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Cities throughout the world have implemented bike-share systems as a strategy for expanding mobility options. While these have attracted substantial ridership, little is known about their influence on travel behavior more broadly. The aim of this study was to examine how shared electric bikes (e-bikes) and e-scooters influence individual travel attitudes and behavior, and related outcomes of physical activity and transportation equity. The study involved a survey in the greater Sacramento area of 1959 households before (Spring 2016) and 988 after (Spring 2019) the Summer 2018 implementation of the e-bike and e-scooterservice operated by Jump, Inc., as well as a direct survey of 703 e-bike users (in Fall 2018 & Spring 2019). Among householdrespondents, 3–13% reported having used the service. Of e-bike share trips, 35% substituted for car travel, 30% substituted for walking, and 5% were used to connect to transit. Before- and after-household surveys indicated a slight decrease in self-reported (not objectively measured) median vehicle miles traveled and slight positive shifts in attitudes towards bicycling. Service implementation was associated with minimal changes in health in terms of physical activity and numbers of collisions. The percentages of users by self-reported student status, race, and income suggest a fairly equitable service distribution by these parameters, but each survey under-represents racial minorities and people with low incomes. Therefore, the study is inconclusive about how this service impacts those most in need. Furthermore, aggregated socio-demographics of areas where trips started or ended did not correlate with, and therefore are not reliable indicators of, the socio-demographics of e-bike-share users. Thus, targeted surveying of racial minorities and people with low-incomes is needed to understand bike-share equity.

The Mobility on Demand (MOD) Sandbox Demonstration Program provides a venue through which integrated MOD concepts and solutions, supported through local partnerships, are demonstrated in real-world settings. For each of the 11 MOD Sandbox Demonstration projects, a MOD Sandbox Independent Evaluation was conducted that includes an analysis of project impacts from performance measures provided by the project partners and an assessment of the business models used. This document presents the Evaluation Report for the BART Integrated Carpool to Transit Access Program project. The project tested a number of hypotheses that explored the project impacts on carpooling, costs, enforcement, ridership, parking, and vehicle miles of travel (VMT). The evaluation generally found that the project increased overall carpooling to BART, commensurately increased the utilization of parking spaces by carpooling vehicles, and increased the number of people per vehicle parking at BART stations. The evaluation determined that the overall cost of enforcement per carpool space declined, primarily because spaces used for carpools increased without significantly increased enforcement burden. The evaluation did not have data available to determine whether illegal use of carpool spaces had changed significantly as a result of the project. On the related matter of enforcement, the evaluation did not have data to quantify changes in fraudulent use of carpool spaces and, instead, relied on discussions with enforcement staff, which suggested that fraudulent use had dropped as a result of the project. The evaluation did find that the project produced a wider distribution of arrival times to carpool spaces, which was an objective of BART, to permit greater flexibility of travel times in the morning for carpooling riders. The evaluation found that the project likely increased BART ridership, although not by margins large enough to be statistically noticeable within normal fluctuations of station ridership. Data were not available to determine whether this increase in ridership raised revenue that exceeded the costs of the project. However, users reported reduced personal transportation costs a result of the project. The project found that overall VMT very likely declined as result of the project due to the reduced driving alone to stations. Finally, expert interviews with project personnel produced lessons learned on implementation and policy that may inform similar projects in the future.

The goal of this study is to assess and quantify the potential employment accessibility benefits of Shared Autonomous Mobility Service (SAMS) commute modes across a large diverse metropolitan region considering heterogeneity in the working population. To meet this goal, this study employs a welfare-based (i.e. logsum-based) measure of accessibility, obtained via estimating a hierarchical work destination-commute mode choice model. The employment accessibility logsum measure incorporates the spatial distribution of worker residences and employment opportunities, the attributes of the available commute modes, and the characteristics of individual workers. This research further captures heterogeneity of workers using latent class analysis (LCA). The LCA model inputs include the socio-demographic characteristics of workers to subsequently account for different worker clusters valuing different types of employment opportunities differently. The accessibility analysis results indicate: (i) the accessibility benefit differences across latent classes are modest but young workers and low-income workers do see higher benefits than high- and middle-income workers; (ii) there are substantial spatial differences in accessibility benefits with workers living in lower density areas benefiting more than workers living in high-density areas; (iii) nearly all the accessibility benefits come from the SAMS-only mode as opposed to the SAMS+Transit mode; and (iv) the SAMS cost per mile assumption significantly impacts the magnitude of the overall employment accessibility benefits.

Low-income rural residents, especially those who do not own a car, have limited transportation options for accessing jobs, health care, education, healthy food, and other basic services. Rural transit service is often expensive, infrequent, and hard to access because of long travel distances and low development densities. Transit providers face very high operating costs of fixed-route and dial-a-ride transit services because of low farebox recovery rates.Shared-use mobility services such as ridehailing and carsharing largely serve major metropolitan areas. However, rural governments are beginning to consider whether these types of services may be able to augment existing transit services while providing cost-effective transportation access to rural residents.This policy brief summarizes findings from a UC Davis study in which researchers compared the cost-effectiveness of existing inter-city transit service in rural disadvantaged communities in California’s San Joaquin Valley to hypothetical ridesharing and carsharing services. The researchers also reviewed existing shared-use mobility pilots and consulted with experts in shared mobility and local transportation planning to develop concepts for future shared mobility pilot programs in the San Joaquin Valley.View the NCST Project Webpage

As the sharing economy develops rapidly, a comprehensive overview of the situation on the European shared mobility scene is becoming increasingly necessary. This paper analyzes the state of shared mobility in European countries and observes how European countries can be segmented based on the populations' participation in the economy of shared mobility. We observed 12 indicators of shared mobility in 26 countries of the European Union, for which the data were available. We used the K-means algorithm of cluster analysis. The results show that the highest percentage of shared mobility users belongs to the group of educated and young people aged between 16 and 35. In addition, three segments of European countries were obtained using cluster analysis. Cluster analysis reveals apparent differences in the use of shared mobility websites and applications, as well as differences in education and income among segments. Additionally, the results indicate that the geographical position of the country does not affect the placement within the cluster, as the second and the third cluster contain countries from different parts of Europe. The results of our analyses can be helpful in decision-making and allocating marketing and transportation resources to specific target markets, as well as for development of market-entry strategies in specific markets.

