Towards Green Production: How Big a Role Does Digital Economic Contribution Play in China? DOI Open Access

Lin Ge,

Haoxiang Zhao, Jiawei Liu

и другие.

Polish Journal of Environmental Studies, Год журнала: 2024, Номер 33(5), С. 5677 - 5692

Опубликована: Июнь 26, 2024

The Chinese government is constantly pursuing a green transformation of its industry under the United Nations Sustainable Development Goals (SDGs).At same time, booming digital economy has brought new opportunities and challenges to government, it relevant discuss contribution China's development.In this study, we use panel data for 247 cities in China from 2011-2019.The impact on total factor productivity examined, mechanism technological innovation process verified.It been found that can promote GTFP positive moderating role process.We also verify threshold effect innovation, be inflated when reaches corresponding threshold.Of course, these findings pass series robustness tests, they are plausible.Accordingly, put forward some policy recommendations mitigate possible problems reality order production China.

Язык: Английский

Does industrial robot adoption affect green total factor productivity? – Evidence from China DOI Creative Commons
Siying Chen,

Siying Mu,

Xingwang He

и другие.

Ecological Indicators, Год журнала: 2024, Номер 161, С. 111958 - 111958

Опубликована: Апрель 1, 2024

This study investigates the impact of industrial robot adoption on Green Total Factor Productivity (GTFP) against backdrop increasing demand for both proliferation and green development utilizing urban panel data from Chinese cities spanning 2007–2019. Findings reveal that significantly improves GTFP, exerting its influence through mechanisms such as energy saving, technological innovation, scale output, linkages. Certain market factors moderate GTFP. Initially, regions reliant high-pollution industries resource-based experience minimal effects, which may diminish or even reverse GTFP improves. Additionally, positive robots is particularly noticeable in with advanced finance. research significant understanding connection between at level exploring pathways transformation.

Язык: Английский

Процитировано

6

The moderate level of digital transformation: from the perspective of green total factor productivity DOI Creative Commons
Kaiwei Jia, Lu‐Jun Li

Mathematical Biosciences & Engineering, Год журнала: 2024, Номер 21(2), С. 2254 - 2281

Опубликована: Янв. 1, 2024

<abstract> <p>In the context of accelerated development digital economy, whether enterprises can drive green total factor productivity (GTFP) through technology has become key to promoting high-quality economy and achieving goal "dual-carbon", However, relationship between transformation GTFP is still controversial in existing studies. Based on data 150 listed companies China's A-share energy industry from 2011 2021, this study empirically analyzes impact using a fixed-effect model. The shows an inverted U-shaped nonlinear effect enterprises' GTFP, conclusion holds after series robustness tests. Mechanism analysis that enterprise investment efficiency labour allocation play significant mediating role above relationship, which mainly stems influence efficiency. Heterogeneity finds more large-scale enterprises, new central western regions. study's findings provide important insights for promote realize industry.</p> </abstract>

Язык: Английский

Процитировано

5

Digitalization transformation and enterprise green innovation: empirical evidence from Chinese listed companies DOI Creative Commons

Rufeng Zhuo,

Yunhua Zhang, Junwei Zheng

и другие.

Frontiers in Environmental Science, Год журнала: 2024, Номер 12

Опубликована: Март 5, 2024

Green innovation is an essential strategy for businesses to gain a competitive edge and attain long-term sustainable growth. It does, however, often run into money problems. The rapid advancement of digital technology provides organizations with potent tools get external resources through transformation, surmount resource obstacles, promote environmentally-friendly innovation. impact mechanism, necessitates additional elucidation. This article analyzes the data Chinese A-share listed firms from 2012 2022, using dependence theory stakeholder theory. study examines how transformation affects ability innovate in environmentally friendly ways by focusing on acquisition resources. Research has shown that may significantly improve quantity quality green businesses. Moreover, findings intermediate indicate potential enhance capacity improving their environmental, social, governance (ESG) standards. Concurrently, we noticed level openness disclosing environmental information corporations partnerships between government enterprises play positive role influencing effects ways. Based our research, provide fresh perspectives policy suggestions assist business managers governments fostering enterprises.

Язык: Английский

Процитировано

5

Does intelligent manufacturing promote a breakthrough in green innovation? Evidence from China DOI Creative Commons
Xiangshu Dong, Yongjiao Du,

Mengchao Zhao

и другие.

