考虑顾客使用行为的汽车租赁容量分配策略研究

随着物联网技术的发展, 租赁公司通过智能技术可以实时监测顾客的使用行为, 因此可以根据顾客使用行为设计补贴策略以激励顾客在使用过程中保持良好的行为习惯。本文将租赁价格作为顾客行为的函数, 构建随机动态规划模型, 研究了多产品、多周期下汽车租赁公司的容量分配决策和补贴机制。考虑到所构建模型的状态变量维度较高, 因此提出两种近似算法对模型进行求解, 并通过数值仿真验证了模型的相关性质。在考虑顾客行为可以转变的前提下, 得到相关结论:租赁公司以机会成本作为容量分配决策的重要依据;当所需等级汽车缺货时, 由于低等级汽车的机会成本低于高等级汽车的机会成本, 因此满足升级条件时, 租赁公司总是按照等级顺序进行升级;在合理的补贴策略下, 公司的总收益将会随着补贴的增加而增加。

Capacity Allocation Policy for Car Rental Systems with Customer Behavior Consideration

With the development of the Internet of Things, the rental company can monitor customers’ behavior in time by intelligent technology. An increasing number of car rental companies are motivated to design a subsidy policy to encourage customers to maintain good behavior in the rental process. Taking rental prices as a function of customer behavior, a dynamic programming model has been constructed to analyze the capacity allocation policy and subsidy policy under multi-period and-product. Because of the highly dimension of the state variable, it is difficult to solve the problem. We have proposed two approximation algorithms to solve this problem and testified the properties of the model. After considering the transfer of customer behavior, the results about capacity allocation, upgrade mechanism and subsidy policies are as follows: The capacity control policy depends on opportunity cost. The upgrade mechanism is in accordance with the hierarchy of the product and the upgrade strategy is upgraded in sequence. An increase in subsidy will not decrease the expected revenue under certain conditions. Thus, an appropriate subsidy strategy can raise the revenue of the company.