Evaluation of the Resilience of the Catering Industry in Hong Kong before and after the COVID-19 Outbreak Based on Point-of-Interest Data

2Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

Abstract

COVID-19 has caused a serious economic shock which challenges the resilience of businesses around the world. Understanding the spatial distribution pattern of business resilience, as well as identifying factors that promote business resilience, is crucial to economic recovery. Most existing studies mainly analyze one side of the concept of resilience, such as how businesses closed, expanded, and innovated, while no studies take all the characteristics of resilience into account and analyze them from a geographical view. To fill this gap, this study first relates the method of calculating stability in ecology to geography, and proposes a point of interest (POI)-based index to evaluate an industry’s resilience in a city. Then, with the catering industry in Hong Kong as an example, the spatial distribution of resilience in June 2020 and December 2020 is investigated using the local indicators of spatial association (LISA) approach. An ordinary least squares (OLS) regression model is adopted to identify impactful factors on resilience. The results reveal that the resilience of restaurants is quite stable in local central areas, but areas near the checking points at Shenzhen in mainland China are severely affected. Most traditional location factors had the benefit of stabilization, while hospitals had negative responses. The presented analysis framework is possible to be easily generalized to other industries or cities. The overall result of the study provides a spatial understanding which would be essential as a reference for future urban planning regarding post-pandemic recovery.

Cite

CITATION STYLE

APA

Liu, Y., Shi, W., Yu, Y., Peng, L., & Zhang, A. (2023). Evaluation of the Resilience of the Catering Industry in Hong Kong before and after the COVID-19 Outbreak Based on Point-of-Interest Data. ISPRS International Journal of Geo-Information, 12(11). https://doi.org/10.3390/ijgi12110443

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free