{"title":"人工智能驱动的绿色创新促进可持续发展:来自印度可再生能源转型的经验见解。","authors":"Biswanath Behera, Puspanjali Behera, Ugur Korkut Pata, Litu Sethi, Narayan Sethi","doi":"10.1016/j.jenvman.2025.126285","DOIUrl":null,"url":null,"abstract":"<p><p>This paper explores the contribution of artificial intelligence (AI), green technology innovation (GTI), and renewable energy generation (REG) to sustainable development in India, with a specific focus on their alignment with the Sustainable Development Goals (SDGs). Employing data from 1987 to 2020 and applying the Dynamic ARDL simulation approach, the study analyzes both direct and moderating effects of AI on green growth. The outcomes illustrate that while REG alone has a statistically insignificant impact on green growth (0.073 %), AI and GTI significantly promote long-term green growth. Specifically, AI contributes 0.241 % and GTI 0.163 % to long-term green growth, supporting SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure). Moreover, interaction effects show that AI significantly enhances the effectiveness of REG (with an interaction coefficient of 0.017 %), facilitating a cleaner energy transition in line with SDG 7 (Affordable and Clean Energy). Similarly, AI enhances the contribution of GTI (with an interaction coefficient of 0.041 %), reinforcing environmental quality in support of SDG 13 (Climate Action). Robustness checks via the KRLS estimator confirm these relationships. Policy implications suggest that integrating AI into energy and innovation policies can amplify sustainability outcomes. Hence, a coordinated strategy encompassing digital transformation, technology financing, and institutional support is essential for India to meet its SDG targets and transition toward a low-carbon, innovation-driven economy.</p>","PeriodicalId":356,"journal":{"name":"Journal of Environmental Management","volume":"389 ","pages":"126285"},"PeriodicalIF":8.4000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence-driven green innovation for sustainable development: Empirical insights from India's renewable energy transition.\",\"authors\":\"Biswanath Behera, Puspanjali Behera, Ugur Korkut Pata, Litu Sethi, Narayan Sethi\",\"doi\":\"10.1016/j.jenvman.2025.126285\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This paper explores the contribution of artificial intelligence (AI), green technology innovation (GTI), and renewable energy generation (REG) to sustainable development in India, with a specific focus on their alignment with the Sustainable Development Goals (SDGs). Employing data from 1987 to 2020 and applying the Dynamic ARDL simulation approach, the study analyzes both direct and moderating effects of AI on green growth. The outcomes illustrate that while REG alone has a statistically insignificant impact on green growth (0.073 %), AI and GTI significantly promote long-term green growth. Specifically, AI contributes 0.241 % and GTI 0.163 % to long-term green growth, supporting SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure). Moreover, interaction effects show that AI significantly enhances the effectiveness of REG (with an interaction coefficient of 0.017 %), facilitating a cleaner energy transition in line with SDG 7 (Affordable and Clean Energy). Similarly, AI enhances the contribution of GTI (with an interaction coefficient of 0.041 %), reinforcing environmental quality in support of SDG 13 (Climate Action). Robustness checks via the KRLS estimator confirm these relationships. Policy implications suggest that integrating AI into energy and innovation policies can amplify sustainability outcomes. Hence, a coordinated strategy encompassing digital transformation, technology financing, and institutional support is essential for India to meet its SDG targets and transition toward a low-carbon, innovation-driven economy.</p>\",\"PeriodicalId\":356,\"journal\":{\"name\":\"Journal of Environmental Management\",\"volume\":\"389 \",\"pages\":\"126285\"},\"PeriodicalIF\":8.4000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Environmental Management\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jenvman.2025.126285\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/6/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Environmental Management","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1016/j.jenvman.2025.126285","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/6/19 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Artificial intelligence-driven green innovation for sustainable development: Empirical insights from India's renewable energy transition.
This paper explores the contribution of artificial intelligence (AI), green technology innovation (GTI), and renewable energy generation (REG) to sustainable development in India, with a specific focus on their alignment with the Sustainable Development Goals (SDGs). Employing data from 1987 to 2020 and applying the Dynamic ARDL simulation approach, the study analyzes both direct and moderating effects of AI on green growth. The outcomes illustrate that while REG alone has a statistically insignificant impact on green growth (0.073 %), AI and GTI significantly promote long-term green growth. Specifically, AI contributes 0.241 % and GTI 0.163 % to long-term green growth, supporting SDG 8 (Decent Work and Economic Growth) and SDG 9 (Industry, Innovation, and Infrastructure). Moreover, interaction effects show that AI significantly enhances the effectiveness of REG (with an interaction coefficient of 0.017 %), facilitating a cleaner energy transition in line with SDG 7 (Affordable and Clean Energy). Similarly, AI enhances the contribution of GTI (with an interaction coefficient of 0.041 %), reinforcing environmental quality in support of SDG 13 (Climate Action). Robustness checks via the KRLS estimator confirm these relationships. Policy implications suggest that integrating AI into energy and innovation policies can amplify sustainability outcomes. Hence, a coordinated strategy encompassing digital transformation, technology financing, and institutional support is essential for India to meet its SDG targets and transition toward a low-carbon, innovation-driven economy.
期刊介绍:
The Journal of Environmental Management is a journal for the publication of peer reviewed, original research for all aspects of management and the managed use of the environment, both natural and man-made.Critical review articles are also welcome; submission of these is strongly encouraged.