Which One is More Attractive to Traveler, Taxi or Tailored Taxi? An Empirical Study in China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Apart from public transit, urban citizens nowadays seek for the personalized travel mode more frequently to satisfy their ever-increasing travel demand. Tailored taxi, based on mobile internet technology, such as Uber in America and Didi-taxi in China, characterizing by its high quality service, is now rapidly expanding its market penetration worldwide. The new emerging tailored taxi challenges the conventional taxi industry. This study concentrates on the personalized travel choices between taxi and tailored taxi. The personalized travel choice is determined by personal characteristic and trip characteristic. Using stated preference technique, a questionnaire is design to acquire data on travel preference. Then the binary logit model is proposed to describe the preferences of traveler's personalized travel behavior. Next, the sensitivity analysis is performed to discuss the influence of different preference factors and individual's characteristics. Finally, the general features of taxi and tailored taxi users are described and the differential development strategies are proposed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it