Resources Policy, Год журнала: 2023, Номер 82, С. 103535 - 103535
Опубликована: Апрель 11, 2023
Язык: Английский
Resources Policy, Год журнала: 2023, Номер 82, С. 103535 - 103535
Опубликована: Апрель 11, 2023
Язык: Английский
Journal of Applied Economics, Год журнала: 2024, Номер 27(1)
Опубликована: Фев. 2, 2024
Green finance is one of the emerging research areas, particularly in academia and industries. However, its contribution to green growth remains relatively unexplored. Unlike previous studies, current contributes existing literature by using as a policy tool for achieving growth. The method moment quantile regression used investigate link between other control variables on 19 selected OECD economies from 1990 2021. main findings study support idea that accelerates countries. Similarly, results human capital show significantly positive relationship with Additionally, increase globalization GDP decrease To promote achieve sustainable environmental goals set economies, policymakers regulators must prioritize finance.
Язык: Английский
Процитировано
21Humanities and Social Sciences Communications, Год журнала: 2024, Номер 11(1)
Опубликована: Янв. 6, 2024
Abstract This study aimed to examine the impact of China’s political openness index and foreign direct investment on its ecotourism from 1985 2019. The findings revealed that a 1% rise in had long-term effect, increasing sustainable tourism by 0.01%. Furthermore, played significant role boosting China over both short long periods. A increase corresponded 0.32 0.53% term, respectively. Additionally, financial positive with improvement resulting approximately 0.24 0.23% increases index. Key policies advance eco-tourism include ensuring stability, enhancing green markets through fintech blockchain, implementing poverty alleviation measures.
Язык: Английский
Процитировано
19Energy Strategy Reviews, Год журнала: 2025, Номер 57, С. 101603 - 101603
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
3Resources Policy, Год журнала: 2023, Номер 87, С. 104315 - 104315
Опубликована: Ноя. 7, 2023
Язык: Английский
Процитировано
39Journal of Bionic Engineering, Год журнала: 2023, Номер 20(6), С. 2863 - 2895
Опубликована: Сен. 7, 2023
Язык: Английский
Процитировано
37Polymers, Год журнала: 2023, Номер 15(13), С. 2767 - 2767
Опубликована: Июнь 21, 2023
Over the last few years, researchers have shown a growing interest in polyvinyl chloride (PVC) gasification and conducted several studies to evaluate enhance process. These recognized that processing parameters crucial impact on assessment of PVC gasification. Despite this, there has been limited exploration use machine learning techniques, particularly regression models, optimize waste This study aims investigate effectiveness models as algorithms predicting performance The uses data collected through validated thermodynamic model, three different are tested compared detail. Cold gas efficiency normalized carbon dioxide emission predicted using linear, quadratic, quadratic with interaction algorithms. outcomes for reveal linear algorithm possesses high R-square value 97.49%, which indicates its strong predictive capability. Nevertheless, outperforms it, exhibiting an 99.81%. term, however, proves be best among them all, displaying perfect 99.90%. A similar observation is detected cold findings suggest term superior greater accuracy. research expected provide valuable insight into how can used maximize reduce associated environmental concerns.
Язык: Английский
Процитировано
29Resources Policy, Год журнала: 2023, Номер 83, С. 103616 - 103616
Опубликована: Апрель 27, 2023
Язык: Английский
Процитировано
27Resources Policy, Год журнала: 2023, Номер 85, С. 103991 - 103991
Опубликована: Июль 31, 2023
Язык: Английский
Процитировано
26Energies, Год журнала: 2023, Номер 16(16), С. 6053 - 6053
Опубликована: Авг. 18, 2023
The rising carbon dioxide emissions from the MENA region constitute a severe danger to environment, public health, and execution of United Nations SDGs. Substantial steps are required solve this problem maintain region’s sustainable future. Hence, current study focused on distinct factors, including renewable energy, energy intensity, green innovation, GDP, CO2 1990 2021. research determines multifarious variables in various quantiles, novel Method Moments Quantile Regression (MMQR) approach, Fully Modified Ordinary Least Square (FM-OLS), Dynamic (D-OLS) Driscoll-Kraay Standard Errors (DKS) applied. findings reveal that significantly reduces all while GDP lead lower, middle, upper quantiles. For robust outcome confirmed by FM-OLS, D-OLS, DKS methods. Also, Granger heterogeneous causality applied bidirectional among variables. study’s imply authorities should emphasize emergence innovation adopting energy-efficient technologies minimize accomplish SDGs 7, 9, 13 secure region.
Язык: Английский
Процитировано
25Resources Policy, Год журнала: 2024, Номер 90, С. 104724 - 104724
Опубликована: Янв. 28, 2024
Язык: Английский
Процитировано
15