Relationships among service quality, corporate image, customer satisfaction, and behavioral intention for the elderly in high speed rail services
Bibliographic record
Abstract
SUMMARY Since the Taiwan High Speed Rail operations, Taiwan's transportation market entered into a new era. Because of its competitive service of speed, convenience, environmental concerns and comfort, the High Speed Rail has not only made significant changes but has played a significant role in Taiwan's transportation. However, Taiwan now is an aging society. Due to the physical constraints among the elderly, demands to redesign the traffic system and maintain transportation safety are essential considerations. In the current market, Taiwan's transportation construction is facing fewer barriers; however, it must still improve, especially considering the health of the elderly. Thus, this study investigates elderly passengers' demands and further examined the relationships among service quality, corporate image, customer satisfaction, and behavioral intention. According to empirical analytical results based on structural equation modeling (N = 341), satisfaction directly affected travel behaviors, while service quality and corporate image played indirect roles. In addition, service quality plays a significant role on the effect of satisfaction. This study provides empirical evidence to indicate the quality of the accessible environment affects not only the effectiveness and efficiency of service quality, but also, the corporate image. The results provide valuable references for critically managing the elderly's usage of the high speed rail transportation service. Copyright © 2011 John Wiley & Sons, Ltd.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".