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Do diverse degree courses matter for university attractiveness?

Author

Listed:
  • Bianca Biagi

    (UNISS - Università degli Studi di Sassari = University of Sassari [Sassari])

  • Laura Ciucci

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Claudio Detotto

    (LISA - Laboratoire « Lieux, Identités, eSpaces, Activités » (UMR CNRS 6240 LISA) - CNRS - Centre National de la Recherche Scientifique - Università di Corsica Pasquale Paoli [Université de Corse Pascal Paoli])

  • Manuela Pulina

    (CRENoS, Sassari)

Abstract

The present paper focuses on an unexplored line of research in Higher Education Institutions' (HEIs) studies: the role of programmatic diversity on university attractiveness. Specifically, it highlights the role of diversification and divergence of the degree courses as a lever to attract more freshers. Diversification measures the range of the offered degree courses, while divergence indicates how the mix differs from the national standard. The work addresses the following three research questions: (1) are diversification and divergence beneficial to universities in attracting more freshers? Do these effects change with (2) the internal characteristics and (3) the external characteristics of universities? To this aim, the paper explores a panel data set of 75 Italian universities between 2012–2019. Overall, the findings indicate that programmatic diversity is beneficial but with specific differences according to size, research quality and the location of the HEIs. Furthermore, the proximity to other competitors plays an important role.

Suggested Citation

  • Bianca Biagi & Laura Ciucci & Claudio Detotto & Manuela Pulina, 2023. "Do diverse degree courses matter for university attractiveness?," Post-Print hal-04542142, HAL.
    • Handle: RePEc:hal:journl:hal-04542142
    DOI: 10.1007/s00168-023-01240-3
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    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

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