The influence of bus service satisfaction on university students' mode choice
Bibliographic record
Abstract
Summary The purpose of this study was to determine the relationship between bus service satisfaction and the transport mode of choice among university students in Qatar. The degree of bus service satisfaction was collected directly from questionnaire surveys, in which university students were asked questions in relation to their satisfaction with the bus service they used and their transport mode of choice. These questions were categorized into three factors according to confirmatory factor analysis: service at bus stops, service of busses, and service of drivers. Furthermore, the students were asked which mode of transport they used given the choice between public and private transport. This study presents a structural equation model to determine how much bus service satisfaction affects people's decisions about their transport mode. The results from the analysis showed that three key factors—namely, service at bus stops, service of busses, and service of bus drivers—were strongly correlated to the mode of choice. In particular, the bus stop was strongly associated with ease of use, shade, cleanliness, safety, and crowdedness level, while the bus itself influenced reliability, travel time, and frequency. Complying with traffic laws and the driver's attitude were also important contributors to the level of bus service satisfaction. Ultimately, this study will be beneficial for policy/decision‐makers. It will allow them to determine what needs to be accomplished to encourage people to use public transportation. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".