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

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.

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Publication Details

Journal
Heliyon
Published
2024-08-01
DOI
https://doi.org/10.1016/j.heliyon.2024.e36620
Citations
7
Primary Topic
Business and Economic Development
Type
article
Field-Weighted Citation Impact
4.97
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article

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

Wei Sun, Ho Young Shin, Alisher Tohirovich Dedahanov, Wei-Ping Li
7 citations
Heliyon
Business and Economic Development
4.97
article

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

Wei Sun, Ho Young Shin, Alisher Tohirovich Dedahanov, Wei-Ping Li
article en
7 citations

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.

HeliyonVol. 10(16)
Henan University of Urban Construction (CN), Zhengzhou Railway Vocational & Technical College (CN), Yeungnam University (KR)
Openalex Percentile: Top 6%
Business and Economic Development
4.97
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Sanctions and opportunities: Factors affecting China's high-tech SMEs adoption of artificial intelligence computing leasing business — Wei Sun, Ho Young Shin, et al. · Heliyon (2024) | TGRS Research Map | TGRS