Perception of Travel Agents Towards Amadeus And Galileo Global Distribution System
Bibliographic record
Abstract
This study was conducted to assess the perception of travel agents towards Amadeus and Galileo Global Distribution System in some selected travel agencies in Lagos Island, Lagos state. Two hundred and forty-three (243) questionnaires were administered while two hundred and seven (207) were retrieved. The first hypothesis was tested using Pearson chi-square value which was less than 0.05 (p=0.000) thereby rejecting the null hypothesis which implies that there is a significant relationship between using Global Distribution System and Travel agencies. Result also reveals that the Pearson chi-square value of the second hypothesis is less than 0.05 (p=0.000) thereby rejecting the null hypothesis which implies that Global Distribution System contributes to the development of travel agencies. Therefore, Global Distribution System helps in the development of travel agencies. Other findings are; Amadeus Global Distribution System is used more than its counterpart Galileo Global Distribution System. Also, Global Distribution System has helped broaden staff knowledge towards reservation and hotel bookings. Based on these findings, it is hereby concluded that Global Distribution System Amadeus is quite prevalent and more used among the agents working with airlines; Global Distribution System Amadeus assumes the foremost position in relation to Galileo Global Distribution Systems, primarily due to the evolution of software that is tailored specially to meet the desires of individual users, allowing the availability and exchange of quality information to enormous number of users, thus linking tourism related companies in the global networks.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".