网约车平台作为按需服务平台的典型代表，在价格机制和司机性质方面相较于传统出租车市场具有明显不同。一方面，网约车平台能够根据市场供需关系实时调整定价，对乘客价格和司机工资具有更强的控制性；另一方面，网约车司机作为独立承包商，拥有灵活工作方式的同时也面临着更高的收入不确定性。因此，对网约车司机的福利保障引起了监管机构的广泛关注。如何设计定价机制以兼顾平台盈利性和对司机的社会责任，对网约车平台而言是一个重要的课题。本文提出了一种考虑社会责任的网约车平台定价策略，即以最大化平台和司机作为整体的总福利为目标进行定价，并引入系数η以调节平台考虑司机福利的程度。本文建立了一个考虑了价格、工资、需求、供给之间交互的双边市场均衡模型，在此基础上围绕动态定价、固定分成比例、最低工资限制这三种不同类型的价格约束，从理论层面推导均衡最优解，并重点探讨了平台考虑司机福利的程度对市场均衡的影响及其作用机制。进一步，本文通过数值分析，对比了考虑司机福利的定价策略在三种不同价格约束下的相对表现，以作为对理论研究的拓展。本文的研究结论能够对平台运营和政府监管提供管理启示。首先，我们发现在目标函数中考虑司机福利能够改善利益在平台和司机之间的分配方式，同时也能够对乘客福利产生积极的影响，说明该定价策略在提升企业社会责任方面的有效性。其次，我们揭示了在目标函数中考虑司机福利的作用机制，即使得均衡解从最大化平台收入的位置向最大化司机有效工资的方向移动，且市场供过于求的程度越高，其对司机福利和总福利的提升作用越明显。同时，我们探讨了价格约束和目标函数之间的交互作用，即虽然价格约束会造成一部分效率损失，但在目标函数中考虑司机福利能够改善总福利的相对表现，同时不会对平台利润的相对表现造成负面影响。
Ride-hailing platforms, as a quintessential representation of the emerging on-demand service platforms, have significant changes in terms of pricing mechanisms and driver independency. On one hand, platforms can apply real-time pricing based on supply and demand, exerting stronger control over passenger fares and driver wages. On the other hand, drivers, as independent contractors, enjoy more flexible working hours but face higher income uncertainty. Consequently, the protection of driver welfare has attracted widespread attention from regulators. Designing a pricing mechanism that balances the profitability with social responsibility poses an important challenge for ride-hailing platforms.We introduce a new pricing strategy that incorporates social responsi-bility by aiming to maximize the joint welfare of both the platform and the drivers, and incorporate the coefficient η to modulate the degree of con-sideration given to driver welfare. We establish a bilateral market equilib-rium model that considers the interactions between prices, wages, demand, and supply. We explore three pricing strategies with different constraints, including dynamic pricing, fixed commission rate, and minimum wage, and derive theoretical optimal solutions. Specifically, we focus on the im-pact of η on market equilibrium and its underlying mechanism. Further-more, through numerical analysis, we compare the relative performance of the welfare-conscious pricing mechanism under different pricing con-straints, thus expanding on our theoretical insights. The key findings of our study can provide meaningful managerial in-sights for platform operations and government regulations. Firstly, we find that the consideration of driver welfare in the objective function im-proves the distribution of benefits between the platform and drivers, and has a positive impact on passenger welfare, demonstrating the effective-ness of this pricing mechanism in enhancing corporate social responsibil-ity. Secondly, we reveal the mechanism of the above impact as the shift of equilibrium solution from maximizing platform revenue towards a direc-tion that can improve driver effective wage, especially when supply large-ly exceeding demand. Thirdly, we discuss the interaction between price constraints and objective function: although price constraints can lead to efficiency losses compared to the optimal dynamic pricing, incorporating driver welfare improves the relative performance of welfare, without nega-tively affecting the platform‘s profitability.
