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Π1.5 Y. Smirlis, D. Sotiros, D. K. Despotis, G. Koronakos (2013). Evaluation of research activity in higher education: A Data Envelopment Analysis approach. 2nd International Symposium and 24th National Conference on Operational Research, Athens, 26-28 Se

Abstract


Academic research is considered as one of the most important activities of academic
stuff in Higher Education. The extent and the quality of the research records are
determinants of the academic profiles and play, or they should play, a key role in the
advancement of the academic stuff members. As the research activity of a University
department is strictly determined by the research activity of its members, quality
individual research outcomes improve the recognition of the University department
and affect its position in international academic rankings.


In this paper we develop a Data Envelopment Analysis (DEA) assessment
framework to evaluate the research activity of individuals in comparable University
departments. The selected factors (inputs and outputs) have a meaningful
interpretation in the analysis and, moreover, provide us the ability to perform the
assessments by taking into account both the extent as well as the quality of the
research records. We take as inputs the duration of the research activity, the funds
received (in monetary values) and the teaching load (adjusted average). We take as
outputs the number of publications in journals ranked as A+ or A, the number of
publications in journals ranked as B or C, the publications in unranked journals,
publications in conferences, the number of research programs in which the researcher
participates and the number of citations (excluding self-citations). We draw the
journal rankings from the Excellence in Research for Australia (ERA) 2010 journal
classification system. The data are drawn from Scopus, Google Scholar, university
personal records and CVs. To facilitate the incorporation of a quality aspect in our
assessments, we use a piece-wise linear variant of the DEA model with assurance
region constraints. For example, assuming convex value functions for the publications
in highly ranked journals and concave value functions for the publications in
unranked journals, we reward the quality research records while diminishing the
contribution of extensive publications in non-quality journals in the overall research
performance. We illustrate our assessment approach with anonymous data and we
provide a meaningful interpretation of the results.

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