Restaurant survival during the COVID-19 pandemic: Examining operational, demographic and land use predictors in London, Canada

Author:

Wray Alexander1ORCID,Arku Godwin1ORCID,Long Jed1ORCID,Minaker Leia2ORCID,Seabrook Jamie1ORCID,Doherty Sean3ORCID,Gilliland Jason1ORCID

Affiliation:

1. The University of Western Ontario, Canada

2. University of Waterloo, Canada

3. Wilfrid Laurier University, Canada

Abstract

The COVID-19 pandemic placed considerable stress on restaurants from restrictions placed on their operations, shifting consumer confidence, rapid expansion of remote work arrangements and aggressive uptake of third-party delivery services. Industry reports suggest that restaurants are experiencing a much higher rate of failure in comparison to other sectors of the economy. Restaurant survival was assessed in the Middlesex–London region of Ontario, Canada as of December 2020 using a novel dataset constructed from public health inspection permits, business listings and social media. Binomial logistic regression models were used to determine the association of operational, demographic and land use factors with restaurant survival during the pandemic. Operations-related factors were considerably more predictive of restaurant survival, though some demographic and land use factors suggest that urban processes continued to play a role in restaurant survival. Restaurants that offered in-house delivery and phone-based ordering methods were considerably less likely to close. Restaurants with a table-based service model, drive-through or an alcohol licence were also less likely to close. Restaurants proximal to a concentration of entertainment land uses were more likely to be closed in December 2020. Closed restaurants were not spatially clustered as compared to open restaurants. The pandemic appears to have disrupted established theoretical relationships between people, place, and restaurant success.

Funder

Ontario Research Fund - COVID-19 Rapid Research Fund

Publisher

SAGE Publications

Reference93 articles.

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