Partnering with Transportation Network Companies to Serve Low-Density Communities

Wesley PhD Darling and Michael J. PhD Cassidy

Institute of Transportation Studies, Research Reports, Working Papers, Proceedings from Institute of Transportation Studies, UC Berkeley

Abstract: This study addresses the persistent challenge of delivering cost-effective, high-quality on-demand transit in low-density communities. Traditional microtransit services often struggle in such areas due to high fixed costs and limited opportunities to consolidate trips, while community partnerships with transportation network companies (TNCs) like Uber and Lyft are typically avoided due to concerns over data transparency and limited community control. To bridge this gap, we propose a new business plan for cooperative TNC partnerships, in which a community-appointed service manager coordinates trip requests, distributes financial incentives to attract drivers to the community from nearby high-demand areas, and leverages the TNC’s existing digital infrastructure for driver dispatch and routing. We evaluate this business plan through case studies of three Northern California communities presently served by microtransit, comparing microtransit’s measured performance against the predicted performance of a TNC operating under the proposed business plan using a simple metric that does not depend on the specific design of the transit system. Results show that TNCs can deliver higher levels of service and higher driver wages in all three communities and were more cost-effective than microtransit in two of the three. Applying the metric across California reveals that many communities with microtransit, and numerous other communities presently underserved by transit, would likely benefit from switching to TNC partnerships. This suggests that a large opportunity exists for using TNC partnerships to provide mobility in areas where other forms of transit are less effective.

Keywords: Engineering; Demand responsive transportation; Public transit; Ridesourcing; Public private partnerships; Benefit cost analysis; Business models (search for similar items in EconPapers)
Date: 2026-01-01
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