Carsharing is a service in which individuals gain the benefits of private vehicle use without the costs and responsibilities of ownership. Individuals typically access vehicles by joining an organization that maintains a fleet of cars and light trucks. Fleets are usually deployed within neighborhoods and at public transit stations, employment centers, and colleges and universities. Typically, the carsharing operator provides gasoline, parking, and maintenance. Generally, participants pay a fee each time they use a vehicle (Shaheen,Cohen,&Zohdy,2016). Carsharing includes three types of service models, based on the permissible pick-up and drop-off locations of vehicles. This toolkit is organized into seven sections. The first section reviews common carsharing business models. The next section summarizes research on carsharing impacts. The remaining sections present policies for parking, zoning, insurance, taxation, and equity. Case studies are located throughout the text to provide examples of existing carsharing programs and policies.

The confluence of vehicle electrification, sharing and pooling, and automation alters petroleum-fueled, human-piloted, and privately-owned and operated vehicles for personal mobility in ways that raises such questions as, “Are such systems safe and secure?” and, “Who is being kept safe and secure from what (or whom)?” Answers are implied by filling in the “who” and “whom” of the second question: system, product, producer, road, and user. This white paper focuses on (actual and potential) users of systems of electrically-powered, shared, and automated vehicles (e-SAVs) as well as other road-users, e.g., pedestrians and cyclists. The role of user perceptions of safety and security are reviewed to create an initial framework to evaluate how they may affect who will initially use systems of e-SAVs for personal mobility and how safety and security will have to be addressed to foster sustained transitions. The paper will primarily be a resource for e-SAV user research, but will also inform system development, operation, and governance. This white paper offers an overarching framework grounded in the social theory of “risk society” and thus organizes past work that, typically, focuses on only one of the constituent technologies or on one dimension of safety or security, e.g., collision avoidance as a subset of road safety.View the NCST Project Webpage

Abstract Background Platform-based fast delivery is developing rapidly in many cities across the world, especially in the food sector. Yet knowledge about the characteristics and the activity patterns of delivery couriers is scarce, especially in terms of their mobility behavior. Methodology Based on two questionnaire surveys conducted in 2020 and 2021 with 300 and 500 couriers respectively, this article analyses the profiles, motivations and mobility patterns of couriers working in Paris (France), with a focus on the impacts of the pandemic. Results First, the analysis of the profiles and motivations of couriers reveals that platform-based delivery is largely a temporary activity performed by young males of foreign origin, and undertaken as a student job or an entry to the labor market. Second, data on mobility patterns confirm that platform-based delivery is a dangerous activity with a high risk of road accidents. Moreover, many couriers break the law in order to increase their income by using motorized two-wheelers that are not legally permitted in France. We also show the use of shared bikes, which seems to be a great support tool for couriers who are starting work in this sector or have a problem with their own bikes. Third, the pandemic prompted many students to become platform-based delivery couriers in order to compensate for the lack of student jobs. It also worsened the working conditions of the majority of platform-based couriers. These findings raise new urban policy challenges and also new avenues for research in terms of topics and methods.

In rural regions, needs-based mobility services play an important role in the provision of public services. Shared Mobility Services can optimally complement local public transportation such as buses and trains, even in rural regions, and support the transformation of transportation. There is already research on Shared Mobility Services in the literature, but there is no comparison between all of Germany-wide and a specific municipality. We were interested in learning to what extent there is acceptance among citizens and what their usage behavior is towards such new alternatives. We also aimed to find out whether there are differences between large cities and rural regions and to what extent they differ from each other. In this case study, interplay was demonstrated using the example of a funded Smart City mobility project in a German rural municipality. The objective was to show whether the potential exists to initiate traffic turnaround with the help of Shared Mobility Services. In a quantitative survey of 418 German citizens, 114 of them from the rural municipality, the acceptance and usage behavior of Shared Mobility Services (in the form of car, bike and e-scooter sharing) was investigated. The results show that participants are very interested in Shared Mobility Services and have already gained initial experience with such services. However, there is still a lack of comprehensive services; for instance, the demand for car sharing is still too low, as many citizens still own a private vehicle. Our results show that citizens are too little informed about Shared Mobility Services and that these services need to be advertised much more strongly and clearly, both in analog and digitally. Our study shows that traffic turnaround can be achieved and that many citizens can imagine greater use of Shared Mobility Services in their everyday lives in the future. However, for this to happen, the necessary infrastructure must be in place in rural regions, and local authorities must motivate citizens with sufficient educational work about what is on offer and how to use it.

We study the operational problem of shared autonomous electric vehicles that cooperate in providing on-demand mobility services while maximizing fleet profit and service quality. Therefore, we model the fleet operator and vehicles as interactive agents enriched with advanced decision-making aids. Our focus is on learning smart charging policies (when and where to charge vehicles) in anticipation of uncertain future demands to accommodate long charging times, restricted charging infrastructure, and time-varying electricity prices. We propose a distributed approach and formulate the problem as a semi-Markov decision process to capture its stochastic and dynamic nature. We use cooperative multiagent reinforcement learning with reshaped reward functions. The effectiveness and scalability of the proposed model are upgraded through deep learning. A mean-field approximation deals with environment instabilities, and hierarchical learning distinguishes high-level and low-level decisions. We evaluate our model using various numerical examples based on real data from ShareNow in Berlin, Germany. We show that the policies learned using our decentralized and dynamic approach outperform central static charging strategies. Finally, we conduct a sensitivity analysis for different fleet characteristics to demonstrate the proposed model's robustness and provide managerial insights into the impacts of strategic decisions on fleet performance and derived charging policies. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.1187. [ABSTRACT FROM AUTHOR]

This study provides a comprehensive review of the significant elements in sustainable transportation systems with shared mobility. The main subsets of shared mobility includes ridesharing, carsharing, shared micromobility, on-demand ride services, and shared autonomous vehicles (SAVs). This paper revisits the related studies in the last decade since shared mobility spread via the emergence of smartphones and numerous applications. A framework is proposed to describe the shared mobility systems and understand the interactions among various elements in shared mobility systems, such as the supply and demand relationship between users and enterprises. Based on this framework, many fundamental research problems of shared mobility systems are summarized to cover travel behavior, enterprise supply, government policy, and sustainability. With the sustainability theme of shared mobility, we review the literature on the impacts of shared mobility on transportation sustainability. It is discovered that shared mobility has many advantages and improves urban transportation systems in many aspects, but these benefits vary with travel behavior and enterprise supply. We also discuss how government policies regulate travel behavior and enterprise supply in the sustainable development of urban transportation systems. [ABSTRACT FROM AUTHOR]

