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  • Leveraging data analytics to understand the relationship between restaurants’ safety violations and COVID-19 transmission
Title: Leveraging data analytics to understand the relationship between restaurants’ safety violations and COVID-19 transmission
This paper leverages natural language processing, spatial analysis, and statistical analysis to examine the relationship between restaurants’ safety violations and COVID-19 cases. We used location-based consumers’ complaints data during the early stage of business reopening in Florida, USA. First, statistical analysis was conducted to examine the correlation between restaurants’ safety violations and COVID-19 transmission. Second, a neural network-based deep learning model was developed to perform topic modeling based on consumers’ complaints. Third, spatial modeling of the complaints’ geographic distributions was performed to identify the hotspots of consumers’ complaints and COVID-19 cases. The results reveal a positive relationship between consumers’ complaints about restaurants’ safety violations and COVID-19 cases. In particular, consumers’ complaints about personal protection measures had the highest correlation with COVID-19 cases, followed by environmental safety measures. Our analytical methods and findings shed light on customers’ behavioral shifts and hospitality businesses’ adaptive practices during a pandemic.  more » « less
Award ID(s):
1937833
PAR ID:
10355712
Author(s) / Creator(s):
Date Published:
Journal Name:
International journal of hospitality management
Volume:
104
ISSN:
0278-4319
Page Range / eLocation ID:
103241
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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