Connections to global markets and supplies are a precondition for trade driven development, investments, and jobs. Here, we analyze how the global shipping network has evolved and the impact on countries position in the network over the last two decades.
The data reviewed here describe scheduled container shipping services between pairs of countries, capturing both the presence of a direct connection and the number of shipping lines operating on each bilateral link. We benefit from a unique dataset, the MDST Container Data Bank, which comprehensively captures all regular container shipping services, globally, for two full decades. The period has been characterized by a process of consolidation among shipping lines, while also seeing a continued growth of containerized trade.
The analysis compares two snapshots of the network, one from early 2006 and one from early 2026, redrawn using identical methods to permit visual comparison. The third chart displays the distribution of the number of direct partners per country in each year
The dataset enables an examination of the number of bilateral connections, and the intensity of those connections, expressed through shipping line counts. It also allows a comparison of how direct connectivity is distributed, and how the network’s structure has shifted.
Figure 1. Q1 2006 Liner Shipping Network
(Click on image for full resolution)
Source: Authors, based on data provided by MDST
Figure 2. Q1 2026 Liner Shipping Network
(Click on image for full resolution)
Source: Authors, based on data provided by MDST
The total number of countries included in the global liner shipping network rises from 174 in 2006 to 178 in 2026. Yet the number of direct bilateral connections falls from 2,444 to 2,243. A larger network with fewer direct links results in a lower density: the percentage of country pairs with a direct link decreased from 16.2% to 14.2%.
The main consequence is that trade between more than four out of five pairs of countries depends on transshipment, and this reliance becomes more pronounced over the two decades, as direct links thin out. For many smaller developing economies and small island states, which already sit at the lower end of the connectivity distribution, this shift heightens their dependence on intermediary hubs for access to global markets.
The average number of direct partners per country falls from 28.1 to 25.2, and the median declines from 22 to 17. These shifts are also visible in the histogram of degree distributions, where the 2026 curve sits to the left of the 2006 curve. More countries have fewer direct partners than they did twenty years earlier.
Figure 3. Number of direct connections per country, 2006 and 2026
The long tail of highly connected countries also shortens. In 2006, the United Kingdom had 117 direct partners, followed by Belgium and the United States. By 2026, the top position is held by Spain with 97, followed closely by the United States, China, and the Netherlands. The underlying cause for these trends is the process of consolidation in liner shipping, including mergers and acquisitions, which, combined with larger vessel sizes, encourages hub-and-spoke operations.
The range between the best and worst connected countries remains high. In both years the least connected countries have only one or two direct partners—these are mostly small island states. For these economies, direct maritime access is limited, and the decline in average connectivity globally is particular concern, as investments and new jobs require access to markets and to supplies.
Two different metrics are useful to describe service intensity in the network.
First, at the global level (across all bilateral links), the number of shipping lines per edge captures how intensively each country pair is served. The median remains unchanged at four liner companies, while the global average declines from 9.76 to 8.32 between 2006 and 2026. This combination indicates that the “typical” link is stable, but heavily served routes have lost choice over time, making the overall distribution more uneven.
Second, at the country level, we look at the average number of lines per direct connection for each country. In 2006, a typical country had 6.7 companies per link, with a median of five, but the range was wide: from countries averaging only two operators per route to a few with averages approaching twenty‑four. This reflected large differences in competitive conditions across countries, particularly disadvantaging many small developing economies and small island states. By 2026, this country‑level pattern largely persists, though with lower averages across much of the distribution. Some countries continue to enjoy routes served by many companies, while many others remain reliant on a small number of operators. The persistence of low per‑country averages for less connected economies underscores the continued unevenness of service availability in the global network.
A country’s position in the global liner shipping network depends on three key determinants.
Shipping lines may not only choose to call in a port, but also potentially invest through vertically integrated terminal operators. Once a terminal is operated by a shipping line-associated operator, it is more likely that its sister shipping line or alliance chooses this port – with the collateral that competitors my prefer not to call elsewhere.
The World Bank Group is supporting its clients to improve their position in the global shipping network to ensure that trade-driven development creates the necessary jobs. Performance indicators such as the Container Port Performance Index (CPPI) or the Logistics Performance Indicators (LPI) help identify potential improvements in the time ships and containers spend in port. The Global Supply Chain Stress Index (GSCSI) tracks supply chain stress, including port congestion. And the Port Reform Toolkit (PRT) helps governments and private investors identify options for public-private-partnerships and potential investments in partnership with the World Bank Group.
1 The “Containership Databank” provided by MDS Transmodal covers the world’s container carrying fleet of over 6,000 vessels based on known service deployment. Every vessel in service has multiple fields of information including operator, service, route, TEU capacity, service frequency, port rotation and much more. The Containership Databank also includes information about vessels on order and vessels removed from the commissioned fleet. Service deployment of individual vessels in the fleet frequently changes – the Containership Databank tracks these changes and is continually updated. Analyses that are regularly produced to provide advice for clients include: Capacity by operator, route and trade lane; Trends on a consistent quarterly basis since 2006; and Fleet analysis by operator, size, configuration of ships and fuel type.
The Containership Databank is among the sources for global indicators such as the Logistics Performance Indicators (LPI) developed by the World Bank; the Liner Shipping Connectivity Index (LSCI) developed in partnership with UNCTAD; and the Maritime Trade Connectivity Indicator (MTCI) developed in partnership with OECD/ITF.
The data reviewed here describe scheduled container shipping services between pairs of countries, capturing both the presence of a direct connection and the number of shipping lines operating on each bilateral link.
2 The liner shipping network is modelled as a weighted, undirected graph. Nodes represent countries (ISO‑3 codes). An edge exists between two countries if at least one liner shipping company operates a direct bilateral service; edge weight reflects the number of distinct shipping lines serving that pair.
Layout is generated using a force‑directed spring layout (NetworkX spring_layout) with parameters: k = 4.0, iterations = 500, random seed = 42, node_size = log(degree+1) × 75, weighted_degree = ∑ companies on all adjacent edges. Distances are weighted inversely to edge weights, so country pairs connected by many shipping lines are drawn closer together.
Images generated with Microsoft Copilot Analyst World Bank Group license.
3 Wang and Cullinane 2016; Fugazza and Hoffmann 2017; UNCTAD 2017; Jouili 2019; Ducruet 2020; Hoffmann and Hoffmann 2020; Guerrero et al. 2021; Mishra et al. 2021; Hoffmann and Hoffmann 2021; Wang, Dou, and Haralambides 2022; Hoffmann et al. 2024; Faure and Ducruet 2025; Canbay et al. 2026; Tsantis et al. 2026.
Source : World Bank
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