Supply Allocation Under Sequential Advance Demand Information
研究了在序贯开放的市场中，公司如何利用提前需求信息分配有限库存，发现早期市场获得的供应系统性地少于晚期市场，且信息价值在初始供应接近初始预测时最大。
We study the problem of allocating supply under advance demand information. We consider a company that must allocate limited inventory to different markets that open sequentially. To reduce uncertainty, the company receives advance demand information and updates forecasts about its markets each time it makes an allocation decision. We study the value and optimal use of this information. This research is motivated by an agrifood manufacturer that operates in several European countries. We develop the optimal policy under relaxed conditions and an efficient heuristic policy that performs close to optimally under general conditions. We derive structural properties of the model to gain managerial insights, and we derive the optimal policy in closed form for the case of markets with identical prices. We use numerical experiments to demonstrate that the value of advance demand information can be significant. The managerial insights of this study include the observations that in environments such as the one that motivated our research, early markets receive systematically less supply than late markets and that the value of advance demand information is greatest if the initial supply is close to the initial forecasts.