Strategy to Increase the Stateâs Role in the Business Process Management on the Airport Service Market
Bibliographic record
Abstract
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.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".