Influence of tolerable, perceived, and actual travel time on trip satisfaction among Canadian older adults
Bibliographic record
Abstract
As older adults cease driving, public transit can support them maintain their independence and remain connected to their communities. This population is particularly sensitive to travel times. While previous research has explored the impact of ideal and perceived travel times on satisfaction, the role of tolerable travel times—representing the maximum acceptable time threshold before satisfaction declines—has been underexplored. Understanding this relationship can provide valuable insight for improving transit experiences and meeting the mobility needs of older adults. To explore this gap, we examine how subjective (perceived and tolerable) and objective (actual) measures of travel time influence trip satisfaction among older adults. To do so, we use data from the 2023 Aging in Place Survey, a Canadian bilingual online survey, focusing on respondents who used transit at least once in the past year from Toronto, Montréal, and Vancouver (N = 731). We asses the impact of these measures of travel time on trip satisfaction through multi-level ordered probit models, accounting for both individual and regional factors. Our findings suggest that older adults are more likely to be satisfied with their trip when perceived travel time aligns with what they consider as tolerable, rather than the actual, objective trip duration. They also reinforce the strong role of previous transit experiences and perceptions on shaping future trip satisfaction. Given the link between satisfaction and continuous transit use, these findings are relevant for practitioners and policymakers seeking to improve public transit experiences for older adults and support their healthy aging. • We investigate the influence of objective and subjective measures of travel time by transit on trip satisfaction. • We build multi-level ordered probit models using travel time, sociodemographic data, and transit perceptions. • Transit trip satisfaction depends on perceived and tolerable travel times, but not actual travel time. • Positive perceptions of transit are strongly related to trip satisfaction.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".