engleski

Incorporating quality considerations in DEA-based benchmarking of higher education

It is well known that DEA has been used for estimating and ranking education on different levels (primary, secondary, tertiary) and across different units (schools, universities, countries, …). However, DEA is a method that generally rewards the greater quantity of the output and the fewer inputs, which raises some question about the results of the DEA-based research of education since the education is a specific area where the quality of the output and the quality of the input matter more than the quantity itself. Despite that fact, many of the previous studies overlooked to incorporate the output quality considerations in their research. Also, the researches should be adjusted for input quality to avoid potential bias towards low input units within DEA. In our research, we investigate the use of data envelopment analysis (DEA) for benchmarking the higher education using multiple criteria and the possibilities to incorporate quality considerations of education by using different DEA models and the quality measures/ corrections of inputs and outputs. Our sample contains 24 EU countries in the period of 2004- 2015. Preliminary results indicate that the outcome of the analysis can change significantly when quality concerns are included. A part of the results was published in a paper submitted for the award of the Prof. Dr. Marijan Hanžeković Prize in 2018.

Data Envelopment Analysis, Efficiency Analysis, Education and Distance Learning

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