Selective proportionality and integer-valued data in DEA: an application to performance evaluation of high schools

Conventional data envelopment analysis (DEA) models are often extended for constant or variable returns to scale assumptions based on the under-investigated technology. It is assumed that all inputs and outputs are real-valued data. However, in many practical applications, proportionality or convexity axioms require to be modified. This study attempts to further expand upon the hybrid returns to scale DEA models in the presence of integer-valued input and output data. We refine the previous axioms to introduce a new minimal extrapolation technology set. Moreover, we formulate a couple of mixed-integer linear programming models for efficiency evaluation and target setting. An empirical application on 30 high schools in Iran is provided to validate the proposed approach. The data analysis, including efficiency evaluations along with providing benchmark units, is also performed.