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.

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.

Accelerating Adoption of Disruptive Technologies: Impact of COVID-19 on Intentions to Use On-Demand Autonomous Vehicle Mobility Services

One of the most notable global transportation trends is the accelerated pace of development in vehicle automation technologies. Uncertainty surrounds the future of automated mobility as there is no clear consensus on potential adoption patterns, ownership versus shared use status, and travel impacts. Adding to this uncertainty is the impact of the COVID-19 pandemic which has triggered profound changes in mobility behaviors as well as accelerated the adoption of new technologies at an unprecedented rate. Accordingly, this study examines the impact of the COVID-19 pandemic on people?s intention to adopt the emerging technology of autonomous vehicles (AVs). Using data from a survey disseminated in June 2020 to 700 respondents in the United States, a difference-in-difference regression is performed to analyze the shift in willingness to use AVs as part of an on-demand mobility service before and during the pandemic. The results reveal that the COVID-19 pandemic had a positive and highly significant impact on the intention to use AVs. This shift is present regardless of tech-savviness, gender, or urban/rural household location. Results indicate that individuals who are younger, politically left-leaning, and frequent users of on-demand modes of travel are expected to be more likely to use AVs once offered. Understanding the systematic segment and attribute variation determining the increase in consideration of AVs is important for policy making, as these effects provide a guide to predicting adoption of AVs?once available?and to identify segments of the population likely to be more resistant to adopting AVs.

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.

Shifting Behaviors in Unprecedented Times: How Are Intentions to Use Shared Modes Changing During the COVID-19 Pandemic

The spread of COVID-19 globally has been a major disruptive force in people’s everyday lives and general mobility. A component of the transportation system that has been specifically impacted by these disruptions is that of shared modes of travel, such as taxis and ridehailing, given the concerns about virus transmission. Today, demand for these modes have decreased by as much as 80%. This study aims to understand the shift in consideration of these modes as a result of unprecedented experiences in order to both, understand the potential recovery for shared mobility modes as well as the behavioral impact of drastic changes in lifestyle on transportation systems. With multiple reports and discussions on how COVID-19 will fundamentally change and redesign urban mobility, this study sets precedence for future efforts in assessing realized behavioral changes in the future. The results indicate that political orientation and experiences during the pandemic are significant in explaining the individual change in intentions to use ridesourcing. Additionally, characteristics such as age and income result in consideration shifts that would normally contradict the typical ridership profiles found in the ridesourcing literature. Specifically, this analysis finds that hailed ride consideration decreases as a function of either age or income. These findings are carefully presented and contextualized in this study.