Evidence map›Paper›PMID 39258203›Full record

ArticleHeliyon2024

Sanctions and opportunities: Factors affecting China's high-tech SMEs adoption of artificial intelligence computing leasing business.

Wei Sun, Alisher Tohirovich Dedahanov, Wei Ping Li, Ho Young Shin

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Wei SunManagement School, Henan University of Urban Construction, Pingdingshan, China.
Alisher Tohirovich DedahanovBusiness School, Central Asian University, Tashkent, Uzbekistan.
Wei Ping LiNational Cyber Security Experimental Center, Railway Police College, Zhengzhou, China.
Ho Young ShinSchool of Business, Yeungnam University, Gyeongsan, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to sanctions, more Chinese high-tech SMEs are turning to rent AI computing power through cloud service providers. Therefore, it is necessary to give a variety of suggestions for China's high-tech SMEs to better develop AI applications through computing power leasing. Because traditional theories are difficult to explain this new technology adoption behavior, this research combines and extends TTF and UTAUT2 theories to take an empirical research. A total of 387 questionnaires were received, of which incomplete questionnaires and invalid questionnaires were issued, leaving 281 valid questionnaires. The results indicate that SME innovativeness, perceived risk, performance expectancy, price value and task technology fit are all significantly related to usage, whereas task technology fit moderates the other relationships significantly. Results give a variety of suggestions for China's high-tech SMEs to better develop AI applications through computing power leasing in the context of sanctions. This study not only suggests ways to increase the competitiveness of SMEs by optimizing leasing services but also give directions in investors' investment decisions. The findings are also applicable to the large-scale application of China's domestic AI chips in computing power leasing scenarios in the future.

Indexed as

Artificial intelligenceComputing power leasingInnovativenessSMETask technology fitUTAUT

Identifiers

PMID39258203
PMCPMC11385760

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.