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Record W3004436101

Maritime Networks: a source of competitiveness for shipping lines. In : International Handbook of Maritime Business

2010· preprint· en· W3004436101 on OpenAlexaff
Antoine Frémont

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2010
Typepreprint
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsMinistère des Transports
Fundersnot available
KeywordsCompetitor analysisDominance (genetics)BusinessInternational shippingContainerizationInternational tradeIndustrial organizationHierarchyOrder (exchange)East AsiaEconomic geographyTelecommunicationsEconomyComputer scienceGeographyChinaEngineeringMarketingEconomicsPolitical scienceMarket economyFinanceContainer (type theory)Law
DOInot available

Abstract

fetched live from OpenAlex

The generally accepted view nowadays appears to be that as a result of the impact of containerization shipping lines propose similar maritime services with identical vessels. As the maritime companies are unable to create a comparative advantage on the sea, they attempt to do so on inland services. However, it was by developing new maritime capacity that the Asian shipping lines asserted themselves in the 1980s and new European shipping lines such as MSC or CMA asserted themselves as very large global carriers in the 1990s and 2000s. Our hypothesis is that the maritime line remains the core activity of the shipping lines. The maritime networks of the shipping lines are not the same from the geographical standpoint. The competitiveness of a shipping line depends partly on its capacity to operate a maritime network which is differentiated from that of its competitors. Once we have justified our hypothesis, we shall propose a method for studying the networks of shipping lines using our database on Weekly Containerized Transport Capacity (WCTW). We shall then show that the Asian shipping lines, which are grouped together in large alliances, differ from the European shipping lines Maersk, MSC and CMA. This leads us to propose a historical interpretation, based on the unequal power of the maritime networks, in order to explain the upheavals that have occurred in the global hierarchy of shipping lines, firstly in favour of the Asian shipping lines in the 1980s which gave way, from the 1990s, to the new dominance of 3 European shipping lines - Maersk, MSC and CMA.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.213
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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