高峰期考虑乘客议价的网约车定价与平台收益及社会福利优化

现阶段有关网约车动态定价的研究主要是从司机和平台的角度出发，借助排队论、生灭过程等方法描述司机的运行状态，对市场需求的动态变化特征关注较少，同时也没有考虑乘客方的自主议价权力。本文采用动态匹配描述网约车市场中乘客与司机的匹配过程，通过构建动态匹配模型描述短时间内市场变化的影响，采用需求与供给函数描述乘客和网约车的状态，在此基础上，构建平台利润最优模型和社会福利最优模型；然后提出乘客议价影响因子并依据现有数据确定其在市场运行不同时段的函数，将影响因子引入已建立的模型得到修正后的动态匹配模型和定价模型；最后设置算例验证模型可行性，探讨价格变化对市场的作用，分析乘客议价对动态匹配网约车市场的影响。算例结果表明，随着价格变化因子倍数的增加，社会福利、平台利润和匹配量先增后减，在倍数为2.0时，社会福利达到最大，倍数为1.3时匹配量达到最大。对比分析发现，乘客议价将推动市场向供求平衡移动，同时增加网约车市场高峰时段的平台利润和社会福利。

Pricing and Platform Revenue and Social Welfare Optimization for Online Car-hailing in Peak Period by Considering Passenger Independent Bargaining

Existing studies on dynamic pricing of online car- hailing mainly describe drivers' operating state from the perspective of drivers and platforms by the queuing theory, birth and death process, etc. However, the studies always pay little attention to the dynamic characteristics of market demand and ignore the independent bargaining of passengers. This paper formulates a dynamic matching model to describe the matching process between passengers and drivers in car-hailing markets by considering passenger independent bargaining. The model can capture the short-term fluctuations of car-hailing markets. The model uses demand and supply functions to describe the status of passengers and online car-hailing. Furthermore, this paper builds the platform profit optimal pricing model and the social welfare maximum pricing model. This paper puts forward the passenger bargaining influence factor and determines its function in different periods of market operation based on the existing data. We further incorporate the impact factor into the established models to revise the dynamic matching model and pricing model. This paper conducts numerical experiments to test the proposed model. The paper explores the effect of price changes on the market and analyzes theimpact of passenger bargaining on the dynamic car- hailing market. Results of numerical examples show that social welfare, platform profit, and matching amount increase first and then decrease with the increase of the multiple of the price change factor. Social welfare reaches the maximum when the multiple of the price change factor is 2.0. The meeting rate reaches its maximum when the multiple of the price change factor is 1.3. Comparative analysis shows that passenger bargaining will promote the market to balance supply and demand and increase platform profits and social welfare during peak hours of the online car-hailing market.