Shared micromobility services are growing rapidly across the United States and abroad. In 2018, the number of shared micromobility trips in the U.S., including station-based and dockless bike sharing and e-bike sharing and scooter sharing, reached 84 million . Of those trips, 36 million were station-based bike sharing trips, about 500,000 were station based e-bike sharing trips, and about 6 million were dockless e-bike sharing trips. By enabling users to access a fleet of publicly available shared personal transportation devices on an as needed basis, shared micromobility offers on-demand, low-emission public transportation options that can help to reduce congestion and emissions, as well as improve public health within urban areas . Traditional station-based bike sharing systems have been studied in depth, generating some agreement about their positive impact on cycling rates, modal shifts from personal vehicle use, and promotion of public transit ridership through improved first- and last-mile connections to public transit stations . These benefits can contribute to various federal, state, and local objectives to improve mobility, safety, and public health, and reduce congestion, fuel use, and emissions. Innovations to incumbent bike sharing technology and business models are spreading in a new wave of fourth generation bike sharing and scooter sharing, which includes dockless models, demand-responsive pricing and rebalancing, and electric fleets of bicycles, standing scooters,rolling bench and moped-style scooters. The increased geographic coverage and availability of these new service models have great potential to further expand and integrate shared micromobility in the transportation system, as such factors have been identified as significant drivers in traditional bike sharing ridership .
Early analysis of aggregated activity data from dockless and scooter-based models shows substantial expansion of micromobility ridership in urban areas , with an estimated market potential of 8 to 15 percent of all passenger trips under 5 miles . However, concerns about curb management, safety, and the sustainability of the micromobility vehicle supply have become a central focus of the ongoing development of regional and local regulations and permitting programs have . This paper examines the expansion of bike sharing in the City of San Francisco. In January 2018, the San Francisco Municipal Transportation Agency issued a permit for a pilot dockless electric bike sharing system, called JUMP, which began to operate in parallel to the existing regional station-based bike sharing system, Ford GoBike. Around the same time, it was announced that the GoBike system would expand to include electric bicycles as well, which became available in April 2018. The expansion of the docked GoBike system complemented by the newer stationless JUMP bikes necessitates an evaluation of the effectiveness of each system in providing additional mobility in San Francisco and consideration of the spatial distribution of bicycle infrastructure, such as bicycle lanes and public bike racks to support the potential increase in bicycle demand. As a city with a highly concentrated central business district that is surrounded by steep hills with medium density residential and mixed use areas, San Francisco offers an interesting case study for examining the impacts of e-bike and dockless models on bike sharing travel behavior throughout the city.
Our research seeks to understand the impact that the dockless, e-bike sharing model might have on bike sharing users’ travel behavior as compared to traditional docked bike sharing. A primary objective is to characterize the spatial distribution of demand for both dockless electric and docked bike sharing throughout San Francisco. We created a destination choice model using a month of activity data from both JUMP and GoBike to quantify the relative bike sharing attractiveness at a neighborhood scale for users of each system. Our analysis revealed the impact that dockless, e-bike sharing has on the sensitivity of bike sharing users’ destination choices to various exogenous factors such as: bicycle infrastructure, topography, socio-demographics, and land-use variables. This article is organized into four sections. First, we provide background, including a brief history of bike sharing in general and in San Francisco, as well as a discussion of the major factors that impact bike sharing ridership, as revealed in existing literature. Next, we present an overview of our methodology. Third, we present the results of travel behavior analysis, destination choice modeling, and bike sharing suitability analyses. Finally, we highlight our conclusions and future work. Public bike sharing and scooter sharing systems are quickly becoming the most widely adopted and rapidly growing shared miocromobility options across the U.S. . By enabling users to access a fleet of publicly available shared personal transportation devices on an as-needed basis, shared micromobility offers on-demand, low emission public transportation options that can help to reduce congestion and emissions, as well as improve public health within urban areas . As shared micromobility continues to expand and evolve with emerging technology and business models, new insights regarding the unique impacts of electric vehicles and dockless models on ridership and travel behavior is needed to aid cities in understanding how to best manage local micromobility ecosystems to promote a more sustainable and equitable transportation system.
The first public bike sharing system emerged in 1965 in Amsterdam, Netherlands. This innovation has expanded to reach cities across Europe, North America, South America, Asia, and Australia. At present, most bike sharing systems are classified as third generation, characterized by the implementation of information technology for bicycle pick-up, drop-off, and tracking. Bike sharing systems are predominantly “station-based” or docked, where bicycles are located at public docking stations and trips are required to originate and terminate . Docks are typically concentrated in urban areas, creating a network of on-demand bicycles suitable for a variety of trip purposes. Users can instantly unlock an available bicycle from a docking station using a credit/debit card, membership card, key, and/or a smartphone application. There are a variety of fare structures applied in bike sharing systems including: daily, monthly, and annual passes. In most systems, fares tend to cover at least the first 30 minutes of a trip, with overage charges beyond that time. Many systems also allow users to chain multiple trip segments of 30 minutes or less, such that a user can extend their riding time by “ending” a trip segment at a dock and immediately unlocking a bike for another trip segment. Fourth generation bike sharing builds upon the IT-enabled third generation to deliver demand-responsive, multi-modal systems. The dockless, or free floating, bike sharing model is one such innovation, which allows users to pick-up and drop-off bicycles anywhere within a service zone. Demand-responsive bicycle redistribution and value pricing encourages users to participate in the rebalancing of bicycles, facilitating a spatiotemporal distribution of bicycles that closely matches system supply and demand. Bike sharing systems are also becoming more integrated with other transportation modes through mobility as a service models, including: public transit; car sharing ; and ride sourcing/transportation network companies . Uber Technologies, Inc. acquired JUMP in April 2018 . Interestingly,Lyft acquired Motivate, the parent company of GoBike in July 2018. This likely signals that shared mobility companies are interested in becoming multi-modal MAAS platforms consisting of more than one shared mode. In late-2017 and early-2018, bike sharing operators Social Bicycles , Motivate, and Lime, began operating bike sharing systems with electric assist bicycles or e-bikes. E-bikes have an electric motor that reduces the effort required by the rider, allowing for greater speeds and ease in riding uphill. Research on personally owned e-bike use has found that the main reasons people choose to use e-bikes include living or working in hilly areas, medical conditions, fitness,drying rack cannabis and the desire to ride with less effort . E-bikes can mitigate the inconvenience imposed by needing to shower after bicycling, thus providing an attractive alternative to traditional bikes for commute trips.
