Consolidation in container liner shipping - Merger control aspects
Bibliographic record
Abstract
In 2005, three acquisitions of container liner ship ping companies were notified to the European Commission. The consolidation wave started with the public bid of the Danish company A.P. Moller Maersk (Maersk) for the DutchBritish shipping company Royal P&O Nedlloyd (PONL). Prior to the acquisition, Maersk was the leading global player, and by incorporating PONL, the fourth largest carrier in the world, it secured that posi tion. Some months later, the German tourism and logistics company TUI with its shipping subsidi ary HapagLloyd presented a public offer for the Canadian shipping company CP Ships. The bid resulted in the creation of the fifth largest player in the world in terms of capacity. Finally, the French shipping company CMA CGM acquired the French company Delmas, which although relatively small globally, has important activities in the Mediterra nean and Africa. Following the transaction, CMA CGM became the third largest global player. The European Commission approved all three trans actions (1). However the acquisitions of PONL and CP Ships were subject to conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".