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Market Research Report

Mobility as a Service (MaaS)

Published by Juniper Research Product code 690426
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Mobility as a Service (MaaS)
Published: September 4, 2018 Content info:
Description

Our new Mobility-as-a-Service research provides an in-depth examination of this emerging market; delivering crucial insights into vendor strategy and business models being formulated in the nascent area. It provides an evaluation of the current market progress to MaaS (Mobility-as-a-Service) implementation and future opportunities for players across the value chain in each area of MaaS deployment.

The research provides critical analysis of the key sectors, regional opportunities and developments, whilst providing insights into the impact expected on existing transport methods. This is aligned with an extensive scenario-based forecast suite, offering 3 scenarios (for low, medium and high user adoption) for the future of MaaS. Metrics featured in each scenario include:

  • Number of MaaS Users
  • MaaS Revenues
  • Time Savings from MaaS Introduction Compared with Private Car Use
  • Fuel Cost Savings from MaaS Introduction Compared with Private Car Use

This research suite includes:

  • Deep Dive Strategy & Competition (PDF)
  • 5 Year Deep Dive Data & Forecasting (PDF & Excel)
  • Executive Summary & Core Findings (PDF)

Key Features

  • Market Analysis & Impact Assessment: Separate analyses for the impact of MaaS introduction by area, aligned with a breakdown of prevailing market forces. The analysis is conducted for the following areas:
    • Drivers & the Driving Experience
    • Congestion & Environmental Impact
    • Impact on Car Manufacturers
    • Infrastructure Impact
    • Transport Provider Business Models
  • Regional Analysis of MaaS Adoption & Readiness: Including analysis of adoption and barriers to growth across 8 key global regions according to an evaluation of:
    • The Supporting Ecosystem
    • Existing MaaS Efforts
    • MaaS Growth Prospects
    • Barriers to Further Growth
  • Juniper Leaderboard: 12 leading MaaS vendors compared, scored and positioned on the Juniper Leaderboard matrix, including:
    • Citymapper
    • Cubic
    • ESP Group
    • Fluidtime
    • Ioki
    • MaaS Global
    • Masabi
    • moovel
    • Moovit
    • Ridecell
    • SkedGo
    • UbiGo
  • MaaS City Ranking: Evaluation of pioneering cities experimenting with MaaS deployment and their progress to date.
  • MaaS City Ranking: Evaluation of pioneering cities experimenting with MaaS deployment and their progress to date.
    • MaaS Global
    • Masabi
    • moovel
    • Moovit
    • Nextbike
    • Ridecell
    • JOIN Group
  • Benchmark Industry Forecasts: Market forecasts for MaaS adoption in terms of:
    • Users
    • Service revenues
    • End-user time and cost savings
    • Splits according to 3 user adoption scenarios and 8 key global regions

Key Questions

  • 1. What is the revenue opportunity for MaaS deployment in the next 5 years?
  • 2. What will be the impact of MaaS adoption on traditional transport companies?
  • 3. What technologies are required for MaaS deployment and what is their readiness for use?
  • 4. Which cities are best placed for MaaS disruption?
  • 5. What are the biggest challenges to MaaS deployment and how are vendors approaching these?

Companies Referenced

Interviewed: JOIN Group, MaaS Global, Masabi, moovel, Moovit, Nextbike UK, Ridecell.

Profiled: Citymapper, CTS, ESP Group, Fluidtime, Ioki, MaaS Global, Masabi, moovel, Moovit, Ridecell, SkedGo, UbiGo.

Case Studied: Bird, Lime, MaaS Global, Skip, Uber, UbiGo.

