Nonparametric efficiency measurement of undergraduate teaching by university size
Metadata
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Salas Velasco, ManuelEditorial
Springer Nature
Materia
Cluster analysis Data envelopment analysis Meta-frontier frameworks
Date
2024-02-19Referencia bibliográfica
Salas-Velasco, M. Nonparametric efficiency measurement of undergraduate teaching by university size. Oper Res Int J 24, 9 (2024). https://doi.org/10.1007/s12351-024-00816-x
Sponsorship
Funding for open access charge: Universidad de Granada / CBUAAbstract
Conventional data envelopment analysis (DEA) models assume that all decisionmaking
units (DMUs) are homogenous. While higher education institutions (HEIs)
of very different sizes challenge the homogeneity of DMUs, DEA studies have paid
relatively little attention to university size when assessing the performance of HEIs.
This article proposes novel, effective methods for evaluating university performance
and identifying useful benchmarks for improving the operations of inefficient performers.
Specifically, DEA and cluster analysis (CA) are applied for the evaluation
of the performance of traditional Spanish public universities. DEA is utilized to
examine the relative performance of these universities in terms of undergraduate
teaching output. CA is applied to find similar-in-scale universities prior to the DEA
to facilitate peer-groupings. The advantage of this method is that when DMUs are
clustered based on their size, one can obtain homogenous groups of units with comparable
operating environments. Furthermore, using the meta-frontier framework,
this research finds significant evidence that there is an efficiency advantage for
medium- and large-sized universities over small ones in providing undergraduate
teaching. A bootstrapped, non-parametric meta-frontier approach also verifies this
latter result. Some of the factors that contribute to the differences in the relative
efficiencies are identified as well.