Shared electric kick scooters (SEKS) have become widespread in many cities worldwide with great expectations from both users and municipalities. Most cities have not yet passed specific legislation to regulate this new phenomenon, thereby increasing uncertainties across different players such as users, operators, etc. This research provides guidelines for regulating SEKS in urban areas for their successful implementation, taking advantage of a collaborative approach with expert stakeholders that look at the regulation problem from different perspectives. The study focuses on the case of Spain where SEKS have been booming over the last few years. The methodology applied follows a three-step process consisting of the identification of crucial issues and key expert stakeholders, a general survey to them, and a final focus group intended to reach consensus. The paper provides regulatory recommendations in four main areas: market access, technical requirements, traffic and safety, and supervision. It finds large agreement on key aspects such as promoting a homogeneous regulation across the municipalities within the same metropolitan area; establishing fixed bases for parking in the city centre while allowing free floating in low density areas located in the outskirts; and promoting an integration with the public transportation system. • Identification of key regulatory aspects for shared electric kick scooters services. • Collaborative approach with key expert stakeholders: survey and focus group. • Regulatory recommendations for shared electric kick scooters in urban areas. [ABSTRACT FROM AUTHOR]

Electric Micromobility (EM) and the use of dockless shared electric scooters (DSES) has rapidly grown in many cities worldwide. They are promoted as an accessible, low-emissions, versatile, and low-effort alternative. This article conducts a systematic review of DSES, considering their evolution, operation, regulations, user profile, environmental impact, safety, and pricing. The review shows age, income, and gender gaps among their users as most of them are young, male, high-income adults. DSES adopters come mainly from public transport, walking, and cycling. Their environmentally friendly label needs to be analyzed according to the city's context; their distribution and collection logistics impacts, and the vehicle's service life. The review shows significant differences in the way cities have regulated the service. One of the most significant potential contributions from DSES to urban mobility is the possibility to be integrated with public transport, implementing the Mobility-as-a-Service concept. [ABSTRACT FROM AUTHOR]

Cities' high traffic concentration, fast technological change, resource scarcity and growing environmental concerns accentuate competing tensions between stakeholders, transport modes and policies in the mobility sector. Tensions become even more salient in shared mobility – a complex yet relatively new phenomenon at the intersection between sharing economy and the transport sector – and raise numerous concerns for meeting sustainability objectives. The purpose of this paper is to identify conflicting demands associated with shared mobility by conducting a systematic literature review. Our results reveal several contradictions related to shared mobility and sustainability goals, and relations between those constantly evolving in a dynamic fashion. Thus, although shared mobility represents a step forward in achieving sustainability in theory, in practice, this task is only partially completed due to existing inherent contradictions. A paradox perspective on shared mobility, proposed in this paper, provides grounds for revisiting policy actions and finding workable solutions for practitioners. • Competing tensions exist between stakeholders, transport modes and policies in the mobility sector and more saliently within shared mobility. • Attempts to resolve these often result in repeated emergence of persistent tensions. • We conduce a systematic literature review to identify such conflicts following the Paradox literature. • In our approach, we treat tensions not just as static alternatives, but as interrelated elements that can co-exist in a dynamic relationship. • We show that although shared mobility represents an attempt to meet environmental, economic, and social goals, it only partially contributes to these, and resulting issues require decision makers' attention. [ABSTRACT FROM AUTHOR]

Seamless, efficient transport intermodality is a key aspect of the transition of cities toward sustainable mobility. The new "shared mobility hub" concept is increasingly gaining attention as a potential way to make this urgently needed transition happen. The present paper aims to provide an insightful view of the promising concept of shared mobility hub, initially by looking into the existing literature on its definitions and how they are classified to form different typologies. Following that, a new, flexible typology framework for shared mobility hubs is proposed. This is then applied to several existing hubs in five different cities in The Netherlands (Amsterdam, Eindhoven and Helmond), Spain (Sant Cugat de Vallès, Metropolitan Area of Barcelona), and Portugal (Lisbon). As these countries have different shared mobility policies in place and their citizens have very different mobility habits, we were able to reflect on how the proposed typology functions in varied contexts. This paper contributes to the ongoing discussion of a very timely topic in Europe and worldwide, which is the need for the deployment of a new generation of mobility hubs, with an emphasis on shared mobility. We trust that the suggested typology can be useful to policy-makers, local authorities, and transport and urban planners, as it can help with the conducting of a first effective screening with regard to which type of hub is needed for each specific case. [ABSTRACT FROM AUTHOR]

Car-sharing services are developing at an ever-increasing pace. Taking into account the reduction of carbon dioxide emissions and pursuit of the sustainable development of transport, implementing electric cars in car-sharing fleets is being proposed. On the one hand, these types of vehicles are referred to as emission-free, but on the other hand, their environmental friendliness is questionable due to the emission of carbon dioxide during the production of energy to power them. Although many scientific papers are devoted to the issue of reducing emissions through car sharing, there is a research gap concerning the real production of carbon dioxide by car-sharing vehicles during car-sharing trips. To fill this research gap, the objective of the article was to analyze the actual level of carbon dioxide emissions from combustion and electric vehicles from car-sharing systems produced when renting rides. The test results showed that the electric car turned out to be significantly less emitting. The use of electric vehicles in car-sharing fleets can reduce carbon dioxide emissions from 14% to 65% compared to using cars with internal combustion engines. However, the key role during car-sharing trips is played by the driving style of the drivers, which has been omitted from the literature to date. This should be properly regulated by service providers and focus on the proper use of energy from electric vehicle batteries, especially at low temperatures. The article provides support for operators planning to modernize their fleet of vehicles and fills the research gap concerning car-sharing emissions. [ABSTRACT FROM AUTHOR]

Moped-style scooter sharing services (MSS) offer short-period renting for daily urban mobility and are gaining popularity in cities worldwide. MSS provide substantial promise in reducing car-dependency and helping sustainability goals, but also significant risks in terms of spatial access equity and social justice. In recent years, European cities have been testing different regulation strategies for MSS but not always succeeding regarding social equity and spatial accessibility criteria. In this context, this study employs a semi-structured interviewing approach to discuss the main existing MSS regulation models. The aim is to understand how experts, policymakers, and private operators assess the strengths and weaknesses of each model to guarantee spatial and social equity regarding accessibility to the service, while preserving the long-term economic interests of private operators. Our results show a diversity of opinions, with solid consensus on proposing an alternative to the Barcelona regulatory model (capped vehicle licenses, uncapped number of operators), ranging from a numerus clausus model (Paris or Amsterdam) to a laissez-faire model (Madrid or Berlin), based on an open dialogue between administrations and the private sector. However, most respondents noted that the natural path of the regulation (as has happened in the past with other transport innovations) is towards a close public-private partnership model, with greater management and control capacity by the public sector. This option generates the greatest consensus of favouring a more spatial and socially equitable service while preserving its economic viability, although it would involve significant commitment and investment of the public sector. These findings provide valuable feedback for policymakers and transport regulators on how to approach micromobility and MSS regulation. • Mobility stakeholders defend up to four suitable MSS regulation models. • Current MSS regulations fail in considering spatial and social equity goals. • A close public-private collaboration (PPC) model is the one with the most consensus. • A close PPC model would involve a significant investment of the public sector. [ABSTRACT FROM AUTHOR]

