Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco

Shared micromobility – the shared use of bicycles, scooters, or other low-speed modes – is an innovative transportation strategy growing across the United States that includes various service models such as docked, dockless, and e-bike service models. This research focuses on understanding how docked bikesharing and dockless e-bikesharing models complement and compete with respect to user travel behaviors. To inform our analysis, we used two datasets from February 2018 of Ford GoBike (docked) and JUMP (dockless electric) bikesharing trips in San Francisco. We employed three methodological approaches: 1) travel behavior analysis, 2) discrete choice analysis with a destination choice model, and 3) geospatial suitability analysis based on the Spatial Temporal Economic Physiological Social (STEPS) to Transportation Equity framework. We found that dockless e-bikesharing trips were longer in distance and duration than docked trips. The average JUMP trip was about a third longer in distance and about twice as long in duration than the average GoBike trip. JUMP users were far less sensitive to estimated total elevation gain than were GoBike users, making trips with total elevation gain about three times larger than those of GoBike users, on average. The JUMP system achieved greater usage rates than GoBike, with 0.8 more daily trips per bike and 2.3 more miles traveled on each bike per day, on average. The destination choice model results suggest that JUMP users traveled to lower-density destinations, and GoBike users were largely traveling to dense employment areas. Bike rack density was a significant positive factor for JUMP users. The location of GoBike docking stations may attract users and/or be well-placed to the destination preferences of users. The STEPS-based bikeability analysis revealed opportunities for the expansion of both bikesharing systems in areas of the city where high-job density and bike facility availability converge with older resident populations

Evaluating Impacts of Shared E-scooters from the Lens of Sustainable Transportation

As the popularity of shared micromobility is increasing worldwide, city governments are struggling to regulate and manage these innovative travel technologies that have several benefits, including increasing accessibility, reducing emissions, and providing affordable travel options. This dissertation evaluates the impacts of shared micromobility from the perspective of sustainable transportation to provide recommendations to decision-makers, planners, and engineers for improving these emerging travel technologies. The dissertation focuses on four core aspects of shared micromobility as follows: 1) Safety: I evaluated police crash reports of motor vehicle involving e-scooter and bicycle crashes using the most recent PBCAT crash typology to provide a comprehensive picture of demographics of riders crashing and crash characteristics, as well as mechanism of crash and crash risk, 2) Economics: I estimated the demand elasticity of e-scooters deployed, segmented by weekday type, land use, category of service providers based on fleet size using negative binomial fixed effect regression model and K-means clustering, 3) Expanding micromobility to emerging economies: Using dynamic stated preference pivoting survey and panel data mixed logit model, I assessed the intentions to adopt shared micromobility in mid-sized cities of developing countries, where these innovative technology could be the first wave of decarbonizing transportation sector, and 4) Micromobility data application: I identified five usage-clusters of shared e-scooter trips using combination of Principal Component Analysis (PCA) and K-means clustering to propose a novel framework for using micromobility data to inform data-driven decision on broader policy goals. Based on the key findings of the research, I provide five recommendations as follows: 1) decision-makers should be proactive in incorporating new travel technologies like shared micromobility, 2) city governments should leverage shared micromobility usage and operation data to empower the decision-making process, 3) each shared micromobility vehicles should be approached uniquely for improving road safety, 4) city governments should consider regulating the number of service providers and their fleet sizes, and 5) decision-makers should prioritize expanding shared micromobility in emerging economies as one of the first efforts to the decarbonizing transportation sector

A Framework for Integrating Transportation Into Smart Cities

In recent years, economic, environmental, and political forces have quickly given rise to “Smart Cities” -- an array of strategies that can transform transportation in cities. Using a multi-method approach to research and develop a framework for smart cities, this study provides a framework that can be employed to: Understand what a smart city is and how to replicate smart city successes; The role of pilot projects, metrics, and evaluations to test, implement, and replicate strategies; and Understand the role of shared micromobility, big data, and other key issues impacting communities. This research provides recommendations for policy and professional practice as it relates to integrating transportation into smart cities

Chapter 13 - Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes

Shared mobility—the shared use of a vehicle, bicycle, or other mode—is an innovative transportation strategy that enables users to gain short-term access to transportation modes on an “as-needed” basis. It includes various forms of carsharing, bikesharing, scooter sharing, ridesharing (carpooling and vanpooling), transportation network companies (TNCs), and microtransit. Included in this ecosystem are smartphone “apps” that aggregate and optimize these mobility options, as well as “courier network services” that provide last mile package and food delivery. This chapter describes different models that have emerged in shared mobility and reviews research that has quantified the environmental, social, and transportation-related impacts of these services

Identify the success factors of shared micromobility systems in European cities: How could a shared micromobility system be successful in the city of Bodø ?

