Psychological Influences on Bus Travel Mode Choice: A Comparative Analysis between Two Chinese Cities
Bibliographic record
Abstract
Psychological factors give an important influence on the behavior of travel mode choice, but the effects vary from different cities. To identify and explain the differences, this study makes a comparative analysis between two Chinese cities, Chongqing and Chengdu: a typical mountain city and a typical plain city. The sample is obtained by questionnaires containing 401 and 450 valid records of the two cities, respectively. The model used in this study is established based on the framework of the theory of planned behavior. The main work of this study has three aspects: (1) define the measured variables based on the combination of bus travel characteristics and the theory of planned behavior; (2) verify the model validity in both two cities; (3) make a comparative analysis on the two cities. According to the results, the validity of the theory framework and measured variables is verified; the perceived behavioral control plays the most important role in affecting the behavior of traveling by bus in both two cities; significant differences between the two cities are presented and explained.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".