Bibliographic record
Abstract
Purpose The purpose of this paper is to examine how domestic airlines benefit when they have code sharing arrangements with international carriers. Design/methodology/approach The data for this research study have been collected primarily from three sources. The first database, the digest of statistics no. 400 is from International Civil Aviation Organization (ICAO) based in Montreal, Canada. The second source of data comes from the Airline Business database. The third source of data for this research study is from Official Airline Guide (OAG). Ten years of data from 1994 to 2004 are collected from the databases of ICAO, Airline Business and also from individual airlines. Data such as the revenue passenger miles (RPMs) and load factor are obtained from the ICAO database and data such as alliance pattern are culled from the Airline Business database. Findings This research study reveals that code sharing agreements between a domestic and international airline will benefit the former by way of increased RPMs, passenger load factor (PLF), and market share. However, the coefficients of the hypothesized variables suggest that the initial gains achieved by the domestic airlines by way of increased RPMs start to erode in the long run. Thus, a domestic airline must form a code sharing agreement with an international airline at the earliest, so as to get the initial increase in RPMs. The effect of code sharing on the market share of domestic airlines is explicit and consistent throughout this research study. The second dimension in the code sharing is the multiple alliances between domestic and international airlines. Multiple alliances refer to an airline having more than one code sharing agreement with international carriers. The third factor in this sequence of hypotheses is equity investment by international carriers in domestic airlines. The relationship between equity investment and its influence on the performance of the targeted firm is always an interesting topic explored by both the academic researchers and practitioners. However, in this study, the regression results do not support the hypothesis. That means that mere equity investment by international carriers in domestic airlines may not result in increased RPMs, load factor and the market share for domestic airlines. The interesting finding in this particular section is the influence of the large size of the alliance partners on all the three dependent variables; RPMs, PLF, and the market share. Therefore, we can conclude that if both the airlines are large enough and they form code sharing agreements, then this may result in increased RPMs, PLFs, and market share for the domestic airlines. Similarly, the study supports the premise that if the partners are unequal, then the domestic airlines may not be able to increase the RPMs, load factor, and the market share. Originality/value This paper reveals that code sharing arrangements reached earlier in the competition is better as the benefits tend to reduce after a certain period of time.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".