Information distortion in a supply chain: the bullwhip effect
Management Science - Special issue on frontier research in manufacturing and logistics
Value of Information in Capacitated Supply Chains
Management Science
A Single-Item Inventory Model for a Nonstationary Demand Process
Manufacturing & Service Operations Management
The Value of Information Sharing in a Two-Level Supply Chain
Management Science
A Time-Series Framework for Supply-Chain Inventory Management
Operations Research
Measuring Imputed Cost in the Semiconductor Equipment Supply Chain
Management Science
Coordinating Supply Chains by Controlling Upstream Variability Propagation
Manufacturing & Service Operations Management
An Econometric Analysis of Inventory Turnover Performance in Retail Services
Management Science
In Search of the Bullwhip Effect
Manufacturing & Service Operations Management
New Introduction to Multiple Time Series Analysis
New Introduction to Multiple Time Series Analysis
Bullwhip Effect Measurement and Its Implications
Operations Research
| Hi-index | 0.01 |
The bullwhip effect is the amplification of demand variability along a supply chain: a company bullwhips if it purchases from suppliers more variably than it sells to customers. Such bullwhips (amplifications of demand variability) can lead to mismatches between demand and production and hence to lower supply chain efficiency. We investigate the bullwhip effect in a sample of 4,689 public U.S. companies over 1974--2008. Overall, about two-thirds of firms bullwhip. The sample's mean and median bullwhips, both significantly positive, respectively measure 15.8% and 6.7% of total demand variability. Put another way, the mean quarterly standard deviation of upstream orders exceeds that of demand by $20 million. We decompose the bullwhip by information transmission lead time. Estimating the bullwhip's information-lead-time components with a two-stage estimator, we find that demand signals firms observe with more than three-quarters' notice drive 30% of the bullwhip, and those firms observe with less than one-quarter's notice drive 51%. From 1974--1994 to 1995--2008, our sample's mean bullwhip dropped by a third. This paper was accepted by Christian Terwiesch, operations management.