Benchmarking Shared Mobility Data Intelligence Platforms

Cities are evolving toward a more sustainable and efficient model. A focus area is reducing carbon emissions by adopting renewable energy sources like solar and wind power and promoting electric vehicles. In addition, there is a shift toward pedestrian-friendly urban design, with wider sidewalks, bike lanes, and increased green spaces. Cities want to increase the sustainable modal share significantly, especially in terms of mobility. Digitally enabled cities can improve mobility by implementing advanced technologies or integrating all transport options. Initiatives such as data standardization will make sharing data across the mobility ecosystem easier.

The shared mobility market has been growing steadily in the past few years. Frost & Sullivan expects the overall global fleet of the shared mobility market to increase to about 44 million vehicles by the end of 2030, of which the ride-hailing and bike-sharing fleets account for over 85%.

Besides the challenge presented by the large vehicle volume, there is a need to efficiently manage them to enable better supply and demand management. Another problem is the issue of safety that cities face, particularly with kick scooters. Many accidents have occurred because kick scooters are improperly parked or people are riding them on the curb. Cities like Paris, Madrid, Montreal, and Melbourne have banned kick scooters due to safety reasons.

Many urban mobility management solutions exist, including traffic management location-based intelligence (e.g., trip, vehicle, movement, congestion, and distance analysis) and road analytics solutions (e.g., solutions that provide reports on events, tolling, tunnels, hazards, rules, or pricing). This study focuses on start-ups (companies founded post-2010) that offer shared mobility intelligence for cities to help them better manage shared fleets.

This research’s main participants are Fluctuo, Vianova, Populus, Blue Systems, and Nível. However, this selection is not an exhaustive list of solution providers in this space. The study period is 2020 to 2030, with 2023 as the base year.

Author: Albert Geraldine Priya