The impact of forecasting methods on the bullwhip effect [An article from: International Journal of Production Economics]
Book Details
Author(s)X. Zhang
PublisherElsevier
ISBN / ASINB000RR0PME
ISBN-13978B000RR0PM2
AvailabilityAvailable for download now
Sales Rank11,491,085
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from International Journal of Production Economics, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
This paper considers the impact of forecasting methods on the bullwhip effect for a simple replenishment system in which a first-order autoregressive process describes the customer demand and an order-up-to inventory policy characterizes the replenishment decision. A bullwhip effect measure is derived for the optimal forecasting procedure that minimizes the mean-squared forecasting error for the specified demand process. Similar measures are obtained for the moving average and exponential smoothing methods. The findings indicate that different forecasting methods lead to bullwhip effect measures with distinct properties in relation to lead time and underlying parameters of the demand process. Moreover, a simple rule is established to help managers select a forecasting method that yields the lowest inventory cost.
Description:
This paper considers the impact of forecasting methods on the bullwhip effect for a simple replenishment system in which a first-order autoregressive process describes the customer demand and an order-up-to inventory policy characterizes the replenishment decision. A bullwhip effect measure is derived for the optimal forecasting procedure that minimizes the mean-squared forecasting error for the specified demand process. Similar measures are obtained for the moving average and exponential smoothing methods. The findings indicate that different forecasting methods lead to bullwhip effect measures with distinct properties in relation to lead time and underlying parameters of the demand process. Moreover, a simple rule is established to help managers select a forecasting method that yields the lowest inventory cost.

