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1 Horvath, S.- M.; Muhr, M. M.; Kirchner, M.; Toth, W.; Germann, V.; Hundscheid, L.; Vacik, H.; Scherz, M.; Kreiner, H.; Fehr, F.; Borgwardt, F.; Guhnemann, A.; Becsi, B.; Schneeberger, A.; Gratzer, G. 2022. Handling a complex agenda: a review and assessment of methods to analyse SDG entity interactions. Environmental Science and Policy, 131:160-176. (Online first) [doi: https://doi.org/10.1016/j.envsci.2022.01.021]
Sustainable Development Goals ; Assessment ; Interactions ; Indicators ; Synergism ; Policy coherence ; Statistical methods ; Collaboration ; Models ; Network analysis
(Location: IWMI HQ Call no: e-copy only Record No: H050937)
https://www.sciencedirect.com/science/article/pii/S1462901122000351/pdfft?md5=092037f5be9c77a2b4475bab596c75c6&pid=1-s2.0-S1462901122000351-main.pdf
https://vlibrary.iwmi.org/pdf/H050937.pdf
https://vlibrary.iwmi.org/pdf/H050937.pdf
(2.78 MB) (2.78 MB)
The interlinked character of the 2030 Agenda poses both a challenge and an opportunity in terms of coherent policy making. Accordingly, different methods have been used in approaching the interactions between SDG entities (goals, targets, indicators, policies, external entities) in several recent publications.
In this paper, we provide a review and assessment of methods used for analysing SDG entity interactions. Specifically, we assess the suitability of these methods for addressing policy coherence at different levels and from different perspectives.
A total of 30 methods are categorised into argumentative, literature, linguistic, simulation, statistical, and other quantitative methods and are examined with expert elicitation applying a range of criteria on the basis of the following factors: the ability to give detailed information about effects between SDG entities, practicability, sensitivity to interdisciplinarity, and collaboration and systems thinking.
No single method, category, or research tradition (i.e. quantitative or qualitative) can be regarded as the most suitable for analysing SDG entity interactions. Quantitative methods (i.e. statistical, simulation, and other quantitative) are most frequently applied in the scientific context, although assessment results suggest that argumentative methods are particularly useful for obtaining information about effects while enabling interdisciplinarity and collaboration. In contrast, literature, linguistic, and quantitative methods can not be used to process different kinds of information. However, regarding the effort required, quantitative methods (except simulation methods) seem to require fewer resources. Although argumentative methods are evaluated best overall in our assessment, different implementation contexts and the importance assigned to the criteria may justify the application of most other methods as well.
In this paper, we provide a review and assessment of methods used for analysing SDG entity interactions. Specifically, we assess the suitability of these methods for addressing policy coherence at different levels and from different perspectives.
A total of 30 methods are categorised into argumentative, literature, linguistic, simulation, statistical, and other quantitative methods and are examined with expert elicitation applying a range of criteria on the basis of the following factors: the ability to give detailed information about effects between SDG entities, practicability, sensitivity to interdisciplinarity, and collaboration and systems thinking.
No single method, category, or research tradition (i.e. quantitative or qualitative) can be regarded as the most suitable for analysing SDG entity interactions. Quantitative methods (i.e. statistical, simulation, and other quantitative) are most frequently applied in the scientific context, although assessment results suggest that argumentative methods are particularly useful for obtaining information about effects while enabling interdisciplinarity and collaboration. In contrast, literature, linguistic, and quantitative methods can not be used to process different kinds of information. However, regarding the effort required, quantitative methods (except simulation methods) seem to require fewer resources. Although argumentative methods are evaluated best overall in our assessment, different implementation contexts and the importance assigned to the criteria may justify the application of most other methods as well.
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