Events

Mr. Jiayuan Tian
Ph.D. Candidate in Information Systems
University of Florida Gainesville

Congestion pricing imposes fees on vehicles entering high-traffic areas during peak times and has been increasingly proposed for ride-hailing services like Uber and Lyft. While intended to reduce congestion and promote sustainability, applying traditional congestion fees to ride-hailing introduces unique operational challenges, such as managing fees for multi-passenger shared rides and dynamic platform-driven routing decisions. Existing research provides mixed findings, especially regarding the differential effects on lowand high-income communities. Leveraging a natural experiment created by Chicago’s sudden implementation of a ride-hailing-specific congestion tax, this study employs a generalized difference-indifferences approach to empirically examine the policy’s impact on digital access and transportation equity. Using detailed trip-level data, our analysis reveals that congestion pricing disproportionately reduces ridehailing demand in low-income areas by 11.5% more compared to high-income areas, highlighting greater price sensitivity among economically disadvantaged riders despite their lower marginal contribution to overall congestion. We also identify a pronounced “compromise effect,” in which low-income riders respond to increased costs by shifting toward more affordable shared rides, despite potential inconveniences or longer travel times. This effect further manifests in strategic temporal adjustments, with demand from low-income tracts significantly declining during peak hours but increasing for shared rides and for regular rides during adjacent off-peak periods to avoid higher fees. Additionally, the compromise effect is particularly evident for short-distance trips, where fixed congestion fees represent a proportionally larger cost burden, prompting financially disadvantaged riders to substantially adjust their travel behaviors. Collectively, these findings reveal nuanced user responses to congestion pricing in digitally mediated transportation, highlighting critical operational trade-offs for ride-hailing platforms balancing regulatory compliance and customer retention. They also inform policymakers to design equitable, sustainable urban mobility strategies that preserve transportation accessibility for economically disadvantaged populations.