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Who Leads, What Matters? Machine Learning and the Complexity of University Performance

Author

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  • María Teresa Ballestar
  • Kathrin Komp-Leukkunen
  • Jorge Malfeito-Gaviro
  • Alejandra Ramos
  • Jorge Sainz

Abstract

The role of leadership in public institutions, particularly universities, is often linked to goal-setting and decision-making processes that impact efficiency. In Spain, public university rectors are directly elected by academics, staff, and students, offering a unique context for studying leadership influence. This study uses a unique database to analyze Spanish public universities across five categories: academic and research performance, social objectives, internationalization, university characteristics, and rector profiles. Using a K-Means unsupervised machine learning algorithm, we identify five distinct clusters of Spanish public universities, each characterised by a specific combination of institutional performance indicators and management characteristics.

Suggested Citation

  • María Teresa Ballestar & Kathrin Komp-Leukkunen & Jorge Malfeito-Gaviro & Alejandra Ramos & Jorge Sainz, 2026. "Who Leads, What Matters? Machine Learning and the Complexity of University Performance," PLOS ONE, Public Library of Science, vol. 21(5), pages 1-13, May.
    • Handle: RePEc:plo:pone00:0349287
    DOI: 10.1371/journal.pone.0349287
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