Pooling, premier, and hybrid are three business models employed by ride-hailing platforms. We establish an analytical framework to examine these three models for addressing the platform’s optimal business decision. Our results reveal that both the time-sensitive cost of heterogeneous passengers and the operating cost of the platform’s self-operating vehicles play critical roles in the platform’s choice of optimal model. If the operating cost of the platform’s self-operating vehicles is relatively high, the platform should choose the pooling service model when passengers have a low ratio of time-sensitive cost between using the pooling service and using the premier service. The premier service model should be implemented if this ratio is in the middle range and the operating cost is sufficiently low. Otherwise, the hybrid service model is optimal. We characterize the conditions under which the pooling service model and the premier service model can achieve Pareto improvement for the platform and passengers. Furthermore, if the ratio is in the middle range, the pooling service model is more beneficial for passengers, while the premier service model is more profitable for the platform.

拼车，高级和混合是乘车平台采用的三种商业模式。我们建立了一个分析框架，以研究这三种模型来解决平台的最佳业务决策。我们的结果表明，异构乘客的时间敏感性成本和平台自驾车辆的运营成本在平台选择最佳模型中都起着至关重要的作用。如果平台自驾车的运营成本较高，则当乘客在使用共享服务和使用主要服务之间的时间敏感性成本较低时，平台应选择共享服务模型。如果该比率处于中间范围并且运营成本足够低，则应实施首要服务模型。否则，混合服务模型是最佳的。我们描述了集合服务模型和主要服务模型可以为平台和乘客实现帕累托改进的条件。此外，如果比率处于中间范围，则集中服务模型对乘客更有利，而主要服务模型对平台更有利。