A comprehensive study of household transportation expenditure, vehicle ownership, and usage patterns: tale of Canadian cities
Bibliographic record
Abstract
A hierarchy of decision exists across varying temporal scale in the context of automobile fleet decision of households. In the long term, the hierarchy includes the allocation of monetary resources to various consumer expenditure categories and long term vehicle fleet choices (number and type) while in the short-term, conditional on the availability of the fleet, decisions regarding vehicle usage (type and mileage) and travel destinations are considered. Thus, a combined exploration of these aspects would provide a more complete and clear understanding of the factors associated with these decision processes. Keeping that in mind, the objective of this dissertation is to contribute to the growing body of travel behavior literature by focusing on transport expenditure, vehicle fleet choice, and usage decisions of households. In particular, it addresses several methodological gaps in the existing literature while exploring several important empirical issues. Specifically, the current dissertation aims to bridge the gaps in the standard literature along five directions: (1) transport expenditure, (2) population heterogeneity, (3) econometric issues such as the use of ordered vs unordered logit models for modeling vehicle ownership while accounting for population heterogeneity, (4) multiple time point data pooling (pseudo panel analysis), and (5) short term vehicle usage. As part of the contributions in the dissertation, several econometric models are formulated, estimated, and validated to address the aforementioned issues through five different empirical studies. Although the domain of travel behavior literature is continuously evolving and being enriched, there is a paucity of literature in the context of Canadian urban regions. The current dissertation aims to bridge the gap by presenting studies using Canadian household data. The econometric models developed in the current dissertation are estimated using Survey of Household Spending (SHS) of Canada, Origin-Destination (O-D) surveys of both Greater Montreal Area (GMA) and Quebec City, and Quebec City Travel and Activity Panel Survey (QCTAPS) of Quebec City. In addition to model formulation, a variety of policy exercises are conducted and presented to illustrate the applications of the models developed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.018 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".