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Decision-making fitness of methods to understand Sustainable Development Goal interactions

Nature Sustainability volume 5, pages 131–138 (2022)Cite this article

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Abstract

The integrated nature of the Sustainable Development Goals (SDGs) presents a challenge to implementing the 2030 Agenda. Analytical methods to support decision-makers are often developed without explicitly incorporating decision-makers’ views and experience. Here, we investigate whether existing methods are fit-for-purpose in supporting decision-makers at national and subnational levels. We identify prominent methods for SDG interaction analysis, which we then evaluate by engaging directly (via a survey and interviews) with method developers and decision-makers in Sweden. We find that decision-makers prioritize methods that are simple and flexible to apply and able to provide directly actionable and understandable results. They are less concerned with the accuracy, precision, completeness or quantitative nature of the knowledge. Prominent categories of methods include self-assessment, expert judgement, literature-based, statistical analyses and modelling. Interviewed decision-makers consider these methods in line with the features prioritized in the survey but highlight low performance on features they value highly, such as the extent to which results are actionable and overall ease of use. Methods developers have limited awareness of decision-makers’ priorities and requirements, so hindering methodological advancement. They should focus on the practical value of applications to support decision-makers, resource-constrained organizations and those seeking to evaluate multiple cases.

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Fig. 1: Methodological approaches to analysing SDG synergies and trade-offs in the scientific literature.
Fig. 2: Citation networks of the categories of prominent methods identified in the scientific literature.
Fig. 3: Developers’ and decision-makers’ views on the performance of methodological approaches to SDG interaction analysis.

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Data availability

Data of the review of the literature and practice of SDG interaction research are available in the Supplementary Data and the source data for Fig. 1. Source data are provided with this paper. Additional data are available from the corresponding author on reasonable request.

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Acknowledgements

We thank all who collaborated with us on the data collection. We acknowledge the representative of Sweden’s national coordinator for the 2030 Agenda for the support with the engagement of decision-makers. This research was funded by NERC grant no. NE/S012834/1 (L.D. and R.S.) and Formas grant no. 2019-00040 (L.D. and J.K.) under the research initiative Towards a Sustainable Earth: Environment–Human Systems and the UN Global Goals.

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Authors and Affiliations

  1. Centre for Environmental Policy, Imperial College London, London, UK

    Lorenzo Di Lucia & Raphael Slade

  2. Department of Space, Earth and Environment, Physical Resource Theory, Chalmers University of Technology, Gothenburg, Sweden

    Lorenzo Di Lucia

  3. Department of Technology and Society, Environmental and Energy Systems Studies, Faculty of Engineering, Lund University, Lund, Sweden

    Jamil Khan

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  1. Lorenzo Di Lucia
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Contributions

L.D., R.S. and J.K. designed the research. L.D. collected and analysed the data and was the primary writer. All authors edited the manuscript.

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Correspondence to Lorenzo Di Lucia.

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The authors declare no competing interests.

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Peer review information Nature Sustainability thanks Francesco Fuso Nerini and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Sections 1–5, Figs. 1–7 and Tables 1–7.

Reporting Summary

Supplementary Data

Results of the search of methods in the practice of SDG decision-making.

Source data

Source Data Fig. 1

Published records identified in the scientific literature.

Source Data Fig. 2

Citation networks of prominent methods identified in the scientific literature.

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Di Lucia, L., Slade, R. & Khan, J. Decision-making fitness of methods to understand Sustainable Development Goal interactions. Nat Sustain 5, 131–138 (2022). https://doi.org/10.1038/s41893-021-00819-y

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