Mixed Logit Models for Travelers’ Mode Shifting Considering Bike-Sharing

Ye, Mao; Chen, Yajing; Yang, Guixin; Wang, Bo; Hu, Qizhou

doi:10.3390/su12052081

Cited by 20 publications

(16 citation statements)

References 38 publications

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“…With regard to e-bike (including e-cargobike) sharing, it has been found that a range of recurring demographic factors, such as age, gender, income, and education, tend to be associated with bike sharing usage or intention [6,11,14,15,17,22]. For instance, in their review of shared e-mobility services, Liao and Correia [6] conclude that shared mobility users are mostly male, middle-aged, and tend to have higher levels of income and education (see also [23]).…”

Section: Literature Reviewmentioning

confidence: 99%

Exploring the potential of shared electric vehicles from e‐mobility hubs as an alternative for commute and food shopping trips

Bösehans

Kavta

Bell

et al. 2023

IET Intelligent Trans Sys

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Electric shared mobility hubs, called eHUBs, offer users access to a range of shared electric vehicles, including e‐bikes, e‐cargobikes, and e‐cars. Through the diversity of modes offered, eHUBs provide mobility solutions for different target groups and trip purposes. In this study, potential users’ willingness to use shared electric vehicles from eHUBs as either a commute or food shopping trip alternative was analysed using logistic regression methods. Results indicated that half of respondents were willing to use shared electric vehicles for at least a few of their regular commute or food shopping trips, although this proportion dropped substantially if considering the use of shared vehicles in combination with public transport. Across modes and trip purposes, holding a pro‐shared mobility attitude and belonging to the youngest age group strongly increased the willingness to use shared modes. Yet, while eHUBS may offer a potential alternative for at least some of people's regular commute or food shopping trips, cross‐mode shifts may be limited. That is, car drivers show a greater interest in shared e‐cars, whereas cyclists show a greater interest in e‐bikes and e‐cargobikes with public transport. Further influential factors, as well as implications for both shared mobility providers and local authorities, are discussed.

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Section: Literature Reviewmentioning

confidence: 99%

Exploring the potential of shared electric vehicles from e‐mobility hubs as an alternative for commute and food shopping trips

Bösehans

Kavta

Bell

et al. 2023

IET Intelligent Trans Sys

View full text Add to dashboard Cite

show abstract

“…In the context of Asian or developing countries, studies undertaken in China suggest that habitual personal vehicle users are less likely to shift to a potential new transit mode (12). Studies on bike-sharing identify younger, highly educated, and low-income travelers without a car as having a higher propensity to use bikesharing (15) These studies use a choice-based sampling strategy based on the primary mode choice, thus leading to potential selectivity bias. Another issue is the use of only a single target mode for shift and assuming independence between the original mode and the mode shift decision.…”

Section: Mode Shift and The Type Of Modes Shiftedmentioning

confidence: 99%

Joint Model of Sustainable Mode Choice for Commute, Shift Potential and Alternative Mode Chosen

Ramakrishnan

Srinivasan

Mondal

et al. 2021

Transportation Research Record: Journal of the Transportation R

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Rising traffic congestion and severe air pollution in urban areas have led policymakers to find appropriate strategies to encourage the use of sustainable modes. In this context, this paper investigates three choice dimensions related to the work commute travel: (i) Whether and to what extent are sustainable modes considered? (ii) What factors influence the propensity to shift from the primary work commute mode? (iii) Which mode is most likely to be chosen conditional on the decision to shift? These dimensions are analyzed using data of workers from Chennai, India. As the three choices of an individual may be correlated and mutually endogenous because of common and persistent psychological attributes and modal service characteristics, they are modeled using a multi-dimensional probit model. The results show significant evidence of endogeneity, state-dependence, and unobserved correlation across these dimensions leading to significant improvement in fit measures. The results show that perceptions of walkability and environmental impacts of travel modes affect only the consideration of sustainable modes, while vehicle ownership and accessibility to transit affect all three dimensions. Four different behavioral motivations for the decision to shift from the usual mode: dissatisfaction with service attributes, activity constraints, multimodal travel pattern, and inertia, were identified. The mode to which shift occurs is influenced by household vehicle fleet (number and type), exclusive availability to the given decision-maker, and work distance. The insights from this study can be used to identify suitable factors and frame policies to promote sustainable mode choice at various levels.

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“…However, as the price of the private car became much cheaper, carsharing turned to be less attractive until the rising fuel prices and heavy road congestion have drawn the public's attention back to carsharing [8]. In recent years, shared mobility becomes a hot topic in transport development, and so does electrification [12,16,17]. Electric carsharing, a form of carsharing which rents EVs to people, combines these two items and is expected to inherit their positive impacts on sustainable transport development, including guiding the public to form a sustainable travel behavior [6], improving the accessibility and flexibility of the urban transport [12], reducing car ownership [5], vehicle kilometres of travel [9], traffic congestion [18], parking land use [18], and greenhouse gas emissions [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Friend-Invitation Promotion Scheme Used in Electric Carsharing: Empirical Analysis and Policy Implications

Xie

Sun

ShuangJian³

2021

Journal of Advanced Transportation

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The combination of electric vehicle (EV) and carsharing is expected to provide social and environmental benefits, like encouraging sustainable travel behaviors (reducing car ownership and vehicle kilometres of travel) and improving the accessibility and flexibility of urban transport. Thus, electric carsharing is encouraged to be adopted for daily trips, and the operators propose the friend-invitation promotion scheme for the membership expansion. This study explores the effectiveness of this scheme and the characteristics of the scheme participants and their invited friends (e.g., age, friend-invitation pattern, and EV rental pattern). The analysis found that 28.4% of these invited friends would make at least one EV rental after registration, whereas 30.4% of the other members who registered in the same period would do so, indicating that these invited friends were less active. Therefore, suggestions are given based on the EV rental pattern of these invited friends (preferring a longer journey using a smaller but cheaper EV) to enhance the effectiveness of the friend-invitation promotion scheme.

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Mixed Logit Models for Travelers’ Mode Shifting Considering Bike-Sharing

Cited by 20 publications

References 38 publications

Exploring the potential of shared electric vehicles from e‐mobility hubs as an alternative for commute and food shopping trips

Exploring the potential of shared electric vehicles from e‐mobility hubs as an alternative for commute and food shopping trips

Joint Model of Sustainable Mode Choice for Commute, Shift Potential and Alternative Mode Chosen

Friend-Invitation Promotion Scheme Used in Electric Carsharing: Empirical Analysis and Policy Implications

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