Passively wait for gridlock, or proactively invest in service? Strategies to promote car-to-transit switches among aspirational urbanites in rapidly developing contexts

Abstract

As planners and policymakers in cities around the world struggle to attract and retain public transit users, this paper explores strategies to promote transit adoption in contexts where the odds are stacked against transit. Using travel behavior data from India’s National Capital Region – one of the most congested metropolitan areas globally that is experiencing unprecedented growth in personal vehicle ownership and plummeting transit ridership – this study analyzes the choice of intra-urban (metro) rail over personal car for commute trips within a specific population sub-group that is fast adopting the personal car and exiting the transit market. The objective of this mode choice analysis that employs both logistic regression modeling and the propensity-score matching technique is to identify multi-modal service quality/performance factors that determine metro rail vs. car choice, and thereby recommend efficient and effective interventions for inducing car-to-transit switches in addition to retaining existing transit riders. Results suggest that increasing metro rail’s travel time competitiveness relative to car (particularly for long distance commuters), service frequency and safety level, and raising car parking cost at the destination can increase the likelihood of choice of metro rail over car in the study context. Interestingly, increase in traffic congestion and travel time unreliability of the car mode are not expected to automatically boost the demand for metro rail use, all else equal. As the momentum towards more car adoption continues, this study shows that deteriorating traffic conditions may not push drivers out of cars; rather, public transit has to step up and pull drivers out of cars. For planners and policymakers, this study indicates that rather than passively waiting for driving conditions to worsen, they should proactively invest in transit service quality improvements. This study also highlights the importance of communicating service changes to the traveling public in order to efficiently translate interventions to behavior changes, given the dissonance between travelers’ perceptions of multi-modal travel conditions and actual travel conditions. This paper further demonstrates that analysis of travelers’ perception errors, including variation in error across travelers, is important for accurately modeling travel behavior changes in response to interventions. The findings add to the literature on mode choice analysis, and provide strategic advice for transit agencies in India and across other comparable contexts globally