Optimal pricing and pricing policy selection for a B2C car-sharing platform during peak and off-peak hours.

• Study the pricing policy selection for a B2C car-sharing platform. • Develop profit maximization models of the platform under different policies. • Obtain the platform's optimal pricing decisions during peak and off-peak hours. • Present a case study on determining the optimal pricing policy. • Provide useful managerial insights for B2C car-sharing platforms. This study examines the optimal pricing and pricing policy selection for a business-to-consumer (B2C) car-sharing platform during peak and off-peak hours, where two pricing policies are evaluated, that is, fixed pricing policy and dynamic pricing policy. First, we construct the B2C car-sharing market demand function and the sharing platform's profit maximization model under each pricing policy, and obtain optimal outcomes by solving the model, including service price, market demand, platform's profit, consumer surplus, and social welfare. Then, through analysis, we reveal the effects of the pricing policy selection on the optimal outcomes. The results show that compared with the fixed pricing policy, implementing a dynamic pricing policy can increase the sharing platform's profit, but decrease the consumer surplus and social welfare. Additionally, implementing a dynamic pricing policy can also increase the demand during off-peak hours and decrease the demand during peak hours. [ABSTRACT FROM AUTHOR]