Perceived risk of using shared mobility services during the COVID-19 pandemic

Impacts of household vulnerability on hurricane logistics evacuation under COVID-19: The case of U.S. Hampton Roads

Historical data suggest that when a severe tropical storm or hurricane impacts a community, the vulnerable segment of the population suffers the most severe consequences. With an increased aging population, it is crucial to understand how vulnerability alters evacuation behavior. Emergent variables such as fear of COVID-19 require additional exploration. People afraid of COVID-19 exposure may refuse to evacuate, exposing themselves unnecessarily. Differentiation is critical to evacuation logistics since it is needed to determine what proportion would stay in a local shelter, public or other, rather than evacuating or staying in their home and guide the logistics resource allocation process. This research uses data from a web and phone survey conducted in the Hampton Roads area of U.S. Virginia, with 2,200 valid responses to analyze the influence of social and demographic vulnerability factors and risk perception on evacuation decisions. This research contributes to the existing literature by developing a multinomial order logit model based on vulnerability factors and intended evacuation decisions, including staying at home, looking for a shelter, or leaving the Hampton Roads area. Findings show that race and risk perception are the variables that influence the decision-making process the most. Fear of COVID-19 transmission is also associated with an increased likelihood of leaving homes during evacuation. The variations in findings from previous studies are discussed regarding their implications for logistics emergency managers.

Investigating changes in travel behavior over time in response to the COVID-19 pandemic

The COVID-19 pandemic has significantly affected travel behavior, including the frequency and mode of travel, with the magnitude and nature of these effects varying over time. This study investigates the nature of these relationships by examining changes in various measures of travel behavior, including weekly driving hours, as well as the frequency of telecommuting, use of ride-sharing services, travel for medical purposes, and use of food delivery services. Self-reported travel data from a representative statewide survey of Michigan residents were used to assess changes in these metrics during the early stages of the pandemic, as well as one year thereafter. Random effects linear regression and ordered logit regression models were estimated and the findings show that various changes in behavior had long-lasting effects, while other behaviors generally reverted back toward pre-pandemic levels. In addition, these changes were found to vary across individuals. For example, significant differences were observed based on socio-demographic characteristics, between urban and rural areas, and amongst individuals with differing views on COVID-19 and related government interventions. In general, the pandemic tended to have less pronounced and sustained effects among younger adults as compared to older age groups. Further, those individuals who were opposed to mandatory COVID-19 vaccines were less likely to change their travel behavior, during both the early and latter stages of the pandemic. Changes were observed consistently across most of the travel metrics of interest. Among these, overall driving hours, travel for medical purposes, and ride-sharing were still lower during the latter stages of the pandemic, while telecommuting and the use of food delivery services reverted nearer to pre-pandemic levels.

Post-pandemic shared mobility and active travel in Alabama: A machine learning analysis of COVID-19 survey data

The COVID-19 pandemic has had unprecedented impacts on the way we get around, which has increased the need for physical and social distancing while traveling. Shared mobility, as an emerging travel mode that allows travelers to share vehicles or rides has been confronted with social distancing measures during the pandemic. On the contrary, the interest in active travel (e.g., walking and cycling) has been renewed in the context of pandemic-driven social distancing. Although extensive efforts have been made to show the changes in travel behavior during the pandemic, people's post-pandemic attitudes toward shared mobility and active travel are under-explored. This study examined Alabamians' post-pandemic travel preferences regarding shared mobility and active travel. An online survey was conducted among residents in the State of Alabama to collect Alabamians' perspectives on post-pandemic travel behavior changes, e.g., whether they will avoid ride-hailing services and walk or cycle more after the pandemic. Machine learning algorithms were used to model the survey data (N = 481) to identify the contributing factors of post-pandemic travel preferences. To reduce the bias of any single model, this study explored multiple machine learning methods, including Random Forest, Adaptive Boosting, Support Vector Machine, K-Nearest Neighbors, and Artificial Neural Network. Marginal effects of variables from multiple models were combined to show the quantified relationships between contributing factors and future travel intentions due to the pandemic. Modeling results showed that the interest in shared mobility would decrease among people whose one-way commuting time by driving is 30-45 min. The interest in shared mobility would increase for households with an annual income of $100,000 or more and people who reduced their commuting trips by over 50% during the pandemic. In terms of active travel, people who want to work from home more seemed to be interested in increasing active travel. This study provides an understanding of future travel preferences among Alabamians due to COVID-19. The information can be incorporated into local transportation plans that consider the impacts of the pandemic on future travel intentions.

