Optimal Dynamic Pricing for Perishable Assets with Nonhomogeneous Demand
研究有限时间内易逝品的动态定价模型，顾客保留价格分布随时间变化，到达过程为非齐次泊松过程。发现最优价格随库存递减，并给出价格随时间递减的充分条件。数值实验显示动态定价相比单一最优定价可提升收益2.4%至7.3%，在需求变化时收益提升可达100%。
We consider a dynamic pricing model for selling a given stock of a perishable product over a finite time horizon. Customers, whose reservation price distribution changes over time, arrive according to a nonhomogeneous Poisson process. We show that at any given time, the optimal price decreases with inventory. We also identify a sufficient condition under which the optimal price decreases over time for a given inventory level. This sufficient condition requires that the willingness of a customer to pay a premium for the product does not increase over time. In addition to shedding managerial insight, these structural properties enable efficient computation of the optimal policy. Numerical studies are conducted to show the revenue impact of dynamic price policies. Price changes are set to compensate for statistical fluctuations of demand and to respond to shifts of the reservation price. For the former, our examples show that using optimal dynamic optimal policies achieves 2.4–7.3% revenue improvement over the optimal single price policy. For the latter, the revenue increase can be as high as 100%. These results explain why yield management has become so essential to fashion retailing and travel service industries.