Evidence map›Paper›PMID 35677127›Full record

ArticleFrontiers in psychology2022

Intention to Use Mobile Easy Payment Services: Focusing on the Risk Perception of COVID-19.

JiWon Kim, Mincheol Kim

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

2 authors.

JiWon KimDepartment of Faculty of Data Science for Sustainable Growth, Jeju National University, Jeju City, South Korea.
Mincheol KimDepartment of Faculty of Data Science for Sustainable Growth, Jeju National University, Jeju City, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the COVID-19 outbreak, the use of mobile easy payment services that minimize human contact has rapidly increased. Several studies have explored the relationship between the COVID-19 pandemic and the intention to use mobile easy payment services, assuming that the relationship between both variables is simply linear. However, actual complex relationships between variables cannot be fully analyzed in a linear fashion, as most relationships between variables of social phenomena are non-linear. Therefore, this study attempted to analyze the non-linear relationships between factors influencing the intention to use mobile easy payment services, especially since the COVID-19 outbreak, by applying the extended technology acceptance model (TAM2). Online and offline surveys were conducted with users who have used mobile easy payment services since the COVID-19 outbreak; 227 samples were secured for analysis. In addition, an empirical analysis was conducted using PLS-SEM to determine the linearity of relationships between variables. The results showed that subjective norms, perceived ease of use, and perceived usefulness had significant effects on the intention to use mobile easy payment services. Moreover, the COVID-19 pandemic had a significant moderating effect, also implying non-linear relationships between variables. Based on these results, the study proposes that the pandemic is a factor influencing the intention to use mobile easy payment services, and recommends that providers adopt marketing strategies, such as improving the usefulness of these services.

Indexed as

COVID-19extended technology acceptance modelmobile easy payment servicenon-linear relationshipWarpPLS

Identifiers

PMID35677127
PMCPMC9169679

What OpenQuestion holds

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LicenceCC BY
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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.