Academic journal article Canadian Journal of Urban Research

Opportunities and Barriers to Promoting Public Transit Use in a Midsize Canadian City

Academic journal article Canadian Journal of Urban Research

Opportunities and Barriers to Promoting Public Transit Use in a Midsize Canadian City

Article excerpt

INTRODUCTION

Midsize cities--100,000 to 500, 000 population--account for more than 37% of the Canadian population (Toop and Miller, 2014). Canadian midsize cities have historically tended to be highly transit-depleted urban environments (Bunting and Filion 1999). Although there is an extensive literature on determinants of public transit, most studies have reported analyses using data from large metropolitan areas (for example, Taylor et al 2009, Cervero 1998). But, since transportation context in midsize cities is different from large cities in several respects--such as low population density, lack of traffic congestion, shorter trip lengths--it is reasonable to assume that travel patterns in midsize cities are also different from large metropolitan areas. Indeed, the available evidence shows much lower rates of public transit use in midsize as compared to larger metropolitan areas (McLeod, 2011). However, it is unclear whether transit supportive policies that are based on evidence from large cities would be appropriate for midsize cities. Thus, the purpose of this paper is to contribute to our understanding of general commute patterns, as well as barriers and opportunities for promoting public transit as a viable commute mode in midsize Canadian cities.

In this paper, we examine personal travel survey data of employees of Queen's University, the second largest employer in Kingston, Ontario (KEDCO 2014). Kingston, a midsize city, had a 2011 population of 123,363 (Statistics Canada 2011a), and like most cities of its size, is highly automobile-centric with the vast majority of commuters (82%) driving to work (SPC&K, 2009). And while the proportion of Kingstonians who engage in active commuting is relatively high at 12%, only 4% use public transit to get to work (SPC&K, 2009). This figure is in stark contrast to the 23% that commute by transit in Toronto, 20% in Vancouver, and 22% in Montreal, Canada's three largest cities (Statistics Canada 2011b). Queen's university has not only a large employee base from which to study commute patterns and attitudes towards transit, but is also located in Kingston's downtown core, is highly accessible by the municipality's public transit system, and is a major institution of focus in the City's transit redevelopment strategy (Kingston 2011). Figure 1 illustrates the location of Queen's relative to the city's downtown core, as well as within the city's public transit network.

The remaining paper is organized into four parts. Part one presents a succinct description of the factors that affect public transit ridership in general, and a brief summary of evidence available on midsize cities in particular. Part two presents our methods, and part three our analysis. The paper concludes with a discussion of policy implications of the research findings and suggestions for future research.

Factors Affecting Public Transit Ridership

In economic terms, travel mode choice can be explained as a trade-off between utility/benefit versus disutility/ cost of using different modes including public transit (Small 2012, Taylor et al 2009, Dzeikan and Kottenhoff 2006, Small 1992). The utility of a trip is tied to the trip purpose; for example travelling to work would have higher benefit (since it involves earning an income) as compared to travelling to get a haircut. Disutility or cost assessments include both monetary cost and time cost. For example, driving would likely have a higher monetary cost but lower time cost, whereas bicycling would likely have low money cost but high time cost, all else equal.

In general, studies have found that public transit ridership is positively associated with high population densities (Cervero 1998, Zhang 2004), and negatively associated with access to a car (Chen et al 2008, Dargay and Hanly 2007), household income (Balcombe et al 2004, Chen et al 2008), and presence of young children in the household (Chen et al 2008, Kim and Ulfarsson 2008). …

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