Mentioned: 3M, AAA, Aberdeen Council of Voluntary Organisations, Access IS, Actionbase Software Solutions, ALD Automotive, Alibaba, Alzheimer's Scotland, Anchorage People Mover, Apple, AS Roma, Atkins, Atos, Audi, BlaBlaCar, BMW, Breeze Bikeshare, Cabify, Cabonline Group, Caltrain, Car Next Door, car2go, Chalo, Chicago Transit Authority, Citi Bike, City of Atlanta Streetcar, Citybikes, Conduent, Contact Light, Cubic Corporation, Daimler, Deloitte, DENSO, Denver RTD, Deutsche Bahn, DiDi Chuxing, Dojo, Dot Transfers, DOVU, EEA (European Environment Agency), EkoRent, Eyron, Ferrovial, Flitways, Ford, Foursquare, Galois, GM (General Motors), Go Get, GoBike, GoCatch, Google, Grab, Helpten, Helsinki Business Hub, Helsinki City Transport, Hertz, Highways England, Hochbahn, Houston Metro, HRT (Helsinki Regional Transport Authority), Hubway, HVV, Hyundai, IMOVE, Ingogo, INIT, Intel, Intific, IQ Payments, IRCTC (Indian Railway Catering and Tourism Corporation), ITF (International Transport Forum), ITO World, ITS Finland, Jaguar Land Rover, Jalan, Jayride, Kapsch Group, Keolis, Kisio, Kontiki, LA Metrolink, Las Vegas RTC, Los Angeles DOT, Los Angeles Metro, Lyft, MaaS Alliance, MaaS Australia, Manly Ferries, Mastercard, MBTA, Metra, Metro Transit, MIT Media Lab, mobiag, Mobileye, Moia, Motivate, MTA, Mudlark, MVV, mytaxi, NACTO, National Express, Nissan, NorisBike, ofo, Ola, Opel, OptimalTest, Optus, Orange County Transportation Authority, Pace, Parkopedia, PayPal, Paytm, Porsche, Portland Streetcar, Portland TriMet, PSA Groupe, Rakuten, Renault, Route Monkey, San Antonio VIA, San Diego MTS & North County Transit District, San Francisco Municipal Transportation Agency, Santa Clara VTA, Scheidt & Bachmann, Scottish National Entitlement Card Programme Office, Seat, Skoda, SL (Storstockholms Lokaltrafik), SMMT (Society of Motor Manufacturers and Traders), Société Générale, SoftBank, SouthWest Transit, SSB, Swift Fleet, SYSTRA, TAO, TfL (Transport for London), TfWM (Transport for West Midlands), Thames Clippers, The Hague HTM, Ticketer, TomTom, Toronto Transit Commission, Toyota, Trainline, Transit, Transport for Greater Manchester, Transport for New South Wales, Transport Scotland, Travelport, uberPOOL, UK Energy Saving Trust, Urbano, Vauxhall, Velodyne, Vesta, Via, Vinnova, Virginia Railway Express, Vmobil, Volkswagen Group, Volvo, VVS, What3Words, Wiener Linien, Wiman, Yandex, Young Scot, Zipcar.

Data & Interactive Forecast

Juniper's Mobility-as-a-Service forecast suite includes:

  • 5 year benchmark forecasts for key metrics by 8 key regions and 11 country level splits including:
    • Canada
    • China
    • Denmark
    • Germany
    • Japan
    • Norway
    • Portugal
    • Spain
    • South Korea
    • Sweden
    • UK
    • US
  • 3 scenario-based forecast sets modelling low, medium and high adoption rates according to variations in key influencing factors. Outcomes cover the following metrics:
    • Number of MaaS Users
    • Number of MaaS Users who Subscribe to the Service
    • Total MaaS Subscription Revenues
    • Total Number of MaaS Users who Pay for the Service on an Ad Hoc Basis
    • Total MaaS Ad Hoc Revenues
    • Total Revenues from MaaS
    • Total Number of MaaS Trips
    • Total Number of Private Car Trips Replaced with MaaS Trips
    • Total Time Saved via MaaS Compared with Private Car Journeys
    • Total Fuel Cost Savings from MaaS Implementation
  • Access to the full set of forecast data of 38 tables and over 3,850 datapoints.
  • Interactive Excel Scenario tool allowing the user the ability to manipulate Juniper's data for 12 different metrics.
Table of Contents

