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Clustering of Countries Through UMAP and K-Means: A Multidimensional Analysis of Development, Governance, and Logistics

Author

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  • Enrique Delahoz-Domínguez

    (Statistical and Quantitative Methods Research Group (GEMC), Universidad del Magdalena, Santa Marta 470004, Colombia)

  • Adel Mendoza-Mendoza

    (Industrial Engineering Program, Universidad del Atlántico, Barranquilla 080001, Colombia)

  • Delimiro Visbal-Cadavid

    (Industrial Engineering Program, Faculty of Engineering, Universidad del Magdalena, Santa Marta 470004, Colombia)

Abstract

Background : Growing disparities in development, governance, and logistics performance across countries pose challenges for global policymaking and Sustainable Development Goal (SDG) monitoring. This study proposes a classification of 137 countries based on multiple structural dimensions. The dataset for 2023 includes six components of the Logistics Performance Index (LPI), six dimensions of the Worldwide Governance Indicators (WGIs), and four proxies of the Human Development Index (HDI). Methods : The Uniform Manifold Approximation and Projection (UMAP) technique was used to reduce dimensionality and allow for meaningful clustering. Based on the reduced space, the K-means algorithm was employed to group countries with similar development characteristics. Results : The classification process allowed the identification of three distinct groups of countries, supported by a Hopkins statistic of 0.984 and an explained variance ratio of 87.3%. These groups exhibit structural differences in the quality of governance, logistics capacity, and social development conditions. Internal consistency checks and multivariate statistical analyses (ANOVA and MANOVA) confirmed the robustness and statistical significance of the clustering. Conclusions : The resulting classification offers a practical analytical tool for policymakers to design differentiated strategies aligned with national contexts. Furthermore, it provides a data-driven approach for comparative monitoring of the SDGs from an integrated and empirical perspective.

Suggested Citation

  • Enrique Delahoz-Domínguez & Adel Mendoza-Mendoza & Delimiro Visbal-Cadavid, 2025. "Clustering of Countries Through UMAP and K-Means: A Multidimensional Analysis of Development, Governance, and Logistics," Logistics, MDPI, vol. 9(3), pages 1-18, August.
  • Handle: RePEc:gam:jlogis:v:9:y:2025:i:3:p:108-:d:1719225
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    References listed on IDEAS

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    1. Lee, Chien-Chiang & Zhao, Ya-Nan, 2023. "Heterogeneity analysis of factors influencing CO2 emissions: The role of human capital, urbanization, and FDI," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    2. Yong Ae Ri & Chol Ryong Kang & Kuk Hyon Kim & Yong Myong Choe & Un Chol Han & Weifeng Pan, 2022. "A New Method to Determine Cluster Number Without Clustering for Every K Based on Ratio of Variance to Range in K-Means," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-14, July.
    3. Emon Kalyan Chowdhury & Rupam Chowdhury, 2024. "Role of Financial Inclusion in Human Development: Evidence from Bangladesh, India and Pakistan," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 3329-3354, March.
    4. Charrad, Malika & Ghazzali, Nadia & Boiteau, Véronique & Niknafs, Azam, 2014. "NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i06).
    5. Abraham Puente De La Vega Caceres & Estela Quispe Ramos & Carlos Samuel Ramos Meza, 2024. "Moderating the Effect of the Multidimensional Poverty Index on the Relationship between Sustainable Governance Indicators and Worldwide Governance Indicators," Sustainability, MDPI, vol. 16(7), pages 1-24, March.
    6. Rezaei, Jafar & van Roekel, Wilco S. & Tavasszy, Lori, 2018. "Measuring the relative importance of the logistics performance index indicators using Best Worst Method," Transport Policy, Elsevier, vol. 68(C), pages 158-169.
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