Benchmarking Shared Mobility Data Intelligence Platforms
Data Sharing and Standardization Vital for Solution Uptake
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.
Strategic Imperatives
Why is it Increasingly Difficult to Grow?
The Strategic Imperative 8™
The Impact of the Top 3 Strategic Imperatives on Shared Mobility Data Intelligence Start-ups
Growth Opportunity Analysis
Scope of Analysis
Growth Metrics
Growth Drivers
Growth Restraints
City Mobility Stakeholder Evolution
Shared Mobility Data Intelligence Solutions—Evolution
Success Factor for These Solutions—MDS
Success Factor for These Solutions—Curb Data Specification (CDS)
The Impact of Ride-hailing Vehicles on Cities
The Impact of Micromobility Sharing on Cities
The Impact of Carsharing Vehicles on Cities
Comparative Analysis of Notable Start-ups
Shared Mobility Data Intelligence Solutions: The Way Forward
Growth Opportunity Analysis
Company Overview
City Dive Overview
Delta Overview
Bridge Overview
Case Study 1: VeloVision
Case Study 2
Key Takeaways
Growth Opportunity Analysis
Company Overview
Intelligence Data Platform
Data Products
Case Study 1: Brisbane City Council
Case Study 2: Berlin City
Case Study 3: Paris City
Key Takeaways
Growth Opportunity Analysis
Company Overview
Solution Suite
Case Study 1: Seattle City
Case Study 2: Munich City
Key Takeaways
Growth Opportunity Analysis
Company Overview
Mobility Manager Overview
Curb Manager
Enforcement Manager
Mobility Data Hub
Case Study 1: London Transport for London (TfL)
Case Study 2: LADOT
Case Study 3: San Jose
Key Takeaways
Growth Opportunity Analysis
Company Overview
Regulator Analytics
Poor Parking App and Task Manager
Case Study 1: Bergen City
Key Takeaways
Growth Opportunity Universe
Growth Opportunity 1: Geographic and Product Expansion
Growth Opportunity 2: City Operating Systems
Growth Opportunity 3: Integration of Autonomous Vehicles