Fangfang Feng , Junjun Li , Feng Zhang , Jinghuan Sun
{"title":"The impact of artificial intelligence on green innovation efficiency: Moderating role of dynamic capability","authors":"Fangfang Feng , Junjun Li , Feng Zhang , Jinghuan Sun","doi":"10.1016/j.iref.2024.103649","DOIUrl":null,"url":null,"abstract":"<div><div>Environmental concerns have intensified the focus on sustainable innovation, with artificial intelligence (AI) emerging as a potential driver. However, the relationship between AI adoption and green innovation efficiency, particularly in emerging economies, remains unclear. This gap is crucial to address as it could reveal pathways to enhance sustainable development in rapidly growing markets. Here, we investigate how AI impacts green innovation efficiency in Chinese firms and examine the moderating effects of dynamic capabilities. Using panel data from 26,117 firm-year observations of Chinese A-share listed companies (2008–2022), we employ a novel text-based measure of AI adoption and assess green innovation efficiency through patent applications and R&D expenditure. Our findings reveal a significant positive relationship between AI adoption and green innovation efficiency, with dynamic capabilities enhancing this effect. The impact is stronger in non-state-owned and high-tech firms. These results demonstrate AI's potential as a catalyst for sustainable development and highlight the importance of organizational capabilities in realizing these benefits. Our study contributes to the evolving discourse on technology-driven sustainability, providing insights for both theory and practice in leveraging AI for green innovation in diverse economic contexts.</div></div>","PeriodicalId":14444,"journal":{"name":"International Review of Economics & Finance","volume":"96 ","pages":"Article 103649"},"PeriodicalIF":4.8000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Economics & Finance","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1059056024006415","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
Environmental concerns have intensified the focus on sustainable innovation, with artificial intelligence (AI) emerging as a potential driver. However, the relationship between AI adoption and green innovation efficiency, particularly in emerging economies, remains unclear. This gap is crucial to address as it could reveal pathways to enhance sustainable development in rapidly growing markets. Here, we investigate how AI impacts green innovation efficiency in Chinese firms and examine the moderating effects of dynamic capabilities. Using panel data from 26,117 firm-year observations of Chinese A-share listed companies (2008–2022), we employ a novel text-based measure of AI adoption and assess green innovation efficiency through patent applications and R&D expenditure. Our findings reveal a significant positive relationship between AI adoption and green innovation efficiency, with dynamic capabilities enhancing this effect. The impact is stronger in non-state-owned and high-tech firms. These results demonstrate AI's potential as a catalyst for sustainable development and highlight the importance of organizational capabilities in realizing these benefits. Our study contributes to the evolving discourse on technology-driven sustainability, providing insights for both theory and practice in leveraging AI for green innovation in diverse economic contexts.
期刊介绍:
The International Review of Economics & Finance (IREF) is a scholarly journal devoted to the publication of high quality theoretical and empirical articles in all areas of international economics, macroeconomics and financial economics. Contributions that facilitate the communications between the real and the financial sectors of the economy are of particular interest.