Forecasting and Information Sharing in Supply Chains Under Quasi-ARMA Demand

In this paper, we revisit the problem of demand propagation in a multi-stage supply chainin which the retailer observes ARMA demand. In contrast to previous work, we show how eachplayer constructs the order based upon its best linear forecast of leadtime demand given itsavailable information. In order to characterize how demand propagates through the supplychain we construct a new process which we call quasi-ARMA or QUARMA. QUARMA isa generalization of the ARMA model. We show that the typical player observes QUARMAdemand and places orders that are also QUARMA. Thus, the demand propagation model isQUARMA-in-QUARMA-out. We study the value of information sharing between adjacentplayers in the supply chain. We demonstrate that under certain conditions information sharingcan have unbounded bene¯ts. Our analysis hence reverses and sharpens several previous resultsin the literature involving information sharing and also opens up many questions for futureresearch