Robots at your doorstep: acceptance of near-future technologies for automated parcel delivery.

The logistics and delivery industry is undergoing a technology-driven transformation, with robotics, drones, and autonomous vehicles expected to play a key role in meeting the growing challenges of last-mile delivery. To understand the public acceptability of automated parcel delivery options, this U.S. study explores customer preferences for four innovations: autonomous vehicles, aerial drones, sidewalk robots, and bipedal robots. We use an Integrated Nested Choice and Correlated Latent Variable (INCLV) model to reveal substitution effects among automated delivery modes in a sample of U.S. respondents. The study finds that acceptance of automated delivery modes is strongly tied to shipment price and time, underscoring the importance of careful planning and incentives to maximize the trialability of innovative logistics options. Older individuals and those with concerns about package handling exhibit a lower preference for automated modes, while individuals with higher education and technology affinity exhibit greater acceptance. These findings provide valuable insights for logistics companies and retailers looking to introduce automation technologies in their last-mile delivery operations, emphasizing the need to tailor marketing and communication strategies to meet customer preferences. Additionally, providing information about appropriate package handling by automated technologies may alleviate concerns and increase the acceptance of these modes among all customer groups.

Nowhere to go? A study of marginalization, social connection, and mental health outcomes among young adults experiencing the COVID-19 pandemic.

Background: The COVID-19 pandemic onset necessitated large-scale closures of third places, potentially exacerbating social barriers experienced by young adults in the United States. To better understand the role of urban form in facilitating socialization, we examine the effects of pandemic-based third place closures on mental health outcomes as mediated by changes in social connection. Because identifying as a racial, gender, or sexual minority can compound baseline disadvantages rooted in systemic inequities, we investigate outcome differences for non-white, woman/nonbinary, and LGBTQ+ young adults to disentangle identity-based nuances of the pandemic experience. Methods: In February 2021, we administered a web-based survey with retrospective name and place generators to 313 18-to-34-year-olds in California, Illinois, and Texas. A structural equation model is estimated showing the direct and indirect effects of physical and virtual mobility constraints on mental health. Results: Both the closure of third places and dissatisfaction with alternative social spaces are associated with the deterioration of social connections and mental health. The strongest direct predictor of mental health decline is dissatisfaction with virtual socialization (more significant for women and nonbinary respondents). Surprisingly, two distinct categories of third places (i.e., 'civic' and 'commercial') reveal different relationships with social connections and mental health outcomes. Asian, other non-white, and non-heterosexual young adults experienced greater 'civic' visit reduction, while those with intersecting identities of low income and woman/nonbinary or Black experienced greater 'commercial' visit reduction. Conclusions: Physical and virtual mobility reductions contributed to the inequitable mental health outcomes experienced by young adults during the pandemic. This highlights the potential for a careful redesign of physical and virtual social spaces to support feelings of belonging/safety and spontaneous 'weak tie' interactions, encourages further investigation of social infrastructure's role in facilitating the maintenance of social connections and mental health, and reveals the value of examining differences in mobility-related experiences across social identities.

In-person, pick up or delivery? Evolving patterns of household spending behavior through the early reopening phase of the COVID-19 pandemic.

Consumer reactions to COVID-19 pandemic disruptions have been varied, including modifications in spending frequency, amount, product categories and delivery channels. This study analyzes spending data from a sample of 720 U.S. households during the start of deconfinement and early vaccine rollout to understand changes in spending and behavior one year into the pandemic. This paper finds that overall spending is similar to pre-pandemic levels, except for a 28% decline in prepared food spending. More educated and higher income households with children have shifted away from in-person spending, whereas politically conservative respondents are more likely to shop in-person and via pickup.

Shifting Mobility Behaviors in Unprecedented Times: A Multigroup MIMIC Model Investigating Intentions to Use On-Demand Ride Services During the COVID-19 Pandemic.

