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.

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.

On-Demand Automotive Fleet Electrification Can Catalyze Global Transportation Decarbonization and Smart Urban Mobility.

Mobility on-demand vehicle (MODV) services have grown explosively in recent years, threatening targets for local air pollution and global carbon emissions. Despite evidence that on-demand automotive fleets are ripe for electrification, adoption of battery electric vehicles (BEVs) in fleet applications has been hindered by lack of charging infrastructure and long charging times. Recent research on electrification programs in Chinese megacities suggests that top-down policy targets can spur investment in charging infrastructure, while intelligent charging coordination can greatly reduce requirements for battery range and infrastructure, as well as revenue losses due to time spent charging. Such capability may require labor policy reform to allow fleet operators to manage their drivers' charging behavior, along with collection and integration of several key data sets including (1) vehicle trajectories and energy consumption, (2) charging infrastructure installation costs, and (3) real-time charging station availability. In turn, digitization enabled by fleet electrification holds the potential to enable a host of smart urban mobility strategies, including integration of public transit with innovative transportation systems and emission-based pricing policies.

Richardson score predicts short-term adverse respiratory outcomes in newborns >/=34 weeks gestation.

OBJECTIVES: To develop a model to predict which newborns >/=34 weeks gestation with respiratory distress will die or will require prolonged (>3 days) assisted ventilation. METHODS: Retrospective cohort study using data from Northern California newborns >/=34 weeks gestation who presented with respiratory distress. We split the cohort into derivation and validation datasets. Bivariate and multivariate data analyses were performed on the derivation dataset. After developing a simple score on the derivation dataset, we applied it to the original as well as to a second validation dataset from Massachusetts. RESULTS: Of 2276 babies who met our initial eligibility criteria, 203 (9.3%) had the primary study outcome (assisted ventilation >3 days or death). A simple score based on gestational age, the lowest PaO 2 /FIO 2 , a variable combining lowest pH and highest PaCO 2 , and the lowest mean arterial blood pressure had excellent performance, with a c-statistic of 0.85 in the derivation dataset, 0.80 in the validation dataset, and 0.80 in the secondary validation dataset. CONCLUSIONS: A simple objective score based on routinely collected physiologic predictors can predict respiratory outcomes in infants >/=34 weeks gestation with respiratory distress.