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Cruising and on-street parking pricing: A difference-in-difference analysis of measured parking search time and distance in San Francisco

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  • Alemi, Farzad
  • Rodier, Caroline
  • Drake, Christiana

Abstract

When on-street parking is scarce, the cost of parking includes the extra time and fuel spent searching for a parking space (or cruising). Cruising also unnecessarily contributes to local congestion, vehicle emissions, air pollution, and climate change. The theoretical literature shows that these social costs can be reduced, or even eliminated, if high-quality information on the demand for and supply of parking is used to set parking prices at optimal levels. Not surprisingly, cities plagued by parking shortages, congested streets, and limited financial resources are interested in parking policies that reduce cruising and improve the efficient use of their existing parking and roadway infrastructure. The current study sheds light on the effect of the San Francisco parking pricing program (known as SFpark) on curbside parking search time and distance in urban neighborhoods on non-commuter parking. The study differs from previous empirical evaluations of similar parking pricing programs in its use of direct field measurements of parking search time and distance, rather than simulated data or proxy variables, such as parking availability. We use generalized mixed effect difference-in-difference models with data collected before and after the implementation of SFpark in both treatment and control areas to estimates effects of the San Francisco smart parking project, most importantly the demand responsive parking pricing scheme. The models control for time effects by using data from a separate control area, as opposed to using variables such as block face parking price and employment. The results suggest a significant reduction in average parking search time and distance due to SFpark. Average parking search time and distance declines by approximately 15% and 12%, respectively, from the control to the treatment areas.

Suggested Citation

  • Alemi, Farzad & Rodier, Caroline & Drake, Christiana, 2018. "Cruising and on-street parking pricing: A difference-in-difference analysis of measured parking search time and distance in San Francisco," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 187-198.
    • Handle: RePEc:eee:transa:v:111:y:2018:i:c:p:187-198
    DOI: 10.1016/j.tra.2018.03.007
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    References listed on IDEAS

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    Cited by:

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    10. Jun Li & Sifan Wu & Xiaoman Feng, 2021. "Optimization of On-Street Parking Charges Based on Price Elasticity of the Expected Perceived Parking Cost," Sustainability, MDPI, vol. 13(10), pages 1-13, May.
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    16. Haobing Liu & Daejin Kim & Hanyan Li & Michael O. Rodgers & Randall Guensler, 2024. "Synthetic control methods for estimating the effect of purchase incentives on plug-in electric vehicles sales in the United States," Transportation, Springer, vol. 51(4), pages 1209-1238, August.
    17. Khordagui, Nagwa, 2019. "Parking prices and the decision to drive to work: Evidence from California," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 479-495.
    18. Tan, Bing Qing & Xu, Su Xiu & Kang, Kai & Xu, Gangyan & Qin, Wei, 2021. "A reverse Vickrey auction for physical internet (PI) enabled parking management systems," International Journal of Production Economics, Elsevier, vol. 235(C).
    19. Kadkhodaei, Masoud & Shad, Rouzbeh & Ziaee, Seyed Ali & Kadkhodaei, Mohsen, 2023. "Prediction model for drivers' tendency to perpetrate a double parking violation on urban trips," Transport Policy, Elsevier, vol. 141(C), pages 331-339.
    20. Dave, Sanjaykumar M. & Joshi, Gaurang J. & Ravinder, Kayitha & Gore, Ninad, 2019. "Data monitoring for the assessment of on-street parking demand in CBD areas of developing countries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 152-171.
    21. Tan, Bing Qing & Xu, Su Xiu & Thürer, Matthias & Kang, Kai & Zhao, Zhiheng & Li, Ming, 2024. "Booking versus search-based parking strategy: A game-theoretic methodology," Research in Transportation Economics, Elsevier, vol. 104(C).
    22. Bai, Xiwen & Xu, Ming & Han, Tingting & Yang, Dong, 2022. "Quantifying the impact of pandemic lockdown policies on global port calls," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 224-241.
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