Shared electric mobility hubs, or eHUBs, offer users access to a range of shared electric vehicles on demand. However, little is currently known about what the characteristics of potential users of this novel type of shared mobility are. This makes it difficult to plan the location of hubs and to provide facilities, which ultimately will determine their success. This paper therefore seeks to identify potential users based on an in-depth case study of a representative sample of the Municipality of Amsterdam population. The analysis employed an attitudinal market segmentation approach supported by the Theory of Diffusion of Innovations (DOI). The analysis identified four specific target groups, each with a different propensity to use eHUBs in the future. In our sample, two groups expressed an interest in using eHUBs. The first group consists of highly educated and non-car owning young adults (19% of the sample), whereas the second group shows a higher level of car ownership and a greater number of households with children (69% of the sample). The two remaining groups comprise the majority of laggards (52%), despite only representing 12% of the sample. They tend to be older, less educated, and live in a household without children. The four groups are further distinguished based on their current shared mobility use, traveler identity, and perceived barriers to using shared electric vehicles. Finally, general recommendations to practitioners and policymakers to increase the uptake of shared mobility, including paying attention to the availability, cost, and convenience of shared mobility options, are provided. [ABSTRACT FROM AUTHOR]

Carsharing, as an innovative mobility option, can potentially support the urban transition towards a more sustainable mobility system and achieving sustainable development goals. This short communication aims at providing the status of carsharing services in Italy, with a focus on Turin, before and after the COVID-19 pandemic. In this regard, an overview of the role of carsharing in urban traffic is provided. Then, carsharing services in Italy before and after the pandemic are mapped. Accordingly, the implications of the pandemic outbreak for carsharing services are discussed. The provided insights confirm that although carsharing services have been affected by the pandemic, even after returning to normal life, the usage of carsharing is still far below its pre-pandemic level in Italy. Finally, to support sustainable mobility and incentivize using shared mobility services, a research agenda for further research is proposed, targeting the research gaps regarding (i) the factors leading to lower usage of carsharing after the pandemic, (ii) potential solutions and policies to support carsharing services return to their pre-pandemic level and exceeding it, and (iii) examining the impact of provided supports by governments during the pandemic, such as bonuses for purchasing bikes and scooters, on the adoption of carsharing services for the post-pandemic era. [ABSTRACT FROM AUTHOR]

Electric scooter sharing mobility services have recently spread in major cities all around the world. However, the bad parking behavior of users has become a major source of issues, provoking accidents and compromising urban decorum of public areas. Reducing wild parking habits can be pursued by setting reserved parking spaces. In this work, we consider the problem faced by a municipality that hosts e-scooter sharing services and must choose which locations in its territory may be rented as reserved parking lots to sharing companies, with the aim of maximizing a return on renting and while taking into account spatial consideration and parking needs of local residents. Since this problem may result difficult to solve even for a state-of-the-art optimization software, we propose a hybrid metaheuristic solution algorithm combining a quantum-inspired ant colony optimization algorithm with an exact large neighborhood search. Results of computational tests considering realistic instances referring to the Italian capital city of Rome show the superior performance of the proposed hybrid metaheuristic.

One of the most significant financial benefits of a shared mobility mode such as ridesharing is cost savings. For this reason, a lot of studies focus on the maximization of cost savings in shared mobility systems. Cost savings provide an incentive for riders to adopt ridesharing. However, if cost savings are not properly allocated to riders or the financial benefit of cost savings is not sufficient to attract riders to use a ridesharing mode, riders will not accept a ridesharing mode even if the overall cost savings is significant. In a recent study, the concept of discount-guaranteed ridesharing has been proposed to provide an incentive for riders to accept ridesharing services through ensuring a minimal discount for drivers and passengers. In this study, an algorithm is proposed to improve the performance of the discount-guaranteed ridesharing systems. Our approach combines a success rate-based self-adaptation scheme with an evolutionary computation approach. We propose a new self-adaptive metaheuristic algorithm based on success rate and differential evolution for the Discount-Guaranteed Ridesharing Problem (DGRP). We illustrate effectiveness of the proposed algorithm by comparing the results obtained using our proposed algorithm with other competitive algorithms developed for this problem. Preliminary results indicate that the proposed algorithm outperforms other competitive algorithms in terms of performance and convergence rate. The results of this study are consistent with the empirical experience that two people working together are more likely to come to a correct decision than they would if working alone.

Dynamic and responsive transportation systems are a core pillar of equitable and sustainable communities. Achieving such systems requires comprehensive mobility data, or data that reports the movement of individuals and vehicles. Such data enable planners and policymakers to make informed decisions and enable researchers to model the effects of various transportation solutions. However, collecting mobility data also raises concerns about privacy and proprietary interests. We argue that a middle-ground approach, in which data are shared in specific contexts and managed by a trusted third party, can capture the benefits of data sharing while minimizing risks. This brief provides an overview of the top needs and challenges surrounding mobility data sharing and presents relevant policy strategies.

Dynamic and responsive transportation systems are a core pillar of equitable and sustainable communities. Achieving such systems requires comprehensive mobility data, or data that reports the movement of individuals and vehicles. Such data enable planners and policymakers to make informed decisions and enable researchers to model the effects of various transportation solutions. However, collecting mobility data also raises concerns about privacy and proprietary interests. We argue that a middle-ground approach, in which data are shared in specific contexts and managed by a trusted third party, can capture the benefits of data sharing while minimizing risks. This brief provides an overview of the top needs and challenges surrounding mobility data sharing and presents relevant policy strategies.

