ABSTRACT
In this study, we employ a choice experiment to analyze New York City residents' preferences for online grocery shopping at the beginning of the COVID-19 pandemic. We employ a latent class specification to identify three market segments and estimate consumers' willingness to pay for a variety of attributes of online grocery services related to the quality of the stock, delivery characteristics, and the cost of the online order. We characterize consumers in each segment by their observed characteristics as well as fear-related latent variables. On the one hand, we find that individuals who are actively protecting themselves against COVID-19 have a higher willingness to pay for almost all attributes. On the other hand, consumers who avoid crowds have a lower willingness to pay, but they assign relatively higher importance to no-contact delivery.
ABSTRACT
We investigate preferences for COVID-19 vaccines using data from a stated choice survey conducted in the US in March 2021. To analyse the data, we embed the Choquet integral, a flexible aggregation operator for capturing attribute interactions under monotonicity constraints, into a mixed logit model. We find that effectiveness is the most important vaccine attribute, followed by risk of severe side effects and protection period. The attribute interactions reveal that non-pecuniary vaccine attributes are synergistic. Out-of-pocket costs are independent of effectiveness, incubation period, and mild side effects but exhibit moderate synergistic interactions with other attributes. Vaccine adoption is significantly more likely among individuals who identify as male, have obtained a bachelor's degree or a higher level of education, have a high household income, support the democratic party, had COVID-19, got vaccinated against the flu in winter 2020/21, and have an underlying health condition.
ABSTRACT
BACKGROUND: Using choice microdata (N=2723) across the USA, this paper analyzes elicited acceptance of hypothetical COVID-19 vaccines. METHODS: The hypothetical vaccines in a choice experiment were described in terms of effectiveness, days for antibodies to develop, duration of protection, risk of both mild and severe side effects, which health agency mainly supports the vaccine, country of origin, and when the vaccine was developed. Out-of-pocket cost was also considered as characteristic of the vaccines to derive welfare measures. RESULTS: All vaccine attributes had expected signs with significant estimates. Vaccines developed in the USA and the UK were preferred to a hypothetical German vaccine, whereas a Chinese origin was very negatively perceived. Since the choice scenarios also gave the option to opt out from taking the vaccine, odds ratios were derived to characterize the segments that are more and less likely to accept vaccination. More likely to opt out were found to be those who stated to be against vaccination in general, African Americans, individuals without health insurance, and older people. Males, democrats, those who took the flu vaccine appear as more willing to accept vaccination. CONCLUSIONS: Estimates of the fitted choice models in this study are informative for current and future immunization programs.
ABSTRACT
Public health officials enforced several measures to contain the COVID-19 pandemic that affected grocery stores, such as limits on store capacities and enforcement of masks and physical distancing among customers. Nevertheless, these measures can provoke queues, which could drive customers away from stores. In this study, we investigate how customers trade off between social distancing measures and increased waiting times during the peak of the COVID-19 pandemic. Our data comes from an online survey applied in New York City in May 2020. This survey included a set of discrete choice experiments framed in virtual stores, as well as a set of psychometric indicators regarding the pandemic. With this data, we estimated a latent class conditional logit model where assignment to classes is correlated with COVID-19 latent variables. We identified three latent classes with preference structures that valued social distancing to varying degrees. In spite of this heterogeneity in preferences, we found that customers were willing to wait longer to access stores with better social distancing measures. This result suggests that stores could increase, rather than decrease, their sales if they enforce public health measures at the expense of longer waiting times.
ABSTRACT
This project will study how the COVID-19 pandemic has affected both travel and pro-environmental preferences and how commuters interact with transportation infrastructure, with particular focus on sustainable transportation modes and how transit preferences evolve during the pandemic receding stage. A multi-wave survey of commuters will capture changes in behavior and priorities and how attitudes toward the environment and diseases shape mobility preferences over time. The collected data will be used to train a microeconometric model of welfare changes under the “new normal” of the mobility ecosystem.