On-demand mobility services such as bikesharing, scooter sharing, and transportation network companies (TNCs, also known as ridesourcing and ridehailing) are changing the way that people travel by providing dynamic, on-demand mobility that can supplement public transit and personal-vehicle use. Adoption of on-demand mobility has soared across the United States and abroad, driven by the flexibility and affordability that these services offer, particularly in urban areas where population density and land use patterns facilitate a reliable balance of supply and demand. The growth of app-based ridesharing, microtransit, and TNCs presents a unique opportunity to reduce congestion, energy use, and emissions through reduced personal vehicle ownership and increased vehicle occupancy, the latter of which is largely dependent on the decisions of individual travelers to pool or not to pool. This research provides key insights into the policy levers that could be employed to reduce vehicle miles traveled and emissions by incentivizing the use of pooled on-demand ride services and public transit. We employ a general population stated preference survey of four California metropolitan regions (Los Angeles, Sacramento, San Diego, and the San Francisco Bay Area) to examine the opportunities and challenges for drastically expanding the market for pooling, taking into account the nuances in emergent travel behavior and demand sensitivity across on-demand mobility options. Although high-frequency TNC users – those that use TNCs once a week or more - are more likely to consider pooling than less frequent users and reflect more multimodal travel behavior than other travelers, we find that the most captive and price sensitive TNC users are often the most vulnerable. Heavy TNC users – those using TNCs more than three days per week - are disproportionately low income, more likely not to own or lease a car and more likely to use TNCs for essential trip purposes than are less frequent users. Pooling demand sensitivity varies significantly across trip contexts, metropolitan regions, socio-demographics, travel behavior, and attitudes and perceptions toward sharing. We estimate the time and price tradeoffs in choosing between ride alone and shared on-demand service options, finding significant differences across values that travelers place on each component of travel time (wait time, access/egress walking time, and in-vehicle time) by geography and income level. We discuss the potential to leverage these insights to develop policies that combine pricing, curb management, and promotional strategies to increase the pooling market share.
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Jan 1, 2022
Pengyu Zhu + 3
Open Access