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Performance Evaluation of University Faculty Members Using DEA Models with Categorical Variables

In: Advances in the Theory and Applications of Performance Measurement and Management

Author

Listed:
  • Tamás Koltai

    (Budapest University of Technology and Economics)

  • Katalin Gerákné Krasz

    (Budapest University of Technology and Economics)

Abstract

Data Envelopment Analysis (DEA) is used for efficiency evaluation of decision-making units (DMU) based on input and output information. DMUs are generally for-profit or non-profit organizations. It is possible, however, to consider employees as DMUs, and in this case DEA can be used for personal performance appraisal. This paper shows, how performance of university faculty members can be evaluated with DEA. Output information is determined by the achievement of faculty members in teaching, research, and service areas, and the inputs are formed by the elements of the faculty compensation system. Input-oriented DEA models are used to explore how the compensation of a faculty member is justified by the achievements. To refine the analysis, categorical variables are applied to distinguish faculties being in different university positions. Weight restrictions are also applied to express the different expectations of management in three fundamental areas of performance: teaching, research, and service. The suggested method is illustrated with the case of the School of Economic and Social Sciences of the Budapest University of Technology and Economics. Output and input data are collected through the performance evaluation system of the school. The presented results show how DEA can support individual performance appraisal and may enrich the application experience of DEA in this special area.

Suggested Citation

  • Tamás Koltai & Katalin Gerákné Krasz, 2024. "Performance Evaluation of University Faculty Members Using DEA Models with Categorical Variables," Lecture Notes in Operations Research, in: Ali Emrouznejad & Emmanuel Thanassoulis & Mehdi Toloo (ed.), Advances in the Theory and Applications of Performance Measurement and Management, pages 205-218, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-61597-9_16
    DOI: 10.1007/978-3-031-61597-9_16
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