Evidence map›Paper›PMID 39650365›Full record

ArticlePeerJ. Computer science2024

Modelling the effects of perceived system quality and personal innovativeness on the intention to use metaverse: a structural equation modelling approach.

Sultan Hammad Alshammari, Mohammed Habib Alshammari

Abstract read
In one paragraph

Article in PeerJ. Computer science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Sultan Hammad AlshammariDepartment of Educational Technology, College of Education, University of Ha'il, Ha'il, Saudi Arabia.ORCID 0000-0001-7294-9053
Mohammed Habib AlshammariDepartment of Educational Technology, College of Education, University of Ha'il, Ha'il, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The metaverse, an interactive and immersive 3D virtual environment, has recently become popular and is widely used in several fields, including education. However, the successful use of metaverse relies on the extent to which users intend to adopt and use it. Close examination of this critical issue reveals a lack of research that examines the effects of certain factors on users' intentions toward using metaverses. Thus, this study extends the technology acceptance model by integrating two constructs-perceived system quality and students' personal innovativeness. Using a survey to collect data, 164 responses were received from students at the University of Ha'il in Saudi Arabia. Two steps in structural equation modelling (SEM) using the AMOS software were applied to analyse the data and test the research hypotheses. The results revealed that perceived system quality had a significant effect on students' intentions to use metaverses through perceived ease of use. Furthermore, personal innovativeness had a significant effect on students' intentions through the perceived usefulness of the metaverse. In addition, perceived usefulness affected students' intentions to use a metaverse. Surprisingly, perceived ease of use had an insignificant effect on students' intentions to use the metaverse. Although the proposed model and its findings contribute to the technology acceptance model (TAM) literature, the study's practical value is significant because it can help educational policymakers and authorities to understand the effect of each factor and plan future strategies. Additionally, the findings of this study can assist practitioners, designers, and developers in designing and promoting the utilisation of metaverses.

Indexed as

Higher educationMetaversePersonal innovativenessSystem qualityTAM

Identifiers

PMID39650365
PMCPMC11623023

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.