Evidence map›Paper›PMID 35571509›Full record

ArticleInternational journal of hospitality management2022

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

Arthur Huang, Efrén de la Mora Velasco, Ashkan Farhangi, Anil Bilgihan, Melissa Farboudi Jahromi

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of hospitality management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Arthur HuangRosen College of Hospitality Management, University of Central Florida, Orlando, FL 32819, USA.
Efrén de la Mora VelascoRosen College of Hospitality Management, University of Central Florida, Orlando, FL 32819, USA.
Ashkan FarhangiDepartment of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA.
Anil BilgihanCollege of Business, Florida Atlantic University, Boca Raton, FL 33431, USA.
Melissa Farboudi JahromiRosen College of Hospitality Management, University of Central Florida, Orlando, FL 32819, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

ComplaintsCOVID-19Neural networksRestaurantSafety violationSpatial analysis

Identifiers

PMID35571509
PMCPMC9091265

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.