Year
2025
Season
Summer
Paper Type
Master's Thesis
College
College of Computing, Engineering & Construction
Degree Name
Master of Science in Civil Engineering (MSCE)
Department
Engineering
NACO controlled Corporate Body
University of North Florida. School of Engineering
Committee Chairperson
Dr. Thobias Sando
Second Advisor
Dr. Adel ElSafty
Third Advisor
Dr. Ryan Shamet
Department Chair
Dr. Alan Harris
College Dean
Dr. William Klostermeyer
Abstract
Fare capping is a transit policy that limits how much a rider pays within a certain period, after which all rides are free for the rest of that period. Fare capping has become a potential strategy to reverse the trend of declining transit ridership, which has been caused by factors like fare increases, service reductions, and shifts in travel behavior. While demographic and socioeconomic characteristics are known to influence ridership, their role in fare capping adoption remains underexplored. This study examines how factors like age, income, race, education, and car ownership affect fare capping adoption at the neighborhood level and evaluates the policy’s impact on ridership using the Jacksonville Transportation Authority (JTA) as a case study. It employs an Interrupted Time Series Analysis to assess ridership changes and a Negative Binomial (NB) model to analyze predictors of fare capping adoption.
Statistics show that multiday fare caps, such as Adult Month, 7-Day, and 3-Day, have more users benefiting from fare capping upgrades. This suggests that many riders accumulate pay-as-you-go/single-ride fares or purchase multiple low-value passes, rather than buying the full-period passes in advance. Additionally, results from the Interrupted Time Series (ITS) model demonstrate a significant positive effect of fare capping on ridership. The analysis also emphasizes the important roles of holidays, weekends, rainfall, temperature, and service frequency in influencing ridership.
The NB model identifies the age group 25-44, African American (Black) residents, and lower middle-income households ($25,000-$49,999) as significant predictors of fare capping usage. The findings from this study will be useful to all agencies that have implemented fare capping or are considering it, as they assess strategies to enhance fare equity, affordability, and ridership growth. Future research should examine longer-term impacts and incorporate fare capping systems that include mobile apps and smart cards.
Suggested Citation
Majuto, Maige, "Understanding fare capping in public transit: Socioeconomic predictors and ridership outcomes" (2025). UNF Graduate Theses and Dissertations. 1355.
https://digitalcommons.unf.edu/etd/1355