Companies in a collaborative economy that introduce innovative mobility programs such as free-floating scooter or car sharing can help to reduce the impact of vehicle ownership on cities. According to Dawe, scooter sharing in particular reduces congestion levels and the demand for parking, and users benefit from reductions in overall travel duration.
Dawe teamed up with the Hamburg-based start-up Jaano GmbH and analyzed their bookings with a focus on demand patterns. “Knowing the physical location of demand and the general direction of travel at a certain time under certain weather conditions and congestion levels enables providers to better satisfy demand and optimize revenue by (re-)locating and pricing their fleet accordingly,” Dawe concluded. If all providers understood their demand, cities would experience noticeable relief since the demand for travel could be satisfied more efficiently and more flexibly. By applying conjoint analysis to survey data, he found support for the theory that dynamic pricing is a valuable lever for providers who want to maximize their revenue under certain demand conditions and incentivize user-based vehicle relocation.
Examples of applied dynamic pricing in urban transportation include Uber’s surge pricing that reacts to an imbalance between demand and supply and the recent implementation of discounted fares by the car sharing provider DriveNow, which encourages the user-based relocation of vehicles from low-demand areas.
In Meissner’s opinion, Dawe’s findings that “providers of new mobility need to engage in demand learning and apply valuable levers like dynamic pricing to optimize the benefits for the public, their customers and themselves” provide very important insights for the future of urban transportation.