Renewable energy and sustainable development goals: Insights from latent dirichlet allocation thematic and bibliometric analysis

Abstract

This research conducts a comprehensive analysis of the intricate relationship between renewable energy and the sustainable development goals (SDGs). Employing diverse methodologies including latent dirichlet allocation (LDA) topic modeling, bibliometrics, citation analysis, and regression modeling, the study explores the evolving landscape of renewable energy research and its implications for SDGs. The analysis identifies a pronounced scholarly interest in renewable energy, reflected in the escalating publication volumes and citations across environmental sciences, green technology, and energy studies. Through meticulous examination, it uncovers interconnected research themes; encompassing policy uncertainty, Environmental Kuznets Curve, and ecological footprint, elucidating the multifaceted impact of renewable energy on the SDGs. Geographical distributions underscore diverse regional focuses, emphasizing the need for nuanced, context‐specific approaches. Regression analysis highlights influential factors like carbon dioxide emissions and gross domestic product (GDP) growth, delineating their pivotal roles in shaping scholarly attention toward renewable energy research. Furthermore, the study delves into the economic, environmental, and social dimensions of renewable energy's influence. It reveals its contributions to employment generation, sustainable production, energy access, and infrastructure development while navigating challenges related to climate change mitigation and biodiversity conservation. This comprehensive investigation offers crucial insights into the complex interplay between renewable energy and the SDGs. It predicts future research directions and highlights the urgency for interdisciplinary collaboration, international cooperation, and policy innovations to harness renewable energy's transformative potential for global sustainable development.