Table of Contents

1. Deep Dive Strategy & Competition Table of Contents

1. MaaS: Market Status & Outlook

  • 1.1 Introduction
    • 1.1.1 The Open Data Vision
      • i. Case Study: NYC OpenData
    • 1.1.2 Benefits of MaaS
    • 1.1.3 The Urban Mobility Stack
      • Figure 1.1: The Urban Mobility Stack
    • 1.1.4 Drivers for MaaS
      • Figure 1.2: Number of Vehicles in Service, (m) 2014-2017, Global
      • Table 1.3: Tom Tom Traffic Index, Top 10 Congested Cities with a Population of Over 8 Million
      • Figure 1.4: CO2 Emissions, (Kilotons), Worldwide, 1980-2014
      • Figure 1.5: CO2 Emissions, (Kilotons), Selected Countries, 19+80-2014
  • 1.2 Current State of MaaS development
    • 1.2.1 Deployment Status
      • Case Study: Whim
      • Case Study: UbiGo
    • 1.2.2 Investments in MaaS
      • Table 1.6: Prominent Investments in MaaS Vendors & Related Vendors
      • Figure 1.7: MaaS Investment Funding by Nation, ($m), Selected Countries, to Date
      • Figure 1.8: MaaS Investment Funding ($m) by Segment, to Date
    • 1.2.3 The Blockchain Opportunity
      • Figure 1.9: MaaS Stakeholder Ecosystem
  • 1.3 MaaS Impact Assessment
    • 1.3.1 Summary
      • Table 1.10: MaaS Impact Assessment
      • Table 1.11: MaaS Impact Assessment Heatmap Key
      • Table 1.12: Impact Assessment Methodology
    • 1.3.2 MaaS Impact Assessment Commentary
      • i. Drivers & Driving Experience
      • Table 1.13: Drivers & the Driving Experience Heatmap
      • ii. Congestion & Environmental Impact
      • Table 1.14: Congestion & Environmental Impact Heatmap
      • iii. Impact on Car Manufactures
      • Table 1.15: Impact on Car Manufactures Heatmap
      • iv. Infrastructure Impact
      • Table 1.16: Infrastructure Impact Heatmap
      • v. Transport Provider Business Models
      • Table 1.17: Impact on Transport Provider business Models Heatmap
  • 1.4 Trends & Constraints to MaaS Adoption
    • 1.4.1 Key Trends
    • 1.4.2 Key Constraints
  • 1.5 Open Policy & Regulatory Requirements
    • 1.5.1 The Need for Regulation
      • Case Study: Uber London
      • Case Study: San Francisco Scootersharing
      • i. The Positive Role of Cities
    • 1.5.2 MaaS Implementation Blueprint
      • Figure 1.18: Juniper MaaS Implementation Blueprint
  • 1.6 Future Outlook
    • 1.6.1 MaaS Business Model
      • i. The Subscription Model
      • ii. The Ad Hoc Model
      • iii. Juniper's View
    • 1.6.2 MaaS Benefits for Consumers & Businesses
      • i. Time Savings
      • ii. Fuel Savings
      • iii. Productivity Increases
      • iv. Methodology
    • 1.6.3 MaaS Opportunities for Insurance Providers

