The effects of forecasting errors on the total cost of operations
Ts Lee,
Fw Cooper and
Ee Adam
Omega, 1993, vol. 21, issue 5, 541-550
Abstract:
The industrial customer faces the need to forecast utility demand. This paper demonstrates how the utility can help the industrial customer forecast more accurately and thus reduce costs. Using the actual business conditions of a public utility, an extensive examination of traditional time series forecasting techniques under various simulated or demand patterns has been carried out. In this paper, traditional forecasting error measures such as bias, mean absolute deviation (MAD) and mean squared error (MSE) have been analysed in correlation with a much more relevant error measure for a business environment: the total cost of a time series model relative to the organization. Finally, some previously held assumptions of autocorrelation and 'model fit' are examined.
Keywords: operations; management; inventory; control; forecasting (search for similar items in EconPapers)
Date: 1993
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0305-0483(93)90022-D
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:jomega:v:21:y:1993:i:5:p:541-550
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
Access Statistics for this article
Omega is currently edited by B. Lev
More articles in Omega from Elsevier
Bibliographic data for series maintained by Catherine Liu ().