{"title":"An integrated analysis of AI-driven green financing, subsidies, and knowledge to enhance CO2 reduction efficiency","authors":"Chien-Chiang Lee , Jafar Hussain , Qasir Abass","doi":"10.1016/j.eap.2024.12.021","DOIUrl":null,"url":null,"abstract":"<div><div>The demanding global challenge of climate change necessitates innovative strategies to achieve carbon neutrality, particularly in industrial sectors that contribute significantly to Carbon dioxide (CO<sub>2</sub>) emissions. In this context, understanding the interplay between Artificial intelligence (AI) driven green financing and targeted subsidies is critical for enhancing emission reduction efficiency (ERE). This research explores a significant advancement in revealing optimal pathways toward carbon neutrality through AI-driven green financing at the industrial level. Robust regression analysis and simulation-based optimization were employed on data from 1000 firms in Punjab, Pakistan. The study indicates the positive impact of knowledge about green awareness, green inventions, and emission impact awareness on CO<sub>2</sub> ERE. The finding elaborates that subsidies targeting CO<sub>2</sub> emission impact awareness have a more significant influence on CO<sub>2</sub> ERE than AI-based green financing, focusing on the pivotal role of targeted financial incentives in achieving effective industrial-level carbon reduction. These insights offer valuable guidance for policymakers and industry practitioners, emphasizing the interconnected dynamics of AI-driven green financing and optimal subsidies in realizing sustainable economic outcomes.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"85 ","pages":"Pages 675-693"},"PeriodicalIF":7.9000,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Analysis and Policy","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0313592624003576","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
The demanding global challenge of climate change necessitates innovative strategies to achieve carbon neutrality, particularly in industrial sectors that contribute significantly to Carbon dioxide (CO2) emissions. In this context, understanding the interplay between Artificial intelligence (AI) driven green financing and targeted subsidies is critical for enhancing emission reduction efficiency (ERE). This research explores a significant advancement in revealing optimal pathways toward carbon neutrality through AI-driven green financing at the industrial level. Robust regression analysis and simulation-based optimization were employed on data from 1000 firms in Punjab, Pakistan. The study indicates the positive impact of knowledge about green awareness, green inventions, and emission impact awareness on CO2 ERE. The finding elaborates that subsidies targeting CO2 emission impact awareness have a more significant influence on CO2 ERE than AI-based green financing, focusing on the pivotal role of targeted financial incentives in achieving effective industrial-level carbon reduction. These insights offer valuable guidance for policymakers and industry practitioners, emphasizing the interconnected dynamics of AI-driven green financing and optimal subsidies in realizing sustainable economic outcomes.
期刊介绍:
Economic Analysis and Policy (established 1970) publishes articles from all branches of economics with a particular focus on research, theoretical and applied, which has strong policy relevance. The journal also publishes survey articles and empirical replications on key policy issues. Authors are expected to highlight the main insights in a non-technical introduction and in the conclusion.