Evidence map›Paper›PMID 41792405›Full record

ArticleScientific reports2026

Unlocking the road to entrepreneurial success: quality drivers and digital competence in cloud computing adoption.

Chun Wu, Ahmed Muneeb Mehta, Zhi Li, Muhammad Asif, Muhammad Farrukh Shahzad

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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

5 authors.

Chun WuSchool of Continuing Education, NingboTech University, Ningbo, 315000, China.
Ahmed Muneeb MehtaHailey College of Banking and Finance, University of the Punjab, Lahore, Pakistan.
Zhi LiSchool of Media and Law, NingboTech University, Ningbo, 315000, China. lizhi@nbt.edu.cn.
Muhammad AsifUE Business School, University of Education, Lahore, Pakistan.
Muhammad Farrukh ShahzadCollege of Economics and Management, Beijing University of Technology, Beijing, 100124, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cloud computing has transformed small and medium-sized enterprises (SMEs) by providing flexible, scalable, and affordable IT solutions. However, adoption decisions are influenced by issues with digital competency, trust, and service quality; therefore, it’s critical to investigate the main factors that support and hinder cloud adoption in SMEs. Based on data from 367 managers in Pakistan, this study employs a hybrid structural equation modelling (SEM) and artificial neural network (ANN) approach to examine the effects of information quality, service quality, and system quality on cloud computing adoption in SMEs. Regulatory support as a mediator, and entrepreneurial digital competency as a moderator. The findings reveal that information quality and service quality significantly impact cloud computing adoption in SMEs, while system quality has an insignificant effect, and that regulatory support mediates these connections to some extent. Furthermore, entrepreneurial digital competency has a negligible effect on system quality but moderates the effects of information quality and service quality on cloud computing adoption. Regulatory support is the most significant predictor, according to ANN data. This study enhances the literature by using a hybrid SEM-ANN approach to investigate nonlinear interactions in SMEs’ adoption of cloud computing, offering fresh perspectives on the moderating role of entrepreneurial digital competency.

Indexed as

Artificial neural networkCloud computingInformation qualityService qualitySMEsSystem quality

Identifiers

PMID41792405
PMCPMC13083961

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.