This paper presents a study of various factors that influenced online and in-store shopping behaviors in New York City during the COVID-19 pandemic. It uses panel data collected by the New York City Department of Transportation for May, July, and October 2020. In the survey, 696 respondents consistently responded in all three months and, therefore, this group was used for analysis. The study adopts random effect ordered probit models with marginal effects and dynamic discrete choice models to understand the factors that influenced online and in-store shopping during the pandemic. The models reveal that increased subway usage was correlated with in-store shopping during the pandemic. Income also played a part in shopping behavior: higher-income individuals were less likely to shop in store, whereas lower-income individuals (more likely to ride the subway or bus) were more likely to shop in store. Contrary to previous research, age did not appear to have an impact on online and in-store shopping behaviors. Finally, this study discovered that online and in-store shopping are not necessarily indirectly proportional, which was unexpected. This means an increase in online shopping does not necessarily lead directly to a decrease in in-store shopping. By understanding how individuals reacted to the pandemic, proper policies—especially from a transportation aspect—can be developed in advance to prepare for future pandemic threats.


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    Title :

    Online and In-Store Shopping Behavior during the COVID-19 Pandemic: Lessons Learned from a Panel Survey in New York City


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2023-03-03




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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