Shared Mobility - Australia & Oceania

  • Australia & Oceania
  • Australia & Oceania is projected to witness a significant rise in revenue in the Shared Mobility market, which is expected to reach US$22,840.00m by 2024.
  • It is projected to show an annual growth rate of 2.15%, culminating in a projected market volume of US$25,400.00m by 2029.
  • The largest market in the region is Flights, which is expected to reach a projected market volume of US$12,690.00m by 2024.
  • Additionally, the number of users in the Public Transportation market is expected to amount to 21,320.00k users by 2029.
  • The user penetration is expected to be 69.4% in 2024 and 74.2% by 2029.
  • The average revenue per user (ARPU) is expected to be US$758.30.
  • Furthermore, the region is expected to generate 78% of total revenue through online sales by 2029.
  • It is noteworthy that, in global comparison, China is expected to generate the most revenue in this market, amounting to US$365bn in 2024.
  • Australia's shared mobility market is seeing a rise in electric bike and scooter rentals as cities prioritize sustainable transportation options.

Key regions: United States, Saudi Arabia, Germany, Malaysia, India

 
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Analyst Opinion

The Shared Mobility market in Australia & Oceania has been experiencing significant growth and evolution in recent years.

Customer preferences:
Customers in Australia & Oceania are increasingly embracing shared mobility services due to the convenience, cost-effectiveness, and environmental benefits they offer. The younger generation, in particular, is more inclined towards shared mobility options as they prioritize experiences over ownership.

Trends in the market:
In Australia, ride-hailing services have become extremely popular, with major players expanding their operations to cover more cities and regions. Additionally, the electric scooter market is gaining traction in countries like New Zealand, offering a sustainable transportation alternative in urban areas. Car-sharing services are also on the rise, catering to individuals who prefer occasional access to a vehicle without the burden of ownership.

Local special circumstances:
The unique geography of Australia & Oceania, with vast distances between cities and limited public transportation options in certain areas, has created a demand for flexible and on-demand mobility solutions. This has led to the rapid growth of shared mobility services as a convenient and efficient way to bridge transportation gaps.

Underlying macroeconomic factors:
The growing urban population, increasing traffic congestion, and rising environmental concerns are driving the shift towards shared mobility in Australia & Oceania. Government support for sustainable transportation initiatives, along with advancements in technology, are further propelling the development of the Shared Mobility market in the region.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of car rentals, ride-hailing, taxi, car-sharing, bike-sharing, e-scooter-sharing, moped-sharing, trains, buses, public transportation, and flights.

Modeling approach:

Market sizes are determined through a bottom-up approach, building on a specific rationale for each market. As a basis for evaluating markets, we use financial reports, third-party studies and reports, federal statistical offices, industry associations, and price data. To estimate the number of users and bookings, we furthermore use data from the Statista Consumer Insigths Global survey. In addition, we use relevant key market indicators and data from country-specific associations, such as demographic data, GDP, consumer spending, internet penetration, and device usage. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, ARIMA, which allows time series forecasts, accounting for stationarity of data and enabling short-term estimates. Additionally, simple linear regression, Holt-Winters forecast, the S-curve function and exponential trend smoothing methods are applied.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change.

Overview

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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