. To solve this trade-off problem, a model is proposed based on classical newsvendor problem with lead time as a controllable variable. In this model, the demand forecasting process and the production cost structure are assumed as general functions with the amount of compressed lead time, respectively. Our investigation shows that under some circumstances, the trade-off problem can be solved and the proposed model can increase the profitability of enterprise. Finally, some numerical examples are given to illustrate the model.

Keywords: Lead time; Demand forecasting risk; Newsvendor problem; Trade-off problem; Crashing cost (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S136655451500191X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:transe:v:84:y:2015:i:c:p:61-72

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/bibliographic
http://www.elsevier. ... 600244/bibliographic

DOI: 10.1016/j.tre.2015.10.006

Access Statistics for this article

Transportation Research Part E: Logistics and Transportation Review is currently edited by W. Talley

More articles in Transportation Research Part E: Logistics and Transportation Review from Elsevier
Bibliographic data for series maintained by Catherine Liu ().