Document Type
Article
Publication Date
6-2023
Keywords
Artificial intelligence; Geographical information science; Geography
Abstract
The COVID-19 pandemic has imposed catastrophic impacts on the restaurant industry as a crucial socioeconomic sector that contributes to the global economy. However, the understanding of how the restaurant industry was recovered from COVID-19 remains underexplored. This study constructs a spatially explicit evaluation of the effect of COVID-19 on the restaurant industry in the US, drawing on the attributes of +200,000 restaurants from Yelp and +600 million individual-level restaurant visitations provided by SafeGraph from 1st January 2019 to 31st December 2021. We produce quantitative evidence of lost restaurant visitations and revenue amid the pandemic, the changes in the customers’ origins, and the retained visitation law of human mobility—the number of restaurant visitations decreases as the inverse square of their travel distances—though such a distance-decay effect becomes marginal at the later pandemic. Our findings support policy makers to monitor economic relief and design place-based policies for economic recovery.
Citation
Wang, S., Huang, X., She, B., & Li, Z. (2023). Diverged Landscape of Restaurant Recovery from the COVID-19 Pandemic in the United States. iScience, 26 (6), 106811. https://doi.org/10.1016/j.isci.2023.106811
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
