Prohibiting cherry-picking: Regulating vehicle sharing services who determine fleet and service structure

Vehicle sharing services make travel more convenient, but increase traffic, pollute the environment, and negatively impact existing markets. To achieve a high societal welfare, public authorities regulate vehicle sharing. However, it remains unclear whether these regulations work efficiently without unexpected influences on seemingly unrelated aspects of the fleet and service structure. We study impact of regulations on decisions of vehicle sharing operators, and measure efficiency and effectiveness of these regulations. By investigating the influences of these interactions on societal welfare, we gain insights on how operators should adjust their decisions and regulators should adjust their regulations. Operators adapt fleet size, open stations, availability, and rebalancing operations to given regulations. We formalize the decision on the optimal fleet and service structure as a Mixed Integer Second-Order Cone Program. Using examples, we show that the inter-dependencies between different regulations and societal welfare indicators are non-trivial, possibly even counter-intuitive, suggesting a numerical approach to determine the direction and relevance of influencing factors. We, thus, conduct a large numerical study on artificial instances and a case study using data from New York City. Regulating the number of open stations, fleet size, or total distance reduces empty vehicle distance to a similar extent (by more than 30% of empty vehicles in the NYC case study), and more substantially than regulating the empty vehicle distance directly. Among all studied regulations, enforcing equal service availability results in the least profit loss (10% in the NYC case study). Unlike other regulations, imposing a tax predominantly affects the societal welfare indicators linearly, and can thus be enforced and controlled more easily.