Frontiers in Environmental Science, Год журнала: 2025, Номер 13

Опубликована: Янв. 31, 2025

Breakthroughs in green innovation (BGI) have become increasingly prominent spearheading technology, while intelligent manufacturing (IM) offers a fresh technical paradigm for the industry’ development. Yet, due to limitations measuring BGI, existing research on IM and BGI has been ignored. By devising ground-breaking approach this paper takes pilot demonstration projects as an ideal quasi-natural experiment investigates influence of BGI. Our findings indicate that can effectively enhance which are further validated by series rigorous examinations. Further mechanism analysis reveals crowding-in R&amp;D resources, strengthening open innovation, alleviating agency conflict play potential pathways bridging nexus between A heterogeneity highlights disrupt technological path dependency observed high-pollution high-energy consumption industries. suggests form joint effect with environmental regulations promote driven also improve both firm’s economic environmental, social, governance (ESG) performance, leading “win-win” scenario performance study confirms promoting emerging countries is indispensable enhancing serves new impetus

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

Impact of AI Applications on Corporate Green Innovation DOI Creative Commons

Kang Xi,

Xuefeng Shao

International Review of Economics & Finance, Год журнала: 2025, Номер unknown, С. 104007 - 104007

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Impact of Intelligent Manufacturing on Total-Factor Energy Efficiency: Mechanism and Improvement Path DOI Open Access
Pengfei Zhou, Mengyu Han, Yang Shen

и другие.

Sustainability, Год журнала: 2023, Номер 15(5), С. 3944 - 3944

Опубликована: Фев. 21, 2023

Intelligent technology is the core driving force of fourth industrial revolution, which has an important impact on high-quality economic development. In this paper, panel data 30 provinces from 2006 to 2019 were selected construct a regression model conduct empirical analysis role and mechanism intelligent manufacturing in improving total factor energy efficiency. The research results show that first, productivity effect, scale effect resource allocation can significantly improve efficiency factor, conclusion still established after endogenous treatment robustness testing. Second, action labor price distortion carbon emission trading policy are mechanisms for total-factor Specifically, corrected enhance motivation enterprise development innovation solve dilemma low-end structure, thus strengthens willingness enterprises process, eliminate backward equipment increase green technology, it positive regulatory process manufacturing.

Язык: Английский

Процитировано

11

Spatial spillover effects of manufacturing agglomeration on China’s total factor carbon productivity: evidence from the regulatory role of fiscal decentralization DOI
Jinyue Zhang,

Zhenglin Sun

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(8), С. 11912 - 11932

Опубликована: Янв. 16, 2024

Язык: Английский

Процитировано

4

Evaluating the mechanism of AI contribution to decarbonization for sustainable manufacturing in China DOI
Jin Wang, Yanmei Wen, Hai Long

и другие.

Journal of Cleaner Production, Год журнала: 2024, Номер 472, С. 143505 - 143505

Опубликована: Авг. 28, 2024

Язык: Английский

Процитировано

4

Digital Economy and Intelligent Manufacturing Coupling Coordination: Evidence from China DOI Creative Commons
Wanyu Zhang, Fansheng Meng

Systems, Год журнала: 2023, Номер 11(10), С. 521 - 521

Опубликована: Окт. 19, 2023

The digital economy uses its own information advantages to reduce the intensity of energy consumption brought by economic growth. Intelligent manufacturing achieves cost reduction and efficiency through integration intelligence as well digitalization technology. two have become a new engine for sustainable development at present, they can promote influence each other. However, there is lack research on relationship between them. In this regard, study aims build coupling coordination model intelligent make an empirical analysis using data Chinese provincial administrative regions in order provide theoretical reference promoting development. finds that (1) are mainly cross-coupled from four aspects: infrastructure, technological innovation, product optimization organizational change. level speed former significantly higher than those latter, gap does not decrease with time. strong correlation, but no high-quality coordination. (2) main obstacle factors lie imperfect supporting facilities, short board innovation application capacity. lacks innovation. (3) Influencing such opening outside world, development, high-level talent input, industrial structure emphasis different effects their coordinated regions. (4) spatial correlation test shows degree region spatially positively correlated. This helps manufacturing.

Язык: Английский

Процитировано

10