2. MaaS Segment Analysis

  • 2.1 Introduction & Analysis Heatmap
    • Figure 2.1: MaaS Segment Mapping
    • Table 2.2: MaaS Segment Impact Analysis Heatmap
  • 2.2 Ridesharing
    • 2.2.1 User Impact
    • 2.2.2 Technology Impact
    • 2.2.3 Business Model Impact
    • 2.2.4 Infrastructure Impact
    • 2.2.5 Barriers to Implementation of MaaS
  • 2.3 Ticketing
    • Figure 2.3: Mobile & Online Transport Ticketing Users (m), Transaction Volume (m) 2014-2017
    • 2.3.1 User Impact
    • 2.3.2 Technology Impact
    • 2.3.3 Business Model Impact
    • 2.3.4 Infrastructure Impact
    • 2.3.5 Barriers to Implementation in MaaS
  • 2.4 Bikesharing
    • 2.4.1 User Impact
    • 2.4.2 Technology Impact
    • 2.3.3 Business Model Impact
    • 2.3.4 Infrastructure Impact
      • Figure 2.4: Station-Based Bikes versus Dockless Bikes, Share of Bikes Available versus Share of Trips, US
    • 2.4.5 Barriers to Implementation in MaaS
  • 2.5 AVs (Autonomous Vehicles)
    • Figure 2.5: Level 4/5 Autonomous Vehicles in Service (m), 2026
    • 2.5.1 User Impact
    • 2.5.2 Technology Impact
      • Figure 2.6: Velodyne LiDAR Systems
    • 2.5.3 Business Model Impact
    • 2.5.4 Infrastructure Impact
    • 2.5.5 Barriers to Implementation in MaaS
  • 2.6 EVs (Electric Vehicles)
    • 2.6.1 User Impact
      • Figure 2.7: Average Price of Gasoline/Diesel per US Gallon, January 2010-May 2018, ($)
    • 2.6.2 Technology Impact
    • 2.6.3 Business Model Impact
    • 2.6.4 Infrastructure Impact
      • i. Barriers to Implementation of MaaS
  • 2.7 On Demand Transport Services
    • 2.7.1 User Impact
    • 2.7.2 Technology Impact
    • 2.7.3 Business Model Impact
    • 2.7.4 Infrastructure Impact
    • 2.7.5 Barriers to Implementation in MaaS

3. Regional Analysis & MaaS City Ranking

  • 3.1 MaaS: Regional Readiness Analysis
    • Table 3.1: MaaS Regional Readiness Analysis Heatmap
    • 3.1.1 North America
      • i. Supporting Ecosystem
      • ii. Existing MaaS Efforts
      • iii. MaaS Growth Prospects
      • iv. Barriers to Further Growth
    • 3.1.2 Latin America
      • i. Supporting Ecosystem
      • ii. Existing MaaS Efforts
      • iii. MaaS Growth Prospects
      • iv. Barriers to Further Growth
    • 3.1.3 West Europe
      • i. Supporting Ecosystem
      • ii. Existing MaaS Efforts
      • iii. MaaS Growth Prospects
      • iv. Barriers to Further Growth
    • 3.1.4 Central & East Europe
      • i. Supporting Ecosystem
      • ii. Existing MaaS Efforts
      • iii. MaaS Growth Prospects
      • iv. Barriers to Further Growth
    • 3.1.5 Far East & China
      • i. Supporting Ecosystem
      • ii. Existing MaaS Efforts
      • iii. MaaS Growth Prospects
      • iv. Barriers to Further Growth
    • 3.1.6 Indian Subcontinent
      • i. Supporting Ecosystem
      • ii. Existing MaaS Efforts
      • iii. MaaS Growth Prospects
      • iv. Barriers to Further Growth
    • 3.1.7 Rest of Asia Pacific
      • i. Supporting Ecosystem
      • ii. Existing MaaS Efforts
      • iii. MaaS Growth Prospects
      • iv. Barriers to Further Growth
    • 3.1.8 Africa & Middle East
      • i. Supporting Ecosystem
      • ii. Existing MaaS Efforts
      • iii. MaaS Growth Prospects
      • iv. Barriers to Further Growth
  • 3.2 MaaS: Top 10 Leading Cities
    • Table 3.4: Top 10 MaaS Cities Rankings Methodology
    • Table 3.4: Top 10 MaaS City Rankings

