Pregled bibliografske jedinice broj: 1274238
The evolution of renewable energy environments utilizing artificial intelligence to enhance energy efficiency and finance
The evolution of renewable energy environments utilizing artificial intelligence to enhance energy efficiency and finance // Heliyon, 9 (2023), 5; e16160, 15 doi:10.1016/j.heliyon.2023.e16160 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1274238 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
The evolution of renewable energy environments utilizing artificial intelligence to enhance energy efficiency and finance
Autori
Yao, Fengge ; Qin, Zenan ; Wang, Xiaomei ; Chen, Mengyao ; Noor, Adeeb ; Sharma, Shubham ; Singh, Jagpreet ; Kozak, Dražan ; Hunjet, Anica
Izvornik
Heliyon (2405-8440) 9
(2023), 5;
E16160, 15
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Artificial intelligence ; Energy efficiency financing ; Renewable energy ; G7 economies
Sažetak
The development of a country is inseparable from the material guarantee mainly based on energy, but energy is limited, which may restrict the sustainable development of the country. It is very necessary to accelerate the adoption of programs aimed at switching non-renewable energy sources to ones that are, and giving priority to improving renewable energy consumption and storage capabilities. From the experience of the G7 economies, the development of renewable energy (RE) is inevitable and urgent. The China Banking Regulatory Commission has recently issued a number of directives, such as the “Directives for Green Credit” and “Instructions for Granting Credit to Support Energy Conservation and Emission Reduction, ” to help businesses that use “renewable energy expand”. This article firstly discussed the definition of the “green institutional environment” (GIE) and the construction of the index system. Then, on the basis of clarifying the relationship between the GIE, and RE investment theory, a semi-parametric regression model was constructed to empirically analyze the mode and effect of the GIE. Considering the balance between improving model accuracy and reducing computational complexity, the number of hidden nodes opted in this study is 300 so as to lower the time needed to predict the model. Finally, from the perspective of enterprise scale, the level of GIE played a significant role in promoting RE investment in small and medium-sized enterprises, with a coefficient of 1.8276, while the impact on RE investment in large enterprises had not passed the significance test. Based on the conclusions, the government should focus on building a GIE dominated by green regulatory systems, supplemented by green disclosure and supervision systems, and green accounting systems, and should make reasonable plans for releasing various policy directives. At the same time, while offering full play to the guiding role of the policy, its rationality should also be paid attention to, and the excessive implementation of the policy should be avoided, so that an orderly, and good GIE can be created.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo, Ekonomija
POVEZANOST RADA
Projekti:
UNIN--UNIN-DRUŠ-21-1-2 - Digitalno poslovanje (Hunjet, Anica, UNIN ) ( CroRIS)
UNIN--UNIN-DRUŠ-22-1-6 - Važnost znanja u modernom društvu (Hunjet, Anica, UNIN ) ( CroRIS)
Ustanove:
Strojarski fakultet, Slavonski Brod,
Sveučilište Sjever, Koprivnica,
Sveučilište u Slavonskom Brodu
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus