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Record W2339612774 · doi:10.4172/1204-5357.s1-005

Strategy to Increase the Stateâs Role in the Business Process Management on the Airport Service Market

2015· article· en· W2339612774 on OpenAlexvenueno aff
Gubenko AV Ksenofontova TY

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsConsolidation (business)AdaptabilityProcess (computing)Industrial organizationBusinessService (business)Process managementComputer scienceMarketingEconomicsFinance

Abstract

fetched live from OpenAlex

The article identifies the causes and factors that prove the urgent need to increase the state’s role in developing and implementing strategies to introduce innovative technologies in the management of Russian airports. Solution of the problem of the international market entry and maintain there the required level of competitiveness of Russian airlines of various sizes requires the selection of optimal forms and mechanisms targeted on improving adaptability and competitiveness in the international systems of constraints and dynamics of indicators of demand for the services of the air carriers. This in the turn requires the substantiation of the choice of strategic directions of development of companies operating in the transport market, the development of tools that determine the characteristics of the relationship between marketing strategy and conditions for its implementation. In this connection, the authors examined the structure of the innovation cycle management and functions assigned to the recommended to the creation state airport management company. The article also refined the forms of airlines consolidation depending on the subject of cooperation, systematized agreements benefits for the joint operation of airlines for the passenger and the carrier. The authors consider methods to improve the efficiency of Russian air transportation market, including by reducing tariffs and the introduction of the economic process of airline low-cost carriers business models.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.188

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.052
GPT teacher head0.253
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2015
Admission routes1
Has abstractyes

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