Yayın:
Exploring impact of AI-robotics, energy transition, energy utilization, and economic growth on environmental degradation: Evidence from leading Asian countries by KRLS model

Yükleniyor...
Küçük Resim

Tarih

Kurum Yazarları

Danışman

item.page.editor

Editör

Bölüm / Program

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

CHINA UNIV GEOSCIENCES, BEIJING

DOI

10.1016/j.gsf.2026.102302

Türü

View PlumX Details

Araştırma Projeleri

Akademik Birimler

Dergi Sayısı

Özet

Compatible with the increasing common interest of countries on the environmental issues and recently increasing phenomenon of artificial intelligence (AI), the study investigates energy-related carbon dioxide emissions by considering energy transition, energy consumption (EC) sub-types, and economic growth in leading three Asian countries (namely, China, Japan, & Korea) as the countries having the highest operational stock in AI robotics. In this vein, the study employs a novel kernel regularized least squares (KRLS) model on yearly data from 2000 to 2019 to uncover the marginal impact. The results show that (i) AI robotics has only a reducing impact on the emissions at 0.25th percentile, whereas it is ineffective across remaining percentiles; (ii) energy transition, fossil EC, and economic growth are completely ineffective to ensure a reducing impact; (iii) renewable EC is beneficial at 0.25th percentile in China while it completely beneficial (ineffective) in Japan (Korea); (iv) interaction of AI with fossil (renewable) EC is beneficial for Japan at 0.25th (all) percentiles; (v) interaction of AI with energy transition is helpful for China and Japan at 0.25th percentile; (vi) KRLS model presents successful estimation results around 99.7%; (vii) the results are robust based on alternative indicator use (i.e., ecological footprint); (viii) the variables considered have varying marginal impacts across percentiles. Thus, the study suggests the inefficiency of AI robotics except for some lower percentiles, whereas renewable EC can be much more helpful to ensure a decline in emissions in the countries examined. (c) 2026 China University of Geosciences (Beijing) and Peking University. Published by Elsevier B.V. on behalf of China University of Geosciences (Beijing). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Tanım

Dergi veya Seri

GEOSCIENCE FRONTIERS

ISSN

1674-9871

ISBN

Haklar

Alıntı

Koleksiyonlar

Onay

Gözden geçir

Tamamlayıcı Bilgiler

Referans Gösteren

Related Patent

Related Goal

0

Views

0

Downloads