Venture Capital and AI Transformation: Evidence from China's A-Share Listed Companies DOI

Lanzhou Jiang,

Qingcheng Huang, Gonglin Yuan

и другие.

Опубликована: Окт. 18, 2024

Язык: Английский

Decoding the Nexus: How Fintech and AI Stocks Drive the Future of Sustainable Finance DOI Creative Commons
Chaoqun Ma,

Xukang Liu,

Tony Klein

и другие.

International Review of Economics & Finance, Год журнала: 2025, Номер unknown, С. 103877 - 103877

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

2
Impact of Artificial Intelligence on Corporate Green Transformation DOI
Houhua Li, Hao Wu,

Jian Rao

и другие.

Finance research letters, Год журнала: 2025, Номер unknown, С. 107427 - 107427

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
How does digital industry agglomeration drive carbon peaking and carbon neutrality in China? The role of digital technology innovation DOI

Ru-Yu Xu,

Ke-Liang Wang

Journal of Cleaner Production, Год журнала: 2025, Номер 510, С. 145642 - 145642

Опубликована: Май 5, 2025

Язык: Английский

Процитировано

0
Impact of Enterprise Artificial Intelligence Development on Human Capital Structure DOI
Zhe Li,

Huiyu Yang,

Tingting Zhang

и другие.

Finance research letters, Год журнала: 2025, Номер unknown, С. 107600 - 107600

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0
Assessing the Impact of Artificial Intelligence Tools on Employee Productivity: Insights from a Comprehensive Survey Analysis DOI Open Access
Sabina-Cristiana Necula, Doina Fotache,

Emanuel Rieder

и другие.

Electronics, Год журнала: 2024, Номер 13(18), С. 3758 - 3758

Опубликована: Сен. 21, 2024

This study provides a nuanced understanding of AI’s impact on productivity and employment using machine learning models Bayesian Network Analysis. Data from 233 employees across various industries were analyzed logistic regression, Random Forest, XGBoost, with 5-fold cross-validation. The findings reveal that high levels AI tool usage integration within organizational workflows significantly enhance productivity, particularly among younger employees. A significant interaction between tools (β = 0.4319, p < 0.001) further emphasizes the importance comprehensive adoption. Analysis highlights complex interdependencies usage, innovation, employee characteristics. confirms strategic integration, along targeted training programs ethical frameworks, is essential for maximizing economic potential.

Язык: Английский

Процитировано

2
Latent Information in the Evolving Energy Structure DOI Open Access
Boqiang Lin, Yitong Zhu

Journal of Global Information Management, Год журнала: 2024, Номер 32(1), С. 1 - 21

Опубликована: Ноя. 10, 2024

Recent studies indicate that Artificial Intelligence (AI) technology, characterized by its integration of information and communication technology attributes, exerts a multifaceted influence on the energy system. The authors employ Difference-in-Differences (DID) Triple-Difference (DDD) models to investigate effects AI. research initially demonstrates AI may exhibit dual attributes constraining structure. Specifically, rapid development tends increase proportion fossil fuel-based electricity generation while optimizing consumption renewable energy. Furthermore, degradation structure stems from surge in AI, which capacity is unable satisfy. Lastly, industrial agglomeration construction digital economy have positive impacts energy; technological innovation aids mitigating negative shocks This study provides new perspective role transition.

Язык: Английский

Процитировано

0
Venture Capital and AI Transformation: Evidence from China's A-Share Listed Companies DOI

Lanzhou Jiang,

Qingcheng Huang, Gonglin Yuan

и другие.

Опубликована: Окт. 18, 2024

Язык: Английский

Процитировано

0