Car-sharing - Luxembourg

  • Luxembourg
  • Luxembourg is expected to see a significant growth in revenue for the Car-sharing market, with a projected amount of US$13.68m by 2024.
  • The market is forecasted to exhibit an annual growth rate of 2.62% from 2024 to 2029, resulting in a market volume of US$15.57m by the end of 2029.
  • By 2029, the number of users in the Car-sharing market is expected to reach 48.51k users.
  • It is projected that the user penetration will increase from 6.1% in 2024 to 7.0% by 2029.
  • The average revenue per user (ARPU) is expected to be US$336.90.
  • Additionally, it is estimated that 93% of the total revenue will come from online sales by 2029.
  • It is worth mentioning that United States is expected to generate the highest revenue in the Car-sharing market globally, with a projected revenue of US$2,986m by 2024.
  • Luxembourg's Car-sharing market is thriving due to the country's high population density and strong environmental consciousness.

Key regions: Europe, Germany, India, United States, Malaysia

 
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Analyst Opinion

The Car-sharing market in Luxembourg has been experiencing significant growth in recent years.

Customer preferences:
One of the main reasons for this growth is the changing preferences of customers. With increasing concerns about environmental sustainability and the rising costs of car ownership, more and more people in Luxembourg are opting for car-sharing services. This allows them to have access to a vehicle when needed, without the hassle and expenses associated with owning a car.

Trends in the market:
The car-sharing market in Luxembourg is also benefiting from technological advancements. The availability of smartphone apps and GPS tracking systems has made it easier for customers to find and book car-sharing services. This convenience factor has contributed to the increasing popularity of car-sharing in the country.

Local special circumstances:
Luxembourg is a small country with a high population density, and this presents unique challenges for transportation. The limited space for parking and the high cost of owning a car make car-sharing an attractive alternative for many residents. Additionally, the country's strong focus on sustainability and environmental protection aligns well with the concept of car-sharing.

Underlying macroeconomic factors:
The strong economy of Luxembourg also plays a role in the growth of the car-sharing market. As the country continues to attract international businesses and professionals, the demand for flexible and affordable transportation options increases. Car-sharing provides a convenient solution for individuals who need to travel for work or leisure, without the commitment and expenses of owning a car. In conclusion, the car-sharing market in Luxembourg is growing due to changing customer preferences, technological advancements, local special circumstances, and underlying macroeconomic factors. As more people recognize the benefits of car-sharing, the market is expected to continue its upward trajectory in the coming years.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of car-sharing services.

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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