test Συγκριτική Αξιολόγηση παραγωγικών μονάδων απόφασης με την μέθοδο της Περιβάλλουσας Ανάλυσης Δεδομένων (Π.Α.Δ.): Παράδειγμα της μεθόδου σε ακαδημαϊκά τμήματα Α.Ε.Ι.|Hellenic Evaluation Society Review

Συγκριτική Αξιολόγηση παραγωγικών μονάδων απόφασης με την μέθοδο της Περιβάλλουσας Ανάλυσης Δεδομένων (Π.Α.Δ.): Παράδειγμα της μεθόδου σε ακαδημαϊκά τμήματα Α.Ε.Ι.

HES 15-16_25
Published: Nov 13, 2025
DOI: https://doi.org/10.12681/eea.43275
Keywords:
Περιβάλλουσα Ανάλυση Δεδομένων Οικονομική Αποδοτικότητα Αποδόσεις Κλίμακας Γραμμικός Προγραμματισμός Παραγωγικές Μονάδες Απόφασης
Hellenic Evaluation Society HES
Abstract

This article aims to present and analyze the method of Data Envelopment Analysis (DEA) as a method of comparative evaluation of the organizational units efficiency such as academic departments of tertiary education, hospitals, local government authorities, Public Benefit Corporations (PBCs). Law 4940/2022 refers to the Common Evaluation Framework as a method of self-evaluation of the organizational unit based on two segments criteria, which have a cause-effect relationship. The first five criteria determine the characteristics and features of the Unit (its structure and organization) and the remaining four determine and capture the effectiveness and efficiency of the operation of the specific Organization. The method of Data Envelopment Analysis (DEA) described in this article goes one step further on the grounds that the efficiency of the specific unit is evaluated and compared with the efficiency of similar units that are part of the so-called efficiency frontier (hull) (efficiency index ≅ 100%). The comparison of organizational units focuses on the quantity and quality of the resources utilized to produce results. Therefore, the main reference point of comparative evaluation focuses on the one hand on the process of measuring the performance of organizational units and on the other hand on the analysis of each unit's contribution to the overall efficiency of the system. Thus, good practice standards, evaluation indicators, and compliance actions can be defined for the implementation, in this case, of reforms, necessary structural changes, and the formulation of strategic options.

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References
Abd Aziz, N. A., Janor, R. M., & Mahadi, R. (2013). Comparative departmental efficiency analysis within a university: A DEA approach. Procedia-Social and Behavioral Sciences, 90, 540–548.
Bhat, R., Verma, B. B., & Reuben, E. (2001). Data envelopment analysis (DEA). Journal of health Management, 3, 309–328.
Bowlin, W. F. (1998). Measuring performance: An introduction to data envelopment analysis (DEA). The journal of cost analysis, 15, 3–27.
Charnes, A., Cooper, W., Lewin, A. Y., & Seiford, L. M. (1997). Data envelopment analysis theory, methodology and applications. Journal of the Operational Research society, 48, 332–333.
Cooper, W. W., Seiford, L. M., & Tone, K. (2006). Introduction to data envelopment analysis and its uses: with DEA-solver software and references. Springer Science & Business Media.
Cooper, W. W., Seiford, L. M., & Zhu, J. (2011). Handbook on data envelopment analysis.
Cooper, W. W., Seiford, L. M., Tone, K., & others. (2007). Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software (Τόμ. 2). Springer.
Ji, Y.-b., & Lee, C. (2010). Data envelopment analysis. The Stata Journal, 10, 267–280.
Johnes, J. (2006). Measuring teaching efficiency in higher education: An application of data envelopment analysis to economics graduates from UK Universities 1993. European journal of operational research, 174, 443–456.
Kohl, S., Schoenfelder, J., Fügener, A., & Brunner, J. O. (2019). The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals. Health care management science, 22, 245–286.
Kuah, C. T., Wong, K. Y., & Behrouzi, F. (2010). A review on data envelopment analysis (DEA). 2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation, (σσ. 168–173).
Lindsay, A. W. (1982). Institutional performance in higher education: The efficiency dimension. Review of Educational Research, 52, 175–199.
Mantri, J. K. (2008). Research methodology on data envelopment analysis (DEA). Universal-Publishers.
Nadoveza Jelić, O., & Gardijan Kedžo, M. (2018). Efficiency vs effectiveness: an analysis of tertiary education across Europe. Public sector economics, 42, 381–414.
Nazarko, J., & Šaparauskas, J. (2014). Application of DEA method in efficiency evaluation of public higher education institutions. Technological and Economic development of Economy, 20, 25–44.
Olariu, G. V., & Brad, S. (2017). Efficiency assessment of universities with DEA method based on public data. Balkan Region Conference on Engineering and Business Education, 2, σσ. 106–114.
Panwar, A., Olfati, M., Pant, M., & Snasel, V. (2022). A review on the 40 years of existence of data envelopment analysis models: Historic development and current trends. Archives of Computational Methods in Engineering, 29, 5397–5426.
Ramanathan, R. (2003). An introduction to data envelopment analysis: a tool for performance measurement. Sage.
Stewart, T. J. (1996). Relationships between data envelopment analysis and multicriteria decision analysis. Journal of the operational research society, 47, 654–665.
Thanassoulis, E., Boussofiane, A., & Dyson, R. G. (1996). A comparison of data envelopment analysis and ratio analysis as tools for performance assessment. Omega, 24, 229–244.
Thanassoulis, E., De Witte, K., Johnes, J., Johnes, G., Karagiannis, G., & Portela, C. S. (2016). Applications of data envelopment analysis in education. Data envelopment analysis: A handbook of empirical studies and applications, 367–438.
Zhou, G., Chung, W., & Zhang, Y. (2014). Measuring energy efficiency performance of China’s transport sector: A data envelopment analysis approach. Expert Systems with Applications, 41, 709–722.