McKesson Drug Company: a case study of Economost—a strategic information system
Journal of Management Information Systems - Special Issue: Decision Support and Knowledge-based Systems
Upstream demand projection and performance mapping in supply chains
WSC '05 Proceedings of the 37th conference on Winter simulation
Disruptions in information flow: a revenue costing supply chain dilemma
Journal of Theoretical and Applied Electronic Commerce Research
A framework for assessing the value of RFID implementation by tier-one suppliers to major retailers
Journal of Theoretical and Applied Electronic Commerce Research
The effects of fuzzy forecasting models on supply chain performance
FS'08 Proceedings of the 9th WSEAS International Conference on Fuzzy Systems
Fuzzy forecasting applications on supply chains
WSEAS TRANSACTIONS on SYSTEMS
A hybrid Grey & ANFIS approach to bullwhip effect in supply chain networks
WSEAS TRANSACTIONS on SYSTEMS
A combined grey & ANFIS approach to demand variability in supply chain networks
FS'09 Proceedings of the 10th WSEAS international conference on Fuzzy systems
Computer Networks: The International Journal of Computer and Telecommunications Networking
Chain-to-chain inventory transshipment model and robust switch control in CSC networks
Concurrency and Computation: Practice & Experience
A study on coordination of capacity allocation for different types of contractual retailers
Decision Support Systems
Hi-index | 0.01 |
(This article originally appeared in Management Science, April 1997, Volume 43, Number 4, pp. 546-558, published by The Institute of Management Sciences.) Consider a series of companies in a supply chain, each of whom orders from its immediate upstream member. In this setting, inbound orders from a downstream member serve as a valuable informational input to upstream production and inventory decisions. This paper claims that the information transferred in the form of "orders" tends to be distorted and can misguide upstream members in their inventory and production decisions. In particular, the variance of orders may be larger than that of sales, and distortion tends to increase as one moves upstream-a phenomenon termed "bullwhip effect." This paper analyzes four sources of the bullwhip effect: demand signal processing, rationing game, order batching, and price variations. Actions that can be taken to mitigate the detrimental impact of this distortion are also discussed.