Turning Trends in a Positive Direction
Public transportation ridership has been declining in most major cities for the last three to five years, threatening support for transit investment. With recent headlines highlighting an influx of “millennials” moving into cities and foregoing cars in favor of public transit, the big question is why? Declines in transit ridership run parallel with disruptive trends in cities, such as the rise in transportation network companies (Lyft, Uber) and the explosion of micromobility options (e-scooters, e-bikes). Research suggests these and many other factors are jointly responsible for chipping away at transit trips. However, public agencies do have tools at their disposal to stop and even reverse these declines, once they know how to identify and use them effectively.
While more mobility options benefit individuals, when many people replace a few transit trips with other options there are large negative effects for transit agencies. A prolonged loss of riders can create a negative cycle: people use transit less, agencies respond by decreasing service, and the reduced service becomes even less useful for the remaining riders. How is this cycle prevented?
Understanding where and how transit outperforms other options.
Many people believe public transportation is better than other options in certain circumstances. For example, many riders own or have regular access to a car but choose to take transit to work during peak traffic times, because they find driving stressful and unproductive in those situations. Others almost exclusively take transit to special events such as baseball games or for an evening downtown. In the Ridership Growth Action Plan, we mapped a series of variables associated with trips that transit serves well at the county level, such as the entertainment district and job centers. The map to the left illustrates where concentrating service might simultaneously address multiple travel markets.
Focusing service on contemporary travel demand.
Many bus routes today trace back to the streetcars of a century ago. While still appropriate in some cases, in others it may ignore significant land use development and modern travel patterns. Agencies can use big data to identify under-served travel patterns and refine their investments to better align service to modern needs. For example, agencies might consider deemphasizing very short trips where e-scooters and improved active transportation networks compete with buses, and instead focus on the medium-distance trips or longer-distance commuter services that integrate with new mobility options for the last leg of trips. We conducted a series of case studies to evaluate how well various transit routes across Los Angeles County serve the travel patterns of people that live in close proximity to each route.
Transit agencies can take a page out of transit network company (TNC) playbooks by using existing apps, customer databases, and social media to promote transit effectively. Direct and personalized contact with current, former, and potential riders can encourage them to use transit, particularly when linked to the agency’s understanding of where and how transit outperforms other options. Many agencies will run promotions when a big event is in town, encouraging people to take transit. The rewards for doing so should encourage customers to take transit again later, ideally by giving a credit for future trips within a defined period. Agencies can measure the effectiveness of these efforts with better data — provide the reward and study how riders respond to these rewards. Our Los Angeles study found that the vast majority of active transit fare cards are used only one day a week or less, on average. Revealing transit ridership consists mainly of individuals who ride only occasionally, and few individuals ride daily.
Massive stores of transit performance data are growing daily as technology improves, and agencies must use that data to focus their efforts where it will benefit the most current and potential riders. This includes on-time performance and quality of service delivery, as well as other factors such as customer experience and safety. Agencies can mine their data more effectively to address the most frequent issues or complaints and identify those that are most likely to result in a bad transit experience. For issues that are outside an agency’s direct control (road conditions or traffic operations), data may be used to build understanding for decision makers regarding how many riders and buses are affected. The Ridership Growth Action Plan identified many agencies could benefit from better data on customer service and operational issues, and riders desire an easy reporting tool similar to how app-based services gather feedback on every trip.
Explore the Ridership Growth Action Plan.
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to turn transit trends in a positive direction.
© 2017 – 2022 Fehr & Peers. All rights reserved.
© 2017 – 2022 Fehr & Peers. All rights reserved.