Evidence map›Paper›PMID 35942187›Full record

ArticleAgricultural economics (Amsterdam, Netherlands)2022

Is no news bad news? The impact of disclosing COVID-19 tracing information on consumer dine out decisions.

Yuan Gao, Rigoberto A Lopez, Ruili Liao, Xiaoou Liu

Open access · greenAbstract readNews
In one paragraph

Article in Agricultural economics (Amsterdam, Netherlands), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 20% of its field
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, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 2 countries.

Yuan GaoSchool of Agricultural Economics and Rural Development Renmin University of China Beijing China.
Rigoberto A LopezDepartment of Agricultural and Resource Economics University of Connecticut Storrs Connecticut USA.
Ruili LiaoSchool of Public Policy and Management Tsinghua University Beijing China.
Xiaoou LiuSchool of Agricultural Economics and Rural Development Renmin University of China Beijing China.
Renmin University of China · CNTsinghua University · CNUniversity of Connecticut · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food markets around the world have been disrupted by the COVID-19 pandemic via consumer behavior upended by fear of infection. In this article, we examine the impact of disclosing COVID-19 contact tracing information on food markets, using the restaurant industry in China as a case study. By analyzing transaction data at 87 restaurants across 10 cities, we estimate difference-in-difference (DID) models to ascertain the impact of COVID-19 infections and contact information tracing on economic activity as measured by a daily number of transactions. Empirical results show that while the overall number of new COVID-19 infections at the national level caused a dramatic drop in numbers of transactions in all restaurants, restaurants in cities that disclosed contact tracing information of COVID-19 infections experienced a 23%-35% higher number of transactions than the ones in cities that did not disclose such information during the recovery period. Ultimately, we show that in the absence of a shelter-in-place mandate, disclosing contract tracing information to mitigate consumers' uncertainties about risks of being infected can contribute to a faster recovery of food markets, in addition to reducing COVID-19 infections.

Indexed as

contact tracing informationCOVID‐19food marketsrisk uncertainties

Identifiers

PMID35942187
PMCPMC9350169
OpenAlexW4283645891

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.