In many evacuations including wildfire evacuations, public agencies often do not have enough resources to evacuate and shelter all citizens. Consequently, we propose that the sharing economy, through private companies and/or private citizens, could be leveraged in disasters for transportation and sheltering resources. To assess this feasibility, we distributed surveys to individuals impacted by three major wildfires in California: 1) the 2017 October Northern California Wildfires (n=79), 2) the 2017 December Southern California Wildfires (n=226), and 3) the 2018 Carr Wildfire (n=284). Using these data, we find that private citizens are moderately to highly likely to share transportation and sheltering resources in future disasters, but numerous reservations persist about sharing. We also find significant spare capacity in evacuating vehicles and potential homes. To supplement this work, we also conducted four focus groups (n=37) of vulnerable populations to determine the benefits and limitations of a sharing economy strategy in terms of equity. Groups included low-income (2017 December Southern California Wildfires), older adult (2017 October Northern California Wildfires), individuals with disabilities (2017 October Northern California Wildfires), and Spanish-speaking (2018 Mendocino Complex Wildfire). We find that while severe equity limitations exist, groups were able to develop several recommendations for successfully leveraging sharing economy resources for the general population and their specific vulnerable group. We conclude with several local agency and statewide recommendations for building a sharing economy framework for California to prepare for future evacuations.

University students are young, open to new technologies, and their perceptions of the Shared Autonomous Vehicles (SAVs) may indicate their travel behaviors in the future. College towns in small urban or suburban areas offer researchers a unique environment to understand the travel behaviors of future commuters, and test emerging mobility services, such as SAVs. The study performs a survey with the aim of understanding university student perception regarding SAVs. The survey was conducted among the University of Alabama students in Tuscaloosa. The key survey questions include their knowledge and attitudes about AV and shared mobility. The results showed 97% of respondents are aware of AVs, but only 41% know specific automation technologies. As for shared mobility services, 98% of respondents are familiar with Uber and Lyft services. The survey also asked survey participants to indicate their Willingness-To-Pay (WTP) for hypothetical SAV services in three price scenarios. The prices were assumed as relative to the cost of using ride-hailing services with human drivers such as Uber and Lyft. Random parameter ordered logit models were developed to uncover the correlates of the WTP for SAV services. The models identified significant relationships between the WTP and various factors related to respondents’ socio-demographics, awareness of AV companies, and experiences with human-driver ride-hailing services. The awareness of AV companies and ride-hailing services is positively related to the WTP for SAV services. Students who know more AV companies appear to have a greater WTP, and students who are heavy users of Uber or Lyft services are also likely to SAV users in the future. Significant variations were also found in model estimates, indicating that some relationships could vary significantly across observations due to the unobserved heterogeneity. The findings offer insights to decision-makers and investors trying to estimate the market potential of emerging mobility services with AVs.

The Mobility on Demand (MOD) Sandbox Demonstration Program provides a venue through which integrated MOD concepts and solutions – supported through local partnerships – are demonstrated in real-world settings. For each of the 11 MOD Sandbox Demonstration projects, the MOD Sandbox Independent Evaluation includes an analysis of project impacts from performance measures provided by the project partners, as well as an assessment of the business models used. This report constitutes the Evaluation Plan for the City of Palo Alto and Prospect Silicon Valley Bay Area Fair Value Commuting (FVC) Demonstration Sandbox project. It includes the following chapters: project overview; evaluation approach and process; evaluation schedule and management; and data collection and analysis plan.

The Mobility on Demand (MOD) Sandbox Demonstration Program provides a venue through which integrated MOD concepts and solutions – supported through local partnerships – are demonstrated in real-world settings. For each of the 11 MOD Sandbox Demonstration projects, the MOD Sandbox Independent Evaluation includes an analysis of project impacts from performance measures provided by the project partners, as well as an assessment of the business models used. This report constitutes the Evaluation Plan for the Chicago Transit Authority (CTA) Integrated Fare Systems -From Transit Fare to Bike Share Sandbox project. It includes the following chapters: project overview; evaluation approach and process; evaluation schedule and management; and data collection & analysis plan.

The Mobility on Demand (MOD) Sandbox Demonstration Program provides a venue through which integrated MOD concepts and solutions – supported through local partnerships – are demonstrated in real-world settings. For each of the 11 MOD Sandbox Demonstration projects, the MOD Sandbox Independent Evaluation includes an analysis of project impacts from performance measures provided by the project partners, as well as an assessment of the business models used. This report constitutes the Evaluation Plan for the Los Angeles County and Puget Sound MOD First and Last Mile Partnership Demonstration Sandbox project. It includes the following chapters: project overview; evaluation approach and process; evaluation schedule and management; and data collection and analysis plan.

Travel increases with urban sprawl leading to increased congestion and emissions. Advances in technologies provides new paradigms of transport such as mobility as a service (MaaS), which is a novel concept providing users with mobility services including ride-hailing, carsharing and bike sharing based on their needs. The goal of transitioning to a low carbon economy and recent development of alternative fuel vehicles (AFVs) including electric and hybrids offers a promising mobility option for MaaS. However, the use decisions of these vehicles, specifically the shared use for their role in MaaS is not well understood. Thus, the study is intended to provide information about travel choice of consumers and shared use of electric and hybrid vehicles for their role in MaaS. This article utilizes over 125,345 observations from the National Household Travel Survey 2017 to calibrate Heckman switching regime models for AFV travel choice decisions, accounting for self-selection and heterogeneity bias and Bayesian logistic regression with random parameter specifications to model the shared mobility decision of AFVs while accounting for unobserved heterogeneity and temporal/spatial variation. On average, 20% AFVs and 26% conventional vehicles are used for shared mobility in Uber and Lyft. Additional increase in ride-hailing involving AFVs are observed to substantially reduce net greenhouse gas emissions (GHGs). The use of AFVs for travel depends on factors such as personal interest in technologies. Furthermore, travelers using ride-hailing apps increase the likelihood of using AFVs for shared mobility purposes. This research has implications for making policy decisions and placing incentives to promote the purchase, and shared mobility use of AFVs for MaaS. [ABSTRACT FROM AUTHOR]

Car-sharing systems have irrupted in our cities following the shared mobility paradigm. They have evolved the personal mobility market from product-based into service-oriented, which ultimately provides a positive impact on the city's sustainability. Car sharing systems are a complex interactive service, whose dynamics can dramatically affect its operational viability. In order to better asses this viability, we must rely on data to produce novel metrics that characterize both the user behavior and the service performance. Up to date, research has focused on modeling the demand on the basis of the number of rentals that start within a specific time slot. However, this approach seems unable to provide a representative metric of the performance of a car-sharing system. In this paper, we propose a novel metric, the utilization rate of the fleet, which considers the precise number of vehicles within a fleet that are in service every minute of the day. From this basic metric, we derive a key performance indicator (KPI) to reflect the viability of any car-sharing system in economic and sustainability terms. We have applied this new metric and KPI to a dataset with 449 days of car2go data, collected in 10 European cities. [ABSTRACT FROM AUTHOR]

