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Value efficiency analysis of academic research


  • Korhonen, Pekka
  • Tainio, Risto
  • Wallenius, Jyrki


We propose a systematic approach to analyzing academic research performance at universities and research institutes. The analysis of research performance based on a set of (abstract) criteria which are relevant from the decision maker's point of view. The scales for these criteria are defined by means of concrete indicators. All indicators, are, however, not necessarily quantitative. Qualitative information is quantified using appropriate analytical tools. Once the criteria and indicators have been agreed upon and quantified, data on the research units is collected and a Value Efficiency Analysis is performed. The efficiency of research units is defined in the spirit of Data Envelopment Analysis (DEA), complemented with a decision makers (Rector in the European university system) preference information. This information is obtained by asking the decision maker to locate a point on the efficient frontier having the most preferred input and output values. Our approach and the accompanying Decision Support System enables a university to allocate resources more efficiently for its research units. Using data from the Helsinki School of Economics, we describe how our approach can be used.
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  • Korhonen, Pekka & Tainio, Risto & Wallenius, Jyrki, 2001. "Value efficiency analysis of academic research," European Journal of Operational Research, Elsevier, vol. 130(1), pages 121-132, April.
  • Handle: RePEc:eee:ejores:v:130:y:2001:i:1:p:121-132

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    References listed on IDEAS

    1. Moed, H. F. & Burger, W. J. M. & Frankfort, J. G. & Van Raan, A. F. J., 1985. "The use of bibliometric data for the measurement of university research performance," Research Policy, Elsevier, vol. 14(3), pages 131-149, June.
    2. Korhonen, Pekka & Wallenius, Jyrki, 1990. "Using qualitative data in multiple objective linear programming," European Journal of Operational Research, Elsevier, vol. 48(1), pages 81-87, September.
    3. M. Halme & T. Joro & P. Korhonen & S. Salo & J. Wallenius, 1998. "Value Efficiency Analysis for Incorporating Preference Information in Data Envelopment Analysis," Working Papers ir98054, International Institute for Applied Systems Analysis.
    4. Thanassoulis, E. & Dyson, R. G., 1992. "Estimating preferred target input-output levels using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 56(1), pages 80-97, January.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. E. Thanassoulis & R. Allen, 1998. "Simulating Weights Restrictions in Data Envelopment Analysis by Means of Unobserved DMUs," Management Science, INFORMS, vol. 44(4), pages 586-594, April.
    7. R. Allen & A. Athanassopoulos & R.G. Dyson & E. Thanassoulis, 1997. "Weights restrictions and value judgements in Data Envelopment Analysis: Evolution, development and future directions," Annals of Operations Research, Springer, vol. 73(0), pages 13-34, October.
    8. Peter Bogetoft, 2000. "DEA and Activity Planning under Asymmetric Information," Journal of Productivity Analysis, Springer, vol. 13(1), pages 7-48, January.
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