Finance research letters, Год журнала: 2024, Номер 72, С. 106617 - 106617
Опубликована: Дек. 11, 2024
Язык: Английский
Finance research letters, Год журнала: 2024, Номер 72, С. 106617 - 106617
Опубликована: Дек. 11, 2024
Язык: Английский
Nano Research, Год журнала: 2024, Номер 17(6), С. 4797 - 4806
Опубликована: Фев. 7, 2024
Язык: Английский
Процитировано
75Energy Economics, Год журнала: 2024, Номер 131, С. 107401 - 107401
Опубликована: Фев. 15, 2024
Язык: Английский
Процитировано
22Australasian Marketing Journal (AMJ), Год журнала: 2024, Номер unknown
Опубликована: Авг. 1, 2024
In an era of data-driven decision-making, a comprehensive understanding quantitative research is indispensable. Current guides often provide fragmented insights, failing to offer holistic view, while more sources remain lengthy and less accessible, hindered by physical proprietary barriers. This gap underscores the urgent need for clear, accessible guide that demystifies research, necessity not just academic rigor but practical application. Against this backdrop, offers overview elucidating its core motivations, defining characteristics, methodological considerations. The necessity, importance, relevance, urgency are articulated, establishing strong foundation subsequent discussion, which delineates scope, objectivity, goals, data, methods distinguish alongside balanced inspection strengths shortcomings, particularly in terms data collection analysis. also addresses various design considerations, ranging from choice between primary secondary cross-sectional longitudinal studies, experimental non-experimental designs. crucial role pretesting piloting instruments underscored, with discussion focal areas, participant selection. Data considerations examined, covering sampling approaches, sample size determination, resource maximization strategies, as well preparation techniques including handling missing managing outliers, standardizing variables, verifying assumptions. further delves into analysis spotlighting assessment psychometric properties, diverse analytical essential robustness checks. concludes demystifying hypothesis testing process, detailing formulation null alternative hypotheses, interpretation statistical significance, issue Type I, II, III, IV errors. Therefore, serves valuable compass researchers seeking navigate multifaceted aspects ensuring rigorous, reliable, valid scientific inquiry.
Язык: Английский
Процитировано
17Journal of Economic Surveys, Год журнала: 2025, Номер unknown
Опубликована: Янв. 21, 2025
ABSTRACT Integrating solar energy into power grids is essential for advancing a low‐carbon economy, but accurate forecasting remains challenging due to output variability. This study comprehensively reviews models, focusing on how Artificial Intelligence (AI) and Machine Learning (ML) enhance forecast accuracy. It examines the current landscape of forecasting, identifies limitations in existing underscores need more adaptable approaches. The primary goals are analyze evolution AI/ML‐based assess their strengths weaknesses, propose structured methodology selecting implementing AI/ML models tailored forecasting. Through comparative analysis, evaluates individual hybrid across different scenarios, identifying under‐explored research areas. findings indicate significant improvements prediction accuracy through advancements, aiding grid management supporting transition. Ensemble methods, deep learning techniques, show great promise enhancing reliability. Combining diverse approaches with advanced techniques results reliable forecasts. suggests that improving model these integrated methods offers substantial opportunities further research, contributing global sustainability efforts, particularly UN SDGs 7 13, promoting economic growth minimal environmental impact.
Язык: Английский
Процитировано
1Energy Economics, Год журнала: 2024, Номер 131, С. 107359 - 107359
Опубликована: Фев. 1, 2024
Язык: Английский
Процитировано
6International Journal of Sustainable Development & World Ecology, Год журнала: 2024, Номер 31(8), С. 1128 - 1144
Опубликована: Авг. 22, 2024
Several existing studies show that macroeconomic uncertainties intensify global environmental and climate challenges, putting the globe at risk of not being able to achieve United Nations' Sustainable Development Goals by 2030. In this study, we provide evidence on role energy-related uncertainty in energy – environment dilemma between 1996 2021. We employ three distinct indicators load capacity factor (LCF), carbon dioxide emissions (CO2), ecological footprint (EFP) alongside a comprehensive index time-frequency-quantile methods based Wavelet Quantile Correlation, Cross-Quantilogram, Local Multiple Correlation with Dominance. The empirical results suggest negative strong nonlinear dependencies LCF across periods quantiles. further has positive dependences only CO2 but also EFP various vary quantiles, stronger dependency structures long run. These findings underscore substantial influence contemporary challenges. governments policymakers need reshape policy directives toward mitigating effects uncertainties.
Язык: Английский
Процитировано
6Journal of International Money and Finance, Год журнала: 2024, Номер 151, С. 103251 - 103251
Опубликована: Дек. 11, 2024
Язык: Английский
Процитировано
6Natural Resources Forum, Год журнала: 2023, Номер unknown
Опубликована: Дек. 13, 2023
Abstract Following The Paris Agreement and United Nations Sustainable Development Goals (SDGs), a significant number of nations globally have pledged to achieve net‐zero emissions by 2050. goal is lower while emphasizing economically socially sustainable practices. To meet these development targets, some countries introduced industry‐specific roadmaps, showing how can systematically allocate resources attain net zero, which includes balancing energy production needs with existing sources. Such transformation will inevitably encounter obstacles, particularly in reducing reliance on non‐renewable fuels mitigating emissions. This study focuses identifying impediments achieving economy. Utilizing the novel concept plithogenic sets, examines interdependent relationships among various barriers, providing insights into navigating constraints. findings reveal external, economic, policy framework obstacles their subsequent impact organizational technological challenges that must be surmounted reach status.
Язык: Английский
Процитировано
14International Review of Financial Analysis, Год журнала: 2024, Номер 93, С. 103114 - 103114
Опубликована: Фев. 13, 2024
Язык: Английский
Процитировано
5Technological Forecasting and Social Change, Год журнала: 2025, Номер 216, С. 124133 - 124133
Опубликована: Апрель 12, 2025
Язык: Английский
Процитировано
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