The diffusion of carsharing in cities can potentially support the transition towards a sustainable mobility system and help build a circular economy. Since urban transportation is a complex system due to the involvement of various stakeholders, including travelers, suppliers, manufacturers, and the government, a holistic approach based on systems thinking is essential to capture this complexity and its causalities. In this regard, the current research aims at identifying cause-and-effect relationships in the diffusion of carsharing services within the urban transport systems. To do so, a causal loop diagram (CLD) is developed to identify and capture the causalities of carsharing adoption. On this basis, the main four players within the carsharing domain in urban transportation were scrutinized and their causes and effects were visualized, including (i) the characteristics, behavior, and dynamics of the society population; (ii) transportation system and urban planning; (iii) the car manufacturing industry; and (iv) environmental pollution. The developed CLD can support decision-makers in the field of urban transport to gain a holistic and systemic approach to analyzing the issues within the transport sector due to their complexity. Moreover, they can help regulators and policymakers in intensifying the diffusion of more sustainable modes of transport by highlighting the role of population, car manufacturing, the transportation system, and environmental pollution. [ABSTRACT FROM AUTHOR]

Micromobility services hold substantial potential in terms of promoting shared and electric-powered mobility modes, however, little is known about their accessibility and what shapes their spatial coverage. These two issues are important to understand how socially equitable these modes can really be and how public policies should manage their implementation in urban areas. Hence, this study examines the determinants of the spatial coverage of four moped-style scooter sharing services (MSS) in Barcelona. The article examines the socio-territorial characteristics of the coverage areas of each MSS, as defined in 2019, together with the minimum area that operators had to provide service in 2020 according to the local regulation. For each MSS, a binomial generalized linear mixed model is employed to predict the odds of each cadastral parcel being covered by the service and analyzed the main spatial determinants associated with it. The results suggest that territorial coverage is defined by centrality, household disposable income, and topography, with low-accessibility areas consistently omitted from services. The conclusions underline the need for the public sector to participate in the design of spatial coverage areas of MSS to guarantee spatial equity and transportation justice and avoid private sector designs that systematically exclude less attractive areas. [ABSTRACT FROM AUTHOR]

Car-sharing systems, i.e., short-term car rentals, are one of the solutions that can be an alternative to individual motorization in cities. However, these services must adapt well to customers' needs to develop appropriately. Currently, there have been attempts in scientific research to make numerous optimizations of car-sharing systems, but little emphasis was placed on the type of car fleet used in the systems, which is particularly important at the stage of transformation of the automotive industry towards electric mobility. In response to this research gap, this article was dedicated to the selection of vehicles for car-sharing systems. The work focuses on users of Polish car-sharing systems who use the services of short-term vehicle rental occasionally, i.e., up to five times a year. The research made it possible to determine the types of vehicles (cars with electric, hybrid and internal combustion engines) that the users are interested in and to indicate the specific features that the cars should have. Interestingly, large family vehicles with hybrid engines turned out to be the leading ones. In turn, small city cars, so far dominant in car-sharing, turned out to be the worst choice from the point of view of occasional users. This showed that the current systems are not properly adapted to the needs of society. The results support car-sharing operators who want to upgrade their vehicle fleet accordingly to encourage the public to use car-sharing more often. It is also a guide to identifying a vehicle for fleet modernization towards hybrid and electric vehicles. [ABSTRACT FROM AUTHOR]

In recent years, the electromobility market has been growing faster and faster. Electric scooters and scooter-sharing services offered for them, available in many cities around the world, have a special impact on its intensification. The constantly growing number of scooters and service operators brings many problems related to the proper functioning of services. In the literature, one can find attempts to solve the problems of scooters with references to the issues of transport, modeling and optimization, as well as legislative and social aspects. Technical issues, however, are overlooked. Among them, however, there is a problem with the appropriate selection of scooter models that can be used in scooter-sharing systems. Solving this type of problem may allow systems to be better matched to urban transport systems, increase the development of electromobility and encourage societies to transition from current means of transport (e.g., cars) to scooters. Paying attention to this research niche, the article is devoted to the selection of electric scooters for scooter sharing. This paper presents the author's own research for the Polish market of scooter-sharing services. As part of the work, the author's own list of factors from the point of view of which scooters can be assessed was developed; social research was conducted, considering the opinions of experts in the field of scooter sharing; and it was proposed to treat the problem of selecting scooters as a complex multicriteria decision-making problem. Moreover, the ELECTRE III method was used to solve this research problem in an innovative way. The research results indicate that when choosing a scooter, you should be guided primarily by such factors as the greatest range, equipping the vehicles with safety systems and the most powerful engine. Interestingly, the price of vehicles does not have to be the lowest possible. The article presents guidelines that support operators when upgrading or equipping systems with scooters and support individual users at the stage of deciding to buy a scooter. [ABSTRACT FROM AUTHOR]

In the era of upcoming European Union regulations limiting the registration of combustion cars from 2035, the development of various types of alternatives to balancing transport is on the agenda of modern cities. One of these types of services includes automated short-term car rental systems, i.e., car-sharing systems. In recent years, car-sharing services have been gaining more and more interest among operators and municipal authorities. Despite their intense activities, there are still people in society who have not used car-sharing services so far. A lot of research has been devoted to an attempt to answer their needs in the field of car-sharing, but there is a research gap in the field of detailed analyses of the fleet of cars that they would like to use. Noticing this niche, this article is dedicated to the topic of selecting vehicles for car-sharing systems from the point of view of current non-users and indicating the features that, in their opinion, are the most important parameters characterizing the given vehicles. The research was conducted for the Polish car-sharing market. The obtained results indicate that current non-users would be most interested in small, city B-class cars equipped with internal combustion or electric engines, equipped with a large luggage compartment, and meeting the highest safety standards. Interestingly, the issue of the charging time for electric vehicles was not considered crucial. The results showed that the expectations of non-user vehicles are in contradiction to the expectations of current system users. The article supports car-sharing operators who want to properly manage and modernize their fleet of vehicles to encourage the use of car-sharing among those who are currently unconvinced. [ABSTRACT FROM AUTHOR]

