Abstract:

Considering cross-side externality between self-scheduling supply and demand in the ride-hailing platform， to match the two sides and optimize profit， subscription pricing is introduced， where if customers choose to subscribe， then they can receive services at a discounted price during the contract period after paying the subscription fee at the beginning； Otherwise， they will receive services at regular prices during the contract period. For the platform， subscription services lock up some revenue from the customers who pay before they observe their perceived value； But at the same time， this part of consumers request services at low prices during the contract period， which will also bring losses to the platform. The platform needs to weigh the pros and cons of introducing subscription services. A model is built and solved that considers endogenous supply capacity and allows customers to choose whether to subscribe. And the firm determines optimal subscription plan as well as the wage. It is found that the optimal strategy balances expected supply and demand at a higher level and the optimal pricing achieves higher profits. It is believed that the reason for this is from two aspects： on the one hand， some passengers choose to purchase subscription services in advance， which allows the platform to take advantage of the passengers' ex-ante homogeneity in their perceived value； on the other hand， the heterogeneity in the number of rides leads different passengers to make different choices， from the platform's perspective， which is equivalent to differential pricing on the dimension of ride frequency. A sensitivity analysis of the impact of relevant market parameters on the optimal decisions is conducted. When the scale of supply （relative to demand） grows， due to the fact that resources are no longer scarce， in order to achieve supply-demand balance， the platform needs to decrease the price of each ride to increase passengers' willingness to request the service， and reduce the driver's wage to control effective supply. At the same time， in order to ensure the optimal number of subscribers， the platform needs to increase the discount. Finally， in order to make up for the loss of revenue caused by the decrease of pay-per-ride and discount rate， the platform needs to increase subscription fees. Numerical experiments show that these conclusions still hold when there are multiple scenarios. These findings are helpful for ride-hailing platforms to determine their pricing strategies.

Key words: ride-hailing platform, subscription, consumer heterogeneity