Metro travel and perceived COVID-19 infection risks: A case study of Hong Kong

The COVID-19 pandemic has exerted unprecedented impacts on travel behaviors because of people's increased health precautions and the presence of various COVID-19 containment measures. However, little research has explored whether and how people changed their travel with respect to their perceived local infection risks across space and time. In this article, we relate elasticity and resilience thinking to the changes in metro travel and perceived infection risks at the station or community level over time. Using empirical data from Hong Kong, we measure a metro station's elasticity as the ratio of changes in its average trip length to the COVID-19 cases' footprints around that station. We regard those footprints as a proxy for people's perceived infection risks when making trips to that station. To explore influencing factors on travel in the ups and downs of perceived infection risks, we classify stations based on their elasticity values and examine the association between stations' elasticities and characteristics of stations and their served communities. The findings show that stations varied in elasticity values across space and different surges of the local pandemic. The elasticity of stations can be predicted by socio-demographics and physical attributes of station areas. Stations serving a larger percentage of population with higher education degrees and certain occupations observed more pronounced trip length decrease for the same level of perceived infection risks. The number of parking spaces and retail facilities significantly explained variations in stations' elasticity. The results provide references on crisis management and resilience improvement amid and post COVID-19.

Designing pandemic resilient cities: Exploring the impacts of the built environment on infection risk perception and subjective well-being

Since the beginning of the COVID-19 pandemic, authorities around the world explored ways to slowdown the spread of the disease while maintaining the physical and mental health of individuals. They redistributed the street space to promote physical activity and non-motorized travel while meeting the social distancing requirements. Although the statistics showed significant increases in walking and bicycling trips during the pandemic, we have limited knowledge about the associations between built environment characteristics, COVID-19 infection risk perception while traveling, and subjective well-being. This study assesses the impacts of the built environment on subjective well-being and infection risk perception while traveling during the pandemic. It uses data collected from the residents of Columbus, Ohio, through a multi-wave survey conducted at different time points during the COVID-19 outbreak. By employing a structural equation modeling approach, it explores the associations between residential neighborhood characteristics, individuals' subjective well-being, and perceived infection risk while using non-motorized modes and shared micromobility. The findings show that those living in more compact, accessible, and walkable neighborhoods are less likely to perceive active travel and shared micromobility as risky in terms of COVID-19 infection. Our results also show that built environment characteristics have an indirect positive effect on the subjective well-being of individuals. The findings of our study demonstrate that built environment interventions can help promote physical activity and support mental health of individuals at this critical time. Our study also indicates that designing compact neighborhoods will be a crucial element of pandemic resilient cities in the post-COVID-19 era.

Impact of perceptions and attitudes on air travel choices in the post-COVID-19 era: A cross-national analysis of stated preference data

The COVID-19 pandemic and the consequent travel restrictions have had an unprecedented impact on the air travel market. However, a rigorous analysis of the potential role of safety perceptions and attitudes towards COVID-19 interventions on future air passenger choices has been lacking to date. To investigate this matter, 1469 individuals were interviewed between April and September 2020 in four multi-airport cities (London, New York City, Sao Paulo, Shanghai). The core analysis draws upon data from a set of stated preference (SP) experiments in which respondents were asked to reflect on a hypothetical air travel journey taking place when travel restrictions are lifted but there is still a risk of infection. The hybrid choice model results show that alongside traditional attributes, such as fare, duration and transfer, attitudinal and safety perception factors matter to air passengers when making future air travel choices. The cross-national analysis points towards differences in responses across the cities to stem from culturally-driven attitudes towards interpersonal distance and personal space. We also report the willingness to pay for travel attributes under the expected future conditions and discuss post-pandemic implications for the air travel sector, including video-conferencing as a substitute for air travel.

