Improved supply chain management based on hybrid demand forecasts
Applied Soft Computing
Automatica (Journal of IFAC)
Is there a benefit to sharing market sales information? Linking theory and practice
Computers and Industrial Engineering
On the link between inventory and responsiveness in multi-product supply chains
International Journal of Systems Science - Production Coordination and Inventory Policies
An improved demand forecasting method to reduce bullwhip effect in supply chains
Expert Systems with Applications: An International Journal
Applicability of ARIMA Models in Wholesale Vegetable Market: An Investigation
International Journal of Information Systems and Supply Chain Management
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This paper presents a multistage supply chain model that is based on Autoregressive Integrated Moving Average (ARIMA) time-series models. Given an ARIMA model of consumer demand and the lead times at each stage, it is shown that the orders and inventories at each stage are also ARIMA, and closed-form expressions for these models are given.The paper also discusses the causes of the bullwhip effect, a phenomenon in which variation in demand produces larger variations in upstream orders and inventory. This discussion reveals how different modeling can lead to different insights because they make different assumptions about the cause of the bullwhip effect. These observations are used to develop managerial insights about reducing the bullwhip effect.