Does Fintech Contribute to Green Total Factor Productivity? Evidence from 270 Cities in China DOI
Zhen Zhu,

zhaoyong chen,

Xiuli Geng

и другие.

Опубликована: Янв. 1, 2024

Язык: Английский

Is artificial intelligence a curse or a blessing for enterprise energy intensity? Evidence from China DOI
Weike Zhang, Ming Zeng

Energy Economics, Год журнала: 2024, Номер 134, С. 107561 - 107561

Опубликована: Апрель 18, 2024

Язык: Английский

Процитировано

30

Artificial intelligence and green product innovation: Moderating effect of organizational capital DOI Creative Commons
Ying Ying, Shanyue Jin

Heliyon, Год журнала: 2024, Номер 10(7), С. e28572 - e28572

Опубликована: Март 22, 2024

Green product innovation (GPDI) is crucial for addressing ecological issues and essential enterprises' green operations long-term growth. Digitization offers new possibilities enhancing corporate practices. Nevertheless, previous studies have predominantly addressed the association between overall digitalization innovation, research on outcome of specific digital technology categories lacking. Within this framework, study broadens investigation into connection distinct technologies innovation. The period 2013–2022 was selected as sample observation period, with companies listed China's A-share market objects. fixed-effects model applied to investigate impact artificial intelligence (AI) firms' GPDI while exploring interaction effect organizational capital. findings indicate that AI beneficial in businesses. This enhanced by employee board human capital but diminished social These results remained valid after two-stage least squares regression. utilization resource-based view dynamic capacity theory business implementation. Furthermore, it extends resulting provides a enhancement pathway GPDI. has significant theoretical practical implications.

Язык: Английский

Процитировано

8

Artificial intelligence and corporate ESG performance DOI
Junjun Li, Tong Wu,

Boqiang Hu

и другие.

International Review of Financial Analysis, Год журнала: 2025, Номер unknown, С. 104036 - 104036

Опубликована: Фев. 1, 2025

Процитировано

1

Artificial Intelligence and Technological Innovation: Evidence from China’s Strategic Emerging Industries DOI Open Access

Daojun Li,

Haiqin Wang,

Wang Juan

и другие.

Sustainability, Год журнала: 2024, Номер 16(16), С. 7226 - 7226

Опубликована: Авг. 22, 2024

Artificial intelligence (AI) is the driving force for leapfrog development of science and technology, optimization upgrading industry, as well overall leap in productivity. Using panel data strategic emerging firms Chinese A-Share Listed companies from 2012 to 2022, this study empirically examines impact AI on technological innovation through a two-way fixed-effects model. The discovered that capability can be greatly enhanced by degree present industry businesses. This conclusion remains valid following series robustness tests. mechanism demonstrates how increases businesses’ capacity lowering funding constraints boosting R&D investment. According heterogeneity analysis, has varying empowering effects different industries within industries. Its strongest effect observed western region, with central eastern regions seeing weakest effects. Additionally, promotion greater state-owned enterprises than non-state-owned enterprises. To better play role encouraging technical industries, it required establish dedicated funds, create an technology platform, develop differentiated regulations.

Язык: Английский

Процитировано

5

Analysis of the Effect of Digital Financial Inclusion in Promoting Inclusive Growth: Mechanism and Statistical Verification DOI Creative Commons
Jingyi Yang, Xiaoyang Guo, Xiuwu Zhang

и другие.

Economics, Год журнала: 2024, Номер 18(1)

Опубликована: Янв. 1, 2024

Abstract As the main goal of economic development, inclusive growth (IG) is an important strategic measure to achieve common prosperity. Whether digital finance can make use advantages scientific and technological innovation promote IG great significance fairness, effectiveness, inclusiveness global development. Based on panel data 30 provinces in China from 2011 2021 (excluding Tibet, Hong Kong, Macao Taiwan), this article first measures index three dimensions: sustainable growth, income distribution, social equity. Subsequently, uses a series mathematical statistical models verify transmission path mechanism influence IG. The findings are as follows: (1) level shows decreasing trend east middle west, while average annual rate eastern region obviously lower than that central western regions; (2) has significant promotion effect IG, regions more obvious IG; (3) by increasing activity improving human capital. Finally, based research conclusions, puts forward relevant policy suggestions, which provide reference value for formulating high-quality national development strategies promoting

