sales@contrivedatuminsights.com
CDI - Contrive Datum Insights

Mobility As A Service Maas MarketSize, Share & Industry Analysis, 2026-2034By Service TypeBy Business ModelBy Vehicle TypeBy End UserBy Revenue Model

Full title & scope — all 5 axes with their segments

Mobility As A Service Maas Market Size, Share & Industry Analysis, By Service Type (Ride Hailing, Car Sharing, Micromobility, Public Transit Integration & Ticketing, Parking & Multimodal Booking), By Business Model (B2C, B2B, B2G), By Vehicle Type (Cars & SUVs, Two-Wheelers, Buses & Shuttles, Bicycles & E-Scooters), By End User (Individual Commuters, Corporate & Business Travelers, Tourists & Visitors), By Revenue Model (Commission & Booking Fees, Subscription & Bundled Passes, Advertising & Data Monetization), and Regional Forecast, 2026-2034

Last Updated: Sep 29, 2026Report ID: CDI-248748
Methodology

How the estimates were built: data sources, modelling approach and validation steps.

Research approach

A market size is a claim about the world, and a claim is only as good as the route to it. Every study is built upward from units and prices — what is actually produced, sold or performed, at what it actually changes hands for — rather than from a headline figure divided downwards. Disclosed company revenue is then used to check that build, not to produce it.

Market size estimation, this report

Sizing began with trip volumes and average fares/subscription prices across ride-hailing, car-sharing, micromobility and transit-integration services in each metro area, aggregated up to city, then country, then regional totals. Vehicle deployment counts, average utilization rates and per-trip or per-pass pricing supplied the unit economics for each service line. This bottom-up build was then checked against disclosed revenue and gross booking figures reported by major platform operators in their public filings and investor disclosures. Where the bottom-up trip-volume estimate implied a materially different total than a company's disclosed regional revenue, the underlying utilization or pricing assumption was revisited and corrected rather than averaging the two figures together.

The four stages

The same sequence runs behind every published study, whatever the industry. The order matters as much as the steps: the segment axes are fixed before any number is collected, so the model is never reshaped to fit whatever data happens to turn up.

1
Scope and segmentation
2
Bottom-up sizing
3
Reconciliation
4
Forecast

What the build rests on, and what checks it

The two are not interchangeable. The left column produces the number; the right column tests it. When the check disagrees with the build, the answer is to find which bottom-up assumption is wrong — a unit count, a price, a take-up rate — not to split the difference between them.

The bottom-up build rests on
  • Volume actually transacted — units produced, installed, dispensed or procedures performed, counted at the level each is genuinely recorded
  • Realised pricing by tier and channel, rather than one blended average applied across the whole market
  • Take-up and frequency: how much of the addressable base buys, and how often it repeats
The build is checked against
  • Disclosed revenue of the companies serving the market, where filings separate it far enough to be usable
  • Buyer-side spending totals — capital budgets, procurement lines, or the output of the end market the product is bought against
  • Trade and customs flows, where the product crosses borders in a separately recorded form
Bottom-up sequence
1
Size the base
2
Apply take-up
3
Apply frequency
4
Apply realised price
Reconciliation sequence
1
Gather disclosed revenue
2
Strip out-of-scope lines
3
Compare against the build
4
Correct the assumption

Data sources

Published data establishes what happened. Only the people transacting in a market can say why, and what is about to change — so the two are collected separately and weighted differently.

Primary — who is interviewed
  • Commercial and product leadership at the companies that supply the market
  • Procurement and specification leads at the organisations that buy it
  • Distributors, integrators and channel partners, where the market is served indirectly
  • Regulatory and standards specialists, where approval governs what can be sold at all
Secondary — what is read
  • Company filings, annual reports and investor disclosure
  • Government statistics, customs records and regulatory registers
  • Trade association output and standards-body publications
  • Technical and peer-reviewed literature, where the market rests on a clinical or engineering claim
Primary research design, this report

Interviews focus on commercial and product leads at ride-hailing, car-sharing and micromobility operators, procurement officers at transit agencies and municipal transport authorities who commission integrated ticketing systems, channel partners that distribute mobility apps and hardware, and regulatory officials overseeing permitting and licensing for shared-mobility fleets. Sampling weights cities with mature multimodal ticketing programs in North America and Europe alongside high-growth metro markets across Asia Pacific and Latin America, since deployment scale and regulatory posture differ sharply between these groups. Findings are cross-checked against operator-reported ridership and revenue trends before being folded into the city-level sizing base.

Secondary sources, this report

Desk research draws on transit-agency procurement records and RFP disclosures for integrated ticketing contracts, vehicle-registration and micromobility-permit registers published by city transport departments, national statistical agency data on urban commuting patterns, and investor disclosures and SEC/prospectus filings from publicly listed ride-hailing and mobility operators. Where available, published app-download and active-user rankings from mobile analytics providers are used to sense-check relative platform scale across metro areas, alongside trade-body benchmarks on shared-mobility fleet utilization published by urban mobility associations, particularly in metro markets where permit data is published at a granular level.

