Christian Müller, Jochen Gönsch, Louisa Albrecht, and Max Staskiewicz explore dynamic pricing mechanisms for car-sharing services. Their data-driven model predicts future vehicle movements and the expected profit of each vehicle, then uses machine learning and AI to combine various data sources. This results in different prices for the same vehicle for different customers, depending on their location, thus rebalancing cars in the pickup/drop-off zone without the operator having to relocate cars (adding emissions). According to the authors, an extensive computational study and a case study showed the approach outperforms all benchmarks, saves providers operational costs, and improves sustainability via clear decarbonization benefits.