Train Tickets - Hungary
Hungary- By ****, in Hungary is projected to generate a revenue of US$*****m in the Train Tickets market.
- This market is expected to show a Compound Annual Growth Rate (CAGR *********) of ****%, resulting in a projected market volume of US$*****m by ****.
- The projected number of users in the Train Tickets market is expected to amount to ****m users by ****.
- In ****, the user penetration is projected to be ****% and it is expected to reach ****% by ****.
- The average revenue per user (ARPU) is expected to amount to US$*****.
- By ****, **% of the total revenue in the Train Tickets market will be generated through online sales.
- It is noteworthy that, in global comparison, China is expected to generate the most revenue in this market, amounting to US$**bn in ****.
- Hungary's railway system is undergoing modernization efforts, with the introduction of new rolling stock and the renovation of existing infrastructure.
- Key regions:
- South America,
- Thailand,
- Germany,
- China,
- Malaysia
Definition:
The Train tickets market consists of tickets for long-distance travel or cross-regional travel by train. This includes country-specific providers of passenger rail transport such as Deutsche Bahn, Amtrak or National Rail. As a rule, travel for single passengers and groups or time-limited subscription based travel can be booked up to a year in advance. Tickets for public transport, for within a city or other local travel are not included.
Additional Information:
The main performance indicators of the Train tickets market are revenues, average revenue per user (ARPU), user numbers and user penetration rates. Additionally, online and offline sales channel shares display the distribution of online and offline bookings. The ARPU refers to the average revenue one user generates per year while the revenue represents the total booking volume. Revenues are generated through both online and offline sales channels and include exclusively B2C revenues and users for the above-mentioned markets. User numbers show only those individuals who have made a reservation, independent of the number of travelers on the booking. Each user is only counted once per year.
The booking volume includes all booked rides made by users from the selected region, regardless of where the ride took place.
For further information on the data displayed, refer to the info button right next to each box.
- Tickets for long-distance travel or cross-regional travel by train
- Time-limited subscription based travel
- Line service and regular train service
- All online and offline booked long-distance bus tickets regardless of the purchase channel
- Tickets for public transport, for within a city or other local travel
Revenue
Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Jun 2025
Source: Statista Market Insights
Most recent update: Jun 2025
Source: Statista Market Insights
Sales Channels
Analyst Opinion
Users
Most recent update: Jun 2025
Source: Statista Market Insights
Electrification of Railway
Global Comparison
Most recent update: Jun 2025
Source: Statista Market Insights
Methodology
Data coverage:
The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of train tickets.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.Key Market Indicators
Notes: Based on data from IMF, World Bank, UN and Eurostat
Most recent update: Jan 2025
Source: Statista Market Insights
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