Shared transport modes can potentially contribute to first and last mile connections of public transport (PT) trips but this remains quite underexplored in the literature. Our study explores the user preferences for shared modes as first and last mile option to connect activity locations. We have focussed on local public transport in the Utrecht province, The Netherlands, which includes bus and tram lines. Its diversity in land use and PT network density, the overall high bicycle usage, as well as the increased proliferation of shared mobility concepts yield promising information which can be a harbinger for future PT integration worldwide. For both the urban and suburban areas of the province, we have designed and conducted a stated choice experiment. Respondents were able to choose from shared bicycles, e-bikes, e-scooters, and e-mopeds to reach their urban destination from a PT stop. For suburban destinations, we also included light-electric vehicles (LEVs), e-cars, and demand-responsive taxi services. Such a complete list of possibilities to travel by shared modes allows comparing the different options and producing trade-offs not available yet in the literature. A sample of 499 respondents (285 urban and 214 suburban PT travellers) considered their first and last mile mode choice of a recent PT trip in light of the new options. Results show that shared (electric-)bicycles and e-scooters are generally preferred over other shared mobility options. The latter specifically targets younger people (<26 years) and travellers towards suburban destinations. Still, a majority of PT users prefers not to use shared modes in the first and last mile. We found that age, current cycling behaviour and weekday/weekend travelling are the most important factors which determine these preferences. We argue that shared bicycles and e-bikes are the most capable modes in providing benefits to PT travellers in this context and, given the relatively low travel time sensitivity, can best be distributed around the most important PT stops. [ABSTRACT FROM AUTHOR]

Compared with men, women have different travel behavior. Various factors may affect women's transportation-related decisions, especially in a developing country like Iran with a patriarchal culture. Moreover, distinct characteristics of some transportation systems in Iran, such as rounding and fixed-route shared taxis, whose properties are different from the conventional taxis in western countries, may lead to further differences in Iranian women's transportation mode choice behavior. Studies investigating women's travel behavior and transportation mode choice have often focused on quantitative modeling and mainly highlight the gender differences rather than identifying the underlying factors contributing to women's different behavior. To fulfill this gap, this study attempts to explore the factors and motivations affecting women's shared mobility choices, specifically, shared taxis, in a less developed country with specific socio-cultural structures. Such exploratory research may necessitate a qualitative study that can clarify the cause of the behaviors. Thus, in this study, the conventional content analysis with an inductive approach, in both the latent and manifest levels, was performed. In-depth semi-structured interviews with 15 students and working women living in Tehran (the capital of Iran) were conducted. According to the latent content analysis results, a complex set of factors contributes to women's intention to use shared taxis that can be classified into seven main themes with several sub-themes. The study showed that the fear of abuse and imaginary harassment strongly influence women's transportation-related decisions. Also, women may face direct and indirect restrictions from the family and society. The gender social halo and family norms , more prevalent in traditional and developing societies, may also challenge women's everyday mobility. Moreover, the impact of individual values and beliefs , as well as personality factors on women's travel behavior, cannot be ignored. Indirect social learning is another important factor identified as influential in using shared taxis. Manifest content analysis also resulted in three main categories, including environment-specific factors , trip-vehicle-specific factors , and individual-specific factors. The study attempted to provide more profound insight into women's transportation-related behaviors for policymakers in order to reconsider transportation planning. Also, findings highlighted the role of collaborative efforts of sociologists, psychologists, and transportation planners in tackling women's transportation-related issues in less developed countries with different socio-cultural norms from Western societies. • A qualitative exploration of factors influencing women's intention to use shared taxis in a developing country with a patriarchal culture is provided. • Content analysis, in both the latent and manifest levels, is performed. • Fear of abuse, imaginary harassment, gender social halo, and family norms are found to be influential on Iranian women's transportation-related decisions. • Indirect social learning, individual values and beliefs, as well as personality factors are other important factors. • Environment, trip-vehicle, and individual-specific factors are the results of manifest analysis. [ABSTRACT FROM AUTHOR]

Public and shared transportation are among the sectors that have been severely affected by the COVID-19 pandemic, as they were perceived to be risky environments for disease transmission. Given that the end of the pandemic is not certain and in order to anticipate future pandemics, attempts have been made to design public and shared mobility systems that are pandemic resilient, avoiding the social and economic burdens of disrupting transportation services. In this paper, we introduce a new ridesharing form based on a novel concept called social bubble vanpooling (SBV) which tries to provide a trade-off between minimizing the risk of exposure of riders to communicable diseases, minimizing the operational costs of ridesharing operators, and providing public health authorities with full contact-tracing capability in ridesharing-related cases, if needed. We propose a new clustering approach where riders are pooled into social bubbles composed of people who are spatio-temporally connected and have similar vulnerability levels with respect to a communicable diseases. We used individual agent-based simulation experiments based on a data sample collected from a real population of riders, and we compared the performance of the proposed SBV with trip-based and long committed ridesharing models. We found that (1) enforcing contact tracing and quarantine is more effective in controlling the spread of the disease when the bubble-based ridesharing scheme is adopted as a commuting mode and (2) it is possible to sustain transportation services without compromising the efforts to mitigate the spread of the pandemic. The proposed ridesharing model appears to be a viable solution when the mobility of individuals is subject to tight restrictions to stop the spread of a communicable airborne disease (such as COVID-19). The flexibility of the model allows maintaining transportation services with profitable operational costs while upholding the precautionary measures to fight the pandemic. [ABSTRACT FROM AUTHOR]

Abstract Background Despite emerging research on novel mobility solutions in urban areas, there have been few attempts to explore the relevance and sustainability of these solutions in rural contexts. Furthermore, existing research addressing rural mobility solutions typically focuses on a specific user group, such as local residents, second-home owners, or tourists. In this paper, we study the social inclusivity, economic viability, and environmental impacts of novel mobility solutions in rural contexts based on published scholarly literature. When doing so, we bring both permanent and temporary residents of rural areas under one research framework. Methods We used grey literature to identify and categorise novel mobility solutions, which have been applied in European rural areas and are suitable for travelling longer distances. By using six service flexibility variables, we reached four categories of novel mobility solutions: semi-flexible demand-responsive transport, flexible door-to-door demand-responsive transport, car-sharing, and ride-sharing. We analysed the social inclusivity, economic viability, and environmental impacts of those categories based on criteria and evidence identified from scholarly literature by including the perspectives of both permanent and temporary residents of rural areas. Conclusion: Integration of the needs of various user groups is essential when aiming to achieve the provision of environmentally, socially, and economically sustainable mobility solutions in rural areas. Results Our findings revealed that while single novel mobility solutions are seldom applicable for all rural travellers, strong spatial and temporal synergies exist when combining different solutions. The need for a connected and flexible set of mobility solutions sensitive to the temporal and spatial patterns of mobility needs is inevitable. Accessible and easily understandable information on routing, booking, and ticketing systems, as well as cooperation, shared values, and trust between various parties, are key success factors for sustainable rural mobility. Conclusion Integration of the needs of various user groups is essential when aiming to achieve the provision of environmentally, socially, and economically sustainable mobility solutions in rural areas.