The spread of COVID-19 has been a major disruptive force in people's everyday lives and mobility behavior. The demand for on-demand ride services, such as taxis and ridehailing, has been specifically affected given both restrictions in service operations and users' concerns about virus transmission in shared vehicles. In the early months of the pandemic, demand for these modes decreased by as much as 80%. This study examines intentions to use on-demand ride services in the early lockdown stage of the pandemic in the United States, a period of unprecedented mobility reductions, changing household routines and transforming travel behaviors. Using data from a survey disseminated in June 2020 to 700 U.S. respondents, we use multigroup MIMIC (Multiple Indicator Multiple Cause) models to investigate the stated shift in intentions to use on-demand modes of travel. By using group-based segmentation we control for variation in ridership intentions according to personal, household, attitudinal factors, and pandemic experiences. The results point to a reduction across the board in the likelihood of using on-demand mobility associated with a significant COVID-19 effect. Beyond this general decrease, several groups are found to have more positive intentions, including younger adults, urban residents, graduate-degree holders, and people of Hispanic, Latino, Asian, and Pacific Islander ethnicities/races. The attitudinal effect of "tech-savviness" drives higher user intentions, revealing indirect effects of gender, education, and age. Multigroup analysis provides further evidence of potential COVID-triggered shifts in on-demand ridership intentions. The most significant drops in likelihood are observed for younger respondents (below 45), Black compared with all other racial/ethnic status, and for past users of on-demand mobility. This latter result is somewhat surprising, as riders who are younger and more experienced with on-demand travel are more likely to have been users in the past, but also more likely to reduce use during the pandemic. To conclude, we discuss the need to investigate pandemic experiences, risk attitudes, and circumstances to understand evolving mobility behavior and specific service model impacts.

For whom did telework not work during the Pandemic? understanding the factors impacting telework satisfaction in the US using a multiple indicator multiple cause (MIMIC) model.

The COVID-19 pandemic required employees and businesses across the world to rapidly transition to work from home over extended periods, reaching what is likely the upper bound of telework in many sectors. Past studies have identified both advantages and disadvantages of teleworking. The pandemic experience offers a unique opportunity to examine employees' experiences and perceptions of telework given the broad participation duration and extent. While employer strategies will play a major role in defining the future forms and adoption of telework, employee preferences and constraints, such as access to appropriate technology to work from home or the home environment, are also going to be important factors. Using data from a U.S. representative sample of 318 working adults, this study uses a Multiple Indicator Multiple Cause Model (MIMIC) to understand employee satisfaction with telework. The presented model links telework satisfaction with experienced and perceived benefits and barriers related to telework, and hence provide a causal structure to our understanding of telework satisfaction. We also present an ordered probit model without latent variables that help us understand the systematic heterogeneity in telework satisfaction across various socio-demographic groups. The results suggest younger and older aged individuals experienced/perceived lower benefits and higher barriers to teleworking compared to middle aged individuals. The results also suggest a disproportionate impact on Hispanic or Latino and Black respondents as well as on those with children attending online school from home. Accordingly, this study highlights important factors impacting telework adoption that employers and policy makers should consider in planning future work arrangements and policies in a post-pandemic world.

Dueling emergencies: Flood evacuation ridesharing during the COVID-19 pandemic.

Volunteered sharing of resources is often observed in response to disaster events. During evacuations the sharing of resources and vehicles is a crucial mechanism for expanding critical capacity and enabling inclusive disaster response. This paper examines the complexity of rideshare decision-making in the wake of simultaneous emergencies. Specifically, the need for physical distancing measures during the coronavirus (COVID-19) pandemic complicates face-to-face resource sharing between strangers. The ability of on-demand ridesharing to provide emergency transportation to individuals without access to alternatives calls for an understanding of how evacuees weigh risks of contagion against benefits of spontaneous resource sharing. In this research, we examine both sociodemographic and situational factors that contribute to a willingness to share flood evacuation rides with strangers during the COVID-19 pandemic. We hypothesize that the willingness to share is significantly correlated with traditional emergency resource sharing motivations and current COVID-19 risk factors. To test these hypotheses, we distributed an online survey during the pandemic surge in July 2020 to 600 individuals in three midwestern and three southern states in the United States with high risk of flooding. We estimate a random parameter multinomial logit model to determine the willingness to share a ride as a driver or passenger. Our findings show that willingness to share evacuation rides is associated with individual sociodemographics (such as being female, under 36 years old, Black, or republican-identifying) and the social environment (such as households with children, social network proximity, and neighborly sharing attitudes). Moreover, our findings suggest higher levels of income, COVID-19 threat perception, evacuation fear, and household preparedness all correspond with a lower willingness to share rides. We discuss the broader implications of emergency on-demand mobility during concurrent disasters to formulate strategies for transportation agencies and on-demand ridehailing providers.