Article ID: | iaor20114218 |
Volume: | 38 |
Issue: | 3 |
Start Page Number: | 545 |
End Page Number: | 560 |
Publication Date: | May 2011 |
Journal: | Transportation |
Authors: | Currie G, Ahern A, Delbosc A |
Keywords: | statistics: regression |
This paper explores the relative influence of factors affecting light rail ridership on 57 light rail routes in Australia, Europe and North America through an empirical examination of route level data. Previous research suggests a wide range of possible ridership drivers but is mixed in clarifying major influences. A multiple‐regression analysis of route level ridership (boardings per route km) and catchment residential and employment density, car ownership, service level, speed, stop spacing, share of accessible stops, share of segregated right of away and integrated fares was undertaken. This established a statistically significant model (99% level, R2 = 0.76) with five significant variables including service level, routes being in Europe, speed, integrated ticketing and employment density. In general these findings support selected results from previous research. A secondary analysis of service effectiveness measures (boardings/vehicle km, i.e. the relative ridership performance for a given level of service), established a statistically significant model (99% level, R2 = 0.67) with 6 significant explanatory variables including being in Europe, speed, employment density, integrated ticketing, track segregation and service level. The latter implies that a higher frequency results in higher service effectiveness. Overall the research findings stress the importance of providing a high level of service as a major driver of light rail ridership. The ‘European Factor’ is also an important though intriguing influence but its cause remains unclear and requires further research to elaborate its nature.