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Segmentation of OECD countries on the basis of selected global environmental indicators using k-means non-hierarchical clustering

  • Energy, Environment and Green Technologies for the Future Sustainability
  • Published:
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Abstract

In order to allocate resources and describe progress, frequently nations are grouped together by many international authorities. A variety of pertinent indicators can provide a more useful basis for classification for each specific area of interest. Based on commonalities between various variables connected to the global environmental sector, we developed a novel typology of country clusters. Four indicators were chosen after a review of the literature. In order to optimize data availability across as many OECD nations as feasible, indicators were chosen based on their relevance for all the OECD countries. Countries were arranged into a natural cluster using the hierarchical clustering method. Four groups, covering 31 countries, were the result of two stages of grouping. These four clusters were found to be more compact and clearly divided which gives policymakers a clear-cut idea as to how these environmental indicators are deteriorating day by day and year by year and what needs to be done to be more environmentally sustainable and responsible.

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Data availability

The datasets generated and analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

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Acknowledgements

The authors would like to express their sincere gratitude towards the management of Dr. D.Y. Patil Institute of Management Studies, Manipal University Jaipur, and Poornima Group of Colleges for their incredible support provided for the research.

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Authors and Affiliations

  1. Balaji Institute of International Business (BIIB), Sri Balaji University, Pune, Maharashtra, India

    Pallavi Kudal

  2. Dr. D.Y. Patil Institute of Management Studies, Pune, Maharashtra, India

    Amitabh Patnaik

  3. Faculty of Management & Commerce, Manipal University Jaipur, Jaipur, Rajasthan, India

    Sunny Dawar

  4. Poornima College of Engineering, Jaipur, Rajasthan, India

    Raj Kumar Satankar

  5. Poornima Group of Colleges, Jaipur, Rajasthan, India

    Prince Dawar

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  1. Pallavi Kudal
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Contributions

Conceptualization: Pallavi Kudal and Amitabh Patnaik. Methodology: Raj Kumar Satankar, Sunny Dawar, and Prince Dawar. Data curation: Pallavi Kudal, Amitabh Patnaik, and Raj Kumar Satankar. Writing—original draft preparation: Pallavi Kudal and Sunny Dawar. Writing—reviewing and editing: Pallavi Kudal, Amitabh Patnaik, Raj Kumar Satankar, Sunny Dawar, and Prince Dawar. Supervision: Raj Kumar Satankar and Prince Dawar. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

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Correspondence to Sunny Dawar.

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Table 2 List of OECD countries considered for analysis
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Kudal, P., Patnaik, A., Dawar, S. et al. Segmentation of OECD countries on the basis of selected global environmental indicators using k-means non-hierarchical clustering. Environ Sci Pollut Res 31, 10334–10345 (2024). https://doi.org/10.1007/s11356-023-26679-x

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