Shared Mobility - Montenegro

  • Montenegro
  • Montenegro is expected to witness an impressive growth in the Shared Mobility market in the coming years.
  • By 2024, the projected revenue in this market is estimated to reach US$78.97m.
  • The market is expected to grow at an annual growth rate (CAGR 2024-2029) of 3.04%, resulting in a market volume of US$91.71m by 2029.
  • Public Transportation are the largest market in the market and are projected to reach a market volume of US$44.11m by 2024.
  • The number of Public Transportation users is expected to increase to 492.60k users by 2029.
  • User penetration is estimated to be 81.7% in 2024 and is projected to reach 87.0% by 2029.
  • The average revenue per user (ARPU) is expected to be US$246.60.
  • In the Shared Mobility market, it is projected that 41% of the total revenue will be generated through online sales by 2029.
  • When compared globally, China is expected to generate the most revenue in 2024, with a projected revenue of US$365bn.
  • Montenegro's shared mobility market is seeing growth in electric scooter rentals, particularly in coastal cities such as Budva and Kotor.

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

 
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Analyst Opinion

In Montenegro, the Shared Mobility market is experiencing significant growth and evolution.

Customer preferences:
Customers in Montenegro are increasingly valuing convenience, flexibility, and cost-effectiveness when it comes to transportation options. Shared Mobility services such as ride-hailing, bike-sharing, and car-sharing are gaining popularity as they offer on-demand access to transportation without the hassle of ownership or maintenance.

Trends in the market:
One notable trend in the Shared Mobility market in Montenegro is the rise of electric scooters as a popular mode of transportation in urban areas. This trend aligns with the global shift towards sustainable and eco-friendly mobility solutions. Additionally, the integration of digital platforms and mobile applications for booking and payment purposes is streamlining the user experience and contributing to the market's growth.

Local special circumstances:
Montenegro's unique geography, characterized by its coastal areas and mountainous regions, presents both challenges and opportunities for the Shared Mobility market. The demand for transportation varies between urban centers, tourist destinations, and rural areas, leading to the need for diverse mobility solutions tailored to each location. Furthermore, the seasonal nature of tourism in Montenegro influences the market dynamics, with fluctuations in demand during peak and off-peak periods.

Underlying macroeconomic factors:
The growing tourism industry in Montenegro, driven by its picturesque landscapes and cultural attractions, is fueling the demand for Shared Mobility services. As more visitors flock to the country, there is a corresponding need for efficient and convenient transportation options, which Shared Mobility providers are well-positioned to offer. Additionally, the increasing urbanization and changing lifestyle preferences among Montenegrin residents are contributing to the expansion of the Shared Mobility market as people seek alternatives to traditional car ownership.

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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