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On bus ridership and frequency

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  • Berrebi, Simon J.
  • Joshi, Sanskruti
  • Watkins, Kari E.

Abstract

Even before the start of the COVID-19 pandemic, bus ridership in the United States had attained its lowest level since 1973. If transit agencies hope to reverse this trend, they must understand how their service allocation policies affect ridership. This paper is among the first to model ridership trends on a hyper-local level over time. A Poisson fixed-effects model is developed to evaluate the ridership elasticity to frequency on weekdays using passenger count data from Portland, Miami, Minneapolis/St-Paul, and Atlanta between 2012 and 2018. In every agency, ridership is found to be elastic to frequency when observing the variation between individual route-segments at one point in time. In other words, the most frequent routes are already the most productive in terms of passengers per vehicle-trip. When observing the variation within each route-segment over time, however, ridership is inelastic; each additional vehicle-trip is expected to generate less ridership than the average bus already on the route. In three of the four agencies, the elasticity is a decreasing function of prior frequency, meaning that low-frequency routes are the most sensitive to changes in frequency. This paper can help transit agencies anticipate the marginal effect of shifting service throughout the network. As the quality and availability of passenger count data improve, this paper can serve as the methodological basis to explore the dynamics of bus ridership.

Suggested Citation

  • Berrebi, Simon J. & Joshi, Sanskruti & Watkins, Kari E., 2021. "On bus ridership and frequency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 140-154.
    • Handle: RePEc:eee:transa:v:148:y:2021:i:c:p:140-154
    DOI: 10.1016/j.tra.2021.03.005
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    References listed on IDEAS

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    5. Erhardt, Gregory D. & Hoque, Jawad Mahmud & Goyal, Vedant & Berrebi, Simon & Brakewood, Candace & Watkins, Kari E., 2022. "Why has public transit ridership declined in the United States?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 161(C), pages 68-87.
    6. Deepa, L. & Rawoof Pinjari, Abdul & Krishna Nirmale, Sangram & Srinivasan, Karthik K. & Rambha, Tarun, 2022. "A direct demand model for bus transit ridership in Bengaluru, India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 126-147.
    7. Yang, Chao & Yu, Chengcheng & Dong, Wentao & Yuan, Quan, 2023. "Substitutes or complements? Examining effects of urban rail transit on bus ridership using longitudinal city-level data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    8. Ziedan, Abubakr & Lima, Luiz & Brakewood, Candace, 2023. "A multiple mediation analysis to untangle the impacts of COVID-19 on nationwide bus ridership in the United States," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    9. Deepa, L. & Pinjari, Abdul Rawoof & Nirmale, Sangram Krishna & Biswas, Mehek & Srinivasan, Karthik K., 2023. "The adverse impact of headway variability on bus transit ridership: Evidence from Bengaluru, India," Transport Policy, Elsevier, vol. 141(C), pages 343-356.

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