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The purpose of this paper is to mitigate bullwhip effect (BWE) in a supply chain (SC). Four main contributions are proposed. The first one is to reduce BWE through considering its multiple causes (demand, pricing, ordering, and lead time) simultaneously. The second one is to model demands, orders, and prices dynamically for reducing BWE. Demand and prices have mutual effect on each other dynamically over time. In other words, a time series model is used in a game theory method for finding the optimal prices in an SC. Moreover, the optimal prices are inserted into the time series model for forecasting price sensitive demands and orders in an SC. The third one is to use demand of each entity for forecasting its orders. This leads to drastic reduction in BWE and mean square error (MSE) of the model. The fourth contribution is to use optimal prices instead of forecasted ones for demand forecasting and reducing BWE. Finally, a numerical experiment for the auto parts SC is developed. The results show that analysing joint demand, orders, lead time, and pricing model with calculating the optimal values of prices and lead times leads to the significant reduction in BWE.

Incorporating demand, orders, lead time, and pricing decisions for reducing bullwhip effect in supply chains