Factors influencing shared micromobility services: An analysis of e-scooters and bikeshare

Hosseinzadeh, Aryan; Karimpour, Abolfazl; Kluger, Robert

doi:10.1016/j.trd.2021.103047

Cited by 29 publications

(5 citation statements)

References 42 publications

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“…Te current study falls within the third stream of research. Tis group of research eforts focused on analyzing real-world dockless shared e-scooter trip data [6,[30][31][32][33][34][35][36]. Previous studies in this stream of research investigated the primary purpose of using e-scooter and found that these emerging mobility systems are mostly used for leisure rather than for commuting purposes [6,31].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Previously published studies on shared dockless e-scooters found that many factors increased e-scooter demand including commercial and industrial presence, population density, land use mix, access to transit, bike score, central business district locations, student populated regions, and weather conditions [19,30,31,39,40]. Te methodological approaches employed to study e-scooter data include negative binomial count models, linear mixed models, and spatial regression models (and variants such as spatial error and autoregressive error models) [30,31,33,34,39,40].…”

Section: Literature Reviewmentioning

confidence: 99%

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Modeling Dockless Shared E-Scooter Demand by Time of Day: A Case Study of Austin

Alsulami

Tirtha

Yasmin

et al. 2023

Journal of Advanced Transportation

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The goal of the current study is to identify and quantify the influence of various contributing factors on dockless e-scooter demand. Drawing on high-resolution e-scooter trip level data for 2019 from Austin, Texas, we develop census tract (CT) level demand data for four time periods of the day. The time-period specific data is partitioned for weekdays and weekends. Using the prepared datasets, we develop a joint panel linear regression (JPLR) model framework that accommodates for the influence of unobserved factors at multiple levels-CT, month, day, and time period levels. The analysis results indicate that the proposed JPLR models outperform the independent linear regression models for both weekdays and weekends. The results also manifest a significant association between e-scooter demand and several independent variables including sociodemographic attributes, transportation infrastructure variables, land use and built environment variables, meteorological attributes, and situational attributes. Further, several panel-specific correlation effects are found to be significant across four dimensions highlighting the importance of accommodating the influence of common unobserved factors on e-scooter demand across different time-of-day dimensions. The model validation exercise results revealed that the proposed models performed well compared to the independent models. Finally, the estimated models are employed to conduct a policy exercise illustrating the value of the estimated models for understanding CT level e-scooter demand on weekdays and weekends. The results indicate that land use mix, proportion of commuters, and season are some of the most influential factors for e-scooter demand.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Modeling Dockless Shared E-Scooter Demand by Time of Day: A Case Study of Austin

Alsulami

Tirtha

Yasmin

et al. 2023

Journal of Advanced Transportation

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“…Hosseinzadeh et al [74] examined how various factors affect shared micromobility services. Their two main goals were, on the one hand, to thoroughly examine how various weather-related factors, major holidays, and special events affect micromobility services, and, on the other hand, to compare the effects of these factors on e-scooters and bikeshares in Louisville, Kentucky.…”

Section: Factors Influencing the Adoption Of Micromobility In Urban T...mentioning

confidence: 99%

Micromobility in Urban Trail Paths: Expanding and Strengthening the Planning of 15-Minute Cities

Vizmpa,

Botzoris,

Lemonakis

et al. 2023

Land

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Contemporary urban planning models include urban trail paths. These are paths that create active transportation corridors within a city’s built environment, providing more sustainable travel, especially for short trips. The benefits of their use are plentiful, including improvements in commuters’ health, reductions in energy footprint, and socio-economic benefits for the entire society. In modern urban planning approaches such as the “15-minute city”, urban trail paths serve as connectors, facilitating access to amenities beyond the close-proximity concept of a “neighborhood”. They act as a way of connecting residents to other 15-minute cities/neighborhoods via safe routes, reducing extensive car use. Micromobility constitutes a novel approach to short trips with proven results. This paper explores the possibility of introducing micromobility as a means of connecting 15-minute cities/neighborhoods through urban trail paths. Through a literature review, an analysis is conducted of the opportunities arising from the introduction of micromobility, as well as on the factors influencing its sustained use in urban mobility and the public realm.

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“…From environmental, sociological, and economic perspectives, micromobility has the potential to promote a sustainable urban future . One frequently cited argument is that the rise of micromobility can contribute to the reduction of car use and the associated negative impacts, such as emissions, noise, and congestion (Wang et al, 2022), while also promoting the use of public transport, which includes buses, trams, trains, and the metropolitan underground railway system (hereinafter, metro) (Hosseinzadeh, Karimpour, et al, 2021;Oeschger et al, 2020). While the exact extent of the tangible bene ts of micromobility is still under debate (Sun & Ertz, 2022), its deployment in urban settlements has been gradually expanding, thus adding variety and complexity to urban transportation systems (Alessandretti et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Understanding multimodal mobility strategies of micromobility users in urban environments: Insights from Barcelona

Roig-Costa

Marquet

Arranz-López

et al. 2023

Preprint

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Micromobility, which includes bicycle-sharing systems, e-scooters, and moped-style scooters, has emerged as a popular alternative to traditional transport modes in urban environments, thus expanding the number of transportation options available to urban travellers. Previous research has primarily relied on trip-based data to explore the multimodal character of micromobility. However, existing evidence has failed to understand the ways in which urban travellers have reshaped their mobility strategies as a consequence of the introduction of micromobility. Using a travel survey (N = 902) set in Barcelona, Spain, cluster techniques are used to group micromobility users according to their frequency of use of three different micromobility modes (bicycle-sharing systems, private e-scooter, and moped-style scooter-sharing services). Then, logistic binomial regressions were used, in order to explore each cluster’s usage of traditional modes of transport, along with all potential weekly combinations between modes. Results show that most micromobility users rely on a single type of transport mode on a weekly basis. The models further indicate that e-scooter, shared bicycle, and moped-style scooter users develop different weekly mobility combination strategies. While personal micromobility options (private e-scooter) are associated with monomodal tendencies, sharing services (bicycle sharing and moped-style scooter sharing) encourage multimodal behaviours. These findings contribute to the limited knowledge concerning the role of some micromobility alternatives in creating more rational and less habit-dependent travel behaviour choices.

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Factors influencing shared micromobility services: An analysis of e-scooters and bikeshare

Cited by 29 publications

References 42 publications

Modeling Dockless Shared E-Scooter Demand by Time of Day: A Case Study of Austin

Modeling Dockless Shared E-Scooter Demand by Time of Day: A Case Study of Austin

Micromobility in Urban Trail Paths: Expanding and Strengthening the Planning of 15-Minute Cities

Understanding multimodal mobility strategies of micromobility users in urban environments: Insights from Barcelona

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