Unveiling the nexus of institutional quality and renewable energy utilizing a Topic Modelling approach

This paper explores the complex relationship between institutional quality and renewable energy adoption within the context of global efforts to mitigate environmental challenges and reduce dependence on non- renewable energy sources. Despite the essential role of institutions in facilitating the transition to renewable energy, systematic research on this relationship remains scarce. This study addresses this gap by being the first to apply Topic Modelling (Latent Dirichlet Allocation – LDA) to systematically analyze the literature, offering a data-driven alternative to conventional reviews and minimizing subjective bias. We hypothesize that the interaction between institutional quality and renewable energy is multifaceted, with key areas influencing each other in an interconnected manner. To test this, we apply LDA to analyze 570 academic documents published from 1998 to 2024. The analysis identifies five prominent topics: Investments (17.2 %), Emissions (22.3 %), Finance (17.3 %), Environment (20.2 %), and Economic growth (23 %). Most documents exhibit a maximum probability of belonging to a topic within 25 %–35 %, with some reaching 40 %–50 %. Although a moderate negative correlation is observed between topics, overlapping themes and interconnections are discovered. By leveraging LDA, this study systematically categorizes and analyzes research trends, offering an objective and scalable method to uncover latent themes in the discourse on institutional quality and renewable energy. By exploring these interrelationships, this study offers valuable insights for future research and policy development, providing a robust foundation for advancing global sustainable energy transition.