Leveraging data analytics to understand the relationship between restaurants' safety violations and COVID-19 transmission.

Autor: Huang A; Rosen College of Hospitality Management, University of Central Florida, Orlando, FL 32819, USA., de la Mora Velasco E; Rosen College of Hospitality Management, University of Central Florida, Orlando, FL 32819, USA., Farhangi A; Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA., Bilgihan A; College of Business, Florida Atlantic University, Boca Raton, FL 33431, USA., Jahromi MF; Rosen College of Hospitality Management, University of Central Florida, Orlando, FL 32819, USA.
Jazyk: angličtina
Zdroj: International journal of hospitality management [Int J Hosp Manag] 2022 Jul; Vol. 104, pp. 103241. Date of Electronic Publication: 2022 May 11.
DOI: 10.1016/j.ijhm.2022.103241
Abstrakt: 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.
Competing Interests: The authors declare no conflict of interest.
(© 2022 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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