Degrowth vs. Green Growth. A computational review and interdisciplinary research agenda

ECOLOGICAL ECONOMICS(2024)

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摘要
The concepts of Green Growth and Degrowth represent two major narratives in the public and academic debate on socio-ecological transformation. Using a computational literature review based on the Latent Dirichlet Allocation algorithm, we systematically review 1449 journal articles on Green Growth and Degrowth published between 1972 and 2020. Based on a comprehensive full-text analysis, we uncover the hidden topic structure in the literature and identify a total of 50 topics. Using a comparative analysis of the two research fields, we confirm several findings from previous reviews, including that Green Growth research is highly policy oriented, focuses on practical implementation and builds on empirical research methods, while Degrowth research is highly theory-driven, focuses on the analysis of complex human-nature interrelationships and builds on a sound theoretical and conceptual foundation. Our analysis further reveals that Green Growth and Degrowth are two rather isolated fields of research with little exchange and mutual reference on related topics. However, the topic of social change and transition represents an intersecting and promising future research area. We derive four generalizable recommendations that address current shortcomings and interdisciplinary potentials of Degrowth and Green Growth research and contribute to shaping the future of social-ecological transformation research.
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关键词
Degrowth,Green growth,Research agenda,Topic modeling,Computational review
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