Examining the impact of green technological specialization and the integration of AI technologies on green innovation performance: evidence from China

Sirinant Khunakornbodintr
{"title":"Examining the impact of green technological specialization and the integration of AI technologies on green innovation performance: evidence from China","authors":"Sirinant Khunakornbodintr","doi":"10.3389/frai.2023.1237285","DOIUrl":null,"url":null,"abstract":"China's commitment to achieving carbon neutrality by 2060 has sparked scholars' interest in examining the environmental ramifications of green technologies in the digital era. While plenty of them provide eco-efficiency policy such as increasing R&D investment or stimulating green exports, little attention has been paid to the firm-level technological management and recombination strategies such as differentiation/specialization of green portfolios along with AI integration, which can significantly impact the pace of net-zero transitions. To address these gaps, this study investigates the moderating effect of technological specialization on levels of AI integration into green technologies estimated by green-AI technological distance and enterprises' innovation performance in Chinese contemporary contexts. Regression results of fixed-effect model in Chinese patent data (2011–2020) indicate that enterprises' green innovation performance is significantly improved as AI integrates more into the green technologies due to the legitimacy and the inability to appropriate more green values. Interestingly, specialized green-technological enterprises demonstrate superior performance in integrating distant AI technologies. This occurrence could potentially be driven by the governments' incentives and the organization's risk attitudes, shaping green innovation outcomes. Hence, the study underscores the importance of considering both the AI integration and green specialization in shaping innovation outcomes amidst green transitions.","PeriodicalId":508738,"journal":{"name":"Frontiers in Artificial Intelligence","volume":"14 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frai.2023.1237285","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

China's commitment to achieving carbon neutrality by 2060 has sparked scholars' interest in examining the environmental ramifications of green technologies in the digital era. While plenty of them provide eco-efficiency policy such as increasing R&D investment or stimulating green exports, little attention has been paid to the firm-level technological management and recombination strategies such as differentiation/specialization of green portfolios along with AI integration, which can significantly impact the pace of net-zero transitions. To address these gaps, this study investigates the moderating effect of technological specialization on levels of AI integration into green technologies estimated by green-AI technological distance and enterprises' innovation performance in Chinese contemporary contexts. Regression results of fixed-effect model in Chinese patent data (2011–2020) indicate that enterprises' green innovation performance is significantly improved as AI integrates more into the green technologies due to the legitimacy and the inability to appropriate more green values. Interestingly, specialized green-technological enterprises demonstrate superior performance in integrating distant AI technologies. This occurrence could potentially be driven by the governments' incentives and the organization's risk attitudes, shaping green innovation outcomes. Hence, the study underscores the importance of considering both the AI integration and green specialization in shaping innovation outcomes amidst green transitions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
考察绿色技术专业化和人工智能技术整合对绿色创新绩效的影响:来自中国的证据
中国承诺到 2060 年实现碳中和,这激发了学者们研究数字时代绿色技术对环境影响的兴趣。尽管许多研究提供了生态效率政策,如增加研发投资或刺激绿色出口,但很少有人关注企业层面的技术管理和重组策略,如绿色产品组合的差异化/专业化以及人工智能整合,这些都会对净零转型的步伐产生重大影响。为了弥补这些不足,本研究探讨了在中国当代背景下,技术专业化对以绿色-人工智能技术距离和企业创新绩效估算的人工智能融入绿色技术水平的调节作用。利用中国专利数据(2011-2020 年)建立的固定效应模型的回归结果表明,随着人工智能更多地融入绿色技术,企业的绿色创新绩效会显著提高,原因在于人工智能的合法性以及无法占有更多的绿色价值。有趣的是,专业化的绿色技术企业在整合遥远的人工智能技术方面表现优异。政府的激励措施和企业的风险态度可能会影响绿色创新的结果。因此,本研究强调,在绿色转型过程中,必须同时考虑人工智能集成和绿色专业化对创新成果的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Using synthetic dataset for semantic segmentation of the human body in the problem of extracting anthropometric data Enhancing educational Q&A systems using a Chaotic Fuzzy Logic-Augmented large language model AI can empower agriculture for global food security: challenges and prospects in developing nations Examining the impact of green technological specialization and the integration of AI technologies on green innovation performance: evidence from China Expandable-RCNN: toward high-efficiency incremental few-shot object detection
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1