Evidence map›Paper›PMID 34305192›Full record

ArticleJournal of international business studies2021

A cross-cultural exploratory analysis of pandemic growth: The case of COVID-19.

Ratan J S Dheer, Carolyn P Egri, Len J Treviño

Erratum issuedAbstract read
In one paragraph

Article in Journal of international business studies, 2021. 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 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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  3. COVID-19 in Memes: The Adaptive Response of Societies to the Pandemic?International journal of environmental research and public health · 2022
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Ratan J S Dheer *Department of Management, College of Business, Eastern Michigan University, Ypsilanti, MI 48197 USA.
Carolyn P Egri *Beedie School of Business, Simon Fraser University, Burnaby, Canada.
Len J Treviño *Department of Management Programs, College of Business, Florida Atlantic University, Boca Raton, FL 33431 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the novel coronavirus that has resulted in more than 3 million deaths and 140 million cases of infection worldwide has wreaked havoc globally, some nations were more successful than others in curbing growth in their number of cases, thereby saving lives. In this research note, we integrate insights from cross-cultural research with inquiry in social psychology and public health literatures to advance a theoretically grounded and culturally derived explanation of cross-national variance in the growth rate of COVID-19. Our multi-level analyses, based on longitudinal time series data from 107 nations, and focused on the first 91 days of this pandemic in different nations, illustrate the direct and interactive effects of culture. Specifically, we find that individualism and uncertainty avoidance have a positive impact, while power distance and masculinity have a negative impact, on the growth rate of COVID-19 cases. Three-way interaction analyses between time, government stringency, and culture indicate that early government stringency attenuated pandemic growth, and this attenuation effect was more significant in collectivistic than in individualistic nations, and in high rather than low power distance nations. Our findings provide evidence that can enable policymakers and organizations to develop strategies that not only conform to science but that also consider the cultural orientation of nations.

Indexed as

COVID-19cross-nationalcultural valuesgovernment stringencynovel coronavirus

Identifiers

PMID34305192
PMCPMC8294215

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.