Kevin J. Krizek, Jessica Horning and Ahmed El- Geneidy
Geneviève Boisjoly, Ahmed El-Geneidy and Bernardo Serra
Several studies conducted in the Global North have shown that accessibility is strongly associated with mode choice. Combining OD survey data with local and regional accessibility measures, this study assesses the relationship between accessibility, mode choice and income in Recife, Brazil. The results highlight that income and poverty-related variables are amongst the main determinants of mode choice, whereas land use and transport variables (e.g.: accessibility to workers by public transport and Walk Score) are not significant determinants of mode choice for low-income and high-income individuals. The results suggest that low-income individuals depend on public transport, regardless of their accessibility conditions, while high-income individuals decide not to use public transport for reasons other than the lack of accessibility. Gender is also an important predictor of mode choice, women being generally more likely to use public transport. Overall, this research emphasizes important equity concerns that should be considered in future research.
Kevin J. Krizek, Ahmed El-Geneidy and Ryan Wilson
Robbin Deboosere, Geneviève Boisjoly and Ahmed El-Geneidy
Robbin Deboosere, Geneviève Boisjoly and Ahmed El-Geneidy consider the impacts of improved accessibility to employment opportunities in the Greater Toronto and Hamilton region, using the concept of competitive job accessibility, defined as the number of accessible jobs by number of workers who can access them. Increases in transit accessibility for low and medium income neighbourhoods are associated with higher increases in income, yet lower increases in income for the higher income areas. This is perhaps explained by the migration of higher income groups out to the car-dependent suburbs, and reflective of the continuing flight to the suburbs in this context.
Madalena Harreman-Fernandes, Ehab Diab, Boer Cui, James DeWeese, Miles Crumley and Ahmed El-Geneidy
Many public transport agencies conduct customer satisfaction surveys to evaluate service quality. These surveys can often yield misleading results due to poor design or failing to elicit feedback not directly asked in the questions. Some researchers and professionals argue that customer complaints are a better indicator of service quality as they directly reveal deficiencies. A recent study at McGill University analyzed customer complaint data from Portland, Oregon’s TriMet transport agency and linked it to automatic vehicle location (AVL) and automatic passenger counters (APC) data. By linking operations to complaints data, it was discovered that complaints regarding pass ups, late arrivals/departures and reckless driving were significantly associated with higher maximum and average trip loads, faster maximum segment speeds, and longer average stop delays. This demonstrates the potential of using customer complaints and transit operations data to help identify and validate perceived service deficiencies and inform decisions to improve service.