An Investigation into Mobility Tool Ownership and Mode Choice Behavior of High-Rise Condo Residents - a Case Study of the Greater Toronto and Hamilton Area
Bibliographic record
Abstract
Decreasing single occupancy vehicle (SOV) use not only reduces the economic burden of congestion but also reduces the need for parking, decreases development costs, and benefits the environment by reducing greenhouse gas (GHG) emissions.This thesis aims to reduce SOV trips among high-rise condominium residents in the Greater Toronto and Hamilton Area.A Stated Preference (SP) survey was conducted to examine mode choice and mobility tool ownership behaviors.Various multinomial and mixed logit models were estimated to identify the factors influencing mode choice and understand the effectiveness of condospecific transportation demand management (TDM) policies.Moreover, a trivariate ordered probit model was estimated to reveal factors affecting mobility tool ownership.The results show that the building's geographical location, tenure status, and parking availability significantly affect car ownership.Additionally, TDM policies, including an innovative parking policy, transit fare incentives, the provision of an e-bike share station, and membership discounts, are effective in encouraging residents to shift toward active modes and public transportation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".