We introduce a class of new sharing arrangements in a multi-stage supplychain in which the retailer observes stationary autoregressive movingaverage demand with Gaussian white noise (shocks). Similar to previousresearch, we assume each supply chain player constructs its best linearforecast of...

We consider the problem of assessing value of demand sharing in a multi-stage supply chain in which the retailer observes stationary autoregressive moving average demand with Gaussian white noise (shocks). Similar to previous research, we assume each supply chain player constructs its best...

We study a two-stage supply chain where the retailer observes two demand streams coming from two consumer populations. We further assume that each demand sequence is a station- ary Autoregressive Moving Average (ARMA) process with respect to a Gaussian white noise sequence (shocks). The shock...

We introduce a class of new sharing arrangements in a multi-stage supply chain in which the retailer observes stationary autoregressive moving average demand with Gaussian white noise (shocks). Similar to previous research, we assume each supply chain player constructs its best linear forecast...

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...

We consider a two-tier inventory management system with one retailer and one supplier. The retailer serves a demand driven by a stationary moving average process (of possibly infinite order) and places periodic inventory replenishment orders to the supplier. In this setting, we study the value...