The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Translating Sustainable Development Goal (SDG) Interdependencies into Policy Advice
Open accessAbstract
The 17 Sustainable Development Goals (SDGs) of the 2030 Agenda, and their 169 targets, are interdependent and interlinked. The successful implementation of all SDGs will rely upon disentangling complex interactions between the goals and their targets. This implies that implementing the SDGs requires cross-sectoral processes to foster policy coherence. Over recent years, academic research has produced a number of different proposals for categorizing the SDGs, systematically mapping the linkages between them, and identifying the nature of their interdependencies. The aim of this review article is to provide ideas of how to move from generic appraisals of SDG interdependencies towards translating these interdependencies into policy action. To do so, the article first provides an overview of existing frameworks for the systematic conceptualization of the SDGs and the interlinkages and interdependencies between them. Secondly, the article critically discusses advantages and limitations of these frameworks, with a particular focus on methodological weaknesses, practical applicability to specific contexts, and utility for the development of policy strategies for coherent SDG planning and implementation. Based on this discussion, the article proposes a roadmap for how research on interdependencies can meaningfully provide orientation for policy action.
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Cited by
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Metadata
- Authors
- Breuer, A., Janetschek, H., & Malerba, D.
- Venue
- Sustainability
- Publisher
- MDPI AG
- Published
- 2019-04-08
- Volume
- 11
- Issue
- 7
- Pages
- 2092
- ISSN
- 2071-1050 (ISSN-L)
- OpenAlex
- W2928452017
- Cited by
- 353
- References
- 38
- FWCI
- 88.36
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
