Multicriteria panel-data directional distances and the efficiency measurement of multidimensional higher education systems

Thyago C.C. Nepomuceno, Tommaso Agasisti, Alice Bertoletti and Cinzia Daraio

Omega, 2024, vol. 125, issue C

Abstract: In this paper, we introduce the notion of multicriteria-based directional distance determination for estimating the efficiency of decision units under different (and sometimes conflicting) interests and objectives. Different objectives are interpreted as different dimensions of a production system. Multidimensional industries, such as the Higher Education system, usually have clear preference structures and value judgments over teaching, research and service (outreach), leading to ranking differences for countries and organizations based on policy perspectives, production compensations, substitutions or complementation. We develop this framework based on the non-compensatory reasoning of outranking multicriteria methods to determine the most practical directional vector for the output expansion of Higher Education and support a multidimensional efficiency measurement. The numerical application using panel data illustrates policy-directed European countries based on the three dimensions of higher education. A similar understanding can be extended for determining directional efficiency for service units based on other multicriteria methods and heuristics.

Keywords: Data envelopment analysis; DEA; Multicriteria decision analysis; MCDA; Directional distance functions; DDF; Economics of education; Higher education systems; Government policy; Europe (search for similar items in EconPapers)
JEL-codes: C44 H52 I2 I23 I28 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.omega.2024.103044

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