Will COVID-19 be the end for the public transit? Investigating the impacts of public health crisis on transit mode choice

COVID-19 had an unprecedented impact on transit demand and usage. Stiff and vigilant hygiene safety requirements changed travellers' mode choice preferences during the COVID-19 pandemic. Specifically, transit modal share is radically impacted. Therefore, quantitative measurements on transit demand impact are urgently needed to facilitate evidence-based policy responses to COVID-19. Thus, we collected 1000 random samples through a web-based survey in the Greater Toronto Area (GTA), Canada, on traveler's modal choices behavior during the COIVD-19 pandemic. The paper presents an analysis with this firsthand dataset to understand transit users' behavioral adaptation resulting from the spreading of COVID-19 in 2020. We found that the transit frequency dropped by 21% to 71% for various socioeconomic groups in the GTA during the pandemic. The transit modal share dipped for all trip purposes. For private vehicle owners, around 70% of transit users switched to their private vehicles. More than 60% of those without cars switched to active transport for all travel purposes. Also, ride-hailing services are the second most popular substitution of transit for them. More than 80% of the respondents agreed with all transit safety policies, such as mandatory face-covering listed in the survey. Moreover, a similar proportion of the respondents agreed to return to public transit in the future. Multinomial, nested, and mixed logit models are estimated to capture relationships between modal choices and various factors. We found that the daily number of new COVID-19 cases impacts the choice of transit negatively. However, vaccine availability and mandatory face-covering onboard positively affect travellers' choices of riding transit during the pandemic.

Travel Behaviour of Vulnerable Social Groups: Pre, during, and Post COVID-19 Pandemic

Since the emergence of COVID-19, travel restrictions due to the pandemic have influenced several activities, in particular the mobility patterns of individuals. Our main goal is to draw the attention of scholars and policy makers to a specific segment of the population, namely (1) older people, (2) persons with disabilities (PwDs), (3) females, and (4) low-income population that are more vulnerable for travel behaviour change due to crisis such as the COVID-19 pandemic. This article systematically reviews the studies that have explored the implications of COVID-19 for the mobility and activities of individuals pre-, during, and post-pandemic using the PRISMA method. It is found that there are a few studies regarding the travel and mobility needs and challenges of older people and PwDs, and there is no direct study concerning female and low-income individuals while such crisis exist. Questions such as "What are the adverse impacts of restrictions on their travel behaviour?", "How can they travel safely to work, shopping, and medical centres?", "Which transportation modes can be more effective for them?", and "What are the government and policy makers' role in providing accessible and affordable mobility services in the presence of such crisis?" are without relevant answers in the literature.

The Impact of COVID-19 on Travel Mode Choice Behavior in Terms of Shared Mobility: A Case Study in Beijing, China

Shared mobility is growing rapidly and changing the mobility landscape. The COVID-19 pandemic has complicated travel mode choice behavior in terms of shared mobility, but the evidence on this impact is limited. To fill this gap, this paper first designs a stated preference survey to collect mode choice data before and during the pandemic. Different shared mobility services are considered, including ride hailing, ride sharing, car sharing, and bike sharing. Then, latent class analysis is used to divide the population in terms of their attitudes toward shared mobility. Nested logit models are applied to compare travel mode choice behavior during the two periods. The results suggest that shared mobility has the potential to avoid the high transmission risk of public transport and alleviate the intensity of private car use in the COVID-19 context, but this is limited by anxiety about shared spaces. As the perceived severity of the pandemic increases, preference for ride hailing and ride sharing decreases, and a price discount for ride hailing is more effective than that for ride sharing at maintaining the ridership despite the impact of COVID-19. These findings contribute to understanding the change in travel demand and developing appropriate strategies for shared mobility services to adapt to the pandemic.

