Domestic Waterborne - Hong Kong

Domestic waterborne or the Inland water transportation efficiently moves goods along rivers, lakes, and other inland waterways, known for its cost-effectiveness, especially for bulk goods. Suited for transporting coal, grain, and raw materials, barges can carry substantial cargo, making it economical for specific industries.

It is often part of intermodal networks, connecting with road and rail via rivers and canals, facilitating goods movement between different modes. Considered environmentally friendly, it generally has lower emissions per ton-mile, utilizing natural waterways as sustainable infrastructure.

Critical for industries along waterways, it supports moving raw materials to manufacturing centers and distributing finished goods, contributing to regional and global trade. In some regions, seasonality can impact inland water transportation, requiring measures like icebreakers in winter.

Investments in maintaining and improving infrastructure, such as dredging channels and maintaining locks, are crucial. Inland water transportation connects with coastal and seaport facilities, serving as transfer hubs between oceangoing vessels and smaller barges for inland transport.

Playing a vital role in moving goods and passengers, inland water transportation offers a sustainable and economically viable option for regions with navigable rivers and waterways.

Data coverage:

The data encompasses B2B enterprises. Figures are based on the activities of the Domestic Waterborne freight market.

Modeling approach:

Market sizes are determined through a bottom-up approach, building on specific predefined factors for each market. As a basis for evaluating markets, we use resources from the Statista platform as well as annual financial reports of the market-leading companies and industry associations, third-party studies and reports, national statistical offices, international institutions, and the experience of our analysts.

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, the S-curve function and exponential trend smoothing are well suited for forecasting transportation activity due to the non-linear growth of this market

Additional notes:

The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russia-Ukraine war are considered at a country-specific level. The market is updated twice a year.