The pathway to curb greenwashing in sustainable growth: The role of artificial intelligence DOI
Dongyang Zhang

Energy Economics, Journal Year: 2024, Volume and Issue: 133, P. 107562 - 107562

Published: April 16, 2024

Language: Английский

Can industrial robots reduce carbon emissions? Based on the perspective of energy rebound effect and labor factor flow in China DOI
Jianlong Wang, Weilong Wang, Yong Liu

et al.

Technology in Society, Journal Year: 2023, Volume and Issue: 72, P. 102208 - 102208

Published: Feb. 1, 2023

Language: Английский

Citations

85

Does corruption hurt green innovation? Yes – Global evidence from cross-validation DOI
Jun Wen, Hua-Tang Yin,

Chyi-Lu Jang

et al.

Technological Forecasting and Social Change, Journal Year: 2023, Volume and Issue: 188, P. 122313 - 122313

Published: Jan. 19, 2023

Language: Английский

Citations

84

Can enterprise green technology innovation performance achieve “corner overtaking” by using artificial intelligence?—Evidence from Chinese manufacturing enterprises DOI

Tian Hong-na,

Liyan Zhao,

Yunfang Li

et al.

Technological Forecasting and Social Change, Journal Year: 2023, Volume and Issue: 194, P. 122732 - 122732

Published: July 14, 2023

Language: Английский

Citations

83

Can digital finance narrow the regional disparities in the quality of economic growth? Evidence from China DOI

Chengchao Lv,

Jie Song, Chien‐Chiang Lee

et al.

Economic Analysis and Policy, Journal Year: 2022, Volume and Issue: 76, P. 502 - 521

Published: Sept. 12, 2022

Language: Английский

Citations

79

Roadmap to achieving sustainable development: Does digital economy matter in industrial green transformation? DOI
Xiaodong Yang, Yang Xu,

Asif Razzaq

et al.

Sustainable Development, Journal Year: 2023, Volume and Issue: 32(3), P. 2583 - 2599

Published: Oct. 27, 2023

Abstract The rapid advancements in the digital economy have created numerous opportunities and solutions for industrial green transformation. However, complex relationship between these two has received relatively less attention. Therefore, this study analyses how impacts transformation across 30 Chinese provinces. empirical findings highlight economy's significant role driving Within dynamic framework, crucial operational mechanisms been identified: heightened public awareness of environmental issues vigorous innovation technologies. It becomes evident that can energize sustain momentum Notably, influence is most pronounced eastern‐central China. its impact western China appears weaker, especially at higher quantiles. We observe a strong correlation evolution terms space time. Higher spatiotemporal regression coefficients are primarily found areas south Hu line, while lower values more common northern regions. These provide insights into be strategically applied to drive

Language: Английский

Citations

72

Environmental performance evaluation of electric enterprises during a power crisis: Evidence from DEA methods and AI prediction algorithms DOI
Yinghao Pan, Chaochao Zhang, Chien‐Chiang Lee

et al.

Energy Economics, Journal Year: 2024, Volume and Issue: 130, P. 107285 - 107285

Published: Jan. 6, 2024

Language: Английский

Citations

71

Modeling the effects of artificial intelligence (AI)-based innovation on sustainable development goals (SDGs): Applying a system dynamics perspective in a cross-country setting DOI Creative Commons
Sharmin Nahar

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 201, P. 123203 - 123203

Published: Jan. 20, 2024

Global environmental outcomes, productivity, inclusion, and equality aspects are already beginning to be impacted by artificial intelligence (AI), both immediately over time. AI is expected have beneficial detrimental effects on Sustainable Development Goals (SDGs). Nevertheless, there a lacuna in the literature regarding systematically forecasting `AI's impact different facets of SDGs time various countries. Moreover, though existing has reported correlation between innovation, no prior studies forecast influence AI-based innovation SDG Outcomes. To fill these significant research gaps, this study forecasts achieving nine years, extending from 2022 2030 22 countries (including developed developing countries) across five continents via system dynamics modeling-based simulation grounded Institutional Theory (Technology Enactment Framework). The findings exhibit varying impacts SDGs. This enriches AI, sustainable development providing intricate relationship SDGs, thereby offering valuable insights reader.

Language: Английский

Citations

58

Influence of green innovation on disclosure quality: Mediating role of media attention DOI
Kung‐Cheng Ho,

Xixi Shen,

Cheng Yan

et al.

Technological Forecasting and Social Change, Journal Year: 2023, Volume and Issue: 188, P. 122314 - 122314

Published: Jan. 6, 2023

Language: Английский

Citations

53

Role of energy utilization intensity, technical development, economic openness, and foreign tourism in environmental sustainability DOI
Gul Jabeen, Dong Wang, Cem Işık

et al.

Gondwana Research, Journal Year: 2023, Volume and Issue: unknown

Published: March 1, 2023

Language: Английский

Citations

49

Industry 4.0 innovations and their implications: An evaluation from sustainable development perspective DOI Creative Commons
Iqra Sadaf Khan, Muhammad Ovais Ahmad, Jukka Majava

et al.

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 405, P. 137006 - 137006

Published: March 30, 2023

As the dyad of Industry 4.0 (I4.0) and innovation have gained greater attention from researchers, practitioners policy makers, integration sustainability sustainable development paradigms to this become fundamental sustain businesses’ competitive advantage. A variety I4.0 based innovations with several implications exists in literature, but they largely address independent distinct knowledge areas, which yields an opportunity explore interconnections I4.0-innovation-sustainability nexus. Therefore, research performs a systematic literature review synthesize nexus by investigating how combination technologies different types innovations, could contribute thereby providing implications. Our portfolio derived three databases analyzed 58 journal articles that addressed simultaneous links I4.0-innovation-sustainability. The primary findings show results various including process, product, business model, supply chain, organizational, open, marketing advance triple bottom line (TBL) sustainability, circular economy (CE), models (SBMs) achievement goals (SDGs). While most studies focus on model TBL CE implications, more is required significant overlooked areas such as SDGs.

Language: Английский

Citations

49