The Use of Behavioural Insights for Crowding Management on Public Transit

• Author / Creator

  Kapatsila, Bogdan

• Overcrowding causes transit riders’ dissatisfaction and may lead to ridership loss while taking a toll on agencies’ resources and forcing them to deal with service disruptions. While the COVID-19 pandemic led to a significant reduction in demand for transit trips, social distancing requirements challenged the capacity of available transit infrastructure to deliver services in a manner viewed as safe by the riders and authorities. Moreover, in the ongoing post-pandemic recovery, transit overcrowding has been outpacing ridership, pointing out the need for operators to address temporal spikes in transit demand. As such, this dissertation aims to answer the primary research question: How can knowledge about the preferences of different behavioural profiles be leveraged to develop policy interventions that affect the travel patterns of transit riders? The answer is developed by achieving four research objectives:
  • To accurately identify distinct behavioural groups of transit users;
  • To investigate the stated choices of distinct behavioural profiles of transit riders;
  • To investigate the effect of preferences for incentives on the stated choices of transit riders;
  • To investigate the effect of accessible information on the revealed choices of transit riders.
  These research objectives are addressed in four analytical chapters. The analysis is preceded by a systematic literature review that investigates the state of knowledge and practice on the application of demand management strategies on public transit and sets the stage for the empirical investigations of the identified opportunities and gaps. The chapters build on each other, collectively advancing knowledge about how transit riders’ travel behaviour can be influenced using policy tools.
  Empirical findings in this dissertation are generated using the context of Metro Vancouver, British Columbia, Canada. Chapter 3 identifies specific behavioural groups of public transit users and their attitudinal preferences that can be used for policy interventions based on behavioural insights. The next chapter takes that classification and employs it to understand the effect of crowding on the class-specific decision to board a bus and the level of comfort of riding a bus at various crowding levels. The knowledge generated in these chapters can be used to develop interventions that appeal to preferences of transit riders and thus have higher chances of influencing a long-term change in travel behaviour.
  Chapters 5 and 6 present insights into the effect of incentives and strategies based on the provision of crowding information. The former identifies how preferences for various incentives affect the actions riders may take in response to crowding, like the decision to change travel time being more influenced by fare-based incentives and the choice to switch to another transit route being more impacted by other incentives (like discounts for other modes, or opportunity to participate in a raffle). The latter investigates revealed preference data and confirms that providing crowding information in a smartphone trip-planning application influences the route choices of transit riders. The outcomes of this stage advance understanding of facilitating factors (like incentives and real-time information) and constraining aspects (e.g. flexibility and trip time) that influence transit riders to change their travel patterns in response to crowding.
  The findings of all studies are consolidated in the concluding chapter, where the overarching contributions are summarized and avenues for future research are indicated. Specifically, this dissertation expands existing knowledge in the following ways:
  • Reviews and evaluates existing policy approaches to public transit demand management based on ex-post studies;
  • Identifies behavioural profiles of transit riders using a probabilistic market segmentation technique that allows for policy interventions to engage a significant share of users and to increase the likelihood of long-term changes in their travel behaviour;
  • Evaluates the potential that monetary and behavioural insights-based incentives have on changing transit riders’ travel time or route to avoid crowding;
  • Provides empirical evidence on the effects of public transit demand management programs that use improved access to crowding information;
  • Develops a framework of how behavioural insights can systematically inform transport policy planning.
  Transit agencies that face crowding challenges can benefit by applying the findings of this thesis and potentially save costs by retaining and attracting riders, reducing system disruptions, and postponing infrastructure expansions. Policies based on the recommendations from this study could lead to higher rider satisfaction, loyalty, and a larger customer base through the attraction of users of other modes.

• Subjects / Keywords

  • Transit Market Segmentation
  • Transportation Demand Management
  • Transit Crowding
  • Travel Behaviour

• Graduation date

  Fall 2024

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/r3-zpq2-cq70

• License

  This thesis is made available by the University of Alberta Library with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.