Latent Information in the Evolving Energy Structure DOI Open Access
Boqiang Lin, Yitong Zhu

Journal of Global Information Management, Год журнала: 2024, Номер 32(1), С. 1 - 21

Опубликована: Ноя. 10, 2024

Recent studies indicate that Artificial Intelligence (AI) technology, characterized by its integration of information and communication technology attributes, exerts a multifaceted influence on the energy system. The authors employ Difference-in-Differences (DID) Triple-Difference (DDD) models to investigate effects AI. research initially demonstrates AI may exhibit dual attributes constraining structure. Specifically, rapid development tends increase proportion fossil fuel-based electricity generation while optimizing consumption renewable energy. Furthermore, degradation structure stems from surge in AI, which capacity is unable satisfy. Lastly, industrial agglomeration construction digital economy have positive impacts energy; technological innovation aids mitigating negative shocks This study provides new perspective role transition.

Язык: Английский

The impact of renewable energy policies on the energy transition -– An empirical analysis of Chinese cities DOI
Chien‐Chiang Lee,

Tianhui Wang

Energy Economics, Год журнала: 2024, Номер 138, С. 107838 - 107838

Опубликована: Авг. 22, 2024

Язык: Английский

Процитировано

22

Industry 4.0 digital technologies for the advancement of renewable energy: Functions, applications, potential and challenges DOI Creative Commons
Ghinwa Naeem, Mohammad Asif, Muhammad Khalid

и другие.

Energy Conversion and Management X, Год журнала: 2024, Номер unknown, С. 100779 - 100779

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

7

Dynamic connectedness of quantum computing, artificial intelligence, and big data stocks on renewable and sustainable energy DOI
حسن حیدری, Sami Ben Jabeur, Hela Nammouri

и другие.

Energy Economics, Год журнала: 2024, Номер unknown, С. 108017 - 108017

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

4

How does artificial intelligence affect manufacturing firms' energy intensity? DOI Creative Commons
Hongyu Li, Zhiqiang Lu, Zhengping Zhang

и другие.

Energy Economics, Год журнала: 2024, Номер unknown, С. 108109 - 108109

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

4

Unleashing the Power of AI DOI

Arzu Alvan,

Sina Kısacık, Nalan GELİRLİ

и другие.

Advances in finance, accounting, and economics book series, Год журнала: 2025, Номер unknown, С. 45 - 64

Опубликована: Янв. 14, 2025

Artificial intelligence (AI) is a powerful force that reshaping multiple sectors of the economy, including energy industry. Its ability to analyze vast amounts data and make quick decisions has potential revolutionize landscape. However, this transformation also brings about concept creative destruction, where new technologies innovations replace existing ones, leading both economic growth disruption in established industries. The fusion AI destruction sector presents challenges opportunities for businesses policymakers alike. Along with this, it aims provide framework understand significant role causing radical changes various sectors, resource distribution, production, security, consumption, related business areas. As continues advance, expected have an increasing impact on pave way more sustainable efficient future.

Язык: Английский

Процитировано

0

Artificial Intelligence in Energy Economics Research: A Bibliometric Review DOI Creative Commons
Zhilun Jiao, Chenrui Zhang,

Wenwen Li

и другие.

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

0

Electricity generation from renewable and non-renewable energy sources in China: The role of environmental policy stringency, FDI, and economic growth DOI

Cpc Hunan,

Daniel Balsalobre‐Lorente, Qasim Raza Syed

и другие.

Energy, Год журнала: 2025, Номер unknown, С. 134695 - 134695

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Impact of geopolitical risks and innovation on global defense stock return DOI Creative Commons
Oana Panazan, Cătălin Gheorghe

PLoS ONE, Год журнала: 2025, Номер 20(2), С. e0312155 - e0312155

Опубликована: Фев. 21, 2025

This study conducts a comparative analysis of how geopolitical risk (GPR) and innovation impact stock returns in the defense industry based on data from 75 companies across 17 countries 4 continents. With daily datasets spanning January 1, 2014 to March 29, 2024, wavelet coherence phase differences were used conduct analysis. The results revealed that had greater more pronounced during entire period compared with influence GPR events. GPRs exerted an uneven heterogeneous global stocks concentrated events generated uncertainty. Overall, we found significant time-varying dependence large number at different time frequencies. COVID-19 pandemic did not have major industry. Further, led increased volatility Russia–Ukraine war, leading In addition dominant role they play world market, US served as robust hedge, especially 2021 2022. Defense UK are sensitive both innovation, followed by Germany France. Comparative scalograms China reveals Thus, diversification opportunities been extended China, offering investors promising way capitalize refuge periods disruption. To mitigate rearmament trend, suggest alternative investment for horizons.

Язык: Английский

Процитировано

0

Artificial Intelligence and Energy Market Quartile Spillovers: Implications for China's Renewable Energy and High Emission Sectors DOI

Zhengyu Ren,

Yujie Chen,

Shi-Jie Ma

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Energy diversification, financial development and economic development: an examination of convergence in OECD countries DOI Creative Commons
Thanh Nguyen, Son Nghiem, Anh‐Tuan Doan

и другие.

China Finance Review International, Год журнала: 2025, Номер unknown

Опубликована: Март 3, 2025

Purpose This study examines the convergence of energy diversification, financial development and per-capita income in OECD countries. Design/methodology/approach The research employs club test to assess among countries uses Granger causality tests panel regressions identify determinants convergence, using data from 1997 2021. Findings showed no overall but revealed clubs for each factor. indicated short-run bi-directional relationships between variables. Long-run regression analysis confirmed that technological progress significantly improves per capita diversification. Additionally, it diversification development, a uni-directional relationship U-shaped effect on with turning point at $67,112.8 year. Practical implications findings suggest within club, implementing microeconomic incentives technology diffusion energy, production services could help lagging catch up. Originality/value pioneers testing identifies this convergence.

Язык: Английский

Процитировано

0