The impact of service quality, ticket price policy and passenger trust on airport train passenger loyalty
Bibliographic record
Abstract
This research aims to know and analyze the direct and indirect impacts of service quality and ticket price policy on trust and also its impact on the passenger loyalty of Soekarno-Hatta Airport Train, Cengkareng, Indonesia. The main problems are that the service quality provided by Soekarno-Hatta Airport Train is not maximal and that the ticket price of the Soekarno-Hatta Airport Train is relatively expensive because the passengers still have to use another transportation mode to go to the station. This research uses a quantitative approach with Structural Equation Modelling, assisted by the Lisrel program with a sample of as many as 150 passengers. The results of this research prove that service quality and ticket price policy have both direct and indirect impacts on passenger loyalty through the mediation of passenger trust. The key finding is that the policymakers can take advantage of the findings of this research, especially the crucial aspects in the questionnaires on service quality and ticket price policy which are considered not optimal by the passengers of Soekarno-Hatta Airport Train. So, passenger loyalty can be enhanced through the improvement of service quality and ticket price policy supported by passenger trust.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".