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Record W1504676404 · doi:10.54648/aila2014011

Ray of Hope for Airline Alliances: Consideration of Out of Market Efficiencies by the European Commission

2014· article· en· W1504676404 on OpenAlexaboutno aff
M P Ram Mohan

Bibliographic record

VenueAir and Space Law · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsCommissionAllianceRevenueBusinessArgument (complex analysis)FinancePolitical scienceLaw

Abstract

fetched live from OpenAlex

The article will analyze the application of 'out of market efficiencies' to airline alliance agreements by the European Commission. The Commission in May 2013 issued a decision in relation to the revenue-sharing joint venture on certain routes offered by Air Canada, United Airlines, and Lufthansa (who are all members of Star Alliance). This decision is the first instance where the Commission accepted the argument of out of market efficiencies. Generally, the assessment of efficiencies by the Commission is confined to 'in market efficiencies' i.e., the markets where concerns were identified by the Commission. Out of market efficiencies are efficiencies which are generated on the market other than the markets where concerns were identified by the Commission. According to the standard test set out by the Commission in its Guidelines, efficiencies on other markets can be accepted where: (i) two markets are related; and (ii) group of consumers affected and benefitting are substantially the same. The Parties contended that the cooperation created efficiencies on the Frankfurt-New York route (market on which Commission raised concerns) and on other related behind and beyond routes (e.g., Prague-Frankfurt-New York or Frankfurt-New York-Seattle). In its decision the Commission broadened the standard test in that it did not require the Parties to demonstrate that the groups of consumers travelling on the Frankfurt-New York route and the related routes are 'substantially the same'. It was sufficient for the parties to demonstrate 'considerable commonality' between passengers travelling on the route of concern and the related behind and beyond route. This article also considers whether the Commission is justified in restricting the application of out of market efficiencies only to those markets which are related to the relevant market.

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 imitation

Not 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.

metaresearch head score (Codex)0.048
metaresearch head score (Gemma)0.096
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.096
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0080.016
Scholarly communication0.0330.022
Open science0.0030.011
Research integrity0.0180.014
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.027
GPT teacher head0.227
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2014
Admission routes1
Has abstractyes

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