Information Sharing and Order Variability Control Under a Generalized Demand Model

The value of information sharing and how it could address the bullwhip effect have been the subject of studies in the literature. Most of these studies used different forms of demand models, assuming that no order smoothing was used by the retailer and that the supplier has full knowledge of the retailer's demand model and order policy. In this paper, we contribute to the literature by starting with a most general demand model, coupled with a smoothing policy for order variability control. In addition, we do not require that the supplier has full knowledge of the retailer's demand model and order policy, but instead let the retailer share its projected future orders (and freely revise them as the retailer sees fit). Under such a setting, we first obtain a unifying formula for the magnitude of the bullwhip effect. The formula indicates that it is the forecast correlation over the exposure period as a whole that determines the magnitude of the bullwhip effect. We then quantify the value of information sharing and generalize the existing results in the literature. Finally, we explore the optimal smoothing parameters that could bene fit the total supply chain. The resulting optimal policy resembles the postponement strategy. We find that information sharing together with order postponement improves the supply chain performance, even though the order variability may amplify in some cases.