MacArthur et al. found that 80% of sampled e-bike users under the age of 55 and 68% of those 55 and older said that they did not need to shower after using e-bicycles. A report on shared micromobility in 2018 found that, in cities where e-bikes were added to station-based bike sharing fleets, e-bike utilization was about twice that of pedal bikes, on average . Ford GoBike launched in Summer 2017 as a re-branding and expansion of the Bay Area Bike Share system, which launched in San Francisco and San Jose in 2013. GoBike provides access to five cities, 540 stations, and 7,000 bikes . As with many docked bike sharing systems, standard GoBike rides are 30 minutes long, with each additional 15 minutes costing extra. GoBike offers single ride, day pass, and annual membership payment plans, with the day/annual passes providing unlimited standard rides for the duration of their validity. Users can locate and unlock a bicycle using a mobile app, Clipper Card, or by paying on-site using a kiosk. Around the same time as the JUMP pilot launch, in April 2018, GoBike added 250 electric pedal-assist bicycles to its San Francisco fleet followed by an additional 600 in December 2018. However, we note that at the time of the study period, the GoBike fleet comprised solely of standard pedal bicycles. Figure 1 below shows the service areas of GoBike and JUMP during the study period. JUMP Bikes, a program of Social Bicycles, launched in January 2018 after the SFMTA issued the city’s first permit to operate a dockless bike sharing service. As an 18-month pilot program under evaluation by SFMTA, JUMP is committed to providing a “safe, equitable, and accountable” dockless e-bike sharing system . For the duration of the pilot, SFMTA will not issue any other dockless bike sharing permits and aims to develop policy recommendations based on the pilot’s results. The initial pilot allowed for 250 bikes until October, 2018 when an additional 250 bikes were added to the fleet. With integrated onboard Ulocks, JUMP bikes are parked at regular bike racks or locked to a fixed object in the sidewalk “furniture zone,” the portion of sidewalk from the curb to the pedestrian walk zone . Users can locate and unlock the bikes using a smartphone application, password, or radio-frequency identification member card . While the literature on ridership and travel behavior of dockless and electric shared micromobility is limited, there has been extensive research on the use of station-based bike sharing models. The literature reveals three major external factors that impact bike sharing ridership: 1) infrastructure , 2) geography , and 3) user demographics . Much of the literature on internal factors has focused on a-priori and optimization analyses of station location, dock allocation, fleet sizing, and rebalancing algorithms . We thus focus our attention on empirical findings from the literature on the impacts of external factors on bike sharing ridership and travel behavior.Infrastructure indicators for bike sharing ridership relate to the availability and attractiveness of bicycle facilities, such as bike lanes, bike paths, and bike boulevards. Buehler and Pucher show that bike commute ridership correlates positively with the supply of bike paths and lanes, even when controlling for other contributing factors . A destination choice analysis of the Divvy docked bike sharing system in Chicago found that bike sharing users preferred destinations with a greater density of bicycle facilities in the surrounding area, and bike sharing members were more sensitive to this factor than non-members . Finally, a multiple regression analysis of the Capital Bike share system in Washington, D.C., found that the total length of bike lanes within .5 miles of a station was a significant positive factor in the number of rides per day at the station .The quality of the bike infrastructure can also impact the sensitivity of demand for bike sharing. Indeed, route choice modeling of Grid Bike share users in Phoenix, Arizona found that bike-specific facilities increase the preference for a particular route by an amount equivalent to decreasing the travel distance by 44.9% . In Portland, Oregon, route choice modeling revealed that bicyclists prefer bike boulevards and bike paths, which are typically on streets with little and no vehicle traffic, respectively, to bike lanes, which are facilities that share the road with regular traffic . The next critical question is where to supply infrastructure per demand. Although station proximity to bike infrastructure is a top design priority , it is important to note⎯that due to geographical constraints⎯not all origin-destination pairs are equally attractive. Job density, proximity to public transit services, and proximity to recreational areas at the location of a bike sharing station have been found to be positive factors in bike sharing demand . For example, in the Nice Ride program in Minneapolis-St. Paul, stations farther away from central business districts of the twin cities as well as those farther away from parks generated fewer bike sharing trips . For e-Bikes, an elevation change between origin and destination locations is also a positive demand factor.