Availability-Based Dynamic Pricing on a Round-Trip Carsharing Service: an Experimental Design Using Agent-based Simulation

Carsharing companies can customize their service by adopting different pricing schemes and offers with the goal of increasing fleet usage and profits. Dynamic pricing policies can be designed to adjust and balance temporally and spatially cars availability but may pose some question on customers’ fairness. In this paper, we develop an experimental design for conducting an explorative analysis of how an availability-based dynamic pricing scheme impacts demand and supply performances. The policy is simulated in MATSim and compared to a fixed pricing policy scheme. This simulation consists of analyzing the behavior of a synthetic population of car-sharing members for the city of Berlin and its surrounding region, in which an availability-based dynamic pricing whose price depends on vehicles availability in booking stations is applied. Results confirm that when the dynamic pricing is applied there is a light decrease in the number of bookings and people with low value of time tend to abandon the carsharing mode in favor of other modes of transportation. Overall, the policy here applied appears not to be fair since it is not equally welcome from all the population classes and, furthermore, hinders low income groups from using the carsharing service