Desk research runs across proprietary research databases including Factiva, OneSource and Hoovers alongside the public sources above. Modelling and statistical validation are run in SAS and SPSS.

Forecasting

The forecast is not a growth rate applied to a base year. It is built from the drivers that are expected to change, each one stated so a reader can disagree with it.

Forecast approach, this report

The forecast is built on continued rollout of city-level low-emission zones and congestion pricing, the pace at which transit agencies convert pilot ticketing integrations into permanent multimodal platforms, and the rate at which subscription and bundled-pass pricing replaces single-trip fares. Micromobility growth is normalized for the sharp deployment swings some cities saw during initial fleet-permitting rounds, treating early-year volatility as a rollout artifact rather than a repeatable growth pattern. The forecast holds if municipal appetite for consolidated mobility platforms continues at its current pace and vehicle-sharing permitting does not tighten materially in the largest metro markets.

Triangulation and validation

No figure enters a report on the strength of one source. Where the two sizing routes disagree the difference is not averaged away — the assumption causing it is isolated, tested against a third independent measure, and either corrected or carried forward as a stated limitation. Historical years are back-tested against the growth actually recorded before any forecast is allowed to run forward from them.

Validation, this report

Historical trip-volume and revenue growth for 2020 through 2024 were back-tested against operator-reported ridership recovery curves to confirm the build reproduces observed patterns rather than a smoothed trend line. Segment-level share shifts, particularly the move toward micromobility and transit-integration services, were reviewed against city-level fleet-permit counts and ticketing-contract announcements. Sensitivities were run against slower transit-agency procurement cycles and against a scenario where fuel or energy price swings alter per-trip pricing, to confirm the forecast band still holds under both conditions before the estimate was finalized.

Confidence and limitations

Where an estimate is firm and where it is not is stated rather than left to be inferred from the precision of the number.

Confidence framing, this report

Ride-hailing and car-sharing sizing is the firmest segment, anchored to fare and utilization data that major operators disclose with some regularity. Transit-integration and micromobility figures rest on thinner public reporting, since many municipal ticketing contracts and scooter-permit terms are not disclosed in detail, so those lines carry wider uncertainty. A shift in municipal permitting policy toward or away from shared-fleet operators, or a change in how transit agencies procure integrated ticketing, would be the most likely source of a future revision to this estimate.

Scope

Questions This Report Answers

6 questions
01

What is the market size and growth rate, globally and by region?

02

How is the market segmented, and which segments lead?

03

Which regions and countries are covered, and how do they compare?

04

What are the key drivers, restraints, opportunities and challenges?

05

Who are the leading companies operating in this market?

06

What trends are expected to shape the market through the forecast period?

Questions

Frequently Asked Questions

01What is the Mobility As A Service Maas Market projected to reach?

USD 1005 Billion by 2034, CAGR 12.35%

02What years does this report cover?

Study period 2020–2034, base year 2025, historical data 2020-2024, forecast period 2026-2034.

03Which regions are covered?

North America, Europe, Asia Pacific, Latin America, Middle East and Africa.

04Which region accounted for the largest market share?

North America leads with 32% of global revenue through 2034.

05Which segment leads the market?

Ride Hailing is the largest line by Service Type, at 42% of revenue in 2025.

06Who are the key companies profiled?

Uber Technologies, Inc., Lyft, Inc., Grab Holdings Limited, DiDi Global Inc., FREE NOW Group, Cabify, Ola (ANI Technologies Pvt. Ltd.), Moovit (An Intel Company), Citymapper Limited, Via Transportation, Inc., Lime (Neutron Holdings, Inc.), MaaS Global Oy (Whim). Full profiles are part of the paid report.

07Can the segmentation be customized?

Yes. Custom data cuts by geography, segment, or competitor set are available on request.

425+
Dedicated research analysts
1,200+
Reports published
Why CDI

Why choose CDI

Data triangulated across primary and secondary sources
Complimentary analyst call included with every purchase
Custom data cuts and post-purchase support available

Need this report shaped around your question?

The scope isn't fixed. Tell us what your team needs that the standard edition doesn't cover, and an analyst will come back on what can be adjusted and how long it takes, before you commit to anything.

Most licences include 30–60 hours of customization at no extra cost. See what each licence includes

Request customization

Additional Companies

Add competitors, suppliers or the peer set you benchmark against to the companies already covered.

Deeper Competitive View

Sharpen the landscape work around your own position: product line, channel, or a named shortlist of rivals.

Extra Segment Splits

Break the market down along an axis the standard scope doesn't cut it by, or go a level deeper inside one.

Application Focus

Narrow the analysis to the specific use cases and end users your team actually sells into.

Different Time Frame

Move the base year, or widen the historical and forecast windows the study is built on.

Country-Level Detail

Go below region level into the individual countries that matter to you, rather than the standard geography split.