This article presents the results of a systematic literature review on modern trends in the implementation of car-sharing and conducts a comparative analysis of Kazakhstani carsharing solutions to some of the world’s most popular alternatives. The findings reveal some socio-economic and cultural barriers for adopting and promoting carsharing services by studying the results of recent literature. It also considers business models and features of various car-sharing services and suggests a P2P(peer-to-peer) model as the main model of the proposed carsharing system, a system architecture of which is presented as well. The main contribution of this article to the research topic is analyzing existing carsharing solutions both in Kazakhstan and abroad, identifying the gaps in the development of carsharing in the country, suggesting the preferred business model, system architecture and finding directions for future research.

Mobility hubs are becoming increasingly relevant in urban transport systems because they have the potential to enhance sustainability and decrease transport disadvantages. However, the literature has not yet identified the use that disadvantaged groups make of mobility hubs, nor has it thoroughly revealed their requirements for using them without difficulties. As a means to fill this knowledge gap, this qualitative study applied the Capabilities Approach to thoroughly investigate the requirements of disadvantaged groups concerning the use of mobility hubs. The data was obtained through 45 semi-structured interviews and four focus groups with local experts and potential or current users of mobility hubs in four European regions: Brussels, Munich, Rotterdam-The Hague and Vienna. As a result, eight main categories of requirements and their prevalence among disadvantaged groups were identified. The findings contain several recommendations to support decision-makers and practitioners in developing inclusive mobility hubs. [ABSTRACT FROM AUTHOR]

Shared mobility services, such as bike sharing, have gained immense popularity and emerged as an integral part of sustainable urban mobility solutions. The planning of such systems requires forecasting the potential origin–destination (OD) flows between mobility sites (e.g., bike sharing stations) within the proposed network. Existing methods primarily focus on mobility flows between large regions, and do not generalize well to detailed planning applications due to the high spatial resolution required, with increased uncertainty and data sparsity. This study proposes a zero-inflated negative binomial graph neural network (ZINB-GNN) to generate sparse OD flows while capturing complex spatial dependencies. To reflect sparsity, OD flows are modeled as following ZINB distributions parameterized via feed-forward networks. To capture spatial dependencies, localized graphs are constructed to represent proximity between OD pairs, with spatial features encoded using GNNs. ZINB-GNN is validated through a case study of the bike sharing system in New York City. The results verify its prowess in both prediction accuracy and uncertainty quantification under real-world network expansion scenarios. We also demonstrate its interpretability by revealing important factors affecting OD flows. These findings can directly inform the planning of bike sharing systems, and the methodology may be adapted for other shared mobility systems. • A graph deep learning model is proposed for origin–destination (OD) flow generation. • Zero-inflated negative binomial distributions are adopted to capture data sparsity. • Graph neural networks are used to model spatial dependencies between OD flows. • The model is validated using data from the bike sharing system in New York City. • The results demonstrate improved prediction accuracy and uncertainty quantification. [ABSTRACT FROM AUTHOR]

Sharing instead of owning consumer goods should significantly reduce their production and the associated environmental damages. However, this ecological promise has yet to be fulfilled, even in mobility, where sharing practices have become mainstream. This is because the most widespread mobility-sharing practice (free-floating carsharing) has the lowest ecological benefit. This study asks why the adoption of more ecologically beneficial shared mobility practices remains lower, addressing this question through digital ethnography. Using digital mobility diaries for three weeks, 21 respondents documented their mobility practices (including various shared mobility practices and private car travel) by uploading pictures, videos and text notes on a dedicated smartphone application. The data show that free-floating carsharing has proliferated because it can leverage the 'system of automobility' as its users are relatively monomodal. Other shared mobility services function well; however, we found that they have not proliferated as widely because the overall multimodal mobility mix (e.g. walking, cycling, public transport, on-demand sharing) associated with this form of shared mobility is highly demanding. Better conditions for multimodal mobility, created through appropriate infrastructure, are crucial for sustainable shared mobility practices to spread. However, space limitations mean this will likely come at the expense of car-centred infrastructure and necessitate its exnovation. [ABSTRACT FROM AUTHOR]

Despite numerous studies focusing on ride-sourcing services, most have concentrated on users' pre-usage behaviour. This study explores users' post-usage behaviour, aiming to identify significant factors affecting existing users' intentions to continue using app-based ride-sourcing services in Egypt. Integrating the Expectation-Confirmation Model (ECM), the Technology Acceptance Model (TAM), and the Technology Readiness Model (TRM), this research identifies key determinants influencing users' perceptions and continued usage intentions. An online questionnaire collected empirical data from 381 respondents, analysed using partial least squares structural equation modelling (PLS-SEM). The results highlight the essential roles of optimism, innovativeness, discomfort, and insecurity in shaping users' perceptions of ride-sourcing apps' usefulness. Additionally, perceived ease of use is determined by innovativeness and discomfort. Furthermore, users' continuance usage intention is significantly associated with satisfaction level, perceived usefulness, and perceived ease of use. This study's findings offer valuable insights for service providers, aiding their understanding of variables influencing users' decisions to continue using ride-sourcing apps and enabling them to retain and satisfy their current users effectively. • The continuance use intention of ride-hailing is determined by users' satisfaction • Ride-hailing continued usage is impacted by apps usefulness and ease of use • Optimism, innovativeness, discomfort, and insecurity determine apps' usefulness • Innovativeness and discomfort determine apps ease of use • Exploring ride-hailing users' post-usage behaviour in Egypt [ABSTRACT FROM AUTHOR]

Recent advancements in technology have increased the potential for demand-responsive feeder transit services to enhance mobility in areas with limited public transit access. For long rail headways, feeder bus network algorithms are straightforward, as the maximum feeder service cycle time is determined by rail headway, and bus–train matching is unnecessary. However, for short rail headways, the algorithm must address both passenger–feeder-bus and feeder-bus–train matching. This study presents a simulated annealing (SA) algorithm for flexible feeder bus routing, accommodating short headway trunk lines and multiple bus relocations for various stations and trains. A 5 min headway rail trunk line example was utilized to test the algorithm. The algorithm effectively managed bus relocations when optimal routes were infeasible at specific stations. Additionally, the algorithm minimized total costs, accounting for vehicle operating expenses and passenger in-vehicle travel time costs, while considering multiple vehicle relocations.