SUPPLY CHAINS FACING ATYPICAL DEMAND: OPTIMAL OPERATIONAL POLICIES AND BENEFITS UNDER INFORMATION SHARING

Demand patterns for products with seasonality and or short life-cycles do not follow a clear discernible pattern (to allow predictive time-series modeling of demand) for individual sales events or seasons due to such factors as considerable demand volatility, product promotions, and unforeseen marketplace events. Suppliers supporting such atypical demand patterns typically incur higher holding costs, lower capacity utilization, and lower order fill-rates, particularly under long lead-times and uncertainty in effective capacity. Retailers on the other hand struggle with product overages and supply shortages. On the other hand, atypical demand settings bring huge financial opportunity to supply chain players, and are pervasive. It is suggested in the literature that an effective means to reap these benefits is through increased information sharing between retailers and suppliers, superior forecasting with forecast update techniques, proper replenishment, and custom designed inventory/manufacturing policies. We also believe that sharing of order forecasts, also known as soft-orders, in advance by the buyer could be beneficial to both parties involved. This dissertation in particular studies a two-player supply chain, facing atypical demand. Among the two-players is a buyer (retailer/distributor/vendor) that makes ordering decision(s) in the presence of upstream supply uncertainty and demand forecast revision(s). We propose a stochastic dynamic programming model to optimally deicide on soft-order(s) and a final firm-order under a deposit scheme for initial soft-order(s). While sharing of upstream soft-order inventory position information by the supplier before receiving a final order is not a common industrial practice, nor is it discussed in the literature, our analysis shows that such information sharing is beneficial under certain conditions. Second player of the supply chain is a supplier (manufacturer) that makes production release decision(s) in the presence of limited and random effective capacity, and final ...