Язык: Английский

Процитировано

4

The impact of carbon emissions trading on green total factor productivity based on evidence from a quasi-natural experiment DOI Creative Commons
Haisheng Hu

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 29, 2025

Based on a balanced panel dataset of 272 prefecture-level cities from 2000 to 2022, this paper systematically investigates the impact carbon emissions trading system green total factor productivity and its underlying mechanisms an integrated perspective overall, dynamic, spatial dimensions. The findings reveal that (1) significantly enhances regional productivity, primarily by optimizing resource allocation efficiency strengthening competitiveness. (2) From dynamic perspective, policy effect exhibited U-shaped relationship: 2013 2018, was suppressed due underdeveloped market environment; after with maturation stabilization, effects improved significantly. (3) Spatial analysis indicates positively influences pilot regions but generates siphon nonpilot regions, leading performance divergence, although overall remains positive. (4) Heterogeneity reveals has more pronounced in higher intensity, stricter environmental regulations, better infrastructure, richer endowments, reflecting significant disparities effectiveness. This study provides empirical evidence theoretical insights optimize policies achieve development.

Язык: Английский

Процитировано

0

The Impact and Mechanisms of Artificial Intelligence on Green Economic Efficiency: Empirical Evidence from China’s GTFP Improvement DOI
Hui Huang,

Jing Yang,

Changman Ren

и другие.

Journal of the Knowledge Economy, Год журнала: 2025, Номер unknown

Опубликована: Фев. 19, 2025

Язык: Английский

Процитировано

0

How Does Artificial Intelligence Shape Supply Chain Resilience? The Moderating Role of the CEOs’ Sports Experience DOI Creative Commons
Yuxuan Xu,

Yu Hua,

Ran Qiu

и другие.

Systems, Год журнала: 2025, Номер 13(3), С. 190 - 190

Опубликована: Март 9, 2025

In the volatility, uncertainty, complexity, and ambiguity (VUCA) environment, application of artificial intelligence (AI) technologies is a key engine for shaping supply chain resilience (SCR). This study employs entropy method to develop an evaluation index system SCR, incorporating two dimensions: resistance recovery capacity. Using sample Chinese-listed enterprises from 2009 2022, this reveals that AI significantly enhances CEOs’ sports experience can positively moderate association between SCR. Mechanism examination shows promotes SCR through operational efficiency optimization, information, knowledge spillover in chain. Heterogeneity analysis positive impact more significant firms with high-skilled labor force, high heterogeneity executive team’s human capital, high-tech industries, regions strong digital infrastructure. Moreover, has diffusion effect on upstream downstream chain, improving adoption levels. Our research not only augments existing literature economic ramifications strategic value derived extramural but also offers both theoretical frameworks empirical insights recruitment fortifying

Язык: Английский

Процитировано

0

Effect of Artificial Intelligence on Chinese Urban Green Total Factor Productivity DOI Creative Commons

Yuanhe Zhang,

Chaobo Zhou

Land, Год журнала: 2025, Номер 14(3), С. 660 - 660

Опубликована: Март 20, 2025

The manner of achieving high-quality economic development in China through artificial intelligence (AI) has become a focus academic attention. On the basis panel data prefecture-level cities from 2010 to 2021, this research utilizes exogenous impact implementation National New Generation Artificial Intelligence Innovation and Development Pilot Zone (AIPZ) explore causal effect between AI green total factor productivity (GTFP). results are as follows: (1) significant enhancement on urban GTFP. After using series robustness tests, such parallel trend sensitivity test, heterogeneity treatment machine learning, conclusion remains robust. (2) Subsequent mechanism analysis shows that GTFP is mainly achieved by enhancing innovation, promoting industrial structure upgrading, reducing land resource misallocation. (3) Lastly, heterogeneous. also markedly effects high human capital, non-resource-based economies, levels consumption behavior. This study provides useful insights for develop achieve development.

Язык: Английский

Процитировано

0

Artificial intelligence of robotics and green transformation: evidence from Chinese manufacturing firms DOI
Lei Sun, Jing Wang, Shanyong Wang

и другие.

Environment Development and Sustainability, Год журнала: 2025, Номер unknown

Опубликована: Март 20, 2025

Язык: Английский

Процитировано

0