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Assessing the Relative Performance of University Departments: Teaching vs. Research

  • Berna Haktanirlar Ulutas


    (Osmangazi University)

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    Data Envelopment Analysis (DEA) is known as a non-parametric method to evaluate the relative efficiencies of a set of homogenous decision-making units (DMUs) (i.e., banking, health, education, etc.) that use multiple inputs to produce multiple outputs. DEA models also have applications for universities or specifically, departments of a university. In practice, determining input and output measures may be based on the available data. However, lack of defining an important measure or use of invalid data may mislead the decision maker. Therefore, this study aims to assess the affect of missing values such as by discarding of outputs on DMU’s efficiency values. The up-to-date data for the departments of an engineering faculty are considered and their performances are presented based on teaching and research oriented measures.

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    Article provided by Department of Econometrics, Faculty of Economics, Istanbul University in its journal Istanbul University Econometrics and Statistics e-Journal.

    Volume (Year): 13 (2011)
    Issue (Month): 1 (Special Issue of 12th International Symposium on Econommetrics, Operation Research and Statistics)
    Pages: 125-138

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    Handle: RePEc:ist:ancoec:v:13:y:2011:i:1:p:125-138
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    1. Kao, Chiang & Hung, Hsi-Tai, 2008. "Efficiency analysis of university departments: An empirical study," Omega, Elsevier, vol. 36(4), pages 653-664, August.
    2. Abel A. Moreno & Raghu Tadepalli, 2002. "Assessing academic department efficiency at a public university," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 23(7), pages 385-397.
    3. Johnes, Jill & Johnes, Geraint, 1995. "Research funding and performance in U.K. University Departments of Economics: A frontier analysis," Economics of Education Review, Elsevier, vol. 14(3), pages 301-314, September.
    4. Tzeremes, Nickolaos & Halkos, George, 2010. "A DEA approach for measuring university departments’ efficiency," MPRA Paper 24029, University Library of Munich, Germany.
    5. Lucia Buzzigoli & Antonio Giusti & Alessandro Viviani, 2010. "The Evaluation of University Departments. A Case Study for Firenze," International Advances in Economic Research, International Atlantic Economic Society, vol. 16(1), pages 24-38, February.
    6. Beasley, J. E., 1990. "Comparing university departments," Omega, Elsevier, vol. 18(2), pages 171-183.
    7. Emrouznejad, Ali & Parker, Barnett R. & Tavares, Gabriel, 2008. "Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 151-157, September.
    8. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
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