How does artificial intelligence affect the transformation of China's green economic growth? An analysis from internal-structure perspective.

Artificial intelligence Green total factor productivity Resource allocation efficiency Scale efficiency Technical progress

Journal

Journal of environmental management
ISSN: 1095-8630
Titre abrégé: J Environ Manage
Pays: England
ID NLM: 0401664

Informations de publication

Date de publication:
03 Jan 2024
Historique:
received: 06 11 2023
revised: 09 12 2023
accepted: 19 12 2023
medline: 5 1 2024
pubmed: 5 1 2024
entrez: 4 1 2024
Statut: aheadofprint

Résumé

Artificial intelligence (AI) has been proved to be an important engine of green economic development, yet how it will affect the internal structure of green economy is unknown. The aim of this study is to examine the impact and its mechanism of AI on green total factor productivity (GTFP) from the internal-structure perspective, by using provincial panel data of China from 2009 to 2021 and global Malmquist index. The main research results show that: (1) the development of AI contributes to China's GTFP growth. And this effect is more significant in undeveloped areas; (2) AI promotes China's GTFP growth mainly by improving resource allocation efficiency, while it exerts little impact through the paths of technological progress and scale efficiency; (3) the transmission mechanism of AI on GTFP varies greatly among China's three main regions. In the eastern region, AI improves GTFP mainly by both advancing technological progress and improving resource allocation efficiency, while in central region AI contributes to GTFP growth mainly through technological progress. Compared with the eastern and central regions, AI in the western region plays a stronger impact on GTFP through the channel of improving scale efficiency. This study helps to understand the pathways of artificial intelligence affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions.

Identifiants

pubmed: 38176382
pii: S0301-4797(23)02711-1
doi: 10.1016/j.jenvman.2023.119923
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

119923

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Chao Feng (C)

School of Economics and Business Administration, Chongqing University, Chongqing, 400030, China.

Xinru Ye (X)

School of Economics and Business Administration, Chongqing University, Chongqing, 400030, China.

Jun Li (J)

School of Economics and Business Administration, Chongqing University, Chongqing, 400030, China. Electronic address: jun_lee223@163.com.

Jun Yang (J)

School of Economics and Business Administration, Chongqing University, Chongqing, 400030, China.

Classifications MeSH