Investigating the Choice Making Behavior of Transport Users: The Role of Psychology and Choice Contexts in Commuting Mode Choice Process
Bibliographic record
Abstract
Using the Theory of Interpersonal Behaviour as the structural framework, a Structural Equations Modeling approach is used to investigate the relationships between the attitudinal, affective and habitual behaviours displayed by transportation users in Toronto and their role in determining the primary mode choice for work trips. A purposely collected data on commuting mode choice behaviour in Toronto was used. It was found that car users associated private transportation with a higher expectancy but attached a higher value to transit. This indicates that while they find cars to be the better mode for work trips currently, they would switch to transit given comparable levels of service to the private automobile. Transit users, on the other hand, attached a higher value to the car implying that they would switch modes provided no economic or geographical limitations. Car users were also found to have strong positive correlations to habit formation with respect to their own mode. This has significant policy implications – once formed, these habits seem very hard to break. As such, it is imperative that the transit network make a concerted effort to attract young users who haven’t yet used automobiles to a significant degree, lest they fall into the same routine that current car users are in.
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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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".