The Intention of Retail Stores in Taiwan to Cooperate with the Government in the Establishment of IT Measures for Pandemic Prevention.

I-Chiu Chang, Chih-Ming Chen, Wei-Chuan Lin, Der-Juinn Horng, Ying-Chin Ho, Hui-Ling Hu

Abstract read

In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

I-Chiu ChangDepartment of Information Management, National Chung Cheng University, Chiayi 621301, Taiwan.

Chih-Ming ChenDepartment of Information Management, National Chung Cheng University, Chiayi 621301, Taiwan.ORCID 0000-0002-5394-3542

Wei-Chuan LinDepartment of Business Administration, National Central University, Taoyuan 320317, Taiwan.

Der-Juinn HorngDepartment of Business Administration, National Central University, Taoyuan 320317, Taiwan.

Ying-Chin HoInstitute of Industrial Management, National Central University, Taoyuan 320317, Taiwan.

Hui-Ling HuQuantitative Analysis and Research Association, Kaohsiung 800305, Taiwan.ORCID 0000-0002-6590-7864

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study focuses on the cooperative attitude and intention of retail stores in Taiwan to cooperate with the government's related pandemic prevention measures. The study is based on the Theory of Planned Behavior (TPB). The study includes factors such as perceived risk of infection, job stress, pandemic prevention IT (information technology) convenience, pandemic prevention attitude, and pandemic prevention intention. Pandemic prevention attitude is used as a mediating variable to establish the research framework. This study collected research data through a questionnaire survey. A total of 457 valid questionnaires were collected through an electronic questionnaire platform. The findings showed that perceived risk of infection and pandemic prevention IT convenience had a positive and significant effect on pandemic prevention attitude (β = 0.567; β = 0.422) and pandemic prevention intention (β = 0.424; β = 0.296). Job stress has a significant negative effect on attitude (β = -0.173). In addition, job stress influenced intention through attitudes. Finally, perceived risk, job stress, and IT convenience had high explanatory power (R

Indexed as

COVID-19job stresspandemic prevention IT measuresperceived risk of infectiontheory of planned behavior

Identifiers

PMID36611490

DOI10.3390/healthcare11010030

PMCPMC9819294

What OpenQuestion holds

Textmetadata

LicenceCC BY

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.