Geographies of infections: built environment and COVID-19 pandemic in metropolitan Melbourne

This paper uses spatial statistical techniques to reflect on geographies of COVID-19 infections in metropolitan Melbourne. We argue that the evolution of the COVID-19 pandemic, which has become widespread since early 2020 in Melbourne, typically proceeds through multiple built environment attributes - diversity, destination accessibility, distance to transit, design, and density. The spread of the contagion is institutionalised within local communities and postcodes, and reshapes movement practices, discourses, and structures of administrative politics. We demonstrate how a focus on spatial patterns of the built environment can inform scholarship on the spread of infections associated with COVID-19 pandemic and geographies of infections more broadly, by highlighting the consistency of built environment influences on COVID-19 infections across three waves of outbreaks. A focus on the built environment influence seeks to enact visions of the future as new variants emerge, illustrating the importance of understanding geographies of infections as global cities adapt to 'COVID-normal' living. We argue that understanding geographies of infections within cities could be a springboard for pursuing sustainable urban development via inclusive compact, mixed-use development and safe public transport.

Wishful thinking? Addressing the long-term implications of COVID-19 for transport in Nigeria

With their inherent economic and infrastructure challenges, developing countries must assess commuters' travel behaviour and establish whether consumers' desire for sustainable transportation is feasible or merely wishful thinking. Using a qualitative research design, these issues were explored based on semi-structured interviews conducted with 72 participants across the six geopolitical zones of Nigeria. Findings suggest that the desires and dreams of the commuters are great, and they want to reduce their journeys, work from home, and do online shopping. However, when they consider the inherent challenges, they can only hope for a better future. COVID-19 has impacted the ownership or use of motorised and non-motorised transport, but this is also influenced by affordability, convenience, and awareness. Likewise, there are long-term effects on home and work location choices, but this is further influenced by the large informal economy of the country, job accessibility and the infrastructural developments across the country.

Risk perception and travel satisfaction associated with the use of public transport in the time of COVID-19. The case of Turin, Italy

The present study examined the association between risk perception and travel satisfaction related to the use of public transport (PT) during COVID-19 pandemic in Turin, Italy. A total of 448 PT users took part in an online survey conducted from January to March 2021. It investigated safety and risk perception related to the use of PT, and the users' subjective experience, measured through the Satisfaction with Travel Scale (STS). These perceptions were compared for three time scenarios: before the pandemic, during the pandemic, and in the future at the end of the pandemic emergency. Results showed that COVID-19 influenced respondents risk perception both during the pandemic and in their projections about the future, especially for females. The risk of contagion from COVID-19 is perceived as higher inside a PT vehicle than in the adjacent/waiting spaces. Regarding travel satisfaction, the overall scores of the STS indicated that the pandemic has impacted reported well-being while travelling, both now and in the future. The dimension of activation shifted towards the negative pole and did not indicate a return to risk perception before the pandemic levels at the end of the crisis (especially for females). Respondents reported a significant decrease in their level of pleasure and satisfaction during the pandemic, but expect that in the future these levels will go back to the levels previously experienced. Regarding travel satisfaction, PT users aged 36 to 50 years reported the highest level of satisfaction, while younger users (18 to 35 years) reported the lowest degree of satisfaction in all three time scenarios. Overall, the results clearly pinpoint that health-related perceived risk is becoming a key determinant for PT use. Within this context, different dimensions of travel satisfaction proved to be impacted differently by the pandemic, for both current and future scenarios.

Exploring the impact of socio-demographic characteristics, health concerns, and product type on home delivery rates and expenditures during a strict COVID-19 lockdown period: A case study from Portland, OR

E-commerce volumes and home deliveries have experienced steady growth in the last two decades. Strict COVID-19 lockdowns made home delivery an essential service and a lifeline for many households that, for travel restrictions or health concerns, were not able to utilize traditional shopping methods. This research studies the impact of socio-demographic variables and e-commerce attitudes on household deliveries for seven product categories (groceries, meals, electronics, household and office goods, recreational items, and fashion, beauty and personal care products, and medicine/health-related products) during the lockdown period in the greater Portland metropolitan region. To understand these impacts, exploratory factor analysis and choice models with latent variables are estimated utilizing data collected from an online survey representing the population in the greater Portland metropolitan region. The results indicate that each factor has a unique profile in terms of significant socio-demographic variables. A novel contribution of this research is to study the impact on home deliveries of non-traditional variables like health and safety concerns and the presence of household members with disabilities during a pandemic. The results show that health concerns are very influential and that there are substantial differences across factors on delivery rate and expenditure levels. Key findings and perspectives regarding future delivery rates and implications for transportation agencies and logistics companies are discussed.