Опубликована: Янв. 1, 2024
Язык: Английский
Опубликована: Янв. 1, 2024
Язык: Английский
Energies, Год журнала: 2025, Номер 18(2), С. 434 - 434
Опубликована: Янв. 20, 2025
Artificial intelligence (AI) is gaining attention in energy economics due to its ability process large-scale data as well make non-linear predictions and providing new development opportunities research subjects for research. The aim of this paper explore the trends application AI over decade spanning 2014–2024 through a systematic literature review, bibliometrics, network analysis. analysis shows that prominent themes are price forecasting, innovations systems, socio-economic impacts, transition, climate change. Potential future directions include supply-chain resilience security, social acceptance public participation, economic inequality technology gap, automated methods policy assessment, circular economy, digital economy. This innovative study contributes understanding from perspective bibliometrics inspires researchers think comprehensively about challenges hotspots.
Язык: Английский
Процитировано
0Applied Economics, Год журнала: 2025, Номер unknown, С. 1 - 17
Опубликована: Март 17, 2025
Язык: Английский
Процитировано
0Energy Economics, Год журнала: 2025, Номер unknown, С. 108450 - 108450
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
0Energy Economics, Год журнала: 2024, Номер 139, С. 107906 - 107906
Опубликована: Сен. 10, 2024
Язык: Английский
Процитировано
1Advances in finance, accounting, and economics book series, Год журнала: 2024, Номер unknown, С. 61 - 98
Опубликована: Окт. 3, 2024
The volatilities observed in different markets have an impact on global inflation. persistent upward trend inflation forms the basis of economic challenges experienced all countries.Therefore, especially considering recent developments and events, stands out as one most researched topics. In this contextthis, study analyzes relationship between inflation, food price, Brend oil energy prices, supply chain, geopolitical risks variables using monthly data from 2004:08 to 2023:10. analysis, Dynamic Wavelet Correlation Analysis For Multivariate (WLMC) approach is employed examine dynamic correlation across time frequency dimensions. Considering findings study, it can be stated that strong relationships among been found after year 2021 analyses. This suggests a stronger integration markets, years.
Язык: Английский
Процитировано
0Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
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