The impact of forecasting methods on bullwhip effect in supply chain management

Abstract

Recently there has been a surge of interest and research on a phenomenon popularly called the bullwhip effect in supply chain management. The focus of this paper is the impact of demand forecasting on the bullwhip effect. Based on a thorough literature review, we classify existing researches into different categories in terms of modeling methods. Then we show quantification results of the bullwhip effect for simple, two-stage, supply chains consisting of a single retailer and a single manufacturer. Order-up-to inventory policy is assumed. The modeling results of three important forecasting methods (moving average, exponential smoothing, and minimum mean square error) are studied. A comparison is made between these forecasting methods, and some practical guidelines are developed to help managers to select a forecasting method that yields the greatest desired benefit. Finally, possible future research directions in this area are proposed.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 24 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.