4. MaaS Competitive Landscape & Leaderboard

  • 4.1 Vendor Analysis & Leaderboard
    • 4.1.1 Introduction
    • 4.1.2 Stakeholder Assessment Criteria
      • Table 4.1: MaaS Player Capability Criteria
      • Figure 4.2: MaaS Stakeholder Leaderboard
      • Table 4.3: MaaS Leaderboard Scoring
    • 4.1.3 Vendor Groupings
      • i. Established Leaders
      • ii. Leading Challengers
      • iii. Disruptors & Emulators
    • 4.1.4 Limitations & Interpretation
  • 4.2 Movers & Shakers
  • 4.3 Vendor Profiles
    • 4.3.1 Citymapper
      • i. Corporate
      • Table 4.4: Citymapper Funding Rounds
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.2 CTS (Cubic Transportation Systems)
      • i. Corporate
      • Table 4.5: Cubic Corporation Financial Snapshot, &m, 2015-2017
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.3 ESP Group
      • i. Corporate
      • Table 4.6: ESP Group Financial Snapshot, &m, 2015-2017
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.4 Fluidtime
      • i. Corporate
      • Table 4.7: Kapsch Group Financial Snapshot, &m, 2015-2017
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.5 Ioki
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • Table 4.8: Ioki Autonomous Bus
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.6 MaaS Global
      • i. Corporate
      • Table 4.9: MaaS Global Funding Rounds
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.7 Masabi
      • i. Corporate
      • Table 4.10: Masabi Funding Rounds
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.8 moovel
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.9 Moovit
      • i. Corporate
      • Table 4.11: Moovit Funding Rounds
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.10
      • i. Corporate
      • Table 4.12: Ridecell Funding Rounds
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.11 SkedGo
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 4.3.12 UbiGo
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities

2. Deep Dive Data & Forecasting Table of Contents

1. Introduction to MaaS

  • 1.1 Introduction
    • Figure 1.1: MaaS Primary Advantages
    • Figure 1.2: MaaS Segment Mapping

2. MaaS Market Sizing & Forecast Methodology

  • 2.1 Forecast Methodology
    • 2.1.1 Methodology
      • Table 2.1: MaaS Forecast Scenario Summary
      • Figure 2.2: Scenario Based Forecast Model
      • Figure 2.3: Maas Forecast Methodology
    • 2.1.2 Key Static Inputs
      • Figure 2.4: Static Forecast Inputs
    • 2.1.3 Key Scenario Variable Inputs
      • Figure 2.5: Variable Forecast Inputs
    • 2.1.4 Assumptions

3. Forecast Summary & Scenario Comparisons

  • 3.1 Scenario Comparisons
    • 3.1.1 MaaS Users
      • Figure & Table 3.1: Number of MaaS Users (m), Split by Scenario 2018-2023
      • Figure 3.2: Number of MaaS Users, US, (m), Split by Scenario, 2023
    • 3.1.2 MaaS Revenues
      • Figure & Table 3.3: Total Revenues from MaaS ($m), Split by Scenario 2018-2023

4. MaaS Scenario 1: Low Adopting Market Forecasts

  • 4.1 Adoption & Revenue Forecasts
    • 4.1.1 Scenario 1 - Number of MaaS Users
      • Figure & Table 4.1: Scenario 1 - Number of MaaS Users (m) Split by 8 Key Regions 2018-2023
    • 4.1.2 Scenario 1 - MaaS Subscribers
      • Figure & Table 4.2: Scenario 1 - Number of MaaS Users who Subscribe to the SErvice (m) Split by 8 Key Regions 2018-2023
    • 4.1.3 Scenario 1 - MaaS Subscription Revenues
      • Figure & Table 4.3: Scenario 1 - Total MaaS Subscription Revenues ($m) Split by 8 Key Regions, 2018-2023
    • 4.1.4 Scenario 1 - Ad Hoc MaaS Users
      • Figure & Table 4.4: Scenario 1 - Total Number of MaaS Users who Pay for the Service on an Ad Hoc Basis (m) Split by 8 Key Regions 2018-2023
    • 4.1.5 Scenario 1 - Ad Hoc MaaS Revenues
      • Figure & Table 4.5: Scenario 1 - Total MaaS Ad Hoc Revenues (&m) Split by 8 Key Regions 2008-2023
    • 4.1.6 Scenario 1 - Total MaaS Revenues
      • Figure & Table 4.6: Scenario 1 - Total MaaS Revenues ($m) Split by 8 Key Regions 2018-2023
  • 4.2 Savings Forecasts
    • 4.2.1 Scenario 1 - MaaS Time Savings
      • Figure & Table 4.7: Scenario 1 - Total Time Saved via MaaS Compared with Private Car Journeys (Million Hours) Split by 8 Key Regions 2018-2023
    • 4.2.2 Scenario 1 - MaaS Fuel Cost Savings
      • Figure & Table 4.8: Scenario 1 - Total Fuel Cost Savings from MaaS Implementation (&m) Split by 8 Key Regions 2018-2023