Masteroppgave i Global ledelse (tidl. energiledelse) - Nord universite

Not all green innovations are created equal : Consumer innovativeness and motivations in the adoption of shared micromobility

The purpose of this thesis is to understand how consumer innovativeness and motivations relate to the decision to adopt green innovations. This thesis examines two forms of green transport innovations, shared e-bikes and e-scooters, which are part of the shared micromobility phenomenon. The penetration of shared micromobility into the market is estimated to increase in the upcoming years, and increasing interest in its use has become evident. However, there are controversies surrounding its impact on society, partly due to how the vehicles are used. This raises questions concerning who the consumers are and what motivates them to use this mode of transport. I employed two cross-sectional surveys to investigate how domain-specific innovativeness and motivations influenced the decision to adopt shared e-bikes and e-scooters. I demonstrate the relevance of the use of two domain-specific innovativeness (transport innovativeness and eco-innovativeness) and four different motivations (instrumental, environmental, hedonic, and social motivations). Specifically, transport innovativeness and eco-innovativeness were positively correlated with decisions to use shared e-bikes and e-scooters. Hedonic motivations had the strongest effects, while social motivations had the weakest, if not insignificant, impact. Environmental motivations were positively significant when other motivations were not considered, but these effects became negative when instrumental and hedonic motivations were taken into account. I also show the differences in these factors between users and non-users, as well as between shared e-bike users and shared e-scooter users. As expected, users had a higher level of transport innovativeness and eco-innovativeness. Users and non-users also differed in their perceptions of the environmental, hedonic, symbolic, and instrumental benefits of shared e-bikes and e-scooters, with users being more sensitive to these benefits. Theoretically, this thesis creates a more nuanced understanding of the diffusion of innovations by showing that products are not limited to only one domain. In addition, it outlines similarities and differences in consumer motivations between two comparable and emergent innovations that are purportedly green. This thesis shows that, although shared e-bikes and e-scooters are promoted similarly, consumer motivations for their adoption can still differ. Of note, this thesis helps to explain why some green innovations could become controversial due to their users’ motivations. Practically, this thesis could help to formulate short- and long-term strategies for shared micromobility providers and policies for transport agencies and city planners. It could also help to understand the environmental impact of shared micromobility and how it could potentially address transport-related environmental problems

The effect of COVID restriction levels on shared micromobility travel patterns: A comparison between dockless bike sharing and e-scooter services

The spread of the coronavirus pandemic had negative repercussions on the majority of transport systems in virtually all countries. After the lockdown period, travel restriction policies are now frequently adapted almost real-time according to observed trends in the spread of the disease, resulting in a rapidly changing transport market situation. Shared micromobility operators, whose revenues entirely come from their customers, need to understand how the demand is affected to adapt their operations. Within this framework, the present paper investigates how different COVID-19 restriction levels have affected the usage patterns of shared micromobility. Usage data of two dockless micromobility services (bike and e-scooters) operating in Turin (Italy) are analyzed between October 2020 and March 2021, a period characterized by different travel restriction levels. The average number of daily trips, trip distances and trip duration are retrieved for both services, and then compared to identify significant differences in trends as restriction levels change. Additionally, related impacts on the spatial dimension of the services are studied through hotspot maps. Results show that both services decreased during restrictions, however e-scooters experienced a larger variability in their demand and they had a quicker recovery when travel restrictions were loosened. Shared bikes, in general, suffered less from travel restriction levels, suggesting their larger usage for work and study-related trip purposes, which is confirmed also by the analysis of hotspots. E-scooters are both substituting and complementing public transport according to restriction levels, while usage patterns of shared bikes are more independent.Comment: Paper presented at the 101st Annual Meeting of the Transportation Research Board, Washington, D.C., January 9-13, 202

Community Transportation Needs and Willingness to Use Shared Micromobility: A Case Study of Fort Smith, Arkansas

Shared micromobility is utilized in “targeted service areas with the usage generally intended for short trips such as first- and last-mile connections to complete trips made via other modes, including transit” (Price et al., 2021). In the United States, this practice has especially taken off with the implementation of sharing-based systems. This is evidenced by ridership numbers in the United States growing from 84 million riders nationwide in 2018 to 136 million riders in 2019 (NACTO, 2020). Users often use their smart phone or another similar device to unlock the vehicle after paying a fee on the device through their credit card. While many people use these scooters or bikes as a novelty or purely for entertainment, “21% [of] adults would consider using e-scooters when available” (Mitra, 2020). The growing market for micromobility could result in changes in the way that the public commutes to their destination. E-scooters and bikes have potential to provide users the “last mile” of transportation. This, for instance, could be seen as a quarter-mile walk from the bus stop to a person’s place of employment. In urban areas, racial minorities and low-income users are almost twice as likely to use public transit (Anderson, 2016). Due to this growing market, it is important to analyze the ways low-income citizens will also be able to use scooter and bicycle sharing in cities in the US. Low-income users have less access to mobile phones (Pew Research Center, 2021). Additionally, 7.1 million Americans do not have access to a bank account (FDIC, 2020). Both of these factors combine into a possible user gap for low-income citizens regarding shared micromobility services. Utilizing data from users and cities, will assist municipalities and companies alike so they can implement micromobility in cities so that low-income communities can also take part. From implementation to public transit, to Sunday joy rides, micromobility has a chance to grow into a 2 mainstay in American cities. If this is the case, it is important that all people can utilize the system for effective public transportation. This thesis examines the transportation needs of citizens of low income communities in Fort Smith, Arkansas. This thesis is developed in conjunction with an NSF sponsored research project called SMILIES: Shared MicromobIlity for affordabLe-accessIblE Housing. SMILIES seeks to better link affordable housing and workplaces through shared micromobility by developing strategy for decision making. This thesis develops the survey that will be used in SMILIES to view the opinions of potential low-income users in the Fort Smith, Arkansas area