Article ID: | iaor20122399 |
Volume: | 22 |
Start Page Number: | 146 |
End Page Number: | 161 |
Publication Date: | Jun 2012 |
Journal: | Transportation Research Part C |
Authors: | Thakuriah Piyushimita (Vonu), Tang Lei |
Keywords: | information, statistics: empirical, statistics: inference, demand |
In this paper, using longitudinal data on route level monthly average weekday ridership in the entire Chicago Transit Authority (CTA) bus system from January 2002 through December 2010, we evaluate the ridership effects of the CTA real‐time bus information system. This bus information system is called CTA Bus Tracker and was incrementally implemented on different CTA bus routes from August 2006 to May 2009. To take account of other factors that might affect bus ridership, we also include data on unemployment levels, gas prices, local weather conditions, transit service attributes, and socioeconomic characteristics during the study period. This combined longitudinal data source enables us to implement a quasi‐experimental design with statistical controls to examine changes in monthly average weekday ridership, before and after the Bus Tracker system was implemented, on each bus route. Based on a linear mixed model, we found that the provision of Bus Tracker service does increase CTA bus ridership, although the average increase is modest. Further, the study findings suggest that there are temporal variations of the ridership effects among the routes, with the ‘winning’ routes more likely to have the technology implemented in the later phases of the overall ‘roll‐out’ period. However, the results are less conclusive regarding geographical variations in the effects of Bus Tracker.