5. MaaS Scenario 2: Medium Adoption market Forecasts

  • 5.1 Adoption & Revenue Forecasts
    • 5.1.1 Scenario 2 - Number of MaaS Users
      • Figure & Table 5.1: Scenario 2 - Number of MaaS Users (m) Split by 8 Key Regions 2018-2023
    • 5.1.2 Scenario 2 - MaaS Subscribers
      • Figure & Table 5.2: Scenario 2 - Number of MaaS Users who Subscribe to the Service (m) Split by 8 Key regions 2018-2023
    • 5.1.3 Scenario 2 - MaaS Subscription Revenues
      • Figure & Table 5.3: Scenario 2 - Total MaaS Subscription Revenues ($m) Split by 8 Key Regions 2018-2023
    • 5.1.4 Scenario 2 - AD Hoc MaaS Users
      • Figure & Table 5.4: Scenario 2 - Total Number of MaaS Users who Pay for the Service on an Ad Hoc Basis (m) Split by 8 Key Regions 2018-2023
    • 5.1.5 Scenario 2 - Ad Hoc MaaS Revenues
      • Figure & Table 5.5: Scenario 2 - Total MaaS Ad Hoc Revenues ($m) Split by 8 Key Regions 2018-2023
    • 5.1.6 Scenario 2 - Total MaaS Revenues
      • Figure & Table 5.6: Scenario 2 - Total MaaS Revenues ($m) Split by 8 Key Regions 2018-2023
  • 5.2 Savings Forecasts
    • 5.2.1 Scenario 2 - MaaS Time Savings
      • Figure & Table 5.7: Scenario 2 - Total Time Saved via MaaS Compared with Private car Journeys (Million Hours), Split by 8 Key Regions 2018-2023
    • 5.2.2 Scenario 2 - MaaS Fuel Cost Savings
      • Figure & Table 5.8: Scenario 2 - Total Fuel Cost Savings from MaaS Implementation (&m), Split by 8 Key Regions 2018-2023

6. MaaS Scenario 3: High Adoption Market Forecasts

  • 6.1 Adoption & Revenue Forecasts
    • 6.1.1 Scenario 3 - Number of MaaS Users
      • Figure & Table 6.1: Scenario 3 - Number of MaaS Users (m), Split by 8 Key Regions 2018-2023
    • 6.1.2 Scenario 3 - MaaS Subscribers
      • Figure & Table 6.2: Scenario 3 - Total Number of MaaS Users who Subscribe to the Service (m) Split by 8 Key Regions 2018-2023
    • 6.1.3 Scenario 3 - MaaS Subscription Revenues
      • Figure & Table 6.3: Scenario 3 - Total MaaS Subscription Revenues ($m) 2018-2023, Split by 8 Key Regions 2018-2023
    • 6.1.4 Scenario 3 - Ad Hoc MaaS Users
      • Figure & Table 6.4: Scenario 3 - Total Number of MaaS Users who Pay for the Service on an Ad Hoc Basis (m) Split by 8 Key Regions 2018-2023
    • 6.1.5 Scenario 3 - Ad Hoc MaaS Revenues
      • Figure & Table 6.5: Scenario 3 - Total MaaS Revenues ($m) Spliut by 8 Key Regions 2018-2023
    • 6.1.6 Scenario 3 - Total MaaS Revenues
      • Figure & Table 6.6: Scenario 3 - Total MaaS Revenues ($m) Split by 8 Key Regions 2018-2023
  • 6.2
    • 6.2.1 Scenario 3 - MaaS Time Savings
      • Figure & Table 6.7: Scenario 3 - Total Time Saved via MaaS Journeys Compared with Private Car (Million Hours), Split by 8 Key Regions 2018-2023
    • 6.2.2 Scenario 3 - MaaS Fuel Cost Savings
      • Figure & Table 6.8: Scenario 3 - Total Fuel Cost Reduction from MaaS implementation ($m), Split by 8 Key Regions 2018-2023
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