Access mode choice behaviors of water transportation: a case of Bangkok
Bibliographic record
Abstract
Abstract This research attempted to analyze the impacts of the enhancement of access modes to the main water transportation mode in Bangkok, Thailand. In order to achieve this purpose, access mode choice behaviors are modeled using the probability distribution function (PDF) model, the multinomial logit (MNL) model, and the nested logit (NL) model. The study also attempted to analyze the catchment areas for different access modes and the factors affecting them. Factors affecting the extent of the catchment area such as main haul distance were evaluated. Based on survey results, service attributes such as access cost, in‐vehicle travel time, and out‐of‐vehicle travel time (OVTT) were found to have a significant impact on access mode choice behavior. Socioeconomic factors such as age, gender, income, and occupation were found to affect access mode choice behavior as well. Apart from these factors, trip departure time, egress mode used, and main haul distance were also found to affect access mode choice behavior. It was evaluated that the NL model is most suitable to model access mode choice behavior. A selected NL model was applied in order to predict the impacts of adopting different policies. It was found that reducing in‐vehicle travel time, waiting time and/or cost of the bus ride gave most significant impact on the enhancement of access modes. As results of this study, various methods have been suggested to enhance the access/egress service of the water transportation. Copyright © 2010 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".