Higher Education

, Volume 53, Issue 4, pp 517–538 | Cite as

The impact of size and specialisation on universities’ department performance: A DEA analysis applied to Austrian universities

  • Karl-Heinz LeitnerEmail author
  • Julia Prikoszovits
  • Michaela Schaffhauser-Linzatti
  • Rainer Stowasser
  • Karin Wagner


This paper explores the performance efficiency of natural and technical science departments at Austrian universities using Data Envelopment Analysis (DEA). We present DEA as an alternative tool for benchmarking and ranking the assignment of decision-making units (organisations and organisational units). The method applies a multiple input and output variables approach, which is a clear advantage to other approaches using simple performance ratios. To deliver reasonable results, suitable input and output variables have been determined in a previous step using correlation analyses and OLS regression. The results validate the methods applied, and reveal performance differences and scale effects. The use of multiple output variables enables the revealing of detailed improvement or reduction amounts of each input and output of the evaluated units and furthermore for identifying the specialisation of teaching, research, and industrial cooperation. We find significant evidence that the size of a department influences its overall and specialisation performance; both small and large departments perform above average, which proves that simple linear scale effects do not exist.


Austria benchmarking Data Envelopment Analysis efficiency evaluation scale effects specialisation patterns Austria universities 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Ali, A.I. 1995‘Computational aspects of DEA’Charnes, A.Cooper, W.Lewin, A.Y.Seiford, L.M. eds. Data Envelopment Analysis: Theory, Methodology and ApplicationKluwer Academic PublishersThe Netherlands6388Google Scholar
  2. Athanassopoulos, A.D., Shale, E. 1997‘Assessing the comparative efficiency of higher education institutions in the UK by means of Data Envelopment Analysis’Education Economics5117134Google Scholar
  3. Banker, R.D., Charnes, A., Cooper, W.W. 1984‘Some models for estimating technical and scale inefficiences in Data Envelopment Analysis’Management Science3010781092CrossRefGoogle Scholar
  4. Beasley, J.E. 1995‘Determining teaching and research efficiencies’Journal of the Operational Research Society46441452CrossRefGoogle Scholar
  5. Bonaccorsi, A. and Daraio, C. (2002). ‘The organization of science: size, agglomeration and age effects in scientific productivity’, SPRU NPR-Net Conference: Rethinking Science Policy: Analytical Frameworks For Evidence-Based Policy. SPRU, University Of Sussex, Brighton, UK, March 21–23, 2002Google Scholar
  6. Charnes, A., Cooper, W.W., Rhodes, E. 1978‘Measuring the efficiency of decision making units’European Journal of Operational Research2429444CrossRefGoogle Scholar
  7. Cooper, W.W., Seiford, L.M., Tone, K. 2000Data Envelopment AnalysisKluwer Academic PublishersBostonGoogle Scholar
  8. Dill, D. 2001‘The regulation of public research universities: changes in academic competition and implications for university autonomy and accountability’Higher Education Policy142135CrossRefGoogle Scholar
  9. Fairweather, J. 2002‘The mythologies of faculty productivity. Implications for institutional policy and decision making’The Journal of Higher Education732648CrossRefGoogle Scholar
  10. Fandel, G. (2003). ‘Zur Leistung nordrhein-westfälischer Universitäten. Gegenüberstellung einer Verteilungslösung und der Effizienzmaße einer Data Envelopment Analysis’, in Backes-Gellner U. and Schmidtke C., (eds.), Hochschulökonomie – Analysen interner Steuerungsprobleme und gesamtwirtschaftlicher Effekte. Berlin, 33–50Google Scholar
  11. Farrell, M.J. 1957‘The measurement of productive efficiency’Journal of the Royal Statistical Society120253281Google Scholar
  12. Gander, J.P. 1995‘Academic research and teaching productivities: a case study’Technological Forecasting and Social Change49311319CrossRefGoogle Scholar
  13. Johnes, G., Johnes, J. 1993‘Measuring the research performance of UK economics departments: an application of Data Envelopment Analysis’Oxford Economics Papers45332347Google Scholar
  14. Leitner, K-H., Schaffhauser-Linzatti, M., Stowasser, R., Wagner, K. 2005‘Data envelopment analysis as method for evaluating Intellectual Capital’Journal of Intellectual Capital6528543CrossRefGoogle Scholar
  15. Moed, H.F., Luwel, M., Houben, J.A., Spruyt, E., Berghe, H. 1998‘The effects of changes in the funding structure of the Flemish universities on their research capacity, productivity and impact during the 1980s and early 1990s’Scientometrics43231255CrossRefGoogle Scholar
  16. Roessner, D. 2000‘Quantitative and qualitative methods and measures in the evaluation of research’Research Evaluation8125132Google Scholar
  17. Salerno C. (2003). ‘What we know about the efficiency of higher education institutions: The best evidence’, Series: Beleidsgerichte studies hoger onderwijs en wetenschappelijk onderzoek, University of TwenteGoogle Scholar
  18. Seiford, L.M., Thrall, R.M. 1990‘Recent developments in DEA: The mathematical programming approach to frontier analysis’Journal of Econometrics46738CrossRefGoogle Scholar
  19. Sinuany-Stern, Z., Mehrez, A., Barboy, A. 1994‘Academic departments efficiency via DEA’Computers and Operations research21543556CrossRefGoogle Scholar
  20. Stevens, P.A. (2001). ‘The Determinants of Economic Efficiency in English and Welsh Universities’, Discussion Paper Number 185, National Institute of Economic and Social Research, LondonGoogle Scholar
  21. Teodorescu, D. 2000‘Correlates of faculty publication productivity: A cross-national analysis’Higher Education39201222CrossRefGoogle Scholar
  22. Vakkuri, J. and Mälkiä, M. (1996). ‘The applicability of DEA Method in Performance. The Case of Finnish Universities and University Departments’, Working Papers 1996 C12, University of Tampere, Administrative ScienceGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  • Karl-Heinz Leitner
    • 1
    Email author
  • Julia Prikoszovits
    • 2
  • Michaela Schaffhauser-Linzatti
    • 3
  • Rainer Stowasser
    • 4
  • Karin Wagner
    • 5
  1. 1.Department of Technology PolicyARC Systems Research GmbHViennaAustria
  2. 2.Austrian Rectors’ ConferenceAustria
  3. 3.Faculty of Business, Economics and StatisticsUniversity of ViennaViennaAustria
  4. 4.Office Austrian Science BoardAustria
  5. 5.Economic Analysis DivisionAustrian Central BankAustria

Personalised recommendations